Citations

Abstract Current discussion surrounding the clinical capabilities of generative language models (GLMs) predominantly center around multiple-choice question-answer (MCQA) benchmarks derived from clinical licensing examinations. While accepted for human examinees, characteristics unique to GLMs bring into question the validity of such benchmarks. Here, we validate four benchmarks using eight GLMs, ablating for parameter size and reasoning capabilities, validating via prompt permutation three key assumptions that underpin the generalizability of MCQA-based assessments: that knowledge is applied, not memorized, that semantic consistency will lead to consistent answers, and that situations with no answers can be recognized. While large models are more resilient to our perturbations compared to small models, we globally invalidate these assumptions, with implications for reasoning models. Additionally, despite retaining the knowledge, small models are prone to answer memorization. All models exhibit significant failure in null-answer scenarios. We then suggest several adaptations for more robust benchmark designs more reflective of real-world conditions.

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.

ABSTRACT Autosomal dominant polycystic kidney disease (ADPKD) is a genetic disease that is caused by mutations in PKD genes. Glucagon‐like peptide‐1 (GLP‐1) receptor agonists (GLP‐1RAs) are a class of medications that mimic the actions of the hormone GLP‐1, conferring beneficial effects on weight management and other metabolic conditions. However, whether GLP‐1RA plays a kidney‐protective action in ADPKD remains unknown. In this study, we define the role and mechanisms of one of the most popular GLP‐1RA agonists, Semaglutide, in ADPKD. We show that the expression of GLP‐1R is decreased in Pkd1 mutant renal epithelial cells and kidneys. Treatment with Semaglutide delays cyst growth in aggressive and long‐lasting Pkd1 mutant mouse models. Treatment with Semaglutide (1) decreases glucose uptake, ATP generation, and glycolysis, (2) deactivates PKD‐associated signaling pathways, including Rb, S6, and Stat3, resulting in a decrease in cell proliferation, (3) deactivates NF‐kB signaling pathways, resulting in a decrease in the expression of cytokines and the recruitment of macrophages, (4) normalizes mitochondrial morphology and function, (5) induces Pkd1 mutant renal epithelial cell death, (6) induces ketosis characterized by an increase in serum level of beta‐hydroxybutyrate (BHB) and the activation of AMPK, and (7) alleviates renal fibrosis through deactivation of TGF‐b signaling in Pkd1 mutant mouse kidneys. This study highlights the potential of GLP‐1R agonists as a novel therapeutic strategy for ADPKD treatment.

Abstract Front-line pharmaceutical interventions for treating acute graft-versus-host disease (GVHD) are not uniformly effective and have toxic side effects. Myeloid-derived suppressor cells (MDSCs) are a heterogeneous population of immature myeloid cells with potent in vitro and in vivo immunosuppressive functions. Clinical translation of in vitro–generated MDSCs has been limited because of requirements for multiple, high infusion doses, the relatively low yield from peripheral blood–sourced MDSCs (PB-MDSCs), and inconsistent product quality. To circumvent these obstacles, we developed a methodology to generate MDSCs using human induced pluripotent stem cell (iPSC)–derived CD34+ cells. Compared with PB-MDSCs, iPSC-derived MDSCs (iMDSCs) shared similar morphology, phenotype, and suppressive function. We found that the CD14+ iMDSC subset possessed the highest suppressor function. In previous studies, we reported that MDSCs transferred into mice with GVHD lost suppressor function because of inflammasome activation and immature myeloid cell maturation. In striking contrast to human PB-MDSCs, we show herein that iMDSCs retained 95% of suppressor function in vitro despite exposure to lipopolysaccharide (LPS) plus adenosine triphosphate (ATP), which are stimuli that activate the inflammasome via danger-associated molecular patterns released during early posttransplant conditioning and GVHD-induced injury. In an in vivo xenogenic GVHD model with PB mononuclear cells, iMDSCs significantly increased recipient survival without loss of antileukemia effects. iMDSC RNA sequencing and gene knockdown studies revealed that the maintenance of the purine metabolizing enzyme, phosphoglycerate dehydrogenase, during LPS plus ATP treatment, was linked to iMDSC inflammasome resistance. Taken together, these findings provide a platform for translating in vitro–generated, off-the-shelf iMDSCs into the clinic for suppressing a spectrum of adverse immune responses, including GVHD.

Summary CD19 chimeric antigen receptor T‐cell (CAR‐T) therapy is a pivotal part of the treatment algorithm for large B‐cell lymphoma (LBCL) in the second‐ and third‐line settings based on numerous clinical trials. However, these studies included very few patients with a diagnosis of high‐grade B‐cell lymphoma, not otherwise specified (HGBCL‐NOS) and it is unclear if outcomes are similar to those observed with more common LBCL histologies. Using the Center for International Blood and Marrow Transplant Research (CIBMTR) registry, we identified 111 HGBCL‐NOS patients who received CAR‐T therapy. The cytokine release syndrome (CRS) rate was 74% (7.7% grade 3+), median onset was 4 days (1–17) and immune effector cell‐associated neurotoxicity syndrome rate was 45.2% (22.6% grade 3+), median onset was 7 days (1–17). At 2 years post‐CAR‐T infusion, the probability of overall survival and progression‐free survival were 41.6% and 28.7% respectively. The 2‐year non‐relapse mortality and relapse/progression were 3.1% (95% confidence interval [CI]: 0.6–7.6) and 68.1% (95% CI: 57.9–77.6) respectively. Our analysis illustrates that patients with HGBCL‐NOS represent a particularly difficult group to treat, even with CAR‐T therapy. We observed that one third of patients achieved a durable response; however, the overall results were less favourable, with lower overall response rate, overall survival and progression‐free survival as compared to published reports on LBCL.

Abstract The Centiloid scale is the standard for Amyloid (Aβ) PET quantification, widely used in research, clinical settings, and trial stratification. However, variability between tracers and scanners remains a challenge. This study introduces DeepSUVR, a deep learning method to correct Centiloid quantification, by penalising implausible longitudinal trajectories during training. The model was trained using data from 2,098 participants (6,762 Aβ PET scans) in AIBL/ADNI and validated using 15,806 Aβ PET scans from 10,543 participants across 10 external datasets. DeepSUVR increased correlation between tracers, and reduced variability in the Aβ-negatives. It showed the strongest association with cognition, highest AUC against visual reads and best longitudinal consistency between studies. DeepSUVR also increased the effect size for detecting lower Centiloid increase per year in the A4 study. DeepSUVR advances Aβ PET quantification, outperforming standard approaches, which is particularly important for consistent decision making and to detect subtle and early changes in clinical interventions.

CDK12 primarily functions as a transcription regulatory cyclin-dependent kinase (CDK) that controls mRNA elongation, splicing, and polyadenylation. The CDK12 gene is implicated in human cancers since it is frequently mutated and/or deleted in prostate and ovarian cancer but paradoxically amplified in breast cancer. Here, we demonstrate that CDK12 promotes serine-933 phosphorylation of DNA2, a nuclease/helicase critical for replication fork stress regulation, and the phosphorylation subsequently facilitates DNA2 polyubiquitination and degradation mediated by the APC/C CDC20 E3 ubiquitin ligase. CDK12 inactivation induces but amplification suppresses genome-wide expression of interferon response and antigen processing and presentation machinery genes in ovarian and breast cancer cells, respectively. Besides causing aberrant DNA2 stabilization, replication stress, genomic instability, and cytosolic double-stranded DNA (dsDNA) accumulation, CDK12 loss also triggers cGAS–STING activation and innate immune response, which can be reversed by forced expression of replication protein A (RPA) subunits or DNA2 depletion. Our findings identify DNA2 as a phosphorylation substrate of CDK12, connecting CDK12 to cell cycle regulation. These data also reveal DNA2 protein destruction as a critical mechanism that dictates genomic instability, cGAS–STING signaling activation, and innate immune response in CDK12-deregulated cancers.

Abstract Background Migraine patients show choroid plexus (CP) changes, impairing the blood-CSF barrier. The CP regulates circadian rhythms, but links between CP circadian genes and migraine are unexplored. Objective This study examined CP circadian gene transcriptome changes in a chronic migraine rat model versus controls to identify migraine-related pathways. Design Chronic migraine model: Sprague Dawley rats (3 females, 3 males) received nitroglycerine (NTG) every other day for 9 days; controls (3 females, 3 males) got saline. CP from the 4th ventricle was collected 2 hours post-final injection for RNAseq. Methods Migraine Behavior: Von Frey hair tests on days 1, 5, and 9, pre- and 2 hours post-NTG/saline injection, assessed basal and NTG-induced pain thresholds. RNAseq & Analysis: Differentially expressed genes (p < 0.05, fold change > 1) were identified. GO, KEGG, and Reactome enrichment analyses evaluated circadian gene expression changes. Results NTG group showed reduced basal and NTG-induced pain thresholds on days 1, 5, and 9. Females had more upregulated genes ( MT2A , SLC7A11 ), males upregulated ZBTB16 , S100A8 . SLC7A11 , SCG2 , GRIA1 showed inverse regulation (up in females, down in males). Circadian gene expression altered: 10 genes upregulated (e.g., SERPINE1, MAPK9, ATF4 ), 13 downregulated (e.g., PER2, DBP, EZH2 ). Sex-specific differences: females ( FBXL12, GPR157 ), males ( NKX2-1, ATF4, CLOCK ). GO/KEGG analyses revealed significant enrichment of circadian rhythm-related pathways, insulin resistance, and inflammatory response processes, with sex-specific differences: females showed HIF-1 signaling and hemoglobin-related pathways, while males exhibited arachidonic acid and leukotriene production. Conclusion CP transcriptomics in the rat migraine model revealed sex-specific gene regulation, with females upregulating antioxidant genes (MT2A, SLC7A11) and males upregulating inflammatory factors (ZBTB16, S100A8), alongside circadian disruption (e.g., SERPINE1 upregulated, PER2 downregulated). Pathway analyses indicate enriched circadian rhythms, HIF-1 signaling (females), inflammatory processes (males), lipid metabolism (PPARα), and heme signaling, highlighting sex-specific and circadian targets for migraine therapy.