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Background: Urinary tract infection (UTI) commonly affects people of different ages. It is important to explore the antibiotic susceptibility of the bacterial agents to improve the empirical antibacterial prescription to tackle the fast emerging of multi-drug resistant (MDR) bacteria. Klebsiella pneumoniae, a Gram-negative bacterium, is widely known for its hypervirulence, drug resistance and opportunistic nature, with significant implications for critically ill or immunocompromised patients. The study aim is to determine the prevalence of antibiotic resistance pattern among isolates from urinary tract infections (UTIs) and provide valuable insights for healthcare management. Methods: This is a retrospective observational study including 250 patients among 500 sample screened to have UTI at the largest hospital in eastern India from July 2020 to November 2022. All UTI patients underwent agar-based bacterium identification and antibiotic sensitivity testing using the disc diffusion method. Results: Klebsiella pneumoniae (122 cases) and Escherichia coli (74) were the first and second most frequent Gram-negative isolates, followed by Pseudomonas aeruginosa (45) and Acinetobacter baumannii (9). Notably, ten Klebsiella pneumoniae strains were resistant to five major antibiotic classes: β-lactam, aminoglycosides, fluoroquinolones, tetracyclines, and polymyxin. piperacillin/tazobactam, ceftazidime, aztreonam, and imipenem exhibited high resistance rates when tested against Klebsiella pneumoniae isolates. In contrast, gentamicin, levofloxacin, minocycline, fosfomycin, and colistin demonstrated relatively lower effectiveness against Klebsiella pneumonia isolates. Conclusion: Monitoring of multidrug-resistant bacteria becomes critical for prudent antibiotic use, ultimately dropping the prevalence of hospital-acquired infections and contributing to the larger fight against antimicrobial resistance.

Abstract Assessment of immune correlates of severe COVID-19 has been hampered by the low numbers of severe cases in COVID-19 vaccine efficacy (VE) trials. We assess neutralizing and binding antibody levels at 4 weeks post-Ad26.COV2.S vaccination as correlates of risk and of protection against severe-critical COVID-19 through 220 days post-vaccination in the ENSEMBLE trial (NCT04505722), constituting ~4.5 months longer follow-up than our previous correlates analysis and enabling inclusion of 42 severe-critical vaccine-breakthrough cases. Neutralizing antibody titer is a strong inverse correlate of severe-critical COVID-19, with estimated hazard ratio (HR) per 10-fold increase 0.35 (95% CI: 0.13, 0.90). In a multivariable model, HRs are 0.31 (0.11, 0.89) for neutralizing antibody titer and 1.22 (0.49, 3.02) for anti-Spike binding antibody concentration. VE against severe-critical COVID-19 rises with neutralizing antibody titer: 63.1% (95% CI: 40.0%, 77.3%) at unquantifiable [

Abstract Lipids are one of the major biomolecules of our life with diverse structures and functions. Dietary lipids are an essential source of nutrients and energy for humans. Even though the mechanisms of dietary lipid absorption and transport are unclear, numerous studies have demonstrated their biological importance in health and disease management. Fish is the major source of essential bioactive lipids called ω-3 fatty acids (docosahexaenoic acid and eicosapentaenoic acid) which have anti-inflammatory, antioxidant, and protective actions in cardiovascular diseases. Despite the various benefits of bioactive lipids derived from food, there is limited information in the literature discussing the sources, analysis, and function of food lipids. This review aims to cover the eight major categories of lipids and their key sources from plants, animals, microbiomes, and insect origin. Further, the aspects of various analytical technologies applied to determine the lipids in food and their anti-inflammatory, antioxidant, antimicrobial, and antiviral functions were discussed. This study offers a thorough overview of food lipid sources and their biological importance, including their analysis using various analytical techniques. Graphical abstract

This study aimed to better understand how autism spectrum disorder (ASD) and developmental coordination disorder (DCD) differ in types of praxis errors made on the Florida Apraxia Battery Modified (FAB-M) and the potential relationships between praxis errors and social deficits in ASD. The ASD group made significantly more timing sequencing errors in imitation of meaningful gestures, as well as more body-part-for-tool errors during gesture-to-command compared to the other two groups. In the ASD group, increased temporal errors in meaningful imitation were significantly correlated with poorer affect recognition and less repetitive behaviors. Thus, in ASD, aspects of imitation ability are related to socioemotional skills and repetitive behaviors.

ABSTRACT This case illustrates the diagnostic challenges in identifying neurocysticercosis, which is initially mistaken for tubercular arachnoiditis. Early recognition and multidisciplinary management are crucial for preventing severe complications. The case also describes the importance of awareness and timely treatment of neglected tropical diseases to improve patient outcomes.

Introduction: Substance-use disorders (SUDs) are a public health problem. The Global Adult Tobacco Survey (GATS) and National Family Health Survey (NFHS) provide evidence of high usage. Hence, the National Mental Health Survey (NMHS) WB data were analyzed to estimate the prevalence, pattern, disability burden, and service utilization of SUD. Methodology: The usual NMHS methodology was used. Four districts were selected, and thereafter, a multistage random sampling was done. The validated Bengali version of the Mini International Neuropsychiatric Interview (MINI) and other instruments like the Fagerstrom Test for Nicotine Dependence (FTND), disability, and health care utilization modules were used. Results: A total of 2,646 eligible members (age >18 years as per 2011 census) were interviewed. It was found that alcohol use as per MINI at least 3 drinks of alcohol within 3 hours on 3 or more occasions was 3.9%, and the weighted prevalence of alcohol-use disorder (AUD) and tobacco-use disorder (TUD) was 3.04% and 14%, respectively. The AUD and TUD prevalence was lower than the national prevalence, yet they were more prevalent in urban areas than in the national trend. The ratio of women to men suffering from AUD in WB (1:5) was one of the highest in the country (all India average 1:18). Also, the treatment gap of 89.2% was more than the national average. Discussion: SUDs are an important public health problem in the state of WB, which requires further research, particularly among women, comorbid psychiatric disorders, and in urban areas.

The COVE trial randomized participants to receive two doses of mRNA-1273 vaccine or placebo on Days 1 and 29 (D1, D29). Anti-SARS-CoV-2 Spike IgG binding antibodies (bAbs), anti-receptor binding domain IgG bAbs, 50% inhibitory dilution neutralizing antibody (nAb) titers, and 80% inhibitory dilution nAb titers were measured at D29 and D57. We assessed these markers as correlates of protection (CoPs) against COVID-19 using stochastic interventional vaccine efficacy (SVE) analysis and principal surrogate (PS) analysis, frameworks not used in our previous COVE immune correlates analyses. By SVE analysis, hypothetical shifts of the D57 Spike IgG distribution from a geometric mean concentration (GMC) of 2737 binding antibody units (BAU)/mL (estimated vaccine efficacy (VE): 92.9% (95% CI: 91.7%, 93.9%)) to 274 BAU/mL or to 27,368 BAU/mL resulted in an overall estimated VE of 84.2% (79.0%, 88.1%) and 97.6% (97.4%, 97.7%), respectively. By binary marker PS analysis of Low and High subgroups (cut-point: 2094 BAU/mL), the ignorance interval (IGI) and estimated uncertainty interval (EUI) for VE were [85%, 90%] and (78%, 93%) for Low compared to [95%, 96%] and (92%, 97%) for High. By continuous marker PS analysis, the IGI and 95% EUI for VE at the 2.5th percentile (519.4 BAU/mL) vs. at the 97.5th percentile (9262.9 BAU/mL) of D57 Spike IgG concentration were [92.6%, 93.4%] and (89.2%, 95.7%) vs. [94.3%, 94.6%] and (89.7%, 97.0%). Results were similar for other D29 and D57 markers. Thus, the SVE and PS analyses additionally support all four markers at both time points as CoPs.

Background: Open-heart surgery is challenging in preterm neonates and infants, and its feasibility in low-resource settings has not been defined. We describe our institutional experience with open-heart surgeries performed on consecutive preterm infants. Materials, Methods and Results: This was a single-center retrospective cohort from a tertiary hospital in Southern India and included consecutive preterm neonates (

Leprosy is a chronic granulomatous infection that primarily affects developing and underdeveloped countries. Co-infection with the hepatitis B virus can complicate its natural course by altering the host immune system response and thereby the disease outcomes. Early detection and treatment of the disease is thus imperative for preventing debilitating deformities. Several studies have shown positive viral markers for human immunodeficiency virus (HIV) and hepatitis B in patients with leprosy. However, in the Indian subcontinent, we have limited evidence highlighting this correlation. We present a case of a 42-year-old male with chronic hepatitis B infection presenting with new-onset lepromatous leprosy. The patient was successfully managed with a multibacillary multidrug regimen. In patients with hepatitis B co-infection, clinicians must be vigilant about the higher risk of complications and poorer patient outcomes. Extensive longitudinal studies assessing the correlation between leprosy and hepatitis B in India can help tailor future guidelines for management.

Measuring immune correlates of disease acquisition and protection in the context of a clinical trial is a prerequisite for improved vaccine design. We analysed binding and neutralizing antibody measurements 4 weeks post vaccination as correlates of risk of moderate to severe-critical COVID-19 through 83 d post vaccination in the phase 3, double-blind placebo-controlled phase of ENSEMBLE, an international randomized efficacy trial of a single dose of Ad26.COV2.S. We also evaluated correlates of protection in the trial cohort. Of the three antibody immune markers we measured, we found most support for 50% inhibitory dilution (ID50) neutralizing antibody titre as a correlate of risk and of protection. The outcome hazard ratio was 0.49 (95% confidence interval 0.29, 0.81; P = 0.006) per 10-fold increase in ID50; vaccine efficacy was 60% (43%, 72%) at non-quantifiable ID50 (

Some studies suggest that individuals with autism spectrum disorder have reduced emotional empathy while others do not. The presence of co-occurring alexithymia in autism spectrum disorder and differences in interoception have been associated with reductions in empathic ability. To fully explore the relationships between interoception, alexithymia, and emotional empathy, we collected self-report and interview data in 35 youth with autism spectrum disorder and 40 typically developing controls (ages 8-17 years). The autism spectrum disorder sample had increased alexithymia and physiological hyperarousal compared to typically developing controls, but there were no group differences in interoception or emotional empathy. Alexithymia severity correlated with higher personal distress in both groups and with lower empathic concern in the autism spectrum disorder group. Within the autism spectrum disorder group, higher incidence of reports of bodily sensation when describing emotional experience correlated with lower personal distress and lower alexithymia. In addition, although empathic concern was negatively correlated with alexithymia in the autism spectrum disorder group, across groups, the alexithymia hypothesis was supported in only the personal distress domain of emotional empathy. These results suggest emotional empathy; personal distress, in particular, is not intrinsically impaired in autism spectrum disorder.

In general, the Body Channel Communication (BCC) is used to transmit human physiological signals over vast distances. Also, the Error-correcting codes can detect and rectify faults in long-range data transmission. Data is encoded in a predetermined manner for secure transmission. In this paper, a Manchester encoding-based high throughput architecture is proposed for a body channel communication system with a low-power operation mode. Further, the Manchester encoder is designed for high throughput performance with a low complexity architecture, and an analog front-end processing circuit which includes two stage pre-amplifiers. Also, the transmission rate on the BCC transceiver side is boosted by the maximum Consecutive Identical Digit (CID), which is limited by Manchester codes. The Manchester code format is generated by encoding the sensed data. Additionally, a full gain buffer is used to reduce data loss and hardware overhead. Results demonstrate that the suggested Manchester encoder is implemented in 90 nano meter (nm) technology, and the 10 Megabits per second (Mbps) data rate is obtained with a configurable operating frequency ranging from 1 to 100 Megahertz (MHz).

In general, ventricular repolarization instability with Premature Activations (PA) plays a significant role in the detection of arrhythmia using an electrocardiogram (ECG) signal. However, clinical detection of this instability is challenging. In this work, a unique technique for analyzing QT Interval (QTI) dynamics unreliability and other abnormalities in the ECG signal are utilized to detect ventricular tachycardia based on the identified anomalies. Further, a feature extraction method based on Chopped Displacement Gaussian (CDGa) is adopted and the features are retrieved from the CDGa signal and its size is reduced using Fisher Discrimination Analysis (FDA). Also, the results of the FDA are fed into the Adaptive Neuro-Fuzzy interference (ANFIS) classifier. The performance of the ANFIS classifier is enhanced in this study by integrating the Grasshopper optimization algorithm for optimizing network parameters. As a result, the values in the signals are predicted using an adaptive Least Mean Square (LMS)-based prediction algorithm, which is utilized to forecast the future status of VT-affected patients. Results indicate that the proposed work has an overall accuracy of 96 % which is higher than any other conventional methods. Also, the various additional performance criteria are tested, and it is demonstrated that the CDGa with adaptive LMS outperforms all previous approaches.

Background: Type 2 Diabetes mellitus (T2DM) may affect the musculoskeletal (MSK) system in a variety of ways. The impacts can be debilitating enough to impair functional ability and quality of life. MSK complications are the most common endocrine arthropathies which are often under-recognized and poorly treated. This study was done to evaluate the prevalence of MSK complications and its correlation with microvascular complications of T2DM given the paucity of similar studies in India particularly South India. Materials and Methods: A cross-sectional study was conducted on 130 diabetic patients at a tertiary care hospital in Bengaluru. The patient's demographic details, clinical profile including history, general physical examination, systemic examination, and relevant investigations were done to record microvascular complications. A thorough MSK system examination along with imaging of bones and joints was also performed. Results: Out of 130 diabetic patients, 21 patients (16.2%) had MSK complications of which 47.6% (n = 10) of them had carpal tunnel syndrome and 42.8% (n = 9) had frozen shoulder and 9.5% (n = 2) had diabetic amyotrophy. It was also noted that patients who were on oral hypoglycemic agents alone were more likely to develop MSK complications (57.14%) than patients solely on insulin (14.2%). Poor glycemic control, existing microvascular complications, and low high-density lipoprotein were found to be associated with increased risk of MSK complications. Conclusion: The prevalence of MSK complications in T2DM patients is quite significant and is also associated with microvascular complications. Improved glycemic control in T2DM was found to reduce the burden of such complications. Early identification of MSK complications can improve the quality of life in diabetic patients and hence demands proper screening and follow-up.

Effects estimated by genome-wide association studies (GWASs) include effects of alleles in an individual on that individual (direct genetic effects), indirect genetic effects (for example, effects of alleles in parents on offspring through the environment) and bias from confounding. Within-family genetic variation is random, enabling unbiased estimation of direct genetic effects when parents are genotyped. However, parental genotypes are often missing. We introduce a method that imputes missing parental genotypes and estimates direct genetic effects. Our method, implemented in the software package snipar (single-nucleotide imputation of parents), gives more precise estimates of direct genetic effects than existing approaches. Using 39,614 individuals from the UK Biobank with at least one genotyped sibling/parent, we estimate the correlation between direct genetic effects and effects from standard GWASs for nine phenotypes, including educational attainment (r = 0.739, standard error (s.e.) = 0.086) and cognitive ability (r = 0.490, s.e. = 0.086). Our results demonstrate substantial confounding bias in standard GWASs for some phenotypes.

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57.

Background: Untargeted lipidomics using collision-induced dissociation-based tandem mass spectrometry (CID-MS/MS) is essential for biological and clinical applications. However, annotation confidence still relies on manual curation by analytical chemists, despite the development of various software tools for automatic spectral processing based on rule-based fragment annotations. Methods: In this study, we present a novel machine learning model, MS2Lipid, for the prediction of known lipid subclasses from MS/MS queries, providing an orthogonal approach to existing lipidomics software programs in determining the lipid subclass of ion features. We designed a new descriptor, MCH (mode of carbon and hydrogen), to increase the specificity of lipid subclass prediction in nominal mass resolution MS data. Results: The model, trained with 6760 and 6862 manually curated MS/MS spectra for the positive and negative ion modes, respectively, classified queries into one or several of 97 lipid subclasses, achieving an accuracy of 97.4% in the test set. The program was further validated using various datasets from different instruments and curators, with the average accuracy exceeding 87.2%. Using an integrated approach with molecular spectral networking, we demonstrated the utility of MS2Lipid by annotating microbiota-derived esterified bile acids, whose abundance was significantly increased in fecal samples of obese patients in a human cohort study. This suggests that the machine learning model provides an independent criterion for lipid subclass classification, enhancing the annotation of lipid metabolites within known lipid classes. Conclusions: MS2Lipid is a highly accurate machine learning model that enhances lipid subclass annotation from MS/MS data and provides an independent criterion.

Background: West Bengal, situated in eastern India, comprising 19 districts as of 2016 and consisting of 9.13 crore population, had been one of the participating states in the National Mental Health Survey, 2015–16. Aim: To estimate the prevalence and pattern of mental disorders in a representative population in West Bengal. Materials and Methods: Based upon a multi-stage stratified random cluster sampling with probability proportionate to each stage, 2646 eligible individuals were interviewed. Standard validated instruments in Bengali like socio-demographic profiles and Mini International Neuropsychiatric Interview (MINI) version 6 were used by trained data collectors with quality monitoring as per a standardized protocol. Results: The current prevalence of mental illness in the state of West Bengal is 13.07% (12.9–13.24 95% CI), which is more than the current national average of 10.56% (10.51–10.61 95% CI). The prevalence of severe mental illness of 2.32% and suicide risk of 1.75% (1.68–1.81 95% CI) is higher than the national average. The common mental illness prevalence is 11.29 (11.13–11.45 95% CI), which is similar to the national weighted average. In West Bengal, severe mental illness is more concentrated in the rural areas in contrast to the national trend. Also, the prevalence of alcohol use disorder is 3.04 (2.96–3.13 95% CI) and epilepsy is 0.03 (0.27–0.29 95% CI), which is less than the national average. Conclusion: The prevalence of mental disorders in the state of West Bengal is higher than the national average, and for severe mental illness, the prevalence is the highest as compared to the national average.

Introduction: Epilepsy is one of the most prevalent noncommunicable neurologic conditions, accounting for significant disability and mortality. The effects of Antiepileptic Drugs (AEDs) on total cholesterol, triglycerides, High-Density Lipoprotein (HDL) cholesterol, low-density lipoprotein cholesterol, and apolipoprotein levels have been demonstrated in many studies, mainly conducted with adults. However, there have been very few studies in children. Derangement of lipid profile and other metabolic abnormalities could lead to the development of metabolic syndrome in children. The adverse metabolic effects of anti-epileptics are underestimated, as only a few studies have been done in this area, which is a legitimate concern. Aim: To assess the impact of AEDs on metabolic parameters in children with epilepsy. Materials and Methods: This was a descriptive, crosssectional study conducted in the Department of Paediatrics and Pharmacology at Pt. BD Sharma PGIMS, Rohtak, Haryana, India. The study included 100 children with epilepsy from May 2022 to October 2022. A predefined case record form, including demographic and clinical characteristics, was filled for each participant. The parameters recorded were age, gender, outpatient number, type of epilepsy, history of duration of epilepsy, current AED history, and seizure frequency over the preceding six months, as per the case record form. Guidelines from the International Diabetes Federation were used for diagnosing metabolic syndrome in children. The data was entered into Microsoft excel and presented using descriptive statistics. The chi-square test was used to differentiate between categorical variables. Results: The mean age of the study participants was 10.2±2.97 years. There were more males (62%) than females (38%). A 48% of the patients received monotherapy, while 52% received polytherapy. A total of 24% of the patients had derangement in lipid profile (increased triglycerides and decreased HDL), with 14% of patients on monotherapy and 10% on polytherapy. The difference in metabolic derangements between monotherapy and polytherapy was not statistically significant (p=0.25). Out of 100 participants, 3% fulfilled the criteria for metabolic syndrome, with a predominance in males. Conclusion: Metabolic derangements are known with 1st generation AEDs, but 2nd generation AEDs can also lead to significant metabolic abnormalities.