Category: Statistics

Nat Genet. 2026 Aug 10. doi: 10.1038/s41588-026-02692-x. Online ahead of print.

ABSTRACT

The incidence of colorectal cancer (CRC) has risen in recent decades, with a disproportionate increase observed among younger individuals in Japan and other countries. The etiological contribution of the gut microbiota to CRC pathogenesis is recognized, yet the mechanisms involved remain to be fully clarified. Here we integrated whole-genome sequencing (WGS) and transcriptome profiling of CRC with whole-genome metagenomic sequencing of fecal samples to interrogate host-microbiome interactions at high resolution. Application of interpretable artificial intelligence enabled the stratification of CRC into four distinct microbiome-informed subtypes. WGS analysis identified mutational signatures SBS88 and ID18, linked to colibactin exposure, as early clonal events detected in 44.8% of non-hypermutated patients. Notably, these signatures were significantly more frequent among patients born after the 1960s. Microbiome-based subclassification revealed subtype-specific clinical and molecular features. Collectively, our findings indicate that colibactin exposure constitutes a prevalent and potentially modifiable risk factor for CRC in the Japanese population.

PMID:42576026 | DOI:10.1038/s41588-026-02692-x

Nat Rev Genet. 2026 Aug 10. doi: 10.1038/s41576-026-00992-w. Online ahead of print.

ABSTRACT

The widespread adoption of electronic health records (EHRs), which capture patient-specific longitudinal information on diagnoses, laboratory tests, clinical procedures, and outcomes, has created unprecedented opportunities to study diseases at scale. Integrating EHR data with genomic information offers novel ways to understand disease heterogeneity, identify biomarkers and therapeutic targets, and predict disease risk to improve clinical decision-making at scale. Recent methodological advances in machine learning (ML) and artificial intelligence (AI) can handle data with high dimensionality, high levels of noise, and irregular temporality better than traditional statistical approaches. Progress in EHR-linked biobank development, data standardization pipelines, and architectures for modelling and implementation have accelerated the advancement of the field and warrant an assessment of current capabilities and limitations. This Review highlights AI and ML frameworks for integrating genomic, multi-omics, and EHR data, and discusses how these approaches are reshaping genomics research as well as clinical practice.

PMID:42576006 | DOI:10.1038/s41576-026-00992-w

J Bone Miner Metab. 2026 Aug 10. doi: 10.1007/s00774-026-01747-7. Online ahead of print.

ABSTRACT

INTRODUCTION: In cortical bone histology, the ratio of Haversian canal and secondary osteon areas reflects bone resorption and formation during metabolic events executed by Basic Multicellular Units (BMUs). Area data can be pooled where they are collected independently, and the ratio calculated from the mean of each measure. They can also be paired, where they are measured from the same secondary osteon at once and the mean of individual ratios is calculated. We evaluate the impact of pooling and pairing on the resulting ratio values and their interpretation of bone remodelling.

MATERIALS AND METHODS: Using both approaches, we calculated the area ratio of 551 Haversian canals and secondary osteons from measurements of existing midshaft femur histology slides. The sample represents n = 38 young and middle-aged females of different social backgrounds from a historical osteological collection. Univariate and bivariate statistics were used to compare and evaluate paired and pooled values and their differences.

RESULTS: The pooled method usually returned a lower canal-to-osteon value than paired data across the whole sample, ages, and social groups. These methods differed in the ratios they produced, independently of the number of measurements per sample.

IN CONCLUSION: The pooling technique indicated the presence of thicker lamellar bone within secondary osteons, suggesting greater quantities of bone formed during BMU activity, than the paired technique results, which suggested less bone formed per BMU. While pooling offers efficiency in data collection and analysis, we show that paired data yield more biologically precise and analytically flexible results at an individual BMU level.

PMID:42576001 | DOI:10.1007/s00774-026-01747-7

Nat Nanotechnol. 2026 Aug 10. doi: 10.1038/s41565-026-02235-9. Online ahead of print.

ABSTRACT

Gut microbial metabolites play crucial roles in regulating systemic immunity, but their mechanisms and limited drug-like properties remain unresolved. Here we report an oral nano-formulation that leverages gut microbial metabolites to modulate T cell metabolism and amplify antitumour immunity. Through an in vitro screening of gut microbial metabolites, we identified 3,4-dihydroxybenzoic acid that improved adoptive T cell therapy and enhanced CD8⁺ T cell stemness by suppressing glycolysis and regulating the Akt-mTORC1-Myc pathway. To harness the potency of 3,4-dihydroxybenzoic acid for systemic cancer immunotherapy, we engineered a 3,4-dihydroxybenzoic acid prodrug nano-emulsion, significantly increasing its oral absorption and half-life. In multiple murine tumour models, the oral nano-emulsion enhanced the expansion of antigen-specific, stem-like CD8⁺ T cells, sensitizing tumours to anti-PD-1 blockade and exerting robust antitumour efficacy. By integrating nanotechnology with microbial-metabolite-based immunotherapy, this study establishes a mechanistic link between the gut microbiota and T cell immunity, offering a promising approach for cancer immunotherapy.

PMID:42575976 | DOI:10.1038/s41565-026-02235-9

Sci Rep. 2026 Aug 11;16(1):24905. doi: 10.1038/s41598-026-66191-z.

ABSTRACT

Despite their well-known efficacy, forced-air warming during operations has its drawbacks, mainly high energy consumption and risk of hyperthermia. We therefore investigated two warming strategies in a prospective randomized study with the aim of reducing the incidence of hyperthermia without increasing the risk of intraoperative hypothermia. In the standard of care group temperature of the forced-air warmer was reduced to 32 °C when core temperature reached 37.3 °C. In the modified warming group this reduction was performed when core temperature reached 36.5 °C. The difference in the duration of normothermia between standard of care and the modified warming strategy was estimated to be 3.9% (90%-CI: 0.8% to 7.1%) and was within the predefined equivalence bounds of ± 20% (p < 0.001). In both treatment groups no intraoperative hyperthermia ocurred. Average energy consumption per hour was significantly higher in the standard-of-care group (0.51 kWh/h; 95%-CI: 0.47-0.56) compared with the modified warming strategy (0.40 kWh/h; 95%-CI: 0.35-0.46; p = 0.002). By strictly limiting the heat supply, intraoperative hyperthermia can be safely prevented during craniotomies. A lower threshold value of 36.5 °C allows for a meaningful reduction in energy consumption.

PMID:42575948 | DOI:10.1038/s41598-026-66191-z

Neural Netw. 2026 Aug 3;205(Pt B):109461. doi: 10.1016/j.neunet.2026.109461. Online ahead of print.

ABSTRACT

This work revisits diffusion Transformers for relative-depth-conditioned and joint image-depth synthesis, focusing on two bottlenecks: (1) cross-modal attention degrades around edges and structural regions, causing geometric distortions; (2) the depth branch can be overly influenced by the semantic branch, leading to over-coupling and instability. To address these issues, we propose JointConn-v2 with GCM-WFM (Gated Cross-Modal Weighted Flow Matching), a unified framework for joint and depth-conditioned image synthesis. JointConn-v2 strengthens bidirectional guidance via Swap-Q cross-attention, explicitly injects 2D relative positions and edge energy into the attention logits through a Geometric Mask Bias, performs token-level spatial selection of where and in which direction to fuse cross-modal features via Regional Routing, and controls whether and how strongly cross-branch injection occurs through a sample-level Content Gate with residual fusion. On the training side, we introduce GCM-WFM, which regresses a joint vector field in the packed sequence space and incorporates temporal, geometric, gating, and routing terms into the objective with diagonal weights. Our approach achieves a better balance between edge controllability and cross-modal consistency. The current formulation treats depth as a normalized relative geometric signal and is not intended to preserve absolute metric scale. Code is available at https://github.com/haizhu12/JointConn-v2.

PMID:42574824 | DOI:10.1016/j.neunet.2026.109461

Oral Oncol. 2026 Aug 10;181:108102. doi: 10.1016/j.oraloncology.2026.108102. Online ahead of print.

ABSTRACT

OBJECTIVE: This study aimed to evaluate the predictive value of a quantitative index measuring the extent of somatic copy-number alteration (SCNA) for malignant transformation (MT) in oral leukoplakia (OLK).

METHODS: A prospective cohort of 122 patients with OLK was followed for a median of 74 months. Whole-exome sequencing (WES) was performed on fresh-frozen tissue specimens. SCNA-L was defined as the total autosomal length of segments exceeding predefined copy-number and minimum-width thresholds. The cohort was stratified into high- and low-SCNA-L groups using a median cutoff of 3.3. The primary outcome was MT to oral squamous cell carcinoma (OSCC). Statistical analyses included Kaplan-Meier survival analysis, Cox proportional hazards models, time-dependent ROC curves, a 1,000-resample bootstrap optimism-corrected C-index, and bootstrap internal validation using calibration curves.

RESULTS: The MT rate was significantly higher in the high-SCNA-L group (26.7%) than in the low-SCNA-L group (6.5%; P < 0.01). SCNA-L remained an independent predictor of MT in the multivariable analysis (hazard ratio = 4.684, P = 0.006). The predictive model, incorporating SCNA-L and lesion type, demonstrated adequate discrimination and satisfactory calibration for mid-term prediction.

CONCLUSIONS: As an independent predictor of MT in OLK, the quantitative index SCNA-L can serve as a molecular supplement to conventional pathological grading.

PMID:42574790 | DOI:10.1016/j.oraloncology.2026.108102

Child Abuse Negl. 2026 Aug 10;180:108257. doi: 10.1016/j.chiabu.2026.108257. Online ahead of print.

ABSTRACT

BACKGROUND: Children’s increasing use of digital platforms elevates their risk for online sexual exploitation (OSE), especially among those with sexual abuse histories. Despite known risk, data on prevalence and related characteristics remain limited. Digital safety screening (DSS) offers child abuse professionals a tool to assess risk or prior exploitation but is not standardized.

OBJECTIVE: To examine age-related variation in OSE disclosure within a clinically relevant population and characterize how DSS is applied in this clinical setting.

PARTICIPANTS AND SETTING: A retrospective chart review was conducted of 307 patients aged 10-18 years who received forensic interviews (FIs) for evaluation for suspected sexual abuse by a single social worker between 2022 and 2024 at a Child Advocacy Center in the Midwestern United States.

METHODS: FI notes were analyzed through content analysis to characterize the utilization of DSS and patient disclosure or denial of OSE. Descriptive statistics revealed prevalence: logistic regression examined associations between patient age and OSE.

RESULTS: Of 307 patients, 96.1% received DSS. Among 299 who discussed OSE, 41.5% reported at least one experience. Odds of reporting increased with age, beginning at 12.0% at age 10, 27.3% at 11, and increasing to 60.0% at age 16.

CONCLUSIONS: OSE exposure likely increases with age and may vary by sex assigned at birth. Findings underscore the need for routine, standardized DSS validated across developmental stages and languages, as well as further research on prevalence and risk and prevention and response strategies.

PMID:42574786 | DOI:10.1016/j.chiabu.2026.108257

Immunobiology. 2026 Aug 6;231(5):153224. doi: 10.1016/j.imbio.2026.153224. Online ahead of print.

ABSTRACT

The effects of long-term parental microplastic exposure on offspring immunity remain unclear. This study investigated how different parental exposure patterns affect immune status in F1 offspring. Parental rats were divided into four groups: paternal, maternal, dual-parental, and control. Treated groups received polystyrene microplastics (5 mg/L) in drinking water for 90 days. F1 offspring were raised under standard conditions until 8 weeks of age, after which fecal samples, thymus, spleen, and serum were collected for immune evaluation. Maternal microplastic exposure significantly disrupted gut microbiota α-diversity, dysbiosis index, and composition in F1 offspring (all P < 0.05). These changes were accompanied by decreased RBCs and PLT counts, elevated serum TNF-α, reduced thymic CD3⁺ and CD4⁺ T cells, and downregulated IL-10 mRNA and NF-kB protein expression. Histological examination revealed blurred corticomedullary boundaries, sparse cellularity, and lymphocyte vacuolization in the thymus, along with thinning of the periarteriolar lymphatic sheaths in the spleen, further indicating immune imbalance. Paternal and dual-parental exposure also induced gut microbiota dysbiosis and reduced thymic CD4⁺ T cells. Paternal exposure upregulated Th17-related RORγt and TNF-α mRNA in the thymus, whereas dual-parental exposure decreased thymic Nrf2 protein, splenic CD4⁺/CD8⁺ ratios, and white pulp area. Thymic pathology was observed in both groups. In conclusion, our findings suggest that prolonged parental exposure to microplastics may disrupt immune homeostasis in F1 offspring by altering gut microbiota composition and modulating oxidative stress or inflammatory responses. Moreover, the extent of these effects varies with the different parental exposure patterns.

PMID:42574783 | DOI:10.1016/j.imbio.2026.153224

Eur J Radiol. 2026 Aug 5;204:113141. doi: 10.1016/j.ejrad.2026.113141. Online ahead of print.

ABSTRACT

BACKGROUND: To systematically compare the diagnostic accuracy of abbreviated breast MRI (AB-MRI) and full diagnostic protocol MRI (FDP-MRI) for breast cancer detection.

METHODS: Ovid-MEDLINE, Embase, Cochrane Library, and Web of Science were searched up to December 1, 2025. Risk of bias was assessed using the modified Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool.

RESULTS: Forty studies (14,266 patients) were included. In screening settings, the first postcontrast subtracted (FAST) protocol achieved sensitivity comparable to FDP‑MRI but significantly lower specificity; adding T2‑weighted (T2W) imaging raised specificity to a level not statistically different from FDP‑MRI. In enriched‑screening settings, FAST with or without T2W performed comparably. In diagnostic settings, FAST combined with ultrafast (UF) and T2W demonstrated significantly higher specificity than FDP‑MRI (ratio 1.61, p < 0.001), while FAST and rapid abridged multiphase (RAMP) with or without T2W or diffusion‑weighted imaging (DWI) were comparable to FDP‑MRI. T2W + DWI alone showed significantly reduced sensitivity in diagnostic settings.

CONCLUSION: The diagnostic performance of AB‑MRI protocols relative to FDP‑MRI varies by protocol and clinical setting; findings apply only to the specific regimens evaluated. FAST maintains high sensitivity, with T2W offsetting specificity limitations in screening, while FAST + UF + T2W offers superior specificity in diagnostic settings. However, most subgroup analyses included only 3-4 studies, and others fewer than three; all results therefore require cautious interpretation and validation in larger, prospective studies before clinical adoption.

PMID:42574771 | DOI:10.1016/j.ejrad.2026.113141