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PubMed2026

Toward real-time quantification of driving risks: a systematic review and research agenda of risk field theory.

In complex traffic systems, driving risk often evolves in a continuous and progressive manner prior to crash occurrence. How to effectively represent and analyze such latent risk states remains a central challenge in traffic safety research. In recent years, risk field-based approaches have introduced spatial and spatiotemporal continuous modeling paradigms, providing new perspectives for characterizing the distribution of traffic risk and its dynamic evolution. Motivated by the rapid growth of this research area and the lack of a systematic synthesis, this paper presents a comprehensive review of studies applying risk field theory to driving safety and traffic risk analysis. Following the PRISMA guidelines, relevant literature was collected through multi-database searches and analyzed using a combination of bibliometric analysis and qualitative review. The review systematically summarizes the theoretical foundations, modeling elements, data sources, analytical methods, and application domains of risk field-related research. Particular attention is given to studies that conceptualize traffic risk as a continuous field, complemented by a broader review of traffic risk factor literature to identify key elements and analytical dimensions involved in risk field modeling. On this basis, the paper synthesizes research progress in major application areas, including traffic safety state representation, driving behavior analysis, traffic conflict assessment, and autonomous driving and human-machine cooperative systems. Differences and commonalities among existing studies are compared in terms of modeling strategies, data support, and application scenarios. Through this systematic review, the paper clarifies the main research themes and methodological trends of risk field-based studies, providing a structured framework for understanding the evolution and application of this approach and offering methodological insights for risk perception modeling and safety-oriented decision support in intelligent transportation systems (ITS).

Humans↗

PubMed2025

The Results After One Year of an Experimental Protocol Aimed at Reducing Paratuberculosis in an Intensive Dairy Herd.

Paratuberculosis or Johne's disease is caused by Mycobacterium avium subsp. paratuberculosis (MAP). The disease is characterized by a chronic and incurable enteritis in ruminants and it is responsible for significant economic losses, also raising concerns about food safety and animal welfare. Effective control is hindered by diagnostic limitations, long incubation periods, and the environmental resistance of the pathogen. This study aimed to reduce the apparent prevalence of paratuberculosis in a single intensive dairy herd through an integrated approach that combines diagnostics and management strategies. All cows over 24 months of age were tested using both fecal PCR and ELISA serology. Digital PCR (dPCR) was used to quantify MAP shedding in fecal-positive animals, enabling prioritization for removal based on environmental contamination risk. Integrating diagnostic tools allowed the precise identification and quantification of high-risk animals. Meanwhile, structural improvements and biosecurity measures were implemented on the farm. Preliminary outcomes suggest a marked reduction in herd-level MAP prevalence, lowering the seroprevalence from 7.6% to 4.5% and the fecal PCR prevalence from 6.5% to 2.8%. This case highlights the effectiveness of combining laboratory testing (serology and molecular diagnostics) and targeted changes in farm management to control paratuberculosis in high-density dairy systems.

MAP↗

PubMed2025

Using homologous network to identify reassortment risk in H5Nx avian influenza viruses.

The resurgence of H5Nx reassortment has caused multiple epidemics resulting in severe disease even death in wild birds and poultry. Assessing H5Nx reassortment risk is crucial for designing targeted interventions and enhancing preparedness efforts to manage H5Nx outbreaks effectively. However, the complexity in H5Nx reassortment, driven by the diversity of influenza A viruses (IAVs) and wide range of hosts, has hindered the effective quantification of reassortment risk. In this study, we utilized a network approach to explore the reassortment history using a large-scale dataset. By inferring genomic homogeneity among IAVs, we constructed an IAVs homologous network with reassortment history embedded within it. We estimated the communities within the IAVs homologous network to represent the reassortment risk of various viruses, revealing diverse reassortment risks across different H5Nx viruses. Our analysis also identified the primary hosts contributing to reassortment: domestic poultry in China, and wild birds in North America and Europe. These primary hosts are critical targets for future H5Nx reassortment interventions. Our study provides a framework for quantifying and ranking H5Nx reassortment risk, contributing to enhanced preparedness and prevention efforts.

Animals↗

PubMed2026

Measuring economic efficiency in adult intensive care units: A systematic review of methods, metrics, and evidence.

OBJECTIVES: Intensive care units (ICUs) consume substantial hospital resources, yet "efficiency" is inconsistently defined and measured. This study systematically reviewed how economic efficiency has been conceptualised and quantified in adult ICUs and appraised the quality of evidence. METHODS: Following PRISMA 2020 and a PROSPERO-registered protocol (CRD420251107866), we searched MEDLINE, Embase, CINAHL, Cochrane Library and Web of Science (2000-August 2025), plus global grey sources. Eligible studies explicitly defined efficiency and reported an efficiency metric/model linking ICU inputs (e.g., staff, beds/capacity, time, consumables, or costs) to outputs/outcomes (e.g., throughput/discharges, length of stay/resource use, risk-adjusted mortality). Dual independent screening and extraction were performed. Study quality was appraised using MMAT, and findings were synthesised narratively (SWiM), given heterogeneity. RESULTS: 39 studies (2001-2025) from 17 countries were included, all from high-income or upper-middle-income settings. Four methodological families were identified: (1) frontier modelling (predominantly DEA; occasional SFA/RFDH), (2) benchmarking indicators (risk-adjusted mortality and LOS/resource-use ratios; "efficiency matrix" quadrant classification), (3) cost-outcome evaluations, and (4) operational/process metrics. Across families, variation in decision-making units, input/output selection, and risk adjustment limited comparability; long-term and patient-reported outcomes were absent, and equity considerations were uncommon. CONCLUSIONS: ICU efficiency research is feasible but fragmented and often methodologically limited. Standardised definitions, validated risk adjustment, uncertainty quantification, and inclusion of patient-centred and equity-relevant outcomes are needed before efficiency metrics can reliably inform value-based decision making.

Intensive Care Units↗

PubMed2026

Meta-ERS: an exposome-based risk score using non-genetic factors to guide osteoporosis prevention.

BACKGROUND: Osteoporosis is influenced by both genetic and environmental factors, yet the relative contribution of the exposome remains unclear. This study aimed to systematically identify non-genetic exposures related to osteoporosis and develop an exposome risk score (ERS) to evaluate individual osteoporosis susceptibility. METHODS: We conducted an exposome-wide analysis of 477,792 UK Biobank participants to identify key exposures associated with osteoporosis. The selected exposures were combined into a weighted Meta-ERS and validated in the Scotland/Wales cohort. The Meta-ERS was further compared with polygenic risk scores (PRS) and linked to plasma proteomics to explore underlying biological pathways. RESULTS: We identified 41 independent non-genetic exposures spanning socioeconomic status, mental health, sleep, diet, smoking, physical activity, environment, and marital status, with socioeconomic status and mental health emerging as the most significant drivers. Based on the identified exposures, we constructed eight domain-specific exposure risk scores and integrated them into a weighted Meta-ERS. The Meta-ERS (R2 = 5.1%; Proportion of Chi-Square = 14.3%) demonstrated an ability to explain osteoporosis variation that was on par with polygenic risk scores (R2 = 4.8%; Proportion of Chi-Square = 12.0%). Importantly, modifying unfavorable exposures mitigated the negative effect of PRS on osteoporosis, particularly among high PRS individuals (1.5- to 1.8-fold greater absolute risk reduction than in those with low PRS). Proteomic analyses further revealed potential mechanisms through which the exposome influences osteoporosis, including hormonal regulation, inflammation, ossification, muscle development, lipid metabolism, and accelerated bone aging. Among these, growth/differentiation factor 15 was identified as a key mediator protein, with a mediation proportion of 13.13%-36.52%. CONCLUSIONS: The Meta-ERS facilitates the quantification of individual osteoporosis risk and identifies modifiable exposures for targeted prevention. Its application can enable personalized risk stratification and guide lifestyle or environmental interventions.

Aged↗

PubMed2025

Association between NAFLD and liver cancer: A two-sample Mendelian randomization study.

Observational studies suggest an association between nonalcoholic fatty liver disease (NAFLD) and liver cancer, but its causal nature remains unclear. A 2-sample Mendelian randomization (MR) analysis was performed using NAFLD and liver cancer summary statistics from genome-wide association study databases. Instrumental variables satisfying the 3 core MR assumptions were selected. Causal effects were estimated using inverse-variance weighted, MR-Egger, weighted median, and other methods, followed by sensitivity and power analyses. All 4 MR analyses demonstrated a positive causal association between NAFLD and liver cancer risk [odds ratio > 1, inverse-variance weighted P < .001]. Sensitivity analysis indicated no significant level of multiplicity or heterogeneity in the instrumental variables, and individual single nucleotide polymorphisms had no significant impact on the results. However, statistical power was insufficient. This study provides the first MR evidence demonstrating a genetically predicted causal relationship between NAFLD and liver cancer that is consistent across subtypes. Sensitivity analyses confirmed the absence of horizontal pleiotropy or heterogeneity, strengthening the robustness of the findings. These results offer genetic support for early NAFLD intervention to reduce the risk of liver cancer. However, the limited statistical power highlights the need for larger-scale genome-wide association study to identify more and stronger genetic instruments for a more precise quantification of the causal effect of NAFLD on liver cancer risk.

Humans↗

PubMed2026

Improving the reliability of polygenic risk score-based prediction for cardiovascular and renal complications across ancestries in type 2 diabetes using Mondrian Cross-Conformal Prediction.

Polygenic risk scores (PRS) developed in European populations often show reduced predictive performance in non-European populations, limiting their clinical utility. This lack of transferability across ancestries remains a major challenge in genomic medicine and raises concerns about health equity. We aimed to evaluate whether uncertainty-aware prediction, implemented through Mondrian Cross-Conformal Prediction, improves the performance and reliability of polygenic risk score-based predictions across ancestries for nephropathy, stroke, and myocardial infarction in individuals with type 2 diabetes in a multi-ethnic cohort. We leveraged Mondrian Cross-Conformal Prediction (MCCP), an uncertainty quantification framework, combined with logistic regression applied to a multi-polygenic risk score (multiPRS) to predict the risk of nephropathy, stroke, and myocardial infarction in individuals with type 2 diabetes. Two training frameworks were evaluated: one using 4,098 individuals with type 2 diabetes of European ancestry from the ADVANCE trial for training and 17,574 White British, 1,145 South Asian, and 749 African UK Biobank participants for testing; and another using the 17,574 White British UK Biobank participants for training and the South Asian and African participants for testing. Logistic regression provided robust baseline performance across populations. On top of this baseline, MCCP did not improve performance but added capabilities absent from probability-based stratification: for each individual, it issued a prediction together with an explicit confidence and credibility level; it allowed a tolerated error level to be set in advance and delivered prediction sets respecting it in the majority of settings; and it flagged individuals for whom no reliable prediction could be made. Applying MCCP to PRS-based prediction thus enables uncertainty-aware risk stratification and improves the reliability of risk prediction across ancestries, providing a more equitable framework for clinical use.

Female↗

PubMed2026

Biomarkers of metastatic disease in pheochromocytoma and paraganglioma.

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors with variable metastatic potential. While metastatic disease occurs in approximately 10-20% of cases, its prediction remains a major clinical challenge, as no histological system has been universally validated to reliably identify aggressive tumors at diagnosis. This review aims to provide a comprehensive and updated overview of current and emerging biomarkers of metastatic risk in PPGL, encompassing histopathological scoring systems, genetic and molecular markers, biochemical phenotyping, liquid biopsy approaches, and imaging-based biomarkers. Among established markers, germline SDHB mutation status, loss of SDHB expression by immunohistochemistry, elevated plasma 3-methoxytyramine, and histopathological scoring systems, such as GAPP and COPPS, represent the most clinically validated tools for risk stratification. Emerging biomarkers - including somatic alterations in ATRX and TERT, genomic instability indices, tumor immune microenvironment characterization, circulating tumor DNA, and oncometabolite quantification - show promise in refining prognostic assessment but require prospective validation before routine clinical implementation. Accurate risk stratification in PPGL demands a multiparametric and dynamic approach, integrating clinical, genetic, biochemical, and molecular parameters. Future progress will depend on large prospective international cohorts, standardized biomarker platforms, and biomarker-driven clinical trial designs to translate emerging molecular knowledge into improved patient outcomes.

SDHB↗

PubMed2026

Human papillomavirus viral load as promising surrogate biomarker of cervical cancer risk and clinical outcome.

INTRODUCTION: Persistent high-risk human papillomavirus (HR-HPV) causes cervical precancerous lesions and cancer. While molecular HPV DNA testing offers superior sensitivity over cytology as a primary screening method, its limited specificity leads to unnecessary follow-up procedures. Therefore, identifying surrogate biomarkers to distinguish transient infections from clinically relevant, persistent ones is essential for improving risk stratification. A comprehensive literature search across PubMed/MEDLINE, Embase, Scopus, and Web of Science databases up to December 2025 identified studies evaluating HR-HPV viral load in cervical lesion progression. AREAS COVERED: Oncogenic HPV viral load, the quantity of HPV genomes in a sample, is a promising biomarker. Levels correlated positively with HR-HPV persistence, increasing the risk of high-grade lesions and invasive cervical cancer. Furthermore, quantification provides prognostic information regarding disease severity, therapeutic response, and post-treatment recurrence. EXPERT OPINION: Recent standardization and validation of multiplex real-time PCR techniques supports integrating HPV viral load into clinical pratice. Incorporating viral load assessment into screening and management algorithms could significantly enhance diagnostic precision, enable personalized follow-up, and guide therapeutic decisions for women with HR-HPV-associated cervical disease. Refining these protocols will ultimately minimize over-treatment while ensuring rigorous monitoring for high-risk patients.

Humans↗

PubMed2025

Proteome organ aging and cardiometabolic risk in a population at risk for heart failure.

BACKGROUND: Biological aging varies across individuals and tissues, influencing chronic diseases, including heart failure (HF). Emerging proteome techniques enable quantification of organ-specific aging acceleration (OAA), but whether OAA relates to HF severity and differs by sex remains unclear. We aim to assess the sex-related association between OAA of heart, artery and kidneys and HF severity, and to investigate relevant cardiometabolic risk factors of organ aging. METHODS: In 556 participants from the HELPFul cohort, we estimated predicted biological age for heart, artery, and kidneys using plasma proteomics and calculated OAA as the deviation from chronological age. Associations between OAA and HF stage, echocardiographic parameters, and cardiometabolic risk factors were evaluated using regression models. Composite indices, including triglyceride-glucose body mass index (TyG-BMI), c-reactive protein-triglyceride glucose index and triglyceride-to-HDL cholesterol ratio were assessed for associations with advanced OAA. RESULTS: Mean age was 63 ± 9 years; 65% were women. Patients were classified as HF stage A (35%), B (29%) and C/D (36%). Heart OAA was significantly associated with advanced HF (Stage C/D) in both sexes (OR = 1.12, 95% CI 1.03 to 1.23 in women; OR = 1.18, 95% CI 1.05 to 1.32 in men), while artery OAA was linked to HF only in women (OR = 1.10, 95% CI 1.01 to 1.18). Multi-organ aging (≥ 2 organs with advanced OAA) conferred over three-fold higher odds of being in Stage C/D. Heart OAA correlated with impaired cardiac structure and function, particularly reduced ejection fraction in men and increased left ventricular mass index in both sexes. Diabetes emerged as the most relevant factor of artery and kidney OAA. TyG-BMI was significantly associated with advanced kidney OAA, only in women (z-scored OR = 1.88, 95% CI 1.45 to 2.45). CONCLUSIONS: Proteome-derived organ aging correlates with HF severity, with possible sex-related patterns. Diabetes and higher TyG-BMI are associated with faster organ aging, which may reflect shared aging mechanisms between metabolic dysfunction and HF.

Humans↗

PubMed2026

Longitudinal Prediction of Retinal Sensitivity Based on Disease Progression Quantified From Optical Coherence Tomography in Geographic Atrophy.

PURPOSE: The purpose of this study was to analyze the association between disease progression of geographic atrophy (GA) from optical coherence tomography (OCT) with retinal sensitivity (RS) in microperimetry (MP) over a 2-year follow-up period. METHODS: This is a longitudinal analysis of the OAKS Phase-III clinical trial. Both study and fellow eyes with GA that underwent imaging with the Spectralis OCT and consecutive MP examination were eligible. Pointwise quantification of ellipsoid zone (EZ) thickness, EZ and retinal pigment epithelium (RPE) loss from OCT volumes was correlated with localized RS. A longitudinal predictive model using a Markov Chain framework was implemented to predict RS change over time based on OCT biomarkers. The modeling of morphological and functional progression was based on the fellow-eye cohort. RESULTS: A total of 39,681 MP points from 406 patients were analyzed. In the fellow eye cohort, baseline (BSL) EZ thickness was positively associated with RS (0.3 decibel [dB]/µm, P < 0.001). Decrease in EZ thickness between visits during follow-up was significantly associated with decrease in RS (0.1 dB / 1 µm change). RS was significantly lower in MP points within EZ loss during follow-up compared with MP points within the retina with measurable EZ (P < 0.001). The largest functional decline was observed within RPE loss, also associated with the highest probability of absolute scotoma (P < 0.001). Morphological progression to EZ and RPE loss was influenced by EZ thickness and the morphology of adjacent MP points (P < 0.001). CONCLUSIONS: Two exploratory endpoints were developed, namely quantification of EZ thickness and loss, and localized RS within high-risk OCT areas. RS decline during follow-up is associated with automatically quantified disease progression in OCT.

Humans↗

PubMed2026

A droplet digital PCR assay targeting 16 human papillomavirus genotypes.

Background. Cervical screening with high-precision assays such as human papillomavirus (HPV) DNA testing is essential for the detection and treatment of precancerous lesions. HPV genotypes have different oncogenic potential and require different clinical management, illustrating the importance of extended genotyping. HPV quantification has demonstrated clinical relevance in both diagnosis and treatment. Objective. To develop a droplet digital PCR assay for the detection and quantification of 16 HPV genotypes, with comparison to a commercial test and validation on clinical samples. Methods. Primers and probes were designed to target the E6 region of 16 HPV genotypes: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, 68, 73 and 82. Each target was evaluated to assess performance and reliability using synthetic DNA constructs, quantified international reference standards and clinical screening samples (n=303) genotyped using the Seegene Anyplex II HR HPV Detection assay. Results. Each assay demonstrated high target specificity, without cross-reactivity observed among the HPV genotypes selected. Using international molecular standards, the assay reliably detected high-risk genotypes across serial dilutions, with detection down to the level of one international unit or genome equivalent per microlitre. When applied to clinical samples with and without a histological diagnosis of cervical intraepithelial neoplasia 2 or worse (CIN2+), the assay reliably detected key HPV genotypes, with the exception of 7 of 234 (3%) of HPV-positive samples, all of which exhibited very low viral load. Conclusion. Although previous studies have described digital PCR methods targeting HPV E6, they have typically focused on a limited number of genotypes. This study expands upon existing methodology by introducing a sensitive and specific method for detection and quantification of 16 high-risk and potentially high-risk HPV genotypes.

PCR↗

PubMed2026

Aflatoxins and their biosynthetic precursors in lotus seeds: simultaneous UPLC-MS/MS determination, contamination profiling, and matrix-specific accumulation during Aspergillus flavus infection.

Aflatoxin (AF) contamination poses a severe global threat to food and medicinal material safety, yet existing research focuses on terminal AF metabolites while neglecting residual biosynthetic precursors, leading to potential underestimation of contamination risks. In this study, a UPLC-MS/MS method was established for the simultaneous quantification of six AFs and their five precursors in lotus seeds, with optimization of mass spectrum parameters, chromatographic separation conditions, and sample pretreatment. Method validation confirmed linearity (R2 > 0.99), LODs (0.03-0.36 μg/kg), and recoveries (76.53%-120.0%, RSD < 15%). Analysis of 41 natural lotus seed samples revealed a 63.4% AF contamination rate, dominated by B-group AFs, while O-methylsterigmatocystin (OMST) and versicolorin hemiacetal (VOH) were identified as the primary co-residual precursors with co-occurrence rates ≥ 50%. Notably, AFM1 was predominantly detected in natural samples with AFB1 concentrations exceeding 100 μg/kg. Artificial inoculation experiments further demonstrated that sterilization and sealing conditions modulated AF biosynthesis in lotus seeds, with non-sterilized and non-sealed groups showing delayed fungal metabolism and lower toxin accumulation. A significant linear correlation was observed between AFM1 and AFB1 levels (r = 0.94) in infected samples, demonstrating their accumulation levels are coupled with fungal overall metabolic flux. Given the high co-occurrence rate of OMST/VOH with AFB1 in natural samples, their individual and combined toxicities require in-depth investigation. This work deciphers matrix-specific AF dynamics in lotus seeds, supporting regulatory standard refinement (e.g., precursor inclusion) and targeted control (e.g., time-sensitive drying after harvest). Further studies will focus on exploring the molecular mechanisms of substrate-dependent AF synthesis.

Aflatoxins↗

PubMed2025

Analytical and clinical performance validation of HPV-SEQ, a novel NGS-based liquid biopsy platform for detection and quantification of human papilloma virus circulating tumor DNA.

BACKGROUND: Human papillomavirus (HPV) is the primary causative driver of oropharyngeal squamous cell carcinoma (OPSCC). Accurate detection of HPV-DNA is critical for risk stratification and management of OPSCC. However, assays designed to detect HPV in primary tumors do not allow monitoring of HPV-DNA over time, whereas commercially available droplet digital PCR-based methods for assessment of circulating cell free (cf)HPV-DNA in plasma remain suboptimal, hindering adaptation into clinical practice. We have developed HPV-SEQ, a novel next-generation-sequencing (NGS) based method for detection and quantification of HPV16/18 DNA in plasma of patients with OPSCC. METHODS: The assay uses primers targeting the L1 gene of HPV16 and HPV18 viral genomes and strain specific calibrators at a defined concentration to determine the ratio of native HPV to a known standard, enabling accurate reporting of patient-derived HPV16/18 viral load in a sample. This study was conducted using two different patient populations in addition to healthy donors and contrived material. All experiments were performed to fulfill several applicable analytical, performance and validation guidelines. RESULTS: A thorough analytical characterization and clinical validation of this platform demonstrates that HPV-SEQ detects cfHPV-DNA with exceptional limit of quantification and high precision, providing a foundation for integrating this platform into clinical settings. CONCLUSIONS: This ultra-sensitive HPV profiling method with optimal analytical performance may represent a significant advancement in risk stratification, treatment management, and post-treatment surveillance for patients with OPSCC.

Humans↗

PubMed2026

Development and validation of an LC-MS/MS method for the quantification of the KRASG12C inhibitor divarasib.

Divarasib is a newly developed covalent KRASG12C inhibitor, currently under clinical investigation in a phase 3 trial in patients with non-small cell lung cancer (NSCLC). At the moment, very limited pharmacokinetic data are publicly known. However, obtaining more insight into the pharmacokinetic properties of divarasib is important, since this may provide a better understanding of its efficacy and safety risks. Pre-clinical studies have been performed in mouse models to evaluate the effect of drug transporters and drug-metabolizing enzymes on the plasma exposure and tissue distribution of divarasib. Therefore, a reliable quantification method is required. To our knowledge, no bioanalytical assay of divarasib has been published yet. Therefore, in this study we developed and validated an assay to quantify divarasib in human plasma and in eight different mouse-related matrices, and partially in mouse plasma, using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The method was initially evaluated over a concentration range of 1-10,000 nM. However, due to carry-over observed at 10,000 nM, the validated calibration range was established at 1-2000 nM, with matrix-dependent LLOQs of 1-10 nM. Erlotinib was used as an internal standard and acetonitrile was utilized to perform protein precipitation as sample pretreatment. Divarasib demonstrated stability in human plasma and in mouse plasma and tissue homogenates under various experimental conditions. A pilot in vivo study showed the applicability of our validated LC-MS/MS method. Ongoing clinical trials may collect plasma samples, and this developed method enables quantification of divarasib in both mouse and human plasma samples.

Animals↗

PubMed2026

Artificial intelligence-derived myocardial fibrosis on cardiac magnetic resonance for prognosis in cardiomyopathy: A systematic review of a sparse evidence base.

BACKGROUND: Myocardial fibrosis on cardiovascular magnetic resonance (CMR), assessed by late gadolinium enhancement (LGE) and parametric mapping, is an established predictor of adverse events in cardiomyopathy. We assessed whether artificial intelligence (AI) quantification of fibrosis adds independent prognostic value. METHODS: We searched six databases, a clinical-trials register, and a preprint server from inception to 13 June 2026. Eligible studies used AI to generate a fibrosis marker in adults with ischemic or nonischemic cardiomyopathy, with covariate-adjusted outcomes over ≥12 months. Risk of bias was assessed using PROBAST, PROBAST+AI, and QUIPS. Fewer than three comparable studies precluded meta-analysis; certainty was rated using GRADE. RESULTS: Of 448 records (381 after de-duplication), 18 full texts were reviewed and two included, one peer-reviewed and one preprint. In an ischemic-cardiomyopathy registry (Ghanbari et al.; n = 216 analytic, 26 events), AI-derived dense LGE scar predicted arrhythmic events (univariable hazard ratio [HR] 2.35, 95% CI 1.33-4.15), and AI-derived but not manual scar improved discrimination beyond guideline criteria (area under the curve 0.63 to 0.68; p = 0.02). In a nonischemic dilated-cardiomyopathy preprint (Kim et al.; n = 347, 119 events), automated extracellular volume ≥30% predicted cardiovascular death or heart-failure hospitalization (adjusted HR 2.00, 95% CI 1.32-3.03). Both were at high risk of bias, with data-derived thresholds and no external validation. CONCLUSIONS: Across only two studies, AI-derived fibrosis was independently associated with adverse cardiovascular events, but its added value over manual quantification remains unproven. Certainty was very low. The evidence base is sparse and not yet ready for clinical use.

Humans↗

PubMed2026

Quantifying uncertainty of predictions from cancer progression models.

MOTIVATION: Cancer progresses through the accumulation of genomic events. Cancer progression models such as Mutual Hazard Networks (MHNs) describe this dynamic, enabling prediction of temporal event positions and patient-specific risks of acquiring mutations. However, current MHN analyses rely on single most likely models and do not quantify the uncertainty inherent to parameter estimation. Assessing forecast stability is essential before using them to anticipate treatment-relevant mutations, adapt targeted therapies, or prioritize monitoring of patients at elevated progression risk. RESULTS: We address a key prerequisite for the responsible clinical use of cancer progression models by making MHN-derived predictions uncertainty-aware. We present a Bayesian framework for MHN that uses Markov Chain Monte Carlo to sample from the posterior distributions of model parameters and derived predictions. For practical use we implemented the Random-Walk Metropolis, Metropolis-Adjusted Langevin Algorithm (MALA), and simplified manifold MALA samplers as part of the existing mhn Python package. Only MALA and smMALA were successful in sampling from MHN posteriors, with MALA performing best. While most MHN parameters and predictions showed low posterior variance, a small subset displayed greater variability across the posterior distribution. This differentiation cannot be obtained from a single most likely model, emphasizing the need for uncertainty quantification, especially in clinical contexts. As an illustrative example, posterior sampling identified a subgroup of STK11$-$, KRAS$+$ lung adenocarcinoma patients with a high predicted short-term risk-with low variance across posterior samples-to develop an STK11 mutation. This subgroup exhibited poorer survival under immunotherapy, resembling patterns observed in STK11+ patients. AVAILABILITY AND IMPLEMENTATION: Our implementation is part of version 1.2.0 of the mhn package (https://github.com/spang-lab/LearnMHN). All analyses including the code to produce all figures in this article can be found under https://github.com/huy29433/MCMC-sampling-for-MHN (https://doi.org/10.5281/zenodo.21160219).

Humans↗

PubMed2025

Quantitative temporal analysis of pancreatic islet T lymphocyte and macrophage infiltration heralded by serum IgE in congenic BioBreeding (BB) Gimap5-/- rats at risk for insulitis and acute onset diabetes.

OBJECTIVE AND DESIGN: The objective was to determine the association between serum IgE levels and the infiltration order of T lymphocytes and macrophages in pancreatic islets in relation to the loss of insulin and glucagon cells in presymptomatic congenic BB Gimap5-DP (Diabetes Prone) rats. MATERIAL: Congenic prediabetes BB Gimap5-DP and control Gimap5-DR (Diabetes Resistant) rats were followed every other day from 29 to 32 days of age until peak serum IgE (≤ 55 days of age). METHODS: Serum IgE was measured using ELISA. The HALO™ platform facilitated quantitative image analysis of infiltrating T lymphocytes, macrophages, and target organ insulin and glucagon cells. Whole genome sequencing (WGS) was employed to identify candidate type 1 diabetes genes. RESULTS: Serum IgE levels increased with age in normoglycemic BB Gimap5-DP rats. Quantification of infiltrating cells per mm2 in and around the islets indicated that T lymphocytes are the initial infiltrators, followed by macrophages. Elevated serum IgE levels inversely correlated with beta-cell mass (total mg insulin/mg pancreas). WGS refined the risk segment for islet inflammation to 1.02 Mbp, leaving 10 candidate genes, including Gimap4 and Gimap5. CONCLUSIONS: Elevated IgE levels herald T lymphocyte and macrophage infiltration. Pancreatic islet inflammation was linked to Gimap4, Gimap5, and other potential candidate genes on rat chromosome 4.

Animals↗