Publications

Endocrine and exocrine insufficiencies are well-recognized pancreatic-specific sequelae of chronic pancreatitis (CP), yet the impact of CP extends beyond the pancreas. The pathophysiology driving these complications is complex and poorly understood, resulting in inadequate recognition and an inability to stratify risk of disease progression. To address this topic, the Collaborative Alliance for Pancreatic Education and Research convened a workshop to summarize our current understanding and identify knowledge gaps related to the complications of CP. The clinical uncertainty related to who will develop systemic complications of CP, and when, negatively affects the patient's clinical experience and is an area of research that requires additional commitment. Adapting modeling strategies proven effective in other conditions (eg, type 2 diabetes) may be effective in identifying and predicting the onset of endocrine and exocrine insufficiencies. Improved understanding related to genetic risk factors, biomarkers, clinical testing, and advanced imaging techniques all represent pathways to better identify these complications and develop pancreatitis-specific interventions. Additional complications of CP, including pain, osteopathies, sarcopenia, malnutrition, and visceral neuropathies, can occur independently or as complications from endocrine and/or exocrine insufficiency. Better screening strategies to identify these conditions are required, many of which may be accomplished using opportunistic screening strategies. Future research will need to utilize existing treatment modalities and medications, in addition to developing new interventions, to treat these complications of CP that have a tremendous impact on patients' quality of life. Genetic testing in pancreatitis is likely to inform any research related to the complications of CP, but low penetrance of disease, poor genotype-phenotype associations, and health disparities that impact the use of testing across centers currently limit its clinical utility for all patients. Genetic testing remains critical in certain populations with CP and should be incorporated into research whenever possible to inform much-needed disease progression prediction models.

OBJECTIVE: To investigate the relationship between cartilage cap thickness, osteochondroma subtype (pedunculated vs. sessile), patient age, and multiple hereditary exostoses (MHE) diagnosis with malignant transformation of osteochondromas.

METHODS: A single-institution retrospective study of patients who underwent surgical excision of one or more osteochondromas between 1983 and 2025 was conducted. The relationship between cartilage cap thickness, osteochondroma subtype (pedunculated vs. sessile), patient age, and MHE diagnosis with malignant transformation was investigated.

RESULTS: Among 1138 pathology-confirmed osteochondromas, 1097 (96.4%) were benign osteochondromas and 41 (3.60%) underwent malignant transformation. In tumors with a pathology-measured cartilage cap (n = 411), benign tumors (n = 397) had a smaller median cap size than malignant lesions (0.3 cm [IQR: 0.2-0.6 cm] vs. 3.15 cm [IQR: 1.93-4.78 cm]; p < .0001). Among 27 malignant cases with preoperative imaging, 63% were sessile and 37% pedunculated. Patients with benign tumors were younger than those with malignant transformations (27.1 ± 15.9 vs. 37.8 ± 12.2 years; p < .0001). Patients with MHE had a greater incidence of malignant transformation compared to patients without (17% vs. 1.98%) (p < .0001). 137 MRIs and 37 CTs were compared to pathology measurements, yielding a concordance correlation coefficient of 0.80 and 0.92, respectively. The sensitivities and specificities were 29% and 91% for MRI and 67% and 94% for CT, respectively.

CONCLUSION: A thicker cartilage cap, older age, and confirmed MHE diagnosis were each significantly associated with a higher rate of malignant transformation. Multidisciplinary teams should factor in a patient's clinical presentation and past medical history in addition to the tumor characteristics in deciding the proper course of treatment.

Circulating and urinary laboratory biomarkers are central to cardiovascular, kidney, and metabolic drug development, and they support diagnosis, risk stratification, dose finding, safety monitoring, and, in selected settings, endpoint definition. Yet only a few materially shape trial design or regulatory decisions, and still fewer meet stringent criteria for surrogate endpoints. This review proposes a context-of-use framework in which circulating biomarkers are assessed along 2 converging "evidence lanes": analytical readiness and clinical or statistical validation. The review outlines fit-for-purpose requirements for enrichment tools, pharmacodynamic and dose-ranging markers, safety biomarkers, and candidate surrogates, by emphasizing preanalytical, analytical, and postanalytical sources of variability. Particular attention is given to surrogate validation, highlighting frequent discordance between biological plausibility or prognostic strength and treatment-induced changes that reliably predict clinical benefit (eg, albuminuria, natriuretic peptides, and glycemic, inflammatory, and lipid markers). The review describes how biomarkers can be embedded prospectively in phase 1 through phase 4 trials to guide dose selection, enrich populations, trigger adaptive design decisions, and support postmarketing surveillance while generally retaining hard outcomes as the basis for efficacy claims. A dedicated section summarizes perspectives from major regulatory agencies, and another applies the framework to concrete cardiovascular examples, illustrating both successful and unsuccessful uses. Finally, the review discusses practical barriers-analytical variability, operational burden, and limited commercial incentives-and proposes shared solutions, including standardized assays, harmonized data standards, open access platforms, and cross-trial biobanks.

INTRODUCTION: The Centiloid scale is the standard for amyloid (Aβ) PET quantification in research and clinical settings. However, variability between tracers and scanners remains a challenge.

METHODS: This study introduces DeepSUVR, a deep learning method to correct Centiloid quantification, by penalizing implausible longitudinal trajectories during training. The model was trained using data from 2,129 participants (7,149 Aβ positron emission tomography [PET] scans) in the Australian Imaging, Biomarkers and Lifestyle Study of ageing (AIBL)/Alzheimer's Disease Neuroimaging Initiative (ADNI) and validated using 15,807 Aβ PET scans from 10,543 participants across 10 external datasets.

RESULTS: DeepSUVR increased correlation between tracers, and reduced variability in the Aß-negatives. It showed significantly stronger association with cognition, visual reads, neuropathology, and increased longitudinal consistency between studies. DeepSUVR also increased the effect size for detecting small treatment related slowing of amyloid accumulation in the A4 study.

DISCUSSION: DeepSUVR substantially advances Aβ PET quantification, outperforming all standard approaches, which is particularly important for clinical decision making and to detect subtle or early changes in Aβ.

HIGHLIGHTS: Novel artificial intelligence (AI)-method that penalizes biologically implausible longitudinal trajectories, enabling the model to learn standardized uptake value ratios (SUVR) correction factors without requiring longitudinal data at inference time. Improves Centiloid consistency across tracers and studies, significantly enhancing cross-sectional and longitudinal amyloid positron emission tomography (PET) quantification. DeepSUVR-derived Centiloids show stronger associations with cognition, visual reads, and neuropathology. Longitudinal variability is reduced three- to five-fold, enabling more reliable tracking of amyloid accumulation and better detection of treatment effects. Novel reference and target masks derived from DeepSUVR replicate most of the model's performance, offering a practical alternative for integration into existing pipelines.

IntroductionLong-acting injectable cabotegravir (CAB-LA) for preexposure prophylaxis (PrEP) is a promising HIV prevention tool for people who inject drugs (PWID), who face elevated HIV risk and barriers to care. While acceptable to PWID, CAB-LA implementation in low-barrier syringe services programs (SSPs) has not been examined.MethodsFrom August 2023 to July 2025, we conducted semistructured interviews with 12 SSP staff involved in CAB-LA delivery. Interviews were transcribed and analyzed using thematic analysis guided by the Consolidated Framework for Implementation Research.ResultsFacilitators included CAB-LA's relative advantage over oral PrEP, external technical support, 340B pharmacy revenue, alignment with SSP mission and workflows, motivated staff, and financial incentives. Barriers included lack of FDA approval for PWID, complex logistics, performance pressures, infrastructure constraints, competing priorities, staff workload, and client outreach and engagement.ConclusionIntegrating CAB-LA into SSPs is promising, but successful implementation requires targeted strategies, including additional resources, workflow adaptations, and enhanced outreach.

The Psychiatric Consultation Service at Massachusetts General Hospital sees medical and surgical inpatients with comorbid psychiatric symptoms and conditions. During their twice-weekly rounds, Dr Stern and other members of the Consultation Service discuss diagnosis and management of hospitalized patients with complex medical or surgical problems who also demonstrate psychiatric symptoms or conditions. These discussions have given rise to rounds reports that will prove useful for clinicians practicing at the interface of medicine and psychiatry. Prim Care Companion CNS Disord 2026;28(1):25f04082. Author affiliations are listed at the end of this article.

The Medicaid Drug Rebate Program (MDRP) is a federal-state partnership program that aims to control prescription drug costs through contractual agreements enabling manufacturers to secure Medicaid coverage for their drugs by paying rebates to state Medicaid agencies. All states participate in MDRP, helping Medicaid beneficiaries obtain affordable access to nearly all Food and Drug Administration-approved outpatient drugs. Although the program has achieved significant cost savings for Medicaid, notable False Claims Act violations in recent years have called into question the program's operational robustness, particularly regarding the accuracy of data which underpin rebate calculations. In 2024, the Centers for Medicare and Medicaid Services made significant, necessary changes to the program; however, gaps remain. In this commentary, we review the program's operational structure, highlight ongoing challenges regarding drug misclassification and price verification, and propose recommendations for future policymaking. Further scrutiny of reporting compliance may be key to maintaining program integrity.

Objective. The efficacy of neuromodulation techniques like transcranial magnetic stimulation (TMS), are highly dependent on the geometry and conductivity of the stimulated target of the brain. Although anatomically accurate head models are routinely used for computational simulations of TMS-induced electric (E) fields, there is still a need for realistic phantoms that mimic the anatomy and electrical conductivity of the head.Approach.Here, we present a realistic rat brain phantom constructed using advanced 3-d printing technologies. Our phantom allows validation of TMS-induced E-fields using embedded mutually orthogonal triaxial dipole probes (TDP) that can measure induced E-fields along three axes. We tested the TDP probes in the constructed phantom using four TMS coils with different core materials and core geometry. These measurements were then compared to computational simulations using the finite element method (FEM).Main results.The rat brain phantoms had a conductivity of roughly 0.5 S m-1, which was mimicked in the FEM simulations. When the measured induced E-fields in the phantoms were compared to the simulated results, the measured results were in the same expected range and fairly close to one another with an average error of 5.1%. The peak E-fields (measured vs. simulated) close to the surface of the gray matter were: permender v-tip core (115.3-110 V m-1), permender flat-tip core (91.9-85 V m-1), AISI 1010 v-tip core (94.7-100 V m-1), and AISI 1010 flat-tip core (85.9-84 V m-1) respectively.Significance.These anatomically accurate and conductive rat head phantoms may be used in some cases to replacein-vivoexperimentation and computational simulations reducing regulatory requirements and lengthy simulation times.

Phenotypic heterogeneity is a defining feature of bacterial stress responses, long framed as irreducible noise arising from stochastic molecular events. This review builds on that view, advancing the idea that much of the apparent randomness instead reflects unmeasured determinants-hidden variables-that render cellular behavior predictable once revealed. We survey canonical cases such as antibiotic persistence, oxidative stress resistance, and DNA repair, highlighting how variability once thought to be stochastic can be traced with deterministic factors such as growth, cell-cycle state, microenvironment changes, or molecular inheritance. Cutting-edge tools-from lineage-resolved microfluidics, single-cell RNA-seq, and high-dimensional reporters to machine learning applied to cellular trajectories-are now beginning to expose these hidden layers of causality. By reframing noise as structure awaiting discovery, this perspective sets the stage for a predictive microbiology: one that links the microscopic state of individual cells to emergent population behaviors, with far-reaching implications for understanding pathogenesis and guiding antimicrobial strategies.