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PubMed2026

Association of time-averaged systemic immune-inflammation indices with in-hospital mortality after intracerebral hemorrhage: a retrospective study.

BACKGROUND: Systemic inflammation plays a central role in secondary brain injury following intracerebral hemorrhage (ICH). Although inflammatory indices such as the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI) are linked to poor outcomes, their associations with mortality are commonly assumed to be linear, potentially overlooking nonlinear patterns where mortality risk rises steeply at higher levels. METHODS: We conducted a retrospective study using the MIMIC-IV database, including 440 patients with non-traumatic ICH who were alive and remained in the ICU for at least 72 h after admission. Mean NLR, SII, and SIRI were calculated from measurements obtained during this period. Multivariable logistic regression and restricted cubic spline (RCS) analyses were applied to assess their independent and nonlinear associations with in-hospital mortality. Model discrimination and calibration were internally validated using 1,000 bootstrap resamples. RESULTS: The in-hospital mortality rate was 26.1%. After multivariable adjustment, NLR and SIRI remained independently associated with mortality. Patients in the highest SIRI quartile had the highest risk of death (aOR = 5.12; 95% CI: 2.57-12.24; p < 0.001). RCS analysis revealed a significant nonlinear association between SIRI and mortality (p-nonlinearity < 0.05), showing a steep risk increase at higher SIRI levels. Adding SIRI to the base model provided a modest improvement in discrimination (AUC 0.762 to 0.785, p = 0.045) and significantly improved risk reclassification (cNRI = 0.4778, p < 0.001; IDI = 0.0240, p = 0.0151). CONCLUSIONS: Among patients with ICH who met the 72-hour eligibility criterion, higher 72-hour average SIRI was independently associated with in-hospital mortality. As a time-averaged measure, SIRI should be interpreted as a dynamic marker integrating the initial inflammatory state and the early clinical course rather than as a purely baseline prognostic factor. Although adding SIRI to the base model modestly improved discrimination and risk reclassification, it should be considered a candidate prognostic marker requiring external validation before clinical application.

Humans↗

PubMed2026

Application of SPI-guided analgesia in laparoscopic gynecologic surgery: a randomized controlled trial evaluating the remifentanil-sparing effect and predictive value of time-weighted SPI.

This study aimed to achieve two primary objectives: (1) to evaluate the opioid-sparing effect of Surgical Pleth Index (SPI)-directed analgesia during surgery via a randomized controlled trial (RCT), and (2) to propose and preliminarily assess a novel dynamic metric, Threshold-based Time-Weighted SPI (Tb-TW-SPI), which integrates stimulus intensity and duration, for its predictive efficacy regarding postoperative moderate-to-severe pain. Employing an RCT combined with exploratory analysis, 61 patients undergoing elective laparoscopic gynecologic surgery were randomized into an SPI-directed analgesia group or a conventional analgesia group. The primary outcome was total intraoperative remifentanil consumption. Postoperatively, an exploratory analysis of the control group data evaluated the correlation between Tb-TW-SPI and Numeric Rating Scale (NRS) pain scores in the post-anesthesia care unit (PACU), calculating its predictive value for moderate-to-severe pain (NRS ≥ 4). Results: The SPI-directed group required significantly less intraoperative remifentanil than the conventional group [median (IQR): 5.84(5.02,6.62)vs. 6.96(5.81,8.19)µg/kg/h; P = 0.016]. Postoperative pain scores did not differ significantly between groups (P > 0.05). Exploratory analysis of the conventional analgesia group revealed that Tb-TW-SPI values were significantly higher in patients with moderate-to-severe postoperative pain (NRS ≥ 4) compared to those without (P = 0.0417).The area under the ROC curve for Tb-TW-SPI predicting this pain was 0.74 (95% CI: 0.52-0.96), with 67% sensitivity and 76% specificity at an optimal cutoff of 1210. This RCT suggests that SPI-directed analgesia can safely and moderately reduce intraoperative remifentanil consumption. Furthermore, the proposed Tb-TW-SPI metric, in this exploratory analysis, suggests potential for predicting postoperative pain, though this finding requires validation in larger cohorts with higher-frequency SPI sampling, offering a new direction for SPI interpretation. Large-scale, multicenter trials are warranted to validate the predictive utility of Tb-TW-SPI. Clinical Trial Registration, China Clinical Trial Registry: ChiCTR2400088444.

Humans↗

PubMed2026

ALID score for treatment-effect heterogeneity of adjunctive low-voltage area ablation in persistent atrial fibrillation: A post hoc analysis of SUPPRESS-AF.

BACKGROUND: In persistent atrial fibrillation (AF), the incremental benefit of adjunctive low-voltage area (LVA) ablation beyond pulmonary vein isolation (PVI) remains inconsistent. OBJECTIVE: To examine whether a simple clinical score characterizes treatment-effect heterogeneity of adjunctive LVA ablation among patients with mapped LVA > 5 cm2 and to perform an exploratory supportive analysis in an independent randomized cohort. METHODS: In this post-hoc analysis of SUPPRESS-AF, which included patients with persistent AF and mapped LVA > 5 cm2 after PVI, four variables-age ≥ 75 years, left atrial diameter > 44 mm, estimated glomerular filtration rate < 60 mL/min/1.73 m2, and absence of diabetes-were combined into the ALID score (0-4). Patients were stratified into low (0-1), intermediate (2), and high (3-4) score groups. Because EARNEST-PVI did not use LVA-guided ablation or select patients based on mapped LVA, it was analyzed as an exploratory supportive cohort rather than as an external validation cohort. RESULTS: In SUPPRESS-AF (n = 336), a significant treatment-by-score interaction was observed (P < 0.001). Adjunctive LVA ablation was associated with increased recurrence in the low-score stratum (HR 3.92; 95% CI 1.50-10.20) and reduced recurrence in the high-score stratum (HR 0.48; 95% CI 0.26-0.86). In EARNEST-PVI (n = 494), a qualitatively similar interaction pattern was observed for additional ablation beyond PVI (interaction P = 0.029), although the ablation strategy differed from LVA-guided ablation. CONCLUSIONS: Among patients with persistent AF and mapped LVA >5 cm2, the ALID score identified heterogeneity in response to adjunctive LVA ablation. These hypothesis-generating findings require prospective validation before clinical implementation.

Humans↗

PubMed2026

Targeting SIRT6: the design and therapeutic implications of activators and inhibitors.

Sirtuin 6 (SIRT6) is an NAD+-dependent deacylase that maintains genomic stability, regulates metabolism, and influences aging, making it an attractive but challenging therapeutic target. Pharmacological modulation of SIRT6 holds promise for cancer and metabolic disorders, yet its context-dependent functions demand precise intervention strategies. Potent, selective, and drug-like chemical probes are therefore essential to dissect SIRT6 biology and to validate its therapeutic potential. This review critically evaluates recent medicinal chemistry advances in SIRT6 modulation. We focus on structure-guided design strategies and structure-activity relationships (SAR) that have transformed initial hits into optimized leads for both activators and inhibitors, highlighting the remaining challenges in achieving isoform selectivity and drug-like properties.

Sirtuins↗

PubMed2026

Analysis of end-stage renal disease mediated by cuproptosis-related genes.

OBJECTIVE: The complex pathophysiological mechanism of end-stage renal disease (ESRD) has not been fully understood. Cuproptosis is a newly discovered type of programmed cell death. Therefore, this study attempts to clarify the relationship between cuproptosis-related genes (CRGs) and the phenotype of ESRD. MATERIALS AND METHODS: The National Center for Biological Information Gene Expression Omnibus database was applied to obtain the GSE37171 dataset comprising whole-genome microarray analysis of peripheral blood samples. A 3 : 1 case-control design was employed with 75 ESRD patients and 20 healthy controls who were frequency-matched for age, sex, and ethnicity. Based on differentially expressed genes (DEGs) and genes related to cuproptosis, CRGs were identified. Thereafter, we explored two different subpopulations based on the cuproptosis gene and analyzed their expression and immune infiltration. Genes specific to the CRG cluster were identified through the weighted gene co-expression network analysis algorithm, and the best prediction model was determined and verified by four machine learning methods. RESULTS: The study identified 14 differentially expressed CRGs, among which ATP7B, SLC31A1, LIAS, LIPT1, DLD, MTF1, CDKN2A, DBT, and DLST had relatively high expression levels in the ESRD samples. Compared with the control group, expression levels of FDX1, DLAT, PDHA1, PDHB, and GLS were significantly lower in the ESRD group, and CRGs played a key role in the regulation of immune infiltration in ESRD. Two cuproptosis-related molecular clusters were identified in the ESRD samples. Cluster2 was more correlated with the immune infiltration of ESRD. By analyzing the intersection points between CRG cluster and key genes of ESRD, a total of 888 specific DEGs were identified. Functional differences related to specific DEGs were further explored using gene set variation analysis. Five significant genes (SMC5, USP47, USP53, AGA, and DMXL1) were identified by the support vector machine model as key predictors for ESRD disease risk, achieving an area under the curve (AUC) of 1.00 in internal validation. However, external validation in independent cohorts is required prior to clinical application. Individual gene analysis showed an AUC > 0.81 in discriminating ESRD patients from healthy controls, and the expression of all 5 genes in ESRD patients was significantly lower than in the control group. CONCLUSION: This study clarified the relationship between CRGs and the phenotype of ESRD, analyzed their specific roles in the immune microenvironment, and obtained a predictive model, providing new insights for the study of its potential therapeutic targets.

Humans↗

PubMed2026

Breastfeeding Outcomes After Radiofrequency Ablation and Surgical Excision of Fibroadenomas Compared to Natural History: A Retrospective Cohort Study.

BACKGROUND: Fibroadenomas, common benign breast tumors in women of reproductive age, are increasingly managed with minimally invasive radiofrequency ablation (RFA) or surgical excision. However, their impact on breastfeeding outcomes remains underexplored. We aimed to assess breastfeeding ability and breast tissue changes in women treated with RFA or surgery compared to those with untreated fibroadenomas. METHODS: In this retrospective cohort study, we evaluated 153 women with biopsy-confirmed fibroadenomas across five groups: RFA with prior breastfeeding (RFA-PreBF; n = 26), RFA with posttreatment breastfeeding (RFA-PostBF; n = 22), surgical excision with prior breastfeeding (Surgical-PreBF; n = 30), surgical excision with posttreatment breastfeeding (Surgical-PostBF; n = 20), and noninterventional with breastfeeding (Observation-BF; n = 55). Breastfeeding ability was assessed using a 5-point scale, and breast tissue changes were evaluated via ultrasound at 18 months, and all breastfeeding attempts occurred at a minimum of 12 months postprocedure. Fisher's exact test compared complete lactation failure rates, and a power analysis validated the study design (Fig. 1). FINDINGS: The combined RFA group (n = 48) had a higher complete lactation failure rate (14.6%) than the Observation-BF group (3.6%; Fisher's exact test, p = 0.045). Similarly, the combined surgical group (n = 50) had a higher complete lactation failure rate (16.0%) than the Observation-BF group (p = 0.034). When pooled, the combined intervention group (n = 98) showed a complete lactation failure rate of 15.3% versus 3.6% in the Observation-BF group. Residual tissue correlated with lactation impairment in the RFA group (Spearman's ρ, p < 0.05). Ultrasound showed no tumor recurrence, with cystic changes in some cases not linked to breastfeeding impairment. Power analysis confirmed 80% power to detect a medium effect size (f = 0.25, Fig. 1), supporting the study's robustness.7 RFA-PreBF (n = 26), RFA-PostBF (n = 22), Surgical-PreBF (n = 30), Surgical-PostBF (n = 20), and Observation-BF (n = 55). Breastfeeding ability was assessed using a 5-point scale, and breast tissue changes were evaluated via ultrasound at 18 months. Fisher's exact test compared complete lactation failure rates, and a power analysis validated the study design (Fig. 1).[Figure: see text]Interpretation:RFA and surgical excision are effective for fibroadenoma management but increase the risk of complete lactation failure compared to untreated fibroadenomas. Careful patient selection, precise procedural techniques, and vigilant posttreatment monitoring are essential to optimize breastfeeding outcomes, particularly for women planning future pregnancies.

Humans↗

PubMed2026

Quality of life and gender identity in females with congenital adrenal hyperplasia after genital restoration surgery: A single-center experience.

BACKGROUND: Legislation restricting surgical interventions in children with differences of sex development (DSD) has intensified debate about female genital restoration surgery (FGRS) in patients with congenital adrenal hyperplasia (CAH). Long-term patient-reported outcomes are needed regarding the optimal timing of surgery. OBJECTIVE: We aimed to assess health-related quality of life (HRQoL), gender identity, and family satisfaction regarding surgical timing and outcome in females with CAH following genital restoration surgery. STUDY DESIGN: Cross-sectional survey of CAH patients who underwent surgery between January 2007 to December 2016 at our institution. Validated instruments (KINDL questionnaire for HRQoL, Utrecht Gender Dysphoria Scale, UGDS) and structured telephone interviews were employed. RESULTS: Data on HRQoL was available for 25 patients (self- and/or parent-reported) out of 56 eligible patients (45% response rate). Median age at first surgery was 6 months (range: 3-137 months). Patients' age at time of participation ranged from 2 to 28 years. All had 21-hydroxylase deficiency (92% salt-wasting form) with Prader grades ranging from II-V. Wound dehiscence requiring secondary suturing occurred in 15% of patients with primary surgery at our center, while only one (4%) patient developed vaginal stenosis after early primary vaginoplasty. Two additional patients (8%) with prior outside surgery required vaginal revision after FGRS at age 12. HRQoL scores were comparable to healthy reference populations across most age groups. Children aged 3-6 and adolescents and young adults showed no significant difference from reference values, while children aged 7-13 showed a slight elevation. None of five patients ≥14 years demonstrated gender dysphoria (all UGDS scores <40, threshold ≥40). 14 patients and families were also interviewed by telephone. All preferred early surgical timing. No family expressed regret about the decision or preferred delayed surgery. DISCUSSION: This study provides validated intermediate-term patient- and parent-reported outcomes after FGRS in CAH. Key limitations include the small sample size, single-center design, and young age of most patients. Selection bias may exist, though participating families included those who underwent revision surgery. The absence of a non-operated comparison group reflects current clinical reality, as nearly all CAH patients with urogenital sinus underwent surgical correction. CONCLUSIONS: Females with CAH reported normal HRQoL and a comfortable female gender identity after early FGRS. The patients and their families expressed a preference for early surgery. However, there is need for longer-term follow-up to assess sexual function and reproductive outcomes as well comparison of outcomes with a non-operated group.

Humans↗

PubMed2026

Hierarchical modeling of tumor subtypes in cell lines using large-scale genomic datasets.

Cancer cell lines (CLs) are widely used to study tumor biology and drug response, yet their translational relevance is often limited by inaccurate subtype annotations. Existing CL-tumor matching approaches are frequently constrained by flat classification schemes, weak subtype definitions, and the exclusion of normal tissue references, leading to potential confounding of tumor-specific and tissue-of-origin signals. To address these limitations, a hierarchical classification (HC) framework is presented in which CLs are aligned with patient tumors across biological resolutions, from organ to molecular subtype. Gene expression profiles from 802 CLs, 5,612 tumors from The Cancer Genome Atlas (TCGA) , and 8,939 non-cancerous tissues were integrated to separate oncogenic signals from tissue-specific signals. Node-specific features were selected using maximum relevance minimum redundancy, and balanced accuracies of 89% in cross-validation and 75%, and 80% on external datasets were achieved. Through the framework, 43 CLs were reassigned, and clinically relevant underrepresented subtypes were identified.

cancer cell lines↗

PubMed2026

Discovery and characterization of multifunctional bioactive peptides from Alaska Pollock (Gadus chalcogrammus) milt: hybrid in silico, in vitro, and proteomic approaches.

The growing demand for multifunctional bioactive peptides has sparked interest in underutilized marine by-products as sustainable bioresources. This study explored Alaska Pollock (Gadus chalcogrammus) milt protein as a novel source of peptides with anti-inflammatory, anti-hypertensive, and anti-diabetic effects. Protein composition was analyzed via LC-MS, followed by in silico digestion and bioactivity prediction. Molecular docking identified peptides targeting DPP-IV, α-glucosidase, ACE, GLP-1 receptor, COX-2, MuRF1, and the 20S proteasome. Among the candidates, a promising peptide (CLPPH) was synthesized and validated in vitro, demonstrating inhibitory effects on nitric oxide production, DPP-IV, ACE, and α-glucosidase. These results highlight CLPPH's potential as a multifunctional bioactive peptide and support the valorization of Alaska Pollock milt as a sustainable source for functional foods and nutraceutical applications.

Animals↗

PubMed2026

Comprehensive quality profiling and comparative metabolic characterization of seven dominant fresh-eating Chinese olive (Canarium album Lour.) cultivars in Southern China.

Fresh-eating Chinese olive (Canarium album Lour.) is a subtropical fruit endemic to southern China with considerable commercial value, yet systematic quality characterization of dominant cultivars remains scarce. This study established a multi-dimensional quality dataset for seven dominant cultivars from Fujian and Guangdong provinces, integrating nutritional components, soluble sugars, organic acids, mineral elements, volatile profiles, and non-targeted metabolomics. Significant cultivar-specific differences were observed across all evaluated dimensions: "Lingfeng" exhibited a sugar-dominant low-acid profile, whereas "Sanleng" showed elevated phenolic constituents accumulation. Volatile profiling identified terpenoid-based candidate discriminatory biomarkers, and metabolomic analysis revealed phenylpropanoid biosynthesis, tryptophan metabolism, and starch and sucrose metabolism as the most variable pathways. Correlations between untargeted profiling and targeted absolute quantification validated untargeted result reliability and revealed their complementarity in nutritional evaluation. These findings provide baseline data for FECO germplasm evaluation and targeted industrial utilization.

China↗

PubMed2026

Family-Wise Error Rate Control in Clinical Trials With Overlapping Populations.

We consider clinical trials with multiple, overlapping patient populations that test multiple treatment policies specifically tailored to these populations. Such designs may lead to multiplicity issues, as false statements will affect several populations. For type I error control, often the family-wise error rate (FWER) is controlled, which is the probability to reject at least one true null hypothesis. If the joint distribution of the test statistics is known, the FWER level can be exhausted by determining critical values or adjusted-levels. The adjustment is typically done under the common ANOVA assumptions. However, the performed tests are then only valid under the rather strong assumption of homogeneous null effects, that is, when the null hypothesis applies to all subpopulations and their intersections. We show that under cancelling null effects, when heterogeneous effects cancel out in some or all subpopulations, this procedure does not provide FWER control. We also suggest different alternatives and compare them in terms of FWER control and their power.

Humans↗

PubMed2026

Modelling the effects of biological intervention in a dynamical gene network.

Cellular response to environmental and internal signals can be modeled by dynamical gene regulatory networks (GRN). In the literature, three main classes of gene network models can be distinguished: (1) non-quantitative (or data-based) models which do not describe the probability distribution of gene expressions; (2) quantitative models which fully describe the probability distribution of all genes co-expression; and (3) mechanistic models which allow for a causal interpretation of gene interactions. We propose two rigorous frameworks to model gene alteration in a dynamical GRN, depending on whether the network model is quantitative or mechanistic. We explain how these models can be used for design of experiment, or, if additional alteration data are available, for validation purposes or to improve the parameter estimation of the original model. We apply these methods to the Gaussian graphical model, which is quantitative but non-mechanistic, and to mechanistic models of Bayesian networks and penalized linear regression.

Gene Regulatory Networks↗

PubMed2026

Environmentally relevant concentrations of DCOIT impaired lifespan and healthspan in Caenorhabditis elegans.

DCOIT (4,5-dichloro-2-n-octyl-4-isothiazolin-3-one) is an antifouling biocide widely used as an alternative to organotin compounds. While previous studies had focused on its effects on energy production, endocrine disruption, and lipid metabolism, its impact on aging and underlying mechanisms remained unclear. Here, we demonstrated that environmentally relevant concentrations of DCOIT (37, 370 and 3700 ng/L) significantly impaired both lifespan and healthspan in Caenorhabditis elegans. RNA-seq and validation assays revealed that DCOIT upregulated comt-4, a key gene in dopamine metabolism, leading to dopamine depletion and subsequent induction of oxidative stress. This redox imbalance critically contributed to accelerated aging phenotypes. Importantly, both genetic (comt-4 RNAi) and pharmacological (opicapone) interventions restored dopamine levels, alleviated oxidative stress, and reversed DCOIT-induced aging deficits. Our study established the comt-4/dopamine/oxidative stress axis as a central mechanism in DCOIT toxicity, suggesting dopamine modulation as a potential countermeasure against environmental toxicant-induced aging.

Animals↗

PubMed2026

Effectiveness of Wearable Digital Therapeutics in Improving Sleep Outcomes Among Individuals With Insomnia: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Wearable devices are increasingly used for sleep monitoring and as adjunctive treatment. Existing meta-analyses mostly pool composite digital therapies and rarely isolate stand-alone wearables or distinguish between objective and subjective end points. Whether stand-alone wearable interventions improve sleep outcomes in adults with insomnia, and which factors moderate treatment heterogeneity, remains unclear. OBJECTIVE: This study aims to evaluate the effectiveness of wearable digital interventions on sleep outcomes in adults with insomnia versus control strategies and explore moderators of effectiveness, including device-wearing position, intervention duration, and control type, using meta-regression. METHODS: This systematic review and meta-analysis was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta‑Analyses) 2020 statement and the PRISMA-S (Preferred Reporting Items for Systematic Reviews and Meta‑Analyses Literature Search Extension) guideline. Five electronic databases and clinical trial registries were searched from inception to May 18, 2026. Eligible studies were randomized controlled trials (RCTs) evaluating wearable digital interventions in adults with insomnia compared with sham, waitlist, usual care, or active control conditions and had an intervention duration of at least 1 week. Study screening, data extraction, and risk-of-bias assessment were carried out independently by 2 reviewers. Pooled estimates were calculated using a restricted maximum likelihood random-effects model with the Hartung-Knapp-Sidik-Jonkman correction. Heterogeneity was assessed using the I² statistic, and 95% prediction intervals (PIs) were calculated for the primary analyses. The certainty of evidence was rated using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) approach. RESULTS: Sixteen RCTs (N=910) were included. Wearable digital interventions were associated with a significant reduction in objective sleep-onset latency (SOL; mean difference [MD] -4.52, 95% CI -8.38 to -0.67, PI -9.52 to 0.47 min) and a significant improvement in subjective sleep efficiency (SE; MD 2.00%, 95% CI 1.90%-2.11%, PI 1.85%-2.15%). Subjective total sleep time (TST) also showed a significant increase (MD 19.11, 95% CI 2.98-35.24, PI -16.20 to 54.43 minutes). Meta-regression showed that control type, intervention duration, and device location did not explain the heterogeneity of the insomnia severity index (ISI) (R²=0). Sensitivity analysis confirmed the robustness of pooled ISI estimates, and an Egger test indicated no small-study effects (P=.07). Certainty of evidence ranged from moderate to high. CONCLUSIONS: Wearable digital interventions provide selective benefits for objective SOL, subjective SE, and subjective TST in adults with insomnia, with no improvement in overall ISI. Despite statistically significant effects on several sleep parameters, wide PIs, substantial heterogeneity, and limited study numbers indicate preliminary, nonconclusive findings. Wearables should be viewed as affordable adjunctive tools requiring further validation, not substitutes for first-line cognitive behavioral therapy for insomnia. Large-scale, long-term RCTs with standardized protocols and patient-level external validation are required to consolidate the evidence base.

Humans↗

PubMed2026

Urban Design Quality and Clinical Mental Health: A Systematic Review.

ObjectivesThis systematic review synthesizes empirical evidence on core urban design dimensions that affect clinical mental health outcomes and examines how environmental exposures mediate or moderate these relationships.BackgroundUrban design has increasingly been recognized as a determinant of psychological well-being, yet a standardized framework to evaluate its mental health impact remains underdeveloped.MethodsFollowing PRISMA 2020 guidelines, we systematically reviewed 19 quantitative empirical studies published through January 2025, examining relationships between outdoor urban design features and validated clinical mental health indicators across four major databases.ResultsFindings reveal that urban design influences clinical mental health outcomes (depression, anxiety, stress, cognitive decline) through two objective spatial scales: street-level features (imageability, enclosure, human scale, complexity) and neighborhood environments (land use mix, density, green infrastructure). Environmental exposures (traffic, noise, air pollution) operate as perceptual and experiential mechanisms that mediate or moderate the mental health effects of these spatial design features.ConclusionsWe propose an integrated three-domain conceptual framework distinguishing objective spatial design scales from subjective exposure mechanisms. This framework provides evidence-based guidance for urban planners and policymakers toward creating mentally healthier urban environments.

Humans↗

PubMed2026

Strategies for mosaic variant calling in brain disorders.

The human brain is a genomic mosaic, where postzygotic mutations arising from embryogenesis to senescence drive diverse neurodevelopmental and neurodegenerative diseases. Because of numerous sequencing artifacts at ultralow variant allele frequencies (VAFs), detecting these variants remains a significant analytical challenge. This review focuses on single-nucleotide variants and small indels, summarizing current strategies for aligning sampling methods, including bulk, laser capture microdissection, and single-cell genomics, with the expected clonal architecture of the brain. It emphasizes that mosaic detection sensitivity is fundamentally constrained by sequencing depth, since even the most advanced algorithms cannot identify variants not physically represented in the sequencing library. The review further recommends the selection of variant calling algorithms based on validated VAF detection performance, matching tools like MuTect2 and MosaicForecast to their optimal performance ranges. Furthermore, we discuss how multitissue sampling, as emphasized by the SMaHT project, addresses the matched-control dilemma and supports accurate variant classification via cross-tissue VAF gradients. Integrating these established pipelines with multiomics modalities, including transcriptomic and epigenetic data, could advance the field toward a functional understanding of how the somatic genome impacts human brain health and disease.

Humans↗

PubMed2026

ORBIT: Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space for cancer driver gene identification.

Accurate identification of cancer driver genes is crucial for precision oncology but remains challenging due to the complexity of integrating heterogeneous data and modeling dynamic biological systems. To address these limitations, we propose ORBIT (Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space). Our framework synergistically fuses multi-omics profiles with functional network data using a context-adaptive graph reweighting mechanism to capture cancer-specific dynamics. The model employs a bi-prototype contrastive learning strategy within hyperbolic space, which aligns gene representations around distinct driver and non-driver semantic anchors while preserving the intrinsic hierarchy of biological networks. Comprehensive evaluations demonstrate that ORBIT achieves highly competitive stability in pan-cancer analysis while consistently outperforming state-of-the-art methods in cancer-specific predictions. Furthermore, functional enrichment analysis confirms that the model effectively segregates core cancer pathways, and drug sensitivity profiling validates the clinical relevance of the identified drivers. By integrating hyperbolic geometry with context-adaptive learning, ORBIT offers a robust and interpretable paradigm for precision medicine. The source codes and datasets are publicly accessible at https://github.com/spcho-dev/ORBIT.

Humans↗

PubMed2026

From population to individual: advocating personalised digital tools for heat-health early warning in a changing climate.

Escalating heat extremes under climate change are imposing substantial health burdens, with 2023 and 2024 consecutively breaking global temperature records. Mounting evidence suggests that heatwaves elevate the risks of hospitalisation and mortality across multiple disease categories, including ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and acute kidney injury. Nonetheless, most existing heat-health warning systems remain primarily reliant on population-level predictions, and considering individual differences and disease-specific considerations when defining warning levels would benefit the effectiveness of early prevention for high-risk groups. In this Viewpoint, which is based on the framework of precision public health-delivering the right intervention to the right population at the right time-we propose a framework for personalised digital heat-health early warning tools comprising three dimensions: individualised, risk-stratified prediction models that generate tiered early warnings; personalised health prompts coupled with theory-informed behavioural interventions; and adaptive, equity-oriented alert delivery mechanisms tailored to diverse populations. Such tools have the potential to bridge precision disease prevention and climate adaptation, thereby helping to mitigate heat exposure risks and disease burdens, particularly among high-risk populations. Future implementation research will be essential to address substantial challenges related to feasibility, validation, and equity.

Journal Article↗