PMTPred: machine-learning-based prediction of protein methyltransferases using the composition of k-spaced amino acid pairs.

Protein methyltransferases (PMTs) are a group of enzymes that help catalyze the transfer of a methyl group to its substrates. These enzymes play an important role in epigenetic regulation and can methylate various substrates with DNA, RNA, protein, and small-molecule secondary metabolites. Dysregulation of methyltransferases is implicated in various human cancers. However, in light of the well-recognized significance of PMTs, reliable and efficient identification methods are essential. In the present work, we propose a machine-learning-based method for the identification of PMTs. Various sequence-based features were calculated, and prediction models were trained using various machine-learning algorithms using a tenfold cross-validation technique. After evaluating each model on the dataset, the SVM-based CKSAAP model achieved the highest prediction accuracy with balanced sensitivity and specificity. Also, this SVM model outperformed deep-learning algorithms for the prediction of PMTs. In addition, cross-database validation was performed to ensure the robustness of the model. Feature importance was assessed using shapley additive explanations (SHAP) values, providing insights into the contributions of different features to the model's predictions. Finally, the SVM-based CKSAAP model was implemented in a standalone tool, PMTPred, due to its consistent performance during independent testing and cross-database evaluation. We believe that PMTPred will be a useful and efficient tool for the identification of PMTs. The PMTPred is freely available for download at https://github.com/ArvindYadav7/PMTPred and http://www.bioinfoindia.org/PMTPred/home.html for research and academic use.

Cross Dehydrogenative Coupling of SF4-Alkyne with Tetrahydroisoquinolines.

This study introduces a dual-catalytic method for cross-dehydrogenative coupling (CDC) between tetrahydroisoquinolines and Py-SF4-alkyne using visible-light photoredox catalysis. This protocol enables selective C(sp3)-H alkynylation, expanding the synthetic toolkit for SF4-based molecules. Demonstrating efficiency and substrate versatility, this approach opens new avenues in hexacoordinated tetrafluorinated sulfur chemistry and CDC strategies and holds significant promise for drug discovery and materials science.

A computational study on structural and functional consequences of nsSNPs in human dopa decarboxylase.

The Dopa Decarboxylase (DDC) gene plays an important role in the synthesis of biogenic amines such as dopamine, serotonin, and histamine. Non-synonymous single nucleotide polymorphisms (nsSNPs) in the DDC gene have been linked with various neurodegenerative disorders. In this study, a comprehensive in silico analysis of nsSNPs in the DDC gene was conducted to assess their potential functional consequences and associations with disease outcomes. Using publicly available databases, a complete list of nsSNPs in the DDC gene was obtained. 29 computational tools and algorithms were used to characterise the effects of these nsSNPs on protein structure, function, and stability. In addition, the population-based association studies were performed to investigate possible associations between specific nsSNPs and arthritis. Our research identified four novel DDC gene nsSNPs that have a major impact on the structure and function of proteins. Through molecular dynamics simulations (MDS), we observed changes in the stability of the DDC protein induced by specific nsSNPs. Furthermore, population-based association studies have revealed potential associations between certain DDC nsSNPs and various neurological disorders, including Parkinson's disease and dementia. The in silico approach used in this study offers insightful information about the functional effects of nsSNPs in the DDC gene. These discoveries provide insight into the cellular processes that underlie cognitive disorders. Furthermore, the detection of disease-associated nsSNPs in the DDC gene may facilitate the development of tailored and targeted therapy approaches.Communicated by Ramaswamy H. Sarma.

CstMYB1R1, a REVEILLE-8-like transcription factor, regulates diurnal clock-specific anthocyanin biosynthesis and response to abiotic stress in Crocus sativus L.

KEY MESSAGE: CstMYB1R1 acts as a positive regulator of Crocus anthocyanin biosynthesis and abiotic stress tolerance which was experimentally demonstrated through molecular analysis and over-expression studies in Crocus and Nicotiana. Regulatory mechanics of flavonoid/anthocyanin biosynthesis in Crocus floral tissues along the diurnal clock has not been studied to date. MYB proteins represent the most dominant, functionally diverse and versatile type of plant transcription factors which regulate key metabolic and physiological processes in planta. Transcriptome analysis revealed that MYB family is the most dominant transcription factor family in C. sativus. Considering this, a MYB-related REVEILLE-8 type transcription factor, CstMYB1R1, was explored for its possible role in regulating Crocus flavonoid and anthocyanin biosynthetic pathway. CstMYB1R1 was highly expressed in Crocus floral tissues, particularly tepals and its expression was shown to peak at dawn and dusk time points. Anthocyanin accumulation also peaked at dawn and dusk and was minimum at night. Moreover, the diurnal expression pattern of CstMYB1R1 was shown to highly correlate with Crocus ANS/LDOX gene expression among the late anthocyanin pathway genes. CstMYB1R1 was shown to be nuclear localized and transcriptionally active. CstMYB1R1 over-expression in Crocus tepals enhanced anthocyanin levels and upregulated transcripts of Crocus flavonoid and anthocyanin biosynthetic pathway genes. Yeast one hybrid (Y1H) and GUS reporter assay confirmed that CstMYB1R1 interacts with the promoter of Crocus LDOX gene to directly regulate its transcription. In addition, the expression of CstMYB1R1 in Nicotiana plants significantly enhanced flavonoid and anthocyanin levels and improved their abiotic stress tolerance. The present study, thus, confirmed positive role of CstMYB1R1 in regulating Crocus anthocyanin biosynthetic pathway in a diurnal clock-specific fashion together with its involvement in the regulation of abiotic stress response.

Computational approach for assessing the involvement of SMYD2 protein in human cancers using TCGA data.

BACKGROUND: SMYD2 is a protein of the SET and MYND domain-containing family SMYD. It can methylate the lysine residue of various histone and nonhistone cancer-related proteins and plays a critical role in tumorigenesis. Although emerging evidence supports the association of SMYD2 in the progression of cancers, but its definitive effect is not yet clear. Therefore, further study of the gene in relation with cancer progression needs to be conducted. In the current study, investigators used TCGA data to determine the potential carcinogenic effect of SMYD2 in 11 cancer types. The transcriptional expression, survival rate, mutations, enriched pathways, and Gene Ontology of the SMYD2 were explored using different bioinformatics tools and servers. In addition, we also examined the correlation between SMYD2 gene expression and immunocyte infiltration in multiple cancer types. RESULTS: Findings revealed that higher expression of SMYD2 was significantly correlated with cancer incidents. In CESC and KIRC, the mRNA expression of SMYD2 was significantly correlated with overall survival (OS). In BRCA, KIRC, COAD, and HNSC, the mRNA expression of SMYD2 was significantly correlated with disease-free survival (DFS). We detected 15 missense, 4 truncating, 4 fusions, and 1 splice type of mutation. The expression of SMYD2 was significantly correlated with tumor purity and immunocyte infiltration in six cancer types. The gene GNPAT was highly associated with SMYD2. Significant pathways and Gene Ontology (GO) terms for co-expressed genes were associated to various processes linked with cancer formation. CONCLUSION: Collectively, our data-driven results may provide reasonably comprehensive insights for understanding the carcinogenic effect of SMYD2. It suggests that SMYD2 might be used as a significant target for identifying new biomarkers for various human tumors.

CstPIF4 Integrates Temperature and Circadian Signals and Interacts with CstMYB16 to Repress Anthocyanins in Crocus.

Crocus sativus has emerged as an important crop because it is the only commercial source of saffron that contains unique apocarotenoids. Saffron is composed of dried stigmas of Crocus flower and constitutes the most priced spice of the world. Crocus floral organs are dominated by different classes of metabolites. While stigmas are characterized by the presence of apocarotenoids, tepals are rich in flavonoids and anthocyanins. Therefore, an intricate regulatory network might play a role in allowing different compounds to dominate in different organs. Work so far done on Crocus is focussed on apocarotenoid metabolism and its regulation. There are no reports describing the regulation of flavonoids and anthocyanins in Crocus tepals. In this context, we identified an R2R3 transcription factor, CstMYB16, which resembles subgroup 4 (SG4) repressors of Arabidopsis. CstMYB16 is nuclear localized and acts as a repressor. Overexpression of CstMYB16 in Crocus downregulated anthocyanin biosynthesis. The C2/EAR motif was responsible for the repressor activity of CstMYB16. CstMYB16 binds to the promoter of the anthocyanin biosynthetic pathway gene (LDOX) and reduces its expression. CstMYB16 also physically interacts with CstPIF4, which in turn is regulated by temperature and circadian clock. Thus, CstPIF4 integrates these signals and forms a repressor complex with CstMYB16, which is involved in the negative regulation of anthocyanin biosynthesis in Crocus. Independent of CstPIF4, CstMYB16 also represses CstPAP1 expression, which is a component of the MYB-bHLH-WD40 (MBW) complex and positively controls anthocyanin biosynthesis. This is the first report on identifying and describing regulators of anthocyanin biosynthesis in Crocus.

Prediabetes in rural adolescent girls from DERVAN cohort: data from the KONKAN region of the state of Maharashtra, India (DERVAN-4).

Background: India is witnessing an epidemic of type 2 diabetes. Overweight/obesity, overnutrition, physical inactivity, and family history are well-known risk factors for diabetes. We investigated the role of undernutrition in the development of diabetes among rural adolescent girls. Methods: DERVAN cohort study was set up in the KONKAN region of the western Indian state of Maharashtra. It enrolled 1,520 adolescent girls (16-18 years old at the time of enrollment). We measured glycemic parameters (glucose, insulin, and HbA1C) and body size using anthropometry and body composition using bioimpedance. Prediabetes was diagnosed using the American Diabetic Association (ADA) criteria. We also calculated various HOMA indices for insulin resistance (HOMA-IR), ß-cell function (HOMA-ß), insulin sensitivity (HOMA-S), and compensatory ß-cell response using a homeostasis model. BMI, body fat%, and waist circumferences were treated as exposures and all the glycemic parameters and indices as outcomes. Results: The median age of the subjects was 16.6 years. The median weight, height, and BMI were 40.7 kg, 151.7 cm, and 17.5 kg/m2, respectively. Prevalence of underweight was 28.8%, and stunting was observed in 30.4%. Thinness and obesity using BMI were observed in 58.4% and 4.2%, respectively. The median body fat% was 22.5, and excess body fat (>35%) was observed in 5.7%. The prevalence of prediabetes was 39.4%. Fasting insulin concentrations, HOMA-IR, and HOMA-ß showed a positive trend across body composition quartiles (p < 0.001). HOMA-S and compensatory ß-cell response showed an inverse trend (p < 0.001). Compared with prediabetic girls in the overweight/obese group, girls most undernourished group had lower median insulin concentrations (8.1 µIU/ml vs. 17.1 µIU/ml), lower HOMA-IR (1.1 vs. 2.3), and lower HOMA-ß (75.6 vs. 129.2) but higher sensitivity (87.4 vs. 43.7) (p < 0.001) for all. Conclusion: We have reported a high prevalence of prediabetes among rural adolescent girls with a very low prevalence of obesity. Prediabetes in obesity is driven by hyperinsulinemia and overworking of the pancreas while poor ß-cell function and poor insulin secretion are major drivers in the undernourished group. The high-risk diabetes screening programs are much needed for the undernourished populations. Caution should be exercised for planning the interventions as overfeeding (or overnutrition) is likely to put the populations at risk of development of obesity and insulin resistance.

Morphological, phytochemical, and transcriptome analyses provide insights into the biosynthesis of monoterpenes in Monarda citriodora.

MAIN CONCLUSION: Morphological, phytochemical, and transcriptome analyses revealed candidate genes involved in the biosynthesis of volatile monoterpenes and development of glandular trichomes in Monarda citriodora. Monarda citriodora Cerv. ex Lag. is a valuable aromatic plant due to the presence of monoterpenes as major constituents in its essential oil (EO). Thus, it is of sheer importance to gain knowledge about the site of the biosynthesis of these terpenoid compounds in M. citriodora, as well as the genes involved in their biosynthesis. In this study, we studied different types of trichomes and their relative densities in three different developmental stages of leaves, early stage of leaf development (L1), mid-stage of leaf development (L2), and later stage of leaf development (L3) and the histochemistry of trichomes for the presence of lipid and terpenoid compounds. Further, the phytochemical analysis of this plant through GC-MS indicated a higher content of monoterpenes (thymol, thymoquinone, γ-terpinene, p-cymene, and carvacrol) in the L1 stage with a substantial decrease in the L3 stage of leaf development. This considerable decrease in the content of monoterpenes was attributed to the decrease in the trichome density from L1 to L3. Further, we developed a de novo transcriptome assembly by carrying out RNA sequencing of different plant parts of M. citriodora. The transcriptome data revealed several putative unigenes involved in the biosynthesis of specialized terpenoid compounds, as well as regulatory genes involved in glandular trichome development. The data generated in the present study build a strong foundation for further improvement of M. citriodora, in terms of quantity and quality of its essential oil, through genetic engineering.

Computational screening of pathogenic missense nsSNPs in heme oxygenase 1 (HMOX1) gene and their structural and functional consequences.

Heme Oxygenase 1 (HMOX1) is a cytoprotective enzyme, exhibiting the highest activity in the spleen, catalyzing the heme ring breakdown into products of biological significance- biliverdin, CO, and Fe2+. In vascular cells, HMOX1 possesses strong anti-apoptotic, antioxidant, anti-proliferative, anti-inflammatory, and immunomodulatory actions. The majority of these activities are crucial for the prevention of atherogenesis. Single amino acid substitutions in proteins generated by missense non-synonymous single nucleotide polymorphism (nsSNPs) in the protein-encoding regions of genes are potent enough to cause significant medical challenges due to the alteration of protein structure and function. The current study aimed at characterizing and analyzing high-risk nsSNPs associated with the human HMOX1 gene. Preliminary screening of the total available 288 missense SNPs was performed through the lens of deleteriousness and stability prediction tools. Finally, a total of seven nsSNPs (Y58D, A131T, Y134H, F166S, F167S, R183S and M186V) were found to be most deleterious by all tools that are present at highly conserved positions. Molecular dynamics simulations (MDS) analysis explained the mutational effects on the dynamic action of the wild-type and mutant proteins. In a nutshell, R183S (rs749644285) was identified as a highly detrimental mutation that could significantly render the enzymatic activity of HMOX1. The finding of this computational analysis might help subject the experimental confirmatory analysis to characterize the role of nsSNPs in HMOX1.Communicated by Ramaswamy H. Sarma.

Comprehensive bioinformatics analysis of structural and functional consequences of deleterious missense mutations in the human QDPR gene.

Quinonoid dihydropteridine reductase (QDPR) is an enzyme that regulates tetrahydrobiopterin (BH4), a cofactor for enzymes involved in neurotransmitter synthesis and blood pressure regulation. Reduced QDPR activity can cause dihydrobiopterin (BH2) accumulation and BH4 depletion, leading to impaired neurotransmitter synthesis, oxidative stress, and increased risk of Parkinson's disease. A total of 10,236 SNPs were identified in the QDPR gene, with 217 being missense SNPs. Over 18 different sequence-based and structure-based tools were employed to assess the protein's biological activity, with several computational tools identifying deleterious SNPs. Additionally, the article provides detailed information about the QDPR gene and protein structure and conservation analysis. The results showed that 10 mutations were harmful and linked to brain and central nervous system disorders, and were predicted to be oncogenic by Dr. Cancer and CScape. Following conservation analysis, the HOPE server was used to analyse the effect of six selected mutations (L14P, V15G, G23S, V54G, M107K, G151S) on the protein structure. Overall, the study provides insights into the biological and functional impact of nsSNPs on QDPR activity and the potential induced pathogenicity and oncogenicity. In the future, research can be conducted to systematically evaluate QDPR gene variation through clinical studies, investigate mutation prevalence across different geographical regions, and validate computational results with conclusive experiments.Communicated by Ramaswamy H. Sarma.

Genetic diversity, population structure, and genome-wide association study for the flowering trait in a diverse panel of 428 moth bean (Vigna aconitifolia) accessions using genotyping by sequencing.

BACKGROUND: Moth bean (Vigna aconitifolia) is an underutilized, protein-rich legume that is grown in arid and semi-arid areas of south Asia and is highly resistant to abiotic stresses such as heat and drought. Despite its economic importance, the crop remains unexplored at the genomic level for genetic diversity and trait mapping studies. To date, there is no report of SNP marker discovery and association mapping of any trait in this crop. Therefore, this study aimed to dissect the genetic diversity, population structure and marker-trait association for the flowering trait in a diversity panel of 428 moth bean accessions using genotyping by sequencing (GBS) approach. RESULTS: A total of 9078 high-quality single nucleotide polymorphisms (SNPs) were discovered by genotyping of 428 moth bean accessions. Model-based structure analysis and PCA grouped the moth bean accessions into two subpopulations. Cluster analysis revealed accessions belonging to the Northwestern region of India had higher variability than accessions from the other regions suggesting that this region represents its center of diversity. AMOVA revealed more variations within individuals (74%) and among the individuals (24%) than among the populations (2%). Marker-trait association analysis using seven multi-locus models including mrMLM, FASTmrEMMA FASTmrEMMA, ISIS EM-BLASSO, MLMM, BLINK and FarmCPU revealed 29 potential genomic regions for the trait days to 50% flowering, which were consistently detected in three or more models. Analysis of the allelic effect of the major genomic regions explaining phenotypic variance of more than 10% and those detected in at least 2 environments showed 4 genomic regions with significant phenotypic effect on this trait. Further, we also analyzed genetic relationships among the Vigna species using SNP markers. The genomic localization of moth bean SNPs on genomes of closely related Vigna species demonstrated that maximum numbers of SNPs were getting localized on Vigna mungo. This suggested that the moth bean is most closely related to V. mungo. CONCLUSION: Our study shows that the north-western regions of India represent the center of diversity of the moth bean. Further, the study revealed flowering-related genomic regions/candidate genes which can be potentially exploited in breeding programs to develop early-maturity moth bean varieties.

A bioinformatics approach to the identification of novel deleterious mutations of human TPMT through validated screening and molecular dynamics.

Polymorphisms of Thiopurine S-methyltransferase (TPMT) are known to be associated with leukemia, inflammatory bowel diseases, and more. The objective of the present study was to identify novel deleterious missense SNPs of TPMT through a comprehensive in silico protocol. The initial SNP screening protocol used to identify deleterious SNPs from the pool of all TPMT SNPs in the dbSNP database yielded an accuracy of 83.33% in identifying extremely dangerous variants. Five novel deleterious missense SNPs (W33G, W78R, V89E, W150G, and L182P) of TPMT were identified through the aforementioned screening protocol. These 5 SNPs were then subjected to conservation analysis, interaction analysis, oncogenic and phenotypic analysis, structural analysis, PTM analysis, and molecular dynamics simulations (MDS) analysis to further assess and analyze their deleterious nature. Oncogenic analysis revealed that all five SNPs are oncogenic. MDS analysis revealed that all SNPs are deleterious due to the alterations they cause in the binding energy of the wild-type protein. Plasticity-induced instability caused by most of the mutations as indicated by the MDS results has been hypothesized to be the reason for this alteration. While in vivo or in vitro protocols are more conclusive, they are often more challenging and expensive. Hence, future research endeavors targeted at TPMT polymorphisms and/or their consequences in relevant disease progressions or treatments, through in vitro or in vivo means can give a higher priority to these SNPs rather than considering the massive pool of all SNPs of TPMT.

Seroprevalence of anti SARS-CoV-2 IgG antibodies among adults in Jammu district, India: A community-based study.

Background & objectives: Serology testing is essential for immunological surveillance in the population. This serosurvey was conducted to ascertain the cumulative population immunity against SARS-CoV-2 among adults in Jammu district and to understand the association of seropositivity with sociodemographic and clinical correlates. Methods: On September 30 and October 1, 2020, a household survey was done in 20 villages/wards chosen from 10 health blocks in district Jammu, India. Demographic, clinical and exposure information was collected from 2000 adults. Serum samples were screened for IgG antibodies using COVID Kavach MERILISA kit. Tests of association were used to identify risk factors associated with IgG positivity. Crude odds ratio with 95 per cent confidence intervals (CIs) was calculated during univariate analysis followed by logistic regression. Results: Overall adjusted seroprevalence for SARS-CoV-2 was 8.8 per cent (95% CI: 8.78-8.82); it varied from 4.1 per cent in Chauki choura to 16.7 per cent Pallanwalla across 10 blocks in the district. Seropositivity was observed to be comparatively higher in 41-50 and 61-70 yr age groups, among males and in rural areas. Fever, sore throat, cough, dyspnoea, myalgias, anosmia, ageusia, fatigue, seizures, history of exposure, medical consultation, hospitalization and missing work showed significant association with seropositivity on univariate analysis. On logistic regression, only sore throat, myalgia and missing work showed significant adjusted odds of IgG positivity. Extrapolation to adult population suggested that exposure to SARS-CoV-2 was 14.4 times higher than reported cases, translating into Infection fatality rate of 0.08 per cent. Interpretation & conclusions: Since a major part of population was immunologically naive, all efforts to contain COVID-19 need to be vigorously followed while these baseline results provide an important yardstick to monitor the trends of COVID-19 and guide locally appropriate control strategies in the region.

Assessment of snout analysis of Himalayan glaciers: impact studies on Pindari, Kafni, Sundardhunga, and Baljuri base camp glaciers.

There are several causes for the increasing rate of deglaciation, such as global warming, increase in the concentration of black carbon, and extensive use of fossil fuels which causes the change in the overall climate system and shifting glacier ecosystem. This study was conducted on Pindari valley glaciers part of lesser Himalaya in Uttarakhand. This study investigates to (1) monitor and map change in the frontal length or the snout region of a glacier that can be studied with the help of remote sensing techniques and (2) evaluate the decadal and annual retreat rate of the glacier from 1972 to 2018. The study applies both the maximum likelihood classifier and NDSI spectral indices based classification for extracting the glacier region for different periods. This study reveals a significant amount of retreats taking place in the selected glaciers, Pindari, Sundardhunga, Kafni, and Baljuri base camp glaciers, from 1972 to 2018 as 1719.95 m, 1751.21 m, 1057.01 m, and 810.78 m, respectively. The highest amount of change is noticed in Pindari and Sundardhunga glaciers, higher than ~ 1700 m. The study analyses temporal variation of the annual and decadal retreat rate in the Pindari valley glaciers, which would be helpful for the further study of the other glaciers.

Impacts, Tolerance, Adaptation, and Mitigation of Heat Stress on Wheat under Changing Climates.

Heat stress (HS) is one of the major abiotic stresses affecting the production and quality of wheat. Rising temperatures are particularly threatening to wheat production. A detailed overview of morpho-physio-biochemical responses of wheat to HS is critical to identify various tolerance mechanisms and their use in identifying strategies to safeguard wheat production under changing climates. The development of thermotolerant wheat cultivars using conventional or molecular breeding and transgenic approaches is promising. Over the last decade, different omics approaches have revolutionized the way plant breeders and biotechnologists investigate underlying stress tolerance mechanisms and cellular homeostasis. Therefore, developing genomics, transcriptomics, proteomics, and metabolomics data sets and a deeper understanding of HS tolerance mechanisms of different wheat cultivars are needed. The most reliable method to improve plant resilience to HS must include agronomic management strategies, such as the adoption of climate-smart cultivation practices and use of osmoprotectants and cultured soil microbes. However, looking at the complex nature of HS, the adoption of a holistic approach integrating outcomes of breeding, physiological, agronomical, and biotechnological options is required. Our review aims to provide insights concerning morpho-physiological and molecular impacts, tolerance mechanisms, and adaptation strategies of HS in wheat. This review will help scientific communities in the identification, development, and promotion of thermotolerant wheat cultivars and management strategies to minimize negative impacts of HS.

Impact of climate on vegetation in Pindari watershed of Western Himalayas, Kumaun, India, using spatiotemporal analysis: 1972-2018.

Vegetation dynamics is an important aspect for determining climate change trends. The present study delineates to examine spatiotemporal changes of vegetation cover in Pindari valley (Kumaun Himalaya) from the 1972 to 2018 timeline. The study includes the calculation of vegetation spectral indices of normalized vegetation index (NDVI), extraction of different vegetation classes, and statistical analysis of the Mann-Kendall (MK) test on historical metrological data (especially precipitation and temperature) of the study site. For the statistical analysis of metrological data, the power data access viewer datasets have been used. The central feature classes of the study are grassland, scrubland, and forest cover. The results revealed that the region's forest cover significantly decreased by 24.74 sq. km from 1972 to 2018, increased in grassland cover by 17.84 sq. km, respectively, and a slight increase in scrubland class by 3.13 sq. km for the study period. The calculated NDVI shows significant changes over the study location; it has been noticed that the maximum values of the NDVI decreased by 0.24, and the minimum values show growth of about 0.047. The analysis indicates that climatic parameters such as precipitation and temperature are the main limiting factors affecting vegetation growth. The annual mean maximum temperature showed a decreasing trend. The estimated results show an increase in annual rainfall and annual minimum temperature, while the decreasing trend is observed in the case of maximum annual temperature. Objectives of the study are (1) spatiotemporal analysis of the vegetation cover, (2) identification of the main causes of change in the vegetation cover, and (3) statistical trend analysis of long-term metrological data. The outcome of the presented research work would be beneficial for the proper management and monitoring of the forest ecosystem.

Enhanced recovery protocol after single-stage bilateral primary total knee arthroplasty decreases duration of hospital stay without increasing complication rates.

PURPOSE: With an increasing number of total knee arthroplasty (TKA), protocols for better standard of patient care and shorter duration of hospital stay are necessary. Enhanced recovery (ER) protocols are becoming popular to meet these objectives. The current study aims to evaluate the clinical outcome of fast-track TKA using ER protocol in terms of length of hospital stay, perioperative complications and functional outcomes. METHODS: Patients undergoing single-stage bilateral primary TKA were prospectively included in the study. All patients went through a pre-defined ER protocol of TKA. Length of hospital stay, readmission rates, pain scores and functional scores of patients operated under ER protocol were compared with another matched historical control-group. Factors delaying the discharge of the patients by 48 h after the surgery were noted. RESULTS: We compared 275 patients undergoing single-stage bilateral primary TKA through ER protocol (Group 1) with 190 patients who had undergone bilateral primary TKA before the ER protocol was initiated (Group 2). The length of hospital stay (3.9 ± 2.1 days in group 1 and 7.5 ± 3.2 days in group 2, p 0.0001) and post-operative pain scores at 12 h (5.2 ± 2.9 in group 1 and 5.7 ± 2.1 in group 2, p 0.03) and 24 h (4.1 ± 1.6 in group 1 and 4.6 ± 1.4 in group 2, p 0.0005) were found to be significantly better with ER protocol. There was no difference in Oxford knee scores, infection rates, readmissions or mortality between the two groups. CONCLUSION: ER protocol in single-stage bilateral primary TKA resulted in decreased length of hospital stay without increasing complications and compromising the clinical outcome. It requires an integrated approach and adherence to clinical pathways. LEVEL OF EVIDENCE: Level II, Prospective comparative study.

In-silico screening of plant-derived antivirals against main protease, 3CLpro and endoribonuclease, NSP15 proteins of SARS-CoV-2.

Novel Coronavirus or SARS-CoV-2 outbreak has developed a pandemic condition all over the world. The virus is highly infectious and spreads by human to human local transmission mode. Till date, there is no vaccination or drugs been approved for the treatment by the World Health Organisation. Henceforth, the discovery of the potential drugs is an urgent and utmost requirement for the medical fraternity. Since, the side effects of plant-derived compounds will be lower compared to synthetic/chemical drugs. The Main protease (3CLpro or NSP5) and endoribonuclease (NSP15) proteins are necessity for viral replication and its survival in the host cell. In the present study, in-silico approach of drug development was used to search for potential antiviral plant-derived compounds as inhibitors against SARS-CoV-2 replication proteins. Eight plant-derived compounds of which the antiviral activity was known and available, and two reported drugs against SARS-CoV-2 selected for the molecular docking analysis. The docking results suggested that bisdemethoxycurcumin, demethoxycurcumin, scutellarin, quercetin and myricetin showed least binding energy, i.e., greater than -6.5 Kcal/mol against 3CLpro and endoribonuclease of SARS-CoV-2. Further studies of ADME-Tox and bioavailability of drugs were also performed that exhibited efficient parameters of drug likeness. Molecular dynamics simulation calculations were performed for the most negative binding affinity of the compound to evaluate the dynamic behavior,and stability of protein-ligand complex. Our findings suggest that these compounds could be potential inhibitors of SARS-CoV-2 main protease and endoribonuclease. However, further in-vitro and pre-clinical experiments would validate the potential inhibitors of SARS-CoV-2 proteins.