Nevin Manimala

Commun Chem. 2025 Nov 20;8(1):364. doi: 10.1038/s42004-025-01734-5.

ABSTRACT

The peptide-centric strategy is widely applied in data-independent acquisition (DIA) proteomics to analyze multiplexed MS2 spectra. However, current software tools often rely on single-run data for peptide peak identification, leading to inconsistent quantification across heterogeneous datasets. Match-between-runs (MBR) algorithms address this by aligning peaks or elution profiles post-analysis, but they are often ad hoc and lack statistical frameworks for controlling peak quality, causing false positives and reduced quantitative reproducibility. Here we present DreamDIAlignR, a cross-run peptide-centric tool that integrates peptide elution behavior across runs with a deep learning peak identifier and alignment algorithm for consistent peak picking and FDR-controlled scoring. DreamDIAlignR outperformed state-of-the-art MBR methods, identifying up to 21.2% more quantitatively changing proteins in a benchmark dataset and 36.6% more in a cancer dataset. Additionally, DreamDIAlignR establishes an improved methodology for performing MBR compatible with existing DIA analysis tools, thereby enhancing the overall quality of DIA analysis.

PMID:41266840 | DOI:10.1038/s42004-025-01734-5

Environ Geochem Health. 2025 Nov 20;48(1):9. doi: 10.1007/s10653-025-02882-2.

ABSTRACT

Coal-fired thermal power plant operations significantly impact aquatic environments by releasing fly ash leachate, untreated effluents, and airborne pollutants, thereby deteriorating surface water quality. This study assesses the spatial distribution, pollution load, and ecological risk of potentially toxic elements (PTEs) in surface water collected from the surroundings of coal-based thermal power plant (TPP) in Andhra Pradesh, India. Jupudi Reservoir (JR) showed relatively lower pH levels, indicating mildly acidic conditions possibly resulting from ash pond leachate influence, while the other water bodies maintained a more alkaline nature. The mean concentrations of Chromium (406 µg/L) and Arsenic (214 µg/L) were highest at JR and comparatively elevated relative to other water bodies. Furthermore, the total metal load was significantly higher in JR, TPP, and RC across water, sediment, and plant samples, reflecting the significant influence of coal-based thermal power plant activities on these aquatic ecosystems. Geospatial distribution using ArcGIS-IDW interpolation revealed contamination hotspots near coal ash discharge zones, especially at JR and TPP canal sites. Pollution indices highlighted severe pollution and ecological threats at JR and TPP, with ERI values indicating high ecological risk (> 400). Health risk assessments showed that children are particularly at risk, with elevated non-carcinogenic hazard index (HI > 1) and incremental lifetime cancer risk (ILCR > 1 × 10⁻⁴) through both ingestion and dermal pathways. Among the studied sites, JR and TPP canal exhibited the highest PTE concentrations, whereas RC served as the least contaminated reference site. statistical analyses, including Pearson correlation and Positive Matrix Factorization (PMF), identified coal combustion by-products, atmospheric deposition, and ash leachate as the dominant sources of contamination, with minor contributions from domestic and agricultural runoff. The findings underscore the urgent need for pollution control, regular monitoring, and site-specific remediation strategies to protect both ecological and human health in coal-affected aquatic systems.

PMID:41266830 | DOI:10.1007/s10653-025-02882-2

Commun Eng. 2025 Nov 20. doi: 10.1038/s44172-025-00548-6. Online ahead of print.

ABSTRACT

Accurate estimation of core body temperature (CBT) is essential for physiological monitoring, yet current non-invasive methods lack statistically calibrated uncertainty estimates required for safety-critical use. Here we introduce a conformal deep learning framework for real-time, non-invasive CBT prediction with calibrated uncertainty, demonstrated in high-risk heat-stress environments. Developed from over 140,000 physiological measurements across six operational domains, the model achieves a test error of 0.29 °C, outperforming the widely used ECTemp™ algorithm with a 12-fold improvement in calibrated probabilistic accuracy and statistically valid prediction intervals. Designed for integration with wearable devices, the system uses accessible physiological, demographic, and environmental inputs to support practical, confidence-informed monitoring. A customizable alert engine enables proactive safety interventions based on user-defined thresholds and model confidence. By combining deep learning with conformal prediction, this approach establishes a generalizable foundation for trustworthy, non-invasive physiological monitoring, demonstrated here for CBT under heat stress but applicable to broader safety-critical settings.

PMID:41266785 | DOI:10.1038/s44172-025-00548-6

Commun Med (Lond). 2025 Nov 20;5(1):488. doi: 10.1038/s43856-025-01167-0.

ABSTRACT

BACKGROUND: Mesial temporal lobe epilepsy (mTLE) is a common form of drug-resistant epilepsy and seizure outcomes after minimally invasive laser ablation remain suboptimal. Current imaging-guided strategies often fail to capture individual variability in seizure foci. This study aimed to develop a personalized neuroimaging biomarker to improve surgical planning and predict outcomes.

METHODS: Thirty patients with mTLE (16 women, 53.3%; age range 17-59 years) who underwent magnetic resonance-guided laser interstitial thermal therapy were retrospectively analyzed. The asymmetry index (AI) from [¹⁸F]fluorodeoxyglucose positron emission tomography ([¹⁸F]FDG PET) defined the personalized NeuroMetabolic Signature (pNMS). Prognostic thresholds and optimal pNMS ablative rate were explored using restricted cubic spline (RCS) analysis and Youden’s index as statistical methods for identifying cutoffs. A generalized additive model (GAM) was applied to examine imaging-derived features associated with pNMS.

RESULTS: Here we show that the AI of PET metabolic values significantly predicted seizure outcomes (odds ratio = 1.43, P = 0.02), with -0.06 as the threshold for defining pNMS (P for non-linearity = 0.04). A hippocampal pNMS ablative rate of 39.79% is significantly associated with seizure freedom (Pearson χ² = 10.16, P = 0.001; balanced accuracy = 0.83). Hippocampal atrophy contributes most to pNMS expression (Shapley value = -0.026), and correlates with metabolic asymmetry (Pearson’s r = 0.47, P < 0.01).

CONCLUSIONS: The pNMS provides an individualized imaging marker for guiding laser ablation and predicting postoperative seizure outcomes. This approach supports more precise surgical planning and may improve long-term prognosis in patients with mesial temporal lobe epilepsy.

PMID:41266775 | DOI:10.1038/s43856-025-01167-0

Commun Chem. 2025 Nov 20;8(1):362. doi: 10.1038/s42004-025-01771-0.

ABSTRACT

Quantifying the effects of point mutations is of utmost interest for pharmaceutical and biotechnological applications. Reliable computational methods range from statistical and AI-based to physics-based approaches, with the optimal balance between accurate and fast predictions remaining a challenge. Free energy perturbation (FEP) simulations, a powerful physics-based approach available for decades, constitutes nowadays a method of common application in protein mutational studies. We present QresFEP-2, a novel hybrid-topology FEP protocol benchmarked on a comprehensive protein stability dataset of 10 protein systems, encompassing almost 600 mutations. QresFEP-2 combines excellent accuracy with the highest computational efficiency among available FEP protocols, and its robustness is further validated through comprehensive domain-wide mutagenesis, assessing the thermodynamic stability of over 400 mutations generated by a systematic mutation scan of the 56-residue B1 domain of streptococcal protein G (Gβ1). We also demonstrate the applicability domain of QresFEP-2 on evaluating site-directed mutagenesis effects on protein-ligand binding, tested on a GPCR, as well as on protein-protein interactions examined on the barnase/barstar complex. QresFEP-2 emerges as an open-source, physics-based alternative for advancing protein engineering, drug design, and elucidating the impact of mutations on human health.

PMID:41266769 | DOI:10.1038/s42004-025-01771-0

Commun Med (Lond). 2025 Nov 20;5(1):487. doi: 10.1038/s43856-025-01177-y.

ABSTRACT

BACKGROUND: Glioblastoma is a malignant primary brain tumor. Because of its highly invasive and infiltrative nature, surgical resection and radiation therapy are not able to remove all tumor cells, even with state-of-the-art imaging and fluorescence-guided surgery.

METHODS: 24 newly diagnosed glioblastoma patients were enrolled. Pre- and post-surgery MRI scans were performed. Magnetic susceptibility was quantified based on gradient echo MRI. The ratio between sub-voxel paramagnetic and diamagnetic susceptibility components was computed. Relationships between the proposed ratio metric and prognostic factors and pathological iron were investigated. Perfusion and permeability imaging were used to exclude the presence of blood-related contribution to the paramagnetic component.

RESULTS: Here we show that by decomposing tissue magnetic susceptibility into paramagnetic and diamagnetic sources, we can identify, non-invasively and in vivo, areas of altered iron metabolism associated with tumor activities in the edema tissue surrounding glioblastoma. We find that the paramagnetic to diamagnetic susceptibility ratio uniquely delineates area of hyperintensity corresponding to a Tumor and Immune cells Infiltration Zone. Statistically significant relationships are found between the ratio metrics in the infiltration zone and tumor prognostic factors. Follow-up scans reveal tumor progression and later contrast-enhancement in the predicted infiltration zone. Histological data indicate that increased iron content causes the elevated ratio metric.

CONCLUSIONS: Our study proposes a method to derive an iron-related imaging marker of abnormal patterns in the edema region of the glioblastoma associated with tumor cell infiltration. We show the potential of the imaging marker to aid and improve surgical and treatment planning.

PMID:41266763 | DOI:10.1038/s43856-025-01177-y

Int J Cardiovasc Imaging. 2025 Nov 21. doi: 10.1007/s10554-025-03556-x. Online ahead of print.

ABSTRACT

PURPOSE: Exercise stress echocardiography (ExE) includes assessment of regional wall motion and EKG changes and, not uncommonly, discordant results are observed. Though stress induced wall motion abnormalities are widely considered positive for presence of ischemia, EKG-only positive studies are dismissed as equivocal/false positive, in which case, further evaluation is appropriate.

METHODS: Patients who had undergone a clinically indicated ExE and subsequent coronary CT angiogram (CCTA) within one month were identified. They were categorized based on the discordant results of the echocardiographic and electrocardiographic components of the study (EKG+/ECHO-, EKG-/ECHO+). The CCTA results were classified using CAD-RADS 2.0. CT fractional flow assessment was performed for 30-90% stenosis lesions.

RESULTS: 197 patients with discordant ExE results were identified (EKG+/ECHO- n = 159, EKG-/ECHO + n = 38). 35.2% of the EKG+/ECHO- group were classified as CAD-RADS 3 or greater (28.9% left anterior descending, 12.6% left circumflex, and 15.1% right coronary artery moderate/severe stenoses). Of the EKG-/ECHO + patients, 23.7% were classified as CAD RADS 3 or greater (15.8% left anterior descending, 5.3% left circumflex, and 10.5% right coronary artery moderate/severe stenoses). No statistically significant difference was observed between the two groups in the overall degree of coronary artery disease.

CONCLUSIONS: Discordant ExE results with ST segment depressions during exercise without regional wall motion abnormalities (EKG+/ECHO-) and discordant ExE results without ST segment changes with stress-induced regional wall motion abnormalities (EKG-/ECHO+) are both associated with a clinically relevant burden of coronary artery disease, without a statistically significant difference in the degree or severity between the two groups.

PMID:41266719 | DOI:10.1007/s10554-025-03556-x

Sci Rep. 2025 Nov 20;15(1):41093. doi: 10.1038/s41598-025-24989-3.

ABSTRACT

Endoscopic skull base surgery has transformed craniofacial treatment by reducing morbidity and enhancing precision. Traditional outcome measures often overlook the multidimensional aspects of quality of life (QoL) in recovery. Patient-reported tools, such as the anterior skull base questionnaire (ASBQ), offer a comprehensive view of QoL. However, the ASBQ’s effectiveness is limited in non-English-speaking populations without cultural adaptation. This study aims to culturally adapt and psychometrically validate the Persian version of the anterior skull base questionnaire (ASBQ-P) for patients undergoing transnasal transsphenoidal surgery. Translation and cross-cultural adaptation adhered to ISPOR guidelines, encompassing forward and backward translation, expert review, and cognitive debriefing. Internal consistency was evaluated through Cronbach’s α, and test-retest reliability was assessed using intraclass correlation coefficients (ICCs). Convergent validity was assessed using Pearson’s correlation with SNOT-22 scores, while responsiveness was evaluated through effect sizes and standardized response means. Statistical analyses were performed using SPSS version 27, with a significance threshold set at P < 0.05. A total of 36 patients completed the Persian version of the ASBQ and SNOT-22 questionnaires. The ASBQ demonstrated excellent internal consistency (Cronbach’s α = 0.936). Test-retest reliability was high, with an ICC of 0.927 for average measures. Convergent validity was supported by a significant moderate negative correlation between ASBQ and SNOT-22 scores (r=-0.544, P = 0.001). A known-groups validity analysis revealed significant differences in ASBQ scores across SNOT-22 severity categories (P = 0.001), supporting the instrument’s discriminative capacity. Our findings confirm the Persian ASBQ as a reliable and valid tool for assessing outcomes in anterior skull base surgery.

PMID:41266717 | DOI:10.1038/s41598-025-24989-3

Sci Rep. 2025 Nov 20;15(1):41029. doi: 10.1038/s41598-025-24883-y.

ABSTRACT

Perimenopause is a high-risk period for depressive symptoms in women. Investigating the urban-rural differences in key factors associated with depressive symptoms among Chinese perimenopausal women can provide a scientific basis for developing targeted intervention strategies. Using data from the 2020 wave of the China Health and Retirement Longitudinal Study (CHARLS), we employed a random forest model combined with Shapley value decomposition (a cooperative-game-theoretic approach that quantifies each variable’s marginal contribution to model accuracy), supplemented by logistic regression analysis, to systematically explore urban-rural differences in key factors influencing depressive symptoms in perimenopausal women. Among 1,105 perimenopausal women, the overall prevalence of depressive symptoms was 39.3%, with 34.4% in urban areas and 42.4% in rural areas. Life satisfaction, self-rated health, and sleep duration emerged as common factors affecting depressive symptoms in both urban and rural perimenopausal women. Chronic disease, hospitalization history, children’s financial support, and child contact were unique key factors influencing depressive symptoms in urban women. In contrast, activities of daily living (ADL), cognitive function, and total annual household income were unique key factors influencing depressive symptoms in rural women. Significant urban-rural differences exist in the key factors associated with depressive symptoms among Chinese perimenopausal women. Policy makers should therefore design context-specific mental-health programmes. for example, urban initiatives could integrate chronic-disease management with family-based psychosocial support, whereas rural programmes might combine economic-security improvements with community-level cognitive-health screening and rehabilitation of activities of daily living-to maximise intervention effectiveness.

PMID:41266681 | DOI:10.1038/s41598-025-24883-y

Lasers Med Sci. 2025 Nov 21;40(1):489. doi: 10.1007/s10103-025-04747-7.

ABSTRACT

This in vitro study aimed to evaluate the shear bond strength of four different bioactive restorative materials to dentin prepared using either a high-speed bur or Er, Cr: YSGG laser. A total of 120 extracted human molars were divided into two groups (n = 60) based on dentin surface preparation: high-speed diamond bur or Er,Cr:YSGG laser (3 W, 20 Hz, 70% H₂O, 60% air). Each group was further divided into four subgroups (n = 15) according to the restorative material: Group I-glass hybrid (EQUIA Forte HT), Group II-bioactive resin composite (Activa BioActive-Restorative), Group III-giomer (Beautifil II), and Group IV-alkasite (Cention Forte). Materials were applied per manufacturers’ instructions using a standardized Teflon mold system. After 24 h, shear bond strength was tested with a universal testing machine at 1.0 mm/min. One sample per group was examined under SEM to assess the resin-dentin interface. Data were analyzed using two-way ANOVA and Games Howell post hoc test (p < 0.05). Group IV showed the highest bond strength in both surface treatments, while Group I had the lowest (p < 0.05). In Group II, laser treatment resulted in a statistically significant reduction in bond strength compared to bur-prepared surfaces (p < 0.05), whereas surface preparation had no significant effect on the bond strength of the remaining groups. Adhesive failures were most common, though cohesive failures were more frequent in Group II-Bur and Group I-Laser. The bonding performance of bioactive restorative materials was influenced by both their composition and the dentin surface preparation method. Cention Forte showed the most reliable adhesion on both bur- and laser-prepared dentin, whereas EQUIA Forte HT exhibited lower bonding performance.

PMID:41266675 | DOI:10.1007/s10103-025-04747-7