Citations

Enteroblastic, hepatoid, and clear cell carcinomas are rare subtypes of colorectal carcinoma (CRC) with histologic and immunohistochemical (IHC) overlap. We assessed 37 CRCs that possibly represent these subtypes. Provisional criteria for each subtype, along with case photomicrographs and IHC data, were circulated among the authors to provide diagnostic interpretations. Based on plurality consensus, the carcinomas were classified as enteroblastic (n=13), hepatoid (n=6), and clear cell (n=18). Unanimous agreement was reached in 18% (3 clear cell, 3 hepatoid). Interobserver analysis revealed a mean pairwise Cohen κ of 0.63 (range: 0.32 to 0.91), with the hepatoid subtype eliciting the greatest consensus. Clear cell areas were the most likely to intermix with areas of conventional CRC ( P <0.001). Seven patients (20%) had inflammatory bowel disease (mostly linked to enteroblastic CRC). Twenty-three of 34 patients (68%) had nodal metastasis, and 12 (32%) had distant metastasis (mostly to the liver) at presentation. Median recurrence-free survival was 17 months, with enteroblastic cases the most likely to recur (54%, P =0.015). Median follow-up length was 27 months, with 14 patients (40%) dying of disease (representing 7 enteroblastic, 4 hepatoid, and 3 clear cell CRC). Mutations were identified in TP53 (n=8) , APC (n=3) , FBXW7 (n=2), and KRAS (n=1). Inflammatory bowel disease significantly worsened recurrence-free survival on multivariate analysis, while distant metastasis significantly worsened both recurrence-free and overall survival on multivariate analysis. Enteroblastic, hepatoid, and clear cell CRC demonstrate morphologic and IHC overlap, leading to interobserver variability in diagnosis. Given potential differences in clinical correlations and outcomes, more refined criteria are likely necessary.

Abstract Background Accurate assessment of left ventricular outflow tract (LVOT) gradients is critical for hypertrophic cardiomyopathy (HCM) management, yet Doppler-based measurements are technically demanding and require expertise. Objective To develop a multi-view deep learning model capable of classifying LVOT obstruction (> 20mmHg) using routine 2D echocardiographic windows without reliance on Doppler imaging. Methods We trained and externally validated a cross-attention-based video-to-video fusion framework that integrated EchoPrime-derived video representations from three standard transthoracic echocardiographic views to classify LVOT gradients. Results Training was performed on a derivation cohort (N = 1833) from a tertiary care system in the United States, with model performance evaluated on an internal held-out test set (N = 275) and a Korean external validation cohort (N = 46). Single-view baselines showed limited discrimination (external AUROCs 0.47–0.70). Conversely, domain-specific foundational model (EchoPrime) achieved superior single-view performance (AUROCs 0.75–0.80 internal; 0.79–0.83 external), highlighting the importance of echo-specific pretraining and temporal modeling. The proposed multi-view fusion further enhanced predictive performance, with the late fusion model reaching an AUROC of 0.84 on the external cohort with significant population-shift. Conclusions These results suggest LVOT physiology is encoded in routine 2D imaging and can be leveraged for clinically relevant gradient classification without Doppler input- proposed AI-guided strategy demonstrates substantial cost savings compared with the screen-all approach. By integrating complementary spatial-temporal information across multiple views, our approach generalizes robustly across populations and may enable real-time decision support, extend LVOT assessment to portable or resource-limited settings, and complement Doppler-based evaluation for longitudinal HCM management.

Importance Brain imaging biomarkers may (1) identify underlying mechanisms of intervention effects and (2) define brain characteristics of those most likely to benefit cognitively from the intervention. Objective To test whether (1) a lifestyle intervention is related to brain changes, (2) brain changes are correlated with intervention-specific cognition changes, and (3) brain imaging biomarkers provide information about who is likely to benefit from a lifestyle intervention. Design, Setting, and Participants In this randomized clinical trial, the POINTER Imaging study was an ancillary study of the 2-year, single-blind multicenter US POINTER clinical trial in which neuroimaging data were collected on eligible enrolled participants. The study was conducted from May 2019 to March 2023 (final follow-up, May 14, 2025). Participants were enrolled into the POINTER Imaging study following a standard procedure at 5 clinical sites in the US. Participant eligibility criteria included an age of 60 to 79 years, sedentary lifestyle, and suboptimal diet, plus at least 2 additional risk criteria for cognitive decline and no contraindications for neuroimaging. Interventions Participants were randomly assigned to receive the structured or self-guided intervention. Both interventions emphasized increased physical and cognitive activity, healthy nutrition, social engagement, and cardiovascular health monitoring, but they differed in intensity and accountability. Main Outcomes and Measures There were 4 primary imaging outcomes: global β-amyloid (Aβ) burden, tau burden in the entorhinal cortex (ERC), hippocampal (HC) volume, and white matter hyperintensity volume. The primary cognitive measure was a global cognitive composite. Results Among 1943 parent trial participants who were assessed for eligibility, 983 underwent at least 1 magnetic resonance imaging or positron emission tomography scanning session. The mean (SD) age was 68.4 (5.2) years; 605 participants (61.5%) were female and 378 male (38.5%). Five hundred sixteen participants received the structured intervention and 467 the self-guided intervention. There were no intervention group differences in longitudinal cognitive or imaging outcomes. Intervention group differences were not associated with or moderated by Aβ status or accumulation. There was a negative association between change in ERC tau and change in global cognition in the self-guided group that was attenuated in the structured group (difference in association: 0.289; 95% CI, 0.029 to 0.550; interaction P = .03). Lower baseline HC volume was associated with greater cognitive benefit for participants in the structured group vs the self-guided group (lower HC: 0.077 SD; 95% CI, 0.022 to 0.132; higher HC: 0.002 SD; 95% CI, −0.037 to 0.041; interaction P = .03). Conclusion and Relevance This study found that a high-intensity multidomain lifestyle intervention did not affect brain biomarker trajectories and was not associated with Aβ pathology, but older adults with specific at-risk brain characteristics, including lower baseline HC volume, showed a greater cognitive benefit of the structured intervention. Trial Registration ClinicalTrials.gov Identifier: NCT03688126

Objective: To compare 1-year changes in estimated 10-year and lifetime atherosclerotic cardiovascular disease (ASCVD) risk following metabolic and bariatric surgery (MBS) versus glucagon-like peptide-1 receptor agonist (GLP-1RA) therapy among adults with obesity. Summary Background Data: Obesity is a major driver of ASCVD through adverse metabolic and inflammatory pathways. Metabolic and bariatric surgery and GLP-1 receptor agonists represent the most effective contemporary treatments for obesity and are increasingly used to mitigate cardiovascular risk. However, their comparative effects on integrated short-term and lifetime ASCVD risk in real-world clinical practice remain incompletely characterized. Methods: We conducted a retrospective cohort study of adults with obesity (body mass index ≥30 kg/m²) who underwent MBS or initiated GLP-1RA therapy between 2020 and 2023 within a large tertiary health care system in the United States. Participants were identified from electronic health records and followed for 12 months. Primary outcomes were 1-year changes in estimated 10-year and lifetime ASCVD risk. Secondary outcomes included percent total body weight loss, blood pressure, and lipid parameters. Multivariable linear regression models were used to adjust for baseline body mass index and baseline ASCVD risk. Results: The final cohort included 812 patients, of whom 579 underwent MBS and 233 initiated GLP-1RA therapy. At baseline, patients receiving GLP-1RAs were older and had higher estimated ASCVD risk. At 1 year, reductions in 10-year ASCVD risk were similar between groups (−0.8% vs. −1.1%; P =.36). In contrast, lifetime ASCVD risk decreased significantly more following MBS than GLP-1RA therapy (−8.6% vs. −1.7%; P <.001). MBS was associated with greater percent total body weight loss (−27.8% vs. −11.1%; P <.001) and more favorable lipid changes, including larger reductions in low-density lipoprotein cholesterol and greater increases in high-density lipoprotein cholesterol. After adjustment, MBS remained independently associated with a greater reduction in lifetime ASCVD risk compared with GLP-1RA therapy (β −6.92; 95% CI −9.22 to −4.62). Conclusions: In this real-world cohort, both MBS and GLP-1RA therapy were associated with improvements in estimated cardiovascular risk, but MBS conferred substantially greater reductions in lifetime ASCVD risk, accompanied by superior weight loss and lipid improvements. These findings highlight the complementary roles of surgical and pharmacologic therapies in obesity management and may inform strategies to optimize long-term cardiovascular risk reduction.

Abstract Machine learning (ML) enables adaptive immune receptor repertoires (AIRRs) analyses for biomarker identification and therapeutic development. With the majority of AIRR data partially or imperfectly labeled, unsupervised ML is essential for motif discovery, biologically meaningful clustering, and generation of novel receptor sequences. However, no unified framework for unsupervised ML exists in the AIRR field, hindering the assessment of model robustness and generalizability. Here, we present an immuneML release advancing unsupervised ML in the AIRR field through unified clustering workflows, interpretable generative modeling, integration with protein language model embeddings, dimensionality reduction, and visualization. We demonstrate immuneML’s utility in three use cases: (i) benchmarking generative models for epitope-specific sequence generation, assessing specificity and novelty, (ii) systematic evaluation of clustering approaches on experimental receptor sequences against biological properties, such as epitope specificity and MHC, and (iii) unsupervised analysis of an experimental AIRR dataset to examine potential confounding, a practice widespread in related fields but unexplored in AIRR analyses.

Abstract Human visual cortex comprises three interacting streams, but anatomy and correlated activity cannot determine the direction or reliability of interareal influence. Characterizing directional interactions among these streams can reveal the architecture through which activity can propagate across the visual system. Here, we used single-pulse electrical stimulation during intracranial EEG recordings in 17 patients to map directed causal influences among 22 atlas-defined visual cortical areas. The resulting effective connectivity matrix revealed a selective and asymmetric architecture of interareal influence. Feedforward influences from early visual areas to the dorsal, lateral, and ventral streams were more reliable and more prevalent than feedback influences. Cross-stream interactions favored temporal-to-parietal over parietal-to-temporal influence, with higher response reliability and a greater proportion of significant responses among sampled connections. Network-level profiles were consistent with source-like organization in early visual areas and the ventral stream, and integrator-like organization in the dorsal and lateral streams. Independent visual-task data collected in three of the same patients illustrated how stimulation-derived connectivity may relate to functional responses across connected visual regions. These findings reveal a directional architecture for activity propagation across the human visual cortex and provide empirical constraints for biologically grounded models of visual processing.

Abstract Alzheimer's disease (AD) is neuropathologically defined by amyloid‐beta (Aβ) plaques and tau neurofibrillary tangles. However, co‐pathologies and other pathobiological processes are involved in the pathogenesis of AD, contributing to neurodegeneration and clinical symptoms. The most common co‐pathologies in people with AD are alpha‐synucleinopathy, vascular brain injury and transactive response DNA‐binding protein of 43 kDa‐related pathology. Neuroinflammation, iron accumulation, cholinergic dysfunction and cellular senescence are recognized pathobiological processes beyond Aβ‐ and tau‐related pathology. However, the exact mechanisms by which these co‐pathologies and pathobiological processes contribute to the neurodegeneration and clinical symptoms in people with AD remain unclear. The individual combination of these co‐pathologies and pathobiological processes increases phenotypical heterogeneity in people with AD. This highlights the unmet need to advance their current understanding, and the field strives to develop accurate biomarkers for personalized assessment and investigation. Elucidating this biologic‐clinical complexity and heterogeneity is crucial for increasing our current understanding of AD, with implications for diagnosis, prognosis and therapeutics.

ABSTRACT Background Visceral myopathy (VSCM) is an ultra‐rare life‐threatening condition characterized by severe impairment of gastrointestinal (GI), genitourinary, and uterine smooth muscle. This disorder represents a significant clinical challenge due to variable presentation and the lack of standardized diagnostic and therapeutic protocols. Methods To discuss advances in the field, scientists and clinicians with a special interest in VSCM met in Arenzano, Genova, Italy in October 2024 for the second International Forum on Visceral Myopathy 2024 (IFVM2024) ( https://ifvm2024.ge.ibf.cnr.it/ ). Key Results As in the previous edition of the event ( https://poic‐e‐dintorni.org/efvm‐2022/ ), attendees included clinicians and researchers from around the world who study this disease, representatives from support organizations, patients affected by VSCM and their families, and companies that co‐funded the event. The present manuscript aims to summarize knowledge shared during the IFVM2024 conference, thus providing an updated state‐of‐the‐art summary of VSCM biology and disease management. Conclusions Here, we pay particular attention to the epidemiology of the disease, histopathology, genetics, novel treatments, advances in molecular and cell biology, experimental models, and the lived experiences and impact of this disorder on families.