Yan, Yan

Ex vivo liver perfusion (EVLP) sustains human or large animal livers outside the body under near-physiological conditions, enabling functional monitoring for lactate clearance, bile production, and oxygen consumption and allowing targeted therapeutic interventions. Originally developed to optimize donor grafts for transplantation, EVLP has evolved into a powerful translational research platform bridging preclinical discovery and early clinical translation. This review discusses EVLP as a platform for gene therapy, immunotherapy, pharmacology, and personalized medicine, with particular emphasis on gene- and immune-based interventions as mechanistically mature exemplars. We consolidate advances in pharmacological testing and toxicity modeling, viral and non-viral gene delivery, genome engineering, and immunomodulation using perfused livers. We further describe emerging applications, including autologous EVLP pathways for organ-confined therapy, ex vivo liver surgery, and bioengineering strategies such as biliary organoid repair, RNA interference, and mitochondrial transfer. We highlight how these applications align with a paradigm shift in biomedical research, including the NIH’s recent initiative to prioritize human-based experimental models over animal-only studies. By leveraging transplant-declined or surgically resected organs that would otherwise be unused, ex vivo perfusion bridges the gap between pre-clinical testing and clinical practice, enabling real-time evaluation of interventions in functional human tissue. We discuss both the scientific opportunities afforded by EVLP and the technical, biosafety, and ethical challenges that must be addressed to enable responsible clinical translation.

Background: Colorectal cancer (CRC) remains one of the common causes of cancer-related morbidity and mortality in the United States. Emerging increases in early-onset CRC and persistent disparities remain major public health concerns. Objective: To characterize long-term CRC incidence and mortality trends in the United States, with particular emphasis on identifying demographic groups experiencing rising or plateauing disease burden. Methods: We conducted a population-based ecological study using CRC incidence data from the United States Cancer Statistics database (1999–2022) and mortality data from CDC WONDER (1999–2023). Temporal trends were evaluated using Joinpoint regression to estimate annual percent change (APC) and average annual percent change (AAPC), stratified by age, sex, race/ethnicity, and urbanization level. Results: Overall CRC incidence and mortality declined during the study period (both AAPC approximately −2.08%). However, incidence increased significantly among adults younger than 55 years, particularly those aged 20–24 years. Mortality also increased among younger adults aged 25–44 years and remained elevated among individuals aged 45–54 years. Non-Hispanic Black individuals consistently experienced the highest incidence and mortality rates. Mortality declines plateaued in several older age groups after 2018–2020. Conclusions: Despite overall improvements in CRC burden, increasing incidence and mortality among younger adults and persistent disparities highlight the need for risk-stratified prevention, earlier detection strategies, and tailored therapeutic approaches.

INTRODUCTION: Colonoscopies reduce colorectal cancer incidence and mortality, but challenges remain in detecting all precancerous lesions. Operator fatigue, technique variability, and subtle lesions can lead to missed adenomas, highlighting the need for tools that standardize detection quality. Computer-aided detection (CADe) systems use artificial intelligence to enhance lesion detection and improve screening colonoscopy quality. This study evaluates the impact of CADe on key quality and efficiency metrics in a clinical setting. METHODS: A single-center retrospective study at an academic tertiary center analyzed 4,028 colonoscopies from October 2022 to December 2023. The CADe system was used in 4 of 8 endoscopy suites, creating a CADe and control group. Propensity matching accounted for age, sex, indication, and physician. Primary outcomes included adenoma detection rate (ADR) and polyp detection rate (PDR). Adenomas per colonoscopy (APC) and polyps per colonoscopy (PPC) were also measured. Per-polyp analyses were performed as a tertiary outcome. RESULTS: ADR was significantly higher in the CADe group (38.6%) vs control (34.2%) (rate ratio [RR] = 1.127, P < 0.05). PDR was significantly higher in the CADe group (67.2%) vs control (59.4%) (RR = 1.130, P < 0.05). APC was significantly higher in the CADe group (M = 0.406, SD 0.637) vs control (M = 0.359, SD 0.599) (RR = 1.131, P < 0.05). PPC was significantly higher in the CADe group (M = 1.297, SD 1.188) vs control (M = 1.046, SD 1.002) (RR = 1.240, P < 0.05). The increase in polyp resection with CADe was driven predominantly by ≤5 mm lesions, with comparatively smaller differences for larger polyps. DISCUSSION: Implementing CADe in clinical practice significantly improved ADR, PDR, APC, and PPC. However, the increase in ADR seems inflated by the detection of polyps ≤5 mm, whose clinical significance in reducing colorectal cancer remains uncertain.

Abstract Objectives To comprehensively evaluate the validity of International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes for both prevalent diagnoses and less common diseases, and to assess the performance of a large language model (LLM)-based system in validating these codes. Materials and Methods This retrospective study analyzed hospital admissions from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. We developed a validated LLM-based system using GPT-4o, refined through iterative prompt engineering, to assess ICD-10-CM code validity. We measured the positive predictive value (PPV) of ICD-10-CM codes, PPV of principal and secondary diagnoses, and the performance of an LLM-based system in code validation. Results Among 865 079 assigned codes, the PPV was 84.6% (95% CI, 84.5%-84.6%). Principal diagnoses had a PPV of 93.9% (95% CI, 93.7%-94.1%), while secondary diagnoses had a PPV of 83.8% (95% CI, 83.7%-83.9%). The LLM system demonstrated high performance in validating ICD codes, achieving 93.6% accuracy, 95.4% sensitivity, and 85.2% specificity. Among correctly assigned secondary diagnoses, the majority (67.9%) represented historical or baseline conditions, while 32.1% reflected active conditions that deviated from baseline status; 22.3% of these emerged after hospital admission. PPV decreases with later diagnosis positions, with the largest decline occurring between principal and secondary diagnoses. Discussion and Conclusion In this large-scale evaluation, ICD-10-CM codes exhibited generally high accuracy, though variability existed by position and condition type. A validated LLM system performed comparably to physician review and offers a scalable means to improve coding accuracy. These findings support the potential for integrating LLM-based auditing into routine workflows to strengthen the quality of administrative and research data.

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) has surged as a major cause of liver transplants in the United States. Existing studies have presented conflicting findings regarding the association between liver characteristics (specifically steatosis and fibrosis) and mortality. This study investigates the relationship between the controlled attenuation parameter (CAP) and liver stiffness measurement (LSM) via vibration-controlled transient elastography (VCTE) and all-cause mortality in MASLD patients. Methods: Using the NHANES 2017-2018 database, 3821 individuals representing the United States population with MASLD underwent VCTE for liver stiffness measurement. Exclusion criteria were applied, eliminating ineligible cases, incomplete examinations, underage individuals, and those with hepatitis B or C, along with significant alcohol consumption history. Cox proportional hazard models assessed the hazard ratio (HR) for all-cause mortality in CAP and LSM. Cox regression analysis with interaction terms was employed for deeper exploration. Results: The study unveiled a strong, independent correlation between LSM and all-cause mortality. However, the CAP failed to demonstrate a significant association with mortality in both univariate and adjusted analyses, contrary to recent findings. The analysis underscores the importance of accurately measuring liver stiffness via VCTE in predicting adverse outcomes in MASLD patients, emphasizing the pivotal role of fibrosis in assessing mortality risk. Conclusion: This study reaffirms the robust link between liver fibrosis (measured through VCTE) and mortality among MASLD individuals. The absence of a significant association between steatosis (indicated by CAP) and mortality challenges recent research, urging further comprehensive investigations with larger cohorts to delineate steatosis’ precise impact on MASLD-related mortality.