Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “AI modeling”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

867 records · Page 6Linked to original sources
PubMed2026

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry↗
PubMed2026

Combining neuromelanin-sensitive MRI and quantitative susceptibility mapping for enhanced diagnosis and differentiation of parkinson's disease: A systematic review.

BACKGROUND: Loss of dopaminergic neurones and iron deposition in the substantia nigra pars compacta (SNpc) are two major pathological hallmarks of Parkinson's disease (PD). Such changes can be visualised by advanced techniques including neuromelanin-sensitive MRI (NM-MRI) and quantitative susceptibility mapping (QSM). This systematic review investigates the diagnostic performance and methodological development of the integrated use of NM-MRI and QSM in PD. METHODS: The systematic search was performed in four databases (Scopus, PubMed, ScienceDirect, and Web of Science) according to the PRISMA 2020 guidelines until July 2026. Bias was assessed using QUADAS-2 and certainty of evidence was assessed using GRADE. RESULTS: Seventeen studies with 2228 participants were included. Combined NM-MRI and QSM consistently showed reduced neuromelanin volume/contrast and increased iron deposition in the SNpc of PD patients compared to healthy controls. Multimodal integration yielded a significant improvement in diagnostic accuracy (AUC values 0.86-0.99), and was able to successfully differentiate PD. Recent methodological advances included simultaneous acquisition sequences (e.g. MTC-GRE, STAGE, setMag) and AI-driven automated segmentation, which led to significantly reduced scan times and improved reproducibility. CONCLUSION: The combination of NM-MRI and QSM has a synergistic effect and provides powerful complementary biomarkers for the diagnosis and differential diagnosis of PD.

Humans↗
PubMed2026

The mighty microproteins: from versatile cellular regulators to precision medicine therapeutics.

Microproteins, are tiny proteins encoded by small open reading frame (sORF), translation of these non-canonical open reading frames (ncORFs) has been implicated in diverse biological processes and diseases. This review summarizes recent developments in the discovery, biogenesis, and functional characterization of microproteins, and their involvement in various disease, with special focus on their roles in cancer, cardiovascular, metabolic, neurodegenerative and immune-related disorders. We emphasize the regulation of key cellular pathways by microproteins, including mitochondrial homeostasis, apoptosis, metabolic reprogramming, and immune signaling, all of which affect disease initiation and progression. Emerging evidence also supports their potential as disease biomarkers and therapeutic candidates for precision medicine. Finally, the review critically discusses the current challenges including discrepancies in microprotein annotation, the limitations of ribosome profiling and proteogenomic approaches, the gap between computationally predicted and experimentally validated microproteins, and the need for rigorous orthogonal validation by means of CRISPR-based genome editing, ribosome release assays, mutational analysis, high-resolution mass spectrometry, and functional studies. Finally, we review recent development of AI-assisted ORF prediction, single-cell translatomics, spatial proteomics, and integrated multi-omics as emerging technologies reshaping. Microprotein discovery and functional annotation. Finally, we discuss the translational potential of microproteins and highlight the remaining challenges to clinical application, including peptide stability, pharmacokinetics, tissue-specific delivery, immunogenicity, and the need for rigorous preclinical and clinical validation. Together, this review provides an updated and critical overview of the rapidly evolving microprotein field and highlights future research priorities for translating these molecules into clinically useful biomarkers and precision therapeutics.

Microproteins↗
PubMed2026

Durvalumab and tremelimumab, with or without lenvatinib, combined with transarterial chemoembolisation in participants with embolisation-eligible hepatocellular carcinoma (EMERALD-3): a global, randomised, open-label, sponsor-blinded, phase 3 study.

BACKGROUND: Transarterial chemoembolisation (TACE), a standard treatment for embolisation-eligible hepatocellular carcinoma (HCC), induces tumour immune responses. Single tremelimumab regular interval durvalumab (STRIDE) is a standard treatment in advanced HCC. In this phase 3 trial, we assessed the efficacy and safety of STRIDE, with or without lenvatinib, plus TACE, in participants with embolisation-eligible HCC. METHODS: EMERALD-3 is a phase 3, randomised, open-label, sponsor-blinded study, conducted at 177 medical sites in 21 countries. Eligible participants were 18 years or older (aged &#x2265;21 years in Egypt or Singapore) at screening and had confirmed HCC (by imaging or histopathologically from biopsy specimen, surgery, or both) not amenable to curative surgery, curative ablation, or transplantation but amenable to TACE. Participants had Child-Pugh class A liver function, an Eastern Cooperative Oncology Group performance status of 0-1, and at least one measurable target intrahepatic lesion per modified Response Evaluation Criteria in Solid Tumours. Participants were randomly allocated in a 1:1:1 ratio to receive STRIDE plus lenvatinib plus TACE, STRIDE plus TACE, or TACE until each group reached its preplanned enrolment target of 175 participants. After the STRIDE plus TACE group reached its enrolment target, randomisation was adjusted to continue in a 1:1 ratio between the STRIDE plus lenvatinib plus TACE group and TACE group until approximately 275 participants were enrolled in each of these two groups. Randomisation used a centrally assigned interactive response technology system, stratified by region, baseline tumour burden, and previous palliative embolisation. In the STRIDE plus lenvatinib plus TACE group, on the first day, participants were given 300 mg tremelimumab intravenously, followed by 1500 mg durvalumab plus oral lenvatinib (8 mg for <60 kg bodyweight or 12 mg for &#x2265;60 kg bodyweight); participants then received 1500 mg durvalumab every 4 weeks plus once-daily lenvatinib for up to 36 cycles. In the STRIDE plus TACE group, participants were given 300 mg tremelimumab and 1500 mg durvalumab intravenously on the first day, followed by 1500 mg durvalumab every 4 weeks. The technique and number of TACE procedures were at the investigators' discretion, with the first procedure administered at least 7 days after the first dose of durvalumab in the two investigation treatment groups and within 7 days of random allocation in the TACE group. The primary endpoint was progression-free survival for STRIDE plus lenvatinib plus TACE versus TACE. Key secondary endpoints were overall survival for STRIDE plus lenvatinib plus TACE versus TACE and progression-free survival and overall survival for STRIDE plus TACE versus TACE. This study was registered with ClinicalTrials.gov (NCT05301842), with enrolment completed. FINDINGS: From March 28, 2022, to Nov 20, 2024, 1124 participants were screened. The full analysis set comprised 760 participants, who were randomly allocated to STRIDE plus lenvatinib plus TACE (n=293), STRIDE plus TACE (n=175), or TACE (n=292). 633 (83%) participants were male and 127 (17%) were female; 548 (72%) were Asian. At the first data cutoff (Sept 2, 2025); the overall median follow-up for progression-free survival was 10&#xb7;0 months (IQR 4&#xb7;6-17&#xb7;2); median follow-up for progression-free survival was 11&#xb7;0 months (IQR 4&#xb7;8-18&#xb7;4) for STRIDE plus lenvatinib plus TACE and 8&#xb7;3 months (4&#xb7;1-15&#xb7;5) for TACE. Median progression-free survival was 13&#xb7;0 months (95% CI 12&#xb7;2-16&#xb7;7) for STRIDE plus lenvatinib plus TACE versus 9&#xb7;8 months (8&#xb7;0-11&#xb7;4) for TACE (HR 0&#xb7;70 [95% CI 0&#xb7;57-0&#xb7;86]; p=0&#xb7;0007). At the second data cutoff (Feb 23, 2026) and a median follow-up for overall survival of 24&#xb7;6 months (IQR 16&#xb7;5-31&#xb7;5) for STRIDE plus lenvatinib plus TACE and 22&#xb7;9 months (14&#xb7;9-30&#xb7;2) for TACE, median overall survival was 39&#xb7;5 months (95% CI 34&#xb7;1-not reached) for STRIDE plus lenvatinib plus TACE and 34&#xb7;7 months (28&#xb7;8-not reached) for TACE (HR 0&#xb7;84 [95% CI 0&#xb7;65-1&#xb7;09]; p=0&#xb7;18). At this data cutoff, median progression-free survival was 12&#xb7;9 months (95% CI 10&#xb7;2-15&#xb7;9) for STRIDE plus TACE and 8&#xb7;1 months (6&#xb7;5-10&#xb7;2) for the first 175 participants randomised to TACE (HR 0&#xb7;71 [95% CI 0&#xb7;56-0&#xb7;91]), with median follow-up of 10&#xb7;3 months (IQR 4&#xb7;6-23&#xb7;7) for STRIDE plus TACE and 7&#xb7;7 months (3&#xb7;0-18&#xb7;5) for the first 175 participants randomly allocated to TACE. The most common adverse events of maximum grade 3 or 4 were hypertension (34 [12%] of 287) for STRIDE plus lenvatinib plus TACE, post-embolisation syndrome and anaemia (ten [6%] of 175 each) for STRIDE plus TACE, and post-embolisation (17 [6%] of 290) for TACE. 184 (64%) participants receiving STRIDE plus lenvatinib plus TACE, 89 (51%) receiving STRIDE plus TACE, and 68 (23%) receiving TACE had serious adverse events. Treatment-related adverse events with an outcome of death during the treatment-emergent period occurred in seven (2%) of 287 participants who received STRIDE plus lenvatinib plus TACE (two for myocarditis; and one each for hepatic failure, haemophagocytic lymphohistiocytosis, septic shock, cardiac failure, and unknown cause), none of 175 participants who received STRIDE plus TACE, and two (1%) of 290 participants who received TACE (one each for acute myocardial infarction and unknown cause). INTERPRETATION: STRIDE plus lenvatinib plus TACE showed a statistically significant progression-free survival improvement versus TACE. These findings support a STRIDE-based regimen as a potential new treatment option for people with embolisation-eligible HCC; additional follow-up is being conducted for final analysis of overall survival across treatment groups. FUNDING: AstraZeneca.

Adult↗
PubMed2026

Age-related differences in semen quality in Holstein-Friesian bulls: a paired within-bull comparison of early and mature reproductive stages.

Genomic selection has changed dairy cattle breeding by increasing the use of young bulls for artificial insemination and shortening the reproductive lifespan of sires. Under these conditions, semen quality at the beginning of commercial use has become an important practical issue. Semen samples from 39 fertile Holstein-Friesian bulls used for commercial AI were collected between 2013 and 2016, during the introduction of genomic selection in Poland. This paired within-bull study compared semen collected from the same bulls at an early reproductive stage (13-20 months; young bulls, YB) and at full maturity (5-6 years; mature bulls, MB). The evaluation included conventional ejaculate traits, CASA-derived motility and kinematic descriptors, mtDNA copy number, and mitochondrial content per sperm cell. Importantly, all ejaculates met the quality requirements for commercial insemination. Ejaculate volume, sperm concentration, mitochondrial DNA copy number, and mitochondrial content did not differ significantly between age groups. The CASA-derived sperm movement profile, in contrast, differed with age. Semen from young bulls showed a higher proportion of progressively motile spermatozoa, whereas semen from mature bulls showed higher velocity-related parameters, including VSL, VCL, and STR. These findings indicate that bull age mainly affected sperm movement characteristics rather than semen output or mitochondrial content. Overall, the results support the use of young bulls in artificial insemination programs and show that age-related differences in semen quality are expressed mainly through changes in the post-thaw sperm motility and kinematic profile.

Animals↗
PubMed2026

Emerging hantavirus risks in mass gatherings: epidemiology, diagnostic challenges, and outbreak preparedness.

Hantaviruses are emerging rodent borne zoonotic pathogens of increasing global public health concern because of their high mortality, expanding ecological distribution, and potential for international dissemination. Although traditionally associated with sporadic rural outbreaks, recent ecological disruption, climate variability, urbanization, and increased global mobility have heightened concerns regarding hantavirus risks in mass gathering settings. This review critically examines the epidemiology, transmission uncertainty, diagnostic and surveillance challenges, and preparedness strategies related to hantavirus infections in the context of mass gatherings, including religious events, refugee settlements, cruise tourism, sporting events, and temporary accommodations. Particular emphasis is placed on the 2026 multinational cruise ship associated outbreak linked to the MV Hondius, which highlighted vulnerabilities related to delayed diagnosis, international passenger dispersal, and uncertainties surrounding possible human to human transmission of Andes virus. Current evidence indicates that hantavirus transmission occurs primarily through inhalation of aerosolized rodent excreta; however, controversies regarding limited interpersonal transmission, environmental persistence, and asymptomatic infections continue to complicate risk assessment and outbreak preparedness. Diagnostic limitations, underreporting, insufficient environmental surveillance, and lack of mass gathering specific preparedness frameworks remain major public health challenges, especially in resource limited settings. Strengthening proactive preparedness through integrated One Health approaches, ecological surveillance, genomic monitoring, AI driven epidemic intelligence, and coordinated international response systems is essential for mitigating future risks. The review emphasizes the urgent need for multidisciplinary research and evidence based policy development to improve global preparedness against emerging hantavirus associated threats in increasingly interconnected mass gathering environments.

Humans↗
PubMed2026

Unravelling bioanalytical innovations, degradation processes, and impurity landscapes of VEGFR inhibitors.

From pre-formulation studies to clinical trials, VEGFR-targeted small-molecule tyrosine kinase inhibitors (TKIs) require rigorous analytical standards. Bioanalysis, stability-indicating studies, and impurity profiling are used to examine chromatographic advances for VEGFR-targeted TKIs like sunitinib, pazopanib, axitinib, sorafenib, cabozantinib, vandetanib, apatinib, lenvatinib, nintedanib, and regorafenib. An LC-MS/MS and UPLC-MS/MS routinely show sub ng/mL performance, as shown by LLOQs (0.2&#xa0;ng/mL) for sunitinib and axitinib, 1&#xa0;ng/mL for pazopanib, 5-7&#xa0;ng/mL for sorafenib, 0.5-1.5&#xa0;ng/mL for regorafenib metabolic products, and 0.1-0.5&#xa0;ng/mL for lenvatinib. These approaches are used for pharmacokinetics and therapeutic drug monitoring due to their good correlation coefficient of 0.1-10,000&#xa0;ng/mL, accuracy of 95%-108%, and precision of 15% RSD. UPLC-QTOF-MS/MS distinguishes degradants and metabolites during forced degradation studies, enabling structural elucidation following ICH M7 risk evaluation protocol. HPTLC/MLC offers fast, sensitive screenings, while RP-HPLC/DAD or HPLC-UV offer reliable, cost-effective routine quality-control solutions with LOD/LOQ in the &#x3bc;g/mL range and linearity of 10-240&#xa0;&#x3bc;g/mL. This review lists the structures and CAS numbers of ten VEGFR-2 TKI degradants and metabolites, as well as pharmacopeial impurities in SMILES forms. It will be useful for future method development and regulatory applications. To ensure VEGFR-targeted TKI quality, safety, and therapeutic efficacy, LC-MS/MS for trace quantification and HRMS for structure elucidation provide a robust, future-oriented framework. To improve VEGFR-targeted TKI quality, safety, and regulatory compliance, analytical development should focus on HRMS-based impurity characterization, AI-assisted degradation prediction, green chromatography, and harmonized bioanalytical validation.

Humans↗
PubMed2026

Associations between smart infusion pump-electronic health record interoperability and healthcare outcomes: A systematic review.

OBJECTIVE: This study synthesized available evidence on the associations between smart infusion pump-electronic health record (EHR) interoperability and healthcare outcomes. METHODS: A systematic review of PubMed, CINAHL, Embase, and Scopus databases identified 901 records, which were imported into Rayyan&#xae; for duplicate removal, independent screening by three reviewers, and resolution of discrepancies. Eligible studies were peer-reviewed, data-driven, and reported associations between smart infusion pump-EHR interoperability and healthcare outcomes. Studies focused solely on technical validation or interoperability prototypes were excluded. A backward citation search identified additional studies. Two reviewers independently extracted and cross-validated study characteristics using standardized templates. Methodological quality was assessed with the Joanna Briggs Institute Critical Appraisal Tools. RESULTS: Twenty records of 14 full-text studies and 6 conference proceedings were included. Most records reported positive associations between smart infusion pump-EHR interoperability and outcomes related to safety (e.g., medication administration errors, safety-reported events, pump alerts, and compliance with interoperability and drug library), operational efficiency (e.g., programming and documentation time and technical issues), financial performance (e.g., charges captured, and cost avoided), and user experience domains. Most studies used observational designs, reflecting real-world interoperability implementations, where controlling confounding factors is challenging. Limited reporting of baseline characteristics, pump type, and sample sizes limited comparability across studies. CONCLUSIONS: Smart infusion pump-EHR interoperability was associated with improvements in patient safety, efficiency, charge capture, and user experience, with variable findings across studies. Future research should use rigorous methodologies and standardized measures, examine relationships across outcome domains, assess limitations of pump-EHR interoperability, and evaluate underexplored outcomes, including team communication, cognitive workload, and AI-enabled pumps. IMPLICATIONS FOR CLINICAL PRACTICE: Interoperability should be viewed as a component of a broader sociotechnical system, in which technology, user, workflow, clinical content, and organizational practices collectively determine overall effectiveness.

Humans↗
PubMed2026

Effects of testosterone-augmented multimodal exercise intervention in spinal cord injury: a randomized controlled trial.

CONTEXT: Spinal cord injury (SCI) leads to profound muscle atrophy, aerobic deconditioning, and metabolic dysfunction. Exercise-based interventions alone produce modest benefits. Whether testosterone can augment physiologic responses to exercise in this population remains untested. OBJECTIVE: To evaluate efficacy and safety of home-based intervention combining functional electrical stimulation-assisted leg cycling (FES-LC), arm ergometry (AE), and testosterone compared with FES-LC, AE plus placebo in adults with SCI. METHODS: This randomized, placebo-controlled, double-blind trial enrolled 84 adults (76 males and 8 females) aged 19-70 years with SCI (neurologic levels C4-T12; AIS grades A-D). Participants were randomized to multimodality intervention (home-based FES-LC, AE and intramuscular testosterone undecanoate) (n = 38) or control intervention (FES-LC, AE plus placebo) (n = 46) for 16 weeks. The primary outcome was change in aerobic capacity (peak VO2) during AE cardiopulmonary exercise testing. Secondary outcomes included lean mass, hemoglobin, cardiometabolic markers, and safety. RESULTS: Mean (SD) age was 44 (13) years and time since injury was 13.9 (13) years). Between-group changes in peak VO2 were not statistically significant. Within-group improvements were larger in multimodality (&#x223c;19% increase; 0.10 L/min; 95% CI, 0.02-0.18 L/min) compared to controls (&#x223c;6% increase; 0.06 L/min; 95% CI, -0.01-0.13). The multimodality group gained significantly more lean mass (whole-body:1.84 kg, 95% CI: 0.52-3.16, P = .007; lower extremity 0.92 kg, 95% CI: 0.38-1.45, P = .001), and anemia was corrected in a greater proportion of participants. Adverse event rates were similar between groups. CONCLUSION: A home-based multimodality intervention combining FES-LC, AE, and testosterone was safe and associated with greater improvements in lean mass and hemoglobin. Although between-group differences in aerobic capacity were not statistically significant, greater within-group increases were observed in the multimodality group. These findings may inform future studies of testosterone-augmented exercise interventions for individuals living with SCI.

Humans↗
PubMed2026

Artificial intelligence enabled social robotic interventions (PARO) in Australian dementia care: A systematic review and meta-analysis.

BACKGROUND: Although there is a growing body of research indicating that Personal Robot/Social Robot could be used in various aspects of care for individuals with dementia, little is known about how well these types of interventions work in an actual hospital setting in Australia. AIMS & OBJECTIVES: The objective of the present systematic review and meta-analysis is to assess the effectiveness of PARO-based socially assistive robotic intervention in terms of its effectiveness outcomes towards the reduction of dementia-related behavioural and psychological symptoms in Australian based healthcare settings. METHODS: A systematic search was conducted across five electronic databases, including MEDLINE (PubMed), EMBASE, CINAHL, PsycINFO, and the Cochrane Library, to identify randomised controlled trials (RCTs) investigating PARO-based socially assistive robotic interventions for dementia in Australian healthcare settings. This review was registered with PROSPERO (CRD420251251916) and followed the PRISMA 2020 guidelines. In addition, the Cochrane Risk of Bias tool (RoB 2) was used to evaluate the risk of bias across all studies. Pooled standardised mean differences (SMD) with 95&#xa0;% confidence intervals (CI) were calculated for agitation, anxiety, and depression. Heterogeneity across studies was evaluated using the I2 statistic. RESULTS: Six RCTs involving 1444 participants were identified for inclusion in this review. AI-enabled socially assistive robotic interventions, specifically the PARO therapeutic robot, significantly reduced agitation and anxiety when compared to standard treatment or control conditions. The pooled analysis showed that agitation [SMD&#xa0;=&#xa0;-0.44 (95&#xa0;% CI: -0.70, -0.18) p&#xa0;=&#xa0;0.0008] and anxiety [SMD&#xa0;=&#xa0;-0.59 (95&#xa0;% CI: -0.91, -0.27) p&#xa0;=&#xa0;0.0003] were reduced significantly, while the decrease in depression [SMD&#xa0;=&#xa0;-0.44 (95&#xa0;% CI: -0.95, -0.07) p&#xa0;=&#xa0;0.09] scores was non-significant among dementia patients receiving PARO-based socially assistive robotic interventions as compared to the control. The overall risk of bias across all six studies was considered low to moderate. CONCLUSION: PARO-based socially assistive robotic interventions may provide preliminary evidence of effectiveness in reducing agitation and anxiety in individuals with dementia in Australian healthcare, but the evidence regarding the reduction of depression remains unclear. Therefore, additional high-quality trials with consistent methodology and extended follow-up will be necessary to determine both the short-term and long-term clinical efficacy and practicality of implementing these interventions into practice.

Humans↗
PubMed2026

Statistical test to compare the linkage model and the admixture model based on central limit results.

In the Admixture Model, the probability that an individual carries a certain allele at a specific marker depends on the allele frequencies in K ancestral populations and the proportion of the individual's genome originating from these populations. The markers are assumed to be independent. The Linkage Model is a Hidden Markov Model that extends the Admixture Model by incorporating linkage between neighboring loci. We prove consistency and asymptotic normality of maximum likelihood estimators for the ancestry of individuals in the Linkage Model, complementing earlier results by (Pfaff et al., 2004; Pfaffelhuber and Rohde, 2022; Heinzel, 2025) for the Admixture Model. These results are used to prove that a statistical test that allows for model selection between the Admixture Model and the Linkage Model is an asymptotic level-&#x3b1;-test. Finally, we demonstrate the practical relevance of our results by applying the test to real-world data from The 1000 Genomes Project Consortium (2015).

Genetic Linkage↗
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

The landscape of pruning for large language models: A systematic review and unified taxonomy.

Confronting the inherent tension between the exceptional capabilities and the immense computational costs of Large Language Models (LLMs), pruning has become a crucial technique for achieving efficient deployment. However, a systematic analytical framework dedicated specifically to LLM pruning remains absent. In this paper, we aim to bridge this gap. We first elucidate the theoretical foundations that underpin the effectiveness of pruning, namely overparameterization and redundancy, and then propose a multidimensional taxonomy that organizes existing approaches along the axes of granularity, timing, and criteria. Building upon this unified perspective, we further analyze performance recovery mechanisms and the broader evaluation ecosystem, while also exploring forward-looking challenges such as interpretability, automation, and hardware-algorithm co-design. Through this comprehensive synthesis, we seek to provide an integrated and coherent analytical lens for advancing both research and practice in LLM pruning.

Large Language Models↗
PubMed2025

An integrated multiscale air quality modelling framework for industrial park pollution: Linking local emissions to regional transport.

Capturing the spatiotemporal distribution of pollutants in industrial parks remains challenging for regional air quality models because of their coarse resolution (3 km), resulting in uncertainties in local emission quantification. To address this, we developed the Integrated Multiscale Air Quality Modelling System for Industry (IAQMS-Industry), coupling the regional Nested Air Quality Prediction Modelling System (NAQPMS) with a city-scale chemical transport model. This framework integrates point-source locations and Gaussian plume dispersion to simulate particulate matter with a diameter smaller than 2.5 micrometres (PM2.5) at 100 m resolution. Applied to the Beijing Yi Zhuang and Tangshan industrial parks and evaluated against observations. The coupled model achieved a normalized mean bias (NMB) ranging from 3.1 % to 6.2 %, improving upon NAQPMS (-16.9 % to -7.7 %). Spatial analysis revealed that coarse regional grids underestimated the PM2.5&#x200b; concentrations at industrial sites by smoothing gradients, whereas IAQMS-Industry successfully resolved spatial patterns. Industrial point emissions accounted for 22.9 %-26.4 % of PM2.5 in the coupled model, which was significantly greater than the regional model estimates of 1.6 %-13.7 %. These findings indicate that regional models overestimate pollutant dispersion processes in industrial parks while underestimating local industrial impacts. By explicitly resolving point-source dynamics and linking them to regional transport, IAQMS-Industry provides a robust tool for designing targeted emission controls in industrial cities and balancing local air quality improvements with minimized regional pollution outflow. This study underscores the necessity of multiscale modelling for accurate source apportionment and informed environmental governance in industrial zones.

Air Pollution↗
PubMed2026

Penalized Cumulative Probability Model for a Continuous Outcome Subject to Detection Limits.

Mixed-type outcome data occur when the outcome variable's distribution is a mixture of both continuous and discrete ordinal variables. Such mixed-type outcomes are common in biomedical, psychological, and the health sciences, particularly for variables having either a detection or quantitation limit. When interest lies in identifying a combination of genomic features associated with a mixed-type outcome, any method used would require a variable selection strategy for high-dimensional data. Unfortunately, few variable selection methods exist for modeling a mixed-type outcome when the covariate space is high dimensional. This study develops a high-dimensional penalized cumulative probability model (CPM), to allow for the identification of genomic features associated with mixed-type outcome of interest. We demonstrated how such model may be estimated using the iterative penalization procedure-the generalized monotone incremental forward stagewise (GMIFS) algorithm. The Model-X knockoffs procedure was combined with the estimation algorithm to control the false discovery rates (FDR) when performing variable selection. Through extensive simulation studies, our penalized CPM was shown to outperform alternative methods in terms of controlled variable selection performance by achieving high statistical power with the FDR being controlled at the target level. We demonstrate the utility of our method by applying it to predict estimated glomeruli filtration rate (eGFR) in kidney transplant recipients at 24&#x2009;months post-transplant using baseline gene expression data as predictors. Our CPM model identified five genes associated with this mixed-type outcome which have important links to renal disease, which may provide prognostic guidance for kidney transplantation recipients.

Models, Statistical↗
PubMed2026

Construction of precision clinical-proteomics risk model based on machine learning for predicting heart failure in type II diabetes mellitus.

BACKGROUND AND AIMS: Heart failure (HF) is a severe complication in type 2 diabetes mellitus (T2DM), but current risk stratification scores have limited predictive accuracy. We aimed to develop novel prediction tools integrating clinical variables with proteomics to improve risk stratification of hospitalization for HF in T2DM. METHODS AND RESULTS: In this study, we included 2111 UK Biobank participants with T2DM but no prior HF, and profiled 2920 proteins to predict 10-year incident HF hospitalization. Participants were randomly divided into training (70%), tuning (10%), and validation (20%) sets.Three prediction models were developed: a Clinical model based on demographic characteristics, comorbidities, medication use, and laboratory indices; a Protein model based on 40 proteins selected by the Light Gradient Boosting Machine (LGBM); and the Clinical OMics and Protein ASSessment for Heart Failure (COMPASS-HF) model, which integrated both clinical variables and the LGBM-selected proteins. Models were evaluated for area under the curve (AUC), sensitivity, and specificity. During follow-up, 168 participants (7.96%) developed incident HF. The COMPASS-HF model showed better discrimination than the Clinical model, with an AUC of 0.897 (95% CI: 0.850-0.945) versus 0.790 (95% CI: 0.723-0.856). It also demonstrated higher sensitivity (0.882; 95% CI: 0.725-0.967) and consistent performance in subgroups. COMPASS-HF effectively stratified risk of hospitalization for HF, with cumulative incidence rates of 31.9% in the high-risk group and 1.2% in the low-risk group. CONCLUSIONS: By combining clinical and proteomic variables, we developed a high-performance HF prediction model for T2DM, enabling precise risk stratification and informing early intervention strategies.

Humans↗