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Biomedical subjects

Liaofu Luo

Publications and source records attributed to Liaofu Luo.

12 recordsLinked to original sources

Physicochemical attack against solid tumors based on the reversal of direction of entropy flow: an attempt to introduce thermodynamics in anticancer therapy.

BACKGROUND: There are many differences between healthy tissue and growing tumor tissue, including metabolic, structural and thermodynamic differences. Both structural and thermodynamic differences can be used to follow the entropy differences in cancerous and normal tissue. Entropy production is a bilinear form of the rates of irreversible processes and the corresponding "generalized forces". Entropy production due to various dissipation mechanisms based on temperature differences, chemical potential gradient, chemical affinity, viscous stress and exerted force is a promising tool for calculations relating to potential targets for tumor isolation and demarcation. METHODS: The relative importance of five forms of entropy production was assessed through mathematical estimation. Using our mathematical model we demonstrated that the rate of entropy production by a cancerous cell is always higher than that of a healthy cell apart from the case of the application of external energy. Different rates of entropy production by two kinds of cells influence the direction of entropy flow between the cells. Entropy flow from a cancerous cell to a healthy cell transfers information regarding the cancerous cell and propagates its invasive action to the healthy tissues. To change the direction of entropy flow, in addition to designing certain biochemical pathways to reduce the rate of entropy production by cancerous cells, we suggest supplying external energy to the tumor area, changing the relative rate of entropy production by the two kinds of cells and leading to a higher entropy accumulation in the surrounding normal cells than in the tumorous cells. CONCLUSION: Through the use of mathematical models it was quantitatively demonstrated that when no external force field is applied, the rate of entropy production of cancerous cells is always higher than that of healthy cells. However, when the external energy of square wave electric pulses is applied to tissues, the rate of entropy production of normal cells may exceed that of cancerous cells. Consequently, the application of external energy to the body can reverse the direction of the entropy current. The harmful effect brought about by the entropy flow from cancerous to healthy tissue can be blocked by the reversed direction of entropy current from the irradiated normal tissue around the tumor.

Journal Article↗

Ultrasound absorption and entropy production in biological tissue: a novel approach to anticancer therapy.

UNLABELLED: The entropy production of tumorous cells is higher than that of normal cells, and entropy flow is therefore directed from tumorous toward healthy cells. This results in information concerning the cancer propagating into the surrounding normal tissue. However, ultrasound absorption results in additional entropy production in tissues. The entropy mechanism possibly provides a basis for a novel approach to anticancer therapy through the use of ultrasound irradiation. METHODS: Through the calculation of ultrasound-induced entropy production and comparison of the theoretical results with the experimental data on ultrasound absorption in biological tissues, we have demonstrated that ultrasound absorption will increase the entropy in normal tissue more efficiently than in tumorous tissue due to the more acidic nature of the latter. Consequently, the direction of entropy flow between these two kinds of cells may be reversed on exposure to ultrasound. CONCLUSION: The higher entropy accumulation of normal cells during ultrasound irradiation may possibly lead to a change in the original direction of entropy flow and avoid the propagation of information on the cancer into the normal tissues. We suggest that low-intensity, low-frequency ultrasound irradiation may be an efficient tool for the therapy of solid tumors.

Journal Article↗

The relation between mRNA folding and protein structure.

About 200 mRNA sequences of Escherichia coli and human with matching protein secondary structure data were studied. The mRNA folding for each native sequence and for corresponding randomized sequences was calculated through free energy minimization. We have found that the folding energy of mRNA segments in different protein secondary structures is significantly different. The average Z score is more negative for regular secondary structure (alpha-helix and beta-strand) than that for coil. This suggests that the codon choice in native mRNA sequence coding for protein regular structure contributes more to the mRNA folding stability.

Escherichia coli Proteins↗

Shannon information in complete genomes.

Shannon information in the genomes of all completely sequenced prokaryotes and eukaryotes are measured in word lengths of two to ten letters. It is found that in a scale-dependent way, the Shannon information in complete genomes are much greater than that in matching random sequences--thousands of times greater in the case of short words. Furthermore, with the exception of the 14 chromosomes of Plasmodium falciparum, the Shannon information in all available complete genomes belong to a universality class given by an extremely simple formula. The data are consistent with a model for genome growth composed of two main ingredients: random segmental duplications that increase the Shannon information in a scale-independent way, and random point mutations that preferentially reduces the larger-scale Shannon information. The inference drawn from the present study is that the large-scale and coarse-grained growth of genomes was selectively neutral and this suggests an independent corroboration of Kimura's neutral theory of evolution.

Algorithms↗

Protein structure preference, tRNA copy number, and mRNA stem/loop content.

From statistical analyses of protein sequences for humans and Escherichia coli we found that the messenger RNA segment of m-codons (for m=2 to 6) with average high tRNA copy number (TCN) (larger than approximately 10.5 for humans or approximately 1.95 for E. coli) preferably code for the alpha helix and that with low TCN (smaller than approximately 7.5 for humans or approximately 1.7 for E. coli) preferably code for coil. Between them there is an intermediate region without correlation to structure preference. For the beta strand the preference/ avoidance tendency is not obvious. All strong preference-modes of TCN for protein secondary structures have been deduced. The mutual interaction between two factors--protein secondary structural type and codon TCN--is tested by F distribution. A phenomenological model on the relation between structure preference and translational efficiency or accuracy is proposed. It is pointed out that the structure preference of codons is related to the distribution of mRNA stem/loop content in three TCN regions.

Bacterial Proteins↗

Statistical correlation between protein secondary structure and messenger RNA stem-loop structure.

A new integrated sequence-structure database, called IADE (Integrated ASTRAL-DSSP-EMBL), incorporating matching mRNA sequence, amino acid sequence, and protein secondary structural data, is constructed. It includes 648 protein domains. Based on the IADE database, we studied the relation between RNA stem-loop frequencies and protein secondary structure. It was found that the alpha-helices and beta-strands on proteins tend to be preferably "coded" by mRNA stem region, while the coils on proteins tend to be preferably "coded" by mRNA loop region. These tendencies are more obvious if we observe the structural words (SWs). An SW is defined by a four-amino-acid-fragment that shows the pronounced secondary structural (alpha-helix or beta-strand) propensity. It is demonstrated that the deduced correlation between protein and mRNA structure can hardly be explained as the stochastic fluctuation effect.

Databases as Topic↗

Shannon information in complete genomes.

Shannon information in the genomes of all completely sequenced prokaryotes and eukaryotes are measured in word lengths of two to ten letters. It is found that in a scale-dependent way, the Shannon information in complete genomes are much greater than that in matching random sequences - thousands of times greater in the case of short words. Furthermore, with the exception of the 14 chromosomes of Plasmodium falciparum, the Shannon information in all available complete genomes belong to a universality class given by an extremely simple formula. The data are consistent with a model for genome growth composed of two main ingredients: random segmental duplications that increase the Shannon information in a scale-independent way, and random point mutations that preferentially reduces the larger-scale Shannon information. The inference drawn from the present study is that the large-scale and coarse-grained growth of genomes was selectively neutral and this suggests an independent corroboration of Kimura's neutral theory of evolution.

Base Sequence↗

Splice site prediction with quadratic discriminant analysis using diversity measure.

Based on the conservation of nucleotides at splicing sites and the features of base composition and base correlation around these sites we use the method of increment of diversity combined with quadratic discriminant analysis (IDQD) to study the dependence structure of splicing sites and predict the exons/introns and their boundaries for four model genomes: Caenorhabditis elegans, Arabidopsis thaliana, Drosophila melanogaster and human. The comparison of compositional features between two sequences and the comparison of base dependencies at adjacent or non-adjacent positions of two sequences can be integrated automatically in the increment of diversity (ID). Eight feature variables around a potential splice site are defined in terms of ID. They are integrated in a single formal framework given by IDQD. In our calculations 7 (8) base region around the donor (acceptor) sites have been considered in studying the conservation of nucleotides and sequences of 48 bp on either side of splice sites have been used in studying the compositional and base-correlating features. The windows are enlarged to 16 (donor), 29 (acceptor) and 80 bp (either side) to improve the prediction for human splice sites. The prediction capability of the present method is comparable with the leading splice site detector--GeneSplicer.

Algorithms↗

Minimal model for genome evolution and growth.

Textual analysis of typical microbial genomes reveals that they have the statistical characteristics of a DNA sequence of a much shorter length. This peculiar property supports an evolutionary model in which a genome evolves by random mutation but primarily grows by random segmental duplication. That genomes grew mostly by duplication is consistent with the observation that repeat sequences in all genomes are widespread and intragenomic and intergenomic homologous genes are preponderant across all life forms.

DNA, Bacterial↗

Coding rules for amino acids in the genetic code: the genetic code is a minimal code of mutational deterioration.

Coding rules for amino acids in the genetic code are discussed from the point that the genetic code is a minimal code of mutational deterioration. The global mutational deterioration (GMD) function is defined through several parameters describing single base mutations and amino acid distances. The problem of searching for the global minimum of the GMD function is discussed in some detail. From GMD minimization under initial constraints we have succeeded in deducing the standard genetic code.

Amino Acids↗

Sequence-dependent flexibility in promoter sequences.

The non-neighbor interactions between base-pairs were taken into account to calculate the angular parameters (Omega, rho and tau) describing the orientation of successive base-pair planes and the translation parameters (D(y)) along the long axis of base-pair steps for 36 independent tetramers. A statistical mechanical model was proposed to predict the DNA flexibility that is mainly related to the thermal fluctuations at individual base-pair steps. The DNA flexibility can be described by the root-mean-square deviation of the end-to-end distance of DNA helical structure. The present model was then used to investigate the extreme flexible pattern in prokaryotic and eukaryotic promoter sequences. The results demonstrated several extreme flexible regions related to functionally important elements exist both in prokaryotic promoters and in eukaryotic promoters, DNA flexibility and AT content are highly correlated. The probabilities finding flexibility pattern in promoter sequences were also estimated statistically. The biological implications were discussed briefly.

Animals↗

Construction of genetic code from evolutionary stability.

The construction of the genetic code is investigated based on a stability principle. The concept and formulation of mutational deterioration (MD) of the genetic code is proposed. It is proved that the degeneracies of codon multiplets obey the rule to best resist MD. The MD for each ideal multiplet of codons is expressed by four parameters and it takes on a minimum value for real distributions of codons in the multiplet. Then the global mutational deterioration (GMD) of code table is calculated and the minimal code is deduced. The domain-like distribution of hydrophobic and hydrophilic amino acids on the genetic code is explained from the minimization of GMD. It is demonstrated that the standard code is approximately GMD-minimal. By introducing some constraints that are related to the initial condition of the system, we have deduced the standard genetic code from the minimization of GMD. The minimization shows the general trend of evolutionary process to some stable state while the constraints reflect a 'frozen accident.' Many deviant codon assignments are also explained through MD minimization assuming the changeable degrees of degeneracies for some multiplets. So, a possible answer to the question of "Why are synonymous codons and amino acids distributed in the code table just as they are?" is given.

Biological Evolution↗