Search

Abstract Objective Glial fibrillary acidic protein (GFAP) is expressed in astrocytes and may be a useful marker of non‐active progressive multiple sclerosis (MS). We evaluate serum GFAP (sGFAP) in a large cohort of MS patients to determine if it predicts progression independent of relapse activity (PIRA), future gait aid, and conversion to secondary progressive disease (SPMS). Methods Adults with clinically isolated syndrome or any subtype of MS who were listed in the Brigham MS Center Research Database and had at least one sGFAP result were included. All clinic visits following first sample were analyzed for PIRA, future gait aid, and conversion to SPMS. Future cognitive dysfunction and fatigue were evaluated as secondary outcomes. Results In total, 741 patients were included (average age: 42.3, average disease duration: 3.7 years, median EDSS: 2, and median follow‐up duration: 10.0 years). Of 643 patients (86.8%) without progressive disease at baseline, 15.9% developed SPMS. Among all 741, 50.5% had PIRA and 18.6% developed a gait aid requirement. sGFAP level predicted PIRA, future gait aid, and conversion to SPMS in univariable models (p

Abstract Breast Cancer (BC) is the most common cause of cancer-associated deaths in females worldwide. Despite advancements in BC treatment driven by extensive characterization of its molecular hallmarks, challenges such as drug resistance, tumor relapse, and metastasis persist. Therefore, there is an urgent need for alternative treatment approaches with multi-modal efficacy to overcome these hurdles. In this context, natural bioactives are increasingly recognized for their pivotal role as anti-cancer compounds. This study focuses on predicting molecular targets for key herbal phytoconstituents—gallic acid, piperine, quercetin, resveratrol, and beta-sitosterol—present in the polyherbal formulation, Krishnadi Churna. Using an in-silico network pharmacology model, key genes were identified and docked against these marker compounds and controls. Mammary carcinoma emerged as the most significant phenotype of the putative targets. Analysis of an online database revealed that out of 135 predicted targets, 134 were mutated in breast cancer patients. Notably, ESR1, CYP19A1, and EGFR were identified as key genes which are known to regulate the BC progression. Docking studies demonstrated that the herbal phytoconstituents had similar or better docking scores than positive controls for these key genes, with convincing protein-ligand interactions confirmed by molecular dynamics simulations, MM/GBSA and free energy landscape (FEL) analysis. Overall, this study highlights the predictive potential of herbal phytoconstituents in targeting BC genes, suggesting their promise as a basis for developing new therapeutic formulations for BC.

Abstract Late blight is a serious disease of potato worldwide. Our study aimed to unveil genes involved in late blight resistance in potato by RNA-seq analysis after artificial inoculation under controlled conditions. In this study, two potato somatic hybrids (P7 and Crd6) and three varieties such as Kufri Girdhari, Kufri Jyoti and Kufri Bahar (control) were used. Transcriptiome analysis revealed statistically significant (p

Increasing urbanisation and industrialisation produce major environmental challenges such as air pollution, which endangers human, animal, and vegetation life. Reliable measurement, monitoring, and prediction of Air Quality (AQ) have emerged as key global concerns. The State Government-Municipal Corporation is working on policy reforms to fight the deterioration of air quality in Pune and other Indian cities. In this paper, Real Time Air Quality Surveillance & Forecasting System (RTAQSFS) has been developed, which work in the cascaded model incorporating electronics hardware as well as machine learning algorithms. The presence of air pollutants is measured using sensors like MQ135, MQ7, MQ131 etc. The performance of machine learning algorithms viz. Linear regression, Ridge regression, Lasso regression, Decision tree and Random Forest has been evaluated wrt. RMSE and R2. The experimental results show that Random Forest outperforms the other algorithm providing less RMSE and R2 as 99.9% for all the parameters.

This study introduces a novel SI2HR model, where “I2” denotes two infectious classes representing asymptomatic and symptomatic infections, aiming to investigate and analyze the cost-effective optimal control measures for managing COVID-19. The model incorporates a novel concept of infectious density-induced additional screening (IDIAS) and accounts for treatment saturation. Furthermore, the model considers the possibility of reinfection and the loss of immunity in individuals who have previously recovered. To validate and calibrate the proposed model, real data from November–December 2022 in Hong Kong are utilized. The estimated parameters obtained from this calibration process are valuable for prediction purposes and facilitate further numerical simulations. An analysis of the model reveals that delays in screening, treatment, and quarantine contribute to an increase in the basic reproduction number R0, indicating a tendency towards endemicity. In particular, from the elasticity of R0, we deduce that normalized sensitivity indices of baseline screening rate (θ), quarantine rates (γ, αs), and treatment rate (α) are negative, which shows that delaying any of these may cause huge surge in R0, ultimately increases the disease burden. Further, by the contour plots, we note the two-parameter behavior of the infectives (both symptomatic and asymptomatic). Expanding upon the model analysis, an optimal control problem (OCP) is formulated, incorporating three control measures: precautionary interventions, boosted IDIAS, and boosted treatment. The Pontryagin's maximum principle and the forward-backward sweep method are employed to solve the OCP. The numerical simulations highlight that enhanced screening and treatment, coupled with preventive interventions, can effectively contribute to sustainable disease control. However, the cost-effectiveness analysis (CEA) conducted in this study suggests that boosting IDIAS alone is the most economically efficient and cost-effective approach compared to other strategies. The CEA results provide valuable insights into identifying specific strategies based on their cost-efficacy ranking, which can be implemented to maximize impact while minimizing costs. Overall, this research offers significant insights for policymakers and healthcare professionals, providing a framework to optimize control efforts for COVID-19 or similar epidemics in the future.

The current work presents a theoretical framework to boost heat transmission in a ternary hybrid nanofluid with homogeneous and heterogeneous reactions in the conical gap between the cone and disk apparatus. Furthermore, the impacts of non-linear thermal radiation on the ternary hybrid nanofluid composed of white graphene, diamond, and titanium dioxide dispersed in water are analyzed.

The Ayush sector has attained buoyant growth in the past decade as a science, public health, medicine, and industry. Artificial Intelligence, computational drug designing, and other combinatorial techniques could further accelerate the sector's growth. In this edition, we delve into the confluence of Ayurveda and technology, a theme that resonates profoundly in the contemporary healthcare and wellness landscape. The fusion of Ayurveda, an ancient system of medicine rooted in holistic well-being, with cutting-edge technology, is not just a paradigm shift but a necessary evolution in pursuing an integrated healthcare system where all systems have their defined, recognized, and respected contribution. Here, We are highlight one-such fusion initiative ''Ayurinformatics Laboratory''.

Background: Postoperative delirium is a common complication in patients undergoing elective surgery under general anesthesia. We aimed to minimize the incidence with an oral dose of 3 mg of melatonin administered the night before surgery. Methods: Hundred and sixty-two patients aged 40–80 years posted for various urological and gastrointestinal surgeries under general anesthesia with no preoperative cognitive deficits were randomly distributed equally to melatonin or control groups. In the control group, routine premedication was done with tablet alprazolam (0.25 mg) and ranitidine (150 mg), but in the melatonin group, the patients were given 3 mg melatonin orally the night before surgery along with routine premedication. The CAM scale was used for diagnosis of postoperative delirium. Results: Incidence of delirium was significantly lower in the melatonin group, 23.5%, 8.6%, and 2.5% at 6, 24, and 48 hours, respectively, and the corresponding mean (SD) values of CAM scores were 1.37 (1.30), 1.07 (1.03), and 0.69 (0.80). In contrast, the incidence of delirium was 46.9%, 30.9%, and 16% at 6, 24, and 48 hours, respectively, in the control group. There was a significant reduction in anxiety, a lower incidence of cognitive dysfunction (i.e., MoCA score

Abstract The multifaceted nature of multiple sclerosis requires quantitative biomarkers that can provide insights related to diverse physiological pathways. To this end, proteomic analysis of deeply-phenotyped serum samples, biological pathway modeling, and network analysis were performed to elucidate inflammatory and neurodegenerative processes, identifying sensitive biomarkers of multiple sclerosis disease activity. Here, we evaluated the concentrations of > 1400 serum proteins in 630 samples from three multiple sclerosis cohorts for association with clinical and radiographic new disease activity. Twenty proteins were associated with increased clinical and radiographic multiple sclerosis disease activity for inclusion in a custom assay panel. Serum neurofilament light chain showed the strongest univariate correlation with gadolinium lesion activity, clinical relapse status, and annualized relapse rate. Multivariate modeling outperformed univariate for all endpoints. A comprehensive biomarker panel including the twenty proteins identified in this study could serve to characterize disease activity for a patient with multiple sclerosis.

Abstract Bullous cutaneous reactions can be caused by many factors, including vaccines.1 However, among all cutaneous reactions following coronavirus disease 2019 (COVID‐19) mRNA vaccines, bullous reactions are rare. Here, we describe two patients with delayed generalised bullous cutaneous reactions 7 days after receiving Moderna (Spikevax®) and Pfizer–BioNTech (Comirnaty®) COVID‐19 vaccination, respectively.

The persistent non-biodegradable nature of plastic highlights the urgent need for effective waste management and resource conservation, underscoring the crucial importance of recycling and upcycling within a cradle-to-cradle framework. This research introduces an eco-friendly and straightforward upcycling process for plastic waste, which produces significant quantities of reduced graphene oxide through a carefully designed 2-stage pyrolysis method. To enhance the electrochemical properties of the reduced graphene oxide, they were doped with heteroatoms (i.e. nitrogen and phosphorus) via a hydrothermal route. Also, as the nature of the electrolyte plays a significant role in electrochemical analysis, a comparative evaluation of the supercapacitive performance of the heteroatom-doped reduced graphene oxide was conducted across various aqueous electrolytes, including 1 M H2SO4, 6 M KOH, and 2 M KCl, as well as hydrogel polymer electrolytes such as 1 M H2SO4/1 M PVA, 2 M KCl/1 M PVA, and 6 M KOH/1 M PVA. Our results demonstrate that synthesized material from waste plastic exhibits excellent performance, particularly when combined with a 1 M H2SO4 electrolyte, achieving the highest specific capacitance of 407.6 F/g. In conclusion, this study presents a cost-effective and sustainable approach to promoting a circular economy by repurposing waste plastic for energy storage applications.

Verification of real-time system properties using formal models can improve system design and quality. The Timed Petri net is a formal model for modelling and designing real-time systems with time constraints. Furthermore, model checking is a formal verification method used to verify system properties using model checkers. This article proposes an automated transformation system for mapping a Timed Petri net into one of the common model checkers, the SPIN PROMELA model, to verify real-time system properties. This approach enables the combination of two modelling paradigms and supports system verification using system design models. In this study, the system properties were verified using both the simulation method and linear temporal logic formulas supported by the SPIN model checker. Timed Petri net models of two different case studies, a central server computer system and a manufacturing Kanban system were considered to verify the boundedness, liveness and system behavioral properties using the proposed transformation system.

ABSTRACTPresent economy is largely dependent on the precise forecasting of the business avenues using the stock market data. As the stock market data falls under the category of big data, the task of handling becomes complex due to the presence of a large number of investment choices. In this paper, investigations have been carried out on the stock market data analysis using various density-based clustering approaches. For experimentation purpose, the stock market data from Quandl stock market was used. It was observed that the effectiveness of Dynamic Quantum clustering approach were better. This is because it has better adopting capability according of changing patterns of the stock market data. Similarly performances of other density-based clustering approaches like Weighted Adaptive Mean Shift Clustering, DBSCAN and Expectation Maximization and also partitive clustering methods such as k-means, k-medoids and fuzzy c means were also experimented on the same stock market data. The performance of all the approaches was tested in terms of standard measures. It was found that in majority of the cases, Dynamic Quantum clustering outperforms the other density-based clustering approaches. The algorithms were also subjected to paired t-tests which also confirmed the statistical significance of the results obtained.

AbstractIn this work, an empirically derived multi-domain model of a light-emitting diode (LED) luminaire is proposed. The optical, electrical, and thermal characteristics of LEDs are obtained from the data sheets provided by manufacturers. Both transient and steady-state performance of LED luminaire were realized theoretically and validated against experimental findings from earlier investigations. The difficulties encountered in creating an ideal LED luminaire are discoursed and examined. Most of the studies on LED luminaires described in prior works ignored the influence of luminaire housing and optics on the thermal management of the luminaire. Knowledge of thermal time constants of LED luminaires is important, as they decide the rate of luminous flux decay when LED lighting systems are used for long periods of operation. Thermal time constants also decide the time taken by the LED junction to reach steady state with its surrounding. From the study it is inferred that the increase in junction temperature and deterioration of luminous flux is controlled by the product of the single most dominant thermal resistance from the junction to a point along the heat conduction path and sum of all the downstream thermal capacitances. This is true as in most cases LED device thermal capacitance is very less related to the thermal capacitance of the heat-sink, hence the product of single most dominant thermal resistance and thermal capacitance of heat-sink decide the rate of rising of junction temperature or luminous flux deterioration.

A major change in postgraduate medical education in India will occur in 2023 with the launch of the District Residency Programme (DRP) by the National Medical Commission (NMC). This required three-month curriculum immerses resident physicians in the reality of district-level healthcare with the goal of bridging the knowledge gap between theory and practice. Postgraduates in community medicine have a priceless chance to close the knowledge gap between theory and practice using DRP. They become well-prepared public health professionals ready to have a big impact on community health by actively engaging in public health programs and obtaining clinical experience within the district system. Its successful implementation will however depend on addressing the issues of what work community medicine postgraduates should be assigned and custom duties for them.

Recently published near full-length KSHV genomes from a Cameroon Kaposi sarcoma case-control study showed strong evidence of viral recombination and mixed infections, but no sequence variations associated with disease. Using the same methodology, an additional 102 KSHV genomes from 76 individuals with KSHV-associated diseases have been sequenced. Diagnoses comprise all KSHV-associated diseases (KAD): Kaposi sarcoma (KS), primary effusion lymphoma (PEL), KSHV-associated large cell lymphoma (KSHV-LCL), a type of multicentric Castleman disease (KSHV-MCD), and KSHV inflammatory cytokine syndrome (KICS). Participants originated from 22 different countries, providing the opportunity to obtain new near full-length sequences of a wide diversity of KSHV genomes. These include near full-length sequence of genomes with KSHV K1 subtypes A, B, C, and F as well as subtype E, for which no full sequence was previously available. High levels of recombination were observed. Fourteen individuals (18%) showed evidence of infection with multiple KSHV variants (from two to four unique genomes). Twenty-six comparisons of sequences, obtained from various sampling sites including PBMC, tissue biopsies, oral fluids, and effusions in the same participants, identified near complete genome conservation between different biological compartments. Polymorphisms were identified in coding and non-coding regions, including indels in the K3 and K15 genes and sequence inversions here reported for the first time. One such polymorphism in KSHV ORF46, specific to the KSHV K1 subtype E2, encoded a mutation in the leucine loop extension of the uracil DNA glycosylase that results in alteration of biochemical functions of this protein. This confirms that KSHV sequence variations can have functional consequences warranting further investigation. This study represents the largest and most diverse analysis of KSHV genome sequences to date among individuals with KAD and provides important new information on global KSHV genomics.

Soil provides essential nutrients for plant growth, but excess salts hinder development, making crops more vulnerable under climate change conditions. Soil microorganisms play a significant role in nutrient cycling. However, limited information is available on microbial behavior/community changes, and functional diversity in different soil types (normal, sodic, and highly sodic) and cropping systems [rice-wheat (RW); rice-wheat-mungbean (RWMb); maize-wheat-mungbean (MWMb)] and management practices in the north-western Indo-Gangetic Plains of India. We investigated the influence of different soil types on physical and chemical properties at the surface level (0–15 cm) in relation to soil microbial population, activities, and functional diversity, focusing on community-level physiological profiling (CLPP) under different agriculture systems. Seven treatment combinations of soil types, cropping systems, and management practices were evaluated. Soil pHs were found to be lower in zero-till (ZT)-based sodic soil than in conventional-till (CT) sodic soil. Soil organic carbon (SOC) (0.91 and 0.90%) content and available N (154.46 and 132.74 kg ha−1) were higher with the ZT-based system under normal (N) soils (ZT-RWMb-N and ZT-MWMb-N) than in CT-based normal soil (0.67 and 121.04 kg ha−1). Similarly, higher SOC and N (0.85 and 76.11 kg ha−1) were found under ZT management in sodic soils (S) than under CT management (0.73% and 121.05 kg ha−1). Substrate utilization (amino acids, amines, carbohydrates, carboxylic acids, phenolic compounds, and polymers) increased with the incubation period. During 0–120 h of incubation, the highest utilization of amino acids, amines, carboxylic acids, phenolic compounds, and polymers was observed for ZT-MWMb-S soils, while the lowest was recorded for ZT-MWMb-N soils. Under high salt conditions, soil enzymatic activities (dehydrogenase, acid phosphatase, alkaline phosphatase, etc.) declined significantly compared to normal soils, affecting soil chemical and physical conditions. Microbial population and enzyme activities decreased with increasing salt stress across all cropping systems. These findings suggest that adopting efficient crop management practices can help mitigate the adverse effects of soil salinity on microbial diversity and soil health, thereby enhancing sustainable agricultural productivity in salt-affected regions.

The present experiment was conducted during 2020–21, 2021–22 and 2022–23 at Regional Station, ICAR-Central Potato Research Institute, Gwalior, Madhya Pradesh to evaluate the best spacing combination and dehaulming time for enhancing the seed size potato (Solanum tuberosum L.) tubers and profitability under north-central plains of India. Experiment was conducted in a split-plot design (SPD) comprised of 5 spacing combinations, viz. S1, Ridge and furrow 60 cm × 20 cm (Control); S2, Ridge and furrow 60 cm × 15 cm; S3, Flatbed paired row 90 cm bed width (two rows at 40 cm × 20 cm plant to plant spacing); S4, Flatbed paired row 90 cm bed width (two rows at 40 cm × 15 cm plant to plant spacing); and S5, Flatbed triple row 90 cm bed width (three rows at 20 cm × 20 cm plant to plant spacing) in main plot and 2 haulm killing dates, viz. 70 and 80 days after planting in sub plots. The treatment S5, Flatbed triple row 90 cm bed width (three rows at 20 cm × 20 cm plant to plant spacing) spacing combination significantly increased the number and weight of seed size tubers, net seed size and total tuber yield when dehaulming was done after 80 days. The highest increase in seed size and total tubers over control reported when dehaulmed at 70 days. However, the treatment S3, Flatbed paired row 90 cm bed width (two rows at 40 cm × 20 cm plant to plant spacing) with 80 days haulm killing recorded highest seed size tuber 58.03% and benefit cost (B:C) ratio of 2.51:1 among all other treatment combinations. Though, treatment S3 i.e. flatbed paired row 90 cm bed width (two rows at 40 cm × 20 cm plant to plant spacing) with 80 days haulm killing combination require higher seed rate but can be an economically viable option for enhancing seed size tuber percent and B:C ratio.

This work describes the first-ever use of Wet copper slag for 2-(subs.)-1H-benzimidazoles synthesis. It is a by-product of the copper refining and smelting processes utilized as a basic catalyst in the present work. Wet copper slag is prepared by immersing a natural copper slag in water to improve the hydroxyl group and, hence, basicity. Iron oxide content in the copper slag helps provide the basic environment and uses surrounding air for the successful oxidative condensation of imines and o-phenylenediamine. Various aldehydes reacted well with p-anisidine for imine synthesis. Further reaction with substituted o-phenylenediamine and o-phenylenediamine gives desired 2-(subs.)-1H-benzimidazoles in environmental-friendly ethanol: water (9:1) as solvent at 85 °C within 40 to 60 min. The present method showed critical advantages of mild reaction conditions, wide availability, recyclability, and magnetic separability of a Copper-slag with moderate to excellent product yields. Overall, the present approach offers a promising route for the efficient and sustainable synthesis of 2-(subs.)-1H-benzimidazoles, which have a wide range of applications in various fields, including pharmaceuticals, agrochemicals, and materials science.

AbstractOcimum basilicum var. purpurascens Bentham 1830 (Red Rubin Basil) is an aromatic herb belonging to the family Lamiaceae and is known for its medicinal uses. It is commonly used in traditional medicine to treat cardiovascular diseases and obesity. It possesses anti-inflammatory, antioxidant, antifungal, and anti-spasmodic properties. In our recent study, we assembled the chloroplast genome sequence of O. basilicum var. purpurascens using Illumina paired-end sequencing technology. The assembled chloroplast genome was 152,407 base pairs (bp), inclusive of a large single-copy (LSC) region accounting for 83,409 bp and a small single-copy (SSC) region spanning 17,604 bp. Two inverted repeats (IRs) interspersed these regions, each 25,697 bp long. The chloroplast genome harbored 132 genes, comprising 88 protein-coding genes, 36 transfer RNA (tRNA), and eight rRNA genes. Among these, nine genes encompassed a single intron, two presented with two introns, with the remaining devoid of any introns. The overall GC content of the chloroplast genome was determined to be 38%. The GC content in the LSC, SSC, and IR regions was 35.9%, 31.6%, and 43.1%, respectively. Our phylogenetic exploration of the chloroplast genomes elucidated that O. basilicum var. purpurascens exhibits close genetic affinity with O. basilicum var. basilicum and other constituents of the Ocimum genus within the Lamiaceae family.

Electrocardiogram is a heartbeat signal that can be used for the application of Human-computer interaction. Electrocardiography (ECG) is a prominent way to analyze heart rate and to diagnose cardiovascular disease. However, its availability has been restricted, especially in contexts with limited resources, due to the cost associated with conventional ECG signal processing equipment. The importance of ECG signal processing classification for improving early diagnoses in clinical and remote monitoring contexts is highlighted here. The dataset considered for this work is MIT-BIH arrhythmia which has 15 categories and summarized in 5 classes Normal (N), Superventricular ectopic beats (SVEB), Ventricular ectopic beat (VEB), Fusion beats (F), and Unknown beats (Q). The work discusses the importance of automated classification techniques that make it possible to analyze vast amounts of ECG data effectively and objectively. This research presents an investigation into the classification of ECG signals using various Machine Learning (ML) methods. Specifically, the performance of Decision Tree (DT), Logistic Regression (LR), Random Forest (RF), K Nearest Neighbor (KNN), and Support Vector Machine (SVM) algorithms are examined. Among these classifiers, RF exhibits a remarkable accuracy of 98%. The results demonstrate the superior performance of the proposed approach for heartbeat classification systems.

Introduction: Focal Segmental Glomerulosclerosis (FSGS) is a nephrotic syndrome with a variety of clinicopathological presentations and varied responses to treatment. Hence, this study attempts to classify FSGS based on clinical presentation and pathological findings on kidney biopsy, which is essential for appropriate treatment and avoidance of inappropriate use of immunosuppressants. Aim: To analyse clinicopathological findings and responses to immunosuppressants in FSGS. Materials and Methods: A retrospective cohort study was conducted at Department of Nephrology, Vydehi Institute of Medical Sciences and Research Centre Bengaluru, Karnataka, India, to analyse clinicopathological parameters such as urine analysis, 24-hour urine protein, serum creatinine, serum albumin, lipid profile, renal biopsy details, and response to treatment in 97 patients. The study was planned, analysed, and executed between January 2023 and February 2023. All variables were expressed as mean±standard deviation or percentage. Statistical analysis was performed using Statistical Package for Social Sciences (SPSS) software version 16.0. Results: Among a total of 97 patients, 64% were males. Sudden onset oedema was observed in 90% of the cases, while nephrotic proteinuria was seen in 71%. The Not Otherwise Specified (NOS) variant was noted in 60% of the cases. Complete remission was observed in 61%, suggesting a possible primary FSGS. Persistent nephrotic proteinuria with a poor response to therapy was noted in 32%, indicating a possible secondary/genetic FSGS, despite adequate immunosuppressive therapy. Therefore, differentiating between primary and secondary forms of FSGS has therapeutic and prognostic implications. Accurate diagnosis of each form of FSGS is vital to avoid unnecessary immunosuppressive-based therapy and establish appropriate treatment. Conclusion: Resistance to steroid therapy was observed in one-third of FSGS patients. It is likely that unrecognised genetic FSGS or secondary FSGS were included among the study group of primary FSGS, leading to misinterpretation of treatment responses in primary FSGS. Hence, a clinicopathological approach for correctly differentiating between primary FSGS, secondary (maladaptive, viral, or toxic) FSGS, and genetic FSGS helps in making correct treatment decisions.

The leaves essential oil of Eupatorium odoratum (L.) obtained by the hydro-distillation method was light yellowish in colour, having pungent aromatic fragrance with the yield of 0.010%. Fifteen secondary metabolites were identified via the GC-MS analysis of the essential oil and tau-Cadinol (20.10%) was found to be the major secondary metabolite in the essential oil followed by α Bisabolol (15.33%), cis-muurola-4 (14) 5- diene (10.79%), Isobornyl acetate (6.40%), and Isocaryophyllene (5.39%). The antimicrobial efficacy was investigated via agar well diffusion technique and essential oil was most effective against P. aeruginosa with inhibition zone 22.00±0.57 mm, which was followed by E. coli (19.00±0.57 mm), S. aureus (18.33±0.33 mm), K. pneumoniae (16.50±0.33 mm), and S. pyogenes (11.00±0.33 mm). MIC and MBC values were observed lowest against P. aeruginosa, i.e. 3.12µl/ml and 6.24µl/ml, respectively. Antioxidant activity of essential oil was investigated by DPPH and H2O2 scavenging assay and IC50 value was found very low, i.e. 10.58µl/ml and 11.76µl/ml, respectively, so the essential oil was considered as a potential antioxidant agent. The results validate scientifically the traditional utilization of leaves essential oil of E. odoratum in traditional medicinal system and confirmed that it can be used as modern phytomedicines as an antimicrobial as well as antioxidant agent.

Abstract Background SARS-CoV-2 infections caused mild-to-moderate illness. However, a sizable portion of infected people experience a rapid progression of hyper-inflammatory and hypoxic respiratory illness that necessitates an effective and safer remedy to combat COVID-19. Methods A total of 150 COVID-19-positive patients with no to mild symptoms, between the age groups 19–65 years were enrolled in this randomized, open-labeled three-armed clinical trial. Among them, 136 patients completed the study with RT-PCR negative reports. The patients received herbal drugs orally (Group A (Adhatoda vasica; AV; 500 mg; n = 50); Group B (Tinospora cordifolia; TC; 500 mg; n = 43), and Group C (AV + TC; 250 mg each; n = 43)) for 14 days. Clinical symptoms, vital parameters, and viral clearance were taken as primary outcomes, and biochemical, hematological parameters, cytokines, and biomarkers were evaluated at three time points as secondary outcomes. Results We found that the mean viral clearance time was 13.92 days (95% confidence interval [CI] 12.85–14.99) in Group A, 13.44 days (95% confidence interval [CI] 12.14–14.74) in Group B, and 11.86 days (95% confidence interval [CI] 10.62–13.11) days in Group C. Over a period of 14 days, the mean temperature in Groups A, and B significantly decreased linearly. In Group A, during the trial period, eosinophils, and PT/INR increased significantly, while monocytes, SGOT, globulin, serum ferritin, and HIF-1α, a marker of hypoxia reduced significantly. On the other hand, in Group B hsCRP decreased at mid-treatment. Eosinophil levels increased in Group C during the treatment, while MCP-3 levels were significantly reduced. Conclusions All the patients of the three-armed interventions recovered from COVID-19 and none of them reported any adverse effects from the drugs. Group C patients (AV + TC) resulted in a quicker viral clearance as compared to the other two groups. We provide the first clinical report of AV herbal extract acting as a modifier of HIF-1α in COVID-19 patients along with a reduction in levels of ferritin, VEGF, and PT/INR as the markers of hypoxia, inflammation, and thrombosis highlighting the potential use in progression stages, whereas the TC group showed immunomodulatory effects. Trial registration Clinical Trials Database -India (ICMR-NIMS), CTRI/2020/09/028043. Registered 24th September 2020, https://www.ctri.nic.in/Clinicaltrials/pdf_generate.php?trialid=47443&EncHid=&modid=&compid=%27,%2747443det%27 Graphical Abstract

Purpose To evaluate the safety and efficacy of vacuum-assisted breast biopsy (VABB) under ultrasound and stereotactic guidance.

Phyla nodiflora (Linnaeus) Greene (1899) is a perennial creeping herb belonging to the family Verbenaceae. It has numerous pharmacological properties, including anti-dandruff, anti-inflammatory, anti-oxidant, anti-melanogenesis, anti-hypertensive, and anti-hyperuricemic properties. We generated the complete chloroplast genome sequence of P. nodiflora using Illumina paired-end sequencing data. The P. nodiflora chloroplast genome is 154,341 bp in length, containing a large single copy (LSC) region of 85,185 bp and a small single copy (SSC) region of 17,222 bp, separated by a pair of inverted repeats (IRs) of 25,967 bp. The genome contained 128 genes, including 86 protein-coding, 34 tRNA, and eight rRNA genes. Six genes had one intron, one gene had two introns, and the others did not have an intron. Overall GC content of the chloroplast genome was 39%, while those of LSC, SSC, and IR regions were 38.2%, 33.7%, and 44%, respectively. Phylogenetic analysis of the chloroplast genome revealed that P. nodiflora is closely related to the other species from Verbenaceae.

Diploid inbred-based F1 hybrid True Potato Seed (DHTPS) breeding is a novel technique to transform potato breeding and cultivation across the globe. Significant efforts are being made to identify elite diploids, dihaploids and develop diploid inbred lines for heterosis exploitation in potatoes. Self-incompatibility is the first obstacle for developing inbred lines in diploid potatoes, which necessitates the introgression of a dominant S locus inhibitor gene (Sli) for switching self-incompatibility to self-compatibility. We evaluated a set of 357 diploid clones in different selfing generations for self-compatibility and degree of homozygosity using Kompetitive Allele Specific PCR (KASP) Single Nucleotide Polymorphism (SNP) markers. A subset of 10 KASP markers of the Sli candidate region on chromosome 12 showed an association with the phenotype for self-compatibility. The results revealed that the selected 10 KASP markers for the Sli gene genotype could be deployed for high throughput rapid screening of self-compatibility in diploid populations and to identify new sources of self-compatibility. The homozygosity assessed through 99 KASP markers distributed across all the chromosomes of the potato genome was 20–78 % in founder diploid clones, while different selfing generations, i.e., S0, S1, S2 and S3 observed 36.1–80.4, 56.9–82.8, 59.5–85.4 and 73.7–87.8 % average homozygosity, respectively. The diploid plants with ∼80 % homozygosity were also observed in the first selfing generation, which inferred that homozygosity assessment in the early generations itself could identify the best plants with high homozygosity to speed up the generation of diploid inbred lines.

The Neuromyelitis Optica Spectrum Disorders (NMOSD) constitute a spectrum of rare autoimmune diseases of the central nervous system characterized by episodes of transverse myelitis, optic neuritis, and other demyelinating attacks. Previously thought to be a subtype of multiple sclerosis, NMOSD is now known to be a distinct disease with unique pathophysiology, clinical course, and treatment options. Although there have been significant recent advances in the diagnosis and treatment of NMOSD, the field still lacks clinically validated biomarkers that can be used to stratify disease severity, monitor disease activity, and inform treatment decisions. Here we review many emerging NMOSD biomarkers including markers of cellular damage, neutrophil-to-lymphocyte ratio, complement, and cytokines, with a focus on how each biomarker can potentially be used for initial diagnosis, relapse surveillance, disability prediction, and treatment monitoring.

BackgroundRegulatory B cells (Bregs) play a pivotal role in suppressing immune responses, yet there is still a lack of cell surface markers that can rigorously identify them. In mouse models for multiple sclerosis (MS), TIM-1 or TIGIT expression on B cells is required for maintaining self-tolerance and regulating autoimmunity to the central nervous system. Here we investigated the activities of human memory B cells that differentially express TIM-1 and TIGIT to determine their potential regulatory function in healthy donors and patients with relapsing-remitting (RR) MS.MethodsFACS-sorted TIM-1+/-TIGIT+/- memory B (memB) cells co-cultured with allogenic CD4+ T cells were analyzed for proliferation and induction of inflammatory markers using flow cytometry and cytokine quantification, to determine Th1/Th17 cell differentiation. Transcriptional differences were assessed by SMARTSeq2 RNA sequencing analysis.ResultsTIM-1-TIGIT- double negative (DN) memB cells strongly induce T cell proliferation and pro-inflammatory cytokine expression. The TIM-1+ memB cells enabled low levels of CD4+ T cell activation and gave rise to T cells that co-express IL-10 with IFNγ and IL-17A or FoxP3. T cells cultured with the TIM-1+TIGIT+ double positive (DP) memB cells exhibited reduced proliferation and IFNγ, IL-17A, TNFα, and GM-CSF expression, and exhibited strong regulation in Breg suppression assays. The functional activity suggests the DP memB cells are a bonafide Breg population. However, MS DP memB cells were less inhibitory than HC DP memB cells. A retrospective longitudinal study of anti-CD20 treated patients found that post-treatment DP memB cell frequency and absolute number were associated with response to therapy. Transcriptomic analyses indicated that the dysfunctional MS-derived DP memB/Breg population exhibited increased expression of genes associated with T cell activation and survival (CD80, ZNF10, PIK3CA), and had distinct gene expression compared to the TIGIT+ or TIM-1+ memB cells.ConclusionThese findings demonstrate that TIM-1/TIGIT expressing memory B cell subsets have distinct functionalities. Co-expression of TIM-1 and TIGIT defines a regulatory memory B cell subset that is functionally impaired in MS.

Bruton’s tyrosine kinase (BTK) inhibitors are an emerging class of therapeutics in multiple sclerosis (MS). BTK is expressed in B-cells and myeloid cells, key progenitors of which include dendritic cells, microglia and macrophages, integral effectors of MS pathogenesis, along with mast cells, establishing the relevance of BTK inhibitors to diverse autoimmune conditions. First-generation BTK inhibitors are currently utilized in the treatment of B-cell malignancies and show efficacy in B-cell modulation. B-cell depleting therapies have shown success as disease-modifying treatments (DMTs) in MS, highlighting the potential of BTK inhibitors for this indication; however, first-generation BTK inhibitors exhibit a challenging safety profile that is unsuitable for chronic use, as required for MS DMTs. A second generation of highly selective BTK inhibitors has shown efficacy in modulating MS-relevant mechanisms of pathogenesis in preclinical as well as clinical studies. Six of these BTK inhibitors are undergoing clinical development for MS, three of which are also under investigation for chronic spontaneous urticaria (CSU), rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). Phase II trials of selected BTK inhibitors for MS showed reductions in new gadolinium-enhancing lesions on magnetic resonance imaging scans; however, the safety profile is yet to be ascertained in chronic use. Understanding of the safety profile is developing by combining safety insights from the ongoing phase II and III trials of second-generation BTK inhibitors for MS, CSU, RA and SLE. This narrative review investigates the potential of BTK inhibitors as an MS DMT, the improved selectivity of second-generation inhibitors, comparative safety insights established thus far through clinical development programmes and proposed implications in female reproductive health and in long-term administration.

The world has undergone a remarkable transformation from the era of famines to an age of global food production that caters to an exponentially growing population. This transformation has been made possible by significant agricultural revolutions, marked by the intensification of agriculture through the infusion of mechanical, industrial, and economic inputs. However, this rapid advancement in agriculture has also brought about the proliferation of agricultural inputs such as pesticides, fertilizers, and irrigation, which have given rise to long-term environmental crises. Over the past two decades, we have witnessed a concerning plateau in crop production, the loss of arable land, and dramatic shifts in climatic conditions. These challenges have underscored the urgent need to protect our global commons, particularly the environment, through a participatory approach that involves countries worldwide, regardless of their developmental status. To achieve the goal of sustainability in agriculture, it is imperative to adopt multidisciplinary approaches that integrate fields such as biology, engineering, chemistry, economics, and community development. One noteworthy initiative in this regard is Zero Budget Natural Farming, which highlights the significance of leveraging the synergistic effects of both plant and animal products to enhance crop establishment, build soil fertility, and promote the proliferation of beneficial microorganisms. The ultimate aim is to create self-sustainable agro-ecosystems. This review advocates for the incorporation of biotechnological tools in natural farming to expedite the dynamism of such systems in an eco-friendly manner. By harnessing the power of biotechnology, we can increase the productivity of agro-ecology and generate abundant supplies of food, feed, fiber, and nutraceuticals to meet the needs of our ever-expanding global population.

AbstractOcimum basilicum L. var. basilicum (Sweet Basil) is an aromatic herb belonging to the family Lamiaceae and is known for its medicinal uses. It is commonly used in traditional medicine for its therapeutic value, including anti-allergic, anti-inflammatory, antioxidant, antitumor, and antimicrobial properties. In this study, we generated the complete chloroplast genome sequence of O. basilicum var. basilicum using Illumina paired-end sequencing data. The chloroplast genome was 152,407 bp in length, containing a large single-copy (LSC) region of 83,409 bp and a small single-copy region (SSC) of 17,604 bp, separated by a pair of inverted repeats (IRs) of 25,697 bp. The genome contained 134 genes, including 89 protein-coding, 37 tRNA, and eight rRNA genes. Nine genes had one intron, two genes had two introns, and others did not have any intron. Overall GC content of the chloroplast genome was 38%, while that of LSC, SSC, and IR regions was 35.9%, 31.6%, and 43.1%, respectively. Phylogenetic analysis of the chloroplast genomes revealed that O. basilicum var. basilicum was closely related to Ocimum basilicum from the Ocimum species.

Ocimum americanum Linnaeus 1755 (Lemon basil) is an essential medicinal species in the Ocimum genus. Its leaf decoction is traditionally used to treat diabetes, constipation, diarrhea, piles, and dysentery. The essential oils from this species have intense fungicidal activity. The complete chloroplast genome sequence of O. americanum was assembled from Illumina paired-end sequencing data. The O. americanum chloroplast genome was 152,460 bp in length, containing a large single copy (LSC) region of 83,459 bp and a small single copy (SSC) region of 17,607 bp, separated by a pair of inverted repeats (IRs) of 25,697 bp. The genome contained 134 unique genes, including 89 protein-coding, 37 tRNA, and eight rRNA genes. Among them, nine genes had a single intron, and two genes contained two introns. The overall GC content of the chloroplast genome was 38%, while the corresponding values of LSC, SSC, and IR regions were 35.8%, 31.7%, and 43.1%, respectively. In the phylogenetic analysis, all the Ocimum species formed a group closely related to Plectranthus barbatus. O. americanum was more closely related to O. gratissimum and O. basilicum than the other species of Ocimum included in this study.

Nonalcoholic fatty liver disease or NAFLD is a complex and multifactorial liver disease that is affecting a majority of the world’s population now more than ever. The review focuses on two major contributing factors in the etiology of the disease – oxidative stress and the gut microbiota. There is a complex interplay between oxidative stress and the gut microbiota in the pathogenesis of NAFLD. Oxidative stress in NAFLD can result from both the accumulation of lipids in the liver and the interactions between gut-derived metabolites and the liver. Dysbiosis in the gut microbiota can contribute to oxidative stress by promoting the production of reactive oxygen species and altering the balance of antioxidant systems. This interplay between oxidative stress and the gut microbiota can create a vicious cycle, where dysbiosis contributes to oxidative stress, and oxidative stress further promotes dysbiosis, exacerbating liver damage in NAFLD. Understanding the intricate relationship between oxidative stress, the gut microbiota, and NAFLD is essential for developing targeted therapeutic strategies. In this context, more scientific research is required to unravel the complex and interconnecting pathways underlying NAFLD pathogenesis and progression. Modulating the gut microbiota through dietary interventions, prebiotics, probiotics, and change in lifestyle may help restore microbial balance and reduce oxidative stress in NAFLD.

Background Palmaris longus (PL) is a short-bellied muscle with a long tendon that merges with the palmar aponeurosis. It is supplied by the median nerve and acts as a tensor of the palmar aponeurosis and flexes the wrist. This tendon is commonly used for tendon transfers and as a donor for tendon graft. There are numerous clinical tests to detect the presence of PL like Schaeffer's test, Thompson's test, Mishra's test I, Mishra's test II, Pushpakumar's “two-finger sign” method, and AIIMS test. The principle of all these tests is to make the tendon prominent by eliciting its flexor action and then its identification by inspection and palpation.

Immunological dysregulation and inflammation may play a role in the nature of menstruation. Coronavirus disease 2019 (COVID-19) can produce a systemic inflammatory reaction that involves extrapulmonary organs and can also affect the immune system. This study aimed to analyze changes in the menstrual cycle in coronavirus (COVID)-positive women of reproductive age. Methods: The data of 35 women of reproductive age were collected telephonically from said patients admitted to the COVID Health Centre (CHC) ward of All India Institute of Ayurveda, New Delhi, during June 20, 2020, to October 31, 2020. Purposive sampling was used for data collection. Wyatt menstrual pictogram and Visual Analogue Scale (VAS) were used to assess the bleeding pattern and pain during menstruation, respectively. Results: Clinically, changes were noted in post-COVID menstruation such as irregularity, polymenorrhea, oligomenorrhea, clots, and menstrual flow in days. However, all results were statistically non-significant. But significant (P = 0.003) menstrual pain was reported. Conclusion: Menstrual changes were observed in COVID-19-positive women belonging to the reproductive age group.

Environmental catastrophes on a global scale have prompted a thorough evaluation of river morphology for sustainable basin development methods. Geomorphological investigations of river basins can provide significant information regarding Quaternary tectonic deformations. The present investigation intends to reveal tectonic imprints in the Bearma River Basin (BRB). Bearma is a significant river in central India that flows through Vindhyan Supergroup, Lameta, and Deccan Trap and contributes to developing the architecture of the marginal Gangetic plain. The digital elevation data has been utilized to obtain the morphotectonic indices, tectonic activity classes, and topographic characteristics. Bearma is an elongated basin with uplifted topography, continuously migrating channels, high hypsometric integral, and several stream length-gradient anomalies, indicating tectonically controlled. According to the tectonic activity index, 15.33%, 38.99%, and 46.55% areas of the BRB have high, moderate, or low tectonic activity, respectively. In conjunction with field investigations, the topographic and lineament study of the BRB has revealed significant relief variations and the importance of tectonic activity over erosion and depositional processes in determining the landscape. Reactivation of basement faults and subsurface lineaments caused by Himalayan tectonics and the Narmada Son North Fault have resulted in the recent deformation and development of the hydrographic network. HIGHLIGHTS The morphotectonic evolution of Northern Peninsular river basin in drought-prone Bundelkhand region of India is addressed.; Reactivation of basement faults and subsurface lineaments due to Himalayan tectonic and activity of Son-Narmada North Fault are responsible for the recent deformation and development of the current hydrographic network in the Northern Peninsular River Basin.;

Abstract Deregulation of vascular endothelial growth factor (VEGF) levels leads to retinopathy of prematurity (ROP). Vitamin D (VIT-D) is known to regulate VEGF in an oxygen dependent manner. The purpose of this study was to correlate tear levels of VEGF and VIT-D with different ROP stages in preterm infants. In this prospective cross-sectional study, we enrolled 104 pre-term infants. They were grouped into: Group-1 (Classical ROP) and Group-2 (Aggressive ROP), which were further subdivided into Group-1A (progressing), Group-1B (regressing), Group-2A (pre-treatment), and Group-2B (post-treatment). Tear VEGF and VIT-D levels and their association with different ROP stages were assessed. Stage 1 and stage 2 had higher whereas stage 3 had lower VEGF levels in Group-1B compared to Group-1A. Stage 1 and stage 3 showed higher levels of VIT-D with no difference in stage 2 in Group-1B compared to Group-1A., Group-2B showed higher VEGF and lower VIT-D levels compared to Group-2A. Presence of a positive correlation at an early stage (stage 1) of ROP and a negative correlation at a more advanced stage (stage 3) of ROP with VIT-D and VEGF implies stage-specific distinct signaling crosstalk. These findings suggest that VIT-D supplementation may have the potential to modify the course and outcome of ROP.

Glioblastoma is one of the most devastating central nervous system disorders. Being a highly vascular brain tumor, it is distinguished by aberrant vessel architecture. This lends credence to the idea that endothelial cells (ECs) linked with glioblastoma vary fundamentally from ECs seen in the healthy human brain. To effectively design an antiangiogenic treatment, it is crucial to identify the functional and phenotypic characteristics of tumor-associated ECs. The ECs associated with glioblastoma are less prone to apoptosis than control cells and are resistant to cytotoxic treatments. Additionally, ECs associated with glioblastoma migrate more quickly than control ECs and naturally produce large amounts of growth factors such as endothelin-1, interleukin-8, and vascular endothelial growth factor (VEGF). For designing innovative antiangiogenic drugs that particularly target tumor-related ECs in gliomas, it is critical to comprehend these distinctive features of ECs associated with gliomas. This review discusses the process of angiogenesis, other factors involved in the genesis of tumors, and the possibility of ECs as a potential target in combating glioblastoma. It also sheds light on the association of tumor microenvironment and ECs with immunotherapy. This review, thus gives us the hope that neuro endothelial targeting with growth factors and angiogenesis regulators combined with gene therapy would open up new doorways and change our traditional perspective of treating cancer.

Psychological Wellbeing in students has recently have lot of attention, especially after the pandemic outburst. Positive psychological intervention was proved as helpful in promoting psychological wellbeing and it is also connected with the story reading intervention; stories which support positive indicators. This study showed the effect of story reading intervention on positive indicators of psychological wellbeing over time for a group of literature undergraduates (n=60). This included 8 stories provided to the intervention group only for comparison with control group. The result showed that story reading led to improvement in students’ positive constructs over a period of eight weeks. The obtained results are discussed in the context of their implications for story reading intervention in higher educational institutions.

Pyomyositis or tropical pyomyositis is an uncommon infection of skeletal muscle that may be primary or secondary. Primary type has bacterial aetiology, and Staphylococcus aureus is associated in most cases. The diagnosis requires high index of suspicion and careful assessment of radiological investigations. Diagnosis often requires magnetic resonance imaging (MRI) for better delineation of the disease process, associated site involvement and exclusion of related conditions. Evacuation of pus coupled with appropriate antibiotic therapy is the mainstay and curative in most cases. Caution, however, is required due to increased morbidity, protracted course of recovery and mortality in few cases. The association with comorbidities including immunocompromised status compounds the problem. We describe our experience with this condition in a series of five cases (four male and one female) with diverse involvement of scapular muscle. All cases had primary pyomyositis except one case secondary to shoulder joint tuberculosis. Right side was involved in three and left in two cases. Infraspinatus was commonly involved, and one case had extensive involvement around scapula. All cases were managed by one or multiple aspiration, except one managed with open surgical drainage. The outcome was good in all cases with no recurrence or complication noted in their respective follow-up. Primary care centres may play important role in the early diagnosis of this condition with clinical evaluation and judicious use of imaging. Cases with severe involvement or those requiring advanced procedures may be referred to higher centres as per the requirement. Most of the times, timely diagnosis, antibiotic therapy and drainage of the pus is required and may also be performed in the primary care level through a standard protocol.

While the impact of combustible cigarette smoking on cardiovascular disease (CVD) is well-established, the longitudinal association of non-traditional tobacco products with subclinical and clinical CVD has not been fully explored due to: 1) limited data availability; and 2) the lack of well-phenotyped prospective cohorts. Therefore, there is the need for sufficiently powered well-phenotyped datasets to fully elucidate the CVD risks associated with non-cigarette tobacco products. The Cross-Cohort Collaboration (CCC)-Tobacco is a harmonized dataset of 23 prospective cohort studies predominantly in the US. A priori defined variables collected from each cohort included baseline characteristics, details of traditional and non-traditional tobacco product use, inflammatory markers, and outcomes including subclinical and clinical CVD. The definitions of the variables in each cohort were systematically evaluated by a team of two physician-scientists and a biostatistician. Herein, we describe the method of data acquisition and harmonization and the baseline sociodemographic and risk profile of participants in the combined CCC-Tobacco dataset. The total number of participants in the pooled cohort is 322782 (mean age: 59.7 ± 11.8 years) of which 76% are women. White individuals make up the majority (73.1%), although there is good representation of other race and ethnicity groups including African American (15.6%) and Hispanic/Latino individuals (6.4%). The prevalence of participants who never smoked, formerly smoked, and currently smoke combustible cigarettes is 50%, 36%, and 14%, respectively. The prevalence of current and former cigar, pipe, and smokeless tobacco is 7.3%, 6.4%, and 8.6%, respectively. E-cigarette use was measured only in follow-up visits of select studies, totaling 1704 former and current users. CCC-Tobacco is a large, pooled cohort dataset that is uniquely designed with increased power to expand knowledge regarding the association of traditional and non-traditional tobacco use with subclinical and clinical CVD, with extension to understudied groups including women and individuals from underrepresented racial-ethnic groups.

Introduction Acute exposure to e-cigarette aerosol has been shown to have potentially deleterious effects on the cardiovascular system. However, the cardiovascular effects of habitual e-cigarette use have not been fully elucidated. Therefore, we aimed to assess the association of habitual e-cigarette use with endothelial dysfunction and inflammation – subclinical markers known to be associated with increased cardiovascular risk. Methods In this cross-sectional study, we analyzed data from 46 participants (23 exclusive e-cigarette users; 23 non-users) enrolled in the VAPORS-Endothelial function study. E-cigarette users had used e-cigarettes for ≥6 consecutive months. Non-users had used e-cigarettes

Abstract Human mobility has played a critical role in the spread of COVID-19. The understanding of mobility helps in getting information on the acceleration or control of the spread of disease. The COVID-19 virus has been spreading among several locations despite all the best efforts related to its isolation. To comprehend this, a multi-patch mathematical model of COVID-19 is proposed and analysed in this work, where-in limited medical resources, quarantining, and inhibitory behaviour of healthy individuals are incorporated into the model. Furthermore, as an example, the impact of mobility in a three-patch model is studied considering the three worst-hit states of India, i.e. Kerala, Maharashtra and Tamil Nadu, as three patches. Key parameters and the basic reproduction number are estimated from the available data. Through results and analyses, it is seen that Kerala has a higher effective contact rate and has the highest prevalence. Moreover, if Kerala is isolated from Maharashtra or Tamil Nadu, the number of active cases will increase in Kerala but reduce in the other two states. Our findings indicate that the number of active cases will decrease in the high prevalence state and increase in the lower prevalence states if the emigration rate is higher than the immigration rate in the high prevalence state. Overall, proper travel restrictions are to be implemented to reduce or control the spread of disease from the high-prevalence state to other states with lower prevalence rates.

Abstract Background Multiple sclerosis (MS) is a chronic demyelinating autoimmune disorder which may cause long-term disability. MicroRNA (miRNA) are stable, non-coding molecules that have been identified in our Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women’s Hospital (CLIMB)-cohort, as well as other international cohorts, as potential disease biomarkers in MS. However, few studies have evaluated the association of miRNA expression early in the MS disease course with long-term outcomes. Therefore, we aimed to evaluate the potential role of three candidate serum miRNAs previously correlated with MS disability in patients with MS, miR-320b, miR-25-3p and miRNA 486-5p, as early biomarkers of MS disability at 10-year follow-up. Main body We included 144 patients with serum obtained within three years of MS onset. miRNA expression was measured by RNA extraction followed by RT-PCR. Demographic, clinical, brain MRI and other biomarkers were collected. The primary outcome was the association between early miRNA expression and retaining benign MS, defined as EDSS ≤ 2 at 10-year follow-up. Among the 144 patients, 104 were benign and 40 were not benign at 10-year follow-up. 89 (62%) were women, with mean age at onset 37.7 (SD: 9.6) years. Patients who retained benign MS had lower values of miR-25-3p (p = 0.047) and higher miR-320b (p = 0.025) values. Development of SPMS was associated with higher miR-320b (p = 0.002) levels. Brain parenchymal fraction at year 10 was negatively correlated with miR-25-3p (p = 0.0004) and positively correlated with miR-320b (p = 0.006). No association was found between miR-486-5p and any outcome, and 10-year T2-lesion volume was not associated with any miRNA. Conclusions Our results show that miR-320b and miR-25-3p expression are early biomarkers associated with MS severity and brain atrophy. This study provides class III evidence of that miR-320b and miR-25-3p are associated with long-term MS disability which may be a potential tool to risk-stratify patients with MS for early treatment decisions.

The future of South Asia’s major production system (rice–wheat rotation) is at stake due to continuously aggravating pressure on groundwater aquifers and other natural resources which will further intensify with climate change. Traditional practices, conventional tillage (CT) residue burning, and indiscriminate use of groundwater with flood irrigation are the major drivers of the non-sustainability of rice–wheat (RW) system in northwest (NW) India. For designing sustainable practices in intensive cereal systems, we conducted a study on bundled practices (zero tillage, residue mulch, precise irrigation, and mung bean integration) based on multi-indicator (system productivity, profitability, and efficiency of water, nitrogen, and energy) analysis in RW system. The study showed that bundling conservation agriculture (CA) practices with subsurface drip irrigation (SDI) saved ~70 and 45% (3-year mean) of irrigation water in rice and wheat, respectively, compared to farmers’ practice/CT practice (pooled data of Sc1 and Sc2; 1,035 and 318 mm ha−1). On a 3-year system basis, CA with SDI scenarios (mean of Sc5–Sc8) saved 35.4% irrigation water under RW systems compared to their respective CA with flood irrigation (FI) scenarios (mean of Sc3 and Sc4) during the investigation irrespective of residue management. CA with FI system increased the water productivity (WPi) and its use efficiency (WUE) by ~52 and 12.3% (3-year mean), whereas SDI improved by 221.2 and 39.2% compared to farmers practice (Sc1; 0.69 kg grain m−3 and 21.39 kg grain ha−1 cm−1), respectively. Based on the 3-year mean, CA with SDI (mean of Sc5–Sc8) recorded −2.5% rice yield, whereas wheat yield was +25% compared to farmers practice (Sc1; 5.44 and 3.79 Mg ha−1) and rice and wheat yield under CA with flood irrigation were increased by +7 and + 11%, compared to their respective CT practices. Mung bean integration in Sc7 and Sc8 contributed to ~26% in crop productivity and profitability compared to farmers’ practice (Sc1) as SDI facilitated advancing the sowing time by 1 week. On a system basis, CA with SDI improved energy use efficiency (EUE) by ~70% and partial factor productivity of N by 18.4% compared to CT practices. In the RW system of NW India, CA with SDI for precise water and N management proved to be a profitable solution to address the problems of groundwater, residue burning, sustainable intensification, and input (water and energy) use with the potential for replication in large areas in NW India.

Background: Concerns and misconceptions surrounding coronavirus disease 2019 (COVID-19) vaccines may account for vaccine hesitancy and low uptake. Aim: To determine prevalence of COVID-19 vaccine hesitancy, vaccine-related misconceptions, and predictors of vaccine hesitancy among South Africans. Setting: Community setting in five districts in KwaZulu- Natal province. Methods: Between August 20, 2021, and September 27, 2021, we conducted a cross-sectional survey, interviewing 300 unvaccinated adults amid the national vaccination campaign. Predictors of hesitancy were identified through multivariable logistic regression analysis. Results: Participants had a median age of 29 years (IQR: 23–39), 86.7% were Black African, 63.2% were male, 53.3% resided in rural communities, and 59.3% (95% CI: 53.8% – 64.9%) were classified as vaccine hesitant. The primary reason for not vaccinating was a lack of trust in the vaccine (62.1%). Factors associated with reduced vaccine hesitancy included age (participants aged 35–49 years: OR: 0.28, 95% CI: 0.18–0.64, p = 0.003; participants over 50 years: OR: 0.18, 95% CI: 0.07–0.47, p = 0.0004), previous COVID-19 infection (OR: 0.31, 95% CI: 0.11–0.87, p = 0.03), and receiving vaccine information from healthcare workers (OR: 0.32, 95% CI: 0.10–1.0, p = 0.05). Unemployed (OR: 2.14, 95% CI: 1.1–4.2, p = 0.03) and self-employed individuals (OR: 2.98, 95% CI: 1.27–7.02, p = 0.01) were more likely to be vaccine hesitant. Conclusion: COVID-19 vaccine hesitancy rates are high in KwaZulu-Natal. Uptake could be enhanced by healthcare workers leading information campaigns with messages targeting younger individuals, the unemployed, and the self-employed. Contribution: This survey provides evidence to improve COVID-19 vaccination uptake in South Africa.

Background: Understanding the relationship between climate change and child health is crucial for making informed decisions and implementing successful treatments. However, the extensive scientific literature on climate change and child health has not undergone a general dynamic quantitative examination. This bibliometric analysis was undertaken to study pertinent literature on climate change impact on child health over a 22-year period (2000–2022). Methods: change's A five-step PRISMA process was used to extract 1864 peer-reviewed journal articles from the Web of Science Core Collection database. The data was analysed using bibliometric software tools, including VOSviewer, CiteSpace, and Biblioshiny. Results: The annual publication patterns showed a steady increase in the number of articles published on climate change's impact on child health over the past 22 years. The most well-known climate change impact on child health monitoring articles was identified, as were the most active researchers and top-contributing nations in climate change impact on child health research. The most dependable information sources for academic researchers were further determined using the citation analysis of journals. Finally, science mapping analysis was used to visualize and study the conceptual and intellectual knowledge structures to chart the evolution of the research area related to climate change's impact on child health. Science mapping also identified emerging trends and intriguing research directions. Conclusions: This bibliometric analysis provides a comprehensive overview of the scientific landscape of climate change's impact on child health research. The findings highlight the growing interest in this field of research, as well as the key players and emerging trends. This study's results can inform future research priorities and develop effective interventions to protect children from the harmful effects of climate change.

The laboratory-scale (in-vitro) microbial fermentation based on screening of process parameters (factors) and statistical validation of parameters (responses) using regression analysis. The recent trends have shifted from full factorial design towards more complex response surface methodology designs such as Box-Behnken design, Central Composite design. Apart from the optimisation methodologies, the listed designs are not flexible enough in deducing properties of parameters in terms of class variables. Machine learning algorithms have unique visualisations for the dataset presented with appropriate learning algorithms. The classification algorithms cannot be applied on all datasets and selection of classifier is essential in this regard. To resolve this issue, factor-response relationship needs to be evaluated as dataset and subsequent preprocessing could lead to appropriate results. The aim of the current study was to investigate the data-mining accuracy on the dataset developed using in-vitro pyruvate production using organic sources for the first time. The attributes were subjected to comparative classification on various classifiers and based on accuracy, multilayer perceptron (neural network algorithm) was selected as classifier. As per the results, the model showed significant results for prediction of classes and a good fit. The learning curve developed also showed the datasets converging and were linearly separable.