Category: Nevin Manimala

Pest Manag Sci. 2026 Jun 3. doi: 10.1002/ps.70987. Online ahead of print.

ABSTRACT

BACKGROUND: Migratory locusts threaten grassland productivity and transboundary biosecurity in arid Central Asia, but climate-driven changes in suitable habitats remain unclear. This study quantified the historical and future habitat suitability of Calliptamus italicus and Locusta migratoria migratoria in the China-Kazakhstan border region, identified key environmental factors linked to critical developmental periods, and analysed habitat shifts and centroid migration under future climate scenarios.

RESULTS: Model performance was high for both species (mean area under the curve/true skill statistic (AUC/TSS): 0.964/0.854 for C. italicus and 0.967/0.823 for L. migratoria migratoria). For C. italicus, eclosion-period wind speed and overwintering relative humidity were the main historical drivers, whereas future suitability was driven mainly by overwintering relative humidity and slope. Low-suitability habitat declined from 206 900 to 139 400 km² during 2000-2020, while future expansion was concentrated in Almaty, Ulytau, Tacheng, and Ili, with moderate-suitability area increasing by up to 522 000 km². For L. migratoria migratoria, eclosion-period normalized difference vegetation index (NDVI) was the main historical factor, whereas future suitability was driven mainly by wind and precipitation. Its habitat showed a stable-core-expanding-edge pattern, extending into east Kazakhstan, Abai, and Altay, with moderate- and high-suitability areas increasing by up to 469 900 and 128 700 km². Habitat centroids shifted mainly northeastward for C. italicus and northwestward for L. migratoria migratoria.

CONCLUSION: Climate change is likely to intensify habitat redistribution and transboundary invasion risk for both locusts. Integrating developmental-period environmental controls with dynamic habitat-shift analysis improves risk assessment and supports earlier warning, cross-border monitoring, and coordinated locust management. © 2026 Society of Chemical Industry.

PMID:42237061 | DOI:10.1002/ps.70987

Mem Cognit. 2026 Jun 3. doi: 10.3758/s13421-026-01901-6. Online ahead of print.

ABSTRACT

Structural priming effects within language (e.g., Bock, 1986) have guided theory and research on structural representation for several decades. Structural priming has also been observed across domains, such as from mathematics to language (e.g., Scheepers et al., 2011), suggesting highly abstract structural representation within the global cognitive system. Experiment 1 investigated how this effect is impacted by a mathematical structural prime that lacks an overt operator, as is the case with exponents. A weak numerical trend toward a math-to-language priming effect was not found to be statistically significant. Experiments 2-3 sought to replicate Scheepers et al.’s (2011) original math to language priming effects in online and in-person settings, respectively. Separately and combined, these experiments failed to yield significant math to language priming effects, despite robust sample sizes. Bayes factor estimates suggest a null effect was more likely than a priming effect in the combined dataset. These results highlight the fact that cross-domain structural priming is understudied and underspecified, leading to difficulty planning and implementing the types of studies needed to establish when and how abstract structural representations persist across cognitive domains. Recommendations for future research include increasing item numbers and exploring methodologies that measure processing as well as behavioral responses.

PMID:42237051 | DOI:10.3758/s13421-026-01901-6

Eur Spine J. 2026 Jun 4. doi: 10.1007/s00586-026-10039-7. Online ahead of print.

ABSTRACT

BACKGROUND: Clinical manifestations of aging spine, such as lumbar spinal stenosis, intervertebral disc degeneration, osteoporosis and sciatica, frequently co-occur, yet their shared genetic basis remains unclear.

METHODS: We assembled large-scale GWAS summary statistics for telomere length, osteoporosis, intervertebral disc degeneration, lumbar spinal stenosis and sciatica, and applied Genomic structural equation modelling to model their SNP-based heritability and genetic covariance structure. A latent aging spine factor was fitted to capture common genetic liability, followed by mvGWAS of the factor, fine-mapping, MAGMA, SCCA-TWAS with FOCUS, pathway, cell-type and functional enrichment analysis.

RESULTS: All five traits showed non zero SNP based heritability and a coherent pattern of genetic covariance, and were well summarized by a single latent aging spine factor that loaded most strongly on lumbar spinal stenosis, sciatica and intervertebral disc degeneration. GWAS of this factor identified 273 independent lead variants, and fine mapping highlighted a focused set of putatively causal SNPs, such as rs61981103, rs111736973 and rs963278. Integrative TWAS and MAGMA analysis converged on susceptibility genes such as LRRC34, MYNN, SAMHD1 and EEF1A2. Enrichment analysis consistently implicated telomere biology, chromosome maintenance and genomic stability pathways.

CONCLUSIONS: These findings support the aging spine as a biologically meaningful construct with a shared genetic basis, and provide an initial map of its polygenic architecture that extends previous single-trait studies.

PMID:42237046 | DOI:10.1007/s00586-026-10039-7

World J Pediatr. 2026 Jun 3. doi: 10.1007/s12519-026-01046-1. Online ahead of print.

ABSTRACT

BACKGROUND: Screen viewing time is associated with children’s academic and cognitive outcomes, but longitudinal studies are scarce, hindering identification of the most sensitive age periods. We assessed the associations of single and cumulative average screen viewing time with academic performance and working memory.

METHODS: In the Growing Up in Singapore Towards healthy Outcomes birth cohort, parents reported their child’s screen viewing time at ages 1, 1.5, 2, 3, 6 and 8 years. At ages 9 and 10.5, trained psychologists assessed academic performance (Wechsler Individual Achievement Test-Third Edition) and working memory (Letter-Number Sequencing task; Wechsler Intelligence Scale for Children-Fifth Edition). Associations of single and cumulative average screen viewing time with psychological outcomes were examined by multivariable linear regression (N = 502 children).

RESULTS: Mean (standard deviation) screen viewing time ranged from 2.1 (2.0) hours/day at age 1 year, to 3.0 (2.2) hours/day at 8 years. In unadjusted models, higher screen viewing time from age 1 to 8 years was consistently associated with poorer academic performance at age 9 years and working memory at 10.5 years. After adjustment, effect sizes were reduced, but higher screen viewing time at ages 1 year [β = – 1.47, 95% confidence interval (CI): – 2.37 to – 0.57 standard points per additional hour per day], 1.5 years (β = – 0.95, 95% CI: – 1.85 to – 0.06), and 6 years (β = – 0.88, 95% CI: – 1.55 to – 0.21) had persisting associations with poorer academic performance at age 9 years. Greater screen viewing time at ages 1 year (β = – 1.12, 95% CI: – 2.07 to – 0.17) and 6 years (β = – 1.01, 95% CI: – 1.71 to – 0.31) was associated with poorer working memory at age 10.5 years. Cumulative average exposure models showed that screen viewing time over childhood was consistently associated with poorer academic performance but not working memory.

CONCLUSION: In this longitudinal study, cumulative average screen viewing time was associated with lower academic performance but not working memory, with the strongest effect sizes seen for single screen viewing time occurring in early infancy.

PMID:42237043 | DOI:10.1007/s12519-026-01046-1

Eye (Lond). 2026 Jun 3. doi: 10.1038/s41433-026-04575-1. Online ahead of print.

ABSTRACT

BACKGROUND/OBJECTIVES: Our previous validation studies indicated that automated best corrected visual acuity (BCVA) testing using the DigiVis web application is comparable to standard testing. Here, we evaluate real-world experience of digital BCVA self-testing (DVA) and remote consultation (RC) in a paediatric ophthalmology service.

METHODS: Electronic records of children assigned follow up RC with home DVA testing for their routine clinical care between March 2021 and October 2024 were reviewed. Demographic and clinical features, test duration and usability scores were analysed. Serial BCVA and DVA results were compared using Bland Altman statistical methods. Clinical outcomes and service adaptations were assessed.

RESULTS: 205 RC appointments with DVA testing were scheduled for children (aged 4-14, median 6 years). DVA results were available for 192 (93.7%) RCs, with 166 (86.5%) tests undertaken without clinical supervision. The mean bias between serial BCVA and DVA was 0.005 logMAR (p < 0.001) with upper and lower limits of agreement of +0.182 (95%CI: 0.169 to 0.195) and -0.173 (-0.186 to -0.160) logMAR respectively. Expedited follow-up face-to-face consultations (f2fC) were arranged for 13 families unwilling or unable to self-test, 5 children with poor concentration and 9 with self-detected deterioration of BCVA. Informative DVA results were available for 187 (91.2%) encounters. 116 (81.7%) of 142 families voluntarily completing Likert scoring rated the application good/excellent.

CONCLUSION: In this real-world evaluation, 91.2% of offered DVA tests were informative and contributed to clinical decision making. DVA correctly identified unexpected deterioration in 9 children supporting the utility of this innovative service model.

PMID:42237023 | DOI:10.1038/s41433-026-04575-1

Dig Dis Sci. 2026 Jun 3. doi: 10.1007/s10620-026-10014-8. Online ahead of print.

ABSTRACT

BACKGROUND: Circulating tumor DNA (ctDNA)-based minimal residual disease (MRD) is an emerging biomarker, but its utility in resectable gastric cancer remains incompletely characterized.

METHODS: We conducted a systematic review and meta-analysis of eight studies (520 patients) to evaluate the prognostic value of ctDNA-based MRD for recurrence-free survival (RFS) and overall survival (OS) in resectable gastric cancer.

RESULTS: In localized resectable gastric cancer (Stage I-III), the setting in which postoperative ctDNA most coherently represents true molecular residual disease after curative-intent surgery, postoperative ctDNA positivity was associated with diminished recurrence-free survival (RFS: HR 12.26, 95% CI 3.30-45.52) and overall survival (OS: HR 8.57, 95% CI 3.06-23.98). The test for subgroup differences between localized and mixed-stage cohorts was not statistically significant (P = 0.57), and the numerically higher HR in the localized subgroup should therefore not be interpreted as evidence of a quantitatively stronger prognostic effect. Postoperative ctDNA detection demonstrated substantially stronger prognostic value (overall RFS: HR 10.00, 95% CI 4.53-22.10) compared to preoperative assessment (HR 2.17, 95% CI 1.10-4.28). Both tumor-informed and tumor-agnostic strategies effectively stratified high-risk patients. However, these effect sizes should be interpreted cautiously given the small number of studies and substantial heterogeneity (I² = 65-72%). Results from mixed-stage cohorts including Stage IV disease are supportive but should not be considered equivalent to localized-disease findings, as ctDNA in metastatic disease reflects persistent systemic burden rather than minimal residual disease in the postoperative sense.

CONCLUSIONS: Postoperative ctDNA-based MRD shows a consistent adverse prognostic association in resectable gastric cancer, with localized disease (Stage I-III) representing the most biologically and clinically coherent setting for interpretation. However, the large pooled hazard ratios (HR 10.00-12.26) should be interpreted as a directionally consistent signal rather than precise quantitative estimates, given the small number of studies, wide confidence intervals, and substantial heterogeneity (I² = 65-73%). This heterogeneity is largely driven by substantial variation in postoperative sampling timing (4 days to 16 weeks) and ctDNA assay characteristics (platform, sensitivity, coverage, variant filtering, and positivity thresholds), which require standardization in future studies. While ctDNA is prognostically valuable, its clinical utility remains unestablished. Prospective randomized trials are needed to determine whether ctDNA-guided strategies improve patient outcomes before routine clinical implementation can be recommended.

PMID:42236991 | DOI:10.1007/s10620-026-10014-8

Sci Rep. 2026 Jun 3. doi: 10.1038/s41598-026-56432-6. Online ahead of print.

ABSTRACT

Pulmonary hypertension (PH) is a heterogeneous condition with variable prognosis across World Health Organization (WHO) subtypes. The fasting blood glucose to high-density lipoprotein cholesterol (FBG/HDL-C) ratio has been suggested as a metabolic predictor of adverse outcomes in critically ill patients, but its prognostic value in PH remains unclear. This retrospective cohort included 281 ICU patients with pulmonary hypertension (PH) from MIMIC-IV (2008-2022). Patients were divided into tertiles based on ln(1 + FBG/HDL-C). The primary endpoint was 90-day all-cause mortality, which was assessed using Cox proportional hazards regression, with exploratory subgroup analyses by WHO PH groups. In fully adjusted models, patients in the highest tertile of ln(1 + FBG/HDL-C) had higher 90-day mortality than those in the lowest tertile (HR = 3.30, 95% CI: 1.82, 5.97; p < 0.001). Elevated risk was observed across WHO PH Groups 1, 2, and 5, with the most statistically robust and clinically interpretable association in Group 2 (HR = 2.66, 95% CI: 1.40, 5.05; p = 0.003). Elevated FBG/HDL-C ratio was independently associated with 90-day mortality, with the association in Group 2 being the most statistically stable and clinically interpretable.

PMID:42236962 | DOI:10.1038/s41598-026-56432-6

Sci Rep. 2026 Jun 3. doi: 10.1038/s41598-026-55978-9. Online ahead of print.

ABSTRACT

Floods remain one of the most destructive natural hazards, causing extensive loss of life and infrastructure, largely due to delayed warnings generated by conventional threshold-based monitoring systems. Such systems are inherently reactive and fail to account for evolving hydrological behaviour driven by complex interactions among environmental variables. To address these limitations, this study proposes an unsupervised, explainable anomaly-detection framework for early flood warning using multivariate time-series data from Digital Water Level Recorder (DWLR) sensors. The proposed approach utilises sliding-window temporal modelling and an LSTM autoencoder to learn normal hydrological patterns from water-level, rainfall, temperature, pH, and dissolved-oxygen measurements, without requiring labelled events. Anomalies are identified through reconstruction error and statistically grounded thresholding, enabling proactive detection of abnormal system behaviour. To enhance transparency and trust, Integrated Gradients-based explainability is incorporated to quantify feature- and time-wise contributions to detected anomalies. Experimental results on real-world DWLR data demonstrate that the framework consistently identifies anomalous behaviour several weeks before critical water-level exceedance, providing meaningful early warning signals. Explainability analysis reveals that anomalies often originate from chemical and environmental factors, such as changes in pH and dissolved oxygen, before an observable water-level rise. The proposed framework offers a robust, interpretable, and data-driven solution for smart flood monitoring systems, supporting informed decision-making and improved disaster preparedness.

PMID:42236952 | DOI:10.1038/s41598-026-55978-9

Nat Med. 2026 Jun 3. doi: 10.1038/s41591-026-04381-y. Online ahead of print.

ABSTRACT

The world has made progress in increasing the number of births attended by skilled health personnel (SHP), but maternal and neonatal mortality have not declined proportionately. This may indicate that quality of care has not risen at the same rate as SHP coverage. Several ‘Exemplar’ countries have been previously recognized for outstanding progress in improving maternal and newborn health, and offer a unique opportunity to understand coverage and quality of care provided by SHP. Here we describe quality of care and how it compares with SHP coverage in three Exemplar countries-Nepal, Senegal and Zambia. We developed a conceptual framework, compiled primary and secondary data, and employed latent variable analysis. We combined quality estimates with coverage estimates to quantify the effective coverage of SHP. Results show that effective SHP coverage ranges between 12% and 43% across subnational regions, compared with crude SHP coverage ranging from 30% to 100%, indicating that mothers and newborns are receiving less lifesaving care than coverage statistics portray. The detection of this quality gap in Exemplar settings, which represent some of the highest-performing health systems among low- and middle-income countries, emphasizes the criticality of quality care to reduce maternal and neonatal mortality worldwide.

PMID:42236909 | DOI:10.1038/s41591-026-04381-y

Sci Rep. 2026 Jun 3. doi: 10.1038/s41598-026-56107-2. Online ahead of print.

ABSTRACT

Artificial intelligence is increasingly used in Life Sciences, though the pace and direction of adoption varies widely across countries. To map the Greek landscape, we performed a data‑driven analysis of 916,824 AI-related life-science papers harvested from OpenAlex and PubMed. We tagged each publication with Medical Subject Headings (MeSH) and compared topic frequencies between articles linked to at least one Greek institution and the rest of the world. Greek‑affiliated outputs are disproportionately concentrated under the theme of methodology and algorithm‑development, whereas the global corpus is dominated by disease‑focused, organism‑centered and clinical applications. Statistical contrasts across three MeSH hierarchy levels exposed clear national strengths in machine learning techniques and analytical tools, alongside under‑representation in translational, patient‑centred research. Overall this study combines bibliometric evidence with community perspectives and provides a comprehensive overview of AI activity in Life Sciences in Greece, highlighting potential thematic strengths and gaps.

PMID:42236907 | DOI:10.1038/s41598-026-56107-2