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PubMed2026

A Conserved 3'UTR Stem-loop Directs UPF1/eIF4AIII-Dependent Regulation of GABARAPL1 mRNA.

RNA-binding proteins (RBP) interact with mRNA untranslated regions containing cis-regulatory elements to govern mRNA localization, stability, and translational efficiency. Among these trans-regulatory factors, RNA helicase UPF1 is a central factor which play a role in multiple mRNA decay pathways, including nonsense-mediated mRNA decay (NMD). NMD is triggered when an exon-junction complex (EJC) is located downstream of a premature termination codon. However, in some cases, NMD can be activated in an EJC-independent manner through mechanisms involving the 3'UTR. In the present study, we focused on the GABARAPL1 3'UTR, as previous studies had shown that this region plays a key role in NMD targeting, although the underlying molecular mechanism had not yet been elucidated. Unlike canonical NMD targets such as SC35, we found that the chemical inhibition of eIF4AIII helicase activity did not affect GABARAPL1 transcript levels, indicating that this transcript is regulated through its 3'UTR via an EJC-independent mechanism. We therefore investigated the potential presence of cis-regulatory element within the 3'UTR of GABARAPL1 which can regulate mRNA and protein levels in a UPF1-dependent manner. Furthermore, we identified a conserved RNA region spanning nucleotides 364-421 involved in GABARAPL1 targeting and used biochemical analysis to demonstrate the direct binding of UPF1 and eIF4AIII to this RNA region, to analyse its secondary structure in solution, and to map the protein-binding sites. By complementing these approaches with molecular modelling, we showed that this stem-loop adopts a stable global fold but a local flexibility and dynamic behaviour properties. Together, our results support the role of UPF1 and eIF4AIII as specific regulators of GABARAPL1 transcript and reveal a novel RNA regulatory element within its 3'UTR, which provides a completely unexpected binding site for these factors.

3' Untranslated Regions↗

PubMed2026

Transvalvular Flow Rate is Associated With Mortality Rate and Lifetime Loss in Aortic Valve Stenosis: A Meta-Analysis of Reconstructed Time-to-Event Data.

Low-flow states are associated with adverse outcomes in aortic stenosis (AS), but the prognostic value of transvalvular flow rate (TFR) has not been consistently established across studies. This study is a systematic review and meta-analysis of reconstructed time-to-event data was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-analyses. PubMed/MEDLINE, EMBASE, and Cochrane Library were searched for studies (published by November 14, 2025) comparing low versus normal TFR in AS. Data were collected from Kaplan-Meier curves. The primary endpoint was all-cause mortality. Survival was assessed using pooled Kaplan-Meier curves, Cox regression, flexible parametric survival models, and restricted mean survival time (RMST) analysis. A total of 9 studies including 6,494 patients were analyzed; 2,575 (39.7%) had low TFR. At 8 years of follow-up, estimated survival was 34.1% (95% confidence interval [CI] 24.7% to 47%) in the low-TFR group and 63% (95% CI 58.9% to 67.4%) in the normal-TFR group. Low TFR was associated with higher all-cause mortality (hazard ratio 1.59, 95% CI 1.45 to 1.74, p < 0.001). We observed a progressively greater hazard over time, with the hazard ratio approaching 1.9 by 8 years. At 8 years, RMST in the normal-TFR group was 7.37 years (95% CI 7.21 to 7.53 years) versus 5.07 years (95% CI 4.91 to 5.23 years) in the low-TFR group, representing a lifetime loss of 2.3 years in the low-TFR group (ΔRMST -2.30 years, 95% CI -2.53 to -2.07 years, p < 0.001). In patients with AS, low TFR is associated with significantly higher mortality and lifetime loss. These findings support TFR as a clinically meaningful marker for risk stratification in AS.

Aortic Valve Stenosis↗

PubMed2026

Internet-based acceptance and commitment therapy (iACT) improves professional psychological help-seeking attitudes: A randomized controlled trial.

BACKGROUND: Professional psychological help-seeking attitudes are crucial for addressing mental health challenges, yet the mechanisms underlying their improvement through internet-based interventions remain poorly understood. OBJECTIVE: This randomized controlled trial aimed to (1) evaluate the efficacy of Internet-based Acceptance and Commitment Therapy (iACT) in enhancing professional help-seeking attitudes, and (2) elucidate the longitudinal mediating roles of psychological rigidity and self-stigma. METHODS: A total of 91 male participants (Mean Age = 21.09) were randomly assigned to either a 12-day iACT intervention group (n = 46) using a self-developed mobile application or a waitlist control group (n = 45). Psychological flexibility, rigidity, self-stigma, and help-seeking attitudes were measured at four time points: baseline, mid-intervention (Day 6), post-intervention (Day 12), and 1-month follow-up. Data were analyzed using repeated-measures ANOVA and latent growth modeling. RESULTS: Intention-to-treat analysis revealed the iACT group showed greater improvements in help-seeking attitudes than controls (F (3,87) = 5.95, p < 0.001), with medium-to-large between-group effects at post-test for reducing psychological rigidity (d = -0.77, 95% CI [-1.19, -0.34]) and self-stigma (d = -0.88, 95% CI [-1.31, -0.45]). Latent growth modeling revealed a sequential mediation effect: the iACT intervention reduced psychological rigidity (β = -0.53, SE = 0.12), which in turn reduced self-stigma (β = 0.61, SE = 0.09) and improved help-seeking attitudes (β = 0.47, SE = 0.08). CONCLUSION: This study provides the first evidence that a self-guided iACT mobile intervention can effectively enhance professional help-seeking attitudes by reducing psychological rigidity, which in turn alleviates self-stigma. The developed app offers a scalable solution to overcoming stigma-related barriers to mental health care.

Humans↗

PubMed2026

Beyond predictive performance: A systematic review and critical methodological appraisal of AI/ML and conventional modelling strategies in breast, colorectal, and pancreatic Cancer.

BACKGROUND: Predictive modelling for cancer risk, treatment-related complications, and survival is central to precision oncology. Conventional logistic regression (LR) and Cox proportional hazards (CoxPH) regression remain widely used but are limited when modelling nonlinear interactions, high-dimensional imaging features, and multimodal clinical-metabolic predictors. Artificial intelligence (AI) and machine learning (ML) methods offer expanded capability through automated feature extraction, ensemble learning, and flexible survival modelling, but the evidence on when AI/ML adds value over conventional models across cancer sites and predictive tasks remains fragmented. OBJECTIVE: To systematically evaluate the methodological performance, validation strategies, and translational limitations of AI/ML models compared with conventional statistical models in published predictive-modelling studies for breast, colorectal, or pancreatic cancer. METHODS: PubMed, Scopus, and Web of Science were searched for studies published between January 2019 and March 2025. Two reviewers independently conducted title-and-abstract screening, full-text eligibility assessment, and PROBAST risk-of-bias assessment. Sixty-five studies (n = 907,567 participants) were narratively synthesised by cancer site, predictive task, model family, comparator, validation strategy, predictor modality, and calibration or explainability reporting. RESULTS: The 65 studies comprised breast cancer (n = 35), colorectal cancer (n = 21), and pancreatic cancer (n = 9). AI/ML superiority over LR and CoxPH was task- and data-dependent. CNN- and U-Net-based models predominated in imaging and body-composition tasks, tree-based ensembles consistently outperformed LR for tabular perioperative complication prediction, and CoxPH remained competitive, and in the largest pancreatic risk study, superior to XGBoost (C-index 0.802 vs 0.723) in well-structured datasets. PROBAST analysis-domain risk was moderate in 54 of 65 studies (83%), driven by limited external validation, sparse calibration reporting (11/65), and few decision-curve analyses (7/65). CONCLUSION: AI/ML adds the most methodological value in imaging-derived feature extraction and nonlinear perioperative prediction, while conventional regression remains preferable in large, structured datasets with linear predictors. Clinical translation requires standardised body-composition definitions, external validation, calibration assessment, decision-curve analysis, and explainability, in line with TRIPOD+AI and CLAIM standards.

Humans↗

PubMed2026

A modified stomal construction technique to reduce incidence of stomal stenosis in continent catheterizable channels.

BACKGROUND: Antegrade continence enema (ACE) and catheterizable bladder channel (Mitrofanoff) procedures are routinely performed in pediatric urology patients diagnosed with a neurogenic bladder and bowel. Stomal stenosis is a common surgical complication of these procedures, occurring in approximately 10-30% of stomas. Our frustration with this complication prompted us to modify our suturing technique during stomal construction to attempt to decrease the incidence of stomal stenosis. METHODS: We compared the rates of stomal stenosis between patients with neurogenic bladder who underwent the creation of an ACE or Mitrofanoff channel using the historical techniques (prior to April 2018) versus the current technique (from April 2018 to December 2020). Our current technique for stoma creation consists of suturing full thickness bowel to only the dermal layer of the skin using interrupted 5-0 polydioxanone interrupted sutures with the knots buried. Statistics were performed using Fisher's exact t-test, with p-values <0.05 considered significant. RESULTS: There were no significant differences in demographics between patients in the 2 cohorts. Stomal stenosis occurred in 25 of 98 stomas (25.5%) after undergoing either an ACE or Mitrofanoff procedure using the historical techniques, with a median patient follow-up of 122.6 months for ACE cohort and 165.8 for Mitrofanoff cohort. The incidence of stomal stenosis was significantly decreased in the current technique, with one of the 31 stomas (3.2%) experiencing stenosis (p = 0.022), with a median follow-up of 78.4 months for ACE cohort, and 66.5 months for Mitrofanoff cohort. These follow-up durations exceed the upper limits of time-to-stenosis in the historical stomas. Stomas in the current cohort have a minimum follow-up of 4.5 years and a maximum follow-up of 7 years. CONCLUSIONS: Our current suturing technique has significantly reduced the incidence of stomal stenosis in our patients. The technique is straightforward and flexible and can be applied to any stoma placed in any position. Only one of the patients with stomas created with the current suturing technique have developed stomal stenosis, with follow-up exceeding the median time to development of stenosis of our historical cohort.

Humans↗