Nevin Manimala

Sci Rep. 2025 Dec 15;15(1):43843. doi: 10.1038/s41598-025-29026-x.

ABSTRACT

Iran, located in arid and semi-arid regions, has faced significant weather and climate extremes in recent years. This study aims to investigate the climate-related hazards associated with precipitation and temperature in Iran during the Hindcast period (1991-2019) and the Forecast period (2023-2028) using the Near-term Climate Prediction (NTCP) project. We investigate compounding climate-related hazards to assess the severity and importance of weather and climate extremes. To accomplish this, we integrated ten climate extreme indices, namely heavy precipitation (R10mm), the Simple Precipitation Intensity Index (SDII), heat wave frequency (HWF), heat wave duration (HWD), cold wave frequency (CWF), and cold wave duration (CWD), along with the Standardized Precipitation Evapotranspiration Index (SPEI-12), which further encapsulates drought frequency (DF), drought duration (DD), drought severity (DS), and drought intensity (DI). The CMIP6-DCPP models effectively simulate climate extremes and their seasonal cycle across Iran, with minor discrepancies in arid and mountainous regions due to data limitations. The result demonstrates a significant anticipated rise in drought frequency and heat wave events throughout the country within the near-term forecast period. Future projections indicate a shift in precipitation patterns, with increased heavy precipitation in the Zagros Mountains and southwest regions alongside more frequent but less intense droughts nationwide. Heat wave frequency and duration are projected to increase, particularly in southern Zagros and eastern and western Iran, with high-altitude areas experiencing accelerated warming. The results project a shift in climate risk distribution over the next decade, with low to moderate-risk areas decreasing by approximately 15.7% and high-risk areas increasing by roughly 10%, encompassing over 36% of Iran’s total area by 2028. Integrated risk maps reveal high to very high compound climate hazard levels across large parts of Iran, necessitating urgent adaptation planning, especially in western, southern Zagros, and eastern regions. Sensitivity analysis confirms that identified multi-hazard hotspots in Iran are spatially robust and statistically significant, reflecting the dominant influence of key climatic extremes.

PMID:41398423 | DOI:10.1038/s41598-025-29026-x

Sci Rep. 2025 Dec 15;15(1):43767. doi: 10.1038/s41598-025-27583-9.

ABSTRACT

This study models oxygen-transfer efficiency (OTE) in circular solid-jet aerators using a laboratory dataset of 320 observations collected under controlled conditions. Experiments varied jet count (1-8), opening area (49.24-124.03 mm²), jet length (170-470 mm), and discharge (1.05-3.04 l s⁻¹); dissolved oxygen was measured, and OTE was computed and standardized to 20 °C. Five regressors-Linear Regression (LR), M5P, Random Tree (RT), Reduced Error Pruning (REP) Tree, and Random Forest (RF)-were trained with a 70/30 train-test split and evaluated using CC, RMSE, MAE, NSE, and SI. Residual histograms with kernel-density overlays and an uncertainty summary (U95, bounds) indicated compact, slightly negative-centered errors for the tree-based models and broader, heavy-tailed errors for LR; a Taylor diagram and a Spearman heatmap supported these patterns. Among all models, RF achieved the highest test performance and the lowest errors, with results statistically superior to alternatives by paired t-tests on residuals (α = 0.05); the Spearman heatmap also showed the strongest concordance between RF predictions and observations, while a leave-one-input-out sensitivity analysis identified discharge (Q) as the dominant driver. Taken together, the results identify RF as the most accurate and generalizable predictor across the tested operating envelope, providing a practical basis for the design and optimization of aeration systems in water and wastewater treatment.

PMID:41398418 | DOI:10.1038/s41598-025-27583-9

Sci Rep. 2025 Dec 15. doi: 10.1038/s41598-025-32422-y. Online ahead of print.

ABSTRACT

Neurofibromatosis type 1 (OMIM 613,113, NF1) is a neurocutaneous disorder caused by pathogenic genetic alteration in NF1 gene, which exhibits nearly full penetrance and affects multiple systems. Previously two association studies of optic pathway glioma and NF1 protein domains, derived from 215 and 381 patients, respectively, obtained contradicting results, reflecting different datasets can lead to different conclusions and there is a need for a larger dataset to reach a solid conclusion. There is another association study based on 832 patients considering protein domains, clinical features, and types of variants. But it only investigated the GTPase-activating protein domain and non-truncating variants. In this study, an extended association analysis involving eight protein domains, two types of variants, namely truncating and non-truncating variants, and 32 clinical features, was performed based on a combined dataset of 1663 NF1 patients consisting of 738 cases recruited in Hong Kong and 925 reported cases from 25 studies. In summary, this study has identified 121 statistically significant associations between clinical features, types of variants, and protein domains, with 120 of them being novel findings. These new insights about the genotype-phenotype association promote better clinical management.

PMID:41398366 | DOI:10.1038/s41598-025-32422-y

Sci Rep. 2025 Dec 16. doi: 10.1038/s41598-025-31435-x. Online ahead of print.

ABSTRACT

Ulcerative colitis (UC) is a chronic inflammatory disease of the colon, associated with gut microbiota dysbiosis. While global studies have explored this link, region-specific microbial profiles remain underreported. This pilot study aimed to characterize and compare, for the first time, the gut microbiota of Lebanese UC patients and healthy controls using 16 S rRNA gene sequencing (V3-V4 region). Fecal samples from 11 UC patients and 11 healthy individuals were analyzed. Alpha and beta diversity metrics were computed, and gut microbial composition was assessed across taxonomic levels. Statistical comparisons used Mann-Whitney and Fisher’s exact tests. UC patients showed significantly reduced microbial diversity based on Faith’s Phylogenetic Diversity and Shannon index (p < 0.05), though evenness was unaffected. Beta diversity also revealed significant group-level dissimilarities (p < 0.05). At the phylum level, Bacteroidota was elevated in UC, while Bacillota and Actinomycetota were reduced. Genera such as Ruminococcus, Bacteroides, and Coprococcus were depleted in UC. Faecalibacterium, commonly reduced in UC, showed no significant difference. This first analysis of gut microbiota in Lebanese UC patients reveals a distinct microbial signature that partially diverges from global trends, supporting the need for region-specific microbiome studies and personalized microbiota-targeted therapies.

PMID:41398357 | DOI:10.1038/s41598-025-31435-x

Sci Rep. 2025 Dec 15. doi: 10.1038/s41598-025-29387-3. Online ahead of print.

ABSTRACT

Individual recognition is fundamental to the social behaviour of many animals. In the context of territorial behaviour, animals in high-density populations encounter conspecific rivals and potential mates more frequently, which should enhance the individuality of territorial signals to facilitate recognition among conspecifics. We investigated vocal individuality in male territorial calls of two populations of little owls (Athene noctua) with different densities. Further, to explore the potential influence of local population distribution on individuality, we also examined isolated males without neighbours and clumped males with neighbours. Our findings indicate higher individuality at higher densities across both scenarios, measured using two individuality metrics: Beecher’s information statistic and Discrimination score. Clumped males exhibited significantly lower acoustic niche overlaps (i.e. higher vocal individuality) compared to isolated males. However, only a non-significant trend for lower acoustic niche overlaps (i.e. higher vocal individuality) was found for males from high density compared to low density populations. This suggests that the immediate social environment might be more influential than larger-scale population density patterns. This study suggests that vocal individuality in a territorial species is influenced by conspecific density, similar to findings in group-living and colonial species.

PMID:41398350 | DOI:10.1038/s41598-025-29387-3

Sci Rep. 2025 Dec 15. doi: 10.1038/s41598-025-31836-y. Online ahead of print.

ABSTRACT

Childhood obesity is a major public health problem, affecting one in 5 youths. We aimed to characterize biomarkers for pediatric obesity among circulating proteins using Mendelian randomization (MR). We utilized genome-wide significant cis-protein quantitative trait loci (pQTL) from three large adult proteomic GWAS (N total>58,000) and a small childhood proteomic GWAS (N=2,147) as genetic instruments for circulating protein levels. Using two-sample Mendelian randomization, we estimated causal effects of the circulating proteins on childhood body mass index (BMI) in a European GWAS of 39,620 children. MR Wald ratios were calculated to estimate the causal effect of each protein on childhood BMI. Sensitivity analyses testing the MR assumptions included colocalization and phenome-wide association studies (PheWAS). Replication was conducted using independent GWAS datasets, complemented by reverse MR and tissue enrichment analyses. Among 535 tested proteins, three colocalized and demonstrated decreasing effects on BMI per standard deviation increase in their level: endoglin (ENG; MR beta: -0.07, 95% CI [-0.10, -0.04], P=4.4×10⁻⁵), fatty acid binding protein 4 (FABP4; MR beta: -0.33, 95% CI [-0.50, -0.16], P=1.3×10⁻⁴), and cell adhesion molecule 1 (CADMI1; MR beta: -0.26, 95% CI [-0.37, -0.15], P=5.45×10⁻⁵). All three proteins showed evidence of colocalization (posterior probability >75%) and were identified using adult proteomic GWAS, given a limited statistical power using the pediatric proteomic GWAS data. Reverse causation was identified for FABP4, suggesting a compensatory mechanism. In conclusion, we identified three circulating proteins as potential blood biomarkers or drug targets for pediatric obesity, warranting further functional validation to elucidate biological mechanisms and assess therapeutic potential.

PMID:41398348 | DOI:10.1038/s41598-025-31836-y

Sci Rep. 2025 Dec 15;15(1):43856. doi: 10.1038/s41598-025-28433-4.

ABSTRACT

Students’ mental health in the context of emotional learning is essential to their academic and personal development. Emotional learning affects students’ emotional intelligence, social support, psychological capital, and educational environment. Emotions significantly impact learning, academic achievement, and overall well-being. Thus, students’ emotional needs must be met, and supportive learning environments must be created. This study examined the impact of emotional learning on student outcomes at the nexus of behavior, technological acceptance, mental well-being, cognitive engagement, and psychological resilience. This research was conducted using a convenience sampling technique across 10 major cities in nine provinces of China. A total of 5,313 students, comprising 2,633 males and 2,680 females, participated, and the data were analyzed using SmartPLS 3.2.9 to assess the relationships between key constructs. Out of the 11 direct correlations, 10 were confirmed with statistical significance (H1: t > 26.769, p < 0.000; H2: t > 25.226, p < 0.000; H3: t > 15.656, p < 0.000; H5: t > 11.334, p < 0.000; H6: t > 231.784 p < 0.000; H7: t > 34.375, p < 0.000; H8: t > 17.719 p < 0.000; H9: t > 19.060, p < 0.000; H10: t > 9.235, p < 0.000; H11: t > 10.307 p < 0.000), while the correlation for the 4th hypothesis was not statistically significant (H4: t > 0.248, p < 0.804). Students’ cognitive engagement is multifaceted and influenced by their prior knowledge, cognitive load, perceived value of the learning system, and instructional practices. Establishing effective learning environments that support students’ academic success and cognitive development requires understanding and fostering cognitive engagement.

PMID:41398346 | DOI:10.1038/s41598-025-28433-4

Sci Rep. 2025 Dec 15;15(1):43742. doi: 10.1038/s41598-025-28070-x.

ABSTRACT

Alzheimer’s Disease (AD) is a very common neurodegenerative disorders and early detection using electroencephalography (EEG) can enable timely intervention, however, existing computational models often lack robustness, interpretability, and clinical scalability. This study proposes NeuroFusionNet, a hybrid deep learning framework for accurate, explainable, and efficient EEG-based classification of Alzheimer’s Disease and related dementias. The model fuses handcrafted spectral, statistical, wavelet, and entropy features with latent temporal embeddings extracted from a customized one-dimensional convolutional neural network (1D-CNN). Feature selection is performed using Pearson Correlation Coefficient (PCC) and Particle Swarm Optimization (PSO), Principal Component Analysis (PCA)-based dimensionality reduction, and SMOTE-based class balancing has been performed to enhance discriminative learning. Comprehensive preprocessing including bandpass filtering, Artifact Subspace Reconstruction (ASR), and Independent Component Analysis (ICA) improves signal quality prior to classification through a five-layer deep neural network optimized via adaptive learning rate scheduling. Proposed method has been validated on three public EEG datasets including OpenNeuro ds004504 (eyes-closed), ds006036 (eyes-open), and the independent OSF dataset. Our method demonstrates state-of-the-art accuracy and macro F-1 score of 94.27% and 0.94 respectively. Cross-validation yielded minimal variance (SD <0.3%) that confirms the robustness and reproducibility. Model interpretability was ensured using Shapley Additive Explanations (SHAP) and Gradient-weighted Class Activation Mapping (Grad-CAM), which revealed physiologically consistent biomarkers such as posterior alpha attenuation and frontal-theta enhancement patterns well aligned with established AD pathophysiology. Demographic fairness analysis showed negligible bias (<0.6% difference) across gender and age subgroups. Despite its high accuracy, NeuroFusionNet remains lightweight (0.94M parameters, 4.1 MB footprint) and computationally efficient (6.5 ms inference per sample), enabling real-time deployment on standard clinical CPUs without GPU support.

PMID:41398345 | DOI:10.1038/s41598-025-28070-x

Gerontol Geriatr Educ. 2025 Dec 15:1-15. doi: 10.1080/02701960.2025.2603237. Online ahead of print.

ABSTRACT

This study aims to investigate high school students’ attitudes toward ageism within the context of intergenerational conflict and to examine the sociodemographic factors associated with these attitudes and experiences. A total of 406 high school students from five different school types in Turkey participated in the study. Data were collected using a Personal Information Form, the Assessment of Conflict with Elderly People (ACE), and the Fraboni Ageism Scale (FSA). Group comparisons and correlation analyses were conducted to explore the relationships between key variables, including school type, family structure, maternal education level, co-residence with older adults, and willingness to live with parents in the future. Participants generally exhibited positive attitudes toward older adults. A significant negative correlation was found between levels of intergenerational conflict and levels of ageism (r = -0.398, p < .001), suggesting that students who reported lower levels of conflict with older adults also held more positive attitudes toward them. Levels of ageism differed significantly based on school type, family structure, maternal education, prior co-residence with older adults, and intentions for future cohabitation with parents. In contrast, none of these variables had a statistically significant impact on levels of intergenerational conflict. The findings suggest that while adolescents’ attitudes toward older adults are shaped by sociodemographic and familial variables, their perceived intergenerational conflict may arise from other contextual or relational dynamics. This discrepancy highlights the need for targeted interventions to foster intergenerational empathy and communication. The study provides original insights into age-related attitudes among adolescents in a non-Western context and contributes to the broader literature on ageism and intergenerational relations.

PMID:41398341 | DOI:10.1080/02701960.2025.2603237

Sci Rep. 2025 Dec 15;15(1):43743. doi: 10.1038/s41598-025-28695-y.

ABSTRACT

This paper proposes a novel multiplicative logistic map derived from the rule of multiplicative calculus and introduces an additional parametric freedom that fundamentally extends its dynamical capabilities. The theoretical and numerical analysis confirm that this map undergoes a period-doubling bifurcation cascade into chaos as rigorously validated by stability analysis, bifurcation diagrams, transversality conditions and stability conditions. Crucially, compared to the classical logistic map, it exhibits a significantly broader chaotic region and an expanded output range beyond [0,1]. Cobweb and time-series plots visually confirm these enhanced and complex behaviors. Moreover, owing to its greater parametric flexibility and wider chaotic dynamics, the multiplicative logistic map is a highly suitable candidate for advanced encryption applications. Experimental results and comparative analysis demonstrate that the image encryption algorithm based on the proposed map exhibits strong resistance to statistical attacks and superior parameter robustness in practical implementations.

PMID:41398336 | DOI:10.1038/s41598-025-28695-y