Citations

BACKGROUND AND OBJECTIVES: Brainstem cavernous malformations (BSCM) can result in spontaneous intracerebral hemorrhage (ICH), often resulting in significant morbidity. We aimed to assess the functional outcome and identify predictors of functional neurological outcome after single and multiple symptomatic hemorrhages. METHODS: As part of an international multicenter collaboration, institutional databases from 3 different tertiary referral centers included BSCM patients with complete baseline characteristics, MRI Data set, ≥1 ICH, and ≥1 follow-up examination followed at our institutions between 2003 and 2023. Functional neurological outcome was obtained using the modified Rankin Scale at diagnosis, before and after each ICH, and last follow-up. Patients were excluded after surgical removal of the lesion and/or loss of follow-up. RESULTS: A total of 383 patients (41.47 ± 15.51 age; 220 [57.4%] female) were included and followed for an average of 63.16 ± 85.75 months. Functional neurological outcome deteriorated in 47.2% ( P = .010) after the second ICH and in 46.5% ( P = .007) after the third ICH. Moreover, the functional neurological status was impaired in 22.3% ( P < .001) of patients at last available follow-up compared with the time of BSCM diagnosis. CONCLUSION: In our study, we observed that the chance of full recovery might decrease with each ICH. We observed a significantly associated neurological deterioration after each ICH compared with initial ICH.

Abstract With the rapid advancements in large language model technology and the emergence of bioinformatics‐specific language models (BioLMs), there is a growing need for a comprehensive analysis of the current landscape, computational characteristics, and diverse applications. This survey aims to address this need by providing a thorough review of BioLMs, focusing on their evolution, classification, and distinguishing features, alongside a detailed examination of training methodologies, datasets, and evaluation frameworks. We explore the wide‐ranging applications of BioLMs in critical areas such as disease diagnosis, drug discovery, and vaccine development, highlighting their impact and transformative potential in bioinformatics. We identify key challenges and limitations inherent in BioLMs, including data privacy and security concerns, interpretability issues, biases in training data and model outputs, and domain adaptation complexities. Finally, we highlight emerging trends and future directions, offering valuable insights to guide researchers and clinicians toward advancing BioLMs for increasingly sophisticated biological and clinical applications.

Abstract Background Acupuncture, a key modality in traditional Chinese medicine, is gaining global recognition as a complementary therapy and a subject of increasing scientific interest. However, fragmented and unstructured acupuncture knowledge spread across diverse sources poses challenges for semantic retrieval, reasoning, and in-depth analysis. To address this gap, we developed AcuKG, a comprehensive knowledge graph that systematically organizes acupuncture-related knowledge to support sharing, discovery, and artificial intelligence–driven innovation in the field. Methods AcuKG integrates data from multiple sources, including online resources, guidelines, PubMed literature, ClinicalTrials.gov, and multiple ontologies (SNOMED CT, UBERON, and MeSH). We employed entity recognition, relation extraction, and ontology mapping to establish AcuKG, with human-in-the-loop to ensure data quality. Two cases evaluated AcuKG’s usability: (1) how AcuKG advances acupuncture research for obesity and (2) how AcuKG enhances large language model (LLM) application on acupuncture question-answering. Results AcuKG comprises 1839 entities and 11 527 relations, mapped to 1836 standard concepts in 3 ontologies. Two use cases demonstrated AcuKG’s effectiveness and potential in advancing acupuncture research and supporting LLM applications. In the obesity use case, AcuKG identified highly relevant acupoints (eg, ST25, ST36) and uncovered novel research insights based on evidence from clinical trials and literature. When applied to LLMs in answering acupuncture-related questions, integrating AcuKG with GPT-4o and LLaMA 3 significantly improved accuracy (GPT-4o: 46% → 54%, P = .03; LLaMA 3: 17% → 28%, P = .01). Conclusion AcuKG is an open dataset that provides a structured and computational framework for acupuncture applications, bridging traditional practices with acupuncture research and cutting-edge LLM technologies.

Abstract Background Delirium is often underdiagnosed in clinical practice and is not routinely coded for billing. While manual chart review can identify delirium, it is labor-intensive and impractical for large-scale studies. Natural language processing (NLP) can analyze unstructured text in electronic health records (EHRs) to extract meaningful clinical information. Methods To support national integration of NLP for EHR-based delirium identification across different institutions, we launched the Delirium Interest Group within the national Evolve to Next-Gen Accrual to Clinical Trials (ENACT) NLP Working Group. This paper outlines our initial efforts to standardize, evaluate, and translate an NLP-based delirium detection model into the i2b2/ENACT platform. Results Multisite contextual inquiry identified several key challenges, including variations in local screening practices (eg, tools used, documentation frequency, and quality control), the need for harmonized definitions in the context of EHRs, and the complexity of modeling temporal logic. Multisite NLP evaluation revealed variable performance degradation driven by differences in delirium screening practices, clinical documentation patterns and semantics, and note syntactic structures. Conclusion Our work represents an important first step toward enabling scalable and standardized NLP-based delirium detection across institutions. By engaging diverse institutions through the ENACT NLP Working Group, we identified shared challenges and site-specific variations that impact model implementation and performance. Our collaborative approach enabled the development of a more robust framework for delirium identification across heterogeneous EHR systems. Future efforts will build on this foundation to enhance the validity, usability, and translational impact of delirium detection.

Abstract Diffuse large B-cell lymphoma (DLBCL) poses a challenge in hematology given its varied symptoms, and the complex interplay between disease and treatment effects on health-related quality of life (HRQoL). The phase 3 POLARIX study demonstrated superior progression-free survival and a similar safety profile with polatuzumab vedotin plus rituximab, cyclophosphamide, doxorubicin, and prednisone (Pola-R-CHP) vs R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) in patients with previously untreated DLBCL. Here, we evaluate HRQoL through patient-reported outcome (PRO) instruments to fully characterize the patient experience in the POLARIX study. Changes from baseline in HRQoL, lymphoma symptoms, and gastrointestinal (GI) symptoms were assessed, as well as incidence and severity of common symptoms by PROs vs clinician-reported adverse events (AEs). Baseline characteristics of PRO-evaluable patients (N = 874) were consistent. Comparison between PROs and clinician-reported AEs revealed a notable discordance; patients generally reported a higher incidence of symptoms than clinicians, emphasizing the need for patient-centric tools to accurately capture the patient experience. Both treatments exhibited rapid and sustained improvements in HRQoL and lymphoma symptoms, with the most substantial improvements seen in global health status/QoL, lymphoma symptoms, fatigue, role, emotional, and social functioning. GI symptoms (diarrhea, constipation, nausea, and vomiting) were generally similar between treatment arms and returned to baseline levels after treatment completion. These HRQoL data underscore the complementarity of PROs, as an adjunct to clinician-reported AEs, in evaluating the efficacy and tolerability of new treatments, including Pola-R-CHP, which may represent a new benchmark for patient-reported HRQoL in previously untreated DLBCL. This trial was registered at www.clinicaltrials.gov as NCT03274492.

Abstract BACKGROUND Tau‐derived cerebrospinal fluid (CSF) biomarkers correlate with amyloid‐beta (Aβ) plaques or tau tangles in Alzheimer's disease (AD). This study assessed the effects of long‐term anti‐Aβ antibodies on amyloid plaques, tau tangles, and CSF tau species to determine the relationships between them. METHODS A post‐hoc analysis of the DIAN‐TU‐001 trial (NCT01760005) examined 142 participants at risk for dominantly inherited AD randomized to solanezumab ( n = 50), gantenerumab ( n = 52), or placebo ( n = 40). High‐resolution mass spectrometry quantified CSF tau species over four years. RESULTS Phosphorylated tau (p‐tau) species (153, 181, 217, 231) increased early in preclinical AD but were reduced with gantenerumab‐mediated Aβ plaque reduction. Nearly a decade later, MTBR‐tau243 and p‐tau205 increased, showing no association with Aβ reduction, aligning with tau tangle pathology progression. DISCUSSION Initially changing soluble p‐tau species track Aβ plaque reduction, while ptau205 and MTBR‐243 reflect tau tangle pathology, informing different pathways of therapeutic strategies. Highlights p‐tau217 and p‐tau231 correlate with Aβ‐PET and respond to Aβ‐plaque lowering therapies. Aβ immunotherapy trials support a direct link between p‐tau changes and Aβ plaques Gantenerumab reduces Aβ plaques but does not affect tau NFT‐related biomarkers. Blood‐based p‐tau217 assays may provide a non‐invasive tool to monitor Aβ therapies. MTBR‐tau243 strongly correlates with tau PET and tracks NFT pathology progression. Further studies are needed to validate tau biomarkers for tracking NFT‐targeting therapies.

ABSTRACT While BAG3 has been identified as a causative gene for dilated cardiomyopathy, the major pathological events in BAG3‐ related cardiomyopathy that could be targeted for therapeutic benefit remain to be discovered. Here, we aim to uncover novel pathological events through genetic studies in a zebrafish bag3 cardiomyopathy model. Given the known cardioprotective effects of mtor inhibition and the fact that transcription factor EB (tfeb ) encodes a direct downstream phosphorylation target of mTOR signaling, we generated a cardiomyocyte‐specific transgenic line overexpressing tfeb ( Tg[cmlc2:tfeb] ). This overexpression was sufficient to restore defective proteostasis and rescue cardiac dysfunction in the bag3 cardiomyopathy model. Importantly, we detected accelerated cardiac senescence in the bag3 cardiomyopathy model, which can be mitigated by Tg(cmlc2:tfeb) . We compared cardiac transcriptomes between the Tg(cmlc2:tfeb) transgenic fish and the mtor xu015/+ mutant and found that inhibition of the fatty acid binding protein a ( fabp7a ) gene exerts therapeutic effects. Consistent with this genetic evidence, we detected elevated fabp7a expression in the bag3 cardiomyopathy model, whereas cardiomyocyte‐specific overexpression of fabp7a induced dysregulated proteostasis, accelerated cardiac senescence, and cardiac dysfunction. To elucidate the functions of Fabp7a in normative cardiac aging, we turned to the African Turquoise Killifish. We noted elevated Fabp7a expression in the hearts of aged killifish, and pharmacological inhibition of Fabp7a mitigated the cardiac aging process. Together, this study uncovered accelerated cardiac senescence as a key pathological event in bag3 cardiomyopathy and reveals that manipulating the mTOR‐Tfeb‐Fabp7a axis can mitigate this pathology and confer cardioprotective effects.

Objective: Patients with chronic pancreatitis commonly experience abdominal pain, anxiety, depression, reduced mobility, and difficulty performing daily activities or maintaining employment. These factors contribute to diminished quality-of-life and high healthcare utilization. This study aims to explore the relationship between specific quality-of-life domains among patients with chronic pancreatitis. Methods: A 55-item online survey was administered to patients with the diagnosis of chronic pancreatitis at 3 Mayo Clinic sites from December 26, 2023, to December 26, 2024. The survey included validated questions assessing demographic, clinical, and quality-of-life metrics using EuroQol 5-Dimension 5-Level instrument—a standardized assessment tool that evaluates 5 key health dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Results: Of the 298 patients with chronic pancreatitis who completed the survey, employed patients had decreased odds of reporting problems with mobility (odds ratio [OR] = 0.45, P < .05), self-care (OR = 0.26, P < .01), usual activities (OR = 0.47, P < .05), and anxiety/depression (OR = 0.41, P < .05). Similarly, older patients had decreased odds of reporting problems with self-care (OR = 0.91, P < .01), usual activities (OR = 0.96, P < .01), pain/discomfort (OR = 0.96, P < .01) and anxiety/depression (OR = 0.92, P < .01). However, Medicare patients had greater odds of reporting problems with self-care (OR = 5.54, P < .01) and pain/discomfort (OR = 2.58, P < .05). Conclusions: Chronic pancreatitis impacts multiple dimensions of quality-of-life beyond pain. The EuroQol 5-Dimension 5-Level tool enables comprehensive assessment of physical and mental health. Our findings highlight key associations between patient characteristics and quality-of-life domains, supporting the need for individualized, deficit-targeted interventions. These results also suggest a potential role for vocational rehabilitation in promoting functional recovery and enhancing overall well-being in individuals with chronic pancreatitis.

ABSTRACT Aims The impact of treatment for tricuspid regurgitation (TR) across different levels of left ventricular ejection fraction (LVEF) remains uncertain. This study aimed to compare the outcomes of surgical and transcatheter tricuspid valve interventions (TTVI) to conservative (medical) management across LVEF categories. Methods and results Patients with severe isolated TR from the TRIGISTRY, a multicentre international registry, were categorized based on LVEF (preserved ejection fraction [pEF]: ≥50%, mildly reduced ejection fraction [mrEF]: 41–49%, and reduced ejection fraction [rEF]: ≤40%). We assessed the impact of treatment modality and procedural success (mild-to-moderate or lower residual TR) on 2-year survival within each LVEF category. Among 2384 patients, 1383 had pEF, 400 had mrEF, and 601 had rEF. Compared to conservative management, surgery (p &lt; 0.0005) and TTVI (p &lt; 0.0001) were associated with a survival benefit in patients with pEF. No significant survival advantage was observed in patients with mrEF (p = 0.28 for both), nor in those with rEF (p = 0.76 and p = 0.22, respectively). Similar results were obtained when surgical and transcatheter interventions were grouped (p &lt; 0.0001, p = 0.17 and p = 0.29 in patients with pEF, mrEF and rEF, respectively). Patients with residual TR after TTVI exhibited a trend toward worse survival compared to those managed conservatively across all LVEF categories (p = 0.47, p = 0.33 and p = 0.008 in pEF, mrEF and rEF, respectively). Conclusions Transcatheter tricuspid valve intervention, whether surgical or transcatheter-based, was associated with improved survival in patients with pEF but not in those with mrEF or rEF. Residual TR remained a significant prognostic factor across the entire LVEF spectrum. These findings highlight the need for careful patient selection when considering TTVI in individuals with rEF.