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Objective: To identify the clinical, laboratory, and radiological markers that could predict a positive GeneXpert result in patients suspected of tuberculous meningitis. Methods: In this prospective, observational study, patients with tuberculous meningitis were systematically evaluated. Various clinical, laboratory [including cerebrospinal fluid (CSF) microscopy, culture, and GeneXpert], and neuroimaging factors were examined. All participants were administered anti-tuberculous treatment and corticosteroids. A six-month follow-up was done to evaluate the outcome. Results: Of the 116 patients studied, 54 (46.6%) tested positive for GeneXpert, while 62 (53.4%) were negative. Third cranial nerve involvement (OR 3.71, 95% CI 1.052-13.09, P=0.04) and the presence of basal exudates on neuroimaging (OR 5.22, 95% CI 2.03-13.42, P=0.001) emerged as independent predictive factors for a positive GeneXpert result. A positive CSF GeneXpert result (P=0.002) and drug resistance (P=0.004) were significantly linked to adverse outcomes. Additionally, a high score on the Medical Research Council stage III (OR 5.64, 95% CI 1.18-26.87, P=0.03) and elevated CSF cell counts (OR 1.002, 95% CI 1.00-1.001, P=0.03) were identified as independent predictors of poor prognosis. Conclusions: Third cranial nerve involvement and the presence of basal exudates were significant indicators of a positive GeneXpert result. MRC stage III disability and elevated CSF cell counts predicted poor outcomes.

Background: Public health action (PHA) in tuberculosis (TB) includes six components: doing screening for HIV/diabetes, carrying out drug susceptibility testing, counseling on tobacco, counseling on nutrition, benefits of Nikshay Poshan Yojana, and contact tracing. All the patients notified by the private practitioners (PPs) and missing any of the above components are intervened by the government staff to cover all the above components. Objectives: The aim of the article is (1) to assess the timeliness and completeness of PHA and (2) to assess the impact of PHA on the quality of care for TB patients in the private sector. Methods: A sequential mixed-method (cross-sectional study followed by qualitative study) study was carried out in the Patan district, North Gujarat for a period of one year. Quantitative data were collected through home visits to patients residing in three randomly selected talukas out of nine talukas in the Patan district. Qualitative data were collected purposively from selected clinics of PPs (including a mix of PP notifying and not notifying TB till saturation is achieved) from the above talukas. Results: Out of a total of 176 patients from the private sector, 48 patients took all six components of PHA. Out of them, 98% were cured compared to 82% who did not receive PHA. None of the PP had heard about PHA or its components. Conclusion: The Public–private model for TB management needs strengthening. Regular and mandatory training of PPs on the latest TB management guidelines including importance of timely and complete PHA should be carried out.

Purpose: Assessment of central and peripheral contrast sensitivity (CS) in thyroid eye disease (TED) with and without dysthyroid optic neuropathy (DON). Methods: This cross-sectional study enrolled 33 eyes of 18 treatment-naïve TED patients and 18 age- and sex-matched healthy controls for comparative analysis. A detailed ophthalmic examination included visual acuity (VA), intraocular pressure measurement, slit-lamp biomicroscopy, and CS testing (central and four peripheral regions) using Spaeth–Richman Contrast Sensitivity test was done. Results: The average age of TED patients was 47.17 ± 13.99 years and a female preponderance was noted (66.66%, n = 12). Twenty-five eyes (75.8%) were diagnosed as TED without DON, while eight eyes (24.2%) had DON. Nine eyes (27.2%) were in the active stage of disease and 29 eyes (87.8%) had proptosis. The difference in mean logMAR visual acuities between TED patients and controls was statistically insignificant (P = 0.189), but a significant difference was noted in central and total CS score (P < 0.001, Wilcoxon–Mann–Whitney test). On CS comparison between DON and non-DON eyes, a significant difference in average scores was noted in central and all peripheral areas (P < 0.05, Wilcoxon–Mann–Whitney test). With increasing clinical activity score, a statistically significant reduction was noted in CS in three out of four peripheral regions (Spearman correlation, P < 0.05). Conclusion: Visual function compromise can be detected in TED in the presence of intact VA, by testing CS. Peripheral CS deteriorates with increasing inflammation and in DON. Serial monitoring of both central and peripheral CS may help in diagnosing DON early.

This study aimed to comprehensively explore the intricacies of corneal neurotization (CN) and the nuanced factors that set it apart from routine clinical practice, exerting a substantial influence on its success. A symbiotic relationship is evident between corneal innervation and ocular surface health. The loss of corneal innervation results in a potentially challenging corneal condition known as neurotrophic keratopathy (NK). The majority of treatments are primarily focused on preventing epithelial breakdown rather than addressing the underlying pathogenesis. Consequently, to address the impaired corneal sensation (underlying etiology), a novel surgical approach has emerged, namely CN, which involves transferring healthy sensory nerve axons to the affected cornea. This review offers valuable insights into the existing body of supporting evidence for CN, meticulously examining clinical studies, case reports, and experimental findings. The aim is to enhance our understanding of the effectiveness and potential outcomes associated with this innovative surgical technique. The exploration of innovative therapeutic avenues holds promise for revolutionizing the management of NK, offering a potentially permanent solution to a condition once deemed incurable and severely debilitating.

Background: Over the last decade, the rate of cesarean sections has steadily increased owing to various reasons, and along with it the incidence of wound sepsis. Different risk factors identified are maternal age, socioeconomic status, educational status, antenatal visits, pregestational diabetes, obesity, recurrent pregnancy losses, duration of surgery, preterm rupture of membranes, etc. Hence, assessing infections and their management is an integral part of health care, as it helps develop strategies for prevention, better management of infection, reducing the hospital stay, and cost of healthcare. Aims and Objectives: The aim of the study was to assess and note the variability of social and demographic profiles of patients undergoing cesarean sections and developing wound infection, along with its various presentations and categories. Materials and Methods: A prospective observational study was conducted on patients who developed wound sepsis after undergoing cesarean section at a tertiary center in India. Results: Among the patients enrolled, 35.83% were illiterate and 45.83% were educated up to the tenth standard. About 74% of patients were not registered during the antenatal period. Furthermore, the majority of patients were overweight and obese (74%) and were from lower socioeconomic strata. About 85% of the patients who developed wound infection had their surgery lasting for more than 60 minutes. About 87.50% developed a superficial category of infection, and 68.33% presented within the first 5 days of surgery. Patients with deep infected wounds had significantly bigger wounds and longer hospitalization. Conclusion: Illiteracy and lower socioeconomic conditions predispose women to wound sepsis. A longer duration of surgery was associated with a higher risk of infection. Superficial wounds are the most common type of infection encountered. Deep and organ space categories of wound infection are associated with increased morbidity and longer hospitalization warranting aggressive management. Reducing the incidence of wound sepsis can help to reduce morbidity by identifying risk factors before pregnancy and supporting the implementation of preconception counseling centers and prenatal programs to educate and raise awareness among patients.

Widespread academic dishonesty among higher education (HE) students has been a concern for higher education institutes (HEIs). Ethics literature reports that unintentional plagiarism is more prevalent among HE students and the root cause is, limited or no awareness of nuances of ethics concerning plagiarism resulting in poor ethical judgments. This study attempts to examine what is students' ethical reasoning for unintentional plagiarism and how HEIs' ethical awareness efforts impact students' ethical judgments which ultimately shape their ethical behavior. The study also explored whether and how individual-level factors such as intrinsic religiosity, age, gender, and work experience moderate the focal relationships. A longitudinal quasi-experimental field study was conducted. The subjects of the study were 294 postgraduate students of an internationally accredited higher education institution in India. The pretest-posttest design involved a set of experimental manipulations reflecting the HEI's endeavors to explicate the unethical implications of plagiarism.

This study explores the factors that affect the accumulation of employee emotional capital and the subsequent returns generated in an organisation. It uses qualitative research methods based on interpretative phenomenological analysis (IPA) to collect data which enables an in-depth investigation of the lived experience of the participants. This study identifies how factors like investment, leadership, culture, and systems impact the accumulation of employee emotional capital in an organisation. It also identifies which specific returns emotional capital can generate for individual employees and the organisation. This study also augments the Socio-technical systems theory (Trist and Bamforth, 1951) and makes it more relevant for the current business scenarios. The study provides a comprehensive understanding of factors which can strengthen the integration of technology and human components of an organisation and generate a higher order performance.

Sleep is a highly stereotyped phenomenon, requiring robust spatiotemporal coordination of neural activity. Understanding how the brain coordinates neural activity with sleep onset can provide insights into the physiological functions subserved by sleep and the pathologic phenomena associated with sleep onset. We quantified whole-brain network changes in synchrony and information flow during the transition from wakefulness to light non-rapid eye movement (NREM) sleep, using MEG imaging in a convenient sample of 14 healthy human participants (11 female; mean 63.4 years [SD 11.8 years]). We furthermore performed computational modeling to infer excitatory and inhibitory properties of local neural activity. The transition from wakefulness to light NREM was identified to be encoded in spatially and temporally specific patterns of long-range synchrony. Within the delta band, there was a global increase in connectivity from wakefulness to light NREM, which was highest in frontoparietal regions. Within the theta band, there was an increase in connectivity in fronto-parieto-occipital regions and a decrease in temporal regions from wakefulness to Stage 1 sleep. Patterns of information flow revealed that mesial frontal regions receive hierarchically organized inputs from broad cortical regions upon sleep onset, including direct inflow from occipital regions and indirect inflow via parieto-temporal regions within the delta frequency band. Finally, biophysical neural mass modeling demonstrated changes in the anterior-to-posterior distribution of cortical excitation-to-inhibition with increased excitation-to-inhibition model parameters in anterior regions in light NREM compared with wakefulness. Together, these findings uncover whole-brain corticocortical structure and the orchestration of local and long-range, frequency-specific cortical interactions in the sleep-wake transition.SIGNIFICANCE STATEMENT Our work uncovers spatiotemporal cortical structure of neural synchrony and information flow upon the transition from wakefulness to light non-rapid eye movement sleep. Mesial frontal regions were identified to receive hierarchically organized inputs from broad cortical regions, including both direct inputs from occipital regions and indirect inputs via the parieto-temporal regions within the delta frequency range. Biophysical neural mass modeling revealed a spatially heterogeneous, anterior-posterior distribution of cortical excitation-to-inhibition. Our findings shed light on the orchestration of local and long-range cortical neural structure that is fundamental to sleep onset, and support an emerging view of cortically driven regulation of sleep homeostasis.

Pancreatic islets consist of multiple cell types that produce hormones required for glucose homeostasis, and islet dysfunction is a major factor in type 1 and type 2 diabetes. Numerous studies have assessed transcription across individual cell types using single-cell assays; however, there is no canonical reference of gene expression in islet cell types that is also easily accessible for researchers to query and use in bioinformatics pipelines. Here we present an integrated map of islet cell type-specific gene expression from 192,203 cells from single-cell RNA sequencing of 65 donors without diabetes, donors who were type 1 diabetes autoantibody positive, donors with type 1 diabetes, and donors with type 2 diabetes from the Human Pancreas Analysis Program. We identified 10 distinct cell types, annotated subpopulations of several cell types, and defined cell type-specific marker genes. We tested differential expression within each cell type across disease states and identified 1,701 genes with significant changes in expression, with most changes observed in β-cells from donors with type 1 diabetes. To facilitate user interaction, we provide several single-cell visualization and reference mapping tools, as well as the open-access analytical pipelines used to create this reference. The results will serve as a valuable resource to investigators studying islet biology.Article highlights

The relationship between brain functional connectivity and structural connectivity has caught extensive attention of the neuroscience community, commonly inferred using mathematical modeling. Among many modeling approaches, spectral graph model (SGM) is distinctive as it has a closed-form solution of the wide-band frequency spectra of brain oscillations, requiring only global biophysically interpretable parameters. While SGM is parsimonious in parameters, the determination of SGM parameters is non-trivial. Prior works on SGM determine the parameters through a computational intensive annealing algorithm, which only provides a point estimate with no confidence intervals for parameter estimates. To fill this gap, we incorporate the simulation-based inference (SBI) algorithm and develop a Bayesian procedure for inferring the posterior distribution of the SGM parameters. Furthermore, using SBI dramatically reduces the computational burden for inferring the SGM parameters. We evaluate the proposed SBI-SGM framework on the resting-state magnetoencephalography recordings from healthy subjects and show that the proposed procedure has similar performance to the annealing algorithm in recovering power spectra and the spatial distribution of the alpha frequency band. In addition, we also analyze the correlations among the parameters and their uncertainty with the posterior distribution which cannot be done with annealing inference. These analyses provide a richer understanding of the interactions among biophysical parameters of the SGM. In general, the use of simulation-based Bayesian inference enables robust and efficient computations of generative model parameter uncertainties and may pave the way for the use of generative models in clinical translation applications.

Background: Phenotypic drug susceptibility testing (DST) is considered the gold standard for detecting linezolid (LZD) resistance in Mycobacterium tuberculosis (MTB), but it is time-consuming. Nanopore sequencing offers a potentially faster alternative approach. This study evaluated the agreement between phenotypically detected LZD resistance and mutations in the rrl and rplC genes of MTB isolates using nanopore sequencing. Methods: Consecutive drug-resistant MTB isolates from pulmonary samples collected in 2021 underwent liquid culture (LC) DST for LZD. All resistant isolates and an equal number of susceptible isolates were subjected to targeted sequencing of the rrl and rplC genes using nanopore technology. Results: Sequencing identified a C154R mutation in the rplC gene in only one LZD-resistant isolate. No mutations were detected in the rrl gene. The agreement between sequencing and LC-DST for detecting LZD resistance was poor (Cohen’s kappa: 0.03571, 95% confidence interval [CI]: −0.034–0.105). Additionally, no significant association was found between LZD resistance and clinical or microbiological outcomes at 6-month follow-up. Conclusion: This study revealed a considerable discrepancy between phenotypic and genotypic detection of LZD resistance in MTB. Further research is needed to better understand the genetic mechanisms underlying LZD resistance and to develop reliable molecular diagnostics for rapid resistance detection.

Abstract Sustainable farming practices aim to produce agricultural products at a low environmental cost, ensuring food availability for future generations. These approaches combine the production of agricultural crops and livestock for site-specific uses, with an emphasis on long-term objectives including satisfying the food supply worldwide, improving the environment, making the most efficient use of resources and boosting the welfare of farmers and society as a whole. Sustainability in farming is mostly dependent on soil health, which is the soil’s capacity to function within ecological and land-use boundaries. It enhances general wellness, maintains the purity of the air and water, and supports biological productivity. The depletion of soil functions brought about by modern agricultural intensification has an impact on ecosystem services and long-term productivity. The goal of sustainable farming is to raise fertility and organic matter in the soil. Key practices include carbon farming, conservation agriculture, integrated pest management (IPM), and precision farming. In order to support sustainable crop production, these techniques improve soil fertility, structure, and biodiversity. Going forward, research should concentrate on developing novel approaches to tackle the issues of climate change and global food security.

Abstract Skin conditions are becoming increasingly prevalent across the world in current times. With the rise in dermatological disorders, there is a need for computerized techniques that are completely noninvasive to patients’ skin. As a result, deep learning models have become standard for the computerized detection of skin diseases. The performance efficiency of these models improves with access to more data with their primary aim being image classification. In this paper, we present a skin disease detection methodology using image processing techniques, non-local means denoising and convolutional neural network (CNN) backed by sparse dictionary learning. Here, the major benefit of using NLM denoising followed by sparse dictionary learning with CNNs in image classification lies in leveraging a multi-stage approach that enhances the quality of input data, extracts meaningful and discriminative features, and improves the overall performance of the classification model. This combined approach addresses challenges such as noise robustness, feature extraction, and classification accuracy, making it particularly effective in complex image analysis tasks. For denoising, the average Peak Signal to Noise Ratio (PSNR) obtained for images from HAM-10000 dataset is 33.59 dB. For the ISIC-2019 dataset, the average PSNR for the train folder is 34.37 dB, and for the test folder it is 34.39 dB. The deep learning network is trained for the analysis of skin cancer images using a CNN model and is achieving acceptable results in classifying skin cancer types. The datasets used contain high-resolution images. After all the tests, the accuracy obtained is 85.61% for the HAM-10000 dataset and 81.23% for the ISIC-2019 dataset, which is on par with existing approaches validated by benchmarking results.

Background: Sebaceous carcinoma is a rare cancer, and little is known about its current epidemiology and treatment. This is particularly true for sebaceous carcinomas of the trunk and extremities. Objective: We present a database analysis of sebaceous carcinoma cases to further delineate demographics, location, tumor characteristics, and treatment modalities among patients diagnosed with these tumors. Methods: The National Cancer Database was queried for cases of sebaceous carcinoma between 2004 and 2016. 3211 cases were analyzed for descriptive and comparative statistics. Results: Twenty-six percent of sebaceous carcinomas were found on the trunk and extremities. Tumors on the trunk and extremities were more likely to be larger than tumors on the head and neck, with 8% being greater than 50 mm (P

Background and Aims: Ultrasonography (USG)-guided arterial cannulation is a frequently performed procedure in the operating room and intensive care unit. Conventionally, longitudinal/in-plane and transverse/out-of-plane approaches are used for cannulation. Recently, a longitudinal oblique approach has been described with the advantage of wide visualization area. Hence, the present study was designed to compare the success of USG-guided radial artery cannulation in longitudinal oblique axis (LOA) and longitudinal axis (LA). Material and Methods: Seventy patients requiring radial artery cannulation were randomly allocated into two groups: group L (USG-guided radial artery cannulation in LA) and group O (USG-guided radial artery cannulation in LOA). Primary outcome was to assess cannulation success in the first attempt, while the secondary outcomes were to assess the number of attempts, failure rate, total cannulation time, and associated complications. Results: First-attempt success was higher in group O (80%) compared to group L (54.3%), with a P value of 0.022. In group L, 31.4% required two attempts and 5.7% had three attempts, while in group O, 14.3% had two attempts and 2.9% required three attempts. Group L failure rate was 8.6%, while it was 2.9% in group O. The mean total cannulation time (sec) for group L was 146.83 ± 89.37 and group O was 63.89 ± 26.277. No complication was observed with group O, while in group L, 9% had hematoma formation. Conclusion: The LOA approach for USG-guided radial artery cannulation has higher first-pass success rate, total success rate, and requires less cannulation time compared to the LA approach.

Background: Patients with posterior uveitis can develop vision-threatening complications. Optical coherence tomography (OCT) plays an important role in the diagnosis and management of these complications. Aims: The objectives of this study were to describe different retinal morphological characteristics presenting on OCT in patients with posterior uveitis, with an aim to facilitate early diagnosis to initiate specific treatment and also to observe the response to treatment. Materials and Methods: A cross-sectional prospective non-randomized study was undertaken at a tertiary eye care hospital. The study included 30 eyes of 30 patients with posterior uveitis between the period of May 2016 and May 2018. All subjects underwent a set of systemic investigations for etiological diagnosis and complete ophthalmic examination, including OCT (Zeiss Cirrus machine (model number 5000)] imaging). Data were collected and analyzed. A P value of

The extreme conditions linked with abiotic stresses have greatly affected soil and plant health. The diverse biochemical activities occurring in the soil environment have been attributed to shaping the dynamics of plant–soil microbiomes by contributing to microbial lifestyles and enhancing microbial functional properties to boost plant tolerance to abiotic-induced stresses. Soil microbiomes play crucial roles in enhancing plant nutrition and abiotic stress management through diverse mechanisms. With the current insights into the use of engineered soil microbes as single or combined inoculants, their use has contributed to plant fitness and stability under different environmental stress conditions by activating plant defense mechanisms, enzyme production (lowering free radicals resulting in plant oxidative stress), protein regulation, and the production of growth factors. The detection of certain genes involved in the growth factors can underline microbial functions in mitigating plant stress. Hence, the projections for sustainable eco-friendly agriculture with the possible exploration of beneficial rhizosphere microbes to manage the effect of abiotic stress on plant nutrition remain critical points of discussion recently, with prospects for ensuring food security. Therefore, this review focuses on the impacts of soil microbiomes in abiotic stress mitigation for enhancing plant nutrition.

Abstract Background Does preschool height predict adult stature in undernourished settings? The extent to which preschool length or height forecasts young adult stature is unclear in chronically undernourished populations. Methods In 2006-8, we assessed height in a cohort of 2074 young adults, aged 16–23 years, in rural Nepal who, as preschoolers (≤ 4 year), were measured at baseline and again 16 months later during a vitamin A supplementation trial in 1989-91. We assessed by linear regression the ability of preschool length (L, measured -1) increased from 38–40% mid-infancy to ∼ 69–74% by 6 years of age. By 3–6 years of age heights of stunted children (L/HAZ

Abstract The spectral content of macroscopic neural activity evolves throughout development, yet how this maturation relates to underlying brain network formation and dynamics remains unknown. Here, we assess the developmental maturation of electroencephalogram spectra via Bayesian model inversion of the spectral graph model, a parsimonious whole-brain model of spatiospectral neural activity derived from linearized neural field models coupled by the structural connectome. Simulation-based inference was used to estimate age-varying spectral graph model parameter posterior distributions from electroencephalogram spectra spanning the developmental period. This model-fitting approach accurately captures observed developmental electroencephalogram spectral maturation via a neurobiologically consistent progression of key neural parameters: long-range coupling, axonal conduction speed, and excitatory:inhibitory balance. These results suggest that the spectral maturation of macroscopic neural activity observed during typical development is supported by age-dependent functional adaptations in localized neural dynamics and their long-range coupling across the macroscopic structural network.

Abstract Background The ongoing global crisis of Higher Education (HE) institutions during the post-COVID-19 pandemic period has increased the likelihood of enduring psychological stressors for staff. This study aimed to identify factors associated with job insecurity, burnout, psychological distress and coping amongst staff working at HE institutions globally. Methods An anonymous cross-sectional study was conducted in 2023 with staff at HE institutions across 16 countries. Job insecurity was measured using the Job Insecurity Scale (JIS), burnout using the Perceived Burnout measure question, psychological distress using the Kessler Psychological Distress Scale (K10), and coping using the Brief Resilient Coping Scale. Multivariable logistic regression with a stepwise variable selection method was used to identify associations. Results A total of 2,353 staff participated; the mean age (± SD) was 43(± 10) years and 61% were females. Most staff (85%) did not feel job insecurity, one-third (29%) perceived burnout in their jobs, more than two-thirds (73%) experienced moderate to very high levels of psychological distress, and more than half (58%) exhibited medium to high resilient coping. Perceived job insecurity was associated with staff working part-time [Adjusted Odds Ratio 1.53 (95% Confidence Intervals 1.15–2.02)], having an academic appointment [2.45 (1.78–3.27)], having multiple co-morbidities [1.86 (1.41–2.48)], perceived burnout [1.99 (1.54–2.56)] and moderate to very high level of psychological distress [1.68 (1.18–2.39)]. Perceived burnout was associated with being female [1.35 (1.12–1.63)], having multiple co-morbidities [1.53 (1.20–1.97)], perceived job insecurity [1.99 (1.55–2.57)], and moderate to very high levels of psychological distress [3.23 (2.42–4.30)]. Staff with multiple co-morbidities [1.46 (1.11–1.92)], mental health issues [2.73 (1.79–4.15)], perceived job insecurity [1.61 (1.13–2.30)], and perceived burnout [3.22 (2.41–4.31)] were associated with moderate to very high levels of psychological distress. Staff who perceived their mental health as good to excellent [3.36 (2.69–4.19)] were more likely to have medium to high resilient coping. Conclusions Factors identified in this study should be considered in reviewing and updating current support strategies for staff at HE institutions across all countries to reduce stress and burnout and improve wellbeing.

Introduction: Measles, a highly transmissible disease marked by fever and a maculopapular rash, posed a substantial threat to life in the 1960s. Nevertheless, the advent of the measles vaccine had a profound impact, significantly diminishing its toll on mortality. Similarly, through effective influenza surveillance and early epidemic warning systems, public health officials can timely identify influenza trends and provide crucial scientific support for prevention and control measures. This proactive approach holds great public health significance. Aim: To analyse the long-term trend of measles cases in Rajasthan, India, and the impact of Coronavirus Disease-2019 (COVID-19) on it, with future predictions using Auto-Regressive Integrated Moving Average (ARIMA) modelling. Materials and Methods: The present study was a retrospective, descriptive observational study in which monthly diagnosed measles cases were collected from the Measles Rubella Laboratory, Department of Microbiology, Sawai Man Singh Medical College, Jaipur, Rajasthan, India, for the period of April 2010 to April 2023. An ARIMA model was developed using data from 2010 to 2020 to predict the monthly number of measles cases in 2021. The predicted values were then compared to the actual cases in 2021 to assess the model’s accuracy. Results: Out of the total positive cases, males were slightly more prone to acquire infection than females (1734 males, 54%; 1477 females, 46%). The monthly index for new measles cases ranged from 0.11 to 2.6. It reached its lowest point in July (0.106) and August (0.25) and peaked in March (2.594) and April (1.84). The overall trend was fluctuating; however, the incidence of measles cases clearly increased after the year 2021. The difference between observed cases and predicted cases for the period of April 2020 to December 2021 was not statistically significant (t-value=0.261 and p-value=0.797). Conclusion: The fluctuating trend of measles was observed during the last decade; however, the observed cases of measles showed an upward trajectory during and after the COVID-19 outbreak. This study also highlighted the monthly index of the measles cases, which peaked in March to April and was lowest in July to August.

Growth faltering in children (low length for age or low weight for length) during the first 1,000 days of life (from conception to 2 years of age) influences short-term and long-term health and survival1,2. Interventions such as nutritional supplementation during pregnancy and the postnatal period could help prevent growth faltering, but programmatic action has been insufficient to eliminate the high burden of stunting and wasting in low- and middle-income countries. Identification of age windows and population subgroups on which to focus will benefit future preventive efforts. Here we use a population intervention effects analysis of 33 longitudinal cohorts (83,671 children, 662,763 measurements) and 30 separate exposures to show that improving maternal anthropometry and child condition at birth accounted for population increases in length-for-age z-scores of up to 0.40 and weight-for-length z-scores of up to 0.15 by 24 months of age. Boys had consistently higher risk of all forms of growth faltering than girls. Early postnatal growth faltering predisposed children to subsequent and persistent growth faltering. Children with multiple growth deficits exhibited higher mortality rates from birth to 2 years of age than children without growth deficits (hazard ratios 1.9 to 8.7). The importance of prenatal causes and severe consequences for children who experienced early growth faltering support a focus on pre-conception and pregnancy as a key opportunity for new preventive interventions.

Sustainable Development Goal 2.2-to end malnutrition by 2030-includes the elimination of child wasting, defined as a weight-for-length z-score that is more than two standard deviations below the median of the World Health Organization standards for child growth1. Prevailing methods to measure wasting rely on cross-sectional surveys that cannot measure onset, recovery and persistence-key features that inform preventive interventions and estimates of disease burden. Here we analyse 21 longitudinal cohorts and show that wasting is a highly dynamic process of onset and recovery, with incidence peaking between birth and 3 months. Many more children experience an episode of wasting at some point during their first 24 months than prevalent cases at a single point in time suggest. For example, at the age of 24 months, 5.6% of children were wasted, but by the same age (24 months), 29.2% of children had experienced at least one wasting episode and 10.0% had experienced two or more episodes. Children who were wasted before the age of 6 months had a faster recovery and shorter episodes than did children who were wasted at older ages; however, early wasting increased the risk of later growth faltering, including concurrent wasting and stunting (low length-for-age z-score), and thus increased the risk of mortality. In diverse populations with high seasonal rainfall, the population average weight-for-length z-score varied substantially (more than 0.5 z in some cohorts), with the lowest mean z-scores occurring during the rainiest months; this indicates that seasonally targeted interventions could be considered. Our results show the importance of establishing interventions to prevent wasting from birth to the age of 6 months, probably through improved maternal nutrition, to complement current programmes that focus on children aged 6-59 months.

Globally, 149 million children under 5 years of age are estimated to be stunted (length more than 2 standard deviations below international growth standards)1,2. Stunting, a form of linear growth faltering, increases the risk of illness, impaired cognitive development and mortality. Global stunting estimates rely on cross-sectional surveys, which cannot provide direct information about the timing of onset or persistence of growth faltering-a key consideration for defining critical windows to deliver preventive interventions. Here we completed a pooled analysis of longitudinal studies in low- and middle-income countries (n = 32 cohorts, 52,640 children, ages 0-24 months), allowing us to identify the typical age of onset of linear growth faltering and to investigate recurrent faltering in early life. The highest incidence of stunting onset occurred from birth to the age of 3 months, with substantially higher stunting at birth in South Asia. From 0 to 15 months, stunting reversal was rare; children who reversed their stunting status frequently relapsed, and relapse rates were substantially higher among children born stunted. Early onset and low reversal rates suggest that improving children's linear growth will require life course interventions for women of childbearing age and a greater emphasis on interventions for children under 6 months of age.

To address the challenge of translating genetic discoveries for type 1 diabetes (T1D) into mechanistic insight, we have developed the T1D Knowledge Portal (T1DKP), an open-access resource for hypothesis development and target discovery in T1D.

BACKGROUND: Many women experience suboptimal gestational weight gain (GWG) in low- and middle-income countries (LMICs), but our understanding of risk factors associated with GWG in these settings is limited. We investigated the relationships between demographic, anthropometric, lifestyle, and clinical factors and GWG in prospectively collected data from LMICs. METHODS AND FINDINGS: We conducted an individual participant-level meta-analysis of risk factors for GWG outcomes among 138,286 pregnant women with singleton pregnancies in 55 studies (27 randomized controlled trials and 28 prospective cohorts from 25 LMICs). Data sources were identified through PubMed, Embase, and Web of Science searches for articles published from January 2000 to March 2019. Titles and abstracts of articles identified in all databases were independently screened by 2 team members according to the following eligibility criteria: following inclusion criteria: (1) GWG data collection took place in an LMIC; (2) the study was a prospective cohort or randomized trial; (3) study participants were pregnant; and (4) the study was not conducted exclusively among human immunodeficiency virus (HIV)-infected women or women with other health conditions that could limit the generalizability of the results. The Institute of Medicine (IOM) body mass index (BMI)-specific guidelines were used to determine the adequacy of GWG, which we calculated as the ratio of the total observed weight gain over the mean recommended weight gain. Study outcomes included severely inadequate GWG (percent adequacy of GWG 125). Multivariable estimates from each study were pooled using fixed-effects meta-analysis. Study-specific regression models for each risk factor included all other demographic risk factors measured in a particular study as potential confounders, as well as BMI, maternal height, pre-pregnancy smoking, and chronic hypertension. Risk factors occurring during pregnancy were further adjusted for receipt of study intervention (if any) and 3-month calendar period. The INTERGROWTH-21st standard was used to define high and low GWG among normal weight women in a sensitivity analysis. The prevalence of inadequate GWG was 54%, while the prevalence of excessive weight gain was 22%. In multivariable models, factors that were associated with a higher risk of inadequate GWG included short maternal stature (