Citations

This pilot, randomized, double-blind trial in a relatively small sample of patients with IBS-related pain shows rimegepant significantly reduced sensations of gas, urgency, and pain during rectal distention and decreased rectal compliance. Decrease in compliance implies that changes in physical properties or distensibility of rectum did not contribute to alterations in rectal sensation. Same dose of rimegepant did not significantly impact daily abdominal pain, BM frequency, or colonic transit. There were no serious adverse events.

Limited information on the business practices of liver transplant (LT) centers worldwide has been published. Characterizing this data could help identify best practices as well as opportunities for improvement. As such, the International Liver Transplant Society (ILTS) Business Practice Committee conducted a global online survey of LT centers, which was sent to the ILTS membership. Questions focused on 5 main domains: transplant practice and volumes, workforce, finances, quality assessment and performance improvement, and overall program function. Data was compared across program geographic regions and transplant volume. A total of 89 discrete centers were represented, of which 76.4% were academic/university-affiliated, and about one-third each were from Europe (36.0%) and North America (31.5%). The top 3 problems programs reported were finances/funding (60.7%), adequate program support/guidance (48.3%), and transplant volumes (43.8%). In all, 59.6% of respondents felt their salary was undercompensated, consistent across geographic regions. In addition, 69.7% felt their center was not adequately funded to meet program goals, with programs in Europe (N=28/32, 87.5%) and Oceania (N=2/3, 66.7%) most impacted. Transplant surgeon retainment was noted as more difficult for lower volume programs (<50 liver transplants/year, N=13/31). Nearly half (42.7%) of all programs felt under-resourced to provide high-quality care, and the majority (80.9%) felt there was room for growth and improvement under their current model. While international concerns varied widely among LT centers, inadequate salary and center funding, low transplant and referral volumes, and staff retainment were persistent themes. Focusing on adopting region-specific best practices and developing transplant systems of care that focus on these elements is critical to provide optimal care to LT patients worldwide.

Abstract Background Electronic health record (EHR)–based prognostic modeling is increasingly used in oncology, yet incorporating pharmacogenomic (PGx) knowledge derived from experimental systems into clinical prediction frameworks remains challenging. This gap is driven by fundamental mismatches between controlled drug–mutation assays and heterogeneous, incomplete real-world clinical data. Methods We propose a representation transfer framework that integrates PGx embeddings learned from large-scale in vitro pharmacogenomic screens into patient-level EHR models. A frozen pharmacogenomic encoder is used to generate interaction-aware embeddings from patient mutation profiles and administered therapies, which are aggregated into a fixed-length PGx Complementarity Representation. These representations are incorporated into multimodal survival prediction models alongside standard clinical features. Performance was evaluated using systematic modality ablation analyses, attribution analyses, and exploratory unsupervised representation analyses. Results Integrating PGx embeddings yielded consistent performance improvements across all evaluated modality combinations. Relative gains were largest in modality-sparse settings, where baseline EHR features encode limited biological context, and were attenuated—but remained significant—in biologically enriched configurations. Attribution analyses indicated that PGx embeddings contributed non-redundant predictive signal beyond standard clinical features. Exploratory unsupervised analyses further demonstrated that the learned representations exhibit interpretable association patterns aligned with known therapeutic exposures and pathway-level associations. Conclusion These findings suggest that externally learned pharmacogenomic representations can be transferred into real-world EHR models as a context-dependent, non-redundant augmentation. By framing PGx knowledge as an interaction-aware representation rather than a mechanistic model, this work provides an informatics framework for integrating experimental pharmacogenomic data into clinical prediction tasks in a reproducible and interpretable manner.

Ameloblastomas are locally aggressive odontogenic tumors that most commonly arise in the mandible and maxilla and often harbor BRAF V600E mutations. While rare extragnathic ameloblastomas have been reported, primary pulmonary cases have not been documented. We identified 3 pulmonary neoplasms with features of ameloblastoma that were submitted for consultation between 2022 and 2025 at 3 academic institutions and performed detailed clinicopathologic and molecular analysis. The tumors presented as 5.4 to 7.3 cm peribronchial solitary lung masses. All resected tumors exhibited a predominant stellate reticulum-like component composed of loosely arranged p40-reactive bland squamoid-to-spindled cells with long intercellular bridges, and streaming and swirling architecture, surrounded by palisaded columnar cells with focal reverse nuclear polarity at the interface with myxoid stroma. All tumors were immunoreactive for BRAF V600E IHC, and BRAF V600E mutations were confirmed by molecular assays, including broad next-generation sequencing on 2 cases. Florid hyperplasia of entrapped pneumocytes initially suggested a biphasic neoplasm, but the absence of BRAF V600E IHC labeling confirmed pneumocyte entrapment. Occult gnathic primary tumors were excluded by subsequent clinical examination, including negative panoramic dental x-rays. No recurrences or metastases have been observed to date. This first series of primary pulmonary ameloblastomas highlights a distinctive tumor with histologic and molecular features identical to gnathic counterparts. We discuss the potential histogenesis of these unusual tumors.

632 Background: Paltusotine is an oral, nonpeptide, selective somatostatin receptor 2 agonist. In a phase 2 study, treatment with once-daily paltusotine reduced the frequency and severity of carcinoid syndrome (CS) symptoms and was well tolerated. The effect of paltusotine on biomarkers of serotonin and 5-hydroxyindoleacetic acid (5-HIAA) was further explored. Methods: This exploratory study, without formal power calculations, included an 8-week randomized treatment phase (completed) and a 102-week open-label extension phase (currently ongoing). The purpose was to evaluate safety, pharmacokinetics, and exploratory efficacy endpoints, including changes in biomarkers of paltusotine treatment. Enrolled patients were adults with a stable, documented grade 1 or 2 neuroendocrine tumor (NET) and CS. These patients were actively symptomatic and either untreated with somatostatin receptor ligand (SRL) therapy (average of ≥4 bowel movements [BMs] per day or >2 flushing episodes per day in ≥2 days over a 2-week period) or washed out of SRL therapy (symptoms previously controlled on SRL), with demonstrated symptom worsening after washout. Patients were randomized to once-daily paltusotine 40 mg or 80 mg; one optional uptitration (from 40 mg to 80 mg or 80 mg to 120 mg) was permitted. Blood samples for assessment of biomarkers (serum serotonin and plasma 5-HIAA) were collected longitudinally from screening to end of treatment. Upper limit of normal was prespecified as 541 ng/mL for serotonin and 22 ng/mL for 5-HIAA. This analysis focuses on changes in biomarker from baseline to the end of 8-week randomized treatment phase and after approximately one year (48 weeks). Results: Thirty-six patients (n=9 untreated; n=27 SRL washout) were randomized. Mean age was 60.8 years (range 35-83), and 52.8% were female. Nineteen patients had grade 1 NETs, and 17 had grade 2 NETs. As reported previously, treatment with once-daily, oral paltusotine was well tolerated and reduced the frequency and severity of CS symptoms, justifying further clinical development of the 80 mg dose. Mean serum serotonin decreased from 1553.0 ng/mL at baseline to 643.9 ng/mL at Week 8, and mean plasma 5-HIAA decreased from 245.1 ng/mL to 159.7 ng/mL. There was a trend of untreated patients achieving a greater reduction in comparison to washout patients. At 48-week follow-up, mean serum serotonin was stabilized at 791.50 ng/mL (n=20), and mean plasma 5-HIAA was stabilized at 190.45 ng/mL (n=20). Conclusions: Paltusotine significantly reduced serotonin and 5-HIAA levels, with effects maintained at 48 weeks. Biomarker reductions paralleled reductions in BM and flushing frequency. These findings support further investigation in the ongoing phase 3 study (CAREFNDR, NCT07087054). Clinical trial information: NCT05361668 .

Abstract Background Ten years after the original publication, the Centiloid framework is now broadly used to harmonize amyloid‐PET quantification, facilitate data sharing and comparison across cohorts, and even assist visual interpretation in clinical settings. We evaluated the global implementation of Centiloids by comparing their distribution and corresponding positivity thresholds across cohorts. Methods We gathered data from publicly available cohorts and reached out to investigators across the world to collect cross‐sectional Centiloids, demographic and clinical information, and visual read data. Gaussian mixture models (GMM, k=2) were fitted to Centiloid values for each cohort and cutoffs were calculated as mean + 2SD of the lower Gaussian. When visual reads were available, we determined Centiloid cutoffs that maximized correspondence with visual reads (Cohen's kappa). Data was combined across cohorts using random effects meta‐analyses. Results As of January 2025, we included 37 cohorts ( n = 41,678 participants) with heterogeneous pipelines, radiotracers, and clinical and demographic characteristics (Table‐1). The low Gaussian peaks ranged from ‐9 to 10CL; the meta‐analysis identified a common peak at 1CL. The second peaks were more heterogeneous (range=38‐102CL; meta‐analysis outcome=64CL). Across cohorts, the proportion of cognitively unimpaired versus impaired participants impacted the position of both peaks, with better separation in cohorts enriched in impaired individuals (Figure 1C). The meta‐analysis indicated a GMM‐based cutoff of 19CL (95%CI: 16‐21CL, Figure 1B); subgroup analyses showed no evidence of significant effect between single versus multicenter settings (17 versus 20CL, p = 0.30), MRI‐based or PET‐only processing (18 versus 19CL, p = 0.88), and no evidence of difference across radiotracers (Flutemetamol: 16CL; PIB: 17CL, Flutafuranol: 18CL, Florbetaben: 19CL, Florbetapir: 20CL, p = 0.78). In a subset of 29,496 participants with visual reads available, binary visual reads corresponded well to Centiloids (common kappa=0.86, Figure 2A). The visual read‐based cutoff of 24CL (95%CI: 21‐27CL, Figure 2B) maximized correspondence between visual read and quantification and was slightly higher than the GMM‐based cutoff. All meta‐analysis models showed high non‐random heterogeneity (I 2 >80%) across studies, suggesting non‐random differences in peaks and cutoffs. Conclusions Meta‐analysis‐based cutoffs align well with thresholds from the existing literature. High heterogeneity among studies underscores the need to investigate contributing factors, raising concerns about applying common cutoffs.

SUMMARY Artificial intelligence (AI)-based methods are increasingly critical in peptide drug discovery, but their applications are limited in a narrow scope such as antimicrobial peptides. For indications where peptide therapy inherently excels, such as metabolism, endocrinology, and tissue regeneration, AI-based pipeline for therapeutic peptide discovery is long awaited but still unmet. Here, we propose a deep learning-based pipeline, Deepeptide, capable of identifying therapeutic oligopeptides for various metabolism-related indications. Leveraging the intrinsical relationship of ‘disease indication — biological processes — molecular functions’, Deepeptide discovers oligopeptides with indication-ameliorating-related molecular functions as lead candidates for indication of interest. Deepeptide was applied in five representative indications of metabolism, endocrinology, and tissue regeneration: angiogenesis, lipid metabolism, osteogenesis, glucose metabolism, and anti-angiogenesis. Overall, 62% of the identified oligopeptide candidates demonstrated significant bioactivity in vitro, with most of them showing comparable potency to the first-line drugs. Notably, the heptapeptide AP7 exhibited angiogenic potency comparable to VEGF in excisional wound splinting mouse model by promoting cell migration rather than proliferation, and hexapeptide TP6 showed significant dual-efficacy against hyperlipidemia and obesity in high-fat diet mice by inhibiting lipid synthesis and regulating gut microbiota. These findings highlight the potential and generalizability of Deepeptide in therapeutic oligopeptide discovery for metabolic diseases.

ABSTRACT Lymphocytic colitis (LC) is a subtype of microscopic colitis, often associated with chronic watery diarrhea and characterized by an increase in intraepithelial lymphocytes. Although various medications are implicated in drug-induced LC, its incidence as a treatment-related adverse effect of rearrangement during transfection-selective tyrosine kinase inhibitors is not known. We report a case of pralsetinib-induced LC in a patient with stage 3c nonsmall cell lung cancer. This case highlights pralsetinib-induced LC as a cause of persistent diarrhea that is refractory to standard antidiarrheal treatments and prompts gastrointestinal evaluation and histopathological examination to facilitate early diagnosis and management.