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Metabolic dysfunction-associated steatotic liver disease (MASLD) and its progressive form, metabolic dysfunction-associated steatohepatitis (MASH), are among the most prevalent causes of chronic liver disease worldwide, closely linked to the global rise in overweight and obesity, type 2 diabetes, and metabolic syndrome. Until recently, treatment options were limited to lifestyle interventions, with no approved pharmacologic therapies. Resmetirom, a liver-directed, selective thyroid hormone receptor beta (THR-β) agonist, is a promising disease-modifying agent that targets hepatic lipid metabolism, inflammation, and fibrosis. Clinical trials, including the pivotal phase 3 MAESTRO-NASH and MAESTRO-NAFLD-1 trials, have demonstrated significant improvements in liver fat reduction, lipid profiles, histological endpoints, and health-related quality of life, with a favorable safety profile. In March 2024, the FDA granted accelerated approval of resmetirom for adults with MASH and moderate-to-advanced fibrosis, marking a significant milestone in MASLD treatment. This review discusses the mechanistic rationale, preclinical data, and pivotal clinical trial outcomes supporting resmetirom’s role in MASLD/MASH management, while outlining ongoing research needs, including long-term safety, pediatric evaluation, and biomarker development for optimized patient selection.

Key Points Our study found a high prevalence of monoclonal gammopathy (MG) in patients diagnosed with ANCA-negative pauci-immune crescentic GN. Patients with MG showed a higher degree of fibrosis on kidney biopsy than those without MG with higher mortality rate. Our data suggest an association between MG and ANCA-negative pauci-immune crescentic GN, emphasizing this population's need for MG testing and monitoring. Background In a small subset of patients with pauci-immune crescentic GN (PICGN), ANCA are not identified, and patients are referred to as having ANCA-negative vasculitis. The cause of the disease in this subset of patients has remained elusive. We explored the role of monoclonal gammopathy (MG) in those with ANCA-negative PICGN. Methods We conducted a retrospective study and identified patients with PICGN who had undergone ANCA and monoclonal testing. Those positive for ANCA were excluded. Results We identified 14 patients with ANCA-negative vasculitis, of whom eight (57%) tested positive for MG with a mean age of 60.3±12.2 years, 75% were female, and with a mean serum creatinine of 4.3±1.92 mg/dl. The most common monoclonal proteins were IgG ( n =4, 50%) and kappa ( n =4, 50%). One patient had diagnosis of multiple myeloma. Most common extra-renal manifestations were skin rash (leukocytoclastic vasculitis) and neuropathy. Kidney biopsy showed a higher degree of interstitial fibrosis and tubular atrophy compared with those without MG. The median follow-up time was 3.2 years, with 50% mortality in those with MG. Conclusions More than 50% of the patients with ANCA-negative PICGN have MG, and patients present with more evidence of fibrosis on kidney biopsy, with higher mortality rate observed in our cohort. Monoclonal proteins may trigger the development of PICGN; their specific role in the pathogenesis of this disease needs further investigation.

Background: EUS-guided gastroenterostomy (EUS-GE) is an effective option for the management of gastric outlet obstruction (GOO). Due to the poor prognosis of patients undergoing it, data on its long-term adverse events (AE) is scarce. Herein, we describe a cohort of patients with gastro-entero-colic fistula (GECF) as a late AE of previously successful EUS-GE. Methods: Patients who developed a GECF after EUS-GE from 10 high-volume centers were analyzed. Information collected included demographic characteristics, indications, clinical and technical success rates, stent type and size, fistula characteristics, management, and outcomes. Results: Sixteen cases were identified. The mean interval from index EUS-GE to the diagnosis of GECF was 4 to 8 weeks. The most common cause of GOO was pancreatic adenocarcinoma (PDAC). The transverse colon was the most common site for the GECF (14 patients). A 20×10 mm lumen apposing metal stent (LAMS) was utilized in 10 patients. Endoscopic management with a variety of modalities was successful in 13 cases. Follow-up interval after endoscopic management of the fistula averaged 2 to 4 weeks. At the time of the manuscript elaboration, 10 patients had died, 5 were alive, and 1 was lost to follow-up. Conclusions: This is the first description of a cohort of patients with GECF after EUS-GE. The exact mechanisms leading to GECF in these cases are unknown. Possible explanations include inadvertent colon puncture during the index procedure and/or entrapment of mesocolon. More data is needed to further characterize this AE.

Background: Fluorescence in situ hybridization (FISH) is recommended as part of multimodality sampling in the evaluation of biliary strictures, but can be false negative in 40%–50% cases. The aim of this study was to comprehensively assess predictors of false-negative FISH in patients with biliary strictures. Methods: Patients undergoing tissue sampling for biliary strictures from October 20 to February 22 were prospectively enrolled (NCT04572711). Procedural factors such as sampling techniques, order, and utilization of combination sampling were recorded. Results of an optimized pancreatobiliary FISH panel with locus-specific probes for 1q21, 7p12, 8q24, and 9p21 were reported per guidelines. Statistical analyses were performed using BlueSky Statistics v.10.3.1, R package v8.81. Results: Of 327 patients, 93 (28.5%) were diagnosed with malignancy. A false-negative pancreatobiliary fluorescence in situ hybridization (PB-FISH) was reported in 40 (43.1%) patients. A history of primary sclerosing cholangitis was associated with lower odds of having a false-negative PB-FISH (aOR=0.38, 95% CI=0.16–0.82, p=0.02), whereas a hilar stricture was associated with a significantly higher false-negative PB-FISH in those with cholangiocarcinoma (aOR=3.2 [1.4–7.9], p=0.009). Dilation of biliary strictures prior to brushing was not associated with a lower rate of false-negative PB-FISH. Conclusions: In this prospective study, hilar strictures were more likely to have false-negative PB-FISH. Dilation of strictures did not affect PB-FISH performance. These results can help guide PB-FISH interpretation.

Abstract Background The radiation oncology clinical practice involves many steps relying on the dynamic interplay of abundant text data. Large language models have displayed remarkable capabilities in processing complex text information. But their direct applications in specific fields like radiation oncology remain underexplored. Purpose This study aims to investigate whether fine‐tuning LLMs with domain knowledge can improve the performance on Task (1) treatment regimen generation, Task (2) treatment modality selection (photon, proton, electron, or brachytherapy), and Task (3) ICD‐10 code prediction in radiation oncology. Methods Data for 15 724 patient cases were extracted. Cases where patients had a single diagnostic record, and a clearly identifiable primary treatment plan were selected for preprocessing and manual annotation to have 7903 cases of the patient diagnosis, treatment plan, treatment modality, and ICD‐10 code. Each case was used to construct a pair consisting of patient diagnostics details and an answer (treatment regimen, treatment modality, or ICD‐10 code, respectively) for the supervised fine‐tuning of these three tasks. Open source LLaMA2‐7B and Mistral‐7B models were utilized for the fine‐tuning with the Low‐Rank Approximations method. Accuracy and ROUGE‐1 score were reported for the fine‐tuned models and original models. Clinical evaluation was performed on Task (1) by radiation oncologists, while precision, recall, and F‐1 score were evaluated for Task (2) and (3). One‐sided Wilcoxon signed‐rank tests were used to statistically analyze the results. Results Fine‐tuned LLMs outperformed original LLMs across all tasks with p value ≤ 0.001. Clinical evaluation demonstrated that over 60% of the fine‐tuned LLMs‐generated treatment regimens were clinically acceptable. Precision, recall, and F1‐score showed improved performance of fine‐tuned LLMs. Conclusion Fine‐tuned LLMs demonstrated statistically significant improvements over original LLMs upon three clinically important tasks in radiation oncology. This study explored the feasibility of applying fine‐tuned LLMs in radiation oncology, inspiring further development of utilizing LLMs to assist with radiation oncology tasks.

ABSTRACT Knowledge of Treponema pallidum subspecies pallidum ( TPA ) outer membrane protein (OMP) sequence variability is essential for understanding spirochete proliferation within endemic populations as well as the design of a globally effective syphilis vaccine. Our group has identified extracellular loops (ECLs) of TPA BamA (TP0326) and members of the FadL family (TP0548, TP0856, TP0858, TP0859, and TP0865) as potential components of a multivalent vaccine cocktail. As part of a consortium to explore TPA strain diversity, we mapped the variability of BamA and FadL orthologs in 186 TPA strains from Malawi, China, and Colombia onto predicted 3D structures. The 186 genomes fell into eight subclades (five Nichols- and three SS14-lineage) with substantial geographic restriction. Single nucleotide variants accounted for the large majority of proteoforms, with variability notably higher within the Nichols-lineage strains. Most mutations were in regions of the proteins predicted to be extracellular and harboring B cell epitopes. We observed a striking difference in the degree of variability between the six OMPs, suggesting that these proteins are following divergent evolutionary paths. Concatenation of OMP sequences recapitulated the phylogenetic structure of the TPA strains, effectively segregating within clades and largely clustering by subclades. Finally, we noted that BamA and FadL candidate ECL vaccinogens, previously shown to elicit antibodies that kill treponemes during in vitro cultivation, are well conserved. Taken as a whole, our study establishes a structural-phylogenetic approach for analyzing the forces shaping the host-pathogen interface in syphilis within endemic populations while informing the selection of vaccine targets. IMPORTANCE Syphilis remains a major global health concern, reinforcing the need for a safe and effective vaccine. Understanding the variability of TPA OMPs is essential for tracking pathogen evolution and informing vaccine design. Here, we analyzed the variability of six TPA OMPs in 186 strains from Malawi, China, and Colombia, identifying protein-specific evolutionary patterns. Most mutations were localized in extracellular regions and, notably, appeared to correlate with the phylogenetic structure of TPA . Despite OMP heterogeneity, several candidate vaccinogens remained highly conserved, reinforcing their potential as globally effective vaccine targets. Our study establishes a structural-phylogenetic framework for dissecting the forces shaping the host-spirochete interface within endemic populations and provides a foundation for designing a globally effective syphilis vaccine.

Abstract Introduction: Radiotherapy (RT)-induced acute esophagitis (AE) is a common side effect in lung cancer patients receiving RT, which can significantly impact their quality of life. This highlights the need for a predictive model that can estimate AE risk in advance using pretreatment imaging data. However, collecting sufficient data for model development is often resource-intensive and costly. Additionally, acquiring a homogeneous training dataset (e.g., from a single center or modality) is not always feasible. This study aimed to develop an automated artificial intelligence-based 3D vision foundation model (VFM) combining standard-of-care planning computed tomography (pCT) and planned radiation dose maps to predict grade II or higher AE. Materials and methods: This study included 246 patients with non-small cell lung cancer who underwent either image-guided radiation treatment (IMRT) or proton-beam radiation therapy. The endpoint was grade two or higher AE (33% positive and 67% negative). The IMRT group consisted of 182 patients from a single center, whereas the proton therapy group included 64 patients from the Proton Collaborative Group trial from 11 different institutions. For each patient, pCT, dose maps, and radiotherapy segmentations were available. The VFM was created using a transformer pretrained using a large number of unlabeled volumetric 3D CTs from patients with varied diseases through a self-supervised learning approach, which extracts useful features directly from images. Next, the pretrained encoder was combined with fully connected classification layers and fine-tuned using stratified 5-fold cross-validation with 20 patients set aside for testing. We developed two models: a CT only and CT + dose model. Model performance was assessed using the area under the curve (AUC), specificity, and sensitivity. Results: In cross-validation, adding dose information to CT (CT+Dose) improved model performance, increasing AUC from 0.72 ± 0.08 to 0.76 ± 0.10 and specificity from 0.82 ± 0.09 to 0.87 ± 0.04, while sensitivity remained the same. On the independent test set, CT+Dose showed a marked improvement over CT only (AUC: 0.82 vs. 0.59; sensitivity: 0.57 vs. 0.14), with a slight decrease in specificity (0.77 vs. 1.00). Conclusion: A VFM model combining CT and radiation dose showed the capability to predict AE more accurately with higher specificity. Further studies on larger cohorts of testing patients are planned to assess model generalization. Citation Format: Chloe Min Seo Choi, Jue Jiang, Nikhil Mankuzhy, John Chang, Jing Zeng, Carlos Vargas, James Urbanic, Isabella Choi, Mark Mcdonald, James Gray, Joseph Deasy, Maria Thor, Charles Simone, Harini Veeraraghavan. Prediction of radiotherapy-Induced esophagitis in non-small cell lung cancer using a 3D vision foundation model [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Artificial Intelligence and Machine Learning; 2025 Jul 10-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(13_Suppl):Abstract nr B022.

Background and Aims: Prognosticating outcomes such as hospitalizations in outpatients with cirrhosis is challenging, especially with changing etiologies and demographics. This study aims to determine the impact of multi-omic strategies on outcome prediction. Approach and Results: NACSELD3 enrolls outpatients with cirrhosis with controlled/eradicated etiologies from 10 centers and follows them systematically. At baseline, clinical/demographic and cirrhosis details were recorded and saliva and serum samples were collected for microbiome and metabolome analysis, respectively. Multi-omic bioinformatic studies to determine the interaction of microbiota and metabolites with the clinical prediction of 6-month hospitalizations were performed. Five hundred sixty-five patients (60.2 y, 68% men, 35% alcohol, 33% metabolic dysfunction-associated steatohepatitis, 21%, eradicated HCV with MELD 3.0 12) were enrolled. One hundred sixty-three (29%) required 6-month hospitalizations; most (75%) were liver-related. Those hospitalized had worse cirrhosis severity and comorbidity indices but similar demographics and oral health variables. Salivary microbiome alpha-diversity was lower (1.96±0.48 vs. 2.09±0.45, p =0.018) with greater pathobionts ( Streptococcus , Treponema, Enterococcaceae) and lower commensal genhospitalized/noera ( Veillonella, Prevotella, Haemophilus , Lachnospiraceae spp) at baseline. Serum metabolomics showed significant separation at baseline between hospitalized/non-hospitalized patients using supervised analyses with microbial-origin (phenyllactate, secondary bile acids, indoles), choline moieties, and polyamine/GABA (3-ureidopropionate/spermidine) metabolites being most prominent. Area under the curve using random forest for clinical, microbial, and metabolomic variables was higher than that of these individually. Latent factor analysis showed clinical variables (MELD 3.0, hemoglobin, and albumin) with the greatest impact, followed by salivary microbiota and then serum microbiome for hospitalization prediction. Conclusions: In a multicenter North American outpatient cirrhosis cohort with controlled etiologies, serum metabolomics and salivary microbiome add to clinical variables to prognosticate 6-month hospitalization.

ABSTRACT Anastomotic leaks following complex gastrointestinal surgeries pose a significant challenge, especially in patients unfit for further surgical intervention. We present a novel 3-staged endoscopic approach to restore gut continuity in a 55-year-old woman with multiple anastomotic leaks and discontinuous bowel segments following extensive abdominal surgeries. The procedure included stent placement, endoscopic ultrasound (EUS)-guided gastrojejunostomy with a lumen-apposing metal stent (LAMS), and fistula plug insertion with glue. Over 6 months, bowel continuity was restored, and at 6-year follow-up, the patient remains symptom free, tolerating oral intake. This case demonstrates the transformative potential of advanced endoscopic techniques in managing complex gastrointestinal disruptions without further surgery.

Abstract Clinicians struggle to accurately classify biliary strictures as benign or malignant. Current endoscopic retrograde cholangiopancreatography (ERCP)-based sampling modalities including brush cytology and forceps biopsy have poor sensitivity for pathologic confirmation of malignancy. Cholangioscopy allows for direct visualization and sampling of biliary pathology; however, this technology is also associated with inaccurate classification of biliary disease. Previously, an artificial intelligence (AI) system that analyzes cholangioscopy footage was found to be more accurate in diagnosing biliary malignancy than ERCP sampling techniques. The aim of this study was to validate this AI system on a new series of examinations. Three academic centers collected all available unedited cholangioscopy recordings. The videos were processed by the cholangioscopy AI system. After analyzing videos, the AI system provided predictions as to whether malignancy was present. AI performance in classifying strictures was compared with the performance of brush cytology and forceps biopsy. 112 cholangioscopy examinations (containing 4 817 081 images) were generated from 99 patients. Of those examinations, 61 (54.5%) were for investigation of biliary strictures (31 [50.8%] benign, 30 [49.2%] malignant). For the correct classification of strictures, the AI system was 80.0% sensitive and 90.3% specific. It was also significantly more accurate for stricture classification (85.2%) than brush cytology (52.5%; P<0.001), forceps biopsy (68.2%; P=0.04), and the combination of brush cytology and forceps biopsy (66.7%; P=0.02). A previously developed cholangioscopy AI system was found to continually outperform standard ERCP sampling modalities for accurate identification of malignancy, without additional retraining, in a multicenter validation cohort.