Browse Articles

Investigation on potential bias factors in histopathology datasets

Heteroepitaxial Growth of Narrow Band Gap Carbon-Rich Carbon Nitride Using In Situ Polymerization to Empower Sunlight-Driven Photoelectrochemical Water Splitting

Tetrafluororesorcin[4]arene Hexameric Capsule Enables the Expansion of the Reactivity Space in Supramolecular Catalysis

Socio-economic gradients in hypertension and diabetes management amid the COVID-19 pandemic in India

This study examines socio-economic inequalities in the prevalence and treatment of hypertension and diabetes among adults in India, utilising data from the National Family Health Survey (NFHS) collected before and during the COVID-19 pandemic. Disparities associated with individual demographic and socio-economic characteristics are measured, with the level of inequality quantified using the dissimilarity index and contributing factors analysed through decomposition analysis. The results reveal significant socio-economic gradients, with wealthier individuals more likely to have elevated blood pressure and blood glucose levels and to treat them. Socio-economic gradients in treatment are even steeper among middle-aged groups during the pandemic. These wealth- and education-related disparities become more pronounced with age. This study highlights the need for targeted interventions and policies to address socio-economic disparities in access to essential care for socio-economically disadvantaged populations.

Revision of the Formycin A and Pyrazofurin Biosynthetic Pathways Reveals Specificity for <scp>d</scp>-Glutamic Acid and a Cryptic <i>N</i>-Acylation Step During Pyrazole Core Formation

Socioeconomic disparities in anthropometric status among primary school children: A potential association with school meals

Objective To assess the growth and nutritional status of children in primary schools across different socioeconomic groups in Wad-Madani City, Central Sudan, and map it to World Health Organization (WHO) standards; and to investigate a potential association between school meal intake and nutritional status. Methods This cross-sectional anthropometric study involved a randomly selected sample of 506 children from 10 primary schools in the city. Height and weight were measured following WHO standards and converted into Z-scores for weight-for-age (WAZ), height-for-age (HAZ), and BMI-for-age (BAZ). We compared the mean Z-scores between children in the private and public school sectors, adjusting for ethnicity and other potential predictors. Statistical analyses included multivariate linear regression to assess predictors of growth and nutritional status, alongside group comparisons using appropriate statistical tests. Results Children in public schools had significantly lower BAZ and HAZ levels compared to both WHO standards and private school children. The mean BAZ was -1.0 (SD =  1.23) for public school children and -0.13 (SD =  1.40) for private school children (p =  0.001), with 17.8% (n =  57) of public school children classified as thin (wasted) or severely wasted. The median HAZ was -0.20 (95% CI: -0.34, -0.02) for public school children and 0.19 (95% CI: 0.03, 0.40) for private school children (p &lt;  0.001). Additionally, children in suburban public schools had a significantly lower mean HAZ (-0.46, SD =  11.33) compared to those in urban public schools (p =  0.009). Compared to WHO growth standards, public school children had significantly lower mean WAZ (p &lt;  0.001), HAZ (p =  0.002), and BAZ (p &lt;  0.001). Children who received school meals had significantly higher WAZ (mean difference =  0.619, p =  0.001), HAZ (mean difference =  0.401, p =  0.010), and BAZ (mean difference =  0.588, p =  0.003) across the entire sample. Even within the public-school subgroup, while statistical significance was not reached, all three parameters—WAZ (mean difference =  0.334, p =  0.074), HAZ (mean difference =  0.262, p =  0.123), and BAZ (mean difference =  0.299, p =  0.132)—remained consistently higher among those who received school meals. Conclusion Public school children exhibit unfavorable growth and nutritional status, which may be attributed to inadequate nutritional and calorie intake. School meals may improve nutritional outcomes. We propose urgent intervention through the provision of nutritionally adequate school meals.

<i>Mycobacterium tuberculosis</i> CrgA Forms a Dimeric Structure with Its Transmembrane Domain Sandwiched between Cytoplasmic and Periplasmic β-Sheets, Enabling Multiple Interactions with Other Divisome Proteins

A dynamic transmission model for assessing the impact of pneumococcal vaccination in the United States

Streptococcus pneumoniae (SP) is a bacterial pathogen that kills more than 300,000 children every year across the globe. Multiple vaccines exist that prevent pneumococcal disease, with each vaccine covering a variable number of the more than 100 known serotypes. Due to the high effectiveness of these vaccines, each new pneumococcal conjugate vaccine (PCV) introduction has resulted in a decrease in vaccine-type disease and a shift in the serotype distribution towards non-vaccine types in a phenomenon called serotype replacement. Here, an age-structured compartmental model was created that reproduced historical carriage transmission dynamics in the United States and was used to evaluate the population-level impact of new vaccine introductions into the pediatric population. The model incorporates co-colonization and serotype competition, which drives replacement of the vaccine types by the non-vaccine types. The model was calibrated to historical age- and serotype-specific invasive pneumococcal disease (IPD) data from the United States. Vaccine-specific coverage and effectiveness were integrated in accordance with the recommended timelines for each age group. Demographic parameters were derived from US-population-specific databases, while population mixing patterns were informed by US-specific published literature on age-group based mixing matrices. The calibrated model was then used to project the epidemiological impact of PCV15, a 15-valent pneumococcal vaccine, compared with the status quo vaccination with PCV13 and demonstrated the value of added serotypes in PCV15. Projections revealed that PCV15 would reduce IPD incidence by 6.04% (range: 6.01% to 6.06%) over 10 years when compared to PCV13.

Enlightened prognosis: Hepatitis prediction with an explainable machine learning approach

Hepatitis is a widespread inflammatory condition of the liver, presenting a formidable global health challenge. Accurate and timely detection of hepatitis is crucial for effective patient management, yet existing methods exhibit limitations that underscore the need for innovative approaches. Early-stage detection of hepatitis is now possible with the recent adoption of machine learning and deep learning approaches. With this in mind, the study investigates the use of traditional machine learning models, specifically classifiers such as logistic regression, support vector machines (SVM), decision trees, random forest, multilayer perceptron (MLP), and other models, to predict hepatitis infections. After extensive data preprocessing including outlier detection, dataset balancing, and feature engineering, we evaluated the performance of these models. We explored three modeling approaches: machine learning with default hyperparameters, hyperparameter-tuned models using GridSearchCV, and ensemble modeling techniques. The SVM model demonstrated outstanding performance, achieving 99.25% accuracy and a perfect AUC score of 1.00 with consistency in other metrics with 99.27% precision, and 99.24% for both recall and F1-measure. The MLP and Random Forest proved to be in pace with the superior performance of SVM exhibiting an accuracy of 99.00%. To ensure robustness, we employed a 5-fold cross-validation technique. For deeper insight into model interpretability and validation, we employed an explainability analysis of our best-performed models to identify the most effective feature for hepatitis detection. Our proposed model, particularly SVM, exhibits better prediction performance regarding different performance metrics compared to existing literature.

Nonheme Manganese-Catalyzed Oxidative <i>N</i>-Dealkylation of Tertiary Amides: Manganese(IV)-Oxo Aminopyridine Cation Radical Species and Hydride Transfer Mechanism

Targeting NLRP3 and AIM2 signaling pathways by Viscosol alleviates metabolic dysregulations induced inflammatory responses in diabetic neuro- and nephropathy: An in silico and in vivo study

Type 2 Diabetes (T2D) is a chronic metabolic disorder, considered the fastest growing pandemic of the 21stcentury. Meta-inflammation is a pivotal characteristic of T2D. Hyperactivated PTP1B, NLRP3, and AIM2 inflammasomes are considered the major regulators of metabolic inflammation. The concept of diabetes as an inflammatory disease has changed the pathogenic vision of T2D and hence, the compounds that mitigateinflammation in the setting of T2D are under the limelight of research. Current study aimed to evaluatethe anti-inflammatory potency of Viscosol, a novel PTP1B inhibitor, isolated from Dodonaea viscosa, in the STZ-HFD-induced T2D mouse model. Herein, male mice(C57BL/6), were administrated with Streptozotocin (STZ) (40mg/kg) and Viscosol (33mg/kg), intraperitoneally. Computational profiling revealed good absorption, distribution, metabolism and excretion (ADME) properties, least toxicity, and high docking score of Viscosol with PTP1B(−6.4 kcal/mol), NLRP3(−7.2 kcal/mol), and AIM2(−7.4 kcal/mol). Viscosol treatment significantly restored normal body weight (p &lt; 0.0001), decreased the blood glucose level (p &lt; 0.001), serum ROS level(p &lt; 0.05) and diminished the severity of histopathological lesions, inflammatory lobules and increased the cell count of both brain and kidney tissues. The RT-qPCR analysis showed that Viscosol significantly reduced the mRNA expression of PTP1B, NF-κB, NLRP3, and AIM2up to 2.7-folds, 2.6-folds, 5.7-folds and 14.2-folds in the kidney tissues and 1.6-folds, 1.2-folds, 10.2-folds and 1.5-folds in brain tissues. Conclusively, inhibition of PTP1B via Viscosol could attenuate meta-inflammation by suppressing the aberrant NLRP3 and AIM2 inflammasome signaling in diabetes-linked pathophysiology.

Molecular Engineering of Emissive Molecular Qubits Based on Spin-Correlated Radical Pairs

Segmented linear integral correlation Kernel ensemble reconstruction: A new method for climate reconstructions with applications to Holocene era proxies from an East Antarctic ice core

Understanding past climate is essential to our knowledge of how our current climate system operates, and how it might respond to future change. Techniques to reconstruct climate history are challenging, and both accuracy and certainty are hampered by the quality of the datasets used. Here we both develop a new reconstruction tool and apply it to four ice core proxy based multi-millennial Holocene climate reconstructions, chosen because of their potential influence on East Antarctic climate. The new multi-proxy reconstruction method is called Segmented Linear Integral Correlation Kernel Ensemble Reconstruction (SLICKER). This method employs a segmented linear rather than Gaussian correlation approach and builds an ensemble of reconstructions with a best fit and spread related to the best estimate of uncertainty. This method is robust for non-linear, uneven or differently sampled data and produces high-fidelity reconstructions and associated uncertainty estimates. This new method has the potential to produce more realistic reconstructions, with associated uncertainty estimates based on robust statistical measures that are insensitive to outliers. The main findings from these new reconstructions are: Antarctica temperature shows multi-decadal variability over the last twelve thousand years with increased frequency over the last two thousand years; Zonal Wave 3 index and the Southern Annular Mode both show limited trends over the last two thousand years, but an increase since the 1970s CE; and the Indian Ocean Dipole Moment index has a twentieth century CE upward trend, and a thirteenth to sixteenth century CE below average period which may be related to volcanic activity.

Pushing Limits of Ultra-wideline Solid-State NMR Spectroscopy: NMR Signatures of ²⁰⁹Bi and ¹²⁷I in Metal–Organic Frameworks at Ultra-high Magnetic Fields

A new Middle Jurassic lagoon margin assemblage of theropod and sauropod dinosaur trackways from the Isle of Skye, Scotland

Although globally scarce, Middle Jurassic dinosaur tracks are known from the Isle of Skye, Scotland, and help indicate the palaeoenvironmental preferences and behaviour of major dinosaur clades. Here, we report an extensive new tracksite from Skye: 131 in-situ dinosaur tracks at Prince Charles’s Point on the Trotternish Peninsula. The tracks occur in multiple horizons of rippled sandstones of the Late Bathonian aged Kilmaluag Formation, part of the Great Estuarine Group, which formed in a locally, shallowly submerged lagoon margin. We assign these tracks to two morphotypes, further divided into four morphotype subgroups, most likely representing large megalosaurid theropods, and sauropods that are either non-neosauropods or basal neosauropods. The trackways, although relatively short, evidence time-averaged milling behaviour, as observed at other tracksites in the Great Estuarine Group. The presence of sequential manus and pes sauropod tracks amends their previous identification by geologists as fish resting burrows, raising the potential that other such structures locally and globally may in fact be dinosaur tracks, and emphasises the predominant occurrence of sauropods in lagoonal palaeoenvironments in the Great Estuarine Group. At Prince Charles’s Point, however, unlike previously described lagoonal assemblages, large theropod trackmakers are more abundant than sauropods.

Nuclear Quantum Effects Accelerate Hot Carrier Relaxation but Slow Down Recombination in Metal Halide Perovskites

Assessing interface accuracy in macromolecular complexes

Accurately predicting the 3D structures of macromolecular complexes is becoming increasingly important for understanding their cellular functions. At the same time, reliably assessing prediction quality remains a significant challenge in bioinformatics. To address this, various methods analyze and evaluate in silico models from multiple perspectives, accounting for both the reconstructed components’ structures and their arrangement within the complex. In this work, we introduce Intermolecular Interaction Network Fidelity (I-INF), a normalized similarity measure that quantifies intermolecular interactions in multichain complexes. Adapted from a well-established score in the RNA field, I-INF provides a clear and intuitive way to evaluate the predicted 3D models against a reference structure, with a specific focus on interchain interaction sites. Additionally, we implement the F1 measure to assess interfaces in macromolecular assemblies, further enriching the evaluation framework. Tested on 72 RNA-protein decoys, as well as exemplary DNA-DNA, RNA-RNA, and protein-protein complexes, these measures deliver reliable scores and enable straightforward ranking of predictions. The tool for computing I-INF and F1 is publicly available on Zenodo, facilitating large-scale analysis and integration with other computational systems.

Heavy Atom-Induced Spin–Orbit Coupling to Quench Singlet Oxygen in a Li–O₂ Battery

Comorbidities and health-related quality of life among rural older community-dwellers in Vietnam

This study explored the patterns of comorbidities and their impact on health-related quality of life (HRQoL) among elderly individuals living in rural communities in Vietnam. A cross-sectional study was conducted across four communes in Thai Binh province. The demographic characteristics and comorbidities of the participants were evaluated, along with their Euroqol-5 dimensions-5 levels (EQ-5D-5L), using a structured questionnaire supplemented by clinical examinations. A multivariate Tobit regression model was applied to assess the relationship between comorbidities and HRQoL. Results showed that a minority of participants (9.5%) were free of comorbidities. Cataracts were the most common condition (61.0%), followed by osteoarthritis (55.4%), rheumatoid arthritis (46.1%), and dementia (39.0%). The average EQ-5D index was 0.806 (SD =  0.184). Pain/discomfort, difficulties with usual activities, and anxiety/depression contributed most to the reduction in the EQ-5D-5L index. Participants with rheumatoid arthritis (β =  − 0.10; 95% CI =  − 0.13, − 0.07) and postural hypotension (β =  − 0.08; 95% CI =  − 0.14, − 0.02) experienced the greatest decrease in EQ-5D index, followed by those with urinary diseases (β =  − 0.05; 95% CI =  − 0.09, − 0.02) and stroke (β =  − 0.05; 95% CI =  − 0.09, − 0.01). This study highlights the high prevalence of comorbidities among the elderly in rural Vietnam, with arthritis, postural hypotension, urinary diseases, and stroke being most strongly associated with reduced HRQoL. Regular screening and monitoring of comorbidities are vital to identify individuals who would benefit most from healthcare interventions to enhance HRQoL.

Hydroformylation over Zeolite Catalysts with Solvophobic Micropores