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The novel Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) has emerged to be the reason behind the COVID-19 pandemic. It was discovered in Wuhan, China and then began spreading around the world, impacting the health of millions. Efforts for treatment have been hampered as there are no antiviral drugs that are effective against this virus. In the present study, we have explored the phytochemical constituents of Salvia plebeia R. Br., in terms of its binding affinity by targeting COVID-19 main protease (Mpro) using computational analysis. Molecular docking analysis was performed using PyRx software. The ADMET and drug-likeness properties of the top 10 compounds showing binding affinity greater than or equal to - 8.0 kcal/mol were analysed using pkCSM and DruLiTo, respectively. Based on the docking studies, it was confirmed that Rutin and Plebeiosides B were the most potent inhibitors of the main protease of SARS-CoV-2 with the best binding affinities of - 9.1 kcal/mol and - 8.9 kcal/mol, respectively. Further, the two compounds were analysed by studying their biological activity using the PASS webserver. Molecular dynamics simulation analysis was performed for the selected protein-ligand complexes to confirm their stability at 300 ns. MM-PBSA provided the basis for analyzing the affinity of the phytochemicals towards Mpro by calculating the binding energy, and secondary structure analysis indicated the stability of protease structure when it is bound to Rutin and Plebeiosides B. Altogether, the study identifies Rutin and Plebeiosides B to be potent Mpro inhibitors of SARS-CoV-2. Supplementary Information The online version contains supplementary material available at 10.1007/s42535-021-00304-z.

The gene structure of organisms gets altered when exposed to an abnormal condition which could adversely affect the growth of the target. RNA sequencing can be deployed to identify diseasecausing mutations in the genes of patients for whom genetic analysis failed to return a diagnosis. One such disease is Hypoxia, a condition in which there is a deficiency in the availability of oxygen in the tissues. RNA sequencing helps in analyzing the global expression patterns of hypoxia and in understanding the cellular alterations of those suffering from it. It gives an understanding of the comprehensive regulation of the gene expression by environmental spur or specific factors which can be used to diagnose and treat hypoxia before it gets fatal. Prunus persica is a plant which has a high capacity for anoxic tolerance, and analyzing the gene expression changes which are associated to hypoxia treatments in the root tissues of two genotypes of the peach plant (Flooding tolerant and Flooding sensitive) can prevent physiological disorders. Further, gene ontology is used to cover three domains-cellular component, molecular function and biological processes related to the differentially expressed genes. We use Generalized Linear Models here, to find the differentially expressed genes in Prunus persica when exposed to the conditions of Hypoxia (Absence of Oxygen) and Normoxia (Excess of Oxygen) and find their Ontologies and genomic pathways to understand and diagnose the Processes that are most affected.

The magnetic composite of coffee husk hydrochar-Fe3O4 (MCHH) was synthesized and employed as an adsorbent for the removal of methylene blue (MB) from synthetic wastewater. The coffee husk hydrochar was prepared by hydrothermal carbonization, and magnetic composite was produced through the chemical co-precipitation method. The physicochemical properties of the magnetic composite was analyzed by PZC, PXRD, SEM, FTIR, and VSM. The characterization results indicated successful incorporation of iron oxide particles into coffee husk hydrochar. The influence of adsorbent dose (0.2–1.4 g/L), pH (2−10), initial MB concentration (50–250 mg/L), contact time (0–160 min) and temperature (30–60 °C) on adsorption of MB on MCHH were studied. The adsorption equilibrium and kinetic studies suggested that the Freundlich isotherm model adequately explains the adsorption process and pseudo-second-order kinetic model could be regressed well with the experimental kinetics data. The maximum monolayer adsorption capacity of MB on MCHH was found to be 78 mg/g. Mass transfer analysis was also studied in order to understand the diffusion process in the adsorption process. The thermodynamic parameters are evaluated to elucidate the nature of the adsorption of MB onto MCHH. Good adsorption efficiency and easy recovery ability of MCHH suggests it could be a cost-effective adsorbent for the removal of dyes from wastewater.

Graphic abstract The novel Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) has emerged to be the reason behind the COVID-19 pandemic. It was discovered in Wuhan, China and then began spreading around the world, impacting the health of millions. Efforts for treatment have been hampered as there are no antiviral drugs that are effective against this virus. In the present study, we have explored the phytochemical constituents of Salvia plebeia R. Br., in terms of its binding affinity by targeting COVID-19 main protease (Mpro) using computational analysis. Molecular docking analysis was performed using PyRx software. The ADMET and drug-likeness properties of the top 10 compounds showing binding affinity greater than or equal to − 8.0 kcal/mol were analysed using pkCSM and DruLiTo, respectively. Based on the docking studies, it was confirmed that Rutin and Plebeiosides B were the most potent inhibitors of the main protease of SARS-CoV-2 with the best binding affinities of − 9.1 kcal/mol and − 8.9 kcal/mol, respectively. Further, the two compounds were analysed by studying their biological activity using the PASS webserver. Molecular dynamics simulation analysis was performed for the selected protein–ligand complexes to confirm their stability at 300 ns. MM-PBSA provided the basis for analyzing the affinity of the phytochemicals towards Mpro by calculating the binding energy, and secondary structure analysis indicated the stability of protease structure when it is bound to Rutin and Plebeiosides B. Altogether, the study identifies Rutin and Plebeiosides B to be potent Mpro inhibitors of SARS-CoV-2. Supplementary Information The online version contains supplementary material available at 10.1007/s42535-021-00304-z.

Differentially Expressed genes related to Glioblastoma Multiforme as an output of RNASeq studies were further studied to conclude new research insights. Glioma is a type of intracranial tumor (within the skull), which can grow rapidly in its malignant stages. Gene expression in Grade II, III and IV Gliomas is analysed using non linear SVM models. The enriched GO terms were identified GOrilla. Pathways related to NOG and ASCL5 gene were studied using Reactome.

Groundwater samples were collected from Peenya Industrial area of Bengaluru, India to check its inherent bacterial population. After the isolates were grown in lead-induced media, the bacteria that could resist lead were further isolated, identified, and grown. The isolated bacterium was identified as Bacillus toyonensis SCE1 species, and the maximum amount of lead taken up by it to sustain itself as a live biomass was 8 ppm. Lead accumulation was studied based on different factors such as pH, concentration, and time. Bacterial characterization through scanning electron microscopy showed there was lead sorption on the bacterial cells. Transmission electron microscopy revealed that accumulated lead ions inside the bacteria were in the range of 180–190 nm, this was found to correlate with the data obtained by the particle size analyzer. The optimum pH for highest lead accumulation was 7.2, for a time period of 160 min. It was observed that the stable production of homogenous nanoparticles using biomass could be achieved by optimizing factors such as incubation period, agitation, pH, temperature, and contact time.

Lead contamination in groundwater has raised serious health concerns. The traditional technologies available for lead removal are having several shortcomings. Hence, biosorption is considered as a potential eco-friendly alternative to the existing methods. In the present work, several ground water samples were collected from different lead contaminated regions of III and IV phase of Peenya industrial area from Bengaluru district of Karnataka, India. These ground water samples were used as a source to isolate bacteria with distinct morphological characteristics which were identified as Bacillus toyonensis SCE1, Bacillus anthracis SCE2, Acinetobacter baumannii SCE3, Bacillus toyonensis SCE4 and Bacillus toyonensis SCE5 that were tested for their biosorption properties. The interactive effect of initial lead concentration versus contact time was studied using Response Surface Methodology (RSM) while the biosorbent dosage was kept constant. The biosorption kinetics was investigated for the isolates and the results studies indicated that the biosorption charted pseudo-second order kinetic model and it provided the best fit for the bacterial species for lead biosorption.

Groundwater samples were collected from the Peenya Industrial area of Bengaluru, India to test its quality, elemental composition and inherent bacterial population. Further analysis was done using GIS Based Geostatistical techniques to study the level of groundwater and to generate various maps of lineament, digital elevation, geomorphology, soil erosion, salt affected areas and water logging in this region. Physical and chemical parameters such as Total Dissolved Solids, pH, temperature, BOD, COD, metal ions present in the water samples were studied along with predominant microbial constituents. The Total Dissolved Solids and Total Hardness were far beyond the maximum concentration levels. Further analysis of the isolated bacteria was done using staining methods and biochemical tests. The results obtained showed that the area under study had wells ranging from shallow to deep heights of 30 to 80 meters, with a wide variety of 10-400 LPM; whereas the lineament map suggested that the area was bound with parallel ridges and joints. The geographical data represented pediplain complexes, anthropogenic terrains and water bodies. The area was found to go through a seasonal water logging and the soil loss was due to sheet erosion and rill erosion. It was also observed that the groundwater was contaminated with heavy metals such as lead, chromium etc. along with a diversified bacterial population.

Aim: To identify the rate of incidental prostate cancer in patients undergone Transurethral resection of prostate(TURP) over a period of 5 years in our center. Methods: A Retrospective review was conducted using Histopathological department database on all TURP specimens over a period of 5 years from January 2015 to December 2019. Results: Out of 570 cases of TURP during our study period, 1.9% had incidental prostate cancer. Most of these positive cases had a Gleasons score of 10, which represent poorly differentiated Adenocarcinoma. Conclusion: The value of pathologic review of TURP specimens is limited but a detailed review helps to reduce under detection of prostate cancer.

The goal of this study was to propose a workflow using machine learning to identify and predict the miRNA targets of Human Immunodeficiency virus 1. miRNAs which is ~21 nt long are attained from larger hairpin RNA precursors and is maintained in the secondary structure of their precursor relatively than in primary chain of successions. The proposition approach for identification and prediction of miRNA targets in hiv1-miR-H1is based on secondary structure and E-value through machine learning. Data Linearity of Length and e-value for sequence match with hiv1-mir-H1 is verified using Kernel PCA. miRNA targets were grouped into clusters thereby indicating similar targets using K-means algorithm. Classification model using Random Forest was implemented regards to each secondary features variable considering feature relevance. A learning methodology is put forward that assimilate and integrate the score returned by various machine learning algorithms to predict cellular hiv1-miR-H1 targets. Gene targets results using TargetScan, miRanda, PITA, DIANA microT and RNAhybrid are also explored for multiple parameters.

In this paper, a comparative study of various feature extraction methods is carried out on dysarthric speech. Dysarthric speech is difficult to recognize and thus pose challenges that normal speech does not. Since various features can be used to model phonemes in hidden Markov model (HMM) based recognition system, which feature is suitable for the task specified is a topic to be addressed.Dysarthric speech becomes unintelligible due to the improper coordination of articulators. In this paper, recognition results are compared using mel-frequency cepstral coefficients (MFCC), perceptual linear prediction (PLP), filter bank and reflection coefficients feature sets. The performance is analyzed using TORGO database. Phonemes are grouped for the analysis. Our study shows that MFCC and PLP gave better results than filter bank and reflection coefficients for dysarthric speech analysis.

Objectives: Lead is recognized as a serious pollutant on the basis of its persistence, toxicity, bioaccumulation and extensive use in industry. Exposure to lead results in a number of cytogenetical effects on freshwater biota which adversely affects the population, including reducing the rate of cell division and inducing mutations. In order to assess the toxicity of lead, a reliable model of Drosophila melanogaster was taken and experiments were carried out by maintaining a control set and experimental sets with varied concentrations of lead.Methods: The toxicity of lead was studied by varying the lead concentrations from 20-60 ppm in the food media that was given to the fruit flies. Studies on the larval, pupal and adult stages of the flies were done, including the reproductive and locomotion efficiency of the flies.Results: The results of our study shows that as the concentration of lead in the media increased from 20 to 60 ppm, there was a visible change in the number of offsprings and the locomotive behavior of flies. Significantly there was a stretch in the time duration in the conversion of larva to pupa and then pupa to adult. The length and width of the pupa was also found to be affected.Conclusion: Long term exposure to lead can have significant effect on the survival of population even if its concentration is low and it may also reflect population adaptive capacity.

Any foreign chemical substance that is unusually present within an organism or is unexpectedly found in the environment at a higher concentration than the permissible limits can be termed a xenobiotic or a pollutant. Such substances include carcinogens, drugs, food additives, hydrocarbons, dioxins, polychlorinated biphenyls, pesticides or even some natural compounds. Pollutants are known for their higher persistence and pervasiveness, and along with their transformed products, they can remain in and interact with the environment for prolonged periods. In this article, the classification of such substances based on their nature, use, physical state, pathophysiological effects, and sources is discussed. The effects of pollutants on the environment, their biotransformation in terms of bioaccumulation, and the different types of remediation such as in situ and ex situ remediation, are also presented.

Background In the present study, the lemon pulp and peel along-with their secondary metabolites were studied and compared for its antioxidant activity. Method Various in vitro and ex vivo studies were done to estimate the polyphenols and flavonoids present in the lemon pulp and peel. The reducing power, free radical scavenging activity and lipid peroxide inhibition were investigated for the extracts. Results The lemon peel was found to have a slightly greater count of polyphenols and flavonoids, showing a difference of 0.2. The peel extracts also showed better reducing power and higher free radical scavenging activity. The peel extracts gave 82.3% of inhibition towards lipid peroxidation, when compared to the pulp extracts which showed an inhibition of 78.2%. Conclusion The antioxidant activity was found to be higher in the case of lemon peel when compared to the pulp.

Hidden Markov Model (HMM) has become one of the interesting methods for the researchers, especially in bioinformatics where different analysis are carried out. These are widely used in science, engineering and many other areas such as bioinformatics, genomic mapping, computer vision, finance and economics, and in social science. HMMs require much smaller training sets, and that the examination of the inner structure of the model provides often a deeper understanding of the phenomenon. In this survey, we first describe the important algorithms for the HMMs, and provide useful comparisons, aiming at their advantages and shortcomings. We then consider the major g applications, such as annotations, gene alignment and profiling of sequences, DNA structure prediction, and pattern recognition. We also list some analysis on how to use HMM for DNA genomes. Finally, we conclude use and perspectives of HMMs in bioinformatics and provide a critical appraisal for the same.

Bladder cancer is a major health-care concern. A successful treatment of bladder cancer depends on its early diagnosis at the initial stage. Genetic instability is an essential early step toward the development of bladder cancer. This instability is found more often at the chromosomal level than at the nucleotide level. Microsatellite and chromosomal instability markers can be used as a prognostic marker for screening bladder cancer. Bladder cancer can be distinguished in two different categories according to genetic instability: Cancers with chromosomal level instability and cancers with nucleotide level instability. Deoxyribonucleic acid (DNA) mismatch repair (MMR) system and its correlation with other biologic pathway, both are essential to understand the basic mechanisms of cancer development. Microsatellite instability occurs due to defects in DNA MMR genes, including human mutL homolog 1 and human mutL homolog 2. Chromosomal alterations including deletions on chromosome 3, 8, 9, 11, 13, 17 have been detected in bladder cancer. In the current review, the most recent literature of genetic instability in urinary bladder cancer has been summarized.