Category: Statistics

Sci Rep. 2026 Jan 2. doi: 10.1038/s41598-025-34282-y. Online ahead of print.

ABSTRACT

Curcumin’s clinical utility is limited by poor bioavailability and dose-dependent toxicity. Although nano-encapsulation can address these shortcomings, rationally optimizing nanocarrier biosafety remains challenging due to the highly multidimensional design space. Here, we develop an interpretable Physics-Informed Machine Learning (PIML) framework that integrates experimental data from 75 curcumin nanocarriers with DLVO stability theory and drug-release kinetics to predict and optimize cytotoxicity. Among the evaluated models, XGBoost attained the highest statistical performance (R² = 0.89), although the PIML model provided physically coherent predictions with similar accuracy (R² = 0.86). SHAP research indicated a moderate negative zeta potential (-30 to -40 mV), chitosan-based coatings, and particle sizes of 150-250 nm as the principal factors contributing to decreased cytotoxicity. Multi-objective Bayesian optimization delineated a Pareto-optimal design space, facilitating approximately 82% toxicity reduction compared to free curcumin, while preserving around 70% loading efficiency. The study develops a proven, generalizable computational methodology that converts intricate nanocarrier design interactions into practical guidelines for the fabrication of safer curcumin-based nanotherapeutics.

PMID:41484189 | DOI:10.1038/s41598-025-34282-y

Sci Rep. 2026 Jan 3. doi: 10.1038/s41598-025-27634-1. Online ahead of print.

ABSTRACT

Reliable cause-specific mortality statistics are crucial for defining health priorities, public health programs, allocating resources, designing and implementing policies to improve healthcare quality and accessibility. India accounts for almost 18 percent of the world’s population. The 2020 report from the Office of the Registrar General of India indicates that the Medical Certification of Cause of Death (MCCD) rate is only 22.5%, with a minimal improvement of just 2.5% over the past decade. This study is the first to provide a comprehensive evaluation of MCCD-patterns across India over the past 15 years, addressing a critical-gap in the literature by identifying regional patterns, disparities, and healthcare variables that have previously been underexplored. Based on MCCD-trends over this period, the states and Union-Territories of India can be categorized into three clusters. Cluster1 includes 23 states with the lowest-average MCCD-rate of 18%, attributed to a low 0.14 doctors per 1000 people, with only 27.4% of hospitals actively reporting-MCCD. In contrast, Clusters2 and 3 have higher-average MCCD-rates of 63% and 60%, respectively, supported by higher 0.27 and 0.33 doctors per 1000 people, with over 80% of hospitals actively reporting-MCCD. Although, the findings indicate that active MCCD-reporting is a major factor associated with MCCD rates, other factors including healthcare infrastructure, state-specific healthcare policies, socioeconomic factors, and administrative management also influence MCCD-rates.

PMID:41484187 | DOI:10.1038/s41598-025-27634-1

Sci Rep. 2026 Jan 2. doi: 10.1038/s41598-025-34323-6. Online ahead of print.

ABSTRACT

LASER Beam Machining (LBM) has emerged as a highly precise and non-contact thermal machining process, widely adopted for cutting complex geometries in advanced engineering materials. Its ability to machine difficult-to-cut alloys with minimal mechanical stress makes it particularly suitable for aerospace and defense components. This paper presents an experimental investigation and multi-objective optimization of LASER Beam Machining (LBM) for XG3 steel, a high-performance alloy used in aerospace and defense applications. The study evaluates the impact of four process parameters i.e. cutting speed (8, 10, 12 m/min), gas pressure (0.5, 0.7, 0.9 Bar), focus point (2, 4, 6 mm), and depth of cut (3, 6, 9 mm) on four output responses: surface roughness, machining time, surface hardness, and burr thickness. Experiments were conducted using a Taguchi L₂₇ orthogonal array on three distinct hole geometries: circular, triangular, and square. Analysis of Variance (ANOVA) revealed that cutting speed was the most dominant factor, contributing over 82% to the variation in surface roughness, 74% for machining time, 81% for surface hardness, and 84% for burr thickness. The interaction between cutting speed and depth of cut was also found to be statistically significant. For single-objective optimization, the ideal parameters to minimize surface roughness were a cutting speed of 12 m/min, gas pressure of 0.5 bar, focus point of 2 mm, and depth of cut of 3 mm. Multi-objective optimization using a Genetic Algorithm (MOGA) generated Pareto fronts to identify balanced trade-off solutions; for a circular profile, this resulted in surface roughness values of 1.10-1.16 μm and machining times of 2.44-2.52 s. Furthermore, two predictive models, Response Surface Methodology (RSM) and a Back-Propagation Artificial Neural Network (BPANN), were developed. Comparative analysis showed the BPANN model was significantly more accurate, with regression coefficients (R) exceeding 0.999 and Mean Absolute Percentage Error (MAPE) values of 1.48% for surface roughness and 0.72% for surface hardness, confirming its superior predictive capability.

PMID:41484160 | DOI:10.1038/s41598-025-34323-6

Sci Rep. 2026 Jan 2. doi: 10.1038/s41598-025-34114-z. Online ahead of print.

ABSTRACT

To investigate temporal changes in the relationship between central venous pressure (CVP) and B-line scores through dynamic monitoring of the two parameters in patients undergoing transurethral resection of the prostate (TURP). A total of 101 patients who underwent TURP were enrolled in the study, with the procedure being performed under general anesthesia. B-line scores (quantified via transthoracic lung ultrasound), CVP, PaO₂/FiO₂ ratio, hemoglobin (Hb), peak airway pressure (Ppeak), arterial sodium (Na⁺), and potassium (K⁺) concentrations were measured at the following time points: baseline at the start of surgery (T0) and upon irrigation fluid volumes of 5000 mL (T1), 10,000 mL (T2), 15,000 mL (T3), and 20,000 mL (T4). Generalized additive mixed models (GAMMs) were used to analyze the longitudinal data. In the longitudinal study of 101 patients undergoing TURP, 90 were included in the final analysis. Poisson GAMM analyses revealed a significant time effect on B-line scores (F = 62.029-69.486, P < 0.001 across models), showing progressive increases from T0 to T4. CVP demonstrated a modest main effect (F = 3.156-4.026, P = 0.045-0.076) and a non-significant interaction with time (F = 1.441-1.967, P = 0.161-0.231), persisting after adjustments for age, weight, height, effective tidal volume, and intraoperative use of furosemide (adjusted pseudo-R² = 0.553). Quantitative and percentile analyses showed only small and uncertain associations between CVP and B-line scores, with confidence intervals consistently crossing the null. Across multiple sensitivity analyses, the estimated CVP effect remained minimal and statistically non-significant regardless of modeling approach. B-line scores increased progressively during TURP, whereas the association between CVP and B-line scores remained small and statistically non-significant across all analyses. These findings suggest that intraoperative B-line dynamics primarily reflect temporal changes rather than CVP fluctuations.Trial registrationThe trial registration number: ChiCTR2200065753, 14/11/2022. Title: “Application of transthoracic lung ultrasound in patients undergoing prostatectomy”. Website: https://www.chictr.ogr.cn.

PMID:41484158 | DOI:10.1038/s41598-025-34114-z

Sci Rep. 2026 Jan 2. doi: 10.1038/s41598-025-30983-6. Online ahead of print.

ABSTRACT

Prior research consistently reports differences in mental health outcomes among adolescents between intact and non-intact families, highlighting the need to address these disparities. This study aims to investigate the moderating effect of advisers (counselors, teachers, or friends) on the mental health of adolescents from non-intact families. We conducted a cross-sectional study using data from the 2017 Korea Youth Risk Behavior Web-Based Survey, a large, representative nationwide sample of adolescents. We included 61,572 middle and high school students living with at least one parent, categorizing them into five groups: biological parents, single parent (only father or mother), stepfather-biological mother, and biological father-stepmother. We assessed mental health outcomes (poor self-rated health status, self-rated unhappiness, depressive mood, suicidal consideration, suicidal planning, and suicidal attempt) using self-reported measures and evaluated the presence of advisers providing emotional support. Multivariate-adjusted logistic regression analyses were performed to examine associations between family structure and mental health outcomes, and to assess the moderating effect of advisers. Compared to adolescents living with both biological parents, those from non-intact families exhibited significantly higher odds of poor mental health outcomes. While adviser presence was associated with lower odds of adverse outcomes across most family structures, formal tests of interaction were not statistically significant. Our findings suggest that family structure is associated with adolescent mental health, and that adviser presence is generally linked to more favorable outcomes. Although formal interaction tests did not demonstrate statistically significant moderation, the consistent patterns observed across groups highlight the potential value of adviser support. These findings should be interpreted with caution, yet they underscore the importance of promoting access to trusted advisers as a practical strategy to support adolescents, particularly those from non-intact families.

PMID:41484148 | DOI:10.1038/s41598-025-30983-6

Nat Commun. 2026 Jan 2. doi: 10.1038/s41467-025-67324-0. Online ahead of print.

ABSTRACT

Quantum Monte Carlo is one of the most promising approaches for dealing with large-scale quantum many-body systems. It has played an extremely important role in understanding strongly correlated physics. However, two fundamental problems, namely the sign problem and general measurement issues, have seriously hampered its scope of application. We propose a universal scheme to tackle the problems of general measurement. The target observables are expressed as the ratio of two types of partition functions $⟨O⟩=\overline{Z}/Z$, where $\overline{Z}=tr\left({Oe}^{–\beta H}\right)$ and $Z=tr\left(e^{–\beta H}\right)$. These two partition functions can be estimated separately within the reweight-annealing frame, and then be connected by an easily solvable reference point. We have successfully applied this scheme to XXZ model and transverse field Ising model, from 1D to 2D systems, from two-body to multi-body correlations and even non-local disorder operators, and from equal-time to imaginary-time correlations. The reweighting path is not limited to physical parameters, but also works for space and time. Essentially, this scheme solves the long-standing problem of calculating the overlap between different distribution functions in mathematical statistics, which can be widely used in statistical problems, such as quantum many-body computation, big data and machine learning.

PMID:41484118 | DOI:10.1038/s41467-025-67324-0

Nat Commun. 2026 Jan 2. doi: 10.1038/s41467-025-68101-9. Online ahead of print.

ABSTRACT

The positive effect of exercise on the immune system is widely acknowledged, but the molecular response of immune cells to exercise remains largely unknown. Here, we perform mass-spectrometry-based proteomic analysis on peripheral blood mononuclear cells (PBMC) at a depth of >6000 proteins. Comparing high-intensity interval exercise (HIIE) and moderate-intensity continuous exercise (MICE), matched for time and workload, we identify versatile changes in the proteomic makeup of PBMCs and reveal profound alterations, related to effector function and immune cell activation pathways within one hour following exercise. These changes are more pronounced after HIIE compared to MICE and occur despite identical immune cell mobilization patterns between the two exercise conditions. We further identify an immunoproteomic signature that effectively predicts cardiorespiratory fitness, thus allowing insights into potential exercise-triggered adaptations and immunological health benefits that are mediated by exercise. This study provides a reliable data resource that expands our knowledge on how exercise modulates the immune system, and delivers biological evidence supporting the WHO 2020 guidelines, which highlight exercise intensity as a relevant factor to maintain health.

PMID:41484100 | DOI:10.1038/s41467-025-68101-9

J Formos Med Assoc. 2026 Jan 2:S0929-6646(25)00699-0. doi: 10.1016/j.jfma.2025.12.042. Online ahead of print.

ABSTRACT

PURPOSE: Studies exploring changes in fibrosis markers and their predictive performance for histological fibrosis staging after hepatitis C virus (HCV) eradication are limited. The aim of this study was to examine the predictive performance of and exclusionary and confirmatory thresholds for the ELF test, FIB-4 index, APRI, M2BPGi, liver stiffness measurement (LSM) through acoustic radiation force impulse elastography, and the collagen proportionate area (CPA) for each METAVIR fibrosis stage after treatment.

METHODS: We examined 280 and 207 patients (3.1 ± 0.3 years) before and after HCV eradication, respectively, of whom 197 underwent paired liver biopsies. Statistical analysis assessed fibrosis markers’ predictive performance using AUROC and ROC curves, and their optimal thresholds.

RESULTS: The median ELF, FIB-4, APRI, M2BPGi, LSM, and CPA values for each METAVIR stage and the exclusionary and confirmatory thresholds for dichotomized METAVIR stages decreased after HCV eradication. The areas under the receiver operating characteristic curve (AUROCs) derived for ELF, FIB-4, APRI, M2BPGi, LSM, and CPA for predicting advanced fibrosis (F3-F4) were 0.803, 0.826, 0.784, 0.750, 0.863, and 0.920, respectively, before viral eradication and 0.710, 0.791, 0.766, 0.699, 0.810, and 0.901, respectively, after viral eradication. CPA had the highest AUROCs for predicting significant (F2-F4) and advanced fibrosis (F3-F4) before and after HCV eradication. Most of the fibrosis markers decreased significantly after viral eradication, regardless of METAVIR fibrosis stage changes.

CONCLUSIONS: Noninvasive fibrosis markers can be used at a low threshold to determine the stage of liver fibrosis, although their predictive performance decreases after HCV eradication.

PMID:41484047 | DOI:10.1016/j.jfma.2025.12.042

Dig Liver Dis. 2026 Jan 2:S1590-8658(25)01228-9. doi: 10.1016/j.dld.2025.12.002. Online ahead of print.

ABSTRACT

BACKGROUND: Autoimmune atrophic gastritis (AAG) is an immune-mediated disorder affecting the gastric oxyntic mucosa. Two pathogenetic models are proposed: a pure autoimmune disorder or gastric autoimmunity triggered by Helicobacter pylori (Hp)-infection. In AAG, histological diagnosis of Hp may be challenging and serology can help assess exposure to Hp-infection. This study aimed to determine seroreactivity to Hp-antigens in AAG patients by using Hp-multiplex serology assay.

METHODS: A single-centre case-control study on 178 adults: 75 patients with serological and histological AAG diagnosis, 25 controls with histologically Hp-positive-non-atrophic gastritis (Ctr-NAG-Hp+) and 78 subjects with a healthy stomach (Ctr-HS). Sera were analysed using Hp-multiplex serology assay allowing simultaneous detection of antibodies to 13 Hp-proteins. Overall positivity cutoff: seroreactivity to more than 3 Hp-antigens.

RESULTS: The number of seroreactive Hp-antigens was higher in AAG than in Ctr-HS(mean±SEM 2.2±0.3 vs 1.4±0.22,p=0.02) and lower than in Ctr-NAG-Hp+ patients (mean±SEM 5.4±0.5,p<0.001).Overall Hp-seropositivity in AAG was two-fold higher than in Ctr-HS but not statistically significant (21.1% vs 10.3%,p=0.06) and lower than in Ctr-NAG-Hp+(80%,p<0.0001). Complete absence of seroreactivity was similar in AAG and Ctr-HS (29.3% vs 38.5%, p=0.23) and significantly higher than in Ctr-NAG-Hp+ (4%, p=0.009). Main immunogenic Hp-proteins were HP0010(GroEL),HP1098(HcpC),HP0695(HyuA),HP0875(Catalase),HP1564,HP0547(CagA) and HP0243(NapA) with seroreactivity in >50% of AAG patients.

CONCLUSIONS: By Hp-multiplex serology, 30% of histologically Hp-negative AAG pts had no seroreactivity, likely belonging to the pure AAG type. Conversely, 20% of AAG pts showed Hp exposure, indicating that infection might have triggered gastric autoimmunity. The remaining AAG patients showed seroreactivity below cut-off for seropositivity and thus not definitively categorisable by this approach.

PMID:41484031 | DOI:10.1016/j.dld.2025.12.002

Nutr Metab Cardiovasc Dis. 2025 Dec 2:104483. doi: 10.1016/j.numecd.2025.104483. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Combined therapy, sodium-glucose cotransporter 2 inhibitors (SGLT2i), and glucagon-like peptide-1 receptor agonists (GLP1ra) reduce all-cause mortality in patients with diabetes. We aimed to analyse the differential behaviour of combined therapy between women and men regarding all-cause mortality.

METHODS AND RESULTS: This is a retrospective observational cohort study. Using “Big data” according to electronic medical records in the Santiago-Barbanza health area, which covers 450,000 patients. Out of 15,118 patients, 41 % were women. The median follow-up was 33 months. Women were older (71 [62-78] vs. 67 [59-75], p: <0.001) and with a higher incidence of obesity (53 % vs. 41 %, p: <0.001), meanwhile, men presented more coronary artery disease (CAD) (19 % vs. 9 %, p: <0.001). The multinomial propensity score and multivariate Cox regression were used for statistical analysis. All-cause mortality was compared between combined vs. monotherapy in women or men. Men had a higher risk of all-cause mortality than women in this population (HR [95 % CI] 1.50 [1.28-1.75]). Combined regarding monotherapy (GLP1ra (HR [95 % CI] 0.19 [0.14-0.27]), or SGLT2i (HR [95 % CI] 0.30 [0.23-0.40]), and treatment duration (HR [95 % CI] 0.95 [0.94-0.96] were associated with lower risk of all-cause mortality; with higher benefit in women (GLP1ra (HR [95 % CI] 0.14 [0.08-0.27]), or SGLT2i (HR [95 % CI] 0.18 [0.11-0.30]) regarding men (HR [95 % CI] 0.25 [0.16-0.40] for GLP1ra, and HR [95 % CI] 0.41 [0.29-0.58] for SGLT2i).

CONCLUSIONS: Combined therapy vs. monotherapy was associated with a lower risk of all-cause mortality in patients regardless of sex. Nevertheless, a higher benefit was observed in women regarding men.

PMID:41484025 | DOI:10.1016/j.numecd.2025.104483