Publications by Year: 2026

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer-related deaths, accounting for over 90 % of pancreatic cancer cases. Accurate diagnosis is crucial, but often challenging. It typically relies on minimally invasive procedures, such as endoscopic ultrasound-guided fine needle aspiration (EUS-FNA) and small biopsy samples. These small biopsies may be the only tissue diagnosis made before embarking on neoadjuvant therapy, major surgery, or transition to comfort care, depending on clinicoradiologic factors. This paper reviews important diagnostic strategies and criteria for cytologic and small biopsy samples, highlighting cytomorphologic characteristics, histologic patterns, and the role of immunohistochemical and molecular diagnostics. PDAC cytology often shows hypercellular aspirates with disorganized glandular fragments, significant nuclear atypia, prominent nucleoli, and a necrotic background. In contrast, small biopsy samples typically reveal invasive glandular structures surrounded by desmoplastic stroma and nuclear pleomorphism. However, biopsies are often scant and there are a variety of difficult histologic subtypes and mimics that complicate these cases. Although there is a lack of sensitive or specific markers for PDAC, immunohistochemical markers, such as P53, and SMAD4, can be useful for supporting a diagnosis of PDAC over chronic pancreatitis/tumor mimics. Molecular alterations in KRAS, TP53, BRCA1/2, and others may aid in diagnosis, prognostication, and the selection of targeted therapeutic options. By systematically integrating clinicoradiologic, cytological, histological, immunophenotypic, and molecular data, pathologists can effectively differentiate PDAC from benign or reactive lesions and metastatic neoplasms, ensuring accurate diagnoses that are essential for optimal patient management.

TOC Summary R. Mark Richardson argues that, in an era where sensing-enabled devices can provide effective therapy when applied to appropriate seizure networks, treating thalamic implantation as research by default may be overly conservative. He views hypothesis-driven thalamic SEEG as indispensable for optimizing neuromodulation strategies.

Obstructive sleep apnea (OSA) and insomnia could accelerate biological aging through pathways including oxidative stress and systemic inflammation. This systematic review aimed to determine the association of sleep disorders with circulating markers of biological aging. We searched MEDLINE, Embase, CINAHL, Cochrane, PsycINFO from inception to October 2024. Eligibility criteria included full manuscript English studies on adult humans examining OSA or insomnia and circulating markers of aging. Of the 1839 deduplicated records screened, 49 full-text studies were eligible for inclusion. Included studies ranged from poor to good quality and assessed telomere length (TL), DNA methylation clocks (epigenetics), mitochondrial alterations, sirtuin levels and activity, autophagy protein levels, and klotho gene expression. Telomeres were the most extensively studied marker, with our findings showing a significant association between TL and OSA, based on both unadjusted and adjusted values (SMD = -0.451, 95% CI: 0.688 to -0.215, p = 0.0026 and SMD = -3.01, 95% CI: 4.98 to -1.04, p = 0.033, respectively). Most studies linked insomnia and poor sleep quality to shorter TL. Although evidence for other aging biomarkers was more limited, the published literature supports the role of OSA and insomnia in accelerating biological aging, especially for telomere length.

BACKGROUND: Dangling protocols are widely used in the postoperative management of lower extremity free flaps to promote microvascular adaptation. To optimize outcomes, surgeons use dangling protocols, gradually increasing limb dependency, to enhance venous adaptation. However, wide variability exists in their design, and the impact of dangling duration and frequency on complication rates remains unclear.

METHODS: A systematic meta-analysis was performed to evaluate pooled complication rates associated with dangling protocols and to assess whether protocol duration (minutes per session) or frequency (number of sessions) was associated with adverse outcomes. Following PRISMA 2020 guidelines, we searched Medline, Embase, Web of Science, and Cochrane for relevant studies published through 2024. Then, a random-effects model was used to estimate pooled rates of partial flap loss, total flap loss, venous congestion, arterial compromise, hematoma, infection, wound dehiscence, return to the operating room, and donor site complications. Meta-regression was performed to examine associations with dangling protocol characteristics.

RESULTS: Across pooled studies, overall complication rates were low, including total flap loss (0.30%), arterial compromise (0.30%), and venous congestion (0.73%). No statistically significant associations were found between dangling duration and any complication type. While increased frequency of dangling was significantly associated with higher return-to-OR rates in the full model (slope = 0.0224; p = 0.0002), this relationship was entirely driven by a single study reporting 24 sessions/day. When this outlier was excluded, the association became non-significant.

CONCLUSION: Dangling protocols appear safe and well tolerated, with low rates of major complications. While the duration of dangling sessions does not affect complication risk, higher frequency may increase the likelihood of surgical re-intervention. These findings support the need for standardized, evidence-based protocols and further research into the physiologic and clinical thresholds guiding postoperative flap care. A meta-analysis of lower extremity free flap studies demonstrated low complication rates across common endpoints including total flap loss (0.30%), arterial compromise (0.30%), and venous congestion (0.73%).

BACKGROUND: Branched-chain amino acids (BCAAs) are widely used in endurance sports, yet their impact on performance remains unclear. This review evaluated whether biochemical changes from BCAA or leucine supplementation translate into functional benefits.

METHODS: A systematic review was conducted in accordance with PRISMA 2020, the Cochrane Handbook for Systematic Reviews of Interventions, and the GRADE approach. Searches were performed in PubMed, Embase, and Web of Science up to 11 July 2024. Eligible studies included endurance runners or athletes, used BCAA or leucine supplementation, and reported outcomes related to performance, recovery, or adverse effects.

RESULTS: From 152 records, 15 studies met inclusion criteria. No consistent improvement was observed in performance, fatigue, or recovery. Only two studies reported significant differences. One trial found a 42% reduction in muscle soreness (p < 0.05), though with inadequate control for protein intake and confounders. Biochemical changes included: increase 140% valine (p < 0.01), low plasma glucose (p < 0.01), increase free fatty acids (p < 0.001), and raise 25% protein synthesis post-exercise (95% CI: 20-30%, p = 0.01). Mental performance improved after 12 km and 30 km runs (p < 0.05), but no functional performance gains were consistently observed.

CONCLUSION: BCAA and leucine supplementation do not result in meaningful improvements in endurance performance or muscle recovery. Despite biochemical alterations, current evidence - limited by low methodological quality, surrogate outcomes, and risk of bias - does not support the use of BCAA as an effective strategy for endurance athletes.

BACKGROUND: Borderline personality disorder (BPD) is often accompanied by interpersonal dysfunction. Psychotherapy can improve interpersonal functioning, but individual characteristics may moderate outcomes. This systematic review used individual participant data meta-analysis (IPD-MA) to examine such moderators.

METHOD: A literature search up to 26 November 2025 across 10 databases (including PubMed, Medline, Embase, PsychINFO, CINAHL, Web of Science, and Cochrane CENTRAL) identified randomised clinical trials (RCTs) investigating the effects of psychotherapy on interpersonal functioning in individuals with BPD compared to treatment as usual (TAU) or clinical management control interventions (CM). Authors of included trials were contacted to retrieve IPD. IPD-MAs employed a one-stage random-effects approach to estimate treatment effects on interpersonal functioning and potential moderators in bivariate linear mixed-effects models. The study was registered with PROSPERO (CRD42021210688).

RESULTS: Out of 23,735 identified records, 32 RCTs (2762 participants) met inclusion criteria. Individual participant data (IPD) were available for 17 trials (1431 participants). All trials were rated as having either high risk of bias or some concerns. Missing data were common, with 321 out of 1431 participants (23%) lost to follow-up. Meta-analyses of both aggregate data and IPD yielded comparable effect estimates, though statistical significance differed (IPD-MA: β = -0.21, CI: -0.45 to -0.02, SE = 0.12, p = 0.0778; 17 trials, 1071 participants). In unadjusted analyses, the presence of co-occurring anxiety disorder(s) (β = -0.40, 95% CI: -0.73 to -0.08) and a higher number of co-occurring disorders (β = -0.08, 95% CI: -0.15 to -0.01) were associated with larger treatment effects (not significant after alpha correction).

CONCLUSION: Psychotherapy appears to be effective for individuals with BPD. Although moderator effects did not remain statistically significant after alpha correction, unadjusted analyses suggested larger treatment effects in individuals with co-occurring anxiety and greater clinical complexity. Importantly, these findings indicate that such comorbidities may not be a contraindication for psychotherapy for BPD.

BACKGROUND: Lower (<10 mm Hg) discharge echocardiographic mean gradients (MGs) following transcatheter aortic valve replacement with balloon-expandable valves are associated with lower ejection fraction and higher 5-year mortality compared with higher gradients. Using the Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy Registry, we studied the relationship between echocardiographic MG and patient prosthesis mismatch (PPM) following transcatheter aortic valve-in-valve replacement and clinical outcomes.

METHODS: Patients who underwent aortic valve-in-valve replacement with a balloon-expandable valve from July 2015 to December 2023 in the Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy Registry were included. Adjusted Cox models with regression splines explored the relationship between MG and 5-year mortality. Kaplan-Meier estimates and adjusted hazard ratios compared the occurrence of 5-year mortality between gradient cutoffs and PPM presence.

RESULTS: A total of 13 054 patients were included; spline curves demonstrated a nonlinear relationship between discharge MG and 5-year mortality. Kaplan-Meier curves suggested higher 5-year mortality with MG <10 mm Hg compared with MG ≥10 mm Hg (hazard ratio, 1.15 [95% CI, 1.02-1.29]; P=0.024). MG <10 mm Hg was associated with lower ejection fraction compared with higher MG (50.4±13.9 versus 53.2±12.8; P<0.0001). Severe PPM and MG ≥20 mm Hg were not associated with worse 5-year outcomes compared with none/moderate PPM or MG ≤20 mm Hg, respectively.

CONCLUSIONS: Discharge MG <10 mm Hg is associated with lower ejection fraction and increased 5-year mortality following aortic valve-in-valve replacement compared with higher MG in a nonlinear fashion. Severe PPM and MG > 20 mm Hg were not associated with worse 5-year clinical outcomes. Incorporating data on ejection fraction with PPM and MG is important before determining the need for valve optimization.

Machine learning methods based on imaging and other clinical data have shown great potential for improving the early and accurate diagnosis of Alzheimer's disease (AD). However, for most deep learning models, especially those including high-dimensional imaging data, the decision-making process remains largely opaque which limits clinical applicability. Explainable Boosting Machines (EBMs) are inherently interpretable machine learning models, but are typically applied to low-dimensional data. In this study, we propose an interpretable machine learning framework that integrates data-driven feature extraction based on Convolutional Neural Networks (CNNs) with the intrinsic transparency of EBMs for AD diagnosis and prediction. The framework enables interpretation at both the group-level and individual-level by identifying imaging biomarkers contributing to predictions. We validated the framework on the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, achieving an area-under-the-curve (AUC) of 0.969 for AD vs. control classification and 0.750 for MCI conversion prediction. External validation was performed on an independent cohort, yielding AUCs of 0.871 for AD vs. subjective cognitive decline (SCD) classification and 0.666 for MCI conversion prediction. The proposed framework achieves performance comparable to state-of-the-art black-box models while offering transparent decision-making, a critical requirement for clinical translation. Our code is available at: https://gitlab.com/radiology/neuro/interpretable_ad_classification.