Network pharmacology integrated molecular docking of fucoidan against oral cancer and in vitro evaluation- A study using GEO datasets.

Oral cancer is a widespread health concern in rural India due to a lack of awareness, delayed diagnosis and limited access to affordable treatment options. The current chemotherapy has notable side effects, underscoring the need for new drug candidates with improved bioavailability and specificity. In this current research, fucoidan, a sulphated polysaccharide, was extracted from the brown algae Spatoglossum asperum, and shown to be cytotoxic in vitro against oral cancer cells (KB cell line) at an IC50 of 107.76 µg/ml, suggesting its potential as a drug candidate. This study further aimed to explore the potential therapeutic implications of fucoidan in managing oral cancer using network pharmacology. PharmMapper, Comparative Toxicogenomics Database and SuperPred were initially used to identify fucoidan protein targets. The identified targets were further screened against Gene Expression Omnibus (GSE23558, GSE25099 and GSE146483), OMIM, TCGA and GeneCards datasets to identify oral cancer-specific protein targets. The interactions between the selected proteins were visualised using STRING and Cytoscape. Subsequently, Database for Annotation, Visualization and Integrated Discovery was used for gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of candidate targets. The cancer-related network was assessed using CancerGeneNet, while life expectancy based on the expression of the top 10 CytoHubba ranked hub genes was evaluated using Kaplan-Meier plots. Finally, EGFR, AKT1, HSP90AA1 and SRC were selected for docking and molecular dynamics simulation with fucoidan, using Maestro and GROMACS, respectively.Communicated by Ramaswamy H. Sarma.

Structural and Functional Characterization of Exopolysaccharide Produced by a Novel Isolate Bacillus sp. EPS003.

An exopolysaccharide (EPS)-producing soil bacterium was isolated and characterized using 16S rRNA as Bacillus sp. EPS003. EPS was precipitated using ethanol and % composition of total carbohydrate, and protein was determined. Monosaccharide composition was identified using thin layer chromatography (TLC), and it was found to be a levan. Fourier transform infrared (FTIR) spectrum revealed the peaks for carboxyl, hydroxyl, and amide functional groups. 1H nuclear magnetic resonance (NMR) spectrum further confirmed the presence of fructose monomer. Field emission scanning electron microscopic images (FE-SEM) revealed porous and amorphous characteristics of EPS which was further confirmed with broad peaks in X-ray diffraction (XRD) spectrum. Elemental composition was determined using energy-dispersive X-ray analysis (EDAX). Thermogravimetric analysis (TGA) of EPS resulted in a residual mass of 33.81% at 548 °C indicating high thermal stability. In addition, solubility index and water-holding capacity of EPS were found to be 56% and 264%, respectively, making EPS suitable for various applications. Further, antioxidant potential of EPS was studied using hydroxyl and DPPH radical scavenging assays. In vitro cytotoxicity assessment using L929 cells and SK-MEL-3 cell lines clearly indicated that the EPS produced by the novel isolate Bacillus sp. EPS003 could serve as a potential anticancer agent.

Sustainable approaches on industrial food wastes to value-added products - A review on extraction methods, characterizations, and its biomedical applications.

The concept of zero waste discharge has been gaining importance in recent years towards attaining a sustainable environment. Fruit processing industries generate millions of tons of byproducts like fruit peels and seeds, and their disposal poses an environmental threat. The concept of extracting value-added bioactive compounds from bio-waste is an excellent opportunity to mitigate environmental issues. To date, significant research has been carried out on the extraction of essential biomolecules, particularly polysaccharides from waste generated by fruit processing industries. In this review article, we aim to summarize the different extraction methodologies, characterization methods, and biomedical applications of polysaccharides extracted from seeds and peels of different fruit sources. The review also focuses on the general scheme of extraction of polysaccharides from fruit waste with special emphasis on various methods used in extraction. Also, the various types of polysaccharides obtained from fruit processing industrial wastes are explained in consonance with the important techniques related to the structural elucidation of polysaccharides obtained from seed and peel waste. The use of seed polysaccharides as pharmaceutical excipients and the application of peel polysaccharides possessing biological activities are also elaborated.

Artificial neural network modeling and statistical optimization of medium components to enhance production of exopolysaccharide by Bacillus sp. EPS003.

Microbial Exopolysaccharides (EPS) have a wide range of applications in food, cosmetics, agriculture, pharmaceutical industries, and environmental bioremediation. The present study aims at enhancing the production of EPS from a soil-isolate Bacillus sp. EPS003. Effects of carbon and nitrogen sources and process conditions were evaluated one factor at a time. Box-Behnken design has been used and a 2.5-fold increase in yield is reported after optimizing the most influential parameters sucrose, yeast extract, and peptone as identified by the Plackett-Burman method. An artificial neural network (ANN) with two different topologies (EPS-NN1 and EPS-NN2) was developed. On comparing prediction accuracy, EPS-NN2 formulated as one input layer with four input variables (sucrose, yeast extract, peptone, biomass), a single hidden layer with seven neurons and EPS yield in the output layer showed a high coefficient of determination (R2-0.98) and low error (NRMSE-0.024). This study concludes that the consideration of biomass value has increased the prediction accuracy of the model.

Determinants of patients' delay with disability in the diagnosed leprosy cases in the three major states of India: A case-control study.

BACKGROUND: Skin lesions are the most common early symptoms of leprosy, often ignored by patients at an early stage and misdiagnosed as other dermatological diseases by healthcare personnel, leading to delay in diagnosis and treatment of leprosy precipitating permanent neurological deficit, deformities and serious disabilities. AIMS: The objective is to evaluate the duration of delay and factors responsible for the delay in reporting of patients, among the newly detected leprosy cases (Grade 1 and Grade 2 disability patients). METHODS: A case-control study was conducted during 2014-2016 in three major states of India (Delhi, Gujarat and West Bengal) in 140 randomly recruited newly registered adult leprosy patients (aged 18 years and above) with Grade 2/1 disabilities (cases) and 140 Grade 0 disability patients (controls) in each of these Indian states. RESULTS: It is established that the major contributors for the delay in the early diagnosis of leprosy have been patient-related factors. The median patient delay in the three states of Delhi, Gujarat and West Bengal were five months (0.7-1.8), 2.8 months (2-14) and 12 months (2-24), respectively. LIMITATIONS: The study design is case-control and has an inbuilt reporting bias due to the retrospective nature of data collection but the data collection was carried with caution to reduce the recall bias. As the study is carried out in three states, generalisation of interpretation was cautiously executed. The matching ratio of cases and controls was 1:1 in this study, but we could not increase the controls due to operational feasibility during the conduct of the study. CONCLUSION: Patient delay is a crucial factor responsible for the disability among new leprosy cases. A higher patient delay in these three states reflects that the community is not aware about the signs and symptoms of leprosy. Reducing patient delay is very important for reducing disabilities in the newly diagnosed cases.

An insight into the mental health needs of the common public of Tamil Nadu, India, subjected to COVID-19 lockdown, a rare unprecedented crisis.

Purpose: COVID-19, a major "Public Health Emergencies of International Concern", had sought greater attention among researchers to study its pathogenesis, associated complications and management. However, there are only few studies that had studied its potential impact on mental health of general public, who are subjected to social distancing, community lockdown and restrictions in their routine activities. Objectives: The aim of this study is to assess the prevalence of psychological distress and mental health needs among general public in Tamil Nadu subjected to lockdown, social distancing amidst COVID-19 crisis. Tamil Nadu is one of the worst affected states of southern India. Methods: A self-administered, web-based application study using "WHO-Self Reported Questionnaire-20", in bilingual version, both English and Tamil, is used to screen the public for the level of distress. The study is done while the state is under extended lockdown and restricted movement. Key findings: A total of 918 respondents participated in the survey and it is found that about more than one third of the respondents (∼35%) are under psychological distress. A significant association between younger age group, female gender, unmarried, people with children are found to be under distress. The lockdown had increased the frequency of smoking and quantity of cigarettes among smokers, also has increased the frequency of drinking among alcohol consumers. Of the SRQ-20 items recorded, stress related neurotic symptoms (> 70%) was observed more than the depressive mood. About 33% of those scored > 7, had suicidal tendency. The districts declared red zones had significantly reported a greater number of respondents under distress. Conclusion: Besides effectively mitigating the COVID-19 crisis, in terms of prevention, control and treatment strategies, it is prerogative to effectively manage fear, distress due to the COVID-19 and associated anxiety and depression among the public.

But: Le COVID-19, une importante « Urgence de santé publique de portée internationale ¼, a demandé une plus grande attention des chercheurs pour étudier sa pathogenèse, les complications associées et la prise en charge. Cependant, rares sont les études qui ont étudié son impact potentiel sur la santé de la population, qui est soumise à l'éloignement social, au confinement communautaire et à des restrictions dans ses activités courantes. Objectifs: Le but de cette étude est d'évaluer la prévalence de la détresse psychologique et des besoins de santé mentale dans la population du Tamil Nadu soumise au confinement, à la distanciation sociale au milieu de la crise du COVID-19. Le Tamil Nadu est l'un des États les plus touchés du sud de l'Inde. Méthodes: Une étude d'application auto-administrée en ligne utilisant le « WHO-Self Reported Questionnaire-20 ¼, en version bilingue, en anglais et en tamoul, est utilisée pour dépister le niveau de détresse. L'étude est effectuée alors que l'État est sous confinement prolongé et mouvements restreints. Principales conclusions: Sur les 918 répondants qui ont participé à l'enquête, on constate qu'environ plus d'un tiers des répondants (∼35%) sont en détresse psychologique. Les plus jeunes, les femmes, les célibataires, les personnes avec enfants se trouvent en situation de détresse de façon significative. Le confinement a augmenté la fréquence du tabagisme et la quantité de cigarettes chez les fumeurs, a également augmenté la fréquence de consommation d'alcool chez les consommateurs d'alcool. Parmi les items SRQ-20 enregistrés, les symptômes névrotiques liés au stress (> 70 %) ont été plus observés que l'humeur dépressive. Environ 33 % des sujets, ayant obtenu un score supérieur à 7, avaient une tendance suicidaire. Les districts déclarés zone rouge avaient notablement signalé un plus grand nombre de répondants en détresse. Conclusion: En plus d'atténuer efficacement la pandémie du COVID-19, en termes de stratégies de prévention, de contrôle et de traitement, il est capital de gérer efficacement la peur, la détresse due au COVID-19, l'anxiété et la dépression associées et d'étendre le soutien psychosocial au public.

Detrimental Pneumoperitoneum and Bowel Necrosis Secondary to Dilatation and Curettage: Necessitating the Importance of Healthcare Awareness.

We have read about numerous cases depicting life-threatening fatalities due to the lack of awareness and accessibility to health care facilities. A 23-year-old pregnant woman in a village in India underwent a dilation and curettage procedure for spontaneous abortion by an uncertified medical practitioner. Eventually, she presented to the emergency room with ER and an initial abdominal X-ray was consistent with the finding of free air under the diaphragm/pneumoperitoneum and air-fluid levels. Here we present a case of bowel perforation secondary to being strangulated within the uterine cavity.

In silico structure prediction, molecular docking and dynamic simulation studies on G Protein-Coupled Receptor 116: a novel insight into breast cancer therapy.

G Protein-Coupled Receptor gains more importance in cancer research; because of their key role in several physiologic functions of cells. However, most of the GPCR's are orphan receptors, this hampers the finding of drugs against GPCR. G Protein-Coupled Receptor 116 is an adhesion orphan receptor that intensifies the invasion of cells in Triple-Negative Breast Cancer. In this study, existing FDA approved anticancer drugs were chosen as ligands and molecular docking was performed using in silico protein model of GPR116. Molecular interaction was analyzed carefully to identify the crucial amino acids present in binding pocket. Molecular dynamics simulations study executed to verify the structural and dynamic properties of Doxorubicin-GPR116 protein complex. The results have shown that Doxorubicin, Neratinib maleate, Epirubicin, and Lapatinib Ditosylate have good interaction with GPR116 binding site. Tyrosine 195 (Y195), Cysteine 196 (C196), Argenine 197 (R197), and Tryptophan 100 (W100) are commonly found in the majority of ligand-target interaction, hence based on the computational studies selective amino acids might be crucial for functional properties. Further to confirm crucial amino acids, computational mutation studies were executed. Molecular docking analysis with mutated GPR116 disclosed that significant variation in G score compared withligand-native protein interaction. Hence, the theoretical confirmatory structural properties changes support to prove selective crucial amino acids play the significant role in ligand binding. Molecular dynamic simulation results reveal that the interaction was stable throughout the MD simulation. To the best of our prognosis, GPR116 could be the best molecular target for breast cancer drug discovery.Communicated by Ramaswamy H. Sarma.

In silico molecular docking and physicochemical property studies on effective phytochemicals targeting GPR116 for breast cancer treatment.

G protein-coupled receptor 116 (GPR116), an orphan adhesion receptor, found an important role in cell adhesion and migration in eukaryotes. Abnormal expression of GPCR identified in various cancers turns focus of research community towards GPCR to identify the targeting drug against GPCR. Though GPR116 role was studied in progression of metastasis in triple-negative breast cancer (TNBC), unfortunately, still no drugs targeting GPR116 were identified. TNBC is a hormone-negative aggressive breast cancer found even in young women. Since TNBC has no target receptor for therapy, it would be desirable to target GPR116. Currently, chemotherapy is the only promising option for TNBC; however, these drugs cause chemoresistance. Hence this current study concentrated on finding drugable natural phytochemical ligands targeting GPR116 using in silico approach. Best docked ligand with target and active binding site amino acids were identified in molecular docking study. Pharmacokinetic properties (ADME) were assessed by Qikprop. Result showed that pharmacokinetics properties of natural phytochemicals were as good as existing chemotherapeutic cancer drugs. This study indicates that phytochemicals could be a promising target for GPR116. This in silico analysis facilitates further research to design the drug targeting GPR116 for treatment of TNBC.

Validation of a Genome-Wide Polygenic Score for Coronary Artery Disease in South Asians.

BACKGROUND: Genome-wide polygenic scores (GPS) integrate information from many common DNA variants into a single number. Because rates of coronary artery disease (CAD) are substantially higher among South Asians, a GPS to identify high-risk individuals may be particularly useful in this population. OBJECTIVES: This analysis used summary statistics from a prior genome-wide association study to derive a new GPSCAD for South Asians. METHODS: This GPSCAD was validated in 7,244 South Asian UK Biobank participants and tested in 491 individuals from a case-control study in Bangladesh. Next, a static ancestry and GPSCAD reference distribution was built using whole-genome sequencing from 1,522 Indian individuals, and a framework was tested for projecting individuals onto this static ancestry and GPSCAD reference distribution using 1,800 CAD cases and 1,163 control subjects newly recruited in India. RESULTS: The GPSCAD, containing 6,630,150 common DNA variants, had an odds ratio (OR) per SD of 1.58 in South Asian UK Biobank participants and 1.60 in the Bangladeshi study (p < 0.001 for each). Next, individuals of the Indian case-control study were projected onto static reference distributions, observing an OR/SD of 1.66 (p < 0.001). Compared with the middle quintile, risk for CAD was most pronounced for those in the top 5% of the GPSCAD distribution-ORs of 4.16, 2.46, and 3.22 in the South Asian UK Biobank, Bangladeshi, and Indian studies, respectively (p < 0.05 for each). CONCLUSIONS: The new GPSCAD has been developed and tested using 3 distinct South Asian studies, and provides a generalizable framework for ancestry-specific GPS assessment.

Silver nanoparticles in dye effluent treatment: A review on synthesis, treatment methods, mechanisms, photocatalytic degradation, toxic effects and mitigation of toxicity.

The current scenario of water resources shows the dominance of pollution caused by the draining of industrial effluents. The polluted waters have resulted in severe health and environmental hazards urging for a suitable alternative to resolve the implications. Various physical and chemical treatment steps currently in use for dye effluent treatment are more time consuming, cost-intensive, and less effective. Alternatively, nanoparticles due to their excellent surface properties and chemical reactivity have emerged as a better solution for dye removal and degradation. In this regard, the potential of silver nanoparticles in dye effluent treatment was greatly explored. Efforts were taken to unravel the kinetics and statistical optimization of the treatment conditions for the efficient removal of dyes. In addition, the role of silver nanocomposites has also experimented with colossal success. On the contrary, studies have also recognized the mechanisms of silver nanoparticle-mediated toxicity even at deficient concentrations and their deleterious biological effects when present in treated water. Hence, the fate of the silver nanoparticles released into the treated water and sludge, contaminating the soil, aquatic environment, and underground water is of significant concern. This review summarizes the current state of knowledge regarding the use of silver nanoparticles and silver-based nanocomposites in effluent treatment and comprehends the recent research on mitigation of silver nanoparticle-induced toxicity.

Coarse-Grained Clustering Dynamics of Heterogeneously Coupled Neurons.

The formation of oscillating phase clusters in a network of identical Hodgkin-Huxley neurons is studied, along with their dynamic behavior. The neurons are synaptically coupled in an all-to-all manner, yet the synaptic coupling characteristic time is heterogeneous across the connections. In a network of N neurons where this heterogeneity is characterized by a prescribed random variable, the oscillatory single-cluster state can transition-through [Formula: see text] (possibly perturbed) period-doubling and subsequent bifurcations-to a variety of multiple-cluster states. The clustering dynamic behavior is computationally studied both at the detailed and the coarse-grained levels, and a numerical approach that can enable studying the coarse-grained dynamics in a network of arbitrarily large size is suggested. Among a number of cluster states formed, double clusters, composed of nearly equal sub-network sizes are seen to be stable; interestingly, the heterogeneity parameter in each of the double-cluster components tends to be consistent with the random variable over the entire network: Given a double-cluster state, permuting the dynamical variables of the neurons can lead to a combinatorially large number of different, yet similar "fine" states that appear practically identical at the coarse-grained level. For weak heterogeneity we find that correlations rapidly develop, within each cluster, between the neuron's "identity" (its own value of the heterogeneity parameter) and its dynamical state. For single- and double-cluster states we demonstrate an effective coarse-graining approach that uses the Polynomial Chaos expansion to succinctly describe the dynamics by these quickly established "identity-state" correlations. This coarse-graining approach is utilized, within the equation-free framework, to perform efficient computations of the neuron ensemble dynamics.

Biological real-time reaction calorimeter studies for the production of penicillin G acylase from Bacillus badius.

Penicillin G acylase (PGA) is a commercially important enzyme that cleaves penicillin G to 6-amino penicillanic acid (6-APA) and phenyl acetic acid (PAA). The strain Bacillus badius has been identified as potential producer of PGA. A detailed calorimetric investigation on PGA production was carried out to enable generation of thermokinetic data possible for commercial application. Reaction calorimetric studies coupled with respirometric studies suggested that enzyme activity of the species B. badius was calorimetrically traceable. Three phases of growth were distinctly noticeable in the metabolic heat-time curve. Increase in enzymatic activity with restricted growth confirmed intracellular nature of the production process. The estimated heat yields due to biomass growth, 10.026 kJ/g, substrate consumption 22.761 kJ/g, and oxygen uptake 383 ± 10 kJ/mol helped to understand the energetic of the organism under study. Low oxycalorific coefficient confirmed the existence of fermentation-coupled metabolism of B. badius.

Strategies for enhancing the production of penicillin G acylase from Bacillus badius: influence of phenyl acetic acid dosage.

Bacillus badius isolated from soil has been identified as potential producer of penicillin G acylase (PGA). In the present study, batch experiments performed at optimized inoculum size, temperature, pH, and agitation yielded a maximum PGA of 9.5 U/ml in shake flask. The experiments conducted in bioreactor with different oxygen flow rates revealed that 0.66 vvm oxygen flow rate could be sufficient for the maximum PGA activity of 12.7 U/ml. From a detailed investigation on the strategies of the addition of phenyl acetic acid (PAA) for increasing the production of PGA, it was found that the controlled addition of 10 ml of 0.1 % (w/v) PAA once in every 2 h from 6th hour of growth showed the maximum PGA activity of 32 U/ml. Thus, our studies for the first time showed that at concentration above 0.1 % (w/v) PAA, the PGA production decreased. This selective condition paves the way for less costly bioprocess for the production of PGA.

Chimeras in random non-complete networks of phase oscillators.

We consider the simplest network of coupled non-identical phase oscillators capable of displaying a "chimera" state (namely, two subnetworks with strong coupling within the subnetworks and weaker coupling between them) and systematically investigate the effects of gradually removing connections within the network, in a random but systematically specified way. We average over ensembles of networks with the same random connectivity but different intrinsic oscillator frequencies and derive ordinary differential equations (ODEs), whose fixed points describe a typical chimera state in a representative network of phase oscillators. Following these fixed points as parameters are varied we find that chimera states are quite sensitive to such random removals of connections, and that oscillations of chimera states can be either created or suppressed in apparent bifurcation points, depending on exactly how the connections are gradually removed.

Coarse graining the dynamics of heterogeneous oscillators in networks with spectral gaps.

We present a computer-assisted approach to coarse graining the evolutionary dynamics of a system of nonidentical oscillators coupled through a (fixed) network structure. The existence of a spectral gap for the coupling network graph Laplacian suggests that the graph dynamics may quickly become low dimensional. Our first choice of coarse variables consists of the components of the oscillator states--their (complex) phase angles--along the leading eigenvectors of this Laplacian. We then use the equation-free framework, circumventing the derivation of explicit coarse-grained equations, to perform computational tasks such as coarse projective integration, coarse fixed-point, and coarse limit-cycle computations. In a second step, we explore an approach to incorporating oscillator heterogeneity in the coarse-graining process. The approach is based on the observation of fast-developing correlations between oscillator state and oscillator intrinsic properties and establishes a connection with tools developed in the context of uncertainty quantification.

Generalizability of Stabilogram Diffusion Analysis of center of pressure measures.

Quiet standing balance and postural control are often assessed by drawing information from center of pressure (COP) data collected with a force platform. Efforts to better understand the underlying processes involved in postural control have lead to methods that examine the dynamic or stochastic characteristics of the COP. One method that has recently gained popularity is Stabilogram Diffusion Analysis (SDA). There is, however, a lack of standardization in the methodology of data collection for this approach, i.e., how many trials to include and how long to sample a trial. The purpose of this study was to use the tools of Generalizability Theory (G-Theory) to investigate the reliability of SDA measures of quiet standing and to establish an optimal measurement protocol. G-Theory provides a tool that allows us to break down the sources of variation, or facets, in a measurement procedure and ultimately design a protocol that provides optimal reliability. Fifteen young, healthy participants completed ten 90-s trials: first with eyes open and then eyes closed. Common measures of SDA were calculated using the first 30, 60 and 90 s of each trial. G-Theory through a Generalizability Study (G-study) and follow-up Decision Studies (D-studies) were performed to estimate reliability coefficients (G-coefficients). The fully crossed facets included were participants (P), length of trials (L) and number of trials (T). Results of this study suggest that at least five 60s trials should be used when using the selected measures of SDA. These guidelines address acceptable reliability and the gains achieved by adding trials or increasing trial length.

Changing control strategies during standard assessment using computerized dynamic posturography with older women.

The goal of this investigation was to explore the use of spectral analysis to examine the data obtained during computerized dynamic posturography (CDP). In particular, we examined whether spectral analysis would provide more detailed information about underlying postural control strategies and potential learning across conditions and trials of the sensory organization test (SOT). Twenty older women between the ages of 60 and 72 (mean=65.2) were assessed using standard testing protocol. Participants showed significant improvements from the first to the second trials in their equilibrium scores in the more difficult conditions. This finding was reflected in the spectral analysis data by a shift in the frequency distribution towards greater power in the lower frequency range. This frequency change likely reflects a change in the ankle strategy used to maintain balance during the more difficult conditions.