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Cardiovascular (CV) dysfunction is common in severe acute pancreatitis (AP) and contributes substantially to mortality. Although sex differences in CV diseases are well recognized, with males generally exhibiting higher risk and poorer outcomes, their influence on AP-associated CV responses remains poorly defined. Here, we examined sex-dependent alterations in vascular integrity and cardiac function using cerulein-induced mouse models of AP. Because obesity is associated with more severe forms of AP, cerulein was used to induce mild AP in lean wild-type C57BL/6J mice and a more severe phenotype in obese C57BL/6J mice. Across both models, pancreatic injury was comparable between sexes. A modest sex difference in vascular permeability was observed in the mild but not severe AP model. In mild AP, both males and females showed similar compensatory increases in cardiac systolic function; however, in severe AP, only female mice maintained this adaptive systolic augmentation. Circulating levels of free fatty acids, reflecting systemic tissue lipolysis, were lower in females. Impaired cardiac adaptation in males was accompanied by higher levels of seven different myocardial inflammatory cytokines, as well as elevated circulating levels of angiopoietin-2 (Angpt2). While Angpt2 levels correlated with the severity of cardiac dysfunction, Angpt2 neutralization did not improve, and indeed worsened cardiac function in males. Together, these findings delineate both sex-dependent and sex-independent CV responses in mild and severe AP and identify Angpt2 as a potential compensatory cardioprotective factor under obesity-associated severe AP.

Importance The incidence of human papillomavirus type 16 (HPV16–positive) recurrent/metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) is rising. Approved therapies offer a durable response to a minority of patients. Objective To determine the efficacy and safety of a therapeutic HPV16-targeted immunotherapy, PDS0101, in combination with pembrolizumab in participants with HPV16-positive R/M HNSCC, with separate evaluation of immune checkpoint inhibitor (ICI)–naive and ICI-resistant cohorts. Design, Setting, and Participants VERSATILE-002 was a phase 2, open-label, multicenter nonrandomized clinical trial conducted at 26 oncology centers from March 29, 2021, to May 15, 2025, across the US, UK, and Ireland using the Simon 2-stage optimal design. Efficacy analyses were performed on modified intent-to-treat (mITT) population; safety analyses included all participants who received 1 or more doses. Eighty-eight participants with histologically confirmed R/M HPV16-positive HNSCC were enrolled, of whom 87 (98.9%) received treatment and composed the safety population. Seventy five (85.2%) were in the mITT population used for efficacy analyses, of whom 53 (70.7%) were ICI-naive with a programmed cell death ligand 1 combined positive score of 1 or greater and 22 (29.3%) were ICI-resistant. Exposures Pembrolizumab (200 mg, intravenously, every 3 weeks for up to 35 cycles) plus subcutaneous PDS0101 (5 scheduled doses per protocol). Main Outcomes and Measures The primary end point was objective response rate (ORR) per the Response Evaluation Criteria in Solid Tumors , version 1.1, by a masked independent central reviewer. Secondary end points included progression-free survival (PFS), median overall survival (mOS), and safety, with exploratory end points of duration of response, disease control rate, and response rates by programmed cell death ligand 1 status. Results Of the 75 patients in the mITT population, the mean (SD) age was 64.0 (8.3) years; 4 individuals (5%) were female and 71 (95%) were male; and 2 individuals (3%) were Asian, 1 (1%) was Black, 5 (7%) were Hispanic, and 71 (95%) were White. Among 53 ICI-naive participants in the mITT cohort, ORR by the central reviewer was 34.0%, median PFS was 5.3 months (95% CI, 2.10-9.00), and mOS was 39.3 months (95% CI, 23.90 to not evaluable). Among 22 ICI-resistant patients in the mITT cohort, no objective responses were observed and the primary end point (ORR by central reviewer) was not met, but mOS was 14.8 months (95% CI, 8.50-26.00). The treatment was well tolerated, with 13.8% experiencing grade 3 or higher treatment-related adverse events. Conclusions and Relevance The results of this nonrandomized clinical trial suggest that PDS0101 plus pembrolizumab showed antitumor activity in ICI-naive HPV16-positive R/M HNSCC, with favorable safety, response rates, and survival outcomes. The findings support further evaluation in a first-line setting. Trial Registration ClinicalTrials.gov Identifier: NCT04260126

Abstract Objective. Four-dimensional CT (4DCT) enables visualization of dynamic wrist joint pathology but may be compromised by motion artifacts. Deep learning (DL)-assisted motion correction has the potential to enhance wrist 4DCT quality, but model development is hindered by scarce training data. To address this, we developed a model-based motion simulation framework that generated realistic 4DCT data with paired static ground truth images to demonstrate wrist motion correction using a physics-informed DL model trained with simulated data. Approach. Wrist motion was simulated by synchronizing rotational and translational movements of carpal bones and connective tissues. Elastic deformation guided by analytically-derived motion vector fields was applied to static wrist scans at neutral positions to create artifact-free images at multiple angular positions. Virtual motion-corrupted 4DCT images were produced via forward projection and reconstruction with synchronized gantry and wrist motion. Experimental data from 4DCT cadaver scans were collected to validate simulation quality. Low-intensity region score (LIRS), positivity, and entropy were used to assess simulated motion artifacts. A physics-informed motion correction network was adapted exclusively using simulated training data and subsequently deployed on simulated, real cadaveric, and in vivo 4DCT scans. LIRS and structural similarity index (SSIM) were used to evaluate motion correction quality. Wilcoxon signed-rank tests were conducted ( α = 0.05). Results. The simulation method created realistic motion artifacts compared to real scan reference ( p > 0.05). Motion artifacts were effectively mitigated across testing cases demonstrating generalizability. In simulated scans, LIRS improved from 0.55 ± 0.12–0.75 ± 0.04 and SSIM from 0.87 ± 0.08–0.95 ± 0.03 at bone regions (each p < 0.01). In experimental cadaveric scans, LIRS improved from 0.05 ± 0.01–0.31 ± 0.17 in marker regions and from 0.58 ± 0.19–0.77 ± 0.14 in bone regions (each p < 0.01). Significance. Our simulation method facilitates training DL-assisted motion correction algorithms by providing high-quality training data, effectively supporting 4DCT image quality enhancement.

Abstract Purpose Large language models (LLMs) have proven performance for certain diagnostic tasks; however, limited studies have evaluated their consistency in recommending appropriate medication regimens for a given diagnosis. Medication management is a complex task that requires synthesis of drug formulation and complete order instructions for safe use. Here, the performance of GPT-4o, an LLM available with OpenAI’s ChatGPT, was tested on 3 medication management tasks. Methods GPT-4o performance was tested on 3 medication tasks: identifying available formulations for a given generic drug name, identifying drug-drug interactions (DDIs) for a given medication regimen, and preparing a medication order for a given generic drug name. For each experiment, the model’s raw text response was captured exactly as returned and evaluated using clinician evaluation in addition to standard LLM metrics, including Term Frequency-Inverse Document Frequency (TF-IDF) vectors, normalized Levenshtein similarity, and Recall-Oriented Understudy for Gisting Evaluation (ROUGE-1/ROUGE-L) F1 score between each response and its reference string. Results For the first task of drug-formulation matching, GPT-4o had 49% accuracy for generic medications being matched to all available formulations, with an average of 1.23 omissions per medication and 1.14 hallucinations per medication. For the second task of drug-drug interaction identification, the accuracy was 54.7% for identifying the DDI pair. For the third task, GPT-4o generated order sentences containing no medication or abbreviation errors in 65.8% of the cases. Conclusion Model performance for basic medication tasks was consistently poor. This evaluation highlights the need for domain-specific training through clinician-annotated datasets and a comprehensive evaluation framework for benchmarking performance.

Abstract Identification of gene expression changes in post-mortem brain tissue of Alzheimer’s disease donors compared to controls have implicated numerous biological pathways for Alzheimer’s disease pathophysiology. Nonetheless, there is still limited understanding of how gene expression dysregulation underpins specific proteinopathies core to Alzheimer’s disease. Here we investigate brain transcriptomic changes in a well characterized cohort of Alzheimer’s disease donors to identify genes and networks that associate with Alzheimer’s disease endophenotypes including neuropathology measures (Braak stage, Thal phase and cerebral amyloid angiopathy score) and Alzheimer’s disease-related brain protein levels (Apolipoprotein E, Amyloid-β 40, Amyloid-β 42, tau, and phospho-Tau). Bulk transcriptome measures were collected from the temporal cortex tissue of 477 Alzheimer’s disease donors. Following quality control, transcriptome-wide association studies were performed for each endophenotype. We used weighted gene co-expression network analysis to build co-expression networks and integrated transcriptome with epigenetic and genetic data from the same donors. We detected a total of 5,740 Bonferroni significant temporal cortex gene associations with Alzheimer’s disease endophenotypes, most of which were with brain tau levels. We discovered tau-associated co-expression modules enriched in known and novel Alzheimer’s disease pathways. We found that a beneficial (or neutral) brain biochemical state of higher total tau and lower phospho-Tau are associated with increased levels of synaptic, DNA damage/repair, nucleic acid metabolism and myelin processes. In contrast, in a detrimental state of lower total and higher phospho-Tau, there is upregulation of vascular and immune, and downregulation of mitochondrial and myelin pathways. There are brain gene expression perturbations that are associated with Alzheimer’s disease endophenotypes. While some of these associations are common across multiple endophenotypes, many are distinct for different Alzheimer’s disease-related proteins. Based on these findings, we propose a hypothetical model of dynamic brain gene expression changes that track with progressive Alzheimer’s disease proteostasis. These expression changes hold potential to serve as dynamic, precision biomarkers of brain Alzheimer’s disease progression. This study demonstrates the potential of integrative multiomics and deep Alzheimer’s disease endophenotype analyses in well-characterized brain tissues to uncover with precision the complex biology of Alzheimer’s disease.

PURPOSE EA1181 (ClinicalTrials.gov identifier: NCT04266249 ) is a single-arm trial evaluating neoadjuvant taxane, trastuzumab, and pertuzumab (THP) in patients with clinical stage II/IIIa human epidermal growth factor receptor 2 (HER2)–positive breast cancer. This report focuses on the secondary end points of pathologic complete response (pCR) rates and associated factors. The primary end point—3-year recurrence-free survival among patients achieving a pCR (ypT0/Tis, ypN0)—will be reported when data mature. METHODS Patients received four cycles of trastuzumab and pertuzumab (HP) with either once per week paclitaxel (12 weeks) or docetaxel (every 3 weeks for four cycles), followed by surgery. Clinicopathologic characteristics were assessed in all patients. The HER2DX pCR score was determined using diagnostic biopsy samples in a representative subset. Logistic regression models identified factors associated with pCR. RESULTS A total of 2,175 patients were enrolled (781 HER2+/estrogen receptor‑negative [ER–]; 1,394 HER2+/ER+). Of 2,141 patients who initiated THP, the overall pCR rate was 43.8%: 63.7% in HER2+/ER– and 32.4% in HER2+/ER+ tumors. Higher pCR rates were observed in tumors that were ER-negative or low ER expressing, progesterone receptor-negative or low expressing, HER2 immunohistochemistry (IHC) 3+, and in patients treated with once per week paclitaxel. T3 disease was associated with a lower pCR rate in HER2+/ER– tumors; otherwise, tumor (T) and nodal (N) stage did not significantly affect pCR. Among 569 patients assessed for HER2DX pCR scores, a high score was independently associated with higher pCR rates, after adjustment for clinicopathologic variables. CONCLUSION Neoadjuvant THP achieved pCR in nearly two-thirds of patients with HER2+/ER– and one third with HER2+/ER+ breast cancer. Low hormone receptor expression, HER2 IHC 3+ status, once per week paclitaxel use, and a high HER2DX pCR score were independent predictors of pCR. These findings should help optimize risk stratification and treatment personalization for patients with HER2-positive breast cancer.

Abstract Large language models (LLMs) and vision‐language models represent a fundamentally different category of artificial intelligence (AI) compared to prior image analysis approaches in digital pathology, which have largely been based on convolutional neural network architectures. This review from the American Society of Cytopathology Clinical Practice Committee examines the current evidence for LLM and vision‐language model applications in cytopathology, including structured reporting, diagnostic assistance, quality control, education, and workflow integration. The distinction between applications with preliminary evidence and those that remain hypothetical is described. A detailed assessment of the challenges that must be addressed before clinical deployment, including hallucination risk, limited explainability, bias, data privacy, validation gaps, and infrastructure barriers is discussed. A review of the regulatory landscape in the United States and European Union as it applies to AI‐enabled software as a medical device is provided. Recommendations addressing cytopathology‐specific benchmarks, multi‐institutional validation, transparent governance, and incremental deployment beginning with low‐risk applications are suggested. In the current environment, LLMs have the potential to augment cytopathology practice, but responsible adoption requires rigorous validation and sustained collaboration among cytopathologists, AI researchers, and regulatory bodies.

DNA double-strand breaks (DSBs) that occur during mitosis are primarily repaired by Polθ-mediated microhomology-mediated end joining (MMEJ). The CIP2A–TOPBP1 complex has been shown to tether broken chromatin at mitotic DSBs, but whether it coordinates with or functions independently of Polθ remains unknown. Here, we show that the CIP2A–TOPBP1 complex is recruited to mitotic DSB sites, where it directly interacts with Polθ and corecruits Polθ to chromatin. CIP2A sustains Polθ phosphorylation by inhibiting PP2A, thereby prolonging Polθ chromatin retention and enabling efficient repair. Upon repair completion, the CIP2A–TOPBP1 complex dissociates, PP2A dephosphorylates Polθ, and Polθ is released from chromatin. Loss of CIP2A impairs tumor growth, while disruption of CIP2A–Polθ binding leads to persistent DNA damage, micronucleus formation, and synthetic lethality in BRCA1/2-deficient cells. These findings uncover a cooperative mechanism by which CIP2A–TOPBP1 dynamically regulates Polθ in mitotic DSB repair and provide insights into the synthetic lethal interaction of CIP2A with BRCA1/2 under radiotherapy.

TRAIL is a TNF family ligand that trimerizes TRAIL-R1 (DR4) or TRAIL-R2 (DR5) to induce apoptosis, necroptosis, and/or NF-κB activation in receptor-bearing cells. We previously identified TRAILshort as a splice variant of TRAIL that lacks cysteine 230, cannot trimerize, and acts as a dominant-negative ligand that blocks TRAIL-mediated apoptosis. TRAILshort is expressed on cell surfaces and within extracellular vesicles, enabling it to confer TRAIL resistance to both producing and bystander cells. In this study, we showed that elevated TRAILshort levels were associated with chronic viral infections, cancer, and autoimmune diseases, suggesting a link to impaired immune regulation. Using unbiased phosphoproteomics and mechanistic studies, we demonstrated that TRAILshort binding to DR5 recruited and activated the phosphatase Src homology region 2 domain–containing phosphatase 1 (SHP-1), leading to zeta-chain-associated protein kinase 70 (ZAP-70) dephosphorylation, disruption of ZAP-70–CD3ζ interactions, and impaired T cell receptor signaling, thereby reducing T cell activation, proliferation, and cytokine production in response to antigen or CD3/CD28 ligation. Genetic or pharmacologic SHP-1 inhibition reverses these effects. In humanized mouse models, TRAILshort promoted the persistence of transformed mouse embryonic fibroblasts (MEFs) and L428 and antagonized CD19-directed CAR T cell activity, revealing TRAILshort as an immunomodulator of T cell function with therapeutic implications, including blocking TRAILshort to restore T cell immunity or delivering TRAILshort to enforce tolerance. TRAILshort, a variant of TRAIL, suppresses T cell function and immune responses in cancer and infectious diseases, highlighting its potential as a therapeutic target.