Longitudinal patterns of natural hazard exposures and anxiety and depression symptoms among young adults in four low- and middle-income countries.

We estimated the effect of community-level natural hazard exposure during prior developmental stages on later anxiety and depression symptoms among young adults and potential differences stratified by gender. We analyzed longitudinal data (2002-2020) on 5585 young adults between 19 and 26 years in Ethiopia, India, Peru, and Vietnam. A binary question identified community-level exposure, and psychometrically validated scales measured recent anxiety and depression symptoms. Young adults with three exposure histories ("time point 1," "time point 2," and "both time points") were contrasted with their unexposed peers. We applied a longitudinal targeted minimum loss-based estimator with an ensemble of machine learning algorithms for estimation. Young adults living in exposed communities did not exhibit substantially different anxiety or depression symptoms from their unexposed peers, except for young women in Ethiopia who exhibited less anxiety symptoms (average causal effect [ACE] estimate = - 8.86 [95% CI: - 17.04, - 0.68] anxiety score). In this study, singular and repeated natural hazard exposures generally were not associated with later anxiety and depression symptoms. Further examination is needed to understand how distal natural hazard exposures affect lifelong mental health, which aspects of natural hazards are most salient, how disaster relief may modify symptoms, and gendered, age-specific, and contextual differences.

Metagenomic evaluation of peanut rhizosphere microbiome from the farms of Saurashtra regions of Gujarat, India.

The narrow zone of soil around the plant roots with maximum microbial activity termed as rhizosphere. Rhizospheric bacteria promote the plant growth directly or indirectly by providing the nutrients and producing antimicrobial compounds. In this study, the rhizospheric microbiota of peanut plants was characterized from different farms using an Illumina-based partial 16S rRNA gene sequencing to evaluate microbial diversity and identify the core microbiome through culture-independent (CI) approach. Further, all rhizospheric bacteria that could grow on various nutrient media were identified, and the diversity of those microbes through culture-dependent method (CD) was then directly compared with their CI counterparts. The microbial population profiles showed a significant correlation with organic carbon and concentration of phosphate, manganese, and potassium in the rhizospheric soil. Genera like Sphingomicrobium, Actinoplanes, Aureimonas _A, Chryseobacterium, members from Sphingomonadaceae, Burkholderiaceae, Pseudomonadaceae, Enterobacteriaceae family, and Bacilli class were found in the core microbiome of peanut plants. As expected, the current study demonstrated more bacterial diversity in the CI method. However, a higher number of sequence variants were exclusively present in the CD approach compared to the number of sequence variants shared between both approaches. These CD-exclusive variants belonged to organisms that are more typically found in soil. Overall, this study portrayed the changes in the rhizospheric microbiota of peanuts in different rhizospheric soil and environmental conditions and gave an idea about core microbiome of peanut plant and comparative bacterial diversity identified through both approaches.

Measurement and analysis of change in research scholars' knowledge and attitudes toward statistics after PhD coursework.

BACKGROUND: Knowledge of statistics is highly important for research scholars, as they are expected to submit a thesis based on original research as part of a PhD program. As statistics play a major role in the analysis and interpretation of scientific data, intensive training at the beginning of a PhD programme is essential. PhD coursework is mandatory in universities and higher education institutes in India. This study aimed to compare the scores of knowledge in statistics and attitudes towards statistics among the research scholars of an institute of medical higher education in South India at different time points of their PhD (i.e., before, soon after and 2-3 years after the coursework) to determine whether intensive training programs such as PhD coursework can change their knowledge or attitudes toward statistics. METHODS: One hundred and thirty research scholars who had completed PhD coursework in the last three years were invited by e-mail to be part of the study. Knowledge and attitudes toward statistics before and soon after the coursework were already assessed as part of the coursework module. Knowledge and attitudes towards statistics 2-3 years after the coursework were assessed using Google forms. Participation was voluntary, and informed consent was also sought. RESULTS: Knowledge and attitude scores improved significantly subsequent to the coursework (i.e., soon after, percentage of change: 77%, 43% respectively). However, there was significant reduction in knowledge and attitude scores 2-3 years after coursework compared to the scores soon after coursework; knowledge and attitude scores have decreased by 10%, 37% respectively. CONCLUSION: The study concluded that the coursework program was beneficial for improving research scholars' knowledge and attitudes toward statistics. A refresher program 2-3 years after the coursework would greatly benefit the research scholars. Statistics educators must be empathetic to understanding scholars' anxiety and attitudes toward statistics and its influence on learning outcomes.

Multilevel analysis of determinants in postnatal care utilisation among mother-newborn pairs in India, 2019-21.

Background: Postnatal care (PNC) utilisation within 24 hours of delivery is a critical component of health care services for mothers and newborns. While substantial geographic variations in various health outcomes have been documented in India, there remains a lack of understanding regarding PNC utilisation and underlying factors accounting for these geographic variations. In this study, we aimed to partition and explain the variation in PNC utilisation across multiple geographic levels in India. Methods: Using India's 5th National Family Health Survey (2019-21), we conducted four-level logistic regression analyses to partition the total geographic variation in PNC utilisation by state, district, and cluster levels, and to quantify how much of theses variations are explained by a set of 12 demographic, socioeconomic, and pregnancy-related factors. We also conducted analyses stratified by selected states/union territories. Results: Among 149 622 mother-newborn pairs, 82.29% of mothers and 84.92% of newborns were reported to have received PNC within 24 hours of delivery. In the null model, more than half (56.64%) of the total geographic variation in mother's PNC utilisation was attributed to clusters, followed by 26.06% to states/union territories, and 17.30% to districts. Almost 30% of the between-state variation in mother's PNC utilisation was explained by the demographic, socioeconomic, and pregnancy-related factors (i.e. state level variance reduced from 0.486 (95% confidence interval (CI) = 0.238, 0.735) to 0.320 (95% CI = 0.152, 0.488)). We observed consistent results for newborn's PNC utilisation. State-specific analyses showed substantial geographic variation attributed to clusters across all selected states/union territories. Conclusions: Our findings highlight the consistently large cluster variation in PNC utilisation that remains unexplained by compositional effects. Future studies should explore contextual drivers of cluster variation in PNC utilisation to inform and design interventions aimed to improve maternal and child health.

Retrospective Analysis of Hospital Acquired Infection and Antibiotic Resistance in Coronary Care Unit (CCU), Adult, and Pediatric Cardiology Wards.

BACKGROUND: Antibiotics resistance is an paramount threat affecting the whole world but nowhere situation is as gloomy as in India. No study till date regarding epidemiology of hospital acquired infections in coronary care units(CCU) and cardiology wards from India. From Indian perspective it is the first observational study to analyse microbiological profile and antibiotic resistance in CCU. The purpose of this observational study is to explore the epidemiology and importance of infections in CCU patients. METHODOLOGY: After ethics committee approval, the records of all patients who were admitted in coronary care units, adult and pediatric cardiology wards surgery between January 2020 and December 2021 were reviewed retrospectively. The type of organism,source of infection ,age wise distribution and seasonal variability among patients who developed hospital acquired infection (HAI) were determined. RESULTS: 271 patients developed microbiologically documented HAI during from January 2020 to December 2021. Maximum number of organisms(78/271 28.78%) are isolated from urinary samples ,followed by blood stream(60/271 22.14%) and Endotracheal tube (54/271 19.92%). Acinetobacter baumanii (53/271, 19.5%) being the most common isolate among all the samples taken . Acinetobacter was the most frequent pathogens isolated in patients with LRTI and blood stream infection while E. coli was from urinary tract infection . In the adult population, infection with E. coli(24.6%) is the most common followed by Klebsiella pneumoniae (12.8%) and Acinetobacter baumanii (10.1%). In the pediatric population Acinetobacter baumanii (38.6%%) is the most common followed by Klebsiella pneumoniae (20.5%) and Methicillin Resistant Staphylococcus aureus, MRSA (6.8%). Commonly used antibiotics eg ciprofloxacin,ceftazidime and amikacin were found to be resistant against the top three isolates. CONCLUSION: Urinary tract was the most common site of infection and Gram-negative bacilli, the most common pathogens in adult as well as pediatric population. Antibiotic resistance was maximum with commonly isolated microorganisms.

COVID-19 vaccine hesitancy among adults in India: A primary study based on health behavior theories and 5C psychological antecedents model.

Despite the significant success of India's COVID-19 vaccination program, a sizeable proportion of the adult population remains unvaccinated or has received a single dose of the vaccine. Despite the recommendations of the Government of India for the two doses of the COVID-19 vaccine and the precautionary booster dose, many people were still hesitant towards the COVID-19 full vaccination. Hence, this study aimed to identify the primary behavioral and psychological factors contributing to vaccine hesitancy. Cross-sectional data was collected via a multi-stage sampling design by using a scheduled sample survey in the Gorakhpur district of Uttar Pradesh, India, between 15 July 2022 to 30 September 2022. This study has utilized three health behavior models-the Health Belief Model (HBM), the Theory of Planned Behavior (TPB), and the 5C Psychological Antecedents of vaccination, and employed bivariate and multivariable binary logistic regression model to assess the level of vaccine hesitancy and predictive health behavior of the respondents. Results indicate that among the constructs of the HBM and 5C Antecedents models, "perceived benefits", "confidence" and "collective responsibility" showed a lesser likelihood of COVID-19 vaccine hesitancy. However, in the TPB model constructs, a 'negative attitude towards the vaccine' showed a four times higher likelihood of COVID-19 vaccine hesitancy. From the future policy perspective, this study suggested that addressing the issue of 'negative attitudes towards the vaccine' and increasing the trust or confidence for the vaccine through increasing awareness about the benefits of the vaccination in India may reduce vaccine hesitancy.

Towards food security: Exploring the spatio-temporal dynamics of soybean in India.

India is the world's largest edible oil importer, and soybean oil accounts for a major portion of those imports, with implications for the Indian economy. Despite being the 4th largest globally in terms of harvested soybean area and 5th largest in terms of production, India is still heavily dependent on imports to meet the vegetable oil requirement for its population. It is therefore imperative to understand the dynamics and trends in India's soybean production to help the country achieve self-sufficiency in edible oils. This study provides the first spatially explicit analysis of soybean in India, using long-term spatial and temporal statistics at national and subnational levels, using spatial and temporal statistical analysis models to examine the historical trends and its future prospects. Our analysis details the overall soybean expansion across the country and the increase in production but we also note that the annual growth rate has declined in each consecutive decade even though the area continues to expand. The average national yield has been stagnant at around 1 T/Ha but for some of the low-producing districts, a higher yield of more than 3 T/ha is reported. For most major producing districts, soybean yields are below 1.5 T/Ha. The state of Madhya Pradesh which was the major soybean producer is now matched by the state of Maharashtra in terms of production, however, Madhya Pradesh still has the largest area under soybean. We analyzed soybean hotspot expansion in India and found that the mean center of the soybean area and production has shifted approximately 93 km towards the south and 24 km to the west as the crop is rapidly being adopted in the southern and western parts of India expanding the hotspot in these parts. District-level analysis showed that the total number of districts constituting hotspots of soybean cultivation in India has increased from 29 to 42 in three decades. Furthermore, analysis of soybean oil and meal consumption with respect to the national population, import, export, domestic production, GDP per capita, and price of soybean oil and meal suggests that soybean oil and meal are highly correlated with GDP per capita and population, indicating that consumption of soybean oil and meal is likely to increase as GDP per capita increases, and future demand is expected to rise with the anticipated growth in the Indian population. Increased soybean production can play a significant role in increasing national food security for India and reducing dependence on foreign oil imports and also help the economy with soy meal exports. Understanding the spatiotemporal variability in area and yield will help target interventions to increase production. Given the overall low yields with high variability in production, particularly in recent years primarily due to successive extreme rains and droughts in major producing districts and the overall need to increase production to meet the country's demand, there is a pressing need for government policies and research aimed at narrowing the yield gap and developing soybean varieties that are more productive and resilient to climate change.

Translating global evidence into local implementation through technical assistance: a realist evaluation of the Bloomberg philanthropies initiative for global Road safety.

BACKGROUND: Traffic-related crashes are a leading cause of premature death and disability. The safe systems approach is an evidence-informed set of innovations to reduce traffic-related injuries and deaths. First developed in Sweden, global health actors are adapting the model to improve road safety in low- and middle-income countries via technical assistance (TA) programs; however, there is little evidence on road safety TA across contexts. This study investigated how, why, and under what conditions technical assistance influenced evidence-informed road safety in Accra (Ghana), Bogotá (Colombia), and Mumbai (India), using a case study of the Bloomberg Philanthropies Initiative for Global Road Safety (BIGRS). METHODS: We conducted a realist evaluation with a multiple case study design to construct a program theory. Key informant interviews were conducted with 68 government officials, program staff, and other stakeholders. Documents were utilized to trace the evolution of the program. We used a retroductive analysis approach, drawing on the diffusion of innovation theory and guided by the context-mechanism-outcome approach to realist evaluation. RESULTS: TA can improve road safety capabilities and increase the uptake of evidence-informed interventions. Hands-on capacity building tailored to specific implementation needs improved implementers' understanding of new approaches. BIGRS generated novel, city-specific analytics that shifted the focus toward vulnerable road users. BIGRS and city officials launched pilots that brought evidence-informed approaches. This built confidence by demonstrating successful implementation and allowing government officials to gauge public perception. But pilots had to scale within existing city and national contexts. City champions, governance structures, existing political prioritization, and socio-cultural norms influenced scale-up. CONCLUSION: The program theory emphasizes the interaction of trust, credibility, champions and their authority, governance structures, political prioritization, and the implement-ability of international evidence in creating the conditions for road safety change. BIGRS continues to be a vehicle for improving road safety at scale and developing coalitions that assist governments in fulfilling their role as stewards of population well-being. Our findings improve understanding of the complex role of TA in translating evidence-informed interventions to country-level implementation and emphasize the importance of context-sensitive TA to increase impact.

Investigating the relationship of government revenue and expenditure on economic growth using a generalized method of moments: Does state-level panel ensure sustainable growth?

The current research project investigates the correlation between economic growth, government spending, and public revenue in seventeen Indian states spanning the years 1990 to 2020. An analysis of the relationship between key fiscal policy variables and economic growth was conducted utilising a panel data approach, the Generalised Method of Moments (GMM), and fully modified Ordinary Least Squares (FMOLS & DOLS) estimation. In our investigation, we assessed the impacts of non-tax revenue, development plan expenditure, tax revenue, and development non-plan expenditure on (i) the net state domestic product (NSDP) and (ii) the NSDP per capita. The findings indicate that the selected fiscal variables are significantly related. The results indicate that expeditious expansion of the fiscal sector is obligatory to stimulate economic growth in India and advance the actual development of the economies of these states.

Ethnobotanical survey of medicinal plants used by various ethnic tribes of Mizoram, India.

Mizoram has a diverse range of ethnic and cultural groups, including the Lushai, Mara, Lai, Bawm, Hmar, Chakma, and Bru. Through practice and experience in their protracted battles with disease and the harsh natural environment, they have amassed rich folk medicine knowledge. The preservation of indigenous knowledge, identification of bioactive compounds, and the eventual discovery of novel medicinal plant species all depend on the documentation of the traditional uses of medicinal plants. Therefore, the present study was designed to document the ethnomedicinal knowledge related to the usage of medicinal plants in Mizoram, India. An ethnobotanical study of medicinal plants was carried out in 17 villages of 5 districts in Mizoram between September 2022 and January 2023. A total of 128 informants (77 males and 51 females) were interviewed. Information was gathered through field observations, group discussions, and semistructured interviews. The data were presented using descriptive statistics. To assess the importance of medicinal plant species, quantitative indices such as the informant consensus factor (ICF), fidelity level (FL), use value (UV), and cultural index (CI) was used. In our ethnobotanical investigation, 102 medicinal plant species from 95 genera and 58 families were recorded and documented. The majority of them (90 species) were obtained from wild habitats. The majority of the documented species were trees (48), followed by herbs (23 species) and shrubs (21 species). The most common method of preparation was decoction (67 species). Diabetes had the highest ICF value (0.81), followed by cancer, liver problems, and hypertension (0.8). The fidelity level (FL) of indigenous communities in the study area was evaluated to determine the dependability and consistency of herbal drug use. Indigenous knowledge and the variety of medicinal plant species that are used are of great values. The therapeutic applications of documented plants provide fundamental information for additional studies centered on pharmacological investigations and the preservation of the most significant species.

Early-Neonatal, Late-Neonatal, Postneonatal, and Child Mortality Rates Across India, 1993-2021.

Importance: The global success of the child survival agenda depends on how rapidly mortality at early ages after birth declines in India, and changes need to be monitored to evaluate the status. Objective: To understand the disaggregated patterns of decrease in early-life mortality across states and union territories (UTs) of India. Design, Setting, and Participants: Repeated cross-sectional data from the 5 rounds of the National Family Health Survey conducted in 1992-1993, 1998-1999, 2005-2006, 2015-2016, and 2019-2021 were used in a representative population-based study. The study was based on data of children born in the past 5 years with complete information on date of birth and age at death. The analysis was conducted in February 2024. Exposure: Time and geographic units. Main Outcomes and Measures: Mortality rates were computed for 4 early-life periods: early-neonatal (first 7 days), late-neonatal (8-28 days), postneonatal (29 days to 11 months), and child (12-59 months). For early and late neonatal periods, the rates are expressed as deaths per 1000 live births, for postneonatal, as deaths per 1000 children aged at least 29 days and for child, deaths per 1000 children aged at least 1 year. These are collectively mentioned as deaths per 1000 for all mortalities. The relative burden of each of the age-specific mortalities to total mortality in children younger than 5 years was also computed. Results: The final analytical sample included 33 667 (1993), 29 549 (1999), 23 020 (2006), 82 294 (2016), and 64 242 (2021) children who died before their fifth birthday in the past 5 years of each survey. Mortality rates were lowest for the late-neonatal and child periods; early-neonatal was the highest in 2021. Child mortality experienced the most substantial decrease between 1993 and 2021, from 33.5 to 6.9 deaths per 1000, accompanied by a substantial reduction in interstate inequalities. While early-neonatal (from 33.5 to 20.3 deaths per 1000), late-neonatal (from 14.1 to 4.1 deaths per 1000), and postneonatal (from 31.0 to 10.8 deaths per 1000) mortality also decreased, interstate inequalities remained notable. The mortality burden shifted over time and is now concentrated during the early-neonatal (48.3% of total deaths in children younger than 5 years) and postneonatal (25.6%) periods. A stagnation or worsening for certain states and UTs was observed from 2016 to 2021 for early-neonatal, late-neonatal, and postneonatal mortality. If this pattern continues, these states and UTs will not meet the United Nations Sustainable Development Goal targets related to child survival. Conclusions and Relevance: In this repeated cross-sectional study of 5 time periods, the decrease in mortality during early-neonatal and postneonatal phases of mortality was relatively slower, with notable variations across states and UTs. The findings suggest that policies pertaining to early-neonatal and postneonatal mortalities need to be prioritized and targeting of policies and interventions needs to be context-specific.

On-farm crop diversity, conservation, importance and value: a case study of landraces from Western Ghats of Karnataka, India.

Landraces are important genetic resources that have a significant role in maintaining the long-term sustainability of traditional agro-ecosystems, food, nutrition, and livelihood security. In an effort to document landraces in the on-farm conservation context, Central Western Ghat region in India was surveyed. A total of 671 landraces belonging to 60 crops were recorded from 24 sites. The custodian farmers were found to conserve a variety of crops including vegetables, cereals and pulses, perennial fruits, spices, tuber and plantation crops. The survey indicated a difference in the prevalence of landraces across the sites. A significant difference with respect to the Shannon-diversity index, Gini-Simpson index, evenness, species richness, and abundance was observed among the different survey sites. Computation of a prevalence index indicated the need for immediate intervention in the form of collecting and ex situ conservation of landraces of some crops as a back-up to on-farm conservation. The study also identified the critical determinants of on-farm conservation, including (i) suitability to regional conditions, (ii) relevance in regional cuisine and local medicinal practices, (iii) cultural and traditional significance, and (iv) economic advantage. The information documented in this study is expected to promote the collection and conservation of landraces ex situ. The National Genebank housed at ICAR-NBPGR, New Delhi conserves around 550 accessions of landraces collected from the Central Western Ghats region surveyed in this report. Information collected from custodian farmers on specific uses will be helpful to enhance the utilization of these accessions.

A culture-independent approach, supervised machine learning, and the characterization of the microbial community composition of coastal areas across the Bay of Bengal and the Arabian Sea.

BACKGROUND: Coastal areas are subject to various anthropogenic and natural influences. In this study, we investigated and compared the characteristics of two coastal regions, Andhra Pradesh (AP) and Goa (GA), focusing on pollution, anthropogenic activities, and recreational impacts. We explored three main factors influencing the differences between these coastlines: The Bay of Bengal's shallower depth and lower salinity; upwelling phenomena due to the thermocline in the Arabian Sea; and high tides that can cause strong currents that transport pollutants and debris. RESULTS: The microbial diversity in GA was significantly higher than that in AP, which might be attributed to differences in temperature, soil type, and vegetation cover. 16S rRNA amplicon sequencing and bioinformatics analysis indicated the presence of diverse microbial phyla, including candidate phyla radiation (CPR). Statistical analysis, random forest regression, and supervised machine learning models classification confirm the diversity of the microbiome accurately. Furthermore, we have identified 450 cultures of heterotrophic, biotechnologically important bacteria. Some strains were identified as novel taxa based on 16S rRNA gene sequencing, showing promising potential for further study. CONCLUSION: Thus, our study provides valuable insights into the microbial diversity and pollution levels of coastal areas in AP and GA. These findings contribute to a better understanding of the impact of anthropogenic activities and climate variations on biology of coastal ecosystems and biodiversity.

Comparison of a portable, pneumotach flow-sensor-based spirometer (Spirofy™) with the vitalograph alpha Touch™ spirometer in evaluating lung function in healthy individuals, asthmatics, and COPD patients-a randomized, crossover study.

BACKGROUND: Spirofy™ is India's first portable, pneumotach flow-sensor-based digital spirometer developed to diagnose asthma and chronic obstructive pulmonary disease (COPD). In this study, we compared the performance of the Spirofy™ device with that of the Vitalograph Alpha Touch™ spirometer in measuring the lung capacities of healthy individuals, asthmatics, and COPD patients. We also assessed the inter-device variability between two Spirofy™ devices. METHODS: In a randomized, three-way crossover, open-label study, we measured the differences in forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC) between the Spirofy™ and Vitalograph Alpha Touch™ spirometers. A proportion of the FEV1/FVC ratio distribution of < 0.7 was used to compare the diagnostic accuracies of the Spirofy™ with Vitalograph™ Alpha Touch™ spirometers. RESULTS: Ninety subjects participated in this study. The mean ± SD FVC values obtained from the Spirofy™ 1, Spirofy™ 2, and Vitalograph Alpha Touch™ devices were 2.60 ± 1.05 L, 2.64 ± 1.04 L, and 2.67 ± 1.04 L, respectively. The mean ± SD FEV1 values obtained from the Spirofy™ 1, Spirofy™ 2, and Vitalograph Alpha Touch™ devices were 1.87 ± 0.92 (L), 1.88 ± 0.92 (L), and 1.93 ± 0.93 (L), respectively. A significant positive correlation was found between the FVC and FEV1 values recorded by Vitalograph Alpha Touch™, Spirofy™ 1, and Spirofy™ 2. As compared to Vitalograph Alpha Touch™, the Spirofy™ device showed good sensitivity (97%), specificity (90%), and overall accuracy (93.3%) at an FEV1/FVC ratio < 0.7. No inter-device variability was observed between the two Spirofy™ devices. CONCLUSION: Spirofy™ is a portable and easy-to-use device and is as accurate as the standard Vitalograph Alpha Touch™ spirometer for the diagnosis of COPD and asthma. TRIAL REGISTRATION: CTRI/2021/09/036492 (Clinical Trials Registry - India).

Non-communicable diseases, digital education and considerations for the Indian context - a scoping review.

INTRODUCTION: The increasing ageing of the population with growth in NCD burden in India has put unprecedented pressure on India's health care systems. Shortage of skilled human resources in health, particularly of specialists equipped to treat NCDs, is one of the major challenges faced in India. Keeping in view the shortage of healthcare professionals and the guidelines in NEP 2020, there is an urgent need for more health professionals who have received training in the diagnosis, prevention, and treatment of NCDs. This paper conducts a scoping review and aims to collate the existing evidence on the use of digital education of health professionals within NCD topics. METHODS: We searched four databases (Web of Science, PubMed, EBSCO Education Research Complete, and PsycINFO) using a three-element search string with terms related to digital education, health professions, and terms related to NCD. The inclusion criteria covered the studies to be empirical and NCD-related with the target population as health professionals rather than patients. Data was extracted from 28 included studies that reported on empirical research into digital education related to non-communicable diseases in health professionals in India. Data were analysed thematically. RESULTS: The target groups were mostly in-service health professionals, but a considerable number of studies also included pre-service students of medicine (n = 6) and nursing (n = 6). The majority of the studies included imparted online learning as self-study, while some imparted blended learning and online learning with the instructor. While a majority of the studies included were experimental or observational, randomized control trials and evaluations were also part of our study. DISCUSSION: Digital HPE related to NCDs has proven to be beneficial for learners, and simultaneously, offers an effective way to bypass geographical barriers. Despite these positive attributes, digital HPE faces many challenges for its successful implementation in the Indian context. Owing to the multi-lingual and diverse health professional ecosystem in India, there is a need for strong evidence and guidelines based on prior research in the Indian context.

Development, validation and application of single molecule molecular inversion probe based novel integrated genetic screening method for 29 common lysosomal storage disorders in India.

BACKGROUND: Current clinical diagnosis pathway for lysosomal storage disorders (LSDs) involves sequential biochemical enzymatic tests followed by DNA sequencing, which is iterative, has low diagnostic yield and is costly due to overlapping clinical presentations. Here, we describe a novel low-cost and high-throughput sequencing assay using single-molecule molecular inversion probes (smMIPs) to screen for causative single nucleotide variants (SNVs) and copy number variants (CNVs) in genes associated with 29 common LSDs in India. RESULTS: 903 smMIPs were designed to target exon and exon-intron boundaries of targeted genes (n = 23; 53.7 kb of the human genome) and were equimolarly pooled to create a sequencing library. After extensive validation in a cohort of 50 patients, we screened 300 patients with either biochemical diagnosis (n = 187) or clinical suspicion (n = 113) of LSDs. A diagnostic yield of 83.4% was observed in patients with prior biochemical diagnosis of LSD. Furthermore, diagnostic yield of 73.9% (n = 54/73) was observed in patients with high clinical suspicion of LSD in contrast with 2.4% (n = 1/40) in patients with low clinical suspicion of LSD. In addition to detecting SNVs, the assay could detect single and multi-exon copy number variants with high confidence. Critically, Niemann-Pick disease type C and neuronal ceroid lipofuscinosis-6 diseases for which biochemical testing is unavailable, could be diagnosed using our assay. Lastly, we observed a non-inferior performance of the assay in DNA extracted from dried blood spots in comparison with whole blood. CONCLUSION: We developed a flexible and scalable assay to reliably detect genetic causes of 29 common LSDs in India. The assay consolidates the detection of multiple variant types in multiple sample types while having improved diagnostic yield at same or lower cost compared to current clinical paradigm.

Burden of COVID-19 pandemic on tuberculosis hospitalisation patterns at a tertiary care hospital in Rajasthan, India: a retrospective analysis.

OBJECTIVE: This study aimed to investigate the burden of the COVID-19 pandemic on tuberculosis (TB) trends, patient demographics, disease types and hospitalisation duration within the Respiratory Medicine Department over three distinct phases: pre-COVID-19, COVID-19 and post-COVID-19. DESIGN: Retrospective analysis using electronic medical records of patients with TB admitted between June 2018 and June 2023 was done to explore the impact of COVID-19 on patients with TB. The study employed a meticulous segmentation into pre-COVID-19, COVID-19 and post-COVID-19 eras. SETTING: National Institute of Medical Science Hospital in Jaipur, Rajasthan, India. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcome includes patients admitted to the Respiratory Medicine Department of the hospital and secondary outcome involves the duration of hospital stay. RESULTS: The study encompassed 1845 subjects across the three eras, revealing a reduction in TB incidence during the post-COVID-19 era compared with the pre-COVID-19 period (p<0.01). Substantial demographic shifts were observed, with 5.2% decline in TB incidence among males in the post-COVID-19 era (n=529) compared with the pre-COVID-19 era (n=606). Despite the decrease, overall TB incidence remained significantly higher in males (n=1460) than females (n=385), with consistently elevated rates in rural (65.8%) as compared with the urban areas (34.2%). Extended hospital stays were noted in the post-COVID-19 era compared with the pre-COVID-19 era (p<0.01). CONCLUSION: The study underscores the influence of the COVID-19 pandemic on the TB landscape and hospitalisation dynamics. Notably, patient burden of TB declined during the COVID-19 era, with a decline in the post-COVID-19 era compared with the pre-COVID-19 era. Prolonged hospitalisation in the post-COVID-19 period indicates the need for adaptive healthcare strategies and the formulation of public health policies in a post-pandemic context. These findings contribute to a comprehensive understanding of the evolving TB scenario, emphasising the necessity for tailored healthcare approaches in the aftermath of a global health crisis.

Unravelling the metabolomic diversity of pigmented and non-pigmented traditional rice from Tamil Nadu, India.

Rice metabolomics is widely used for biomarker research in the fields of pharmacology. As a consequence, characterization of the variations of the pigmented and non-pigmented traditional rice varieties of Tamil Nadu is crucial. These varieties possess fatty acids, sugars, terpenoids, plant sterols, phenols, carotenoids and other compounds that plays a major role in achieving sustainable development goal 2 (SDG 2). Gas-chromatography coupled with mass spectrometry was used to profile complete untargeted metabolomics of Kullkar (red colour) and Milagu Samba (white colour) for the first time and a total of 168 metabolites were identified. The metabolite profiles were subjected to data mining processes, including principal component analysis (PCA), Orthogonal Partial Least Square Discrimination Analysis (OPLS-DA) and Heat map analysis. OPLS-DA identified 144 differential metabolites between the 2 rice groups, variable importance in projection (VIP) ≥ 1 and fold change (FC) ≥ 2 or FC ≤ 0.5. Volcano plot (64 down regulated, 80 up regulated) was used to illustrate the differential metabolites. OPLS-DA predictive model showed good fit (R2X = 0.687) and predictability (Q2 = 0.977). The pathway enrichment analysis revealed the presence of three distinct pathways that were enriched. These findings serve as a foundation for further investigation into the function and nutritional significance of both pigmented and non-pigmented rice grains thereby can achieve the SDG 2.

Dental caries, oral hygiene status and deleterious habits among migrant construction workers of Belagavi, India.

Background: Occupation significantly influences oral health, with factors like the work environment, stress levels, access to dental care, and job-related habits playing crucial roles. The oral health of construction workers, especially migrant workers, is a noteworthy concern. Understanding the oral health of this population is crucial for enhancing their quality of life through various means. This study aimed to investigate the prevalence of dental caries, oral hygiene status, and deleterious habits in this occupational group of Belagavi district, Karnataka. Materials and methods: Study design was cross-sectional in nature. Before commencement of the study a pilot study was conducted. Multi-stage random sampling technique was employed, and 610 participants were recruited for the study. Trained and calibrated examiners recorded WHO dentition status and treatment needs (2013) and Oral Hygiene Index Simplified (OHI-S). Collected data was analyzed using descriptive analysis, chi-square, one-way ANOVA, and multiple linear regression analysis. Results: The prevalence of dental caries among construction workers was significantly high (81%), and poor oral hygiene was observed among 36.9% of them. The prevalence of smoking, the tobacco chewing habit, and alcohol consumption among the construction workers was found to be 21.6%, 59.9%, and 37.3%, respectively. The dependence of OHI-S and DMFT on predictors (age, gender and deleterious habits) was found to be 21.5% and 39.6%, respectively. Conclusions: Migrant construction workers in Belagavi had a high caries prevalence, poor oral hygiene status, and a high prevalence of deleterious habits such as tobacco use. These results emphasize the necessity of awareness and dental health education programs to improve the oral health of construction workers.

Analysing district-level climate vulnerability pattern in Madhya Pradesh, India, based on agricultural and socio-economic indicators.

Indian agriculture transitioned from a food deficit sector to a food surplus following the Green Revolution. However, the continued progress of Indian agriculture has been hampered by climate change. This research explores the district-wise vulnerability in Madhya Pradesh, India, to climate change by assessing the composite vulnerability index using the agricultural vulnerability index (AVI) and socio-economic vulnerability index (SEVI). The study seeks to understand how agricultural and socio-economic factors lead to variations in vulnerability across districts and influence targeted adaptation and mitigation strategies. The trend analysis results present declining rainfall and inclining temperature from 1951 to 2021 in Madhya Pradesh, directly affecting the agricultural sector and human livelihood. The composite vulnerability index (CVI) results revealed that districts with low values (< 0.394), such as Burhanpur and Balaghat, demonstrate reduced susceptibility due to limited cultivation, low reliance on rainfall, lower drought susceptibility, and decreased population density. Districts such as Panna and Bhopal show moderate vulnerability (0.394-0.423), with lower fallow land, reduced rainfed agriculture, and socio-economic vulnerability. Extensive agriculture and marginalised workers' presence influence high vulnerability (0.423 to 0.456) in districts such as Tikamgarh and Indore. Districts like Barwani and Jhabua have the highest CVI values (> 0.456), indicating substantial susceptibility to climate impacts. The cluster analysis validates the results of the vulnerability index. The findings highlight the urgent need for tailored adaptation strategies to address the diverse agricultural and socio-economic indicators creating vulnerability in Madhya Pradesh. The study helps understand regional vulnerability patterns and provides evidence-based policy approaches for resilience to climate change effects.