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arXiv2019

Towards peptide strings pharmacology

Peptide strings have been developed as a concept for the past fourteen years. They are proposed to basically entail various quantum states engendered by the physical interactions of proteins containing peptide portions that are similar to one another and, moreover, amino acid sequences that are sterically complementary to each other. In this survey, additional insights are presented that support the notion that peptide strings are likely a biophysical phenomenon that warrants further investigations. Specifically, these putative peptide strings traits are the capacity for wave-like interferences and electric current-like properties. Therefore, future experimental validation and quantification of these predicted features as well as application of this potential energy that is stored in the distinct shapes of proteins and peptides may prove beneficial in addressing challenges in physics and medicine. Within the latter field, the key discipline of pharmacology should be most fundamentally advanced by the peptide strings approach.

q-bio.OT↗

arXiv2019

Biophysics at the coffee shop: lessons learned working with George Oster

Over the past 50 years, the use of mathematical models, derived from physical reasoning, to describe molecular and cellular systems has evolved from an art of the few to a cornerstone of biological inquiry. George Oster stood out as a pioneer of this paradigm shift from descriptive to quantitative biology not only through his numerous research accomplishments, but also through the many students and postdocs he mentored over his long career. Those of us fortunate enough to have worked with George agree that his sharp intellect, physical intuition and passion for scientific inquiry not only inspired us as scientists but also greatly influenced the way we conduct research. We would like to share a few important lessons we learned from George in honor of his memory and with the hope that they may inspire future generations of scientists.

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arXiv2019

CoHSI V: Identical multiple scale-independent systems within genomes and computer software

A mechanism-free and symbol-agnostic conservation principle, the Conservation of Hartley-Shannon Information (CoHSI) is predicted to constrain the structure of discrete systems regardless of their origin or function. Despite their distinct provenance, genomes and computer software share a simple structural property; they are linear symbol-based discrete systems, and thus they present an opportunity to test in a comparative context the predictions of CoHSI. Here, without any consideration of, or relevance to, their role in specifying function, we identify that 10 representative genomes (from microbes to human) and a large collection of software contain identically structured nested subsystems. In the case of base sequences in genomes, CoHSI predicts that if we split the genome into n-tuples (a 2-tuple is a pair of consecutive bases; a 3-tuple is a trio and so on), without regard for whether or not a region is coding, then each collection of n-tuples will constitute a homogeneous discrete system and will obey a power-law in frequency of occurrence of the n-tuples. We consider 1-, 2-, 3-, 4-, 5-, 6-, 7- and 8-tuples of ten species and demonstrate that the predicted power-law behavior is emphatically present, and furthermore as predicted, is insensitive to the start window for the tuple extraction i.e. the reading frame is irrelevant. We go on to provide a proof of Chargaff's second parity rule and on the basis of this proof, predict higher order tuple parity rules which we then identify in the genome data. CoHSI predicts precisely the same behavior in computer software. This prediction was tested and confirmed using 2-, 3- and 4-tuples of the hexadecimal representation of machine code in multiple computer programs, underlining the fundamental role played by CoHSI in defining the landscape in which discrete symbol-based systems must operate.

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arXiv2019

A clinical update on Antibiotic Resistance Gram-negative bacteria in Malaysia- a review

Antibiotics are the wonder discoveries to combat microbes. For decades, multiple varieties of antibiotics have been used for therapeutic purposes in hospital settings and communities throughout the world. Unfortunately, bacteria have become resistant to commonly prescribed antibiotics. This review aims to explore the development, challenges, and the current state of antibiotic resistance available literature in Malaysia. This review aims to explore the development, challenges, and the current state of antibiotic resistance available literature in Malaysia. This review reiterates the antibiotic resistance among the gram-negative bacteria is increasing and they are becoming resistant to nearly all groups of antibiotics. The antibiotic treatments are minimal and hard to treat in multi-drug resistance bacterial infection, resulting in morbidity and mortality. The prevalence rate of antibiotic resistance from the literature suggests that educating patients and the public is essential to prevent and control the spread of antibiotic resistance. In particular, there is an urgent need for a surveillance system of regular monitoring on the microbiomes, the discovery of novel antibiotics and therapeutic application of antibiotics are mandatory.

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arXiv2019

Revising the Wilks Scoring System for pro RAW Powerlifting

Purpose: In powerlifting the total result is highly dependent on the athletes bodyweight. Powerlifting is divided to equipped and RAW types. Pro RAW powerlifting competitions use the Wilks scoring system to compare and rank powerlifting results across bodyweights, to choose the winners. The Wilks formulas are 5th order polynomials fitted to equipped powerlifting results from the years 1987 - 1994. The Wilks formulas were meant to be updated every 2 to 5 years, but have never been revised. This study aims to update the Wilks scoring system for use in pro RAW powerlifting. Methods: The 10 highest RAW powerlifting totals per weight class for bodyweights 60 - 175 kg for men, and 44 kg and up for women, were collected from the openpowerlifting.org database. Polynomials were fitted to these data separately for men and women, using polynomial regression. The scores for men and women were calculated using these fits, and the results are assessed. Results: 4th order polynomials were chosen for best describing the dependence of powerlifting total result on bodyweight. The mens scores were normalized to 500 points, and womens to 455 points, on those fitted curves, to bring the top scores to the same level across weight classes of each sex. These scores appeared similar across the different weight classes for both men and women. This even scoring across body weights is here considered the single most important characteristic of a scoring system for pro competitions. Key words: Wilks score, revised prediction curve, polynomial regression, powerlifting

stat.AP↗

arXiv2019

Measurement of trace elements in five popular medicinal plants using Instrumental Neutron Activation Analysis method (INAA) in Arak, Iran

In this work, the specific mass of twelve elements were determined in five of the most commonly used medicinal plants as Caraway (Carum carvi), Savory (Satureia hortensis), Purslane (Portulaca oleracea), Fenugreek (Trigonella foenum-graecum) and Milk thistle (Silibum marianum) prepared from herbal pharmacies. Multi elemental Instrumental Neutron Activation Analysis (INAA) method was applied to analyze the samples. Tehran research reactor was used as a neutron source and gamma ray spectra registered using high purity germanium (HPGe) detector. Among analyzed samples, highest concentrations of Fe (8789 ppm), Cr (8 ppm) and Na (517 ppm) were found in Caraway. Maximum levels of Mn (95 ppm), Cl (3702 ppm), Ca (18328 ppm) , K (21562 ppm) and V (2.7 ppm) were detected in Savory and Fenugreek contains the lowest concentrations of Fe (195 ppm), Zn (13 ppm), Ca (2243 ppm), Al (99ppm), Mn (26 pm) and Mg (177ppm).

q-bio.OT↗

arXiv2019

Detection of Metallo-\b{eta}-Lactamases-Encoding Genes Among Clinical Isolates of Escherichia Coli in a Tertiary Care Hospital, Malaysia

The multidrug resistant Escherichia coli strains causes multiple clinical infections and has become a rising problem globally. The metallo-\b{eta}-lactamases encoding genes are very severe in gram-negative bacteria especially E. coli. This study was aimed to evaluate the prevalence of MBLs among the clinical isolates of E. coli. A total of 65 E. coli isolates were collected from various clinical samples of Malaysian patients with bacterial infections. The conventional microbiological test was performed for isolation and identification of E. coli producing MBLs strains in this vicinity. Multidrug Resistance (MDR) of E. coli isolates were assessed using disk diffusion test. Phenotypic methods, as well as genotypic- PCR methods, were performed to detect the presence of metallo-\b{eta}-lactamase resistance genes (blaIMP, blaVIM) in imipenem resistant strains. Out of 65 E. coli isolates, 42 isolates (57.3%) were MDR. The isolates from urine (19) produced significantly more MDR (10) isolates than other sources. Additionally, 19 (29.2%) imipenem resistant E. coli isolates contained 10 MBLs gene, 7(36.8%) isolates contained blaIMP and 3(15.7%) isolates contained blaVIM genes. This study revealed the significant occurrence of MBL producing E. coli isolates in clinical specimens and its association with health risk factors indicating an alarming situation in Malaysia. It demands an appropriate concern to avoid failure of treatments and infection control management.

q-bio.OT↗

arXiv2019

Base spacing distribution analysis for human genome

The distribution of bases spacing in human genome was investigated. An analysis of the frequency of occurrence in the human genome of different sequence lengths flanked by one type of nucleotide was carried out showing that the distribution has no self-similar (fractal) structure. The results nevertheless revealed several characteristic features: (i) the distribution for short-range spacing is quite similar to the purely stochastic sequences; (ii) the distribution for long-range spacing essentially deviates from the random sequence distribution, showing strong long-range correlations; (iii) the differences between (A, T) and (C, G) bases are quite significant; (iv) the spacing distribution displays tiny oscillations.

q-bio.OT↗

arXiv2019

Effect of E-cigarette Use and Social Network on Smoking Behavior Change: An agent-based model of E-cigarette and Cigarette Interaction

Despite a general reduction in smoking in many areas of the developed world, it remains one of the biggest public health threats. As an alternative to tobacco, the use of electronic cigarettes (ECig) has been increased dramatically over the last decade. ECig use is hypothesized to impact smoking behavior through several pathways, not only as a means of quitting cigarettes and lowering risk of relapse, but also as both an alternative nicotine delivery device to cigarettes, as a visible use of nicotine that can lead to imitative behavior in the form of smoking, and as a gateway nicotine delivery technology that can build high levels of nicotine tolerance and pave the way for initiation of smoking. Evidence regarding the effect of ECig use on smoking behavior change remains inconclusive. To address these challenges, we built an agent-based model (ABM) of smoking and ECig use to examine the effects of ECig use on smoking behavior change. The impact of social network (SN) on the initiation of smoking and ECig use were also explored. Findings from the simulation suggest that the use of ECig generates substantially lower prevalence of current smoker (PCS), which demonstrates the potential for reducing smoking and lowering the risk of relapse. The effects of proximity-based influences within SN increases the prevalence of current ECig user (PCEU). The model also suggests the importance of improved understanding of drivers in cessation and relapse in ECig use, in light of findings that such aspects of behavior change may notably influence smoking behavior change and burden.

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arXiv2019

The challenges of purely mechanistic models in biology and the minimum need for a 'mechanism-plus-X' framework

Ever since the advent of molecular biology in the 1970s, mechanical models have become the dogma in the field, where a "true" understanding of any subject is equated to a mechanistic description. This has been to the detriment of the biomedical sciences, where, barring some exceptions, notable new feats of understanding have arguably not been achieved in normal and disease biology, including neurodegenerative disease and cancer pathobiology. I argue for a "mechanism-plus-X" paradigm, where mainstay elements of mechanistic models such as hierarchy and correlation are combined with nomological principles such as general operative rules and generative principles. Depending on the question at hand and the nature of the inquiry, X could range from proven physical laws to speculative biological generalizations, such as the notional principle of cellular synchrony. I argue that the "mechanism-plus-X" approach should ultimately aim to move biological inquiries out of the deadlock of oft-encountered mechanistic pitfalls and reposition biology to its former capacity of illuminating fundamental truths about the world.

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arXiv2019

Review: dual benefits, compositions, recommended storage, and intake duration of mother's milk

Breastfeeding benefits both infants and mothers. Nutrients in mother's milk help protect infants from multiple diseases including infections, cancers, diabetes, gastrointestinal and respiratory diseases. We performed literature mining on 31,496 mother's-milk-related abstracts from PubMed and the results suggest the need for individualized mother's milk fortification and proper maternal supplementations (e.g. probiotics, vitamin D), because mother's milk compositions (e.g. fatty acids) vary according to maternal diet and responses to infection in mothers and/or infants. We review at details the variability observed in mother's milk compositions and its possible health effects in infants. We also review the effects of storage practices on mother's milk nutrients, recommended durations for mother's milk intake and the associated health benefits.

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arXiv2019

Measuring Time with Minimal Clocks

Being able to measure time, whether directly or indirectly, is a significant advantage for an organism. It allows for the timely reaction to regular or predicted events, reducing the pressure for fast processing of sensory input. Thus, clocks are ubiquitous in biology. In the present paper, we consider minimal abstract pure clocks in different configurations and investigate their characteristic dynamics. We are especially interested in optimally time-resolving clocks. Among these, we find fundamentally diametral clock characteristics, such as oscillatory behavior for purely local time measurement or decay-based clocks measuring time periods of a scale global to the problem. We include also sets of independent clocks ("clock bags"), sequential cascades of clocks and composite clocks with controlled dependency. Clock cascades show a "condensation effect" and the composite clock shows various regimes of markedly different dynamics.

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arXiv2019

Investigating some attributes of periodicity in DNA sequences via semi-Markov modelling

DNA segments and sequences have been studied thoroughly during the past decades. One of the main problems in computational biology is the identification of exon-intron structures inside genes using mathematical techniques. Previous studies have used different methods, such as Fourier analysis and hidden-Markov models, in order to be able to predict which parts of a gene correspond to a protein encoding area. In this paper, a semi-Markov model is applied to 3-base periodic sequences, which characterize the protein-coding regions of the gene. Analytic forms of the related probabilities and the corresponding indexes are provided, which yield a description of the underlying periodic pattern. Last, the previous theoretical results are illustrated with DNA sequences of synthetic and real data.

stat.AP↗

arXiv2019

A Model-Theoretic Approach to Modular Implementation, with Application to Biological Systems

We present a method for logical specification of the behavior of a system based on the specification of its components and for representing and specifying the effect of a class of communication "signaling pathways" among them. Variations in the actions and effects (semantics) of the pathways can be seen in the resulting system. We show how to "enrich" the behavior of the original components by exactly what is provided by the signaling pathways. This has the potential to allow a formal proof of a property of the system as a whole, or a formal diagnosis why a system of communicating modules may not satisfy a desired specification, and if and how it can be "fixed." There are five distinct stages in our view: 1. A description of the connections between potential components at the level of which potential modules are connected. 2. Specific choices for those modules 3. An "elaboration" of the connections among different modules to connections among members of those different modules 4. A description of the semantics of those connections (what they actually do) 5. A "padding" of the modules chosen in step 2 to allow for the action of the connections (step 3), as described in step 4. The formalism is completely hierarchical -- in other words, the formalism works equally for the system as a whole, for each of the modules, and for any larger system in which the original system is a component. As it turns out, for whatever reason -- perhaps evolutionary advantage optimization at the right level of abstraction -- many biological systems are hierarchically modular, with the modules communicating via various pathways. Thus, a formalism such as the one presented here could have application to questions in biology.

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arXiv2019

Deep learning languages: a key fundamental shift from probabilities to weights?

Recent successes in language modeling, notably with deep learning methods, coincide with a shift from probabilistic to weighted representations. We raise here the question of the importance of this evolution, in the light of the practical limitations of a classical and simple probabilistic modeling approach for the classification of protein sequences and in relation to the need for principled methods to learn non-probabilistic models.

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arXiv2022

On the theoretical prediction of microalgae growth for parallel flow

The established microalgae growth models are semi-empirical or considerable fitting coefficients exist currently. Therefore, the ability of the model prediction is reduced by the numerous fitting coefficients. Furthermore, the predicted results of the established models are dependent on the size of the photobioreactor (PBR), light intensity, flow and concentration field. The growth mechanism of microalgae has not clearly understood in PBR cultivation. It is difficult to predict the microalgae growth by theoretical methods, owing to the aforementioned factors. We developed an exploratory bridging microalgae growth model to predict the microalgae growth rate in PBRs by using the nondimensional method which is effectively in fluid dynamics and heat transfer. The analytical solution of the growth rate was obtained for the parallel flow. The nondimensional growth rate expressed as function of Reynolds number and Schmidt number, which can be used for arbitrary parallel flow due to the solution was expressed as nondimensional quantities. The theoretically predicted growth rate is compared with the experimentally measured microalgae growth rate on the order of magnitude. The nondimensional method successfully applied to the microalgae growth problem for the first time. The general nondimensional solution can unify the numerous experimental data for different laboratory conditions, and give a direction for the disorder of the microalgae growth problem. The nondimensional solution may be useful to explain the growth mechanism of microalgae and design large-scale PBRs for microalgae biofuel production. The significance of the work is to give a theoretical foundation and methodology of biological theory of microalgae growth.

physics.bio-ph↗

arXiv2019

A New Framework For Spatial Modeling And Synthesis of Genome Sequence

This paper provides a framework in order to statistically model sequences from human genome, which is allowing a formulation to synthesize gene sequences. We start by converting the alphabetic sequence of genome to decimal sequence by Huffman coding. Then, this decimal sequence is decomposed by HP filter into two components, trend and cyclic. Next, a statistical modeling, ARIMA-GARCH, is implemented on trend component exhibiting heteroskedasticity, autoregressive integrated moving average (ARIMA) to capture the linear characteristics of the sequence and later, generalized autoregressive conditional heteroskedasticity (GARCH) is then appropriated for the statistical nonlinearity of genome sequence. This modeling approach synthesizes a given genome sequence regarding to its statistical features. Finally, the PDF of a given sequence is estimated using Gaussian mixture model and based on estimated PDF, we determine a new PDF presenting sequences that counteract statistically the original sequence. Our strategy is performed on several genes as well as HIV nucleotide sequence and corresponding results is presented.

q-bio.OT↗

arXiv2019

Antibacterial and antifungal activity of various extracts of Bacopa monnieri

Bacopa monnieri was also known as Brahmi. Theses plant has been considered as medicinal plants in Ayurvedic systems for centuries. This present study was carried out to evaluate the antibacterial and antifungal properties of ethanolic, diethyl ether, ethyl acetate, and aqueous extracts of B. monnieri. Agar disc diffusion tests were carried out to determine the antimicrobial effects of ethanolic, diethyl ether, ethyl acetate and aqueous extracts of B. monnieri against Gram-positive (Staphylococcus aureus ATCC 25923), Gram-negative (Escherichia coli ATCC 25922) bacterial strains and antifungal strains (Aspergillus flavus, and Candida albicans). Among the various extracts, diethyl ether extracts of B. monnieri has an antibacterial potency against Staphylococcus aureus (gram positive), and ethyl acetate extract showed effects on E. coli (gram negative) at higher concentrations of 300 microgam mL-1. The ethanolic extract has potent antifungal activity against the fungus (Aspergillus flavus, and Candida albicans) compared to diethyl ether and ethyl acetate-ether. Both extracts (diethyl ether and ethyl acetate) has a minimum antifungal effect while these extracts showed more inhibitory effects on tested bacteria. Inhibitory effects of the aqueous extract were not observed at all concentration (100 microgam mL-1, 200 microgam mL-1and 300 microgam mL-1) against the entire examined bacterial and fungal species. The finding of this study indicates the antibacterial and antifungal activity exhibited by the ethanolic, diethyl ether, and ethyl acetate extract of B. monnieri can be validated to the management of medicinal plant throughout the world.

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