Biomolecular Modeling

Machine learning methods are widely used in bioinformatics and computational and systems biology. Here, we review the development of machine learning methods for protein structure prediction, one of the most fundamental problems in structural biology and bioinformatics. Protein structure prediction is such a complex problem that it is often decomposed and attacked at four different levels: 1-D prediction of structural features along the primary sequence of amino acids; 2-D prediction of spatial relationships between amino acids; 3-D prediction of the tertiary structure of a protein; and 4-D prediction of the quaternary structure of a multiprotein complex. A diverse set of both supervised and unsupervised machine learning methods has been applied over the years to tackle these problems and has significantly contributed to advancing the state-of-the-art of protein structure prediction. In this paper, we review the development and application of hidden Markov models, neural networks, support vector machines, Bayesian methods, and clustering methods in 1-D, 2-D, 3-D, and 4-D protein structure predictions.

This is to certify that the project entitled "Validation of Time Series Technique for Prediction of Conformational States of Amino Acids", submitted by Mr. Nikam Sagar J. in partial fulfilment of the requirements for the degree of Master of Science in Bioinformatics, has been carried out satisfactorily by him at the CERTIFICATE This is to certify that the project entitled "Validation of Time Series Technique for Prediction of Conformational States of Amino Acids", submitted by Mr. Nikam Sagar J. in partial fulfilment of the requirements for the degree of Master of Science in Bioinformatics, has been carried out satisfactorily by her/him at the Bioinformatics Centre, University of Pune, under our guidance and supervision.

Human genome project provided infrastructure of biological information and essential information of gene sequences make it possible to predict proteins for which there is no experimental evidence. Characterization of hypothetical proteins is provided by sequence similarity with proteins of known function. Aim of this study was to describe Hypothetical proteins [Q9Y4F4, Q14166, Q9NUQ6, Q9H0W9 and Q9H0R4] in the perireticular nucleus, a key structure in human brain development. The functional domain prediction was carried out using InterPro, BLASTcds, COGs and CDART. I-TASSER server was used for tertiary structure prediction and structure comparison studies performed using VAST and DALI. This study revealed some probable functions of hypothetical proteins. These proteins were predicted to serve the functional roles in various activities like DNA -protein binding, protein modification process, ligase activity, hydrolase activity and are also involved in the metabolic processes.

This article examines the material culture of migration, focusing on migrants’ house-making projects in their countries of birth. In particular, it examines the houses built or refurbished by Albanians in their home-country, which is no longer their place of permanent residence. This is a widespread phenomenon in Albania, but it is also a frequently appearing practice amongst other international migrants. Why do migrants living outside their home-countries build houses there even though they do not plan to return? I seek to answer this question in the case of Albania by focusing empirically on the process of constructing these houses, rather than merely on the material entity of the house
as such. I propose that such ‘house-making’ by Albanian migrants is not only a simple house-building process; it also ensures a constant dwelling and dynamic ‘proxy’ presence for
migrants in their community of origin. These ethnographic observations have further significance for the anthropological study of both houses and international migration.

The preparation of sulfite biosensor by immobilization of sulfite oxidase on a glassy carbon electrode coated with mercury thin film is described. Dissolved oxygen can be readily reduced at the glassy carbon electrode coated with mercury thin film. The working principle of the biosensor was based on monitoring decrease in the peak current due to the depletion in dissolved oxygen concentration according to the reaction of sulfite oxidase.

In response to double stranded RNA (dsRNA) viruses, toll-like receptor 3 (TLR3) in fish activates signaling like human, and induces innate immunity. This suggested the existence of dsRNA binding domains in fish TLR3 as reported in higher vertebrates. In in silico analysis, leucine rich repeat (LRR) regions (4-6, 13-14, 20-22), and LRR (8-15, 17-24) were identified as key domains in rohu TLR3 as poly I:C and dsRNA of fish reovirus (AGCRV,VHSV and IHNV) binding regions. 3D-models of rohu TLR3-TIR and zebrafish TRIF were generated by homology and ab initio modeling respectively, and their interacting domains were predicted. This is the first report of TLR3 modeling in fish.

Rhizosphere region are the most nutrient rich niche among the soil environment that feeds the soil dwelling microorganisms. Totally eight isolates were obtained from the rhizosphere of sugarcane plant that were grown in agricultural fields of Vellore district. The study was further preceded for in vitro screening of plant growth promoting traits viz., production of Indole acetic acid (IAA), Hydrogen cyanide, Siderophore, solubilization of phosphate, N fixation and 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase activity of the isolates. Siderophore and phosphate solubilization were screened qualitatively on chrome azurol S and Pikovskaya agar. All the isolates exhibited positively for Tri-calcium phosphate solubilisation. The results showed that all isolates produced IAA ranging from 9.14 ± 0.27 to 32.32±0.98 µmol ml -1 in the presence of L-Tryptophan. Five isolates displayed siderophore production and none of the isolates turned positive for Hydrogen cyanide production. Only three isolates were able to cleave 1-aminocyclopropane-1-carboxylate. The bacterial isolates showed difference in plant growth promotion traits while the isolate Vsc-14 exhibited multiple plant growth promotion activity.

A two-component recombinant fusion protein antigen was re-engineered and tested as a medical counter measure against the possible biological threat of aerosolized Yersinia pestis. The active component of the proposed subunit vaccine combines the F1 capsular protein and V virulence antigen of Y. pestis and improves upon the design of an earlier histidine-tagged fusion protein. In the current study, different production strains were screened for suitable expression and a purification process was optimized to isolate an F1-V fusion protein absent extraneous coding sequences. Soluble F1-V protein was isolated to 99% purity by sequential liquid chromatography including capture and refolding of urea-denatured protein via anion exchange, followed by hydrophobic interaction, concentration, and then transfer into buffered saline for direct use after frozen storage. Protein identity and primary structure were verified by mass spectrometry and Edman sequencing, confirming a purified product of 477 amino acids and removal of the N-terminal methionine. Purity, quality, and higher-order structure were compared between lots using RP-HPLC, intrinsic fluorescence, CD spectroscopy, and multi-angle light scattering spectroscopy, all of which indicated a consistent and properly folded product. As formulated with aluminum hydroxide adjuvant and administered in a single subcutaneous dose, this new F1-V protein also protected mice from wild-type and non-encapsulated Y. pestis challenge strains, modeling prophylaxis against pneumonic and bubonic plague. These findings confirm that the fusion protein architecture provides superior protection over the former licensed product, establish a foundation from which to create a robust production process, and set forth assays for the development of F1-V as the active pharmaceutical ingredient of the next plague vaccine.

Background: Transcription factors play the crucial rule of regulating gene expression and influence almost all biological processes. Systematically identifying and annotating transcription factors can greatly aid further understanding their functions and mechanisms. In this article, we present SoyDB, a user friendly database containing comprehensive knowledge of soybean transcription factors.

The cystic fibrosis transmembrane conductance regulator (CFTR) is a transmembrane protein that functions as an ion channel. Mutations in this protein cause Cystic Fibrosis. For this reason, it is important to study the structure and function of CFTR. In this study, constructs of CFTR (C-terminii), a CFTR-interacting protein and full-length CFTR were cloned, expressed and purified for structural and functional studies. The purified C-terminal polypeptides of CFTR were soluble and shown to interact with NHERF1 PDZ 1 (a CFTR-interacting protein). The CFTR C-terminus and NHERF1 PDZ 1 domain were co-expressed and co-purified. The purified complex showed a strong interaction that might induce a conformational change. Site-directed mutation of the C-terminus of CFTR was performed in order to examine the effect of removing a potentially flexible amino acid (Arginine) on protein crystallization.

Establishing the age at which prehistoric individuals move away from their childhood residential location holds crucial information about the socio dynamics and mobility patterns in ancient societies. We present a novel combination of strontium isotope analyses performed on the over 3000 year old "Skrydstrup Woman" from Denmark, for whom we compiled a highly detailed month-scale model of her migration timeline. When combined with physical anthropological analyses this timeline can be related to the chronological age at which the residential location changed. We conducted a series of high-resolution strontium isotope analyses of hard and soft human tissues and combined these with anthropological investigations including CT-scanning and 3D visualizations. The Skrydstrup Woman lived during a pan-European period characterized by technical innovation and great social transformations stimulated by long-distance connections; consequently she represents an important part of both D...

The structure of psychrophilic chitinase (CHI II) from Glaciozyma antarctica PI12 has yet to be studied in detail. Due to its low sequence identity (<30 %), the structural prediction of CHI II is a challenge. A 3D model of CHI II was built by first using a threading approach to search for a suitable template and to generate an optimum target-template alignment, followed by model building using MODELLER9v7. Analysis of the catalytic insertion domain structure in CHI II revealed an increase in the number of aromatic residues and longer loops compared to mesophilic and thermophilic chitinases. A molecular dynamics simulation was used to examine the stability of the CHI II structure at 273, 288 and 300 K. Structural analysis of the substrate-binding cleft revealed a few exposed aromatic residues. Substitutions of certain amino acids in the surface and loop regions of CHI II conferred an increased flexibility to the enzyme, allowing for an adaptation to cold temperatures. A substrate binding comparison of CHI II with the mesophilic chitinase from Coccidioides immitis, 1D2K, suggested that the psychrophilic adaptation and catalytic activity at low temperatures were achieved through a reduction in the number of salt bridges, fewer hydrogen bonds and an increase in the exposure of the hydrophobic side chains to the solvent.

Background: As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e.~75,000 or < 0.07%) have solved tertiary structures determined by experimental techniques. The gap between protein sequence and structure continues to enlarge rapidly as the throughput of genome sequencing techniques is much higher than that of protein structure determination techniques. Computational software tools for predicting protein structure and structural features from protein sequences are crucial to make use of this vast repository of protein resources. Results: To meet the need, we have developed a comprehensive MULTICOM toolbox consisting of a set of protein structure and structural feature prediction tools. These tools include secondary structure prediction, solvent accessibility prediction, disorder region prediction, domain boundary prediction, contact map prediction, disulfide bond prediction, beta-sheet topology prediction, fold recognition, multiple template combination and alignment, template-based tertiary structure modeling, protein model quality assessment, and mutation stability prediction.

Exosome complexes are 3 to 5 exoribonucleases composed of subunits that are critical for numerous distinct RNA metabolic (ribonucleometabolic) pathways. Several studies have implicated the exosome subunits Rrp6 and Dis3 in chromosome segregation and cell division but the functional relevance of these findings remains unclear. Here, we report that, in Drosophila melanogaster S2 tissue culture cells, dRrp6 is required for cell proliferation and error-free mitosis, but the core exosome subunit Rrp40 is not. Micorarray analysis of dRrp6-depleted cell reveals increased levels of cell cycleand mitosis-related transcripts. Depletion of dRrp6 elicits a decrease in the frequency of mitotic cells and in the mitotic marker phospho-histone H3 (pH3), with a concomitant increase in defects in chromosome congression, separation, and segregation. Endogenous dRrp6 dynamically redistributes during mitosis, accumulating predominantly but not exclusively on the condensed chromosomes. In contrast, core subunits localize predominantly to MTs throughout cell division. Finally, dRrp6-depleted cells treated with microtubule poisons exhibit normal kinetochore recruitment of the spindle assembly checkpoint protein BubR1 without restoring pH3 levels, suggesting that these cells undergo premature chromosome condensation. Collectively, these data support the idea that dRrp6 has a core exosome-independent role in cell cycle and mitotic progression.

Aegle marmelos Corr. (Rutaceae) is widely used in Indian Ayurvedic medicine for the treatment of diabetes mellitus. The aqueous extract of Aegle marmelos seeds was administered orally at different doses (100, 250 and 500 mg/kg) to normal as well as sub (fasting blood glucose (FBG) normal; glucose tolerance abnormal) and mild (FBG 120–250 mg/dl) diabetic rats. The dose of 250 mg/kg was found to be most effective dose and it decreases blood glucose level (BGL) by 35.1% in normal healthy rats after 6 h of administration. The same dose also showed a marked reduction in BGL of 41.2% in sub and 33.2% in mild diabetic rats in glucose tolerance test (GTT) after 2 h. Treatment of severely (FBG >250 mg/dl) diabetic rats for 14 days with a dose of 250 mg/kg reduces the fasting blood glucose by 60.84% and urine sugar by 75% than their pretreatment levels. It brought about fall in level of total cholesterol (TC) by 25.49% with increase of 33.43% in high density lipoprotein (HDL) and decrease of 53.97 and 45.77% in low density lipoprotein (LDL) and triglyceride (TG), respectively. These results clearly indicate that aqueous seed extract of Aegle marmelos possess antidiabetic and hypolipidemic effects in diabetic rats.

S100 proteins are a family of small, EF-hand containing calcium-binding signaling proteins that are implicated in many cancers. While the majority of human S100 proteins share 25-65% sequence similarity, S100A7 and its recently identified paralog, S100A15, display 93% sequence identity. Intriguingly, however, S100A7 and S100A15 serve distinct roles in inflammatory skin disease; S100A7 signals through the receptor for advanced glycation products (RAGE) in a zinc-dependent manner, while S100A15 signals through a yet unidentified G-protein coupled receptor in a zinc-independent manner. Of the seven divergent residues that differentiate S100A7 and S100A15, four cluster in a zinc-binding region and the remaining three localize to a predicted receptor-binding surface.

A super-Arrhenius-to-Arrhenius dynamic crossover phenomenon has been observed in the translational R-relaxation time and in the inverse of the self-diffusion constant both experimentally and by simulations for lysozyme hydration water in the temperature range of T L ) 223 ( 2 K. MD simulations are based on a realistic hydrated powder model, which uses the TIP4P-Ew rigid molecular model for the hydration water. The convergence of neutron scattering, nuclear magnetic resonance and molecular dynamics simulations supports the interpretation that this crossover is a result of the gradual evolution of the structure of hydration water from a high-density liquid to a low-density liquid form upon crossing of the Widom line above the possible liquid-liquid critical point of water.

For a vast class of dynamical networks, including chemical reaction networks (CRNs) with monotonic reaction rates, the existence of a polyhedral Lyapunov function (PLF) implies structural (i.e., parameter-free) local stability. Global structural stability is ensured under the additional assumption that each of the variables (chemical species concentrations in CRNs) is subject to a spontaneous infinitesimal dissipation. This paper solves the open problem of global structural stability in the absence of the infinitesimal dissipation, showing that the existence of a PLF structurally ensures global convergence if and only if the system Jacobian passes a structural non-singularity test. It is also shown that, if the Jacobian is structurally non-singular, under positivity assumptions for the system partial derivatives, the existence of an equilibrium is guaranteed. For systems subject to positivity constraints, it is shown that, if the system admits a PLF, under structural non-singularity assumptions, global convergence within the positive orthant is structurally ensured, while the existence of an equilibrium can be proven by means of a linear programming test and the computation of a piecewise-linear-in-rate Lyapunov function.

Representing 20-30% of the human proteome, intrinsically disordered peptides (IDPs) are highly dynamic sequences that do not assume a single, defined native state under physiological conditions. These peptides are implicated as causative agents in various human neurodegenerative diseases, primarily due to their susceptibility to misfold and aggregate. Further, the ambiguous and diverse free energy landscapes for these systems challenge the validity and applicability of our computational modeling techniques, and preclude the application of many of the experimental methods we currently and proficiently use to characterize well-folded proteins. This thesis defines the ensemble structural biases and individual conformations of the monomer state of various disease-relevant IDPs through the union of simulations and experiments, in order to better understand their role in aggregation and disease pathology. Through their application to these challenging systems, this work also aims to identify previously unknown weaknesses and strengths of these biophysical techniques in order to improve their application to other systems.

The majority of this thesis investigates the amyloid β (Aβ) monomer, a prototypic IDP whose aggregates are implicated in the pathogenesis of Alzheimer’s disease (AD), a neurodegenerative disease that affects 36 million people worldwide. Relatively subtle modifications to the peptide, including a two residue change in peptide length (Aβ40 vs Aβ42) and point mutations in the Aβ sequence that are linked to familial AD (FAD), result in profound changes to the aggregation and toxicity of the peptide. We hypothesize these changes are fundamentally linked to the intrinsic disorder of monomer state; these disordered ensembles may be easily perturbed by small changes in physicochemistry, allowing them to sample new conformers that can seed different aggregates.

Here, simulations and experiment were used to describe different variants of Aβ and ascertain the nature and extent of these changes at the monomeric level. Numerous computational characterizations of Aβ monomers exist in the literature, but little consensus exists among these studies. We suspect that simulations of IDPs are particularly sensitive to the conditions of the run; as such, our approach to model Aβ emphasizes explicit representation, broad sampling, and parameter generalizability.

Here, the ensembles of Aβ were simulated using all atom models and explicit water. Further, we employed enhanced sampling through replica exchange molecular dynamics (REMD) using longer timescales than had been employed in the past. Indeed, we observe that these extensive timescales are needed to reach convergence for the emerging β structure of the Aβ monomer simulations. Further, the Aβ variants were each simulated using multiple force fields, including the state of the art OPLS-AA/TIP3P and AMBER99sb-ILDN/TIP4P-Ew combinations. We have also collected various experimental data, primarily at the atomistic level using nuclear magnetic resonance (NMR) spectroscopy. These data, including chemical shifts, J-couplings, solvent exchange rates, and pressure coefficients (measures of the sensitivity of chemical shifts to pressure), are not only observables that can be directly compared to values back-calculated from simulation to validate these runs, but also, collectively provide their own description of the secondary structure biases in the Aβ ensemble that can be compared to that of simulation.

The union between experiment and simulation with multiple force fields reveals a consistent model of Aβ supported by multiple methods. This model describes wild type Aβ40 with antiparallel β-hairpin between L17-A21 and A30-L34, while residues A21-A30 forms an intervening loop region that rarely interacts with the majority of the protein. Meanwhile, Aβ42 contributes new β-hairpin motifs involving V40-I41, with a new turn involving residue G37. These structural trends for the Aβ monomer are of particular interest because they increase the solvent exposure of hydrophobic side chains and because they correlate to intrapeptide models for oligomers and fibrils as determined by solid state NMR. This suggests that these conformations may represent the seeds of aggregation for these higher order forms.

While these trends were common to our approaches to studying Aβ, examination at finer levels revealed key inconsistencies. For example, the two force fields used here model the local structure and electrostatics of the A21-A30 central region in very different ways. Unsurprisingly, the FAD mutations we studied which lie in this region also had very different effects on the structural ensembles observed between the different force fields. Unfortunately, the available experimental data, in general, remain too coarse to inform which model, if any, is correct.

We have further attempted to assess the robustness of our simulation techniques through their application in modeling the conformational landscapes for subpeptides of SOD1 and α-synuclein, involved in the pathogenesis of amyotrophic lateral sclerosis and Parkinson’s disease, respectively. The modeled fragments were of comparable length to Aβ, and some of these are known to be intrinsically disordered. Förster resonance energy transfer (FRET) and small-angle X-ray scattering (SAXS) data were used to inform the ensemble shape of the SOD1 fragments, while NMR measurements were provided for the α-synuclein subpeptide. Unfortunately, comparison to these experimental data yielded poor agreement for these systems. The simulations of SOD1 peptides suggest that our parameters are overly predisposed to sample collapsed states. Meanwhile, simulations between different force fields yielded very different descriptions of the α-synuclein fragment, and neither representation produced observables that agreed well with experimental values. These descriptions inform important weaknesses in our simulation parameters, but also suggest that the concurrences in the characterizations made through simulation and experiment for Aβ are non-trivial.

The final chapter summarizes our findings and proposes new research directions to expand and improve our characterization of IDPs. Ongoing REMD simulations of Aβ peptides, including those run with CHARMM22*/TIP3SP parameters are also described. Simulation of Aβ40 using this CHARMM combination reduces the compaction of the ensemble, while preserving similar tertiary structure biases as the other force field combinations explored in this thesis and showing good agreement to NMR data.

The study of brain dynamics utilizes today the new features of nano-biotechnology.Neurons are connected by synapses in an electronic way, therefore we have a charge transport in the brain. Electronic systems have voltages and currents sources and complex interconnected impedances; the particular behaviour of current generates wanted voltages transformation with the same impedance. Considering the neural computation as the study of the classes of trajectories on a manifold geometry defined under appropriate
constraints, different types of brain geometries change the form of straight line and can be modeled by the electrical power. Locally a new theoretical analytical transport model is able to provide interesting predictions relatively to an appropriate use of nanomaterials for the brain. This clearly indicates that nano-modelling in bio and brain contexts requires a recovery
of the concept of natural computation.

The COMPUTATIONAL ECOLOGY AND SOFTWARE (ISSN 2220-721X) is an open access, peer-reviewed online journal that considers scientific articles in all different areas of computational ecology. It is the transactions of the International Society of Computational Ecology. The journal is concerned with the ecological researches, constructions and applications of theories and methods of computational sciences including computational mathematics, computational statistics and computer science. It features the simulation, approximation, prediction, recognition, and classification of ecological issues. Intensive computation is one of the major stresses of the journal. The journal welcomes research articles, short communications, review articles, perspectives, and book reviews. The journal also supports the activities of the International Society of Computational Ecology.

The topics to be covered by CES include, but are not limited to:

•Computation intensive methods, numerical and optimization methods, differential and difference equation modeling and simulation, prediction, recognition, classification, statistical computation (Bayesian computing, randomization, bootstrapping, Monte Carlo techniques, stochastic process, etc.), agent-based modeling, individual-based modeling, artificial neural networks, knowledge based systems, machine learning, genetic algorithms, data exploration, network analysis and computation, databases, ecological modeling and computation using Geographical Information Systems, satellite imagery, and other computation intensive theories and methods.
•Artificial ecosystems, artificial life, complexity of ecosystems and virtual reality.
•The development, evaluation and validation of software and algorithms for computational ecology. The development and evaluation of apparatus, instruments and machines for ecological and environmental analysis, investigation and monitoring based on the software of computational ecology.
•Methodological applications of computational ecology in the researches of ecology and environmental sciences.

Authors can submit their works to the email box of this journal, [email protected]. All manuscripts submitted to this journal must be previously unpublished and may not be considered for publication elsewhere at any time during review period of this journal. Authors are asked to read Author Guidelines before submitting manuscripts.

In addition to free submissions from authors around the world, special issues are also accepted. The organizer of a special issue can collect submissions (yielded from a research project, a research group, etc.) on a specific research topic, or submissions of a scientific conference for publication of special issue.

Computational Ecology and Software 
ISSN 2220-721X
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Editor-in-Chief: WenJun Zhang

Systems  genetics  is  the  interdisciplinary  field  which  deals  with  the  consequences  of genetic  variation  on  all  biomolecular  levels  of  a  biological  system.  The  aim  of  systems  genetics  is  to  understand  biological  systems  by  partitioning  variation  into  three major categories: genetic, environment and error variation, and explain how complex phenotypes arise from a combination of these three major factors across biomolecular levels.
Currently,  naturally  occurring  genetic  variation  (or  genetic  pertubation)  can  be  used to  interrogate  the  genetic  basis  of  phenotype  variation  on  many  biomolecular  levels such  as:  genetics,  transcriptomics,  proteomics  and  metabolomics. Combined  with environmental pertubation we can investigate the influence of different environments and  the  interaction  between  genetics  and  environment.  Experimental  design and advanced statistics are used to minimize and estimate error variance. To investigate all these factors influencing biological systems it is necessary to collect huge data sets on many individuals, many tissues, at all known biomolecular levels.
Modern  high-throughput  technologies  generate  large  amounts  of  genomic,
transcriptomic,  proteomic  and  metabolomic  data,  creating  a  major  challenge  in
bioinformatics  because  of  the  size  of  data  collected  and  the  multitude  of  technologies  used.  This  thesis  will  highlight  our  solutions  to  the  ‘Big  Data’  challenges  in  systems genetics.  We  propose  to  develop  smarter  more  optimized  algorithms  such  as Pheno2Geno  or  Multiple  QTL  mapping,  and  to  use  a  collaborative  approach  such  as xQTL workbench to store and analyse high-throughput systems genetics data.

Abstrak Cancer is the most dreadful disease worldwide in terms of morbidity and mortality. The exact cause of cancer development and progression is not fully known. Ocimum Basilicum (OB) or basil contains citric acid, essential oils, 1-8 sineol, arigin, anetol, flavonoid, boron, stigmasterol, eugenol, beta-carotene, magnesium and tryptophan. Works as an anticancer through phenolic compounds (caffeine acid, p-kumarat acid) which is an antiproliferative agent, which will increase the number of non-apoptotic cells in the synthesis phase in the cell cycle and decrease the number of non-apoptotic cells in the G2/M phase. While caffeine acid may cause an increase in FasL, which is a receptor of death (Fas). The existence of a complex between FasL and Fas can induce signaling that induces cell death. Phenolics have also been shown to decrease the Bcl2 antiapoptotic protein, so apoptosis does not work. Increased Bcl2 expression will be followed by an increase in Bax, which is produced because cancer cells may mutate in the p53 protein, triggering a dimer between the two and triggering apoptosis through Fas. OB extract, containing flavonoids that have an effect as a chemopreventive agent by protecting lymphocytes from cancer induction. Another compound is the essential oil (terpenoid) that can inhibit tumor by improving the performance of Human Natural Killer in immune system (immunostimulan), so as to destroy tumor cells and increase macrophage cells that act as the phagocytes of damaged cells. In this review will be discussed about the role of OB in the natural treatment of cancer and the working mechanisms involved in it.

""(EN)Compositions are disclosed containing a solvated viscoelastic polymeric gel diluted into an ionically conductive aqueous solution which can be usefully applied to any surface that is hydrophobic to act, for example, as an antifogging coating with minimal optical distortion and excellent transparency. The compositions can also be used as lubricious agents on medical implants, shunts, and surgical supplies to minimize tissue trauma, to maximize bio-compatibility, and to increase healing by enhancing better irrigation and flow in adjacent tissue.
(FR)L'invention porte sur des compositions contenant un gel polymère viscoélastique solvaté, dilué dans une solution aqueuse ioniquement conductrice qui peut être utilement appliquée sur toute surface qui est hydrophobe, pour servir, par exemple, de revêtement antibuée avec une distorsion optique minimale et une excellente transparence. Les compositions peuvent également être utilisées en tant qu'agents lubrifiants sur des implants médicaux, des dérivations, et des fournitures chirurgicales, pour rendre minimal le traumatisme tissulaire, pour rendre maximale la biocompatibilité et pour augmenter la cicatrisation par une meilleure irrigation et une amélioration de la circulation dans le tissu adjacent""

Establishing the age at which prehistoric individuals move away from their childhood residential location holds crucial information about the socio dynamics and mobility patterns in ancient societies. We present a novel combination of strontium isotope analyses performed on the over 3000 year old &quot;Skrydstrup Woman&quot; from Denmark, for whom we compiled a highly detailed month-scale model of her migration timeline. When combined with physical anthropological analyses this timeline can be related to the chronological age at which the residential location changed. We conducted a series of high-resolution strontium isotope analyses of hard and soft human tissues and combined these with anthropological investigations including CT-scanning and 3D visualizations. The Skrydstrup Woman lived during a pan-European period characterized by technical innovation and great social transformations stimulated by long-distance connections; consequently she represents an important part of both D...

TiO 2 thin films were deposited on unheated and heated glass substrates at an elevated sputtering pressure of 3 Pa by radio frequency (RF) reactive magnetron sputtering. TiO 2 films deposited at room temperature were annealed in air for 1 h at various temperatures ranging from 300 to 600 °C. The structural and optical properties of the thin films were investigated using X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM) and ultraviolet-visible-near infrared (UV-VIS-NIR) spectrophotometry. XRD results show that as-grown and post-annealed TiO 2 films have anatase crystal structure. Higher substrate and annealing temperatures result in a slight increase of crystallinity. TiO 2 films deposited at different substrate temperatures exhibit high visible transmittance and the transmittance decreases slightly with an increase in annealing temperature. The refractive indices (at λ = 550 nm) of the as-deposited and annealed films are found to be in the range of 2.31-2....

BackgroundRecently, HEN1 protein from Arabidopsis thaliana was discovered as an essential enzyme in plant microRNA (miRNA) biogenesis. HEN1 transfers a methyl group from S-adenosylmethionine to the 2&#x27;-OH or 3&#x27;-OH group of the last nucleotide of miRNA/miRNA* duplexes produced by the nuclease Dicer. Previously it was found that HEN1 possesses a Rossmann-fold methyltransferase (RFM) domain and a long N-terminal extension including a putative double-stranded RNA-binding motif (DSRM). However, little is known about the details of the structure and the mechanism of action of this enzyme, and about its phylogenetic origin.ResultsExtensive database searches were carried out to identify orthologs and close paralogs of HEN1. Based on the multiple sequence alignment a phylogenetic tree of the HEN1 family was constructed. The fold-recognition approach was used to identify related methyltransferases with experimentally solved structures and to guide the homology modeling of the HEN1 ca...