Citations

Background: Objective performance assessment is essential in surgical skill training, yet current methods are labor-intensive and focus on observing the trainee rather than the end-product of the procedure. Machine learning (ML) methods offer reproducible feedback but have mainly relied on kinematic or video data, often reducing assessment to binary or ternary classification. Our objective was to compare ML regression models predicting expert-assigned scores of vascular anastomoses from computational fluid dynamics (CFD) features of the final product. Additionally, we aimed to assess biomechanical plausibility of predictions. Methods: A total of 146 participants performed 419 end-to-side anastomoses on case-specific three-dimensional (3D) printed simulators. Anastomoses were digitized via 3D scanning, ranked by experts, and characterized using CFD-derived hemodynamic features. These served as input for linear models (Ridge, Partial Least Squares), support vector machines, and tree-based ensembles (Random Forest, Extremely Randomized Trees, and Extreme Gradient Boosting [XGBoost]), evaluated using 10-fold nested cross-validation with genetic hyperparameter optimization. Results: Inter-rater reliability of expert indicated strong agreement (intraclass correlation coefficient ICC3k = 0.846). XGBoost achieved the lowest mean root mean squared error of 0.758 (95% bootstrap CI: 0.722–0.799) and a coefficient of determination (R2) of 0.673 (0.617–0.725), with the most stable performance across folds. Shapley additive explanations (SHAP) identified the wall shear stress gradient, transverse wall shear stress, and maximum pressure as the most influential features—variables associated with intimal hyperplasia and atherosclerotic remodeling. Conclusions: Tree-based ensemble methods, particularly XGBoost, effectively modeled biomechanical properties against expert scores. Combining CFD and ML can provide reproducible, mechanistically relevant feedback in vascular surgical skill training.

Background: Premedications used to prevent paclitaxel-associated infusion hypersensitivity reactions (iHSRs) can cause undesirable toxicities, such as sleep disturbance and weight gain. Although phase II data suggest that discontinuing premedications after paclitaxel-associated iHSRs may be safe and feasible in select patients without prior iHSRs, no prospective randomized trials have evaluated this approach. Patients and Methods: This randomized clinical trial enrolled patients with breast cancer receiving paclitaxel chemotherapy. Those who experienced no iHSRs with the first 2 doses of paclitaxel were randomized to either continue standard premedications (control arm) or to discontinue all premedications (investigational arm). Both arms were followed longitudinally for any subsequent iHSRs requiring parenteral rescue medications. Additionally, changes in weight, drug-related side effects, and quality of life were assessed. Results: A total of 98 patients were randomized; 89 were evaluable (46 in the control arm and 43 in the investigational arm). Only 1 (2.3%) patient in the investigational arm experienced an iHSR, which resolved with rescue medications. No iHSRs occurred in the control arm. The estimated proportion of subjects who experienced a hypersensitivity reaction (exact binomial 95% CI) was 2.3% (95% CI, 0.1%–12.3%) in the investigational arm and 0.0% (95% CI, 0.0%–7.7%) in the control arm. Patients in the investigational arm reported significantly less sleep disruption (0.5 vs 1.7; P =.002) and unwanted appetite increases (1.0 vs 2.5; P =.0018). Conclusions: Discontinuation of premedications after 2 uneventful paclitaxel doses was not associated with a high rate of subsequent iHSRs and resulted in fewer steroid-related side effects. This strategy may reduce unnecessary medication exposure, improve patient experience, and streamline clinical workflows. For patients who do not experience iHSRs during the first 2 paclitaxel treatments, discontinuing premedications appears safe and may improve tolerability.

ABSTRACT Supplemental oxygen (hyperoxia), often provided to premature infants, can disrupt lung growth and contribute to development of neonatal and pediatric lung diseases, necessitating understanding of underlying mechanisms. We previously showed that even moderate hyperoxia (< 60% O 2 ) induces detrimental cellular senescence in 18–22 weeks human fetal airway smooth muscle (fASM), a key cell type in airway contractility and remodeling. In this study, we examined the ability of senotherapeutics Fucoidan and Dasatinib (D) + Quercetin (Q) (D + Q) to mitigate adverse effects of hyperoxia and assessed the preventive effect of mitochondrial antioxidants (MitoQ). fASM cells exposed to normoxia (21% O 2 ) or hyperoxia (50% O 2 ) were treated with Fucoidan [100 μg/mL], D + Q [250 nM + 375 nM] or MitoQ [100 nM] and assessed for senescence markers, senescence‐associated secretory profile (SASP), extracellular matrix (ECM) deposition, and cell viability. Our results showed that moderate hyperoxia increases senescence markers and SASP. Fucoidan decreased p21 expression and inhibited SASP release without inducing cell death, while D + Q decreased β‐galactosidase (β‐Gal) activity, p21 and plasminogen activator inhibitor‐1 (PAI‐1) expression, and caused cell death without affecting SASP in hyperoxia‐induced senescent fASM. MitoQ prevented increases in senescence markers and SASP in hyperoxia‐exposed fASM. These findings demonstrate distinct and viable strategies to counter hyperoxia‐induced fASM senescence. Fucoidan (senomorphic), D + Q (senolytic), and MitoQ (prophylactic antioxidant) represent promising, mechanistically different approaches to alleviate detrimental effects of moderate hyperoxia in developing airways towards limiting perinatal lung disease.

Abstract Prostate adenocarcinomas (PRAD) can acquire resistance to androgen receptor signaling inhibitors through lineage transition to a cell state known as neuroendocrine prostate cancer (NEPC). Using a panel of isogenic PRAD and NEPC mouse tumoroids, we show that NEPC cells acquire new transcription factor (TF) dependencies that function in a previously undefined network. Through selective perturbation of each TF, we identify ASCL1 as a key regulator of NE lineage fate whereas MYCL functions downstream to drive NEPC growth/survival by recruitment of the TIP60/KAT5 acetyltransferase. Interestingly, while dependencies on specific TF family paralogs can vary across NEPC models, all show markedly enhanced dependency on TIP60. Moreover, the H2A.Z-acetyltransferase activity of the TIP60 complex (TIP60-C) is required for NEPC as well as the acetyl-reader BRD8, which is newly incorporated as a TIP60-C subunit with the NEPC transition. Targeted degradation studies in isogenic tumoroids reveal increased dependence on MYCL in NEPC relative to its paralog MYC in PRAD. In addition to a paralog switch (MYC to MYCL), the MYC pathway-addicted NE state is accompanied by a chaperone switch (from TIP60-C to SRCAP) for H2A.Z histone exchange and a coactivator switch (to TIP60) for MYC target gene expression. The NE-specific coupling of MYCL with TIP60 reveals a previously unappreciated opportunity to target MYC-driven NE diseases through pharmacological inhibition of TIP60.

Abstract Patients with extremely rare pathogenic variants pose unique challenges to current healthcare systems. Nano-rare mutations have been defined as mutations with a known prevalence of &lt;30 patients worldwide, but because of the small fraction of humans who have undergone genetic testing, neither the precise prevalence of individual mutations nor the total prevalence of patients with nano-rare mutations is known. n-Lorem is a non-profit founded in 2020 with the mission of equitably discovering, developing, and providing bespoke experimental antisense oligonucleotides (ASOs) for free, for life, to patients with nano-rare mutations that are amenable to ASO treatment. In this perspective, we provide an overview of the n-Lorem processes and systems, the characteristics of the first 329 patients who have applied for treatment for whom initial assessment was completed and suitability for ASO treatment determined, and a summary of the results of ASO treatment for patients treated to date. Detailed data on individual patients and the overall clinical safety and tolerability profiles of the ASOs for which there are clinical data are the subjects of other manuscripts.

Abstract A recent discussion that highlighted the differences between the reported effective orifice area and corresponding incidence of prosthesis-patient mismatch within the 1- and 7-year results of the PERIcardial SurGical AOrtic Valve ReplacemeNt (PERIGON) Trial of the Avalus valve has once again emphasized the instability of such measurements. The effective orifice area, calculated using the continuity equation through measurements of the left ventricular outflow tract diameter, is highly susceptible to measurement variability, as previously demonstrated in literature through both intra- and interobserver variability. To illustrate this problem, a simulation was performed in which the left ventricular outflow tract diameter was systematically altered by −2 mm, −1 mm, 0 mm, +1 mm, and +2 mm. Subsequently, the proportion of severe prosthesis-patient mismatch was recalculated and varied between 13.3%, 6.2%, 3.1% (original), 1.2%, and 0.3%, respectively. These findings demonstrate that small but clinically realistic variability in left ventricular outflow tract measurements can significantly affect the presence of prosthesis-patient mismatch. A measurement variability of 1 mm can nearly double or halve the prevalence of severe prosthesis-patient mismatch. This illustrates that prosthesis-patient mismatch, in its current form, is highly unstable and that indexed effective orifice area-based prosthesis-patient mismatch should not be used in isolation.

Abstract Background Transthoracic echocardiography (TTE) is the most commonly used modality for the diagnosis and follow-up of cardiac diseases. During routine TTE, surrounding extracardiac structures are often visualized, including the lungs, pleural spaces, oesophagus, diaphragm, and sub-diaphragmatic structures such the liver, stomach, bowel, and abdominal aorta. Pathologic conditions affecting these organs may exert extrinsic compression on the cardiac chambers, leading to diagnostic uncertainty or mimicking cardiac disease by producing symptoms, such as dyspnoea, fatigue, chest pain, or palpitations. Case summary We describe five patients who underwent routine TTE and were incidentally found to have unsuspected gastrointestinal abnormalities. The findings subsequently confirmed by other imaging modalities included hiatal hernia, distended bowel loops, oesophageal carcinoma, and oesophageal varices. Reporting of these findings impacted the diagnosis and management of the cases. Conclusion Awareness of the sonographic appearance of gastrointestinal during TTE is essential, as these findings may represent clinically significant pathology that mimics or contributes to cardiac symptoms. Recognition of such findings may be enhanced by modified echocardiographic views, with confirmatory evaluation using chest radiography, computed tomography, or gastrointestinal endoscopy as appropriate

Background Chronic kidney disease (CKD) confers a substantially elevated risk of cardiovascular (CV) mortality, primarily driven by heart failure (HF) and other CV complications. This study aimed to develop a nomogram for predicting incident HF and all-cause death in patients with CKD, and further identify individuals at high risk of these outcomes. Methods We prospectively recruited 440 patients with CKD stages 3–5 and preserved ejection fraction (LVEF) from a nephropathy center between November 2020 to September 2024. Baseline clinical and demographic characteristics, biochemical and echocardiographic parameters, and data from quality-of-life scales were collected. Key predictors were identified using univariate Cox regression, Lasso, Random Forest, and XGBoost algorithms; these identified predictors were then integrated into a nomogram via multivariate Cox regression. Model performance was assessed using the C-index, ROC analysis, and calibration plots. Results Over 29 months (IQR 24–35), 104(23.6%) patients met the primary composite endpoints, which included 62(14.1%) incident HF and 42(9.5%) all-cause death. After selecting variables through forward stepwise regression, age[HR 1.030, P = 0.016], growth differentiation factor 15(GDF-15) [HR 1.076, P &lt; 0.001], lipoprotein(a)[Lp(a)] [HR = 1.011, P = 0.002], ferritin(FER) [HR = 1.009, P = 0.030], and EuroQol-5D (EQ-5D) score [HR 0.099, P = 0.015] were utilized to construct the nomogram. In the training cohort, the model achieved a C-index of 0.772. For temporal validation, time-dependent area under the ROC curve(AUC) values further confirmed its accuracy: 0.779 (95%CI, 0.696–0.863) at 24 months, 0.816(95%CI, 0.743–0.888) at 27 months, 0.836(95%CI, 0.768–0.903) at 32 months, and 0.850(95%CI, 0.771–0.929) at 36 months. Decision curve analysis (DCA) also demonstrated sustained clinical utility across a broad range of threshold probabilities. Conclusion This study identified specific predictors of HF and all-cause mortality in CKD patients. This model has enhanced predictive ability for early identification of these risks, thereby facilitating timely clinical interventions to improve the prognosis of CKD patients.