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Simulation of Bio-signals and Metabolomics/生物信号的模拟与新陈代谢组学

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发表于 2021-1-5 10:29:53 | 显示全部楼层 |阅读模式
This is the article 10 in the theme 'Environmental Physiology/环境生理学' of Journal of Environment and Health Science.

2016. Copyrights Register Information: The majority of these materials are registered as book '著作权人:刘焕;作品:《研究生文凭进展(第三版)》' 2016, which can be cataloged in National Copyright Database: http://qgzpdj.ccopyright.com.cn/

2016. 版权注册信息:本文大多数内容已经以图书形式登记注册在全国版权数据库,登记入库信息:著作权人:刘焕;作品:《研究生文凭进展(第三版)》 2016;可在全国版权登记数据库检索 http://qgzpdj.ccopyright.com.cn/

The formally published serials is the printing <Journal of Environment and Health Science (ISSN 2314-1628)>, and the serials NO. is the month/year when the materials accessible on this website, authorized by publisher;
正式发表的期刊是印刷版《环境与卫生科学杂志(ISSN 2314-1628)》,期刊期号为文章内容在本网站上网年/月,出版人许可自行正式发表。
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 楼主| 发表于 2021-1-6 10:22:45 | 显示全部楼层
Article 10: Biophysical Simulation of Bio-signals and The Metabolomics /生物信号的物理模拟及新陈代谢组学

Author: Liu Huan, MSc (First Class Honours), The University of Auckland.
Published after graduation on 11/01/2016

Methods:

The same strain of microbes is divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for microbe reproduction process: one is the ‘comfortable’ condition (Sample 1); the other is under UV-B radiation for cultivation (Sample 2). The microbe samples are collected after sufficient reproduction process (Ten generations).
2.After sufficient reproduction process, the UV-B radiation simulation stops. Then both sample 1 and sample 2 are separately transferred into moisture simulation process: different moisture conditions of microbial cultivation are simulated in Lab, and labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) after moisture simulation of T1, T2, ..., Tn respectively, resulting in different zymograms as: M1, M2, ..., Mn.
4.Each isozyme family is labeled as 1, 2, 3..., and E; It is hypothesized that the bands at the same line across different isozyme families are the enzyme species at the same locus (due to the same status of relative molecular weight), named as enzyme ‘species i’ (i = 1, 2, ..., I), and each isozyme family has the same amount (I) of enzyme species (Please note: this is different from the identification of real enzyme species in the appendix 2 of chapter 1). Then there is a 3-dimension (I× E × N) matrix presented in this research. I is the total amount of enzyme species within a isozyme family; E is the total amount of isozyme families; N is the total amount of zymograms among different simulated moisture conditions:


X= │Xien │( i = 1, 2, ....I; e = 1, 2, .... E; n= 1, 2, ... N)
Xien is the occurrence of enzyme ‘species i’ in the isozyme ‘family e’ during simulated moisture condition Tn. The value of Xien is one or zero (See PDF version).
            X111 X211 X112 ... X11n X212 ... X21n X121 X221 X122 ...... X12n ......
            X222 ......X22n .......        X1i1 X2i1        X1i2 X2i2        ......
            .......        X1in X2in
X =        .....        .......        ......        .......        .......        ...........        .......        ......        ......        ......        .........
        Xi11        Xi12 ...        Xi1n        Xi21        Xi22        Xi2n        ........        Xie1        Xie2        ......        Xien
        .......        .......        .......        ......        ......        ......        ......        .......        .......        ......        ........


Matrix Se = Xe × (Xe)T Xe = │Xin│( i = 1, 2, ....I; n= 1, 2, ... N); (Xe)T is the transpose of the matrix Xe:

X11                X12 ... X1n X21        X22 ... X2n
Xe = ..... ....... ......

Xi1        Xi2 ...        Xin
....        .....        ......
The Principal Components Analysis (PCA) method of matrix X is specified [1]. PCA is firstly conducted on the basis of matrix Se, revealing the biochemical dynamics of a isozyme ‘family e’ among different simulated moisture conditions. In matrix Se, it is hypothesized that the variable in PCA represents the biochemistry dynamics of each enzyme ‘species i’.

S = ΣSe (e = 1, 2, E)

PCA is further conducted on the basis of matrix S, revealing the biochemical dynamics among different isozyme families over the whole simulated moisture conditions. In matrix S, it is hypothesized that the variable in PCA represents the biochemistry dynamics of each enzyme ‘species i’ across all the isozyme families.

However, for the comparison between sample 1 and sample 2, this book need to present more procedures for subsequent analysis: in matrix Se, the biochemistry

dynamics of the first three enzyme species, which reveal the most differences in the total variation by PCA in an isozyme family, are selected for comparison between sample 1 and sample 2; in matrix S, the biochemistry dynamics of the first three enzyme species, which reveal the most differences in the total variation by PCA  across all the isozyme families, are selected for comparison between sample 1 and sample 2; the sum dynamics of the first three enzyme species in a isozyme family (= the sum Variance Contribution Ratio (VCR) of the first three enzyme species  in matrix Se), represents the total variation of a isozyme family over the whole simulated moisture conditions; the sum dynamics of the first three enzyme species across all the isozyme families (= the sum Variance Contribution Ratio (VCR) of the first three enzyme species in matrix S), represents the variation of the total zymograms over the whole simulated moisture conditions.

Hypotheses:
1.The higher variation in biochemical dynamics of enzyme expression, the better environmental adaptiveness or immunology (the reason of this hypothesis is presented in chapter 7 of this book). It is deduced that the biochemistry dynamics of the first three isozyme families, which show the highest variation by PCA, determines the conclusion of this comparison;

2.Sample 2 leads to higher variation in biochemical dynamics of enzyme expression, which is also revealed by the higher adaptiveness during drought stress or higher immunology.

Discussion:
The findings of this chapter further support the theory, ‘memory’ of gene expression, proposed by other articles of this journal; As discussed by other articles of this journal, the memory of cells can be ‘trained’ by the biophysical simulation in site, indicated by the zymograms in metabolomics test. Consequently, the memory of cells, in terms of identifying the bio-signals of an environmental factor (can be biotic or abiotic) triggering the gene expression for environmental adaptiveness or immunology, can be trained by the biophysical simulation of other environmental factors. The appendix of this chapter (biophysical simulation for blood cell division) further supports above theories (please note: the theory, ‘memory’ of gene expression, is also applicable on cell division in an individual) by assessment of resistance or immunology in host cells.














This is the revised materials in book “Proceedings for Degree of Postgraduate Diploma in Environmental Science (3rd Edition).” Published in 2016. The ‘chapter’ content mentioned in this article is in previous book. Revised on 05/01/2021.







References:
[1] 陶玲,任裙 (2004)。进化生态学的数量研究方法。第一章,第六节,第 49 页。 中国林业出版社。 ISBN:7-5038-3735-7.

Appendix 1. The Experiment Procedure for Blood Cell Cultivation in Biophysical Simulation/生物物理实验中血细胞培养方法
The blood samples of a rat is abstracted and divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for cell division: one is the ‘comfortable’ condition (Sample 1); the other is under electromagnetism simulation for cell cultivation (Sample 2); the cell samples are collected after sufficient cell division (Ten generations).
2.After sufficient cell division process, the electromagnetism simulation stops. Then both sample 1 and sample 2 are separately transferred into the simulation process of physiological saline: cells are cultivated individually in different concentrations of physiological saline in Lab, and different cell environment (salinity stress of cell environment or ‘thirsty’ simulation) are labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) in cell samples after simulation process of physiological saline, T1, T2, ..., Tn, respectively, resulting in different zymograms as: M1, M2, ..., Mn.
The other procedures are the same as described above.
However, for the comprehensive assessment of immunology in host cells, the simulation process of physiological saline is replaced by the invasion simulation caused by different families of bacteria (or virus):
The blood samples of a rat is abstracted and divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for cell division: one is the ‘comfortable’ condition (Sample 1); the other is under electromagnetism simulation for cell cultivation (Sample 2); the cell samples are collected after sufficient cell division (Ten generations).
2.After sufficient cell division process, the electromagnetism simulation stops. Then both sample 1 and sample 2 are separately transferred into the simulation process of bacteria (or virus) invasion: cells are cultivated individually and independently during the simulation of different families of bacteria (or virus) in Lab, and the invasion simulation process of different bacteria (or virus) families are labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) in cell samples after simulation process  of bacteria  (or  virus) invasion, T1,  T2, ..., Tn, respectively, resulting in different zymograms as: M1, M2, ..., Mn.
The other procedures are the same as described above. This comprehensive assessment of immunology is closer to the real situation of disease caused by multiple species of bacteria, as described by the chapter 8 of this book. Even if the pathology  of host cells (such as cancerous blood cells of rat) is not caused by multiple species of invasive virus or bacteria (and by one species only), the invasive virus or bacteria of the same genetic strain also evolves into various phenotypes in host body, which reflects the significance of comprehensive assessment of immunology.

Please note: if all the blood cells have been ‘eaten’ up (or no cell division rate) by a strain of bacteria during invasion simulation, then the value of this zymogram can be counted as zero for subsequent matrix calculation.
For the comprehensive assessment of immunology in host cells caused by the invasive virus or bacteria of the same genetic strain with different phenotypes:
The blood samples of a rat is abstracted and divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for cell division: one is the ‘comfortable’ condition (Sample 1); the other is under electromagnetism simulation for cell cultivation (Sample 2); the cell samples are collected after sufficient cell division (Ten generations).
2.After sufficient cell division process, the electromagnetism simulation stops. Then both sample 1 and sample 2 are separately transferred into the simulation process of bacteria (or virus) invasion of the same genetic strain with different phenotypes: cells are cultivated individually and independently during the invasive simulation by different phenotypes of the same genetic bacteria (or virus) in Lab, and the invasion simulation process by different phenotypes of the same genetic bacteria (or virus) are labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) in cell samples after simulation process  of bacteria  (or  virus) invasion, T1,  T2, ..., Tn, respectively, resulting in different zymograms as: M1, M2, ..., Mn.
The other procedures are the same as described above. This electromagnetism simulation can be either constant electromagnetism fields or time-varying electromagnetic waves, which are further discussed later.
Conclusion:
The comprehensive assessment of immunology in host cells also provides indicators of training host cells by adjusting the parameters of biophysical simulation, once the specific zymograms, indicating the immunology against the specific invasive bacteria or virus (or the specific phenotype of an invasive pathogen), are identified by the methods presented in the appendix of chapter 8. However, the higher dynamics, the better immunology against various pathogen species (or various phenotypes of a pathogen genotype).


Appendix 2. The Determination Method of Bio-signal Range for Biophysical Simulation /生物物理模拟试验中生物信号范围的确定方法
Step 1. The host cells of the same genetic strain (such as the blood cells of rat) are abstracted, which are divided  into  several  cell  samples,  and  labeled  as  S1,  S2,  S3 ,Sn;
Step 2. The simulation of a specific virus (or bacteria) invasion targeting the host cells is conducted in Lab, immediately after host cells are abstracted from host body;
Step 3. The samples of host cells with apparent antibiotics are identified, as described by the appendix of chapter 8; and the samples of host cells without apparent antibiotics are also continuously observed until they are ‘eaten up’ by the specific invasive pathogen;
Step 4. The separation of virus from each sample of host cell without apparent antibiotics are conducted independently in Lab, and the metabolomics test is conducted in each virus sample;
Objective:
The different phenotypes of an invasive virus (or bacteria) strain are identified, and  the biochemistry dynamics of this invasive virus strain is calculated, as discussed in this chapter. The result of biochemistry dynamics calculation helps to determine the range of bio-physical training parameters to enhance the comprehensive immunology of host cells, as described above.
Please note: the simulation of a specific virus (or bacteria) invasion targeting the host cells should be conducted immediately after host cells are abstracted from host body, otherwise the uniform cell cultivation in Lab lead to the homogeneity of host cells, so that different phenotypes of an invasive pathogen can be hardly detected.
Because the virus sample for invasion simulation is cultivated in Lab, which is the uniform phenotype, the samples of host cells with apparent antibiotics usually show specific zymograms correspondingly to the specific invasive virus. However, if virus samples, which are separated from host cell without apparent antibiotics after step 3, re-invade the host cells with apparent antibiotics identified in step 3, virus infection would occur, due to the evolution of new virus phenotypes.


Appendix 3. Bio-magnetic field of Cell and Its Application on Separation of Blood Cell Communities along Environmental
Gradient/细胞的生物磁场及血细胞群落在环境梯度上的分离

Step 1. The host cells (such as blood cells of rat) are abstracted from host body. Step 2. Electrophoresis of blood cells is conducted in moderate electromagnetism;
Step 3. Different blood cell communities are separated along the environmental gradient of electromagnetism signal, leading to cell samples with different immunology.

Discussion
The bio-magnetic field of blood cells varies even within the same genetic strain, so that different cell communities can be separated according to the gradual variation in electromagnetism signals (environmental gradient of electromagnetism) in this electrophoresis, leading to cell samples with different immunology. The cell samples, abstracted from different electric potential (j1, j2...jn), are labeled on the basis of electric potential.

Step 4. The specificity of host-invasion interaction is examined on each cell sample, according to the appendix of chapter 8 in this book. It is expected that the specific electric potential corresponds to the host cells with apparent antibiotics against the specific invasive virus (or bacteria), which also becomes the key parameter of biophysical training for the host cells with immunology against the specific invasive virus (or bacteria). Nevertheless, for the mobilizable blood cells, it is expected that the 'ecological niche' of cells vary in their life cycle along this environmental gradient of electromagnetism signal, because of the variation in bio-magnetic field over cell's life cycle, moving from a specific electric potential to another electric potential.
It is expected that the time-varying electromagnetic field of biophysical training is better than constant electromagnetic field, due to the phenotype evolution of invasive virus (bacteria).
Please note: the intensity of electromagnetism is preliminarily set to be 1.6 H (1H = 1 A/m) in this research, three times than earth magnetism fields. If the intensity of electromagnetism is more than 5 times than earth magnetism fields, blood cell  division rate of rats starts to decline apparently, ‘looking nervous,’ which is closer to the situation of ‘hemorrhage.’ They are unlike microbes who can survive long-termly in sunshine intensity.


Appendix 4. Bio-signal Simulation of Electromagnetic Wave and Its Specificity on the Isozyme Expression/电磁波的生物信号模拟及同工酶表达的专一性
In appendix 3, the specificity of electric potential to the host cells with apparent antibiotics against the specific invasive virus (or bacteria) is determined. However, this method is relatively broader, so that the accuracy of this biophysical training is not sufficient for the synthesis of antibiotics in cells against the specific phenotype of an invasive virus (or bacteria).
Consequently, this section presents a novel methods to train the specific isozyme families catalyzing the synthesis of antibiotics in cells against the specific phenotype of an invasive virus (or bacteria):
Step 1. Host cells (such as blood cells) are cultivated during simulation of electromagnetic wave conditions;
Step 2. Different frequency of electromagnetic wave (or different wavelength) are simulated, and labeled as F1, F2, ..., Fn;
Step 3. Metabolomics test is conducted individually after cultivation in F1, F2,...Fn, respectively.
Step 4. Under each simulated frequency of electromagnetic wave, different electromagnetic wave intensity are simulated, and labeled as I1, I2, ..., and In.
Step 5. Metabolomics test is conducted individually after cultivation in I1, I2,...In, respectively. The amount of N×N metabolomics tests are conducted in total.
Objectives:
The specific frequency of electromagnetic wave simulates the bio-signal regulating gene expression as a specific isozyme family, and the specific electromagnetic wave intensity (AND amplitude) corresponds to the bio-signal regulating gene expression as a specific enzyme species within an isozyme family, which can be determined by metabolomics tests. Consequently, the immunology against the specific phenotype of an invasive virus (or bacteria) can be trained according to the zymograms, described  in the appendix of chapter 8. Please note: the intensity is adjusted and controlled by the amplitude instructed in appendix 5.

This experiment is similar to chapter 4 (UV-B is one of electromagnetic waves). Let’s re-discuss the chapter 4 on the basis of plant cell data (the blood cell data of rat is not clear to this date 18/02/2016): As discussed in chapter 4, UV-B significantly (P<0.001) affected the net photosynthesis (A) (Table 1). Nevertheless, for Tienshan clover and Caucasian clover, there was no significant UV-B induced difference in the total aerial biomass yield, under well-water conditions, and there was no significant effect of UV-B on the relative chlorophyll content, whereas enhanced UV-B apparently decreased the biomass of Kopu II. Further more, the water deficit did not influence   the relative chlorophyll content as comparison to the well-water condition (Table 1).

There are two reasons to explain this science discovery: firstly, the Light Use Efficiency (LUE) already exceeded the saturation point of LUE under well water condition without enhanced UB treatment (as discussed in other articles of journal), so that the reduction of net photosynthesis under enhanced UB treatment did not influence the total aerial biomass yield; Secondly, enhanced UV-B treatment effectively triggered the gene expression of enzyme species within the isozyme families involving in the chlorophyll synthesis in plant cells, which revealed that the isozyme families involving in the chlorophyll synthesis could express effectively under a broader range of UV-B intensity especially for Caucasian clover, but the relevant gene of Kopu II was not effectively expressed as enzyme species within the isozyme families involving in the chlorophyll synthesis under enhanced UV-B. Please note: within the isozyme families involving in the chlorophyll synthesis in plant cells, the enzyme species under enhanced UV-B is different from the one without enhanced UV-B. However, drought condition did not influence the synthesis of chlorophyll, which showed different metabolic pathway in response to the environmental stress. The treatment without UV-B in this experiment was not without any UV-B radiation, and was just lower intensity of UV-B treatment. Although chapter 4 explains that ‘these results indicated that these clovers might have adequately photo-protective mechanism, such as enhancing the synthesis of UV-B screening  secondary metabolites (Hofmann et al., 2003a),’ this explanation is consistent with the above explanation in this section, because the synthesis of UV-B screening secondary metabolites as photo-protective mechanism is also the phenomenon utilizing the light energy effectively, adjusting the photo-metabolic pathways in response to the change of UV-B intensity (UV-B is also the utilizable light energy in photosynthesis rather than visible light only, which can be proven the result that Caucasian clover showed increased biomass during enhanced UV-B of well water treatment as compared to the well water condition without UV-B, although the main utilizable energy is from the visible light --- without visible light, photosynthesis can not only rely on UV-B to happen --- this is the conclusion of this book). As discussed in appendix 5, the receptors (or cells) of electromagnetic wave can NOT identify more than three different frequencies of electromagnetic wave concurrently, it is hypothesized that plant cells themselves select three frequencies of light waves with the highest  intensity for photosynthesis, and Caucasian clover selects UV-B frequency for photosynthesis whereas Kopu II can not, this is definitely the environmental adaptiveness evolved from its origin.

Please note: for the identification of specific zymograms of host cells with specific immunology against invasive gene mutation virus in chapter 8, then invasive simulation of gene mutation virus is added during the whole process of biophysics simulation for identifying the specificity of host-invasion interaction (in which frequency and intensity of cultivation condition, the host cells show effective immunology against the gene mutation virus).

Nevertheless, for the virus (or bacteria) with dormant characters (such as HIV), it is expected that long-term observation is required for this specificity examination after

biophysics simulation stops, because this virus would become dormant in host cells after puncturing cell membrane during biophysics simulation, so that the host cells with effective immunology against the dormant virus are NOT specifically identified during biophysical simulation. In this case, the host cells with really effective immunology against the dormant virus kill the invasive virus during biophysical simulation, whereas the host cells with dormant virus would be re-infected after biophysical simulation stops. After long-termly observing if dormant virus re-starts pathogenetic metabolism in host cells, the identified host cells with really effective immunology against the dormant virus would be screened and become more specific. Finally the range of biophysics parameters in appendix 5 should be based on all the host cell samples which have been identified as effective immunology against the dormant virus during biophysics simulation. The more specific, the more punctual to kill the invasive virus.

Please note: the intensity of electromagnetic waves is preliminarily set to be 1.6 H  (1H = 1 A/m) for blood cells in this research, three times than earth magnetism fields. If the intensity of electromagnetism is more than 5 times than earth magnetism fields, blood cell division rate of rats starts to decline apparently, ‘looking nervous.’ They are unlike microbes who can survive long-termly in sunshine intensity. However, the frequency of electromagnetic waves is preliminarily set to be around UV-B frequency, the sunshine one. Actually, blood cells still function (such as oxygen-carrying capacity) effectively under exposure to sunshine radiation, but the blood cell division only occurs when sunshine radiation is shielded. This is why hematopoietic function of blood cells mainly occurs in marrow! and blood cells division rate actively increases during evening as well!


Appendix 5. The Parameterization of Time-varying Electromagnetic Field for Biophysics Simulation/生物物理模拟实验中时变电磁场参数的确定方法
Method:
This section presents a novel method to determine the parameters of time-varying electromagnetic field, on the basis of ‘Skin Effect’ equations in combination with ‘Maxwell’ equations:
1.Skin effect equations:
I (t)= √2 I sin (wt); w = 2πf ;
2.Maxwell's equations:
I (t)= j H (t)
S = I (t) * H (t)
I is the effective intensity of electric field, t is the varying time, w is the angular frequency (rad/s), f is the frequency, H is the intensity of magnetic field, j is the conductivity, and S is the energy of wave (or the electromagnetic wave intensity) [1]. The determination of biophysical training method is presented for parameter f and S, in appendix 4, and the range of S is determined by appendix 2 and 3 of this chapter.
In this situation, the rhythm of electromagnetic wave in terms of intensity and frequency fluctuates around 3 times earth electromagnetic field and sunshine frequency respectively. Obviously, the intensity of I also determines the amplitude of waves. The intensity of electromagnetic waves is determined by both parameter I and
j. This is important for cells to recognize the bio-signals.

Discussion:
As discussed in this chapter, it is deduced that the biochemistry dynamics of the first three isozyme families, which show the highest variation by PCA, determines the conclusion of the whole biochemistry dynamics in this research. Consequently, three different frequencies of electromagnetic wave are applied concurrently on this biophysical training of host cells for enhancing immunology, which requires three emittors (or launchers) of electromagnetic wave to work concurrently. However, the receptors (or cells) of electromagnetic wave can NOT identify more than three different frequencies of electromagnetic wave concurrently (This is the environmental pollution of electromagnetic wave), which is similar to the limitation of three spatial dimensions in direct perception capacity of human species (The cell is not so clever to deduce the equations at more than three dimensions like me!).
In this chapter, pathogen ‘army’ behaves as camouflage, ambush, or other intelligence strategy for invasion, and host cells need to defend punctually and effectively by training for survival (host cells adjust their skills by themselves on the basis of biophysical learning during this ‘war’ until invasive enemy dies) --- this is the

evolutionary physiology of environmental adaptiveness, the foundation subject of environmental science.


Reference:
[1] 注册环保工程师专业考试复习教材(2009). 第二分册. 中国环境科学出版社. ISBN:978-7-5111-0505-9.


Appendix 6. The Synthesis of Biological Antibiotics and Its Application on Bio-medicine/生物抗生素合成与在生物医药中的应用
In above appendices, the immunology of host cells becomes the key to resist the invasive pathogen. Nevertheless, there are some exceptions that the immunological potential of host cells, which relies on the synthesis of antibiotics in host cells, may not be sufficient to resist the invasive pathogen (such as congenital defect of rat species against a specific pathogen). Then the vegetation antibiotics is helpful as complementary solution. The steps of synthesis of vegetation antibiotics are similar to appendix 4.
Step 1. N×N samples of a vegetation species, which has been identified to be helpful in biomedicine, are cultivated during simulation of different electromagnetic wave conditions;
Step 2. Different frequency of electromagnetic wave (or different wavelength) are simulated, and labeled as F1, F2, ..., Fn;
Step 3. Metabolomics test is conducted individually after cultivation in F1, F2,...Fn, respectively.
Step 4. Under each simulated frequency of electromagnetic wave, different electromagnetic wave  intensity (AND amplitude) are simulated, and labeled as I1,   I2, ..., and In.
Step 5. Metabolomics test is conducted individually after cultivation in I1, I2,...In, respectively. The amount of N×N metabolomics tests are conducted in total.
Step 6. In total N×N different samples of vegetation antibiotics are abstracted from each different cultivation condition (The method of this abstraction is the same as the preparation of Traditional Chinese Medicine).
Step 7. Each sample of vegetation antibiotics is injected into the invasive simulation of pathogens targeting the host cells of rats respectively, in combination with the training of host cells discussed in chapter 8.
Step 8. The infection of host cells are observed, and the effectiveness of each sample of vegetation antibiotics is decided correspondingly.

It is expected that a combination of antibiotics from both host cells and vegetation leads to the best solution, and a combination of different vegetation antibiotics is more effective. However, the ‘dead’ antibiotics abstracted from vegetation is not as effective as ‘living’ antibiotics in host cells, due to the evolved resistance of  pathogens against the static or constant antibiotics. Actually, there are lots of cases that insect pests frequently evolve into resistance to VERY toxic pesticides, which is the same phenomenon. Please note: the abstraction of vegetation antibiotics here is on the basis of ancient preparation method of Chinese medicine, and the advantages of this is to consider all the vegetation metabolites cultivated in Lab as the whole substances for antibiotics, rather than separating a specific chemistry species from the vegetation metabolites, which can be proven by that plant resistance (or antibiotics) substances usually contain multiple biochemistry species discussed in chapter 4. Another advantages of ancient preparation of Chinese medicine is to provide additional nutrition for host cells. During effective vegetation antibiotics condition, the invasive pathogens are usually dormant so that the competition in nutrition between host cells and pathogens is minimized. Otherwise the additional nutrition may benefit the pathogens rather than host cells.

There are three kinds of vegetation species selected in future research for better ‘diversity of antibiotics’ (If funding is available): one is the Ganoderma Lucidum (I started to grow this from 2011), another is Anoectochilus roxburghii (Wall.) Lindl.(I started to grow this from 2016. Not only human species know this, but also wild pigs must be keen to look for this vegetation for remediation after injury), and the last one is rhizome of Leguminosae species, because the symbiosis of rhizobium in Leguminosae species leads to antibiotics with higher dynamics from both vegetation cells and rhizobium cells. However, the inoculation of various rhizobium, which successfully lead to tumour in root system as symbiosis, is necessary. The reason of enriching rhizobium biodiversity has been discussed in chapter 8 (the specificity of host-invasion interaction), which results in various antibiotics from both plant cells and microbial cells.
For the shading-habitat plant species, which suits shading environment only for growth, plants' leaves usually turns to be yellow when they are long-termly exposed  to the intensitive sunshine. Inversely, the leaves of sunshine-habitat plant species turn from green into yellow when they are shaded. For the shading habitat plant such as  the Anoectochilus roxburghii (Wall.) Lindl. as well as Ganoderma Lucidum, the intensity of UV-B radiation must be reduced for the cultivation, as compared to the intensity used in other articles of this journal.

In addition to the synthesis of vegetation antibiotics for biomedicine, the inoculation of microbial vaccine in animals such us rats, pointed out in chapter 8, also provides effective way of generating antibiotics for biomedicine production against similar genetic strains. However, in this case, symbiosis between microbial vaccine and host cells is not compulsory, which means that the host cells can be ‘eaten up’ by microbial vaccine for biomedicine production. Please note: according to the Traditional Chinese Medicine, the biomedicine made from animal cells tends to be ‘warm,’ possibly due  to too much animal proteins, which need to be incorporated into vegetation biomedicines (which tends to be ‘cool’) as mixtures for best biomedicines.


This is the revised materials in book “Proceedings for Degree of Postgraduate Diploma in Environmental Science (3rd Edition).” Published in 2016. The ‘chapter’ content mentioned in this article is in previous book. Revised on 05/01/2021.

References:
All the science terms in English of this journal source from Wikipedia:
https://encyclopedia.thefreedictionary.com/;
本文所有中文科学专业术语引用自百度百科 https://baike.baidu.com/
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 楼主| 发表于 2021-1-5 10:31:52 | 显示全部楼层
Article 10: Biophysical Simulation of Bio-signals and The Metabolomics /生物信号的物理模拟及新陈代谢组学
Author: Liu Huan, MSc (First Class Honours), The University of Auckland.
Published after graduation on 11/01/2016

Methods:


The same strain of microbes is divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for microbe reproduction process: one is the ‘comfortable’ condition (Sample 1); the other is under UV-B radiation for cultivation (Sample 2). The microbe samples are collected after sufficient reproduction process (Ten generations).
2.After sufficient reproduction process, the UV-B radiation simulation stops. Then both sample 1 and sample 2 are separately transferred into moisture simulation process: different moisture conditions of microbial cultivation are simulated in Lab, and labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) after moisture simulation of T1, T2, ..., Tn respectively, resulting in different zymograms as: M1, M2, ..., Mn.
4.Each isozyme family is labeled as 1, 2, 3..., and E; It is hypothesized that the bands at the same line across different isozyme families are the enzyme species at the same locus, named as enzyme ‘species i’ (i = 1, 2, ..., I), and each isozyme family has the same amount (I) of enzyme species (Please note: this is different from the identification of real enzyme species in the appendix 2 of chapter 1). Then there is a 3-dimension (I× E × N) matrix presented in this research. I is the total amount of enzyme species within a isozyme family; E is the total amount of isozyme families; N is the total amount of zymograms among different simulated moisture conditions:


X= │Xien │( i = 1, 2, ....I; e = 1, 2, .... E; n= 1, 2, ... N)
Xien is the occurrence of enzyme ‘species i’ in the isozyme ‘family e’ during simulated moisture condition Tn. The value of Xien is one or zero.
X111 X211        X112 ... X11n X212 ... X21n        X121 X221        X122 ...... X12n ......
X222 ......X22n .......        X1i1 X2i1        X1i2 X2i2        ......
.......        X1in X2in
X =        .....        .......        ......        .......        .......        ...........        .......        ......        ......        ......        .........
        Xi11        Xi12 ...        Xi1n        Xi21        Xi22        Xi2n        ........        Xie1        Xie2        ......        Xien
        .......        .......        .......        ......        ......        ......        ......        .......        .......        ......        ........


Matrix Se = Xe × (Xe)T Xe = │Xin│( i = 1, 2, ....I; n= 1, 2, ... N); (Xe)T is the transpose of the matrix Xe:

X11                X12 ... X1n X21        X22 ... X2n
Xe = ..... ....... ......

Xi1        Xi2 ...        Xin
....        .....        ......
The Principal Components Analysis (PCA) method of matrix X is specified [1]. PCA is firstly conducted on the basis of matrix Se, revealing the biochemical dynamics of a isozyme ‘family e’ among different simulated moisture conditions. In matrix Se, it is hypothesized that the variable in PCA represents the biochemistry dynamics of each enzyme ‘species i’.

S = ΣSe (e = 1, 2, E)

PCA is further conducted on the basis of matrix S, revealing the biochemical dynamics among different isozyme families over the whole simulated moisture conditions. In matrix S, it is hypothesized that the variable in PCA represents the biochemistry dynamics of each enzyme ‘species i’ across all the isozyme families.

However, for the comparison between sample 1 and sample 2, this book need to present more procedures for subsequent analysis: in matrix Se, the biochemistry

dynamics of the first three enzyme species, which reveal the most differences in the total variation by PCA in an isozyme family, are selected for comparison between sample 1 and sample 2; in matrix S, the biochemistry dynamics of the first three enzyme species, which reveal the most differences in the total variation by PCA  across all the isozyme families, are selected for comparison between sample 1 and sample 2; the sum dynamics of the first three enzyme species in a isozyme family (= the sum Variance Contribution Ratio (VCR) of the first three enzyme species  in matrix Se), represents the total variation of a isozyme family over the whole simulated moisture conditions; the sum dynamics of the first three enzyme species across all the isozyme families (= the sum Variance Contribution Ratio (VCR) of the first three enzyme species in matrix S), represents the variation of the total zymograms over the whole simulated moisture conditions.

Hypotheses:
1.The higher variation in biochemical dynamics of enzyme expression, the better environmental adaptiveness or immunology (the reason of this hypothesis is presented in chapter 7 of this book). It is deduced that the biochemistry dynamics of the first three isozyme families, which show the highest variation by PCA, determines the conclusion of this comparison;

2.Sample 2 leads to higher variation in biochemical dynamics of enzyme expression, which is also revealed by the higher adaptiveness during drought stress or higher immunology.

Discussion:
The findings of this chapter further support the theory, ‘memory’ of gene expression, proposed by the appendix 2 of chapter 1 in this book; As discussed by the chapter 8 of this book, the memory of cells can be ‘trained’ by the biophysical simulation in site, indicated by the zymograms in metabolomics test. Consequently, the memory of cells, in terms of identifying the bio-signals of an environmental factor (can be biotic or abiotic) triggering the gene expression for environmental adaptiveness or immunology, can be trained by the biophysical simulation of other environmental factors. The appendix of this chapter (biophysical simulation for blood cell division) further supports above theories (please note: the theory, ‘memory’ of gene expression, is also applicable on cell division in an individual) by assessment of resistance or immunology in host cells.



This is the revised materials in book “Proceedings for Degree of Postgraduate Diploma in Environmental Science (3rd Edition).” published in 2016. Revised on 05/01/2021.







References:
[1] 陶玲,任裙 (2004)。进化生态学的数量研究方法。第一章,第六节,第 49 页。 中国林业出版社。 ISBN:7-5038-3735-7.


Appendix 1. The Experiment Procedure for Blood Cell Cultivation in Biophysical Simulation/生物物理实验中血细胞培养方法
The blood samples of a rat is abstracted and divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for cell division: one is the ‘comfortable’ condition (Sample 1); the other is under electromagnetism simulation for cell cultivation (Sample 2); the cell samples are collected after sufficient cell division (Ten generations).
2.After sufficient cell division process, the electromagnetism simulation stops. Then both sample 1 and sample 2 are separately transferred into the simulation process of physiological saline: cells are cultivated individually in different concentrations of physiological saline in Lab, and different cell environment (salinity stress of cell environment or ‘thirsty’ simulation) are labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) in cell samples after simulation process of physiological saline, T1, T2, ..., Tn, respectively, resulting in different zymograms as: M1, M2, ..., Mn.
The other procedures are the same as described above.
However, for the comprehensive assessment of immunology in host cells, the simulation process of physiological saline is replaced by the invasion simulation caused by different families of bacteria (or virus):
The blood samples of a rat is abstracted and divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for cell division: one is the ‘comfortable’ condition (Sample 1); the other is under electromagnetism simulation for cell cultivation (Sample 2); the cell samples are collected after sufficient cell division (Ten generations).
2.After sufficient cell division process, the electromagnetism simulation stops. Then both sample 1 and sample 2 are separately transferred into the simulation process of bacteria (or virus) invasion: cells are cultivated individually and independently during the simulation of different families of bacteria (or virus) in Lab, and the invasion simulation process of different bacteria (or virus) families are labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) in cell samples after simulation process  of bacteria  (or  virus) invasion, T1,  T2, ..., Tn, respectively, resulting in different zymograms as: M1, M2, ..., Mn.
The other procedures are the same as described above. This comprehensive assessment of immunology is closer to the real situation of disease caused by multiple species of bacteria, as described by the chapter 8 of this book. Even if the pathology  of host cells (such as cancerous blood cells of rat) is not caused by multiple species of invasive virus or bacteria (and by one species only), the invasive virus or bacteria of the same genetic strain also evolves into various phenotypes in host body, which reflects the significance of comprehensive assessment of immunology.

Please note: if all the blood cells have been ‘eaten’ up (or no cell division rate) by a strain of bacteria during invasion simulation, then the value of this zymogram can be counted as zero for subsequent matrix calculation.
For the comprehensive assessment of immunology in host cells caused by the invasive virus or bacteria of the same genetic strain with different phenotypes:
The blood samples of a rat is abstracted and divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for cell division: one is the ‘comfortable’ condition (Sample 1); the other is under electromagnetism simulation for cell cultivation (Sample 2); the cell samples are collected after sufficient cell division (Ten generations).
2.After sufficient cell division process, the electromagnetism simulation stops. Then both sample 1 and sample 2 are separately transferred into the simulation process of bacteria (or virus) invasion of the same genetic strain with different phenotypes: cells are cultivated individually and independently during the invasive simulation by different phenotypes of the same genetic bacteria (or virus) in Lab, and the invasion simulation process by different phenotypes of the same genetic bacteria (or virus) are labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) in cell samples after simulation process  of bacteria  (or  virus) invasion, T1,  T2, ..., Tn, respectively, resulting in different zymograms as: M1, M2, ..., Mn.
The other procedures are the same as described above. This electromagnetism simulation can be either constant electromagnetism fields or time-varying electromagnetic waves, which are further discussed later.
Conclusion:
The comprehensive assessment of immunology in host cells also provides indicators of training host cells by adjusting the parameters of biophysical simulation, once the specific zymograms, indicating the immunology against the specific invasive bacteria or virus (or the specific phenotype of an invasive pathogen), are identified by the methods presented in the appendix of chapter 8. However, the higher dynamics, the better immunology against various pathogen species (or various phenotypes of a pathogen genotype).


Appendix 2. The Determination Method of Bio-signal Range for Biophysical Simulation /生物物理模拟试验中生物信号范围的确定方法
Step 1. The host cells of the same genetic strain (such as the blood cells of rat) are abstracted, which are divided  into  several  cell  samples,  and  labeled  as  S1,  S2,  S3 ,Sn;
Step 2. The simulation of a specific virus (or bacteria) invasion targeting the host cells is conducted in Lab, immediately after host cells are abstracted from host body;
Step 3. The samples of host cells with apparent antibiotics are identified, as described by the appendix of chapter 8; and the samples of host cells without apparent antibiotics are also continuously observed until they are ‘eaten up’ by the specific invasive pathogen;
Step 4. The separation of virus from each sample of host cell without apparent antibiotics are conducted independently in Lab, and the metabolomics test is conducted in each virus sample;
Objective:
The different phenotypes of an invasive virus (or bacteria) strain are identified, and  the biochemistry dynamics of this invasive virus strain is calculated, as discussed in this chapter. The result of biochemistry dynamics calculation helps to determine the range of bio-physical training parameters to enhance the comprehensive immunology of host cells, as described above.
Please note: the simulation of a specific virus (or bacteria) invasion targeting the host cells should be conducted immediately after host cells are abstracted from host body, otherwise the uniform cell cultivation in Lab lead to the homogeneity of host cells, so that different phenotypes of an invasive pathogen can be hardly detected.
Because the virus sample for invasion simulation is cultivated in Lab, which is the uniform phenotype, the samples of host cells with apparent antibiotics usually show specific zymograms correspondingly to the specific invasive virus. However, if virus samples, which are separated from host cell without apparent antibiotics after step 3, re-invade the host cells with apparent antibiotics identified in step 3, virus infection would occur, due to the evolution of new virus phenotypes.


Appendix 3. Bio-magnetic field of Cell and Its Application on Separation of Blood Cell Communities along Environmental
Gradient/细胞的生物磁场及血细胞群落在环境梯度上的分离

Step 1. The host cells (such as blood cells of rat) are abstracted from host body. Step 2. Electrophoresis of blood cells is conducted in moderate electromagnetism;
Step 3. Different blood cell communities are separated along the environmental gradient of electromagnetism signal, leading to cell samples with different immunology.
Discussion
The bio-magnetic field of blood cells varies even within the same genetic strain, so that different cell communities can be separated according to the gradual variation in electromagnetism signals (environmental gradient of electromagnetism) in this electrophoresis, leading to cell samples with different immunology. The cell samples, abstracted from different electric potential (j1, j2...jn), are labeled on the basis of electric potential.
Step 4. The specificity of host-invasion interaction is examined on each cell sample, according to the appendix of chapter 8 in this book. It is expected that the specific electric potential corresponds to the host cells with apparent antibiotics against the specific invasive virus (or bacteria), which also becomes the key parameter of biophysical training for the host cells with immunology against the specific invasive virus (or bacteria). Nevertheless, for the mobilizable blood cells, it is expected that the 'ecological niche' of cells vary in their life cycle along this environmental gradient of electromagnetism signal, because of the variation in bio-magnetic field over cell's life cycle, moving from a specific electric potential to another electric potential.
It is expected that the time-varying electromagnetic field of biophysical training is better than constant electromagnetic field, due to the phenotype evolution of invasive virus (bacteria).
Please note: the intensity of electromagnetism is preliminarily set to be 1.6 H (1H = 1 A/m) in this research, three times than earth magnetism fields. If the intensity of electromagnetism is more than 5 times than earth magnetism fields, blood cell  division rate of rats starts to decline apparently, ‘looking nervous,’ which is closer to the situation of ‘hemorrhage.’ They are unlike microbes who can survive long-termly in sunshine intensity.


Appendix 4. Bio-signal Simulation of Electromagnetic Wave and Its Specificity on the Isozyme Expression/电磁波的生物信号模拟及同工酶表达的专一性
In appendix 3, the specificity of electric potential to the host cells with apparent antibiotics against the specific invasive virus (or bacteria) is determined. However, this method is relatively broader, so that the accuracy of this biophysical training is not sufficient for the synthesis of antibiotics in cells against the specific phenotype of an invasive virus (or bacteria).
Consequently, this section presents a novel methods to train the specific isozyme families catalyzing the synthesis of antibiotics in cells against the specific phenotype of an invasive virus (or bacteria):
Step 1. Host cells (such as blood cells) are cultivated during simulation of electromagnetic wave conditions;
Step 2. Different frequency of electromagnetic wave (or different wavelength) are simulated, and labeled as F1, F2, ..., Fn;
Step 3. Metabolomics test is conducted individually after cultivation in F1, F2,...Fn, respectively.
Step 4. Under each simulated frequency of electromagnetic wave, different electromagnetic wave intensity are simulated, and labeled as I1, I2, ..., and In.
Step 5. Metabolomics test is conducted individually after cultivation in I1, I2,...In, respectively. The amount of N×N metabolomics tests are conducted in total.
Objectives:
The specific frequency of electromagnetic wave simulates the bio-signal regulating gene expression as a specific isozyme family, and the specific electromagnetic wave intensity (AND amplitude) corresponds to the bio-signal regulating gene expression as a specific enzyme species within an isozyme family, which can be determined by metabolomics tests. Consequently, the immunology against the specific phenotype of an invasive virus (or bacteria) can be trained according to the zymograms, described  in the appendix of chapter 8. Please note: the intensity is adjusted and controlled by the amplitude instructed in appendix 5.

This experiment is similar to chapter 4 (UV-B is one of electromagnetic waves). Let’s re-discuss the chapter 4 on the basis of plant cell data (the blood cell data of rat is not clear to this date 18/02/2016): As discussed in chapter 4, UV-B significantly (P<0.001) affected the net photosynthesis (A) (Table 1). Nevertheless, for Tienshan clover and Caucasian clover, there was no significant UV-B induced difference in the total aerial biomass yield, under well-water conditions, and there was no significant effect of UV-B on the relative chlorophyll content, whereas enhanced UV-B apparently decreased the biomass of Kopu II. Further more, the water deficit did not influence   the relative chlorophyll content as comparison to the well-water condition (Table 1).

There are two reasons to explain this science discovery: firstly, the Light Use Efficiency (LUE) already exceeded the saturation point of LUE under well water condition without enhanced UB treatment (as discussed in other articles of journal), so that the reduction of net photosynthesis under enhanced UB treatment did not influence the total aerial biomass yield; Secondly, enhanced UV-B treatment effectively triggered the gene expression of enzyme species within the isozyme families involving in the chlorophyll synthesis in plant cells, which revealed that the isozyme families involving in the chlorophyll synthesis could express effectively under a broader range of UV-B intensity especially for Caucasian clover, but the relevant gene of Kopu II was not effectively expressed as enzyme species within the isozyme families involving in the chlorophyll synthesis under enhanced UV-B. Please note: within the isozyme families involving in the chlorophyll synthesis in plant cells, the enzyme species under enhanced UV-B is different from the one without enhanced UV-B. However, drought condition did not influence the synthesis of chlorophyll, which showed different metabolic pathway in response to the environmental stress. The treatment without UV-B in this experiment was not without any UV-B radiation, and was just lower intensity of UV-B treatment. Although chapter 4 explains that ‘these results indicated that these clovers might have adequately photo-protective mechanism, such as enhancing the synthesis of UV-B screening  secondary metabolites (Hofmann et al., 2003a),’ this explanation is consistent with the above explanation in this section, because the synthesis of UV-B screening secondary metabolites as photo-protective mechanism is also the phenomenon utilizing the light energy effectively, adjusting the photo-metabolic pathways in response to the change of UV-B intensity (UV-B is also the utilizable light energy in photosynthesis rather than visible light only, which can be proven the result that Caucasian clover showed increased biomass during enhanced UV-B of well water treatment as compared to the well water condition without UV-B, although the main utilizable energy is from the visible light --- without visible light, photosynthesis can not only rely on UV-B to happen --- this is the conclusion of this book). As discussed in appendix 5, the receptors (or cells) of electromagnetic wave can NOT identify more than three different frequencies of electromagnetic wave concurrently, it is hypothesized that plant cells themselves select three frequencies of light waves with the highest  intensity for photosynthesis, and Caucasian clover selects UV-B frequency for photosynthesis whereas Kopu II can not, this is definitely the environmental adaptiveness evolved from its origin.

Please note: for the identification of specific zymograms of host cells with specific immunology against invasive gene mutation virus in chapter 8, then invasive simulation of gene mutation virus is added during the whole process of biophysics simulation for identifying the specificity of host-invasion interaction (in which frequency and intensity of cultivation condition, the host cells show effective immunology against the gene mutation virus).

Nevertheless, for the virus (or bacteria) with dormant characters (such as HIV), it is expected that long-term observation is required for this specificity examination after
biophysics simulation stops, because this virus would become dormant in host cells after puncturing cell membrane during biophysics simulation, so that the host cells with effective immunology against the dormant virus are NOT specifically identified during biophysical simulation. In this case, the host cells with really effective immunology against the dormant virus kill the invasive virus during biophysical simulation, whereas the host cells with dormant virus would be re-infected after biophysical simulation stops. After long-termly observing if dormant virus re-starts pathogenetic metabolism in host cells, the identified host cells with really effective immunology against the dormant virus would be screened and become more specific. Finally the range of biophysics parameters in appendix 5 should be based on all the host cell samples which have been identified as effective immunology against the dormant virus during biophysics simulation. The more specific, the more punctual to kill the invasive virus.

Please note: the intensity of electromagnetic waves is preliminarily set to be 1.6 H  (1H = 1 A/m) for blood cells in this research, three times than earth magnetism fields. If the intensity of electromagnetism is more than 5 times than earth magnetism fields, blood cell division rate of rats starts to decline apparently, ‘looking nervous.’ They are unlike microbes who can survive long-termly in sunshine intensity. However, the frequency of electromagnetic waves is preliminarily set to be around UV-B frequency, the sunshine one. Actually, blood cells still function (such as oxygen-carrying capacity) effectively under exposure to sunshine radiation, but the blood cell division only occurs when sunshine radiation is shielded. This is why hematopoietic function of blood cells mainly occurs in marrow! and blood cells division rate actively increases during evening as well!


Appendix 5. The Parameterization of Time-varying Electromagnetic Field for Biophysics Simulation/生物物理模拟实验中时变电磁场参数的确定方法
Method:
This section presents a novel method to determine the parameters of time-varying electromagnetic field, on the basis of ‘Skin Effect’ equations in combination with ‘Maxwell’ equations:
1.Skin effect equations:
I (t)= √2 I sin (wt); w = 2πf ;
2.Maxwell's equations:
I (t)= j H (t)
S = I (t) * H (t)
I is the effective intensity of electric field, t is the varying time, w is the angular frequency (rad/s), f is the frequency, H is the intensity of magnetic field, j is the conductivity, and S is the energy of wave (or the electromagnetic wave intensity) [1]. The determination of biophysical training method is presented for parameter f and S, in appendix 4, and the range of S is determined by appendix 2 and 3 of this chapter.
In this situation, the rhythm of electromagnetic wave in terms of intensity and frequency fluctuates around 3 times earth electromagnetic field and sunshine frequency respectively. Obviously, the intensity of I also determines the amplitude of waves. The intensity of electromagnetic waves is determined by both parameter I and
j. This is important for cells to recognize the bio-signals.

Discussion:
As discussed in this chapter, it is deduced that the biochemistry dynamics of the first three isozyme families, which show the highest variation by PCA, determines the conclusion of the whole biochemistry dynamics in this research. Consequently, three different frequencies of electromagnetic wave are applied concurrently on this biophysical training of host cells for enhancing immunology, which requires three emittors (or launchers) of electromagnetic wave to work concurrently. However, the receptors (or cells) of electromagnetic wave can NOT identify more than three different frequencies of electromagnetic wave concurrently (This is the environmental pollution of electromagnetic wave), which is similar to the limitation of three spatial dimensions in direct perception capacity of human species (The cell is not so clever to deduce the equations at more than three dimensions like me!).
In this chapter, pathogen ‘army’ behaves as camouflage, ambush, or other intelligence strategy for invasion, and host cells need to defend punctually and effectively by training for survival (host cells adjust their skills by themselves on the basis of biophysical learning during this ‘war’ until invasive enemy dies) --- this is the evolutionary physiology of environmental adaptiveness, the foundation subject of environmental science.
Reference:
[1] 注册环保工程师专业考试复习教材(2009). 第二分册. 中国环境科学出版社. ISBN:978-7-5111-0505-9.


Appendix 6. The Synthesis of Biological Antibiotics and Its Application on Biomedicine/生物抗生素合成与在生物医药中的应用
In above appendices, the immunology of host cells becomes the key to resist the invasive pathogen. Nevertheless, there are some exceptions that the immunological potential of host cells, which relies on the synthesis of antibiotics in host cells, may not be sufficient to resist the invasive pathogen (such as congenital defect of rat species against a specific pathogen). Then the vegetation antibiotics is helpful as complementary solution. The steps of synthesis of vegetation antibiotics are similar to appendix 4.
Step 1. N×N samples of a vegetation species, which has been identified to be helpful in biomedicine, are cultivated during simulation of different electromagnetic wave conditions;
Step 2. Different frequency of electromagnetic wave (or different wavelength) are simulated, and labeled as F1, F2, ..., Fn;
Step 3. Metabolomics test is conducted individually after cultivation in F1, F2,...Fn, respectively.
Step 4. Under each simulated frequency of electromagnetic wave, different electromagnetic wave  intensity (AND amplitude) are simulated, and labeled as I1,   I2, ..., and In.
Step 5. Metabolomics test is conducted individually after cultivation in I1, I2,...In, respectively. The amount of N×N metabolomics tests are conducted in total.
Step 6. In total N×N different samples of vegetation antibiotics are abstracted from each different cultivation condition (The method of this abstraction is the same as the preparation of Traditional Chinese Medicine).
Step 7. Each sample of vegetation antibiotics is injected into the invasive simulation of pathogens targeting the host cells of rats respectively, in combination with the training of host cells discussed in chapter 8.
Step 8. The infection of host cells are observed, and the effectiveness of each sample of vegetation antibiotics is decided correspondingly.

It is expected that a combination of antibiotics from both host cells and vegetation leads to the best solution, and a combination of different vegetation antibiotics is more effective. However, the ‘dead’ antibiotics abstracted from vegetation is not as effective as ‘living’ antibiotics in host cells, due to the evolved resistance of  pathogens against the static or constant antibiotics. Actually, there are lots of cases that insect pests frequently evolve into resistance to VERY toxic pesticides, which is the same phenomenon. Please note: the abstraction of vegetation antibiotics here is on the basis of ancient preparation method of Chinese medicine, and the advantages of this is to consider all the vegetation metabolites cultivated in Lab as the whole substances for antibiotics, rather than separating a specific chemistry species from the vegetation metabolites, which can be proven by that plant resistance (or antibiotics) substances usually contain multiple biochemistry species discussed in chapter 4. Another advantages of ancient preparation of Chinese medicine is to provide additional nutrition for host cells. During effective vegetation antibiotics condition, the invasive pathogens are usually dormant so that the competition in nutrition between host cells and pathogens is minimized. Otherwise the additional nutrition may benefit the pathogens rather than host cells.

There are three kinds of vegetation species selected in future research for better ‘diversity of antibiotics’ (If funding is available): one is the Ganoderma Lucidum (I started to grow this from 2011), another is Anoectochilus roxburghii (Wall.) Lindl.(I started to grow this from 2016. Not only human species know this, but also wild pigs must be keen to look for this vegetation for remediation after injury), and the last one is rhizome of Leguminosae species, because the symbiosis of rhizobium in Leguminosae species leads to antibiotics with higher dynamics from both vegetation cells and rhizobium cells. However, the inoculation of various rhizobium, which successfully lead to tumour in root system as symbiosis, is necessary. The reason of enriching rhizobium biodiversity has been discussed in chapter 8 (the specificity of host-invasion interaction), which results in various antibiotics from both plant cells and microbial cells.
For the shading-habitat plant species, which suits shading environment only for growth, plants' leaves usually turns to be yellow when they are long-termly exposed  to the intensitive sunshine. Inversely, the leaves of sunshine-habitat plant species turn from green into yellow when they are shaded. For the shading habitat plant such as  the Anoectochilus roxburghii (Wall.) Lindl. as well as Ganoderma Lucidum, the intensity of UV-B radiation must be reduced for the cultivation, as compared to the intensity used in Chapter 4.

In addition to the synthesis of vegetation antibiotics for biomedicine, the inoculation of microbial vaccine in animals such us rats, pointed out in chapter 8, also provides effective way of generating antibiotics for biomedicine production against similar genetic strains. However, in this case, symbiosis between microbial vaccine and host cells is not compulsory, which means that the host cells can be ‘eaten up’ by microbial vaccine for biomedicine production. Please note: according to the Traditional Chinese Medicine, the biomedicine made from animal cells tends to be ‘warm,’ possibly due  to too much animal proteins, which need to be incorporated into vegetation biomedicines (which tends to be ‘cool’) as mixtures for best biomedicines.

This is the revised materials in book “Proceedings for Degree of Postgraduate Diploma in Environmental Science (3rd Edition).” published in 2016. Revised on 05/01/2021.
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19341
 楼主| 发表于 2021-1-5 11:08:31 | 显示全部楼层
Article 10: Biophysical Simulation of Bio-signals and The Metabolomics /生物信号的物理模拟及新陈代谢组学
Author: Liu Huan, MSc (First Class Honours), The University of Auckland.
Published after graduation on 11/01/2016

Methods:


The same strain of microbes is divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for microbe reproduction process: one is the ‘comfortable’ condition (Sample 1); the other is under UV-B radiation for cultivation (Sample 2). The microbe samples are collected after sufficient reproduction process (Ten generations).
2.After sufficient reproduction process, the UV-B radiation simulation stops. Then both sample 1 and sample 2 are separately transferred into moisture simulation process: different moisture conditions of microbial cultivation are simulated in Lab, and labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) after moisture simulation of T1, T2, ..., Tn respectively, resulting in different zymograms as: M1, M2, ..., Mn.
4.Each isozyme family is labeled as 1, 2, 3..., and E; It is hypothesized that the bands at the same line across different isozyme families are the enzyme species at the same locus, named as enzyme ‘species i’ (i = 1, 2, ..., I), and each isozyme family has the same amount (I) of enzyme species (Please note: this is different from the identification of real enzyme species in the appendix 2 of chapter 1). Then there is a 3-dimension (I× E × N) matrix presented in this research. I is the total amount of enzyme species within a isozyme family; E is the total amount of isozyme families; N is the total amount of zymograms among different simulated moisture conditions:


X= │Xien │( i = 1, 2, ....I; e = 1, 2, .... E; n= 1, 2, ... N)
Xien is the occurrence of enzyme ‘species i’ in the isozyme ‘family e’ during simulated moisture condition Tn. The value of Xien is one or zero.
X111 X211        X112 ... X11n X212 ... X21n        X121 X221        X122 ...... X12n ......
X222 ......X22n .......        X1i1 X2i1        X1i2 X2i2        ......
.......        X1in X2in
X =        .....        .......        ......        .......        .......        ...........        .......        ......        ......        ......        .........
        Xi11        Xi12 ...        Xi1n        Xi21        Xi22        Xi2n        ........        Xie1        Xie2        ......        Xien
        .......        .......        .......        ......        ......        ......        ......        .......        .......        ......        ........


Matrix Se = Xe × (Xe)T Xe = │Xin│( i = 1, 2, ....I; n= 1, 2, ... N); (Xe)T is the transpose of the matrix Xe:

X11                X12 ... X1n X21        X22 ... X2n
Xe = ..... ....... ......

Xi1        Xi2 ...        Xin
....        .....        ......
The Principal Components Analysis (PCA) method of matrix X is specified [1]. PCA is firstly conducted on the basis of matrix Se, revealing the biochemical dynamics of a isozyme ‘family e’ among different simulated moisture conditions. In matrix Se, it is hypothesized that the variable in PCA represents the biochemistry dynamics of each enzyme ‘species i’.

S = ΣSe (e = 1, 2, E)

PCA is further conducted on the basis of matrix S, revealing the biochemical dynamics among different isozyme families over the whole simulated moisture conditions. In matrix S, it is hypothesized that the variable in PCA represents the biochemistry dynamics of each enzyme ‘species i’ across all the isozyme families.

However, for the comparison between sample 1 and sample 2, this book need to present more procedures for subsequent analysis: in matrix Se, the biochemistry

dynamics of the first three enzyme species, which reveal the most differences in the total variation by PCA in an isozyme family, are selected for comparison between sample 1 and sample 2; in matrix S, the biochemistry dynamics of the first three enzyme species, which reveal the most differences in the total variation by PCA  across all the isozyme families, are selected for comparison between sample 1 and sample 2; the sum dynamics of the first three enzyme species in a isozyme family (= the sum Variance Contribution Ratio (VCR) of the first three enzyme species  in matrix Se), represents the total variation of a isozyme family over the whole simulated moisture conditions; the sum dynamics of the first three enzyme species across all the isozyme families (= the sum Variance Contribution Ratio (VCR) of the first three enzyme species in matrix S), represents the variation of the total zymograms over the whole simulated moisture conditions.

Hypotheses:
1.The higher variation in biochemical dynamics of enzyme expression, the better environmental adaptiveness or immunology (the reason of this hypothesis is presented in chapter 7 of this book). It is deduced that the biochemistry dynamics of the first three isozyme families, which show the highest variation by PCA, determines the conclusion of this comparison;

2.Sample 2 leads to higher variation in biochemical dynamics of enzyme expression, which is also revealed by the higher adaptiveness during drought stress or higher immunology.

Discussion:
The findings of this chapter further support the theory, ‘memory’ of gene expression, proposed by other articles of this journal; As discussed by other articles of this journal, the memory of cells can be ‘trained’ by the biophysical simulation in site, indicated by the zymograms in metabolomics test. Consequently, the memory of cells, in terms of identifying the bio-signals of an environmental factor (can be biotic or abiotic) triggering the gene expression for environmental adaptiveness or immunology, can be trained by the biophysical simulation of other environmental factors. The appendix of this chapter (biophysical simulation for blood cell division) further supports above theories (please note: the theory, ‘memory’ of gene expression, is also applicable on cell division in an individual) by assessment of resistance or immunology in host cells.



This is the revised materials in book “Proceedings for Degree of Postgraduate Diploma in Environmental Science (3rd Edition).” published in 2016. Revised on 05/01/2021.







References:
[1] 陶玲,任裙 (2004)。进化生态学的数量研究方法。第一章,第六节,第 49 页。 中国林业出版社。 ISBN:7-5038-3735-7.


Appendix 1. The Experiment Procedure for Blood Cell Cultivation in Biophysical Simulation/生物物理实验中血细胞培养方法
The blood samples of a rat is abstracted and divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for cell division: one is the ‘comfortable’ condition (Sample 1); the other is under electromagnetism simulation for cell cultivation (Sample 2); the cell samples are collected after sufficient cell division (Ten generations).
2.After sufficient cell division process, the electromagnetism simulation stops. Then both sample 1 and sample 2 are separately transferred into the simulation process of physiological saline: cells are cultivated individually in different concentrations of physiological saline in Lab, and different cell environment (salinity stress of cell environment or ‘thirsty’ simulation) are labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) in cell samples after simulation process of physiological saline, T1, T2, ..., Tn, respectively, resulting in different zymograms as: M1, M2, ..., Mn.
The other procedures are the same as described above.
However, for the comprehensive assessment of immunology in host cells, the simulation process of physiological saline is replaced by the invasion simulation caused by different families of bacteria (or virus):
The blood samples of a rat is abstracted and divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for cell division: one is the ‘comfortable’ condition (Sample 1); the other is under electromagnetism simulation for cell cultivation (Sample 2); the cell samples are collected after sufficient cell division (Ten generations).
2.After sufficient cell division process, the electromagnetism simulation stops. Then both sample 1 and sample 2 are separately transferred into the simulation process of bacteria (or virus) invasion: cells are cultivated individually and independently during the simulation of different families of bacteria (or virus) in Lab, and the invasion simulation process of different bacteria (or virus) families are labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) in cell samples after simulation process  of bacteria  (or  virus) invasion, T1,  T2, ..., Tn, respectively, resulting in different zymograms as: M1, M2, ..., Mn.
The other procedures are the same as described above. This comprehensive assessment of immunology is closer to the real situation of disease caused by multiple species of bacteria, as described by the chapter 8 of this book. Even if the pathology  of host cells (such as cancerous blood cells of rat) is not caused by multiple species of invasive virus or bacteria (and by one species only), the invasive virus or bacteria of the same genetic strain also evolves into various phenotypes in host body, which reflects the significance of comprehensive assessment of immunology.

Please note: if all the blood cells have been ‘eaten’ up (or no cell division rate) by a strain of bacteria during invasion simulation, then the value of this zymogram can be counted as zero for subsequent matrix calculation.
For the comprehensive assessment of immunology in host cells caused by the invasive virus or bacteria of the same genetic strain with different phenotypes:
The blood samples of a rat is abstracted and divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for cell division: one is the ‘comfortable’ condition (Sample 1); the other is under electromagnetism simulation for cell cultivation (Sample 2); the cell samples are collected after sufficient cell division (Ten generations).
2.After sufficient cell division process, the electromagnetism simulation stops. Then both sample 1 and sample 2 are separately transferred into the simulation process of bacteria (or virus) invasion of the same genetic strain with different phenotypes: cells are cultivated individually and independently during the invasive simulation by different phenotypes of the same genetic bacteria (or virus) in Lab, and the invasion simulation process by different phenotypes of the same genetic bacteria (or virus) are labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) in cell samples after simulation process  of bacteria  (or  virus) invasion, T1,  T2, ..., Tn, respectively, resulting in different zymograms as: M1, M2, ..., Mn.
The other procedures are the same as described above. This electromagnetism simulation can be either constant electromagnetism fields or time-varying electromagnetic waves, which are further discussed later.
Conclusion:
The comprehensive assessment of immunology in host cells also provides indicators of training host cells by adjusting the parameters of biophysical simulation, once the specific zymograms, indicating the immunology against the specific invasive bacteria or virus (or the specific phenotype of an invasive pathogen), are identified by the methods presented in the appendix of chapter 8. However, the higher dynamics, the better immunology against various pathogen species (or various phenotypes of a pathogen genotype).


Appendix 2. The Determination Method of Bio-signal Range for Biophysical Simulation /生物物理模拟试验中生物信号范围的确定方法
Step 1. The host cells of the same genetic strain (such as the blood cells of rat) are abstracted, which are divided  into  several  cell  samples,  and  labeled  as  S1,  S2,  S3 ,Sn;
Step 2. The simulation of a specific virus (or bacteria) invasion targeting the host cells is conducted in Lab, immediately after host cells are abstracted from host body;
Step 3. The samples of host cells with apparent antibiotics are identified, as described by the appendix of chapter 8; and the samples of host cells without apparent antibiotics are also continuously observed until they are ‘eaten up’ by the specific invasive pathogen;
Step 4. The separation of virus from each sample of host cell without apparent antibiotics are conducted independently in Lab, and the metabolomics test is conducted in each virus sample;
Objective:
The different phenotypes of an invasive virus (or bacteria) strain are identified, and  the biochemistry dynamics of this invasive virus strain is calculated, as discussed in this chapter. The result of biochemistry dynamics calculation helps to determine the range of bio-physical training parameters to enhance the comprehensive immunology of host cells, as described above.
Please note: the simulation of a specific virus (or bacteria) invasion targeting the host cells should be conducted immediately after host cells are abstracted from host body, otherwise the uniform cell cultivation in Lab lead to the homogeneity of host cells, so that different phenotypes of an invasive pathogen can be hardly detected.
Because the virus sample for invasion simulation is cultivated in Lab, which is the uniform phenotype, the samples of host cells with apparent antibiotics usually show specific zymograms correspondingly to the specific invasive virus. However, if virus samples, which are separated from host cell without apparent antibiotics after step 3, re-invade the host cells with apparent antibiotics identified in step 3, virus infection would occur, due to the evolution of new virus phenotypes.


Appendix 3. Bio-magnetic field of Cell and Its Application on Separation of Blood Cell Communities along Environmental
Gradient/细胞的生物磁场及血细胞群落在环境梯度上的分离

Step 1. The host cells (such as blood cells of rat) are abstracted from host body. Step 2. Electrophoresis of blood cells is conducted in moderate electromagnetism;
Step 3. Different blood cell communities are separated along the environmental gradient of electromagnetism signal, leading to cell samples with different immunology.
Discussion
The bio-magnetic field of blood cells varies even within the same genetic strain, so that different cell communities can be separated according to the gradual variation in electromagnetism signals (environmental gradient of electromagnetism) in this electrophoresis, leading to cell samples with different immunology. The cell samples, abstracted from different electric potential (j1, j2...jn), are labeled on the basis of electric potential.
Step 4. The specificity of host-invasion interaction is examined on each cell sample, according to the appendix of chapter 8 in this book. It is expected that the specific electric potential corresponds to the host cells with apparent antibiotics against the specific invasive virus (or bacteria), which also becomes the key parameter of biophysical training for the host cells with immunology against the specific invasive virus (or bacteria). Nevertheless, for the mobilizable blood cells, it is expected that the 'ecological niche' of cells vary in their life cycle along this environmental gradient of electromagnetism signal, because of the variation in bio-magnetic field over cell's life cycle, moving from a specific electric potential to another electric potential.
It is expected that the time-varying electromagnetic field of biophysical training is better than constant electromagnetic field, due to the phenotype evolution of invasive virus (bacteria).
Please note: the intensity of electromagnetism is preliminarily set to be 1.6 H (1H = 1 A/m) in this research, three times than earth magnetism fields. If the intensity of electromagnetism is more than 5 times than earth magnetism fields, blood cell  division rate of rats starts to decline apparently, ‘looking nervous,’ which is closer to the situation of ‘hemorrhage.’ They are unlike microbes who can survive long-termly in sunshine intensity.


Appendix 4. Bio-signal Simulation of Electromagnetic Wave and Its Specificity on the Isozyme Expression/电磁波的生物信号模拟及同工酶表达的专一性
In appendix 3, the specificity of electric potential to the host cells with apparent antibiotics against the specific invasive virus (or bacteria) is determined. However, this method is relatively broader, so that the accuracy of this biophysical training is not sufficient for the synthesis of antibiotics in cells against the specific phenotype of an invasive virus (or bacteria).
Consequently, this section presents a novel methods to train the specific isozyme families catalyzing the synthesis of antibiotics in cells against the specific phenotype of an invasive virus (or bacteria):
Step 1. Host cells (such as blood cells) are cultivated during simulation of electromagnetic wave conditions;
Step 2. Different frequency of electromagnetic wave (or different wavelength) are simulated, and labeled as F1, F2, ..., Fn;
Step 3. Metabolomics test is conducted individually after cultivation in F1, F2,...Fn, respectively.
Step 4. Under each simulated frequency of electromagnetic wave, different electromagnetic wave intensity are simulated, and labeled as I1, I2, ..., and In.
Step 5. Metabolomics test is conducted individually after cultivation in I1, I2,...In, respectively. The amount of N×N metabolomics tests are conducted in total.
Objectives:
The specific frequency of electromagnetic wave simulates the bio-signal regulating gene expression as a specific isozyme family, and the specific electromagnetic wave intensity (AND amplitude) corresponds to the bio-signal regulating gene expression as a specific enzyme species within an isozyme family, which can be determined by metabolomics tests. Consequently, the immunology against the specific phenotype of an invasive virus (or bacteria) can be trained according to the zymograms, described  in the appendix of chapter 8. Please note: the intensity is adjusted and controlled by the amplitude instructed in appendix 5.

This experiment is similar to chapter 4 (UV-B is one of electromagnetic waves). Let’s re-discuss the chapter 4 on the basis of plant cell data (the blood cell data of rat is not clear to this date 18/02/2016): As discussed in chapter 4, UV-B significantly (P<0.001) affected the net photosynthesis (A) (Table 1). Nevertheless, for Tienshan clover and Caucasian clover, there was no significant UV-B induced difference in the total aerial biomass yield, under well-water conditions, and there was no significant effect of UV-B on the relative chlorophyll content, whereas enhanced UV-B apparently decreased the biomass of Kopu II. Further more, the water deficit did not influence   the relative chlorophyll content as comparison to the well-water condition (Table 1).

There are two reasons to explain this science discovery: firstly, the Light Use Efficiency (LUE) already exceeded the saturation point of LUE under well water condition without enhanced UB treatment (as discussed in other articles of journal), so that the reduction of net photosynthesis under enhanced UB treatment did not influence the total aerial biomass yield; Secondly, enhanced UV-B treatment effectively triggered the gene expression of enzyme species within the isozyme families involving in the chlorophyll synthesis in plant cells, which revealed that the isozyme families involving in the chlorophyll synthesis could express effectively under a broader range of UV-B intensity especially for Caucasian clover, but the relevant gene of Kopu II was not effectively expressed as enzyme species within the isozyme families involving in the chlorophyll synthesis under enhanced UV-B. Please note: within the isozyme families involving in the chlorophyll synthesis in plant cells, the enzyme species under enhanced UV-B is different from the one without enhanced UV-B. However, drought condition did not influence the synthesis of chlorophyll, which showed different metabolic pathway in response to the environmental stress. The treatment without UV-B in this experiment was not without any UV-B radiation, and was just lower intensity of UV-B treatment. Although chapter 4 explains that ‘these results indicated that these clovers might have adequately photo-protective mechanism, such as enhancing the synthesis of UV-B screening  secondary metabolites (Hofmann et al., 2003a),’ this explanation is consistent with the above explanation in this section, because the synthesis of UV-B screening secondary metabolites as photo-protective mechanism is also the phenomenon utilizing the light energy effectively, adjusting the photo-metabolic pathways in response to the change of UV-B intensity (UV-B is also the utilizable light energy in photosynthesis rather than visible light only, which can be proven the result that Caucasian clover showed increased biomass during enhanced UV-B of well water treatment as compared to the well water condition without UV-B, although the main utilizable energy is from the visible light --- without visible light, photosynthesis can not only rely on UV-B to happen --- this is the conclusion of this book). As discussed in appendix 5, the receptors (or cells) of electromagnetic wave can NOT identify more than three different frequencies of electromagnetic wave concurrently, it is hypothesized that plant cells themselves select three frequencies of light waves with the highest  intensity for photosynthesis, and Caucasian clover selects UV-B frequency for photosynthesis whereas Kopu II can not, this is definitely the environmental adaptiveness evolved from its origin.

Please note: for the identification of specific zymograms of host cells with specific immunology against invasive gene mutation virus in chapter 8, then invasive simulation of gene mutation virus is added during the whole process of biophysics simulation for identifying the specificity of host-invasion interaction (in which frequency and intensity of cultivation condition, the host cells show effective immunology against the gene mutation virus).

Nevertheless, for the virus (or bacteria) with dormant characters (such as HIV), it is expected that long-term observation is required for this specificity examination after

biophysics simulation stops, because this virus would become dormant in host cells after puncturing cell membrane during biophysics simulation, so that the host cells with effective immunology against the dormant virus are NOT specifically identified during biophysical simulation. In this case, the host cells with really effective immunology against the dormant virus kill the invasive virus during biophysical simulation, whereas the host cells with dormant virus would be re-infected after biophysical simulation stops. After long-termly observing if dormant virus re-starts pathogenetic metabolism in host cells, the identified host cells with really effective immunology against the dormant virus would be screened and become more specific. Finally the range of biophysics parameters in appendix 5 should be based on all the host cell samples which have been identified as effective immunology against the dormant virus during biophysics simulation. The more specific, the more punctual to kill the invasive virus.

Please note: the intensity of electromagnetic waves is preliminarily set to be 1.6 H  (1H = 1 A/m) for blood cells in this research, three times than earth magnetism fields. If the intensity of electromagnetism is more than 5 times than earth magnetism fields, blood cell division rate of rats starts to decline apparently, ‘looking nervous.’ They are unlike microbes who can survive long-termly in sunshine intensity. However, the frequency of electromagnetic waves is preliminarily set to be around UV-B frequency, the sunshine one. Actually, blood cells still function (such as oxygen-carrying capacity) effectively under exposure to sunshine radiation, but the blood cell division only occurs when sunshine radiation is shielded. This is why hematopoietic function of blood cells mainly occurs in marrow! and blood cells division rate actively increases during evening as well!


Appendix 5. The Parameterization of Time-varying Electromagnetic Field for Biophysics Simulation/生物物理模拟实验中时变电磁场参数的确定方法
Method:
This section presents a novel method to determine the parameters of time-varying electromagnetic field, on the basis of ‘Skin Effect’ equations in combination with ‘Maxwell’ equations:
1.Skin effect equations:
I (t)= √2 I sin (wt); w = 2πf ;
2.Maxwell's equations:
I (t)= j H (t)
S = I (t) * H (t)
I is the effective intensity of electric field, t is the varying time, w is the angular frequency (rad/s), f is the frequency, H is the intensity of magnetic field, j is the conductivity, and S is the energy of wave (or the electromagnetic wave intensity) [1]. The determination of biophysical training method is presented for parameter f and S, in appendix 4, and the range of S is determined by appendix 2 and 3 of this chapter.
In this situation, the rhythm of electromagnetic wave in terms of intensity and frequency fluctuates around 3 times earth electromagnetic field and sunshine frequency respectively. Obviously, the intensity of I also determines the amplitude of waves. The intensity of electromagnetic waves is determined by both parameter I and
j. This is important for cells to recognize the bio-signals.

Discussion:
As discussed in this chapter, it is deduced that the biochemistry dynamics of the first three isozyme families, which show the highest variation by PCA, determines the conclusion of the whole biochemistry dynamics in this research. Consequently, three different frequencies of electromagnetic wave are applied concurrently on this biophysical training of host cells for enhancing immunology, which requires three emittors (or launchers) of electromagnetic wave to work concurrently. However, the receptors (or cells) of electromagnetic wave can NOT identify more than three different frequencies of electromagnetic wave concurrently (This is the environmental pollution of electromagnetic wave), which is similar to the limitation of three spatial dimensions in direct perception capacity of human species (The cell is not so clever to deduce the equations at more than three dimensions like me!).
In this chapter, pathogen ‘army’ behaves as camouflage, ambush, or other intelligence strategy for invasion, and host cells need to defend punctually and effectively by training for survival (host cells adjust their skills by themselves on the basis of biophysical learning during this ‘war’ until invasive enemy dies) --- this is the

evolutionary physiology of environmental adaptiveness, the foundation subject of environmental science.


Reference:
[1] 注册环保工程师专业考试复习教材(2009). 第二分册. 中国环境科学出版社. ISBN:978-7-5111-0505-9.


Appendix 6. The Synthesis of Biological Antibiotics and Its Application on Biomedicine/生物抗生素合成与在生物医药中的应用
In above appendices, the immunology of host cells becomes the key to resist the invasive pathogen. Nevertheless, there are some exceptions that the immunological potential of host cells, which relies on the synthesis of antibiotics in host cells, may not be sufficient to resist the invasive pathogen (such as congenital defect of rat species against a specific pathogen). Then the vegetation antibiotics is helpful as complementary solution. The steps of synthesis of vegetation antibiotics are similar to appendix 4.
Step 1. N×N samples of a vegetation species, which has been identified to be helpful in biomedicine, are cultivated during simulation of different electromagnetic wave conditions;
Step 2. Different frequency of electromagnetic wave (or different wavelength) are simulated, and labeled as F1, F2, ..., Fn;
Step 3. Metabolomics test is conducted individually after cultivation in F1, F2,...Fn, respectively.
Step 4. Under each simulated frequency of electromagnetic wave, different electromagnetic wave  intensity (AND amplitude) are simulated, and labeled as I1,   I2, ..., and In.
Step 5. Metabolomics test is conducted individually after cultivation in I1, I2,...In, respectively. The amount of N×N metabolomics tests are conducted in total.
Step 6. In total N×N different samples of vegetation antibiotics are abstracted from each different cultivation condition (The method of this abstraction is the same as the preparation of Traditional Chinese Medicine).
Step 7. Each sample of vegetation antibiotics is injected into the invasive simulation of pathogens targeting the host cells of rats respectively, in combination with the training of host cells discussed in chapter 8.
Step 8. The infection of host cells are observed, and the effectiveness of each sample of vegetation antibiotics is decided correspondingly.

It is expected that a combination of antibiotics from both host cells and vegetation leads to the best solution, and a combination of different vegetation antibiotics is more effective. However, the ‘dead’ antibiotics abstracted from vegetation is not as effective as ‘living’ antibiotics in host cells, due to the evolved resistance of  pathogens against the static or constant antibiotics. Actually, there are lots of cases that insect pests frequently evolve into resistance to VERY toxic pesticides, which is the same phenomenon. Please note: the abstraction of vegetation antibiotics here is on the basis of ancient preparation method of Chinese medicine, and the advantages of this is to consider all the vegetation metabolites cultivated in Lab as the whole substances for antibiotics, rather than separating a specific chemistry species from the vegetation metabolites, which can be proven by that plant resistance (or antibiotics)

substances usually contain multiple biochemistry species discussed in chapter 4. Another advantages of ancient preparation of Chinese medicine is to provide additional nutrition for host cells. During effective vegetation antibiotics condition, the invasive pathogens are usually dormant so that the competition in nutrition between host cells and pathogens is minimized. Otherwise the additional nutrition may benefit the pathogens rather than host cells.

There are three kinds of vegetation species selected in future research for better ‘diversity of antibiotics’ (If funding is available): one is the Ganoderma Lucidum (I started to grow this from 2011), another is Anoectochilus roxburghii (Wall.) Lindl.(I started to grow this from 2016. Not only human species know this, but also wild pigs must be keen to look for this vegetation for remediation after injury), and the last one is rhizome of Leguminosae species, because the symbiosis of rhizobium in Leguminosae species leads to antibiotics with higher dynamics from both vegetation cells and rhizobium cells. However, the inoculation of various rhizobium, which successfully lead to tumour in root system as symbiosis, is necessary. The reason of enriching rhizobium biodiversity has been discussed in chapter 8 (the specificity of host-invasion interaction), which results in various antibiotics from both plant cells and microbial cells.
For the shading-habitat plant species, which suits shading environment only for growth, plants' leaves usually turns to be yellow when they are long-termly exposed  to the intensitive sunshine. Inversely, the leaves of sunshine-habitat plant species turn from green into yellow when they are shaded. For the shading habitat plant such as  the Anoectochilus roxburghii (Wall.) Lindl. as well as Ganoderma Lucidum, the intensity of UV-B radiation must be reduced for the cultivation, as compared to the intensity used in other articles of this journal.

In addition to the synthesis of vegetation antibiotics for biomedicine, the inoculation of microbial vaccine in animals such us rats, pointed out in chapter 8, also provides effective way of generating antibiotics for biomedicine production against similar genetic strains. However, in this case, symbiosis between microbial vaccine and host cells is not compulsory, which means that the host cells can be ‘eaten up’ by microbial vaccine for biomedicine production. Please note: according to the Traditional Chinese Medicine, the biomedicine made from animal cells tends to be ‘warm,’ possibly due  to too much animal proteins, which need to be incorporated into vegetation biomedicines (which tends to be ‘cool’) as mixtures for best biomedicines.


This is the revised materials in book “Proceedings for Degree of Postgraduate Diploma in Environmental Science (3rd Edition).” published in 2016. Revised on 05/01/2021.
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 楼主| 发表于 2021-1-5 11:53:10 | 显示全部楼层
Article 10: Biophysical Simulation of Bio-signals and The Metabolomics /生物信号的物理模拟及新陈代谢组学
Author: Liu Huan, MSc (First Class Honours), The University of Auckland.
Published after graduation on 11/01/2016

Methods:


The same strain of microbes is divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for microbe reproduction process: one is the ‘comfortable’ condition (Sample 1); the other is under UV-B radiation for cultivation (Sample 2). The microbe samples are collected after sufficient reproduction process (Ten generations).
2.After sufficient reproduction process, the UV-B radiation simulation stops. Then both sample 1 and sample 2 are separately transferred into moisture simulation process: different moisture conditions of microbial cultivation are simulated in Lab, and labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) after moisture simulation of T1, T2, ..., Tn respectively, resulting in different zymograms as: M1, M2, ..., Mn.
4.Each isozyme family is labeled as 1, 2, 3..., and E; It is hypothesized that the bands at the same line across different isozyme families are the enzyme species at the same locus, named as enzyme ‘species i’ (i = 1, 2, ..., I), and each isozyme family has the same amount (I) of enzyme species (Please note: this is different from the identification of real enzyme species in the appendix 2 of chapter 1). Then there is a 3-dimension (I× E × N) matrix presented in this research. I is the total amount of enzyme species within a isozyme family; E is the total amount of isozyme families; N is the total amount of zymograms among different simulated moisture conditions:


X= │Xien │( i = 1, 2, ....I; e = 1, 2, .... E; n= 1, 2, ... N)
Xien is the occurrence of enzyme ‘species i’ in the isozyme ‘family e’ during simulated moisture condition Tn. The value of Xien is one or zero.
X111 X211        X112 ... X11n X212 ... X21n        X121 X221        X122 ...... X12n ......
X222 ......X22n .......        X1i1 X2i1        X1i2 X2i2        ......
.......        X1in X2in
X =        .....        .......        ......        .......        .......        ...........        .......        ......        ......        ......        .........
        Xi11        Xi12 ...        Xi1n        Xi21        Xi22        Xi2n        ........        Xie1        Xie2        ......        Xien
        .......        .......        .......        ......        ......        ......        ......        .......        .......        ......        ........


Matrix Se = Xe × (Xe)T Xe = │Xin│( i = 1, 2, ....I; n= 1, 2, ... N); (Xe)T is the transpose of the matrix Xe:

X11                X12 ... X1n X21        X22 ... X2n
Xe = ..... ....... ......

Xi1        Xi2 ...        Xin
....        .....        ......
The Principal Components Analysis (PCA) method of matrix X is specified [1]. PCA is firstly conducted on the basis of matrix Se, revealing the biochemical dynamics of a isozyme ‘family e’ among different simulated moisture conditions. In matrix Se, it is hypothesized that the variable in PCA represents the biochemistry dynamics of each enzyme ‘species i’.

S = ΣSe (e = 1, 2, E)

PCA is further conducted on the basis of matrix S, revealing the biochemical dynamics among different isozyme families over the whole simulated moisture conditions. In matrix S, it is hypothesized that the variable in PCA represents the biochemistry dynamics of each enzyme ‘species i’ across all the isozyme families.

However, for the comparison between sample 1 and sample 2, this book need to present more procedures for subsequent analysis: in matrix Se, the biochemistry

dynamics of the first three enzyme species, which reveal the most differences in the total variation by PCA in an isozyme family, are selected for comparison between sample 1 and sample 2; in matrix S, the biochemistry dynamics of the first three enzyme species, which reveal the most differences in the total variation by PCA  across all the isozyme families, are selected for comparison between sample 1 and sample 2; the sum dynamics of the first three enzyme species in a isozyme family (= the sum Variance Contribution Ratio (VCR) of the first three enzyme species  in matrix Se), represents the total variation of a isozyme family over the whole simulated moisture conditions; the sum dynamics of the first three enzyme species across all the isozyme families (= the sum Variance Contribution Ratio (VCR) of the first three enzyme species in matrix S), represents the variation of the total zymograms over the whole simulated moisture conditions.

Hypotheses:
1.The higher variation in biochemical dynamics of enzyme expression, the better environmental adaptiveness or immunology (the reason of this hypothesis is presented in chapter 7 of this book). It is deduced that the biochemistry dynamics of the first three isozyme families, which show the highest variation by PCA, determines the conclusion of this comparison;

2.Sample 2 leads to higher variation in biochemical dynamics of enzyme expression, which is also revealed by the higher adaptiveness during drought stress or higher immunology.

Discussion:
The findings of this chapter further support the theory, ‘memory’ of gene expression, proposed by other articles of this journal; As discussed by other articles of this journal, the memory of cells can be ‘trained’ by the biophysical simulation in site, indicated by the zymograms in metabolomics test. Consequently, the memory of cells, in terms of identifying the bio-signals of an environmental factor (can be biotic or abiotic) triggering the gene expression for environmental adaptiveness or immunology, can be trained by the biophysical simulation of other environmental factors. The appendix of this chapter (biophysical simulation for blood cell division) further supports above theories (please note: the theory, ‘memory’ of gene expression, is also applicable on cell division in an individual) by assessment of resistance or immunology in host cells.

This is the revised materials in book “Proceedings for Degree of Postgraduate Diploma in Environmental Science (3rd Edition).” published in 2016. Revised on 05/01/2021.


References:
[1] 陶玲,任裙 (2004)。进化生态学的数量研究方法。第一章,第六节,第 49 页。 中国林业出版社。 ISBN:7-5038-3735-7.


Appendix 1. The Experiment Procedure for Blood Cell Cultivation in Biophysical Simulation/生物物理实验中血细胞培养方法
The blood samples of a rat is abstracted and divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for cell division: one is the ‘comfortable’ condition (Sample 1); the other is under electromagnetism simulation for cell cultivation (Sample 2); the cell samples are collected after sufficient cell division (Ten generations).
2.After sufficient cell division process, the electromagnetism simulation stops. Then both sample 1 and sample 2 are separately transferred into the simulation process of physiological saline: cells are cultivated individually in different concentrations of physiological saline in Lab, and different cell environment (salinity stress of cell environment or ‘thirsty’ simulation) are labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) in cell samples after simulation process of physiological saline, T1, T2, ..., Tn, respectively, resulting in different zymograms as: M1, M2, ..., Mn.
The other procedures are the same as described above.
However, for the comprehensive assessment of immunology in host cells, the simulation process of physiological saline is replaced by the invasion simulation caused by different families of bacteria (or virus):
The blood samples of a rat is abstracted and divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for cell division: one is the ‘comfortable’ condition (Sample 1); the other is under electromagnetism simulation for cell cultivation (Sample 2); the cell samples are collected after sufficient cell division (Ten generations).
2.After sufficient cell division process, the electromagnetism simulation stops. Then both sample 1 and sample 2 are separately transferred into the simulation process of bacteria (or virus) invasion: cells are cultivated individually and independently during the simulation of different families of bacteria (or virus) in Lab, and the invasion simulation process of different bacteria (or virus) families are labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) in cell samples after simulation process  of bacteria  (or  virus) invasion, T1,  T2, ..., Tn, respectively, resulting in different zymograms as: M1, M2, ..., Mn.
The other procedures are the same as described above. This comprehensive assessment of immunology is closer to the real situation of disease caused by multiple species of bacteria, as described by the chapter 8 of this book. Even if the pathology  of host cells (such as cancerous blood cells of rat) is not caused by multiple species of invasive virus or bacteria (and by one species only), the invasive virus or bacteria of the same genetic strain also evolves into various phenotypes in host body, which reflects the significance of comprehensive assessment of immunology.

Please note: if all the blood cells have been ‘eaten’ up (or no cell division rate) by a strain of bacteria during invasion simulation, then the value of this zymogram can be counted as zero for subsequent matrix calculation.
For the comprehensive assessment of immunology in host cells caused by the invasive virus or bacteria of the same genetic strain with different phenotypes:
The blood samples of a rat is abstracted and divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for cell division: one is the ‘comfortable’ condition (Sample 1); the other is under electromagnetism simulation for cell cultivation (Sample 2); the cell samples are collected after sufficient cell division (Ten generations).
2.After sufficient cell division process, the electromagnetism simulation stops. Then both sample 1 and sample 2 are separately transferred into the simulation process of bacteria (or virus) invasion of the same genetic strain with different phenotypes: cells are cultivated individually and independently during the invasive simulation by different phenotypes of the same genetic bacteria (or virus) in Lab, and the invasion simulation process by different phenotypes of the same genetic bacteria (or virus) are labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) in cell samples after simulation process  of bacteria  (or  virus) invasion, T1,  T2, ..., Tn, respectively, resulting in different zymograms as: M1, M2, ..., Mn.
The other procedures are the same as described above. This electromagnetism simulation can be either constant electromagnetism fields or time-varying electromagnetic waves, which are further discussed later.
Conclusion:
The comprehensive assessment of immunology in host cells also provides indicators of training host cells by adjusting the parameters of biophysical simulation, once the specific zymograms, indicating the immunology against the specific invasive bacteria or virus (or the specific phenotype of an invasive pathogen), are identified by the methods presented in the appendix of chapter 8. However, the higher dynamics, the better immunology against various pathogen species (or various phenotypes of a pathogen genotype).


Appendix 2. The Determination Method of Bio-signal Range for Biophysical Simulation /生物物理模拟试验中生物信号范围的确定方法
Step 1. The host cells of the same genetic strain (such as the blood cells of rat) are abstracted, which are divided  into  several  cell  samples,  and  labeled  as  S1,  S2,  S3 ,Sn;
Step 2. The simulation of a specific virus (or bacteria) invasion targeting the host cells is conducted in Lab, immediately after host cells are abstracted from host body;
Step 3. The samples of host cells with apparent antibiotics are identified, as described by the appendix of chapter 8; and the samples of host cells without apparent antibiotics are also continuously observed until they are ‘eaten up’ by the specific invasive pathogen;
Step 4. The separation of virus from each sample of host cell without apparent antibiotics are conducted independently in Lab, and the metabolomics test is conducted in each virus sample;
Objective:
The different phenotypes of an invasive virus (or bacteria) strain are identified, and  the biochemistry dynamics of this invasive virus strain is calculated, as discussed in this chapter. The result of biochemistry dynamics calculation helps to determine the range of bio-physical training parameters to enhance the comprehensive immunology of host cells, as described above.
Please note: the simulation of a specific virus (or bacteria) invasion targeting the host cells should be conducted immediately after host cells are abstracted from host body, otherwise the uniform cell cultivation in Lab lead to the homogeneity of host cells, so that different phenotypes of an invasive pathogen can be hardly detected.
Because the virus sample for invasion simulation is cultivated in Lab, which is the uniform phenotype, the samples of host cells with apparent antibiotics usually show specific zymograms correspondingly to the specific invasive virus. However, if virus samples, which are separated from host cell without apparent antibiotics after step 3, re-invade the host cells with apparent antibiotics identified in step 3, virus infection would occur, due to the evolution of new virus phenotypes.


Appendix 3. Bio-magnetic field of Cell and Its Application on Separation of Blood Cell Communities along Environmental
Gradient/细胞的生物磁场及血细胞群落在环境梯度上的分离

Step 1. The host cells (such as blood cells of rat) are abstracted from host body. Step 2. Electrophoresis of blood cells is conducted in moderate electromagnetism;
Step 3. Different blood cell communities are separated along the environmental gradient of electromagnetism signal, leading to cell samples with different immunology.
Discussion
The bio-magnetic field of blood cells varies even within the same genetic strain, so that different cell communities can be separated according to the gradual variation in electromagnetism signals (environmental gradient of electromagnetism) in this electrophoresis, leading to cell samples with different immunology. The cell samples, abstracted from different electric potential (j1, j2...jn), are labeled on the basis of electric potential.
Step 4. The specificity of host-invasion interaction is examined on each cell sample, according to the appendix of chapter 8 in this book. It is expected that the specific electric potential corresponds to the host cells with apparent antibiotics against the specific invasive virus (or bacteria), which also becomes the key parameter of biophysical training for the host cells with immunology against the specific invasive virus (or bacteria). Nevertheless, for the mobilizable blood cells, it is expected that the 'ecological niche' of cells vary in their life cycle along this environmental gradient of electromagnetism signal, because of the variation in bio-magnetic field over cell's life cycle, moving from a specific electric potential to another electric potential.
It is expected that the time-varying electromagnetic field of biophysical training is better than constant electromagnetic field, due to the phenotype evolution of invasive virus (bacteria).
Please note: the intensity of electromagnetism is preliminarily set to be 1.6 H (1H = 1 A/m) in this research, three times than earth magnetism fields. If the intensity of electromagnetism is more than 5 times than earth magnetism fields, blood cell  division rate of rats starts to decline apparently, ‘looking nervous,’ which is closer to the situation of ‘hemorrhage.’ They are unlike microbes who can survive long-termly in sunshine intensity.


Appendix 4. Bio-signal Simulation of Electromagnetic Wave and Its Specificity on the Isozyme Expression/电磁波的生物信号模拟及同工酶表达的专一性
In appendix 3, the specificity of electric potential to the host cells with apparent antibiotics against the specific invasive virus (or bacteria) is determined. However, this method is relatively broader, so that the accuracy of this biophysical training is not sufficient for the synthesis of antibiotics in cells against the specific phenotype of an invasive virus (or bacteria).
Consequently, this section presents a novel methods to train the specific isozyme families catalyzing the synthesis of antibiotics in cells against the specific phenotype of an invasive virus (or bacteria):
Step 1. Host cells (such as blood cells) are cultivated during simulation of electromagnetic wave conditions;
Step 2. Different frequency of electromagnetic wave (or different wavelength) are simulated, and labeled as F1, F2, ..., Fn;
Step 3. Metabolomics test is conducted individually after cultivation in F1, F2,...Fn, respectively.
Step 4. Under each simulated frequency of electromagnetic wave, different electromagnetic wave intensity are simulated, and labeled as I1, I2, ..., and In.
Step 5. Metabolomics test is conducted individually after cultivation in I1, I2,...In, respectively. The amount of N×N metabolomics tests are conducted in total.
Objectives:
The specific frequency of electromagnetic wave simulates the bio-signal regulating gene expression as a specific isozyme family, and the specific electromagnetic wave intensity (AND amplitude) corresponds to the bio-signal regulating gene expression as a specific enzyme species within an isozyme family, which can be determined by metabolomics tests. Consequently, the immunology against the specific phenotype of an invasive virus (or bacteria) can be trained according to the zymograms, described  in the appendix of chapter 8. Please note: the intensity is adjusted and controlled by the amplitude instructed in appendix 5.

This experiment is similar to chapter 4 (UV-B is one of electromagnetic waves). Let’s re-discuss the chapter 4 on the basis of plant cell data (the blood cell data of rat is not clear to this date 18/02/2016): As discussed in chapter 4, UV-B significantly (P<0.001) affected the net photosynthesis (A) (Table 1). Nevertheless, for Tienshan clover and Caucasian clover, there was no significant UV-B induced difference in the total aerial biomass yield, under well-water conditions, and there was no significant effect of UV-B on the relative chlorophyll content, whereas enhanced UV-B apparently decreased the biomass of Kopu II. Further more, the water deficit did not influence   the relative chlorophyll content as comparison to the well-water condition (Table 1).

There are two reasons to explain this science discovery: firstly, the Light Use Efficiency (LUE) already exceeded the saturation point of LUE under well water condition without enhanced UB treatment (as discussed in other articles of journal), so that the reduction of net photosynthesis under enhanced UB treatment did not influence the total aerial biomass yield; Secondly, enhanced UV-B treatment effectively triggered the gene expression of enzyme species within the isozyme families involving in the chlorophyll synthesis in plant cells, which revealed that the isozyme families involving in the chlorophyll synthesis could express effectively under a broader range of UV-B intensity especially for Caucasian clover, but the relevant gene of Kopu II was not effectively expressed as enzyme species within the isozyme families involving in the chlorophyll synthesis under enhanced UV-B. Please note: within the isozyme families involving in the chlorophyll synthesis in plant cells, the enzyme species under enhanced UV-B is different from the one without enhanced UV-B. However, drought condition did not influence the synthesis of chlorophyll, which showed different metabolic pathway in response to the environmental stress. The treatment without UV-B in this experiment was not without any UV-B radiation, and was just lower intensity of UV-B treatment. Although chapter 4 explains that ‘these results indicated that these clovers might have adequately photo-protective mechanism, such as enhancing the synthesis of UV-B screening  secondary metabolites (Hofmann et al., 2003a),’ this explanation is consistent with the above explanation in this section, because the synthesis of UV-B screening secondary metabolites as photo-protective mechanism is also the phenomenon utilizing the light energy effectively, adjusting the photo-metabolic pathways in response to the change of UV-B intensity (UV-B is also the utilizable light energy in photosynthesis rather than visible light only, which can be proven the result that Caucasian clover showed increased biomass during enhanced UV-B of well water treatment as compared to the well water condition without UV-B, although the main utilizable energy is from the visible light --- without visible light, photosynthesis can not only rely on UV-B to happen --- this is the conclusion of this book). As discussed in appendix 5, the receptors (or cells) of electromagnetic wave can NOT identify more than three different frequencies of electromagnetic wave concurrently, it is hypothesized that plant cells themselves select three frequencies of light waves with the highest  intensity for photosynthesis, and Caucasian clover selects UV-B frequency for photosynthesis whereas Kopu II can not, this is definitely the environmental adaptiveness evolved from its origin.

Please note: for the identification of specific zymograms of host cells with specific immunology against invasive gene mutation virus in chapter 8, then invasive simulation of gene mutation virus is added during the whole process of biophysics simulation for identifying the specificity of host-invasion interaction (in which frequency and intensity of cultivation condition, the host cells show effective immunology against the gene mutation virus).

Nevertheless, for the virus (or bacteria) with dormant characters (such as HIV), it is expected that long-term observation is required for this specificity examination after
biophysics simulation stops, because this virus would become dormant in host cells after puncturing cell membrane during biophysics simulation, so that the host cells with effective immunology against the dormant virus are NOT specifically identified during biophysical simulation. In this case, the host cells with really effective immunology against the dormant virus kill the invasive virus during biophysical simulation, whereas the host cells with dormant virus would be re-infected after biophysical simulation stops. After long-termly observing if dormant virus re-starts pathogenetic metabolism in host cells, the identified host cells with really effective immunology against the dormant virus would be screened and become more specific. Finally the range of biophysics parameters in appendix 5 should be based on all the host cell samples which have been identified as effective immunology against the dormant virus during biophysics simulation. The more specific, the more punctual to kill the invasive virus.

Please note: the intensity of electromagnetic waves is preliminarily set to be 1.6 H  (1H = 1 A/m) for blood cells in this research, three times than earth magnetism fields. If the intensity of electromagnetism is more than 5 times than earth magnetism fields, blood cell division rate of rats starts to decline apparently, ‘looking nervous.’ They are unlike microbes who can survive long-termly in sunshine intensity. However, the frequency of electromagnetic waves is preliminarily set to be around UV-B frequency, the sunshine one. Actually, blood cells still function (such as oxygen-carrying capacity) effectively under exposure to sunshine radiation, but the blood cell division only occurs when sunshine radiation is shielded. This is why hematopoietic function of blood cells mainly occurs in marrow! and blood cells division rate actively increases during evening as well!


Appendix 5. The Parameterization of Time-varying Electromagnetic Field for Biophysics Simulation/生物物理模拟实验中时变电磁场参数的确定方法
Method:
This section presents a novel method to determine the parameters of time-varying electromagnetic field, on the basis of ‘Skin Effect’ equations in combination with ‘Maxwell’ equations:
1.Skin effect equations:
I (t)= √2 I sin (wt); w = 2πf ;
2.Maxwell's equations:
I (t)= j H (t)
S = I (t) * H (t)
I is the effective intensity of electric field, t is the varying time, w is the angular frequency (rad/s), f is the frequency, H is the intensity of magnetic field, j is the conductivity, and S is the energy of wave (or the electromagnetic wave intensity) [1]. The determination of biophysical training method is presented for parameter f and S, in appendix 4, and the range of S is determined by appendix 2 and 3 of this chapter.
In this situation, the rhythm of electromagnetic wave in terms of intensity and frequency fluctuates around 3 times earth electromagnetic field and sunshine frequency respectively. Obviously, the intensity of I also determines the amplitude of waves. The intensity of electromagnetic waves is determined by both parameter I and
j. This is important for cells to recognize the bio-signals.

Discussion:
As discussed in this chapter, it is deduced that the biochemistry dynamics of the first three isozyme families, which show the highest variation by PCA, determines the conclusion of the whole biochemistry dynamics in this research. Consequently, three different frequencies of electromagnetic wave are applied concurrently on this biophysical training of host cells for enhancing immunology, which requires three emittors (or launchers) of electromagnetic wave to work concurrently. However, the receptors (or cells) of electromagnetic wave can NOT identify more than three different frequencies of electromagnetic wave concurrently (This is the environmental pollution of electromagnetic wave), which is similar to the limitation of three spatial dimensions in direct perception capacity of human species (The cell is not so clever to deduce the equations at more than three dimensions like me!).
In this chapter, pathogen ‘army’ behaves as camouflage, ambush, or other intelligence strategy for invasion, and host cells need to defend punctually and effectively by training for survival (host cells adjust their skills by themselves on the basis of biophysical learning during this ‘war’ until invasive enemy dies) --- this is the evolutionary physiology of environmental adaptiveness, the foundation subject of environmental science.


Reference:
[1] 注册环保工程师专业考试复习教材(2009). 第二分册. 中国环境科学出版社. ISBN:978-7-5111-0505-9.


Appendix 6. The Synthesis of Biological Antibiotics and Its Application on Bio-medicine/生物抗生素合成与在生物医药中的应用
In above appendices, the immunology of host cells becomes the key to resist the invasive pathogen. Nevertheless, there are some exceptions that the immunological potential of host cells, which relies on the synthesis of antibiotics in host cells, may not be sufficient to resist the invasive pathogen (such as congenital defect of rat species against a specific pathogen). Then the vegetation antibiotics is helpful as complementary solution. The steps of synthesis of vegetation antibiotics are similar to appendix 4.
Step 1. N×N samples of a vegetation species, which has been identified to be helpful in biomedicine, are cultivated during simulation of different electromagnetic wave conditions;
Step 2. Different frequency of electromagnetic wave (or different wavelength) are simulated, and labeled as F1, F2, ..., Fn;
Step 3. Metabolomics test is conducted individually after cultivation in F1, F2,...Fn, respectively.
Step 4. Under each simulated frequency of electromagnetic wave, different electromagnetic wave  intensity (AND amplitude) are simulated, and labeled as I1,   I2, ..., and In.
Step 5. Metabolomics test is conducted individually after cultivation in I1, I2,...In, respectively. The amount of N×N metabolomics tests are conducted in total.
Step 6. In total N×N different samples of vegetation antibiotics are abstracted from each different cultivation condition (The method of this abstraction is the same as the preparation of Traditional Chinese Medicine).
Step 7. Each sample of vegetation antibiotics is injected into the invasive simulation of pathogens targeting the host cells of rats respectively, in combination with the training of host cells discussed in chapter 8.
Step 8. The infection of host cells are observed, and the effectiveness of each sample of vegetation antibiotics is decided correspondingly.

It is expected that a combination of antibiotics from both host cells and vegetation leads to the best solution, and a combination of different vegetation antibiotics is more effective. However, the ‘dead’ antibiotics abstracted from vegetation is not as effective as ‘living’ antibiotics in host cells, due to the evolved resistance of  pathogens against the static or constant antibiotics. Actually, there are lots of cases that insect pests frequently evolve into resistance to VERY toxic pesticides, which is the same phenomenon. Please note: the abstraction of vegetation antibiotics here is on the basis of ancient preparation method of Chinese medicine, and the advantages of this is to consider all the vegetation metabolites cultivated in Lab as the whole substances for antibiotics, rather than separating a specific chemistry species from the vegetation metabolites, which can be proven by that plant resistance (or antibiotics) substances usually contain multiple biochemistry species discussed in chapter 4. Another advantages of ancient preparation of Chinese medicine is to provide additional nutrition for host cells. During effective vegetation antibiotics condition, the invasive pathogens are usually dormant so that the competition in nutrition between host cells and pathogens is minimized. Otherwise the additional nutrition may benefit the pathogens rather than host cells.

There are three kinds of vegetation species selected in future research for better ‘diversity of antibiotics’ (If funding is available): one is the Ganoderma Lucidum (I started to grow this from 2011), another is Anoectochilus roxburghii (Wall.) Lindl.(I started to grow this from 2016. Not only human species know this, but also wild pigs must be keen to look for this vegetation for remediation after injury), and the last one is rhizome of Leguminosae species, because the symbiosis of rhizobium in Leguminosae species leads to antibiotics with higher dynamics from both vegetation cells and rhizobium cells. However, the inoculation of various rhizobium, which successfully lead to tumour in root system as symbiosis, is necessary. The reason of enriching rhizobium biodiversity has been discussed in chapter 8 (the specificity of host-invasion interaction), which results in various antibiotics from both plant cells and microbial cells.

For the shading-habitat plant species, which suits shading environment only for growth, plants' leaves usually turns to be yellow when they are long-termly exposed  to the intensitive sunshine. Inversely, the leaves of sunshine-habitat plant species turn from green into yellow when they are shaded. For the shading habitat plant such as  the Anoectochilus roxburghii (Wall.) Lindl. as well as Ganoderma Lucidum, the intensity of UV-B radiation must be reduced for the cultivation, as compared to the intensity used in other articles of this journal.

In addition to the synthesis of vegetation antibiotics for biomedicine, the inoculation of microbial vaccine in animals such us rats, pointed out in chapter 8, also provides effective way of generating antibiotics for biomedicine production against similar genetic strains. However, in this case, symbiosis between microbial vaccine and host cells is not compulsory, which means that the host cells can be ‘eaten up’ by microbial vaccine for biomedicine production. Please note: according to the Traditional Chinese Medicine, the biomedicine made from animal cells tends to be ‘warm,’ possibly due  to too much animal proteins, which need to be incorporated into vegetation biomedicines (which tends to be ‘cool’) as mixtures for best biomedicines.


This is the revised materials in book “Proceedings for Degree of Postgraduate Diploma in Environmental Science (3rd Edition).” published in 2016. Revised on 05/01/2021.

References:
All the science terms in English of this journal source from Wikipedia:
https://encyclopedia.thefreedictionary.com/;
本文所有中文科学专业术语引用自百度百科 https://baike.baidu.com/
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 楼主| 发表于 2021-1-5 15:26:18 | 显示全部楼层
Article 10: Biophysical Simulation of Bio-signals and The Metabolomics /生物信号的物理模拟及新陈代谢组学

Author: Liu Huan, MSc (First Class Honours), The University of Auckland.
Published after graduation on 11/01/2016

Methods:

The same strain of microbes is divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for microbe reproduction process: one is the ‘comfortable’ condition (Sample 1); the other is under UV-B radiation for cultivation (Sample 2). The microbe samples are collected after sufficient reproduction process (Ten generations).
2.After sufficient reproduction process, the UV-B radiation simulation stops. Then both sample 1 and sample 2 are separately transferred into moisture simulation process: different moisture conditions of microbial cultivation are simulated in Lab, and labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) after moisture simulation of T1, T2, ..., Tn respectively, resulting in different zymograms as: M1, M2, ..., Mn.
4.Each isozyme family is labeled as 1, 2, 3..., and E; It is hypothesized that the bands at the same line across different isozyme families are the enzyme species at the same locus, named as enzyme ‘species i’ (i = 1, 2, ..., I), and each isozyme family has the same amount (I) of enzyme species (Please note: this is different from the identification of real enzyme species in the appendix 2 of chapter 1). Then there is a 3-dimension (I× E × N) matrix presented in this research. I is the total amount of enzyme species within a isozyme family; E is the total amount of isozyme families; N is the total amount of zymograms among different simulated moisture conditions:


X= │Xien │( i = 1, 2, ....I; e = 1, 2, .... E; n= 1, 2, ... N) (See PDF Version)
Xien is the occurrence of enzyme ‘species i’ in the isozyme ‘family e’ during simulated moisture condition Tn. The value of Xien is one or zero.
X111 X211        X112 ... X11n X212 ... X21n        X121 X221        X122 ...... X12n ......
X222 ......X22n .......        X1i1 X2i1        X1i2 X2i2        ......
.......        X1in X2in
X =        .....        .......        ......        .......        .......        ...........        .......        ......        ......        ......        .........
        Xi11        Xi12 ...        Xi1n        Xi21        Xi22        Xi2n        ........        Xie1        Xie2        ......        Xien
        .......        .......        .......        ......        ......        ......        ......        .......        .......        ......        ........


Matrix Se = Xe × (Xe)T Xe = │Xin│( i = 1, 2, ....I; n= 1, 2, ... N); (Xe)T is the transpose of the matrix Xe:

X11                X12 ... X1n X21        X22 ... X2n
Xe = ..... ....... ......

Xi1        Xi2 ...        Xin
....        .....        ......
The Principal Components Analysis (PCA) method of matrix X is specified [1]. PCA is firstly conducted on the basis of matrix Se, revealing the biochemical dynamics of a isozyme ‘family e’ among different simulated moisture conditions. In matrix Se, it is hypothesized that the variable in PCA represents the biochemistry dynamics of each enzyme ‘species i’.

S = ΣSe (e = 1, 2, E)

PCA is further conducted on the basis of matrix S, revealing the biochemical dynamics among different isozyme families over the whole simulated moisture conditions. In matrix S, it is hypothesized that the variable in PCA represents the biochemistry dynamics of each enzyme ‘species i’ across all the isozyme families.

However, for the comparison between sample 1 and sample 2, this book need to present more procedures for subsequent analysis: in matrix Se, the biochemistry

dynamics of the first three enzyme species, which reveal the most differences in the total variation by PCA in an isozyme family, are selected for comparison between sample 1 and sample 2; in matrix S, the biochemistry dynamics of the first three enzyme species, which reveal the most differences in the total variation by PCA  across all the isozyme families, are selected for comparison between sample 1 and sample 2; the sum dynamics of the first three enzyme species in a isozyme family (= the sum Variance Contribution Ratio (VCR) of the first three enzyme species  in matrix Se), represents the total variation of a isozyme family over the whole simulated moisture conditions; the sum dynamics of the first three enzyme species across all the isozyme families (= the sum Variance Contribution Ratio (VCR) of the first three enzyme species in matrix S), represents the variation of the total zymograms over the whole simulated moisture conditions.

Hypotheses:
1.The higher variation in biochemical dynamics of enzyme expression, the better environmental adaptiveness or immunology (the reason of this hypothesis is presented in chapter 7 of this book). It is deduced that the biochemistry dynamics of the first three isozyme families, which show the highest variation by PCA, determines the conclusion of this comparison;

2.Sample 2 leads to higher variation in biochemical dynamics of enzyme expression, which is also revealed by the higher adaptiveness during drought stress or higher immunology.

Discussion:
The findings of this chapter further support the theory, ‘memory’ of gene expression, proposed by other articles of this journal; As discussed by other articles of this journal, the memory of cells can be ‘trained’ by the biophysical simulation in site, indicated by the zymograms in metabolomics test. Consequently, the memory of cells, in terms of identifying the bio-signals of an environmental factor (can be biotic or abiotic) triggering the gene expression for environmental adaptiveness or immunology, can be trained by the biophysical simulation of other environmental factors. The appendix of this chapter (biophysical simulation for blood cell division) further supports above theories (please note: the theory, ‘memory’ of gene expression, is also applicable on cell division in an individual) by assessment of resistance or immunology in host cells.














This is the revised materials in book “Proceedings for Degree of Postgraduate Diploma in Environmental Science (3rd Edition).” Published in 2016. The ‘chapter’ content mentioned
in this article is in previous book. Revised on 05/01/2021.







References:
[1] 陶玲,任裙 (2004)。进化生态学的数量研究方法。第一章,第六节,第 49 页。 中国林业出版社。 ISBN:7-5038-3735-7.

Appendix 1. The Experiment Procedure for Blood Cell Cultivation in Biophysical Simulation/生物物理实验中血细胞培养方法
The blood samples of a rat is abstracted and divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for cell division: one is the ‘comfortable’ condition (Sample 1); the other is under electromagnetism simulation for cell cultivation (Sample 2); the cell samples are collected after sufficient cell division (Ten generations).
2.After sufficient cell division process, the electromagnetism simulation stops. Then both sample 1 and sample 2 are separately transferred into the simulation process of physiological saline: cells are cultivated individually in different concentrations of physiological saline in Lab, and different cell environment (salinity stress of cell environment or ‘thirsty’ simulation) are labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) in cell samples after simulation process of physiological saline, T1, T2, ..., Tn, respectively, resulting in different zymograms as: M1, M2, ..., Mn.
The other procedures are the same as described above.
However, for the comprehensive assessment of immunology in host cells, the simulation process of physiological saline is replaced by the invasion simulation caused by different families of bacteria (or virus):
The blood samples of a rat is abstracted and divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for cell division: one is the ‘comfortable’ condition (Sample 1); the other is under electromagnetism simulation for cell cultivation (Sample 2); the cell samples are collected after sufficient cell division (Ten generations).
2.After sufficient cell division process, the electromagnetism simulation stops. Then both sample 1 and sample 2 are separately transferred into the simulation process of bacteria (or virus) invasion: cells are cultivated individually and independently during the simulation of different families of bacteria (or virus) in Lab, and the invasion simulation process of different bacteria (or virus) families are labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) in cell samples after simulation process  of bacteria  (or  virus) invasion, T1,  T2, ..., Tn, respectively, resulting in different zymograms as: M1, M2, ..., Mn.
The other procedures are the same as described above. This comprehensive assessment of immunology is closer to the real situation of disease caused by multiple species of bacteria, as described by the chapter 8 of this book. Even if the pathology  of host cells (such as cancerous blood cells of rat) is not caused by multiple species of invasive virus or bacteria (and by one species only), the invasive virus or bacteria of the same genetic strain also evolves into various phenotypes in host body, which reflects the significance of comprehensive assessment of immunology.

Please note: if all the blood cells have been ‘eaten’ up (or no cell division rate) by a strain of bacteria during invasion simulation, then the value of this zymogram can be counted as zero for subsequent matrix calculation.
For the comprehensive assessment of immunology in host cells caused by the invasive virus or bacteria of the same genetic strain with different phenotypes:
The blood samples of a rat is abstracted and divided into two samples for the bio-signal simulation:
1.There are two kinds of cultivation conditions simulated in Lab for cell division: one is the ‘comfortable’ condition (Sample 1); the other is under electromagnetism simulation for cell cultivation (Sample 2); the cell samples are collected after sufficient cell division (Ten generations).
2.After sufficient cell division process, the electromagnetism simulation stops. Then both sample 1 and sample 2 are separately transferred into the simulation process of bacteria (or virus) invasion of the same genetic strain with different phenotypes: cells are cultivated individually and independently during the invasive simulation by different phenotypes of the same genetic bacteria (or virus) in Lab, and the invasion simulation process by different phenotypes of the same genetic bacteria (or virus) are labeled as T1, T2, ..., Tn.
3.Metabolomics tests are conducted (listed by the appendix 2 in Chapter 1 of this book) in cell samples after simulation process  of bacteria  (or  virus) invasion, T1,  T2, ..., Tn, respectively, resulting in different zymograms as: M1, M2, ..., Mn.
The other procedures are the same as described above. This electromagnetism simulation can be either constant electromagnetism fields or time-varying electromagnetic waves, which are further discussed later.
Conclusion:
The comprehensive assessment of immunology in host cells also provides indicators of training host cells by adjusting the parameters of biophysical simulation, once the specific zymograms, indicating the immunology against the specific invasive bacteria or virus (or the specific phenotype of an invasive pathogen), are identified by the methods presented in the appendix of chapter 8. However, the higher dynamics, the better immunology against various pathogen species (or various phenotypes of a pathogen genotype).


Appendix 2. The Determination Method of Bio-signal Range for Biophysical Simulation /生物物理模拟试验中生物信号范围的确定方法
Step 1. The host cells of the same genetic strain (such as the blood cells of rat) are abstracted, which are divided  into  several  cell  samples,  and  labeled  as  S1,  S2,  S3 ,Sn;
Step 2. The simulation of a specific virus (or bacteria) invasion targeting the host cells is conducted in Lab, immediately after host cells are abstracted from host body;
Step 3. The samples of host cells with apparent antibiotics are identified, as described by the appendix of chapter 8; and the samples of host cells without apparent antibiotics are also continuously observed until they are ‘eaten up’ by the specific invasive pathogen;
Step 4. The separation of virus from each sample of host cell without apparent antibiotics are conducted independently in Lab, and the metabolomics test is conducted in each virus sample;
Objective:
The different phenotypes of an invasive virus (or bacteria) strain are identified, and  the biochemistry dynamics of this invasive virus strain is calculated, as discussed in this chapter. The result of biochemistry dynamics calculation helps to determine the range of bio-physical training parameters to enhance the comprehensive immunology of host cells, as described above.
Please note: the simulation of a specific virus (or bacteria) invasion targeting the host cells should be conducted immediately after host cells are abstracted from host body, otherwise the uniform cell cultivation in Lab lead to the homogeneity of host cells, so that different phenotypes of an invasive pathogen can be hardly detected.
Because the virus sample for invasion simulation is cultivated in Lab, which is the uniform phenotype, the samples of host cells with apparent antibiotics usually show specific zymograms correspondingly to the specific invasive virus. However, if virus samples, which are separated from host cell without apparent antibiotics after step 3, re-invade the host cells with apparent antibiotics identified in step 3, virus infection would occur, due to the evolution of new virus phenotypes.


Appendix 3. Bio-magnetic field of Cell and Its Application on Separation of Blood Cell Communities along Environmental
Gradient/细胞的生物磁场及血细胞群落在环境梯度上的分离

Step 1. The host cells (such as blood cells of rat) are abstracted from host body. Step 2. Electrophoresis of blood cells is conducted in moderate electromagnetism;
Step 3. Different blood cell communities are separated along the environmental gradient of electromagnetism signal, leading to cell samples with different immunology.

Discussion
The bio-magnetic field of blood cells varies even within the same genetic strain, so that different cell communities can be separated according to the gradual variation in electromagnetism signals (environmental gradient of electromagnetism) in this electrophoresis, leading to cell samples with different immunology. The cell samples, abstracted from different electric potential (j1, j2...jn), are labeled on the basis of electric potential.

Step 4. The specificity of host-invasion interaction is examined on each cell sample, according to the appendix of chapter 8 in this book. It is expected that the specific electric potential corresponds to the host cells with apparent antibiotics against the specific invasive virus (or bacteria), which also becomes the key parameter of biophysical training for the host cells with immunology against the specific invasive virus (or bacteria). Nevertheless, for the mobilizable blood cells, it is expected that the 'ecological niche' of cells vary in their life cycle along this environmental gradient of electromagnetism signal, because of the variation in bio-magnetic field over cell's life cycle, moving from a specific electric potential to another electric potential.
It is expected that the time-varying electromagnetic field of biophysical training is better than constant electromagnetic field, due to the phenotype evolution of invasive virus (bacteria).
Please note: the intensity of electromagnetism is preliminarily set to be 1.6 H (1H = 1 A/m) in this research, three times than earth magnetism fields. If the intensity of electromagnetism is more than 5 times than earth magnetism fields, blood cell  division rate of rats starts to decline apparently, ‘looking nervous,’ which is closer to the situation of ‘hemorrhage.’ They are unlike microbes who can survive long-termly in sunshine intensity.


Appendix 4. Bio-signal Simulation of Electromagnetic Wave and Its Specificity on the Isozyme Expression/电磁波的生物信号模拟及同工酶表达的专一性
In appendix 3, the specificity of electric potential to the host cells with apparent antibiotics against the specific invasive virus (or bacteria) is determined. However, this method is relatively broader, so that the accuracy of this biophysical training is not sufficient for the synthesis of antibiotics in cells against the specific phenotype of an invasive virus (or bacteria).
Consequently, this section presents a novel methods to train the specific isozyme families catalyzing the synthesis of antibiotics in cells against the specific phenotype of an invasive virus (or bacteria):
Step 1. Host cells (such as blood cells) are cultivated during simulation of electromagnetic wave conditions;
Step 2. Different frequency of electromagnetic wave (or different wavelength) are simulated, and labeled as F1, F2, ..., Fn;
Step 3. Metabolomics test is conducted individually after cultivation in F1, F2,...Fn, respectively.
Step 4. Under each simulated frequency of electromagnetic wave, different electromagnetic wave intensity are simulated, and labeled as I1, I2, ..., and In.
Step 5. Metabolomics test is conducted individually after cultivation in I1, I2,...In, respectively. The amount of N×N metabolomics tests are conducted in total.
Objectives:
The specific frequency of electromagnetic wave simulates the bio-signal regulating gene expression as a specific isozyme family, and the specific electromagnetic wave intensity (AND amplitude) corresponds to the bio-signal regulating gene expression as a specific enzyme species within an isozyme family, which can be determined by metabolomics tests. Consequently, the immunology against the specific phenotype of an invasive virus (or bacteria) can be trained according to the zymograms, described  in the appendix of chapter 8. Please note: the intensity is adjusted and controlled by the amplitude instructed in appendix 5.

This experiment is similar to chapter 4 (UV-B is one of electromagnetic waves). Let’s re-discuss the chapter 4 on the basis of plant cell data (the blood cell data of rat is not clear to this date 18/02/2016): As discussed in chapter 4, UV-B significantly (P<0.001) affected the net photosynthesis (A) (Table 1). Nevertheless, for Tienshan clover and Caucasian clover, there was no significant UV-B induced difference in the total aerial biomass yield, under well-water conditions, and there was no significant effect of UV-B on the relative chlorophyll content, whereas enhanced UV-B apparently decreased the biomass of Kopu II. Further more, the water deficit did not influence   the relative chlorophyll content as comparison to the well-water condition (Table 1).

There are two reasons to explain this science discovery: firstly, the Light Use Efficiency (LUE) already exceeded the saturation point of LUE under well water condition without enhanced UB treatment (as discussed in other articles of journal), so that the reduction of net photosynthesis under enhanced UB treatment did not influence the total aerial biomass yield; Secondly, enhanced UV-B treatment effectively triggered the gene expression of enzyme species within the isozyme families involving in the chlorophyll synthesis in plant cells, which revealed that the isozyme families involving in the chlorophyll synthesis could express effectively under a broader range of UV-B intensity especially for Caucasian clover, but the relevant gene of Kopu II was not effectively expressed as enzyme species within the isozyme families involving in the chlorophyll synthesis under enhanced UV-B. Please note: within the isozyme families involving in the chlorophyll synthesis in plant cells, the enzyme species under enhanced UV-B is different from the one without enhanced UV-B. However, drought condition did not influence the synthesis of chlorophyll, which showed different metabolic pathway in response to the environmental stress. The treatment without UV-B in this experiment was not without any UV-B radiation, and was just lower intensity of UV-B treatment. Although chapter 4 explains that ‘these results indicated that these clovers might have adequately photo-protective mechanism, such as enhancing the synthesis of UV-B screening  secondary metabolites (Hofmann et al., 2003a),’ this explanation is consistent with the above explanation in this section, because the synthesis of UV-B screening secondary metabolites as photo-protective mechanism is also the phenomenon utilizing the light energy effectively, adjusting the photo-metabolic pathways in response to the change of UV-B intensity (UV-B is also the utilizable light energy in photosynthesis rather than visible light only, which can be proven the result that Caucasian clover showed increased biomass during enhanced UV-B of well water treatment as compared to the well water condition without UV-B, although the main utilizable energy is from the visible light --- without visible light, photosynthesis can not only rely on UV-B to happen --- this is the conclusion of this book). As discussed in appendix 5, the receptors (or cells) of electromagnetic wave can NOT identify more than three different frequencies of electromagnetic wave concurrently, it is hypothesized that plant cells themselves select three frequencies of light waves with the highest  intensity for photosynthesis, and Caucasian clover selects UV-B frequency for photosynthesis whereas Kopu II can not, this is definitely the environmental adaptiveness evolved from its origin.

Please note: for the identification of specific zymograms of host cells with specific immunology against invasive gene mutation virus in chapter 8, then invasive simulation of gene mutation virus is added during the whole process of biophysics simulation for identifying the specificity of host-invasion interaction (in which frequency and intensity of cultivation condition, the host cells show effective immunology against the gene mutation virus).

Nevertheless, for the virus (or bacteria) with dormant characters (such as HIV), it is expected that long-term observation is required for this specificity examination after

biophysics simulation stops, because this virus would become dormant in host cells after puncturing cell membrane during biophysics simulation, so that the host cells with effective immunology against the dormant virus are NOT specifically identified during biophysical simulation. In this case, the host cells with really effective immunology against the dormant virus kill the invasive virus during biophysical simulation, whereas the host cells with dormant virus would be re-infected after biophysical simulation stops. After long-termly observing if dormant virus re-starts pathogenetic metabolism in host cells, the identified host cells with really effective immunology against the dormant virus would be screened and become more specific. Finally the range of biophysics parameters in appendix 5 should be based on all the host cell samples which have been identified as effective immunology against the dormant virus during biophysics simulation. The more specific, the more punctual to kill the invasive virus.

Please note: the intensity of electromagnetic waves is preliminarily set to be 1.6 H  (1H = 1 A/m) for blood cells in this research, three times than earth magnetism fields. If the intensity of electromagnetism is more than 5 times than earth magnetism fields, blood cell division rate of rats starts to decline apparently, ‘looking nervous.’ They are unlike microbes who can survive long-termly in sunshine intensity. However, the frequency of electromagnetic waves is preliminarily set to be around UV-B frequency, the sunshine one. Actually, blood cells still function (such as oxygen-carrying capacity) effectively under exposure to sunshine radiation, but the blood cell division only occurs when sunshine radiation is shielded. This is why hematopoietic function of blood cells mainly occurs in marrow! and blood cells division rate actively increases during evening as well!


Appendix 5. The Parameterization of Time-varying Electromagnetic Field for Biophysics Simulation/生物物理模拟实验中时变电磁场参数的确定方法
Method:
This section presents a novel method to determine the parameters of time-varying electromagnetic field, on the basis of ‘Skin Effect’ equations in combination with ‘Maxwell’ equations:
1.Skin effect equations:
I (t)= √2 I sin (wt); w = 2πf ;
2.Maxwell's equations:
I (t)= j H (t)
S = I (t) * H (t)
I is the effective intensity of electric field, t is the varying time, w is the angular frequency (rad/s), f is the frequency, H is the intensity of magnetic field, j is the conductivity, and S is the energy of wave (or the electromagnetic wave intensity) [1]. The determination of biophysical training method is presented for parameter f and S, in appendix 4, and the range of S is determined by appendix 2 and 3 of this chapter.
In this situation, the rhythm of electromagnetic wave in terms of intensity and frequency fluctuates around 3 times earth electromagnetic field and sunshine frequency respectively. Obviously, the intensity of I also determines the amplitude of waves. The intensity of electromagnetic waves is determined by both parameter I and
j. This is important for cells to recognize the bio-signals.

Discussion:
As discussed in this chapter, it is deduced that the biochemistry dynamics of the first three isozyme families, which show the highest variation by PCA, determines the conclusion of the whole biochemistry dynamics in this research. Consequently, three different frequencies of electromagnetic wave are applied concurrently on this biophysical training of host cells for enhancing immunology, which requires three emittors (or launchers) of electromagnetic wave to work concurrently. However, the receptors (or cells) of electromagnetic wave can NOT identify more than three different frequencies of electromagnetic wave concurrently (This is the environmental pollution of electromagnetic wave), which is similar to the limitation of three spatial dimensions in direct perception capacity of human species (The cell is not so clever to deduce the equations at more than three dimensions like me!).
In this chapter, pathogen ‘army’ behaves as camouflage, ambush, or other intelligence strategy for invasion, and host cells need to defend punctually and effectively by training for survival (host cells adjust their skills by themselves on the basis of biophysical learning during this ‘war’ until invasive enemy dies) --- this is the evolutionary physiology of environmental adaptiveness, the foundation subject of environmental science.


Reference:
[1] 注册环保工程师专业考试复习教材(2009). 第二分册. 中国环境科学出版社. ISBN:978-7-5111-0505-9.


Appendix 6. The Synthesis of Biological Antibiotics and Its Application on Bio-medicine/生物抗生素合成与在生物医药中的应用
In above appendices, the immunology of host cells becomes the key to resist the invasive pathogen. Nevertheless, there are some exceptions that the immunological potential of host cells, which relies on the synthesis of antibiotics in host cells, may not be sufficient to resist the invasive pathogen (such as congenital defect of rat species against a specific pathogen). Then the vegetation antibiotics is helpful as complementary solution. The steps of synthesis of vegetation antibiotics are similar to appendix 4.
Step 1. N×N samples of a vegetation species, which has been identified to be helpful in biomedicine, are cultivated during simulation of different electromagnetic wave conditions;
Step 2. Different frequency of electromagnetic wave (or different wavelength) are simulated, and labeled as F1, F2, ..., Fn;
Step 3. Metabolomics test is conducted individually after cultivation in F1, F2,...Fn, respectively.
Step 4. Under each simulated frequency of electromagnetic wave, different electromagnetic wave  intensity (AND amplitude) are simulated, and labeled as I1,   I2, ..., and In.
Step 5. Metabolomics test is conducted individually after cultivation in I1, I2,...In, respectively. The amount of N×N metabolomics tests are conducted in total.
Step 6. In total N×N different samples of vegetation antibiotics are abstracted from each different cultivation condition (The method of this abstraction is the same as the preparation of Traditional Chinese Medicine).
Step 7. Each sample of vegetation antibiotics is injected into the invasive simulation of pathogens targeting the host cells of rats respectively, in combination with the training of host cells discussed in chapter 8.
Step 8. The infection of host cells are observed, and the effectiveness of each sample of vegetation antibiotics is decided correspondingly.

It is expected that a combination of antibiotics from both host cells and vegetation leads to the best solution, and a combination of different vegetation antibiotics is more effective. However, the ‘dead’ antibiotics abstracted from vegetation is not as effective as ‘living’ antibiotics in host cells, due to the evolved resistance of  pathogens against the static or constant antibiotics. Actually, there are lots of cases that insect pests frequently evolve into resistance to VERY toxic pesticides, which is the same phenomenon. Please note: the abstraction of vegetation antibiotics here is on the basis of ancient preparation method of Chinese medicine, and the advantages of this is to consider all the vegetation metabolites cultivated in Lab as the whole substances for antibiotics, rather than separating a specific chemistry species from the vegetation metabolites, which can be proven by that plant resistance (or antibiotics) substances usually contain multiple biochemistry species discussed in chapter 4. Another advantages of ancient preparation of Chinese medicine is to provide additional nutrition for host cells. During effective vegetation antibiotics condition, the invasive pathogens are usually dormant so that the competition in nutrition between host cells and pathogens is minimized. Otherwise the additional nutrition may benefit the pathogens rather than host cells.

There are three kinds of vegetation species selected in future research for better ‘diversity of antibiotics’ (If funding is available): one is the Ganoderma Lucidum (I started to grow this from 2011), another is Anoectochilus roxburghii (Wall.) Lindl.(I started to grow this from 2016. Not only human species know this, but also wild pigs must be keen to look for this vegetation for remediation after injury), and the last one is rhizome of Leguminosae species, because the symbiosis of rhizobium in Leguminosae species leads to antibiotics with higher dynamics from both vegetation cells and rhizobium cells. However, the inoculation of various rhizobium, which successfully lead to tumour in root system as symbiosis, is necessary. The reason of enriching rhizobium biodiversity has been discussed in chapter 8 (the specificity of host-invasion interaction), which results in various antibiotics from both plant cells and microbial cells.For the shading-habitat plant species, which suits shading environment only for growth, plants' leaves usually turns to be yellow when they are long-termly exposed  to the intensitive sunshine. Inversely, the leaves of sunshine-habitat plant species turn from green into yellow when they are shaded. For the shading habitat plant such as  the Anoectochilus roxburghii (Wall.) Lindl. as well as Ganoderma Lucidum, the intensity of UV-B radiation must be reduced for the cultivation, as compared to the intensity used in other articles of this journal.

In addition to the synthesis of vegetation antibiotics for biomedicine, the inoculation of microbial vaccine in animals such us rats, pointed out in chapter 8, also provides effective way of generating antibiotics for biomedicine production against similar genetic strains. However, in this case, symbiosis between microbial vaccine and host cells is not compulsory, which means that the host cells can be ‘eaten up’ by microbial vaccine for biomedicine production. Please note: according to the Traditional Chinese Medicine, the biomedicine made from animal cells tends to be ‘warm,’ possibly due  to too much animal proteins, which need to be incorporated into vegetation biomedicines (which tends to be ‘cool’) as mixtures for best biomedicines.


This is the revised materials in book “Proceedings for Degree of Postgraduate Diploma in Environmental Science (3rd Edition).” Published in 2016. The ‘chapter’ content mentioned in this article is in previous book. Revised on 05/01/2021.

References:
All the science terms in English of this journal source from Wikipedia:
https://encyclopedia.thefreedictionary.com/;
本文所有中文科学专业术语引用自百度百科 https://baike.baidu.com/
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