Tag: statistics

Hypertens Res. 2025 Nov 20. doi: 10.1038/s41440-025-02439-x. Online ahead of print.

ABSTRACT

This prospective cohort study compared the associations between office blood pressure (OBP) and home blood pressure (HBP) measured before 20 weeks of gestation with the subsequent development of placenta-mediated pregnancy complications (PMPCs). A total of 975 pregnant women were included in the study. OBP and HBP were measured between 10 weeks 0 days and 19 weeks 6 days of gestation, using HBP values from the same gestational weeks as OBP. When both OBP and HBP were included simultaneously in a binary logistic regression model, per 1 standard deviation increase, the adjusted odds ratios (aORs) for office and home systolic blood pressure (SBP) were 1.16 (95% confidence interval [CI]: 0.95-1.42) and 1.68 (95% CI: 1.36-2.09), respectively. For diastolic blood pressure (DBP), the aORs were 1.36 (95% CI: 1.10-1.69) for office and 1.70 (95% CI: 1.37-2.12) for home measurements. The likelihood ratio test showed that adding home SBP to a model with office SBP improved model fit (P value < 0.0001), whereas adding office SBP to a model with home SBP did not (P value = 0.2). For DBP, adding either home or office values improved model fit (P value < 0.0001 and P value = 0.005, respectively). Home SBP was more strongly associated with PMPCs than office SBP. Although home DBP was not statistically stronger than office DBP, its effect estimate was higher. These findings support the added value of HBP monitoring during pregnancy for predicting PMPCs.

PMID:41266872 | DOI:10.1038/s41440-025-02439-x

Mol Neurobiol. 2025 Nov 21;63(1):110. doi: 10.1007/s12035-025-05439-7.

ABSTRACT

Research on the gut-brain-immune axis shows it plays a critical role in ischemic stroke, but the exact causal links between gut bacteria imbalance, immune system problems, and brain blood vessel damage remain unclear. To investigate this, we combined multiple types of biological data using a statistical method called Bayesian weighted Mendelian randomization (BWMR). We analyzed large genetic datasets covering 731 immune cell traits, 91 inflammatory proteins, 412 gut microbes and their pathways, and ischemic stroke cases. Shared genetic variants were confirmed using colocalization, and we used computer simulations to explore potential treatments. The analysis found that genetically predicted higher levels of the protein CD27 on specific memory B cells (CD24⁺ CD27⁺ and IgD^– CD38^dim) directly increased the risk of stroke caused by large-artery atherosclerosis. Computer modeling indicated that a compound called Dioscin could potentially block CD27 effectively. Conversely, bacteria from the order Burkholderiales (specifically at the family, genus, and species level Burkholderiales_bacterium_1_1_47) showed strong protective effects against small-vessel stroke. Further analysis revealed that about 12.6% of the protective effect of the gut bacterium g_Odoribacter worked through the signaling protein FGF19. This study identifies CD27-positive B cells as key drivers of brain inflammation in stroke and suggests Dioscin as a promising treatment candidate. It also demonstrates a protective mechanism where specific gut microbes communicate with blood vessels in the brain via FGF19, providing a foundation for new stroke therapies targeting the microbiome and immune system.

PMID:41266864 | DOI:10.1007/s12035-025-05439-7

Inflamm Res. 2025 Nov 21;74(1):166. doi: 10.1007/s00011-025-02124-2.

ABSTRACT

BACKGROUND: Periodontitis has been associated with an increased risk of atherosclerotic cardiovascular disease; however, its association with subclinical myocardial injury remains scarce. The purpose of this study was to investigate the association between periodontitis, cardiac biomarkers of subclinical myocardial injury, and cardiovascular mortality in the general U.S.

METHODS: We analyzed data from 9202 participants initially free of cardiovascular disease in the 1999-2004 National Health and Nutrition Examination Survey. The grade of periodontitis was categorized into normal, mild, and moderate-severe. Survey-weighted multiple linear regression model assessed the association between periodontitis and cardiac biomarkers, including high-sensitivity cardiac troponin (hs-cTn) and N-terminal pro-B-type natriuretic peptide (NT-proBNP). Survey-weighted multiple Cox regression model was utilized to estimate the association between periodontitis and cardiovascular disease mortality.

RESULTS: The mean age of participants was 40.65 ± 0.32 years, with 48.44% being men. The individuals with mild and moderate-severe periodontitis had significantly elevated hs-cTn and NT-proBNP, which indicated impaired cardiac structure and function, compared with non-periodontitis individuals. After controlling confounding covariates, moderate-severe periodontitis was significantly correlated with elevated hs-cTnT and NT-proBNP (β coefficients: 0.055, 95% CI 0.004 to 0.106; β coefficients: 0.188, 95% CI 0.077 to 0.300, respectively). Sensitivity analysis and subgroup analysis further verified the robustness of the results. Over a 17.5-year follow-up period, individuals with moderate-to-severe periodontitis exhibited a 44.9% higher risk of cardiovascular mortality compared to those without periodontitis (hazard ratio: 1.449, 95% CI: 1.027 to 2.044).

CONCLUSION: In individuals without established cardiovascular disease, moderate-severe periodontitis was associated with higher concentrations of hs-cTn and NT-proBNP, as well as an increased risk of cardiovascular mortality. These results emphasize the importance of maintaining optimal oral health.

PMID:41266855 | DOI:10.1007/s00011-025-02124-2

Support Care Cancer. 2025 Nov 20;33(12):1102. doi: 10.1007/s00520-025-10171-y.

ABSTRACT

BACKGROUND: Cisplatin causes nephrotoxicity in approximately 30% of patients. Mannitol has been proposed as a nephroprotective agent, yet the clinical evidence remains inconclusive.

METHODS: We systematically searched PubMed, EMBASE, and the Cochrane Library through December 2024 for randomized controlled trials (RCTs) evaluating mannitol versus control interventions for prevention of cisplatin-induced nephrotoxicity. The primary outcome was acute kidney injury (AKI), standardized across CTCAE, AKIN, and RIFLE systems. Given heterogeneous comparators, analyses were stratified by control type without cross-comparator pooling. Odds ratios (ORs) were used for AKI; risk differences (RDs) were used for adverse events. Pooled estimates were generated only when ≥ 5 trials were available per stratum.

RESULTS: Nine RCTs (357 participants) were included. For severe AKI (grade ≥ 2), three small trials (n = 164) were available. Two placebo-controlled studies showed lower AKI risk with mannitol (absolute reductions ~ 15-20%), while one furosemide-controlled study showed no clear difference. These preliminary observations require confirmation in larger trials. For overall AKI (grade ≥ 1; six trials, n = 297), results were inconsistent across studies. Renal function outcomes were heterogeneous: one placebo-controlled trial favored mannitol, one hydration-controlled trial favored control, and a furosemide-controlled trial showed minimal difference. Adverse events were sparsely reported: no consistent differences were seen for electrolyte or hematological toxicities, while several studies suggested modest reductions in nausea/vomiting and a possible increase in diarrhea.

CONCLUSIONS: Based on only three small trials (n = 164), preliminary trends suggest mannitol might reduce severe AKI in cisplatin-treated patients, particularly versus placebo. However, this evidence is insufficient to support clinical implementation. The observed protective trend should be considered hypothesis-generating rather than definitive. Effects on overall AKI, renal function, and toxicities remain inconclusive. Larger, well-designed RCTs with adequate statistical power are urgently needed before mannitol can be recommended for routine nephroprotection in clinical practice.

PMID:41266849 | DOI:10.1007/s00520-025-10171-y

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