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 楼主| 发表于 2020-12-20 19:20:37 | 显示全部楼层
Article 9. The specificity of host-invasion interaction and its application on immunology of cell/宿主细胞与生物入侵关系的专一性机制及在细胞免疫学的应用研究
There is some personal thoughts about the immunology of host cells against microbial pathogens (including virus and bacteria). In addition to the genetics of host body, the ‘memory’ of host cells, which allows host cells to fastly and accurately identify the bio-signals of specifically invasive pathogens so that the immunological reaction of host cells functions punctually, also plays a significant role in immunology. However, this ‘memory’ of host cells can be inherent, which is passed on from parental generation, or acquired skills which are cultivated through the past ‘battle’ against disease. The inherent ‘memory’ has been discussed in the Chapter 1 (appendix 2) of this book.

The isozyme families, associated with the pathology (or immunology), include the AST, CK, LDH, B-ALP and G6PD,... etc[5]. Specificity of host-invasion interaction examination:
1.There are two different genetic strains of host cells (sample 1 and sample 2) in the same tissue (such as the blood samples abstracted from parallel rat samples) selected and cultivated in this research;
2.Before bacteria invasion simulation, the samples of host cells are cultivated in the same environmental conditions (named as pre-invasion samples). After this, bacteria invasion simulation is conducted in a proportion of host cell samples (However, the other environmental condition for cell cultivation is not changed during bacteria invasion simulation).
3.The bacteria (or virus) invasion targeting the cells of host tissue is simulated in Lab.
4.The host cells with apparent antibiotics specifically against a strain of invasive bacteria is identified and cultivated during bacteria invasion simulation (named as after-invasion samples), and the other host cells without apparent antibiotics are also cultivated during bacteria invasion simulation for comparison; Please note: it is important to ensure the uniform pathogenicity of a bacteria (or virus) strain for the invasion simulation;
5.The systematic metabolomics test (both experiment and data analysis methods are listed by the appendix 2 of Chapter 1 in this book) is conducted after bacteria invasion process in host cells (in both pre-invasion and after-invasion samples), as well as in invasive bacteria samples (Please note: the bacteria samples collected are cultivated during invasive simulation process); Please note: differed from the appendix 1 of chapter 1 in this book, the metabolomics test is applicable on virus classification in this research, due to the uniform virus cultivated in simulation process, and the cultivation and separation procedure of virus can be found in relevant references;

6.By the comparison between pre-invasion and after-invasion samples, the isozyme families, involved in the synthesis of antibiotics, are identified consequently (named as antibiotic isozymes); through UPGMA (unweighted pair group method with arithmetic averages) analysis, the patterns of antibiotic isozyme zymograms in host cell groups with apparent antibiotics specifically correspond to the zymograms of a specific invasive bacteria strain, regardless of genetic difference between sample 1  and sample 2, which means that the host cells in both sample 1 and sample 2 with apparent antibiotics are classified into the same group by UPGMA analysis, regardless of genetic difference. Consequently, the effectiveness of gene expression patterns in host cells is mainly determined by the specific phenotype of a bacteria or virus strain.
7.The patterns of zymograms in host cells without apparent antibiotics vary. Similarly, for the other strains of invasive bacteria (or the other phenotypes of the bacteria or virus within the same genetic strain), the patterns of antibiotic isozyme zymograms react differently and specifically in host cells with apparent antibiotics. This study does not only help to diagnose the pathology and invasive bacteria strain, but also provides the indicators of ‘training’ host cells in future, establishing the ‘memory’ of triggering the antibiotics, to improve the immunology by biophysical ‘learning’ in site. Then ‘exchange transfusion’ is applicable on the medical treatment (For example, if the cancerous blood cells of a rat is caused by virus, then blood cells from other healthy rats with better immunology can be trained by biophysics technology, discussed in next chapter, for exchange transfusion). So far there is a number of case reports with regards to exchange transfusion such as Yu (2011)[6], and the recommended volume of bloods per exchange is no more than 10% of total bloods. However, the volume of 'trained' bloods per exchange should be less than this recommended value, due to the allo-antibiotcs of trained cells.

Discussion:
Compared with the bio-signal simulation in chapter 9 of this book, the bio-signal of biotic factor identified by cells is specific, whereas the bio-signals of abiotic factors show the patterns of ‘environmental gradient’(the gene expression patterns react gradually with the gradual change of environmental factors along the environmental gradient).

Please note: The characteristics of host cells with apparent antibiotics can be  identified as: relatively active cell division rate; And constant and healthy ratio between erythrocyte and leukocyte cells. Usually the ratio between erythrocyte and leukocyte tends to be identical in the long term when cells are cultivated in the same environmental conditions of Lab, regardless of genetic variation. However, when enzyme activity is ignored and only variation in enzyme species is considered in this research, the difference in the ratio of erythrocyte to leukocyte between two different genetic strains can be ignored in UPGMA analysis too.

To be continued ...


References:
[1]. 唐银栋(1987)。重金属的结构与其环境污染和毒性的关系。《内蒙古医学院学报》。
第 9 卷,第 1 期。
[2]许国章,樊军明(1995)。重金属中毒性肾脏病。《新医学》。
[3]. 陈文慧, 袁嘉丽, 韩妮萍, 姚政, 张英凯, 赵鹏 (2005)。 春季时令病邪与空气微生物及呼吸道微生态相关性初步研究。《云南中医学院学报》。第 28 卷第 4 期。
[4].Liu Huan (2015). Review of Biological Control: The Population Biology of Microbial Ecosystem/种群生物学原理在微生物生态系统和生物控制技术中的应用研究(英文). Journal of Environmental & Health Science.
[5]. 周延清, 张改娜与杨清香, 生物遗传标记与应用, 2008, 化学工业出版社.
[6]. 余 敏 新生儿换血疗法的治疗及护理 2011 年第 9 卷第 9 期 《中华现代临床医学杂志》
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 楼主| 发表于 2020-12-20 19:23:08 | 显示全部楼层
Article 10. Gene Mutation and Its Pathogenesis (1)/基因突变及其致病性机理(1)
Step 1. The cells with apparent antibiotics of the same genetic strains are identified during the invasive simulation of a specific bacteria strain (Sample 1);

Step 2. The same bacteria strain is cultivated during radiation, leading to gene mutation (Sample-M) detected by FISH using transmission electron microscopy, as described by the chapter 11 of this book;

Step 3. Invasive simulation by Sample-M targeting the cells with apparent antibiotics, identified in step 1, is conducted.

Step 4. The disease infection by Sample-M is observed.

Step 5. The cell division rate (quantify of cells / cultivation time) is observed and compared between cells with gene mutation and cells without gene mutation.

Hypothesis:

The bacteria with gene mutation leads to altered bio-signal which can be difficultly perceived by cells with specific immunology against their parental bacteria (sample 1), and the infection rate by sample-M is higher than sample 1.

Discussion:
Gene mutation, leads to cells with faster cell division rate (DNA or RNA replication rate in virus) than their parental cells (or virus). This explains the sharply epidemic infection caused by bacteria or virus with gene mutation (such as AIV).

Appendix 3. Gene Mutation and Its Pathogenesis (2)/基因突变及其致病性机理(2)
As discussed in chapter 1, gene mutation virus leads to ‘altered’ or distortive bio-signal, which is hardly identified by host cells. Consequently, this chapter presents a novel method to train the host cells’ ‘memory’ in terms of identifying the invasive virus family with gene mutation.

Step 1. The virus classification on the basis of FISH technology is conducted, which  is the morphological markers of genome, as described by chapter 1.

Step 2. The similar virus families (mild sample) to the pathogenetic virus family with gene mutation (pathogenetic sample) is identified in step 1 on the basis of morphological markers of genome; And the similar virus is less pathogenetic virus (such as becoming dormant in host cells after puncture), which is consequently called as ‘mild’ samples;

Step 3. The specific zymograms of host cells with specific immunology against invasive gene mutation virus is identified, as described in appendix 1;

Step 4. The biophysical ‘training’ of host cells, described in chapter 9, is conducted with indication of zymograms in step 3, during the invasive simulation of ‘mild’ samples;

Step 5. This method strengthens the immunology against this gene mutation virus family through similarity invasion simulation.

Discussion:

The pathogenicity of virus invasion in this book is explained by two process: one is to puncture the host cell membrane, and the other is the virus metabolism in host cells after puncture. Consequently, host cells identify the bio-signal of invasive virus by two stages correspondingly: the first stage is the puncture process, and the morphological bio-signal of invasive virus genome is the main bio-signal (this bio-signal by gene mutation virus is similar to the other virus families, rather than its parental virus family); the second stage is the pathogenic metabolism of invasive virus after puncture, and the main bio-signal depends on the gene expression of virus genome (this bio-signal by gene mutation virus is similar to their parental virus). This two process further explains the altered or distortive bio-signal by gene mutation virus.

Please note:
If the specific zymograms of host cells with specific immunology against invasive

gene mutation virus is NOT identified by the method described in appendix 1; then  the specific zymograms of host cells with specific immunology against invasive gene mutation virus has to be identified by adjusting the biophysical parameters during invasion simulation of gene mutation virus in lab, as described in chapter 9. However, it is expected that the specific zymograms of host cells with specific immunology against invasive gene mutation virus is closer to the specific immunology against their parental virus.

However, for the invasive virus (or bacteria) with dormant characters, it is further discussed in chapter 9.
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 楼主| 发表于 2020-12-20 19:31:38 | 显示全部楼层
Article 11. Biophysics and Enzymology / 生物物理与酶谱生物化学
Article 1: Biophysical Simulation of Bio-signals and The Biochemical Dynamics of Enzymology /生物物理对生物信号的模拟及相应的酶谱生化反应动力机制
Author: Liu Huan, MSc (First Class Honours), The University of Auckland.
Published after graduation on 11/01/2016

Methods (All the tables and figures are in PDF version):
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.

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.


Article 2. 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).

Article 3. 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.


Article 4. 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.

Article 5. 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 chapter 2), 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!

Article 6. 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.


Article 7. 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.

I will tell this world a story: the host cells from someone who has practiced Qigong (such as my uncles) help to identify the host cells with specific immunology against the pathogen (the biophysical training of host cells in this book is originally from the principle of Qigong), and the vegetation variety originated from adverse condition help to identify the best antibiotics too. Good luck for my lovely rats, I hope I will remedy you!

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. Good Luck!
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 楼主| 发表于 2020-12-20 19:37:59 | 显示全部楼层
Article 12. The 'intellegence' of cells./细胞的智力
Article 1. Assimilation of The Cells’ ‘Memory’ Between Different Phenotypes and Its Implication on Canceration/ 不同表现型细胞间在‘思维’上的的同化机制及在癌变过程的指示意义
Author: Liu Huan, MSc (First Class Honours), The University of Auckland. Published after graduation on 21/01/2016

Methods (All the tables are in PDF version):
As described in chapter 9 in this book, after UV-B simulation process stops, both sample 1 and sample 2 of the same genetic strain are transferred into moisture simulation process.

Step 1. Both sample 1 and sample 2 are cultivated separately and individually in each moisture simulation process (T1, T2, ..., Tn);

Step 2. The samples of even mixture between sample 1 and sample 2 (50% for each sample) are cultivated individually in each moisture simulation process (T1, T2, ..., Tn) as well; The cultivation condition is the same between step 1 and step 2, and step 1 and step 2 is conducted independently;

Step 3. The reproduction rate (or cell division rate) is observed, and the comparison of cell division rates between step 1 and step 2 under the same cultivation condition is conducted: in step 1, the cell division rate of sample 1 and sample 2 is R1 (cell quantity/time) and R2, respectively; if assimilation of the cells’ ‘memory’ does NOT occur, then the cell division rate of mixture sample is 0.5*(R1+R2); however, if assimilation of the cells’ ‘memory’ does occur, then the cell division rate of mixture sample is not equivalent to 0.5*(R1+R2); if the cell division rate of mixture sample is closer to R1, the sample 1 becomes dominant; if the cell division rate of mixture sample is closer to R2, the sample 2 becomes dominant.


Discussion:

Within the cells of the same genetic strain, cells apparently assimilate each other between different phenotypes. It is expected that sample 1 tends to be dominant  during comfortable condition; and sample 2 tends to be dominant during adverse conditions. This theory is applicable on the cancerous tissue: when cancerous cell without immunology becomes dominant in cell assimilation process, the whole tissue (or organ) starts to be canceration, so the prevention of cancerous cell assimilation is the key in pathological study. Appendix of this chapter lists the experiment procedure for blood cell cultivation, further support the discussion of this chapter.

Appendix. The simulation methods for blood cell cultivation

As described by the appendix of chapter 9 in this book, after electromagnetism simulation for cell cultivation process stops, both blood sample 1 and sample 2 of a  rat (or the same genetic strain) are transferred into simulation process of physiological saline:

Step 1. 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.

Step 2. The samples of even mixture between sample 1 and sample 2 are cultivated individually in each different concentrations of physiological saline (T1, T2, ..., Tn) as well; The cultivation condition for blood cell is the same between step 1 and step 2, and step 1 and step 2 is conducted independently.

The other steps are the same as described above. To be continued...


Article 2. The Inversion of Cancerous Gene Mutation in DNA Molecule and Its Implication on Biochronometry of Life Origin/
癌细胞基因突变的逆转及在生命起源中‘生物钟’论的指示意义
Author: Liu Huan, MSc (First Class Honours), The University of Auckland. Published after graduation on 31/01/2016

Methods:

There are three kinds of cells abstracted from the same tissue of the same genetic strain, which are cultivated in physiological saline in Lab:
Step 1. A stream of cells is cultivated in radiation condition, leading to the gene mutation of DNA molecule (sample 1) which can be detected by FISH technology, pointed out by the chapter 1 of this book; another stream of cells is cultivated in moderate electromagnetism condition leading to better immunology (sample 2) without gene mutation in DNA, as described by the chapter 9 of this book; the last stream of cells (sample 3) is cultivated in ‘comfortable’ conditions.

Step 2. The samples of even mixture between sample 1 and sample 2 (50% for each sample) are cultivated together in moderate electromagnetism condition;

Step 3. The samples of even mixture between sample 1 and sample 3 (50% for each sample) are cultivated together in ‘comfortable’ condition;

Step 4. Finally, the gene mutation rate in DNA molecules of mixed cells are calculated by FISH after step 2 and step 3, respectively.

Please note: it is expected to clearly detect gene mutation after ten generations of cell division.

Objectives:
Step 2 leads to lower gene mutation rate in mixed cells due to the assimilation of cells’ ‘memory’ between different phenotypes, as discussed in the chapter 10 of this book, as compared to step 3. This is the inversion of cancerous gene mutation in DNA molecules, due to the self-repair of genome. The electric potential of different cell communities are recorded, as pointed out in chapter 9, and it is expected that the cells of junior stages are more likely to be assimilated, so the advantages of this electromagnetism gradient is to separate the cell communities with different aging stages. As discussed in chapter 9, the electromagnetic field of cells varies during their life cycle, which is consequently a kind of time-varying electromagnetism yielding the bio-electromagnetic wave. This bio-electromagnetic wave is the bio-signal for cells to communicate each other (or for vegetation species to communicate each

other).

Please note: this method is less effective on the cancerous cells caused by virus, due to the ‘intelligence’ of causal factors. The electromagnetism condition is the constant electromagnetism in this book, and the electromagnetic wave is the time-varying electromagnetism. In chapter 9, the intensity of constant electromagnetic fields for training blood cell is discussed. The electromagnetic fields are obviously the constant one in Chapter 11 rather than time-varying electromagnetic waves. Consequently, the method of this chapter is similar to the situation of ‘taking rest quietly and recovery smoothly by coachers in electromagnetic field after injury,’ whereas the method of application of time-varying electromagnetic waves, which aims to defend against invasive pathogens, is similar to the battle music violently, encouraging cells to fight.

Discussion:
Gene mutation, which occurs during DNA replication process, is triggered by the bio-signal perceived by cell. Once the bio-signal is altered, gene mutation occurs. However, the assimilation of cells results in the inversion of gene mutation during positive biophysical simulation in site.


Article 3: The life origin, Death and The Sustainability of
Population /生命起源、终结与种群的延续
Author: Liu Huan, MSc (First Class Honours), The University of Auckland. Published after graduation on 31/01/2016


Further more, this book asserts that: DNA molecule, as the first molecule of biochemistry chains in cell, is NOT the origin of life cycle, but the ‘spirit’ is! The phenomenon, senescence of cells, is NOT a kind of gene trait which is determined by gene sequences in DNA molecule, but is determined by the biochronometry, the invisible ‘spirit’.

The 'Energy Conservation Law' of cell's life:
As discussed in chapter 9, cells move from a specific electric potential (a) to another electric potential (b) due to the variation in bio-electromagnetic field in their life cycle. Consequently, this section hypothesizes that the cells' life cycle complies with the energy conservation law, and the entropy of 'life energy' is constant for each life cycle of cell.
Wab=Epa-Epb; Epa=qa·φA
Epb=qb·φB        [1]
The entropy of life energy =Epa - N*Epb;

Wab is the electric potential energy, φA and φB is the electric potential (a) and (b), respectively; qa and qb is the electric charge in cells located at electric potential (a) and (b), respectively; N is the amount of cells in the final generation. Once cells exhaust the entropy of life energy, life cycle ends. Please note: electric potential (a) and (b) is based on the ideal conditions. The emission of bio-electromagnetic wave is also a kind of energy consumption. The rest entropy of life energy from the first cell is evenly divided into two of its offspring cells; the rest entropy of life energy from two cells of the second generation are evenly divided into four of their offspring cells; ....
Consequently, the cell division rate starts to decrease, because more and more offspring cells share the rest entropy of life energy.

As pointed out by other biologists, continuous gene mutation gives cells infinite life cycle. Consequently, the population of microbes, as the single cell creatures, must  gain sustainability of population only through gene mutation, after  primary life-energy is exhausted by a cell's division cycle. In principal, after gene mutation, this 'new' population of microbes becomes a new 'species' as well. For example, once  a strain of cells exhausts the entropy of life energy at electric potential (b) and gene mutation occurs at this exact time, then a new cell's division cycle, created by gene mutation, starts at a point before electric potential (b) (such as at potential (a) again),

which means 'fresh' life energy can be only charged by gene mutation. According to the 'Energy Conservation Law,' gene mutation must be driven by other sources of electromagnetic waves (such as radiation), which is an environmental adaptiveness. However, for the species of sexual reproduction, gene communication replaces gene mutation as a way 'charging' life energy. For other multiple-cell creatures of asexual reproduction, gene recombination would replace the gene mutation to sustain the population.

Implication for environmental microbe cultivation: the way of sustainability of microbe population reflects the importance of genetic pool conservation with similar environmental traits. The mixed cultivation of various genetic strains  of microbes with similar environmental traits helps to keep constant and sustainable environmental traits as a whole microbe community during gene mutation process due to cell's assimilation in memory, as discussed above.

Gene Therapy and Gene Modification in Nature: It is further deduced that natural and mild gene mutation would occur during biophysical training process  of blood cells discussed above, which is an indicator of improved environmental adaptiveness like microbes. However, this mild and natural gene mutation is neither like cancerous gene mutation, nor like clone cells which have been artificially inserted or deleted by other DNA sequences. As discussed in chapter 8, gene mutation leads to faster cell division rate. It is deduced that gene mutation caused by stronger intensity of electromagnetic waves results in faster cell division rate, so the recommended intensity of electromagnetic waves in chapter 9 is moderate and increases the blood cell activity once gene mutation is caused by this. Please keep in mind like that: gene mutation is the way for cells evolving into environmental adaptiveness in response to environmental change, and positive gene mutation can be directed in Lab, whereas negative gene mutation is prevented. To data it has been noticed that moderate gene mutation occurs after 10 generation cultivations using common environmental microbes in sewage water treatment, which can be detected by the above method. Actually, this is easy to understand in life: let’s compare two different populations: a population of Chinese who survive in city for several generations without much exposure to sunshine and the other population of Chinese who work as farmers for several generations with much exposure to sunshine. As to compare the skin color of their infants, there must be apparent different between these two populations: city populations tend to be white, and rural populations tend to be brown due to more skin melanin. Obviously, the gene-mutation-induced phenotype is able to pass onto next generations as genetic materials.

Additionally, the mixed cultivation of blood cells with different genetic strains (of course, blood types must be the same) helps to improve the immunology as a whole community against invasive pathogens as well, which focus on the optimization of gene pool in blood cell community. Please note: unlike cells of other tissues (or organs), blood cells can be the mixed cultivation from different genetic strains for

‘exchange transfusion’ remediation. Consequently, DNA sequencing technology is used to relate the gene variation to the specific immunology against specific pathogens, which provides basis of optimization of gene pool for cell transplantation. However, it is deduced that cell transplantation is more effective than the whole tissue or organ transplantation, not just because of less genetic or type matching requirement for cell transplantation, but also because cultivation of 'young' cells after transplantation would lead to less resistance against other organs. Please note: the 'young' cells are the cells with more active cell division rate caused by moderate gene mutation, and the advantages of cell transplantation is particularly important to other tissues or organs rather than just blood cells.

Further more, as discussed in chapter 8, ‘the specific frequency of electromagnetic wave simulates the bio-signal regulating gene expression as a specific isozyme family, and the specific electromagnetic wave intensity corresponds to the bio-signal regulating gene expression as a specific enzyme species within an isozyme family, which can be examined by metabolomics tests.’ Consequently the specific gene locus of moderate gene mutation, expressed as specific gene trait, is caused by this biophysical training as well, which restore the specific congenital defect through gene therapy and cell transplantation. Please note: the detection of gene mutation on specific genome locus can be achieved by FISH technology specified in Chapter 1. The criterion of centromere index or the curve degree of chromosome is used to detect the specific locus of gene mutation, which becomes the unique identifier to  distinguish different loci of gene mutation. Of course, it is further deduced that the specific frequency of electromagnetic wave determines the gene mutation in specific gene locus (a stream of the same and repetitive DNA or RNA sequences on chromosome), and the specific electromagnetic wave intensity determines the ‘modification’ of amount of these repetitive DNA or RNA sequences on this specific gene locus. This science rhythm corresponds to the re-definition of isozyme family: the biochemistry molecules contain the same functional group in the same isozyme family, but the amount of repetitive functional groups varies between different  enzyme species’ molecules within an isozyme family. Obviously, specific gene locus (or loci) express as specific isozyme family in this case.

However, it is expected that a specific life function is not determined by one gene locus only, but is determined by multiple gene loci, which means the time-varying electromagnetic wave proposed in the chapter 9 is more reasonable than static electromagnetic wave.
Acknowledge
A cross awarded by a Christchurch church, 2006, New Zealand.
[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.


Article 4. Reproduction Physiology/生殖生理学
Author: Liu Huan, MSc (First Class Honours), The University of Auckland. Published after graduation on 09/09/2016
Cervix or uterine contraction and women senescence.

There is a significant and direct corelation between women senescence (such as after 25 years old) and cervix or uterine contraction (This is similar to the skin contraction and wrinkle during aging), which tends to cause hemorrhoea during delivery process and also results in negative impacts on baby head, directly expressed as increased frequency of convulsion after birth, due to increased contraction force during birthing process. Consequently, do not try to breed after this age! This is my viewpoints about reproduction health! My wife yields my son and daughter before this senescence!


Article 5. Evolutionary Selection/进化选择
Author: Liu Huan, MSc (First Class Honours), The University of Auckland. Published after graduation on 25/09/2016

After the experiment is conducted as indicated in article 2, it is noticed that only one (or a limited proportion) cell of cell community is selected to start a new life cycle through gene mutation under long-term radiation treatment. In other cases, when the population of a plant variety faces epidemic disease, there is always one (or a limited proportion) plant individual selected by population for survival surrounded by dead plants infected by pathogen. At least this is the observation by myself.

However, I don’t think this selection is determined by genetic variation among this population. As discussed previously, the cell or plants populations are able to communicate each other in a certain mean, so that a population try their best to keep  at least one individual selected to survive when this population faces the risks of extinction. This rhythm is also applicable on the host-invasion simulation of blood  cell community. Once the community of blood cells faces pathogen invasion, there are always a small proportion of cells selected to survive, although the whole cell community can hardly sustain the function in body. The survival cell selected by this cell population is the rare samples for cultivation. At least this is the observation by myself.

Let’s re-discuss the life energy experiment in article 2:
Wab=Epa-Epb; Epa=qa·φA
Epb=qb·φB        [1]
The entropy of life energy =Epa - N*Epb;

If one cell is selected by this cell community (the quantity of cells is N1 at this time in this community) at electric potential b to start a new life cycle through gene mutation under radiation treatment. This gene mutation cell starts new life cycle at electric potential c and other cells cease life cycle at potential b; if radiation treatment is not applied, this cell community (the final quantity of cells is N2 at this time) ceases cell division at electric potential d naturally. Then

Epc * 1 = Epb * N1 - Epd * N2

This means that the whole cell community pass on the rest of life energy entropy into a cell to start a new life cycle through gene mutation. This is the natural law in cell evolution. Consequently, cell evolution costs original life energy!

As discussed in chapter 1, population does not only pass on the genome, the genetic resource, but also passes on the ‘memory,’ in terms of identifying the bio-signal triggering the gene expression, onto their offspring. Similarly, after the disaster to population, their offspring, who are selected by this population and survive after disaster, keep ‘memory’ of this disaster. Consequently, the indigenous microbe population settles in underground water environment of earthquake areas, who keep ‘memory’ of this earthquake disaster, must respond to earthquakes before it happen,  as a kind of ‘immunology,’ which becomes an indicator to predict earthquake as well. The metabolomics test listed in this book is the feasible measure to conduct this.

References: the conceptions and terms of biology in this book sources from Wikipedia, the free encyclopedia.
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 楼主| 发表于 2020-12-21 10:59:55 | 显示全部楼层
Article 13. The Metabolomics and Its Application on the Medicine Production/新陈代谢组学在新药生产中的应用

最近看了一些关于新药的新闻报道的特征描述,提出以下学术观点:本文在之前学术论文《新陈代谢组学》中一直提出使用同工酶最为指示性生化指标对病理进行分析才保证其长期稳定、可靠的表现型特征,不容易受制于环境条件的影响。如果是选用mRNA或是tRNA作为指示性生化分子,在此基础上对最终表现出来的抗体是否呈现阳性进行相关性分析,不会有长期稳定的正相关特性,而且容易受制于环境条件的影响(比如测试前期的饮食、生理作息时间等也可能会对mRNA测试结果产生显著影响)。这对于疫苗抗体的有效性分析尤其重要。因此这类疫苗抗体仅仅类似于西药,产生短期治疗效果。

Recently, I have read the biochemical characteristics of some News reports about new drugs, and presented the following academic viewpoints: in the previous academic paper of metabolomics, it is proposed that the selection of isozymes as the indicative biochemical molecules for pathological analysis mostly relates its phenotype characteristics, which is stable and less environmental sensitive in the long-term. If medicines research chooses mRNA or tRNA as biochemical indicator, it is not expected to show a long-term stable and positive correlation to the eventual phenotype of antibody against virus, and is suscitible to environmental conditions (such as diet and physiological work-rest timetable may significantly influence the results of bio-tests on mRNA) , and this is especially for the analysis of immunology generated by vaccine inoculation. The vaccine produced on the basis of the later indicator is similar to biochemical medicines only, which plays the role in remedy in the short term.
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 楼主| 发表于 2020-12-21 15:05:52 | 显示全部楼层
新陈代谢组学的补充学术观点:
细胞结构生物中DNA分子应当准确定义为物质遗传信息的主要载体。因为细胞是有智力的,遗传过程中除了物质遗传信息,还有精神记忆机制。这在我之前的论文中已经论述。那么在此后,细胞中开始了复杂的新陈代谢过程,这里可以区分为初级代谢生化分子(如tRNA),次级代谢生化分子(如本文在植物逆境生理中论述的glutamic acid),和最终代谢生化分子(如多糖化合物)。其中不可缺少的就是酶。酶是细胞生物中对新陈代谢生化过程进行调节的首要生化指标。初级和次级代谢生化分子既可以受遗传DNA影响、也可以受细胞环境的影响而显著发生变异特性,但是细胞生理功能的调节,仅仅通过调节生物酶的合成和分泌作为生化反应链中首要途径,不管DNA先天遗传和细胞环境变化因素。 正如本文已经论述多细胞高等智慧生物的思维局限于三维思维能力,而单细胞生物的智力思维能力应该仅仅停留在识别生物信号和运用生物酶两个维度而已。而细胞生物对生物酶的识别与合成可以是后天培养的。本文已经在细胞“智慧”一文中论述了细胞的思维。

Additional academic viewpoints of metabolomics:

DNA should be defined as the main carrier of material genetic information. Because cells are intelligent creatures, in addition to material genetic information, there are also memory of spirit passed on to the offspring cells in the genetic process. This has been discussed in my previous paper. After genetics, complex metabolic processes begins in cells, which can be divided into three categories in this article: primary metabolic molecules (such as tRNA), secondary metabolic biochemistry molecules (such as glutamic acid discussed in plant stress physiology), and the final metabolites (such as polysaccharide compounds). However, enzyme is the indispensable biochemicals in this metabolic process. Enzyme is the principal biochemical regulator to initiate the biochemical process of metabolism in cell biology. The primary and secondary metabolites can be significantly influenced by the cell physiological environment and genetics, whereas the cell functions constantly relies on the regulator of enzymes initiating the pathways of various metabolite process regardless of environmental changes and genetics. As has been discussed in previous paper, the thinking ability of multi-cellular individuals of higher intelligent is limited to three-dimension, as the thinking ability of single-cell organisms should only stay in two dimension: the recognition of bio-signals and utilization of biological enzymes. The enzyme utilization capacity can be ‘learned’ by cells. The previous paper has discussed the intelligence of cells.
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 楼主| 发表于 2020-12-21 15:45:11 | 显示全部楼层
新陈代谢组学的补充学术观点:
细胞结构生物中DNA分子应当准确定义为物质遗传信息的主要载体。因为细胞是有智力的,遗传过程中除了物质遗传信息,还有精神记忆机制。这在我之前的论文中已经论述。那么在此后,细胞中开始了复杂的新陈代谢过程,这里可以区分为初级代谢生化分子(如tRNA),次级代谢生化分子(如本文在植物逆境生理中论述的glutamic acid),和最终代谢生化分子(如多糖化合物)。其中不可缺少的就是酶。酶是细胞生物中对新陈代谢生化过程进行调节的首要生化指标。初级和次级代谢生化分子既可以受遗传DNA影响、也可以受细胞环境的影响而显著发生变异特性,但是细胞生理功能的调节,仅仅通过调节生物酶的合成和分泌作为生化反应链中首要途径,不管DNA先天遗传和细胞环境变化因素。比如,在本人之前文章已经论述,针对特定病原体的抗体,不管宿主细胞DNA遗传变异特性,也不管细胞环境的变化,细胞内合成针对特定病原体的有效抗体的同工酶谱都是相对唯一性和特定性。正如本文已经论述多细胞高等智慧生物的思维局限于三维思维能力,而单细胞生物的智力思维能力应该仅仅停留在识别生物信号和运用生物酶两个维度而已。而细胞生物对生物酶的识别与合成可以是后天培养的。本文已经在细胞“智慧”一文中论述了细胞的思维。

Additional academic viewpoints of metabolomics:

DNA should be defined as the main carrier of material genetic information. Because cells are intelligent creatures, in addition to material genetic information, there are also memory of spirit passed on to the offspring cells in the genetic process. This has been discussed in my previous paper. After genetics, complex metabolic processes begins in cells, which can be divided into three categories in this article: primary metabolic molecules (such as tRNA), secondary metabolic biochemistry molecules (such as glutamic acid discussed in plant stress physiology), and the final metabolites (such as polysaccharide compounds). However, enzyme is the indispensable biochemicals in this metabolic process. Enzyme is the principal biochemical regulator to initiate the biochemical process of metabolism in cell biology. The primary and secondary metabolites can be significantly influenced by the cell physiological environment and genetics, whereas the cell functions constantly relies on the regulator of enzymes initiating the pathways of various metabolite process regardless of environmental changes and genetics. For example, in the previous article, it is concluded that the isozyme spectrum correspondingly to the valid antibiotics of specific pathogens must be relatively specific and unique, regardless of DNA genetics and environmental changes between different host cells. As has been discussed in previous paper, the thinking ability of multi-cellular individuals of higher intelligent is limited to three-dimension, as the thinking ability of single-cell organisms should only stay in two dimension: the recognition of bio-signals and utilization of biological enzymes. The enzyme utilization capacity can be ‘learned’ by cells. The previous paper has discussed the intelligence of cells.
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 楼主| 发表于 2020-12-23 14:57:52 | 显示全部楼层
生物物理/Bio-physics
软体生物释放的生物电磁波为纵波,即振动方向与波的传播方向相同;光波(包括紫外光波)为横波,即振动方向与波的传播方向相垂直。

The biological electromagnetic wave released by soft organism is longitudinal wave, which is that the vibration direction is the same as the wave transmission direction; the light wave (including ultraviolet light wave) is shear wave, which is that the vibration direction is perpendicular to the wave propagation direction.
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 楼主| 发表于 2020-12-24 15:40:43 | 显示全部楼层
生物物理/Bio-physics
软体生物释放的生物电磁波为纵波,即振动方向与波的传播方向相同;光波(包括紫外光波)为横波,即振动方向与波的传播方向相垂直。对于生物波(主要是声波和生物电磁波/生命信号波),与无生命机械波或是电磁波区别:对于生物波而言,在其所在频率范围内,生物波的在不同频率之间的转换必须是连续型;对于无生命机械波或是电磁波而言,在不同的频率之间的转换可以是跳跃、断点型。对于生物波而言,在其所在频率范围内,生物波在各频率上所出现概率越接近正态分布率,越为纯正、品质越高(比如歌唱家声调纯正;或是气功生命信号波更上乘,血统更为纯正)。

The biological electromagnetic wave released by soft organism is longitudinal wave, which is that the vibration direction is the same as the wave transmission direction; the light wave (including ultraviolet light wave) is shear wave, which is that the vibration direction is perpendicular to the wave propagation direction. The key characters of biological wave (mainly including acoustic wave and bioelectromagnetic wave / life signal wave) is different from abiotic mechanical wave or electromagnetic wave: for biological wave, the conversion between different frequencies must be continuous in its wave frequency range; for abiotic mechanical wave or electromagnetic wave, the conversion between different wave frequencies can be the ‘jumping points’ and incontinuous type. For biological waves, in their own frequency range, if the probability of occurrence at each frequency is closer to the normal distribution rate, it is expected to give the purer and higher quality (for example, the singer's tone is superior; or the Qigong life signal wave is better, or the bloodlines is purer).

Previously published on 2018. Revised on 24/12/2020
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 楼主| 发表于 2020-12-25 09:36:09 | 显示全部楼层
生物物理学/Biophysics
本文中生物物理学研究论述的主要范围是生物波的特性,其中把生命信号波定义为生命的本质特性,并非以物质生命体定义为生命的本质特性。因此是否具备生命特性是以是否具备生命信号波作为标志。比如,一个多细胞高等智慧生物个体,在个体死亡之后,细胞仍然具备有生命特性,仍然释放生命信号波。生物释放的生物电磁波为生命信号波,具备电磁波的波粒二象性特点。但是本文增加以下论点:软体生物释放的生物电磁波为纵波,即振动方向与波的传播方向相同;光波(包括紫外光波)为横波,即振动方向与波的传播方向相垂直。对于生物波(主要是声波和生物电磁波/生命信号波),与无生命机械波或是电磁波区别:对于生物波而言,在其所在频率范围内,生物波的在不同频率之间的转换必须是连续型;对于无生命机械波或是电磁波而言,在不同的频率之间的转换可以是跳跃、断点型。对于生物波而言,在其所在频率范围内,生物波在各频率上所出现概率越接近正态分布率,越为纯正、品质越高(比如歌唱家声调纯正;或是气功生命信号波更上乘,血统更为纯正)。对于不同物种之间,生命信号波在频率上有鲜明区别,可用于不同物种之间的划分依据。软体生物新陈代谢过程生物能在不同频率之间相互转换,从而创造了新能量,并不适用于能量守恒定理(之前的能量守恒定理是基于无生命能量之间转换得出的结论)。本文在生物钟一文中,细胞磁极在一个周期内会阴阳两极转换倒置一次,因此生物波坐标方程应定义为三个坐标轴,x轴为频率;y轴为波幅;z轴为生命周期。z轴为正值定义为“阳气”时间;z轴为负值定义为“阴气”时间。

In this paper, biophysics academy focus on the biological waves. Biological wave is defined as the indicator of life nature, rather than the material body of creatures. Therefore, whether or not they release life signals is the principal indicator to judge if they are alive. For example, for a multi-cellular intelligent individual organ, after the death of the individual, the body cell still has the characteristics of life and still releases the life signal wave. Life signal waves are the biological electromagnetic waves released by organisms, which possess the characteristics of wave particle duality. However, this paper supplements the following viewpoints: the biological electromagnetic wave released by soft organism is longitudinal wave, which is that the vibration direction is the same as the wave transmission direction; the light wave (including ultraviolet light wave) is shear wave, which is that the vibration direction is perpendicular to the wave propagation direction. The key characters of biological wave (mainly including acoustic wave and bioelectromagnetic wave / life signal wave) is different from abiotic mechanical wave or electromagnetic wave: for biological wave, the conversion between different frequencies must be continuous in its wave frequency range; for abiotic mechanical wave or electromagnetic wave, the conversion between different wave frequencies can be the ‘jumping points’ and incontinuous type. For biological waves, in their own frequency range, if the probability of occurrence at each frequency is closer to the normal distribution rate, it is expected to give the purer and higher quality (for example, the singer's tone is superior; or the Qigong life signal wave is better, or the bloodlines is purer). For different species, there are distinct differences in the frequency of life signal waves, which can be used to classify different species. In the metabolic process of soft organism, bioenergy is converted between different frequencies, thus creating new energy, which does not obey the energy conservation law (the previous energy conservation theorem is based on the conclusion of the conversion of abiotic energy). In the paper of ‘biological clock’, the cell magnetic pole will be inverted once in a life cycle. Therefore, the coordinate of biological waves equation should be defined as three coordinate axes, X axis as frequency, Y axis as amplitude and Z axis as life cycle. Positive value of Z axis is defined as "Yang Qi" time, while negative value of Z axis is defined as "Yin Qi" time.


Previously published on 2018. Revised on 25/12/2020
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