Citations

Stereotactic radiosurgery was associated with a higher obliteration rate compared with embolization in patients with eloquent brain arteriovenous malformations, whereas there was no evidence of a difference in functional outcomes or complications after adjustment.

Of the thousands of genes and substrates identified in KRAS-mutant signaling networks in pancreatic ductal adenocarcinoma (PDAC), more than 200 are transcription factors, implying extensive and complex transcriptional regulation. However, we observed that genetic suppression of the transcription factor MYC alone was sufficient to phenocopy the effect of KRAS suppression in signaling, growth, and metabolic processes in PDAC cells. We determined the gene transcription changes caused by acute suppression of MYC function in KRAS -mutant PDAC cell lines and performed dependency map and pathway analyses on the affected gene sets. The expression of 1685 genes was increased upon suppression of MYC, and this gene set may comprise the bulk of the MYC-regulated genes essential for PDAC growth. In contrast, the 1325 genes whose expression was inhibited may comprise a compensatory response to oncogenic stress, mediated in part by the GTPase RHO. MYC-dependent transcriptional activity was largely ERK dependent, and almost one-third of ERK-regulated genes were also regulated by MYC in PDAC cells. Furthermore, chemical proteomic profiling revealed MYC-regulated protein kinases that can be targeted therapeutically. Together, these data provide a molecular portrait of MYC-dependent signaling that encompasses potentially exploitable mechanisms for treating PDAC.

Abstract Purpose: Isocitrate dehydrogenase (IDH) 1/2–isoform inhibitors have clinical efficacy in IDH1/IDH2-mutated neoplasms. However, primary resistance and secondary resistance limit their therapeutic potential. LY3410738, an oral, brain-penetrant, dual IDH1/IDH2-mutated isoform-selective inhibitor, was designed to overcome resistance. Patients and Methods: This global, multicenter, open-label, phase I study of patients with IDH-mutant solid tumors evaluated LY3410738 as monotherapy (dose escalation) for advanced solid tumors in combination with cisplatin–gemcitabine (CISGEM) for newly diagnosed cholangiocarcinoma or with durvalumab for relapsed/refractory cholangiocarcinoma (dose expansion; NCT04521686). Primary objectives were the maximum tolerated dose, recommended phase II dose, and preliminary antitumor activity. Safety, pharmacokinetics, inhibition of D-2-hydroxyglutarate, and ctDNA were assessed. Results: Overall, 119 patients received LY3410738 alone (N = 94) or in combination with CISGEM (N = 19) or durvalumab (N = 6). No dose-limiting toxicities were observed; the maximum tolerated dose was not determined. Common adverse events included nausea, vomiting, and decreased appetite. Overall response rates of 5.2% and 11.1% and disease control rates of 56.9% and 63.0% were observed for patients with relapsed/refractory IDH1- or IDH2-mutant cholangiocarcinoma or IDH1-mutant glioma, respectively. D-2-hydroxyglutarate normalization was rapid and durable. In dose-expansion cohorts, combination treatments were tolerable, with one dose-limiting toxicity in the durvalumab cohort. LY3410738 plus CISGEM demonstrated a response rate of 42.1%, a median duration of response of 8.1 months, and a median progression-free survival of 10.2 months for patients with newly diagnosed IDH-mutant cholangiocarcinoma. Conclusions: LY3410738 demonstrated largely cytostatic antitumor activity in IDH1- or IDH2-mutated cholangiocarcinoma and IDH1-mutated gliomas. LY3410738 plus CISGEM exhibited favorable antitumor activity in patients with treatment-naïve IDH-mutated cholangiocarcinoma, warranting further exploration as a treatment strategy.

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 Lung adenocarcinoma in never-smokers is a major public health burden, especially among East Asian women. Polygenic risk scores (PRSs) are promising for risk stratification but are primarily developed in European-ancestry populations. We aimed to develop and validate single- and multi-ancestry PRSs for East Asian never-smokers to improve lung adenocarcinoma risk prediction. Methods PRSs were developed using genome-wide association study summary statistics from East Asian (8002 cases; 20 782 controls) and European (2058 cases; 5575 controls) populations. Single-ancestry models included a PRS with 25 single nucleotide variants (PRS-25), PRS clumping and thresholding (CT), and LDpred2; multi-ancestry models included LDpred2 plus European PRS-128, PRS-CSx, and clumping and thresholding, super learning, empirical Bayes (CT-SLEB). Performance was evaluated in independent East Asian data from the Female Lung Cancer Consortium and externally validated in the Nanjing Lung Cancer Cohort. We assessed predictive accuracy via area under the curve operating procedure (AUC), with 10-year and (ages 30-80 years) absolute risks estimates. Results The best multi-ancestry PRS, using East Asian and European data via CT-SLEB, outperformed the best East Asian-only (LDpred2; AUC = 0.629, 95% confidence interval [CI] = 0.618 to 0.641), achieving an AUC of 0.640 (95% CI = 0.629 to 0.653) and odds ratio of 1.71 (95% CI = 1.61 to 1.82) per standard deviation increase. Nanjing Lung Cancer Cohort validation confirmed robust performance (AUC = 0.649, 95% CI = 0.623 to 0.676). The top 20% PRS group had a 3.92-fold higher lung adenocarcinoma risk than the bottom 20%. Further, the top 5% PRS group reached a 6.69% lifetime absolute risk. Notably, this group reached the average population 10-year lung adenocarcinoma risk at age 50 years (0.42%) by age 41 years, 9 years earlier. Conclusions Multi-ancestry PRS approaches enhance lung adenocarcinoma risk stratification in East Asian never-smokers, with consistent external validation, suggesting future clinical utility.

ImportanceStudies suggest that everolimus may reduce the risk of rejection, cardiac allograft vasculopathy (CAV), chronic kidney disease (CKD), and cytomegalovirus (CMV) after heart transplant. Everolimus use is controversial because of data demonstrating higher infection deaths when everolimus is introduced de novo after transplant. It is unclear whether everolimus is safe and effective when initiated at 6 months posttransplant in children, a population in which median graft survival is limited to 15 years and randomized clinical trials are lacking.ObjectiveTo evaluate the safety and efficacy of everolimus combined with low-dose tacrolimus to prevent major adverse transplant events (MATEs) in children after heart transplant.Design, Setting, and ParticipantsMulticenter, randomized, open-label, clinical trial enrolling 211 patients who were alive 6 months after pediatric heart transplant at 25 US sites from February 2018 to August 2020. The last date of follow-up was April 17, 2023.InterventionsParticipants were randomized to receive everolimus and low-dose tacrolimus (n = 107) or standard-dose tacrolimus and mycophenolate mofetil (n = 104) for 30 months.Main Outcomes and MeasuresThe primary efficacy end point was the MATE-3 score at 30 months, a validated composite ordinal end point including acute cellular rejection, CAV, and CKD. The primary safety end point was the MATE-6 score, encompassing the MATE-3 score plus antibody-mediated rejection, infection, and posttransplant lymphoproliferative disorder.ResultsAmong 211 children randomized, the mean age was 8.2 (SD, 6.3) years, 97 (46%) underwent transplant for congenital heart disease, and 49 (23%) were treated for rejection before 6 months. At 30 months, the mean MATE-3 score did not differ between the 2 treatment groups (mean difference, −0.32; 95% CI, −0.90 to 0.20; P = .16). The mean MATE-6 score was no higher in the everolimus group than in the mycophenolate group (baseline-adjusted mean difference, −0.40; 95% CI, −1.81 to 0.93), meeting the success criterion for safety (noninferiority margin <3). There were no differences in graft survival, MATE-free survival, or freedom from any individual MATE. Everolimus was associated with greater improvement in estimated glomerular filtration rate at 12 months (mean difference, 10.5 mL/min/1.73 m2; 95% CI, 1.09-19.91 mL/min/1.73 m2) and a lower incidence of CMV infection (hazard ratio, 0.50; 95% CI, 0.26-0.93).Conclusions and RelevanceAmong 6-month pediatric heart transplant survivors, everolimus and low-dose tacrolimus did not differ from tacrolimus and mycophenolate in preventing the composite of cellular rejection, CAV, and CKD at 30 months. However, everolimus and low-dose tacrolimus appear to be safe based on the total burden of 6 MATEs and may be associated with improved kidney function and less CMV infection.Trial RegistrationClinicalTrials.gov Identifier: NCT03386539

Abstract In March of 2025, 145 attendees convened at the Hub for Clinical Collaboration of the Children's Hospital of Philadelphia for the inaugural International Society for Magnetic Resonance in Medicine (ISMRM) Body MRI Study Group workshop entitled “Body MRI: Unsolved Problems and Unmet Needs.” Approximately 24% of the attendees were MD or MD/PhD's, 45% were PhD's, and 30% were early‐career trainees and postdoctoral associates. Among the invited speakers and moderators, 28% were from outside the United States, with a 40:60% female‐to‐male ratio. The 2.5‐day program brought together a multidisciplinary group of scientists, radiologists, technologists, and trainees. Session topics included quantitative imaging biomarkers, low‐ and high‐field strengths, artifact and motion correction, rapid imaging and focused protocols, and artificial intelligence. Another key session focused on the importance of team science and allowed speakers from academia and industry to share their personal experiences and offer advice on how to successfully translate new MRI technology into clinical practice. This article summarizes key points from the event and perceived unmet clinical needs within the field of body MRI.

Background and objectives Arteriovenous malformations (AVMs) with perinidal aneurysms and single draining vein are associated with an elevated risk of rupture and increased procedural complexity. The role of preoperative embolization in this high-risk anatomical subset remains unclear. This study aimed to evaluate the safety and efficacy of microsurgery with preoperative embolization, compared with microsurgery alone in patients with such AVMs. Methods We conducted a multicenter retrospective analysis of an AVM registry from the MISTA (Multicenter International Study for Treatment of Brain AVMs) consortium and included AVMs with perinidal aneurysms and a single draining vein. Baseline characteristics, angiographic outcomes, functional outcomes, and complication rates were compared. Propensity score weighting (PSW) using the covariate balancing method was applied to adjust for baseline differences. Results Out of a total of 1919 patients, 65 met the inclusion criteria; 45 patients underwent preoperative embolization followed by microsurgery, and 20 underwent microsurgery alone. After adjustment, complete obliteration rates were similar between groups (OR 0.87, 95% CI 0.04 to 16.33, P=0.92), as were rates of functional independence at discharge and follow-up. Overall complication, symptomatic complication, and mortality rates did not differ significantly between groups. However, permanent complications were significantly lower in patients with preoperative embolization (OR 0.06, 95% CI 0.004 to 0.84, P=0.03). Discussion In patients with AVMs featuring perinidal aneurysms and single draining vein, preoperative embolization followed by microsurgery was associated with fewer permanent complications and no increase in adverse outcomes compared with microsurgery alone. However, given the small number of events, this finding should be interpreted cautiously.

Abstract Objective: Electronic Health Record (EHR) data are critical for advancing translational research and AI technologies. The ENACT network offers access to structured EHR data across 57 CTSA hubs. However, substantial information is contained in clinical narratives, requiring natural language processing (NLP) for research. The ENACT NLP Working Group was formed to make NLP-derived clinical information accessible and queryable across the network. Methods: We established the ENACT NLP Working Group with 13 sites selected based on criteria including clinical notes access, IT infrastructure, NLP expertise, and institutional support. We divided sites into five focus groups targeting clinical tasks within disease contexts. Each focus group consisted of two development sites and two validation sites. We extended the ENACT ontology to standardize NLP-derived data and conducted multisite evaluations using the Open Health Natural Language Processing (OHNLP) Toolkit. Results: The working group achieved 100% site retention and deployed NLP infrastructure across all sites. We developed and validated NLP algorithms for rare disease phenotyping, social determinants of health, opioid use disorder, sleep phenotyping, and delirium phenotyping. Performance varied across sites (F1 scores 0.53–0.96), highlighting data heterogeneity impacts. We extended the ENACT common data model and ontology to incorporate NLP-derived data while maintaining Shared Health Research Informatics NEtwork (SHRINE) compatibility. Conclusion: This demonstrates feasibility of deploying NLP infrastructure across large, federated networks. The focus group approach proved more practical than general-purpose approaches. Key lessons include the challenge of data heterogeneity and importance of collaborative governance. This work also provides a foundation that other networks can build on to implement NLP capabilities for translational research.