Nevin Manimala

J Appl Genet. 2025 Aug 20. doi: 10.1007/s13353-025-01001-2. Online ahead of print.

ABSTRACT

Senataxin, an RNA/DNA helicase, is a key protein providing genome stability and one of the best characterized R-loop-binding factors playing an important role in transcription and DNA repair processes. Pathogenic SETX gene variants cause autosomal recessive spinocerebellar ataxia with axonal neuropathy (AOA2, MIM #606002) and autosomal dominant juvenile amyotrophic lateral sclerosis (ALS4, MIM #602433), rare neurodegenerative disorders characterized by juvenile onset of progressive cerebellar ataxia, axonal sensorimotor peripheral neuropathy, combined upper and lower motor neuron symptoms, and increased serum alpha-fetoprotein (AFP; specific for AOA2). We report two cases of adult patients presenting with cerebellar syndrome, scanned speech, and exercise intolerance which started in the second/third decade of life and were followed by muscle weakness and impaired gait coordination. Whole exome sequencing (WES) was performed to analyze single nucleotide and copy number variants. A decreased coverage of a genomic region of around 16 kb on chromosome 9 (chr9:132,295,852-132,311,876), suggesting a deletion encompassing 5 exons of the SETX gene (exons 11-15, NM_015046.7) was observed. This homozygous SETX (9q34.13) deletion leads to a frame shift and consequently truncation of the helicase domain in the protein. Loss-of-function variants in the SETX gene are known to be pathogenic. Statistical analysis of NGS data from the Polish population identified a few heterozygous carriers, suggesting its region-specific origin.

PMID:40830689 | DOI:10.1007/s13353-025-01001-2

Discov Ment Health. 2025 Aug 19;5(1):127. doi: 10.1007/s44192-025-00269-4.

ABSTRACT

Mental health in childhood brings up the state of a child’s emotional and psychological well-being, encompassing their ability to navigate challenges, form relationships, and get by stressors, laying the foundation for their future mental and emotional resilience. This cross-sectional study, conducted between December 1, 2023, and February 1, 2024, intended to identify the substantial risk factors of children’s mental health (CMH) development in Bangladesh. The data were collected using two-phase sampling through a questionnaire filled out by trained interviewers. To test the normality of the dependent variable, Kolmogorov-Smirnov and Shapiro-Wilk tests were applied, and the tests confirmed the non-normality assumption (P < 0.05) of the study variables. Mann-Whitney U and Kruskal-Wallis H tests were applied as bivariate analyses, and generalized gamma regression was performed to determine the significant risk factors of mental development. The odds ratio (OR) and 95% confidence interval (CI) were the measuring parameters of the risk factors of CMH. The results revealed that early childhood disease (OR 0.9537, CI 0.93-0.97, p = 0.000769), monthly family income (OR 0.9247, CI 0.87-0.98, p = 0.015046), and providing supplementary food sometimes (OR 1.0583, CI 1.02-1.09, p = 0.001819) were significant socio-economic factors influencing CMH. Among demographic factors, gender (OR 0.9693, CI 0.94-0.99, p = 0.025684) and division (OR 1.0496, CI 1.007-1.09, p = 0.021429) showed significant associations. Additionally, child opportunities to play outside (OR 0.9451, CI 0.91-0.98, p = 0.007235), which may be shaped by cultural attitudes toward child supervision, gender roles, and norms around outdoor activity, was also found to be significantly associated with children’s mental health. The results of this study would assist policymakers to take initiatives in mental health development including the funding of interventions so that children in Bangladesh can achieve their developmental potential.

PMID:40830687 | DOI:10.1007/s44192-025-00269-4

Sci Rep. 2025 Aug 20;15(1):30486. doi: 10.1038/s41598-025-15256-6.

ABSTRACT

In the recent years, there has been a notable shift in the landscape of statistical and data science research, with increasing attention directed toward the development of advanced probability distributions aimed at addressing the challenges posed by medical and health-related data. In response to this need, the present study introduces a novel probability distribution model termed as the Exponentiated Odd Lomax Power Lindley distribution constructed by embedding the Power Lindley distribution within the Lomax family framework through the T-X transformation technique. This article delves into the application of probability distributions in medical data analysis, with a special focus on their role in understanding and managing the COVID-19 data. A comprehensive theoretical investigation is conducted, deriving key statistical properties including the probability and cumulative distribution functions, reliability functions, moments, moment generating function, order statistics, and entropy measures. To ensure accurate parameter estimation, several estimation methods are employed and rigorously compared through simulation studies. The real-world applicability of the developed distribution is illustrated through the modelling of COVID-19 datasets, where its performance is evaluated against a range of well-established probability distribution models. Empirical findings demonstrate the superior adaptability and modelling accuracy of the distribution while analysing real-world datasets.

PMID:40830631 | DOI:10.1038/s41598-025-15256-6

Sci Rep. 2025 Aug 19;15(1):30423. doi: 10.1038/s41598-025-15428-4.

ABSTRACT

High-sensitivity C-reactive protein (hs-CRP) has been associated with prognosis in acute myocardial infarction (AMI) patients, but data on its role in elderly individuals remains limited. This single-center, retrospective study included 590 elderly AMI patients, who were stratified into three groups based on hs-CRP tertiles. The incidence of adverse in-hospital events increased progressively across higher hs-CRP tertiles (17.2%, 25.5%, and 48%, P<0.001). Notably, patients who experienced these events had significantly higher hs-CRP levels compared to those without adverse outcomes (7.04 [2.38, 20.00] vs. 2.59 [1.06, 6.07], P<0.001). Multivariate logistic regression identified hs-CRP as an independent predictor of in-hospital outcomes in elderly AMI patients (Q3: OR 2.21, 95% CI 1.23-3.97, P=0.008). The area under the curve (AUC) for hs-CRP’s predictive accuracy was 0.712 (95% CI 0.664-0.755, P<0.001). Furthermore, integrating hs-CRP into an established risk factor model significantly improved both reclassification and discrimination (Continuous NRI: 0.461, 95% CI 0.292-0.631, P<0.001; IDI: 0.046, 95% CI 0.025-0.067, P<0.001), although it did not substantially enhance the C-statistic (0.867 (95% CI 0.831-0.895, P<0.001) vs. 0.876 (95% CI 0.841-0.905, P<0.001) , P=0.183). These findings suggest that hs-CRP is a reliable and practical biomarker for predicting poor prognosis in elderly patients with AMI.

PMID:40830625 | DOI:10.1038/s41598-025-15428-4

Sci Rep. 2025 Aug 20;15(1):28582. doi: 10.1038/s41598-025-10591-0.

ABSTRACT

Driven by increasing anthropogenic CO₂, the impact of ongoing climate change on the marine plankton ecosystem ultimately extends to higher trophic levels and the biogeochemical cycling of carbon and nutrients. However, the impacts of multiple environmental changes on trophic interactions between predator and prey have still not been fully explored. Here we conducted incubation experiments to determine the temperature and CO₂ sensitivities of marine phytoplankton growth and microzooplankton grazing in the western Arctic Ocean, where rapid climate change is taking place. The temperature sensitivity of the growth of larger phytoplankton decreased owing to the increase in CO₂ levels, whereas that of the growth of smaller phytoplankton increased under higher CO₂ levels. Notably, the temperature sensitivity of Arctic phytoplankton is at least two times higher than the canonical estimates irrespective of size classes, highlighting the uniqueness of the Arctic ecosystem’s response to warming. Microzooplankton grazing was closely coupled with, but did not exceed, the growth rates of their prey, suggesting that microzooplankton behavior is mainly regulated by prey availability rather than the ambient environment. The higher competitiveness of smaller phytoplankton under higher temperatures and CO₂ conditions might lead to a less productive Arctic Ocean ecosystem for higher trophic-level organisms in the future.

PMID:40830618 | DOI:10.1038/s41598-025-10591-0

Environ Sci Pollut Res Int. 2025 Aug 19. doi: 10.1007/s11356-025-36815-4. Online ahead of print.

ABSTRACT

The global community faces a critical challenge as rising CO₂ emissions threaten both environmental sustainability and human well-being. The swift addressing of these issues is crucial to preserving and enhancing environmental integrity. Therefore, c from 1990 to 2022, advanced statistical methods, including multiple diagnostic tests, Panel-Corrected Standard Errors (PCSE), and Feasible Generalized Least Squares (FGLS), were employed. The findings reveal that renewable energy is pivotal in mitigating CO₂ emissions, while Fintech and industrialization also contribute to reducing emissions. Conversely, geopolitical risk is found to exacerbate CO₂ emissions. Notably, hydro energy does not significantly contribute to CO₂ emissions reduction, whereas wind and solar energy play a substantial role in the same. The study identifies unidirectional causality among the various selected variables and provides crucial policy implications for the development of renewable energy sources and the maintenance of environmental quality.

PMID:40830605 | DOI:10.1007/s11356-025-36815-4

Environ Sci Pollut Res Int. 2025 Aug 19. doi: 10.1007/s11356-025-36822-5. Online ahead of print.

ABSTRACT

Hydrological regimes are crucial for river ecosystems, which depend on flow patterns. Dams disrupt these regimes, creating variations in river systems, requiring management to analyze and assess flow changes. This study aims to assess the impact of the Shahid Kazemi Dam construction on the flow regime and environmental flow components of the Zarrineh-Roud River, a permanent river. The findings of this research can contribute to a better understanding of the changes in natural flow components influenced by river flow regulation. In this study, 33 hydrological parameters, categorized into five statistical groups, were used as indicators of hydrological change at the Sarighamish hydrometric station. The IHA software was utilized to evaluate changes in the Zarrineh River’s flow from 1955 to 2015, comparing pre- and post-dam periods. Additionally, the independent samples t-test was employed to assess river flow changes. The results showed that hydrological indices at the study station were altered due to dam construction, with some indices increasing while others decreased. The construction of the Shahid Kazemi dam has caused substantial changes in environmental flow components (EFCs) at the Sarighamish station, particularly in monthly low flows, where October low flow decreased from 20.65 to 4.2 cms. High flow pulses were also affected, with the high flow peak reducing from 65 to 56 cms, though the duration of these pulses increased significantly from 3.25 to 9.5 days, indicating prolonged high flow conditions post-dam. Significant differences in river flow components at the Sarighamish station were observed after the dam’s construction. March and April showed large increases (70.97 and 86.27), while October and July saw notable decreases (- 19.68 and – 21.38), highlighting the dam’s impact on seasonal flow patterns. To preserve the Zarrineh River’s ecological conditions, water management must regulate the Bukan Dam’s flow regime to align post-dam hydrological indices with the natural flow variation.

PMID:40830604 | DOI:10.1007/s11356-025-36822-5

Sci Rep. 2025 Aug 19;15(1):30314. doi: 10.1038/s41598-025-95302-5.

ABSTRACT

Availability of a dependable electricity source is essential for improving living standards. When designing a micro-grid system, two key factors must be considered: cost-effectiveness and service quality. A major challenge in hybrid system design is balancing cost and reliability. To address this, a Renewable Energy System (RES) is optimized using a hybrid PV/Wind system with a diesel generator and battery storage. A novel hybrid harbor seal jellyfish searching (HHSJS) method is introduced for system configuration and component sizing. HHSJS seeks to address the problem with the investigation of the current harbor seal whiskers optimization algorithm (HSWOA). A temporal control technique is used to switch between JS and HSWOA operators throughout the search operation. The effectiveness of HHSJS is tested using 50 benchmark functions. Recent hourly wind speed data from two meteorological stations in Egypt: the Northwest Coast area and the New Valley Governorate. Despite the complexity of RES design, the optimal component sizing has been effectively determined for each location using HHSJS. This suggests that RES can be a viable solution for electrification projects, improving energy access in remote Egyptian regions and other developing areas with similar climates.

PMID:40830601 | DOI:10.1038/s41598-025-95302-5

Sci Rep. 2025 Aug 19;15(1):30462. doi: 10.1038/s41598-025-16587-0.

ABSTRACT

Composites reinforced with natural fibers are increasingly progressively in diverse engineering practices for their remarkable attributes, including weight reduction, high strength, cost-efficiency, biodegradability, and renewability. This research explores the mechanical attributes of epoxy composites fortified with jute fiber and alumina. Employing Response Surface Methodology (RSM) with a three-factor, three-level design, the research examines independent variables including orientation (A), size of particle (S), and weight% of particle (W) to optimize process parameters for these composites. It evaluates how these variables influence mechanical properties such as tensile strength, tensile modulus, flexural strength, flexural modulus, and water absorption capacity, aiming to enhance composite performance both economically and effectively. The combination of 0/90° fiber orientation, 106-micron particle size, and 8% weight fraction yields composites with optimized flexural and tensile properties. It is critical to effectively and affordably enhance artificial intelligence tools to establish sound mechanical properties. The Jaya algorithm, developed based on Grey-ANFIS, is utilized for process optimization, applying grey theory to establish a multi-performance index that is rigorously assessed through statistical error analysis. Based on experimental results, the study identifies optimal process variable combinations that ensure superior and enhanced multi-performance characteristics in the fabricated composites.

PMID:40830582 | DOI:10.1038/s41598-025-16587-0

Mol Psychiatry. 2025 Aug 19. doi: 10.1038/s41380-025-03155-1. Online ahead of print.

ABSTRACT

Anxiety disorders, including social anxiety disorder (SAD), generalized anxiety disorder (GAD), panic disorder (PD), agoraphobia (AG), and specific phobia (SP), are characterized by core features of excessive anxiety and fear. Furthermore, these disorders are often accompanied by avoidance behaviors. While avoidance is a common behavioral response, it may be a consequence of or a cocontributor to the anxiety and fear driving these disorders. This narrative review integrates the interactions among anxiety, fear, and avoidance behaviors across these five disorders and synthesizes findings from clinical, neuropsychological, brain function, treatment, genetic, and epigenetic studies. Based on the intensity of anxiety and fear, these anxiety five disorders can be categorized into three groups: fear-dominant (SP, AG), mixed (PD, SAD), and anxiety-dominant (GAD). The intensity of avoidance behaviors is related to the age of onset. Each group responds to different treatment approaches. In fear-dominant disorders, exposure therapy is highly effective in reducing avoidance behaviors and fear responses. Cognitive behavioral therapy (CBT) with an emphasis on exposure is useful. In the mixed group, CBT is the preferred treatment, with a focus on both exposure therapy and cognitive restructuring. In addition to CBT, selective serotonin and serotonin-norepinephrine reuptake inhibitors (SSRIs/SNRIs) are commonly used to reduce anticipatory anxiety and fear symptoms. In anxiety-dominant disorders, both SSRIs/SNRIs and CBT with an emphasis on cognitive restructuring are effective for managing chronic worry. Anxiety and fear are regulated by distinct but interacting neurobiological mechanisms, with the amygdala central to fear processing and the hypothalamic‒pituitary‒adrenal axis involved in chronic anxiety regulation. Genetic and epigenetic studies demonstrate substantial heritability across anxiety disorders, with varying degrees of genetic influence on anxiety, fear, and avoidance. Avoidance behaviors, particularly in early-onset disorders such as SP and SAD, may be more strongly influenced by genetic factors. Large-scale genome-wide association studies (GWASs) grouping anxiety disorders have identified shared genetic loci, but GWASs for individual anxiety disorders are limited by small sample sizes. Grouping anxiety disorders into broader categories – namely, fear-dominant, mixed, and anxiety-dominant – rather than considering each specific anxiety disorder in isolation may lead to increased statistical power and yield more comprehensive perspectives on the shared and distinct clinical and genetic risk factors among anxiety disorders.

PMID:40830577 | DOI:10.1038/s41380-025-03155-1