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PubMed2026

Outcomes and Associated Prognostic Factors for Orthograde Canal Obturation Using Ortho MTA III: A Randomised Prospective Clinical Trial.

AIM: To prospectively compare treatment outcomes for orthograde canal obturation using Ortho MTA III (OMTA) with the continuous wave of compaction (CWC) using gutta-percha (GP) and AH Plus sealer, and to identify associated predictive factors. METHODOLOGY: Informed consent was obtained (110 patients), and single- or two-rooted permanent teeth (n = 120) diagnosed with pulp necrosis (or previously treated) and asymptomatic apical periodontitis or chronic apical abscess (periapical index, PAI ≥ 3) were randomly assigned to two groups (n = 60/group). The canals were prepared to a minimal apical size #40 (ISO) based on their initial file size, disinfected and obturated by either CWC or OMTA using an enhanced disinfection protocol (GP disinfected, new gloves after each intraoperative radiograph and before starting obturation). Clinical and periapical radiographic examinations were conducted by two calibrated, independent endodontists during follow-up periods of at least 12 months. Success rates and associated predictive factors (tooth-, operator- and patient-related) were analysed statistically using binary and multiple logistic regression (p < 0.05). RESULTS: The median recall period was 30 months (14-48 months), and 104 teeth were finally analysed (recall rate: 86.67%). No significant differences in success rate were observed between the groups (p > 0.05) under both loose (OMTA: 88.24%, CWC: 83.02%) and strict criteria (OMTA: 64.71%, CWC: 58.49%). Multivariate analysis revealed that age (OR = 5.735, 95% CI: 1.286-25.577, p = 0.022), periapical lesion size (OR = 6.596, 95% CI: 1.397-31.138, p = 0.017) and PAI score (OR = 2.081, 95% CI: 1.047-4.136, p = 0.036) were significant predictors of treatment failure. CONCLUSIONS: Orthograde obturation of infected canals with Ortho MTA III demonstrated comparable success and treatment outcomes to those filled with GP and sealer by CWC, supporting its potential as a clinically viable alternative for the obturation of infected root canals. TRIAL REGISTRATION: cris.nih.go.kr registration number: KCT00099939.

Humans↗

PubMed2026

Impact of a multimodal prehabilitation program on postoperative cognitive dysfunction: a single-center randomized controlled trial.

BACKGROUND: Postoperative cognitive dysfunction (POCD) is a frequent complication after cardiac surgery. Exercise-based prehabilitation may enhance functional reserve and reduce vulnerability to perioperative cerebral insults. We hypothesized that multimodal prehabilitation reduces POCD 3 months after cardiac surgery. METHODS: This prespecified substudy of a single-center randomized controlled trial (NCT03466606) included patients aged ≥50 years undergoing elective coronary artery bypass grafting and/or valve surgery. Participants were randomized 1:1 to 4-6 weeks of multimodal prehabilitation (exercise training, nutritional support, and psychological support) or standard preoperative care. Cognitive function was assessed at baseline and 3 months postoperatively using an age- and education-adjusted neuropsychological battery. POCD was defined as performance ≥1.5 standard deviations below normative values in at least 2 cognitive tests, excluding the Mini-Mental State Examination. Logistic regression analyses were performed to evaluate factors associated with POCD. RESULTS: Of 160 participants screened from the parent trial, 134 met eligibility criteria for the substudy and were randomized; 116 completed 3-month follow-up (prehabilitation n = 53; control n = 63). POCD occurred in 29 patients (25%), including 15/53 (28%) in the prehabilitation group and 14/63 (22%) in controls (odds ratio [OR] 1.37, 95% confidence interval [CI] 0.54-3.50, P = 0.52). In multivariable analysis, preoperative cognitive impairment was independently associated with POCD (OR 13.28, 95% CI 4.06-43.41, P < 0.001), whereas prehabilitation was not (OR 1.09, 95% CI 0.35-3.45, P = 0.877). Higher physical activity levels at 3 months were associated with lower odds of POCD (OR 0.97, 95% CI 0.95-1.00, P = 0.047). CONCLUSIONS: In this randomized controlled trial, a 4-6-week multimodal prehabilitation program did not reduce postoperative cognitive dysfunction 3 months after cardiac surgery. Although the intervention did not achieve measurable cognitive protection, the observed association between postoperative physical activity levels and postoperative cognitive dysfunction warrants further investigation.

Humans↗

PubMed2026

The Association Between NT-Pro BNP, Nephropathy and Endothelial Dysfunction in Patients With Type 2 Diabetes Mellitus.

BACKGROUND: N-terminal pro-B-type natriuretic peptide (NT-Pro BNP) is an established biomarker of heart failure and has been recommended for cardiovascular risk stratification in type 2 diabetes mellitus (T2DM). However, its relationship with diabetic nephropathy and endothelial dysfunction across varying stages of kidney impairment remains unclear. This study examined the associations of NT-Pro BNP, renal impairment, albuminuria and endothelial dysfunction in patients with T2DM without overt heart failure. METHODS: A comparative cross-sectional study was conducted among 192 adults with T2DM. Participants were stratified by KDIGO eGFR groups (≥ 90, 60-89, 30-59 mL/min/1.73m2). NT-Pro BNP was considered abnormal at a cut-off of ≥ 125 pg/mL. Albuminuria was categorized using the urinary albumin-to-creatinine ratio (uACR). Endothelial function was assessed by brachial artery flow-mediated dilatation (FMD). Logistic regression analysis was performed to identify independent factors of elevated NT-Pro BNP, with p-values < 0.05 considered statistically significant. RESULTS: NT-Pro BNP levels were significantly higher in the lower eGFR groups compared with normal eGFR (204.3 vs. 96.8 vs. 62.2 pg/mL, p < 0001). A weak but significant positive correlation was observed between NT-Pro BNP and uACR (r = 0.31, p < 0.001). However, no significant association was found between NT-Pro BNP and FMD (p = 0.388). Following multivariable adjustments, older age (adjusted OR 1.14, 95% CI: 1.06-1.23, p < 0.001), higher systolic blood pressure (adjusted OR 1.05, 95% CI: 1.02-1.08, p = 0.010), lower eGFR (adjusted OR 0.97, 95% CI: 0.95-0.99, p = 0.003) and beta-blocker use (adjusted OR 4.65, 95% CI: 1.61-13.45, p < 0.001) were independently associated with elevated NT-Pro BNP. CONCLUSION: In patients with T2DM without overt heart failure, elevated NT-Pro BNP showed a statistically significant association with lower eGFR and higher albuminuria. Moderate to severe albuminuria becomes an independent factor for elevated NT-Pro BNP after adjustment excluding eGFR. The lack of association with endothelial dysfunction suggests that NT-Pro BNP may reflect different pathophysiological pathways. NT-Pro BNP may serve as a useful biomarker for early cardiovascular risk stratification and identification of individuals at risk of pre-heart failure in diabetic kidney disease.

NT‐Pro BNP↗

PubMed2026

Latent profile analysis of pregnant exercise adherence and the relationship with demographic and socio-psychological factors: a multicentre cross-sectional study.

BACKGROUND: Pregnancy physical activity (PA) and exercise benefits both mothers and babies, but requires sustained adherence. Many pregnant women fail to meet recommended levels. The reasons for low adherence comprised fluctuating physiological and environmental factors. This study aims to identify discrete profiles of pregnant women based on exercise adherence and to examine differences in demographic and socio-psychological factors across these profiles. METHODS: A survey was conducted among 1,255 pregnant women in three hospitals in Shenzhen, Dongguan, and Shunde, China, using the Exercise Adherence Rating Scale (EARS), the Pregnancy Exercise Self-Efficacy Scale (P-ESES), and the Pregnancy Physical Activity Social Support Scale (P-PASSS). In the analysis, EARS items were scored higher, indicating a healthier state (e.g., sufficient time and energy). Latent profile analysis (LPA) was employed to classify adherence profiles, and multinomial logistic regression was used to examine differences in demographic, self-efficacy, and social support across four groups. RESULTS: Four profiles of exercise adherence were identified: (1) Profile 1 (16.97%), characterized by deficits in time and energy, (2) Profile 2 (15.22%), a group with sufficient time resources but the lowest self-efficacy, (3) Profile 3 (43.98%), characterized by high adherence despite moderate barriers, and (4) Profile 4 (23.83%), a group with optimal exercise adherence, confidence, and resources. Women with higher P-ESES (OR: 1.14-1.38) and P-PASSS (OR: 1.04-1.06) scores were more likely to be in Profiles 3 and 4. Additionally, women's partners who never or occasionally exercise were significantly more likely to be categorized into Profile 1 (OR = 0.18 for Profile 4 vs. Profile 1). Furthermore, the first trimester emerged as a significant risk period for lower exercise adherence, whereas overweight/obesity was independently associated with higher odds of membership in Profile 4. CONCLUSION: The study identified four distinct profiles of exercise adherence among pregnant women. 32.19% of participants were in the two lower exercise-adherence groups. Pregnant women in Profile 1 were characterized by challenges related to a lack of time and knowledge. Participants in Profile 2 showed the lowest exercise self-efficacy and social support among the four profiles. Furthermore, women in early pregnancy were more likely to have lower adherence profiles. Hence, targeted interventions addressing these specific groups are warranted to improve exercise adherence during pregnancy.

Humans↗

PubMed2026

Satisfaction with clinical practice environments among early-career health professionals in South Africa: Findings from the WiSDOM cohort study.

BACKGROUND: The work or practice environments of health professionals play a central role in their retention in the healthcare system and their ability to provide quality patient care. The aim of the study was to examine and compare the satisfaction of early-career health professionals in the WiSDOM (Wits longitudinal Study to Determine the Operation of the labour Market among its health professional graduates) study with their clinical practice environments (CPEs) in South Africa, and the factors influencing their satisfaction. METHODS: WiSDOM, a prospective longitudinal cohort study, consists of eight health professions: clinical associates, dentists, doctors, nurses, occupational therapists, oral hygienists, pharmacists, and physiotherapists. Every year we collect information on the cohort's involvement in direct patient care, their perceived workload, availability of medicines and equipment for patients in their care, and their satisfaction with the clinical practice environment (CPE).We used Stata®19 for analysis. We used panel linear regression to investigate factors associated with the cohort's satisfaction with their clinical practice environments from 2018 to 2024, and logistic regression to evaluate the association between CPE and intention to leave in 2024. RESULTS: In 2024, the mean age of the cohort was 30.9 (± 2.0), the majority were female (74.4%) and working in urban areas (92.7%). In 2024, 59.7% of the overall cohort reported a heavy workload compared to 69.2% in 2018. Over the follow-up period, reported problems with the availability of medicines or equipment were worse in the public sector and in rural areas, compared to the private sector and urban areas respectively.The cohort's satisfaction score with the CPE was 6.7 out of 10 in 2018 and 6.9 in 2024. The predictors of CPE were year of follow-up, health profession, employment sector, and geographic location. Nurses (β=-1.2; 95% CI -1.7, -0.7; p < 0.001), and pharmacists (β=-0.7; 95% CI -1.1, -0.4; p < 0.001) scored their CPE significantly lower compared to the other professional groups. Health professionals in the public sector (β=-1.1; 95% CI -1.3, -0.9; p < 0.001) and in rural areas (β=-0.6; 95% CI -0.9, -0.3; p < 0.001) were less satisfied with their CPE compared to those in the private sector and urban areas respectively. Dissatisfaction with the CPE was significantly associated with intention to leave the workplace and the profession. CONCLUSION: The study findings underscore the need for positive clinical practice environments for early-career health professionals in South Africa both as a health workforce and patient safety imperative.

South Africa↗

PubMed2026

Preoperative Proximal Migration of the Radial Head as an Independent Predictor of Suboptimal Outcomes After Osteochondral Autograft Transplantation for Capitellar Osteochondritis Dissecans: A Retrospective Cohort Study.

BACKGROUND: Osteochondral autograft transplantation (OAT) is widely performed for capitellar osteochondritis dissecans (OCD). However, preoperative predictors of suboptimal postoperative outcomes remain unclear. PURPOSE/HYPOTHESIS: The authors aimed to evaluate clinical outcomes after OAT for capitellar OCD and identify preoperative risk factors associated with suboptimal outcomes. They hypothesized that radiographic indicators of disease severity, including preoperative proximal migration of the radial head, lesion size, and lateral wall disruption, would be associated with suboptimal postoperative clinical outcomes. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: The records of adolescent athletes who underwent OAT for capitellar OCD with a minimum 2-year follow-up were retrospectively reviewed. Clinical outcomes included elbow range of motion (ROM) and Timmerman-Andrews (T-A) score. A suboptimal outcome was defined as a postoperative T-A score <160. Preoperative radiographs were used to measure proximal migration of the radial head relative to the coronoid process, hypertrophy of the radial head, OCD lesion area, and a 5-grade lateral wall disruption classification; measurement reliability was assessed. Multivariate logistic regression analysis was performed to identify independent predictors of a suboptimal outcome, and receiver operating characteristic (ROC) curve analysis was used to determine the optimal cutoff value for proximal migration. RESULTS: A total of 69 elbows (mean age, 13.6 years; mean follow-up, 48 months) were included. ROM and T-A scores improved significantly after OAT, and all athletes returned to any sports. Of these, 50 elbows (72%) achieved good outcomes, whereas 19 (28%) had suboptimal outcomes. Preoperative proximal migration was significantly greater in the suboptimal outcome group compared with the good outcome group (mean, 2.1 ± 2.3 vs 0.5 ± 1.7 mm; P = .002), as were lesion area (mean, 70 ± 16 vs 58 ± 20 mm2; P = .02) and lateral wall disruption grade (median, 5 vs 3; P = .01). On multivariate analysis, proximal migration of the radial head was the only independent predictor of a suboptimal outcome (adjusted OR, 1.47 per 1-mm increase; 95% CI, 1.03-2.09; P = .033). ROC analysis showed an area under the curve of 0.72 with an optimal cutoff of 2.2 mm (sensitivity, 56%; specificity, 84%). CONCLUSION: OAT resulted in significant clinical improvement in adolescents with capitellar OCD; however, 28% of patients were classified as having suboptimal outcomes. Preoperative proximal migration of the radial head is an independent predictor of a suboptimal postoperative outcome. A value >2.2 mm may indicate advanced radiocapitellar incongruity, a condition in which OAT may be less effective.

Humans↗

PubMed2026

Longitudinal functional trajectory and surgical outcomes after intracranial meningioma resection: implications for surgical decision-making in older patients.

OBJECTIVE: As the population ages, meningiomas are increasingly encountered in older patients, yet longitudinal functional outcomes following surgery across age groups remain incompletely characterized. This study evaluated age-related differences in clinical and tumor characteristics, functional trajectory, and surgical outcomes. METHODS: This was a retrospective cohort study of 396 consecutive patients who underwent surgery for intracranial meningiomas at a single academic center between January 2023 and September 2025. Patients were stratified into 5 age groups (< 65, 65-69, 70-74, 75-79, and ≥ 80 years). Neurological deficits and Karnofsky Performance Status (KPS) were assessed preoperatively, at discharge, and at last follow-up. Logistic regression analyses identified predictors of prolonged length of stay (LOS) (> 5 days) and poor functional outcome at discharge (KPS < 80). RESULTS: Older patients presented with greater comorbidity burden, larger tumors, and lower preoperative KPS (all p < 0.05), while gross-total resection was achieved at comparable rates across all age groups (p = 0.504). A clinically meaningful inflection point was observed around age 75 years, with KPS < 80 at discharge rising from 7.4% and 9.7% in the < 65-year and 70- to 74-year subgroups and to 36.2% and 57.1% in the 75- to 79-year and ≥ 80-year subgroups (p < 0.001), and median LOS increased from 4 days in the younger groups to 9 and 7 days in the 75- to 79-year and ≥ 80-year groups (p < 0.001). However, recovery rates among patients who experienced functional decline at discharge were comparable across age strata. On multivariable analysis, independent predictors of prolonged LOS were age ≥ 75 years (OR 2.31, p = 0.019), diabetes mellitus (OR 2.85, p = 0.004), posterior fossa location (OR 2.1, p = 0.008), tumor diameter (OR 1.33, p < 0.001), postoperative edema (OR 2.58, p = 0.015), and neurosurgical complications (OR 3.18, p = 0.002). Independent predictors of poor functional outcome at discharge were age ≥ 75 years (OR 5.84, p < 0.001), lower preoperative KPS (OR 2.8, p < 0.001), posterior fossa location (OR 3.72, p = 0.003), neurosurgical complications (OR 3.56, p = 0.008), and recurrent meningioma (OR 2.89, p = 0.025). Among 70 endoscopic endonasal approach patients, higher preoperative deficit burden and subtotal resection rates were observed compared to open craniotomy, though overall functional outcomes were comparable. CONCLUSIONS: Surgical risk in meningioma resection increases from age 75 years onwards, yet recovery capacity following initial functional decline remains similar across all age groups. Preoperative functional status, tumor location, comorbidity burden, and recurrence history should guide surgical decision-making rather than age alone.

Humans↗

PubMed2026

Distal versus proximal radial access for diagnostic cerebral angiography: comparative outcomes and learning curve analysis.

BACKGROUND AND PURPOSE: Distal transradial access (dTRA) is an alternative to proximal transradial access (pTRA) for neuroangiography, but comparative real-world data and evidence on its early learning curve remain limited. We compared procedural performance and access-site complications between dTRA and pTRA and evaluated the early learning curve of dTRA. METHODS: We retrospectively analyzed 470 diagnostic cerebral angiography procedures, representing 421 unique patients, performed via radial access at a single center between January 2025 and February 2026, including 237 dTRA and 233 pTRA procedures. Baseline characteristics, including age, sex, body mass index (BMI) category, aortic arch type, and antiplatelet/anticoagulant use, procedural performance, and clinically assessed access-site events were compared between groups. Radial artery occlusion (RAO) was assessed by postoperative bedside pulse examination and confirmed with Doppler ultrasound when clinical findings were uncertain. Multivariable logistic regression was used to evaluate predictors of RAO, persistent bleeding or repeated compression, hand edema, and a composite access-site event endpoint. Because repeated procedures occurred in a subset of patients and event counts were limited, first-procedure sensitivity analysis and analyses of infrequent outcomes were interpreted cautiously. The dTRA learning process was assessed in the first 100 dTRA cases performed by a single operator using multivariable regression, cumulative sum (CUSUM) analysis, segmented trend analysis, and phase-based comparisons. RESULTS: Baseline characteristics were comparable between groups, including age, male sex, BMI category, aortic arch type, and antiplatelet/anticoagulant use. Compared with pTRA, dTRA was associated with more puncture attempts (3.0 [2.0-4.0] vs 2.0 [1.0-3.0], P < 0.001), longer puncture time (2.0 [1.0-5.0] vs 2.0 [1.0-3.0] min, P = 0.003), lower first-pass success (19.4% vs 35.2%, P < 0.001), and a higher crossover rate (11.4% vs 6.0%, P = 0.037). However, dTRA was associated with a lower clinically assessed RAO rate (2.5% vs 7.7%, P = 0.011). On multivariable analysis, pTRA was independently associated with higher odds of RAO (OR 3.27, 95% CI 1.26-8.49, P = 0.015) and the composite access-site event endpoint (OR 3.12, 95% CI 1.55-6.28, P = 0.001). Similar findings were observed in a sensitivity analysis restricted to the first procedure per patient. In the first 100 dTRA cases, cumulative dTRA experience was independently associated with shorter total procedure time (beta = -0.074 min/case, P = 0.009), while CUSUM and moving-average analyses suggested that the major learning effect occurred within approximately the first 10-15 cases. CONCLUSIONS: In this retrospective single-operator cohort, dTRA was associated with lower clinically assessed RAO than pTRA despite greater access difficulty. The early learning effect was mainly reflected in shorter total procedure time. These findings support the feasibility of dTRA but should be interpreted cautiously given the study's observational design and limited anatomical data.

Humans↗

PubMed2026

Premenarche risk factors for future dysmenorrhoea: a prospective cohort study.

BACKGROUND: Dysmenorrhoea, or pain during menstruation, is common in adolescence and is often dismissed or left untreated. Dysmenorrhoea can interfere with daily functioning and can lead to other chronic pain conditions; however, little is known about the risk factors for dysmenorrhoea. We aimed to characterise premenarche risk factors for the presence and severity of future dysmenorrhoea. METHODS: In this prospective cohort study, we obtained data for female adolescents from the population-based Adolescent Brain Cognitive Development Study (USA) who were premenarchal at baseline (age 9-10 years) and had both reached menarche and completed the Menstrual Cycle Survey at 3-year follow-up (age 12-13 years). Parents or guardians provided sociodemographic information and completed the Child Behavior Checklist, the Sleep Disturbance Scale for Children, and the Pubertal Development Scale, which captured data on non-painful somatic symptoms, attention problems, anxiety, depression, sleep disturbances, and pubertal development at baseline. Our primary objective was to analyse associations between dysmenorrhoea at 3-year follow-up (status and severity) with select symptom domains (sleep problems, attention problems, somatic symptoms, anxious or depressive symptoms, and baseline pain status) at baseline. We also investigated associations between dysmenorrhoea and participant characteristics (pubertal status, race or ethnicity, and income-to-needs ratio) that underlie social determinants of health. Differences by race were tested using Fisher exact tests. Differences by ethnicity and baseline pain status were tested using χ2 tests. Differences in continuous variables were assessed using ANOVA. Wilcoxon-Rank Sum tests were used in analyses of sleep problems, attention problems, and somatic symptoms, and ANOVA was used for pubertal status and income-to-needs ratio. Multinomial logistic regression was used to test associations with dysmenorrhoea severity, and linear regression was used to test associations with dysmenorrhoea status and menstrual pain interference. FINDINGS: 2254 female adolescents were included in this study. 1299 (57·6%) participants developed dysmenorrhoea at age 12-13 years, and 247 (19·0% of those with dysmenorrhoea) reported severe dysmenorrhoea. Non-painful somatic symptoms were prospectively associated with future dysmenorrhoea (odds ratio [OR] 1·17 [95% CI 1·04-1·32]; p=0·0070), whereas anxiety or depression, sleep disturbances, and attention problems were not. Sleep disturbances were prospectively associated with menstrual pain interference (β coefficient 0·16 [95% CI 0·01-0·31]). Advanced pubertal status at ages 9-10 years was prospectively associated with risk of dysmenorrhoea 3 years later (OR 1·79 [95% CI 1·47-2·17]; p<0·0001), as was lower income-to-needs ratio (0·96 [0·93-1·00]; p=0·031). Black (1·38 [1·05-1·83]; p=0·024) and Hispanic (1·34 [1·03-1·68]; p=0·010) young females were at a significantly greater risk of experiencing dysmenorrhoea than were White and non-Hispanic young females, respectively. INTERPRETATION: Sociodemographic characteristics and clinical symptoms present before menarche might help to identify at-risk individuals for dysmenorrhoea before pain becomes a lifelong issue. FUNDING: The National Institute of Nursing Research, the National Institute of Diabetes and Digestive and Kidney Diseases, and the Eunice Kennedy Shriver National Institute for Child Health and Human Development.

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-α-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 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

Snow carps as an emerging model for polyploid genome evolution.

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Editorial↗

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 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↗

PubMed2026

Corrigendum to "The impact of diverse ancestry on polygenic risk score-based prediction models for psychiatric and neurodevelopmental disorders" [Psychiatry Research 2026 Oct:364:117322].

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Published Erratum↗

PubMed2026

Integrative modeling of the genome structure and dynamics in fission yeast.

Genome organization in the nucleus is highly structured and dynamic. Recent advances in genomic technology have enabled the measurement of genome-wide architecture and locus-specific motion, yielding contact maps and live-cell trajectories. However, these outcomes are derived from different modalities and are not directly comparable, with their quantitative integration being a key challenge. Here we establish a genome-wide live-cell imaging platform in fission yeast Schizosaccharomyces pombe, tracking 131 chromosomal loci, along with the spindle pole body (SPB) and nucleolus, to construct a quantitative map of locus dynamics. By integrating these dynamics with contact data through polymer modeling of Hi-C data, we build a physics-based "digital twin" of the S. pombe genome consistent with the spatiotemporal dynamics of interphase chromatin. We validate it against genome-wide mobility patterns and known architectural features, including centromere and telomere clustering. The model also identifies distinct dynamical regimes: centromere- and telomere-proximal loci relax within [Formula: see text]150 s, whereas the remaining loci relax within [Formula: see text]70 s. We measure semiperiodic dynamics of SPB motion, including a characteristic peak near 225 s and [Formula: see text] fluctuations. We use the model with SPB-directed forcing to show how these low-frequency components propagate through the genome to drive genome-wide chromatin displacements. Together, this predictive physics-based modeling framework integrates genome structure and dynamics to reveal how nuclear mechanical driving forces shape chromosome motion, linking mechanically driven chromatin responses to genome maintenance and regulation.

Schizosaccharomyces↗