Browse Articles

Synergistic application of biochar and sodium hydrosulfide enhances maize drought tolerance through improved physiological performance and stress mitigation

Light-induced self-adaptive growth of photonic crystal structures in perfluorosulfonic acid ionomer films

A socio-technical agent-based simulation model for predicting smart agriculture adoption dynamics

Evaporation-driven generic, high-throughput and roll-to-roll printing of nanomaterials

Top-down perspectives on cell membrane potential and protein transcription

Can nighttime lights serve as a proxy for economic inequality at the local administrative unit scale? Evidence from Spain

Economic inequality remains a pressing issue, with localized disparities becoming increasingly visible. Monitoring these subnational dynamics is often constrained by the availability of timely, reliable data. This study evaluates the potential of nighttime light (NTL) data to proxy economic inequality at the scale of local administrative units (municipalities), using Spain as a case study. Spain is among the most unequal EU countries by the Gini index and has published municipal income distribution records since 2015. Its geographic and demographic diversity provides a robust setting for testing NTL-based measures with broader applicability. We combine two remote-sensing products (VIIRS and Harmonized NTL) with WorldPop gridded population data to compute lights-per-capita for each pixel. Within each municipality, Gini coefficients are calculated using pixels as the unit of analysis, enabling fine-grained spatial estimation of inequality. We derive Gini values for over 8,000 municipalities for 2015–2020 and compare them with official income-based Gini coefficients from Spain’s tax administration. Relationships between light- and income-derived measures are assessed using cross-sectional regressions and multilevel panel models. Results show statistically significant associations between NTL- and income-derived Gini coefficients, particularly in smaller settlements and rural areas. Panel models outperform cross-sectional models, indicating that NTL data capture temporal changes in inequality even when contemporaneous correlations are modest. Some regions exhibit elevated NTL-derived inequality despite low official estimates—often where unemployment or informal economic activity is prevalent—suggesting that light-based metrics detect disparities not fully reflected in formal income statistics. These findings demonstrate the promise of NTL-derived indicators as scalable, low-cost, and globally replicable tools for monitoring inequality in both data-rich and data-poor settings. As subnational disparities gain importance, this framework offers a practical avenue for fine-grained and inclusive socioeconomic monitoring. Future work should integrate additional spatial layers—such as urban form, infrastructure, and demographics—to refine accuracy and interpretation.

Asymmetric Synthesis of Quaternary Hydantoins via a Palladium-Catalyzed Aza-Heck Cyclization

The balance between stability and plasticity of the visual word form area in dyslexia

Outcome centred process mapping in healthcare using random forest and process mining

Molecular docking and MD simulations predicted quercetin as a potent human interleukin-1 beta (hIL1β) inhibitor for improved endodontic disease management

IL1β, a pro-inflammatory cytokine, is a key mediator in the inflammatory processes linked to endodontic disorders. Studies have shown that IL1β production is elevated in symptomatic periapical lesions, highlighting its involvement in inflammation and lesion development. Elevated levels of IL1β correlate with larger lesion sizes and increased inflammation in periapical tissues. Given its role in inflammation, IL1β represents a potential therapeutic target for endodontic diseases, including the use of IL1β inhibitors. The present study used molecular docking and MD simulations to identify small molecule inhibitors of hIL1β. A small library of 329 plant-derived natural compounds was screened against hIL1β, the top five hits were selected based on their binding affinity and score and docked with hIL1β. Molecular docking results showed that Quercetin has the highest binding affinity (−10.3 kcal/mol) and exibits favorable interactions with hIL1β compared to the other four hits. Based on these observations, Quercetin was further subjected to MD simulations with hIL1β. MD trajectories were used to determine the interaction and stability of the hIL1β-Quercetin complex using various parameters, such as RMSD, RMSF, Rg, SASA, and hydrogen bond count of the apo hIL1β and Quercetin-hIL1β complex. Consistent RMSD, RMSF, Rg, and SASA values indicated the stability of the complex. Furthermore, hydrogen bond count emphasized the Quercetin’s role as a non-disruptive binder. Moreover, secondary structure analysis, PCA, and calculations of Gibbs free energy revealed minimal structural changes and highlighted the stable conformational state of hIL1β upon Quercetin binding, suggesting a stabilizing effect of Quercetin. These observations suggest Quercetin’s potential in the development of new treatments for endodontic diseases, which may lead to improved clinical outcomes and reduced recurrence rates.

Limitations in PPARα-dependent mitochondrial programming restrain the differentiation of human stem cell-derived β cells

End-to-end human parsing and detection optimized for resource-constrained devices

Impact of childhood household support on depression and self-reported mental and physical health

Background Perceived household support during childhood defined as the presence of an adult who consistently tried to ensure that basic needs were met has lasting effects on mental and physical health across the life course. While its protective role is well recognized, less is known about whether these associations vary across gender and racial/ethnic groups. Methods We conducted a cross-sectional analysis of 31,233 U.S. adults from the 2021–2024 Behavioral Risk Factor Surveillance System (BRFSS). The primary exposure was self-reported childhood household support, categorized as “Never,” “A Little of the Time,” “Some of the Time,” “Most of the Time,” or “All of the Time.” Outcomes included lifetime diagnosis of depression, average monthly poor mental health days, and poor physical health days. Analyses used inverse probability weighting and survey-adjusted regression, controlling for sociodemographic characteristics, state, year, and month fixed effects. Models were stratified by gender and race/ethnicity to evaluate moderating effects. Results Among respondents (mean age 52.2 years; 63.4% female; 76.0% White), Individuals who reported “Never” being supported were 19.4 percentage points more likely to report a depression diagnosis (95% CI, 11.6–27.2), experienced 5.33 more poor mental health days (95% CI, 3.64–7.03), and 2.77 more poor physical health days (95% CI, 1.23–4.32) per month compared to those “Always” supported. A clear dose–response gradient was observed across all categories of support. Gender-stratified analyses revealed that women had consistently higher adjusted probabilities of depression than men across most support categories. Race/ethnicity-stratified analyses indicated that Black respondents consistently exhibited lower adjusted probabilities of depression compared with White respondents, while Hispanic respondents reported more poor mental health days in the “A little of the time” category. Conclusions Perceived childhood household support is strongly and progressively protective against depression and poor mental and physical health outcomes in adulthood. However, its benefits are not uniformly distributed: women remain disproportionately vulnerable to depressive outcomes even with partial support, while race/ethnicity-specific differences suggest the presence of resilience as well as distinct vulnerabilities. These findings highlight the universal importance of stable, supportive caregiving environments and underscore the need for prevention and intervention strategies that are both gender-sensitive and culturally tailored to reduce lifelong health disparities.

Wnt signaling restores evolutionary loss of robust foot regeneration rates in Hydra

Abstract The regenerative potential of animals varies widely, even among closely related species. In a comparative study of regeneration across the Hydra genus, we found that while most species exhibit robust whole-body regeneration, Hydra oligactis and other members of the Oligactis clade display substantially reduced rates of foot regeneration. To investigate the mechanisms underlying this deficiency, we analyzed transcriptional responses during head and foot regeneration in H. oligactis . Our analysis revealed that the general injury response in H. oligactis lacks strong activation of Wnt signaling, a pathway essential for Hydra vulgaris foot regeneration. Notably, transient treatment with a Wnt agonist in H. oligactis triggered a foot-specific transcriptional program, significantly increasing rates of foot regeneration. Our transcriptional profiling also revealed dlx2 as a likely high-level regulator of foot regeneration, dependent on Wnt signaling activation. Our study establishes a comparative framework for understanding the molecular basis of regeneration in Hydra and provides a new platform for investigating the evolution of regenerative mechanisms.

A sparse wavelength aware learning framework for robust FSO channel estimation

Development of machine learning models for prediction of current and future dementia

Dementia is among the most distressing and burdensome health challenges in aging populations. Treatment efficacy is limited; however, early diagnosis can delay or prevent disease progression. Previous machine learning-based prediction models have limitations (e.g., they are based on clinical parameters or are not generalizable). Thus, in this study, prediction models were developed for current and future dementia solely based on demographic, socioeconomic, and health-related features. Demographic, socioeconomic, and health-related variables collected from the Korean Longitudinal Study of Ageing (KLoSA) were used to develop machine learning-based prediction models for current and future dementia with various algorithms. Two sampling strategies were used for feature selection, one based on domain knowledge and the other based on statistical testing. Hyperparameter tuning was performed using grid search with cross-validation on the training set, and model evaluation was conducted on a separate test set. In the initial no-follow-up dataset, 92 of 6,898 participants exhibited dementia. Among 6,207 participants without dementia initially, 69 developed dementia within 2 years. Linear support vector machine (SVM) and radial bias function SVM exhibited the best sensitivity for current and future dementia (79.4% and 77.7%, respectively). The SHAP (SHapley Additive exPlanations) approach improved the transparency of the model by highlighting the top ten features most strongly associated with increased dementia risk. We achieved reasonably accurate prediction results for dementia using only non-clinical features.

Systematic identification of bacterial factors driving Staphylococcus aureus intracellular lifestyle in non-professional phagocytes

Abstract Staphylococcus aureus is a major human pathogen responsible for severe infections. While traditionally described as extracellular, increasing evidence establishes S. aureus as a facultative intracellular pathogen. Intracellularity contributes to immune evasion, dissemination, and antibiotic failure. To identify bacterial factors critical for S. aureus invasion, intracellular replication, persistence, and host cytotoxicity, we screened a comprehensive collection of 1920 S. aureus mutants (Nebraska Transposon Mutant Library) in epithelial cells across five timepoints (0.5 to 48 hours post-infection). We identified 73 bacterial factors strongly modulating S. aureus intracellularity, including mutants displaying multiple phenotypes. Most of these factors have not been linked to intracellular lifestyle. Among these, we characterized the nicotinamidase PncA as a novel regulator of the agr system via redox state modulation, strongly impacting virulence. This study provides a systematic analysis of S. aureus factors critical for intracellular lifestyle, with implications for the development of antimicrobial strategies targeting this resilient bacterial population.

Exploring the structure and functional meaning of pre-performance emotions in young adult musicians

Global burden and future projections of non-communicable diseases (2000–2050): Progress toward SDG 3.4 and disparities across regions and risk factors

Background Non-communicable diseases (NCDs), such as cardiovascular diseases (CVDs), neoplasms, chronic respiratory diseases (CRDs), and diabetes mellitus (DM), are the leading cause of death globally and a major health challenge, threatening Sustainable Development Goal (SDG) 3.4 to reduce premature mortality by one-third by 2030. The study aimed to quantify the current and projected burden of these NCDs, assess disparities, and identify prevention opportunities. Methods Using data from the Global Burden of Disease Study (GBD) 2021 by the Institute for Health Metrics and Evaluation, the study analysed incidence, mortality, and disability-adjusted life years (DALYs) for CVDs, neoplasms, CRDs, and DM from 2000 to 2021, with projections to 2050. Trends were stratified by time, WHO region, Socio-Demographic Index (SDI), gender, and country, alongside risk factor contributions (metabolic, behavioural, environmental). Age-standardized rates and average annual percent changes (AAPC) were calculated to assess trajectories. Results In 2021, NCDs accounted for 12·4 billion incident cases (rate: 156,680·64 per 100,000), 43·8 million deaths (64·5% of total, rate: 554·63 per 100,000), and 1·73 billion DALYs (59·9%, rate: 21,887·11 per 100,000). CVDs led with 19·4 million deaths (28·6%), followed by neoplasms (9·9 million, 14·6%), CRDs (4·4 million, 6·5%), and DM (1·7 million, 2·4%). From 2000–2021, DM incidence rose sharply (AAPC: 2·41%), while CVD mortality increased slightly (AAPC: 0·21%). High SDI regions showed peak DM incidence (461·41 per 100,000), Europe led CVD mortality (419·62), and males had higher CVD deaths (258·55 vs 233·41). Projections estimate 75·5 million deaths and 2·44 billion DALYs by 2050, driven by CVDs (86·1% of deaths). Metabolic risks like hypertension dominated CVD burdens. Conclusions The NCD burden’s rapid rise, marked disparities, and projected escalation demand urgent, equity-focused prevention. Tailored strategies, targeting metabolic risks, gender gaps, and regional inequities, are critical to achieve SDG 3.4 and mitigate this global crisis by 2050.

Efficient perovskite/Cu(In,Ga)Se2 tandem solar cells with a composite intermediate recombination layer

Abstract Monolithic perovskite/Cu(In,Ga)Se 2 (CIGS) tandem solar cells offer unique advantages among tandem configurations, including optimal bandgap pairing, all-thin-film architecture, superior radiation hardness, and exceptional stability. Despite their potential, challenges remain in optimizing efficiency and stability, particularly in the intermediate recombination layer (IRL) that connects subcells. This study addresses these challenges by developing a high-performance IRL using a composite structure comprising Al:ZnO/Au/NiO x /[4-(7H-dibenzo[c,g]carbazol-7-yl)butyl] phosphonic acid (4PADCB). The hybrid NiO x /4PADCB hole transport layer enhances interface trap passivation, optimizes band alignment, and improves minority carrier extraction, while the ultrathin Au layer significantly boosts the majority carrier recombination rate. With well-engineered subcells, our champion perovskite/CIGS tandem device achieved a record PCE of 28.04% at 0.51 cm 2 area and 30.71% at 0.15 cm 2 area (30.1% cross-verified by an external organization), with an exceptional fill factor of 80.9%, alongside outstanding photo- and thermal-stability. This work establishes monolithic perovskite/CIGS tandems as competitive with leading perovskite/Si (34.9%) and perovskite/perovskite (30.1%) technologies, providing a scalable, versatile framework for next-generation photovoltaics.