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Poor sanitation is thought to be a major cause of enteric infections among young children. However, there are no previously published randomized trials to measure the health impacts of large-scale sanitation programs. India's Total Sanitation Campaign (TSC) is one such program that seeks to end the practice of open defecation by changing social norms and behaviors, and providing technical support and financial subsidies. The objective of this study was to measure the effect of the TSC implemented with capacity building support from the World Bank's Water and Sanitation Program in Madhya Pradesh on availability of individual household latrines (IHLs), defecation behaviors, and child health (diarrhea, highly credible gastrointestinal illness [HCGI], parasitic infections, anemia, growth). We conducted a cluster-randomized, controlled trial in 80 rural villages. Field staff collected baseline measures of sanitation conditions, behaviors, and child health (May-July 2009), and revisited households 21 months later (February-April 2011) after the program was delivered. The study enrolled a random sample of 5,209 children <5 years old from 3,039 households that had at least one child <24 months at the beginning of the study. A random subsample of 1,150 children <24 months at enrollment were tested for soil transmitted helminth and protozoan infections in stool. The randomization successfully balanced intervention and control groups, and we estimated differences between groups in an intention to treat analysis. The intervention increased percentage of households in a village with improved sanitation facilities as defined by the WHO/UNICEF Joint Monitoring Programme by an average of 19% (95% CI for difference: 12%-26%; group means: 22% control versus 41% intervention), decreased open defecation among adults by an average of 10% (95% CI for difference: 4%-15%; group means: 73% intervention versus 84% control). However, the intervention did not improve child health measured in terms of multiple health outcomes (diarrhea, HCGI, helminth infections, anemia, growth). Limitations of the study included a relatively short follow-up period following implementation, evidence for contamination in ten of the 40 control villages, and bias possible in self-reported outcomes for diarrhea, HCGI, and open defecation behaviors. The intervention led to modest increases in availability of IHLs and even more modest reductions in open defecation. These improvements were insufficient to improve child health outcomes (diarrhea, HCGI, parasite infection, anemia, growth). The results underscore the difficulty of achieving adequately large improvements in sanitation levels to deliver expected health benefits within large-scale rural sanitation programs. ClinicalTrials.gov NCT01465204. Please see later in the article for the Editors' Summary.

Giardia lamblia , a human gut pathogen, possesses a minimal ESCRT (Endosomal Sorting Complex Required for Transport) machinery. Paradoxically, there are multiple paralogues of some late-ESCRT components- three paralogues for Vps4, GlVps4a, GlVps4b, and GlVps4c, and two for Vps46, GlVps46a and GlVps46b. This study addressed whether these paralogues can potentially discharge distinct cellular functions by determining the subcellular distribution of the paralogues in trophozoites and during encystation. Consistent with the distribution of orthologues from model organisms, most of these components were found to be associated with various cellular membranes, particularly in regions of acute membrane bending. Some of these paralogues are also associated with microtubule structures, such as cytoplasmic axonemes and the median body. Considering their diverse sub-cellular distributions, it is likely that they perform non-overlapping functions within the cell. Further, their redistribution during encystation indicates that they may play a role in the morphological and functional changes accompanying this transition. The study also characterized GlIst1, an ESCRT-III accessory protein that undergoes unique post-translational myristoylation at lysine 43. GlIst1 selectively interacts with GlVps4b through non-canonical MIT-MIM interactions. GlIst1 also exhibits selective interaction with GlVps46b. Such selective interaction of GlIst1 with only specific paralogues of GlVps4 and GlVps46 further underscores the distinct cellular roles of these late-ESCRT paralogues.

Anxiety disorders represent a significant global health challenge, yet a substantial treatment gap persists, motivating the development of scalable digital health solutions. This study investigates the potential of integrating passive physiological data from consumer wearable devices with subjective self-reported surveys to predict state–trait anxiety. Leveraging the multi-modal, longitudinal LifeSnaps dataset, which captured “in the wild” data from 71 participants over four months, this research develops and evaluates a machine learning framework for this purpose. The methodology meticulously details a reproducible data curation pipeline, including participant-specific time zone harmonization, validated survey scoring, and comprehensive feature engineering from Fitbit Sense physiological data. A suite of machine learning models was trained to classify the presence of anxiety, defined by the State–Trait Anxiety Inventory (S-STAI). The CatBoost ensemble model achieved an accuracy of 77.6%, with high sensitivity (92.9%) but more modest specificity (48.9%). The positive predictive value (77.3%) and negative predictive value (78.6%) indicate balanced predictive utility across classes. The model obtained an F1-score of 84.3%, a Matthews correlation coefficient of 0.483, and an AUC of 0.709, suggesting good detection of anxious cases but more limited ability to correctly identify non-anxious cases. Post hoc explainability approaches (local and global) reveal that key predictors of state anxiety include measures of cardio-respiratory fitness (VO2Max), calorie expenditure, duration of light activity, resting heart rate, thermal regulation and age. While additional sensitivity analysis and conformal prediction methods reveal that the size of the datasets contributes to overfitting, the features and the proposed approach is generally conducive for reasonable anxiety prediction. These findings underscore the use of machine learning and ubiquitous sensing modalities for a more holistic and accurate digital phenotyping of state anxiety.

The prevalence and genetic diversity of the protozoan pathogen Giardia duodenalis have been extensively studied worldwide. There is currently a lack of data regarding the genetic variability of the organism in eastern India. Understanding the circulating genotypes and associated risk factors is crucial for effective planning and implementing control measures. Therefore, the objective of the study was to conduct an epidemiological study to determine the prevalence and identify the various genotypes present. This survey adds to our knowledge on the occurrence and distribution of Giardia genotypes in the studied region. The overall prevalence was found to be 6.8%. This parasitic infection was significantly associated with two age groups, i.e., >0–5 years and >5–12 years. Using a multilocus genotyping method, we genotyped 52 human Giardia isolates that were obtained from diarrheal patients. Two distinct assemblages were found in the population—30.8% belonged to assemblage A; 63.5% belonged to assemblage B, prevalent in the population; and 5.7% belonged to a combined assemblage A+B. Sub-assemblage AII was found in 17.3% of the cases, followed by sub-assemblage AI (13.5%). High levels of genetic diversity were found within the population of assemblage B undergoing balancing selection. Overall, the high prevalence of the parasite observed, particularly among children, raises a major concern and necessitates implementation of robust control measures. Furthermore, we report the presence of numerous unique genotypes, circulating in this limited geographical boundary, which can be useful dataset for future studies.

Importance of the amphizoic amoeba Entamoeba moshkovskii is increasing in the study of amoebiasis as a common human pathogen in some settings. Limited studies are found on the genetic and phylogenetic characterization of E. moshkovskii from India; hence remain largely unknown. In this study, we determined the prevalence and characterized the E. moshkovskii isolates in eastern India. A three-year systemic surveillance study among a total of 6051 diarrhoeal patients from ID Hospital and BC Roy Hospital, Kolkata was conducted for E. moshkovskii detection via a nested PCR system targeting 18S rRNA locus. The outer primer set detected the genus Entamoeba and the inner primer pair identified the E. moshkovskii species. The 18S rRNA locus of the positive samples was sequenced. Genetic and phylogenetic structures were determined using DnaSP.v5 and MEGA-X. GraphPad Prism (v.8.4.2), CA, USA was used to analyze the statistical data. 4.84% (95%CI = 0.0433-0.0541) samples were positive for Entamoeba spp and 3.12% (95%CI = 0.027-0.036) were infected with E. moshkovskii. E. moshkovskii infection was significantly associated with age groups (X2 = 26.01, P<0.0001) but not with gender (Fisher's exact test = 0.2548, P<0.05). A unique seasonal pattern was found for E. moshkovskii infection. Additionally, 46.56% (95%CI = 0.396-0.537) were sole E. moshkovskii infections and significantly associated with diarrheal incidence (X2 = 335.5,df = 9; P<0.0001). Sequencing revealed that the local E. moshkovskii strains were 99.59%-100% identical to the prototype (GenBank: KP722605.1). The study found certain SNPs that showed a correlation with clinical features, but it is not necessarily indicative of direct control over pathogenicity. However, SNPs in the 18S rRNA gene could impact the biology of the amoeba and serve as a useful phylogenetic marker for identifying pathogenic E. moshkovskii isolates. Neutrality tests of different coinfected subgroups indicated deviations from neutrality and implied population expansion after a bottleneck event or a selective sweep and/or purifying selection in co-infected subgroups. The majority of FST values of different coinfected subgroups were <0.25, indicating low to moderate genetic differentiation within the subgroups of this geographical area. The findings reveal the epidemiological significance of E. moshkovskii infection in Eastern India as the first report in this geographical area and expose this species as a possible emerging enteric pathogen in India. Our findings provide useful knowledge for further research and the development of future control strategies against E. moshkovskii.

Epidemiological studies on amoebic infections are complicated by morphological overlap between the pathogenic E. histolytica , the commensal E. dispar and the amphizoic E. moshkovskii , necessitating molecular identification. The present study developed a simple and economical 18S PCR–RFLP method for the simultaneous detection and differentiation of the three species. PCR products were differentiated by Tat1 restriction digestion generating three different RFLP patterns. Validation was conducted by screening 382 faecal samples from human patients from Kolkata, India, hospitalized for diarrhoea. Analysis indicated that the PCR–RFLP could successfully differentiate between the three species and was confirmed by sequence analysis. This method could prove useful for clinical and epidemiological studies of amoebiasis.

Depression is one of the most common mental health disorders, affecting approximately 280 million people worldwide. This condition is defined as emotional dysregulation resulting in persistent feelings of sadness, loss of interest and inability to experience pleasure. Early detection can facilitate timely intervention in the form of psychological therapy and/or medication. With the widespread public adoption of wearable devices such as smartwatches and fitness trackers, it is becoming increasingly possible to gain insights relating the mental states of individuals in an unobtrusive manner within free-living conditions. This work presents a machine learning (ML) approach that utilizes retrospectively collected data-derived consumer-grade wearables for passive detection of depression severity. The experiments conducted in this work reveal that multimodal analysis of physiological signals in terms of their discrete wavelet transform (DWT) features exhibit considerably better performance than unimodal scenarios. Additionally, we conduct experiments to view the impact of severity on emotional valence-arousal detection. We believe that our work has implications towards guiding development in the domain of multimodal wearable-based screening of mental health disorders and necessitates appropriate treatment interventions.

Entamoeba moshkovskii, according to recent studies, appears to exert a more significant impact on diarrhoeal infections than previously believed. The efficient identification and genetic characterization of E. moshkovskii isolates from endemic areas worldwide are crucial for understanding the impact of parasite genomes on amoebic infections. In this study, we employed a multilocus sequence typing system to characterize E. moshkovskii isolates, with the aim of assessing the role of genetic variation in the pathogenic potential of E. moshkovskii. We incorporated 3 potential genetic markers: KERP1, a protein rich in lysine and glutamic acid; amoebapore C (apc) and chitinase. Sequencing was attempted for all target loci in 68 positive E. moshkovskii samples, and successfully sequenced a total of 33 samples for all 3 loci. The analysis revealed 17 distinct genotypes, labelled M1–M17, across the tested samples when combining all loci. Notably, genotype M1 demonstrated a statistically significant association with diarrhoeal incidence within E. moshkovskii infection (P = 0.0394). This suggests that M1 may represent a pathogenic strain with the highest potential for causing diarrhoeal symptoms. Additionally, we have identified a few single-nucleotide polymorphisms in the studied loci that can be utilized as genetic markers for recognizing the most potentially pathogenic E. moshkovskii isolates. In our genetic diversity study, the apc locus demonstrated the highest Hd value and π value, indicating its pivotal role in reflecting the evolutionary history and adaptation of the E. moshkovskii population. Furthermore, analyses of linkage disequilibrium and recombination within the E. moshkovskii population suggested that the apc locus could play a crucial role in determining the virulence of E. moshkovskii.

Cyclospora cayetanensis, a recently described coccidian parasite causes severe gastroenteric disease worldwide. Limited studies are found on the incidence of C. cayetanensis infection from India; hence remains largely unknown. To date, no case of cyclosporiasis from eastern India has been reported. In this study, we described an incidental case of C. cayetanensis in a 30 years old Bengali female patient with no travel history from eastern India. In June 2022, the patient presented with a history of diarrhoea persisting for more than two months with continuous passage foul smelling stools for which she took multiple antibiotics that were ineffective. There were no Salmonella, Shigella, or Vibrio-like organisms in the patient's faecal sample, and Toxin A/B of Clostridium difficile was also not detected by ELISA. The patient was HIV-negative. Finally, UV autofluorescence and DNA-based diagnosis confirmed the presence of C. cayetanensis, and the treatment with a combination of appropriate antibiotics was successful. This case report could raise awareness about C. cayetanensis associated diarrhoeal cases in India.

Background The differently-diverged parasitic protist Giardia lamblia is known to have minimal machinery for vesicular transport. Yet, it has three paralogues of SNAP, a crucial component that together with NSF brings about disassembly of the cis -SNARE complex formed following vesicle fusion to target membranes. Given that most opisthokont hosts of this gut parasite express only one α-SNAP, this study was undertaken to determine whether these giardial SNAP proteins have undergone functional divergence. Results All three SNAP paralogues are expressed in trophozoites, encysting trophozoites and cysts. Even though one of them clusters with γ-SNAP sequences in a phylogenetic tree, functional complementation analysis in yeast indicates that all the three proteins are functionally orthologous to α-SNAP. Localization studies showed a mostly non-overlapping distribution of these α-SNAPs in trophozoites, encysting cells and cysts. In addition, two of the paralogues exhibit substantial subcellular redistribution during encystation, which was also seen following exposure to oxidative stress. However, the expression of the three genes remained unchanged during this redistribution process. There is also a difference in the affinity of each of these α-SNAP paralogues for GlNSF. Conclusions None of the genes encoding the three α-SNAPs are pseudogenes and the encoded proteins are likely to discharge non-redundant functions in the different morphological states of G. lamblia . Based on the difference in the interaction of individual α-SNAPs with GlNSF and their non-overlapping pattern of subcellular redistribution during encystation and under stress conditions, it may be concluded that the three giardial α-SNAP paralogues have undergone functional divergence. Presence of one of the giardial α-SNAPs at the PDRs of flagella, where neither GlNSF nor any of the SNAREs localize, indicates that this α-SNAP discharges a SNARE-independent role in this gut pathogen.