Citations

Metabolic dysfunction-associated steatohepatitis (MASH) is a global health care burden. Appropriate large animal models mimicking the main MASH characteristics of steatosis, inflammation, and hepatocyte damage alongside progression of fibrosis are imperative for robust preclinical studies, especially in the field of hepatobiliary surgery. The present study aimed to characterize a novel model of steatohepatitis in fumarylacetoacetate hydroxylase-deficient ( FAH -/- ) pigs. FAH -/- pigs were generated using a CRISPR/Cas9 system. The animals received a choline-deficient, L-amino acid-defined high-fat diet and subtherapeutic doses of nitisinone and were followed for 3 months. Liver biopsies were obtained at baseline and every month during treatment. Steatosis, inflammation, and fibrosis were assessed by conventional histological scoring systems and by an artificial intelligence (AI) model. Serum liver parameters were analyzed every 2 weeks. Steatosis increased significantly throughout the study, with severe steatosis observed as early as 2 months into treatment. The inflammation score was increased in all animals after 3 months of treatment, whereas the AI-based CD45+ cell count showed region-specific trends in the portal and lobular areas. Collagen content and the corresponding fibrosis stage showed an increase over the 3-month period; however, the difference was not significant. Serum liver parameters did not show any relevant elevations during the study. In summary, we successfully developed and characterized a novel model of steatohepatitis in the FAH -/- pig within 3 months. Further studies with prolonged observation time and/or cycling of nitisinone administration are needed to evaluate whether progressive fibrosis and cirrhosis could be achieved with this model.

Abstract Object Transdermal biosensors may provide an alternative to conventional blood-based biomarker measurement. Our purpose was to determine the binary correlation between transdermal (Infrasensor™; RCE, Inc, Carlsbad, CA) and conventional blood-based measurements. Methods This was a secondary analysis from a previously published observational cardiac troponin I (cTnI) study performed to establish the upper reference level of cTnI, at 10 US hospitals. After obtaining informed consent, 2 cohorts of patients were enrolled: 1) those who completed a health assessment questionnaire and appeared healthy, and 2) those with a known elevated cTnI per the local hospital standard assay. All blood lab analyses were performed at the University of Maryland Medical Center, Baltimore, MD. Normal was defined as cTnI <53.48 ng/L (male) or 34.11 ng/L (female) using the Siemens Atellica IM assay (Siemens Medical Solutions, Mountain View, CA), NT-proBNP <450 pg/mL (>75 years) or <124 pg/mL (<75 years), creatinine >1.17 mg/dL (male) or >0.95 mg/dL (female), and HbA1c <6.4%. The Infrasensor was placed on the patient’s wrist for measurement and blood drawn for analysis at approximately the same time. Results Of 840 enrolled patients, the median (IQR) age was 46 (30,57), 416 (49.5%) were female, 10.36% Hispanic, 6.7% Asian, 12.9% African American, and 69.1% White. Elevated lab tests were 102 hscTnI’s, 156 NTproBNP’s, 37 HbA1C’s, and 163 creatinine’s. Significant binary correlations were found between all transdermal signals and the corresponding lab blood levels Conclusion Infrasensor transcutaneous measurement demonstrates similar results as that obtained from blood testing in the central laboratory. Capsule The Infrasensor (RCE, Inc, Carlsbad, CA, USA) is rapid point of care transcutaneous biomarker measurement device. This study evaluated its ability to provide qualitative results for troponin I, NTproBNP, creatinine, and HbA1c levels in 840 patients. Significant correlations were found between all transdermal signals and the corresponding binary lab blood levels.

Abstract Objective High-frequency oscillations (HFOs) are highly specific biomarkers of epileptogenic tissue, yet their noninvasive localization remains challenging due to their brief duration, low amplitude, and poor signal-to-noise ratio. Here, we introduce TH-DeepSIF, a transformer-based deep learning framework trained on biologically realistic neural mass model simulations, to robustly perform HFO source imaging from scalp EEG. Methods TH-DeepSIF was evaluated in simulated single- and dual-source HFO scenarios, where it was tasked with recovering both the spatial location and temporal dynamics of HFO generators under increasing spatiotemporal complexity. We further validated TH-DeepSIF in 25 patients with drug-resistant epilepsy by comparing EEG source imaged HFO sources against surgical resection regions. Results TH-DeepSIF accurately recovered both the spatial location and temporal dynamics of simulated HFO generators, achieving low localization error and strong waveform correspondence with ground truth. TH-DeepSIF localization for pathological HFOs (pHFOs, or spike ripples) demonstrated strong agreement with surgical resection regions, achieving a median localization error of 11.9 mm and specificity of 0.896. Compared with all HFOs (aHFOs), pHFO-based source imaging showed significantly stronger spatial correspondence with resection regions, significantly smaller localization error, and higher precision, sensitivity, geometric mean, and F1 score. Significance These findings demonstrate that TH-DeepSIF provides a robust, data-driven framework for noninvasive HFO source imaging with improved anatomical specificity and enhanced clinical utility for presurgical evaluation using scalp EEG. Moreover, they show that pathological HFOs (spike ripples )—rather than general HFOs—serve as robust EEG biomarkers for accurate localization of the epileptogenic zone. Key Points A fully data-driven, parameter-free framework for noninvasive HFO source imaging using scalp EEG. Pathological HFO source maps exhibit strong spatial concordance with both the surgical resection region and the seizure onset zone. Source imaging based on pathological HFOs consistently outperforms imaging based on all detected HFOs.

Abstract Background Ventricular arrhythmias (VAs) are a proximate mechanism of sudden cardiac death, yet national patterns in place of death (POD) and their determinants remain sparsely described. We quantified 25-year trends and factors associated with POD among UAs decedents in the United States. Methods We analyzed CDC WONDER Multiple Cause of Death data (1999–2024) for adults ≥25 years with ventricular arrhythmias (ICD-10 I47.2, I49.0) as underlying cause. POD was categorized as inpatient, outpatient/emergency department (ED), home, hospice/nursing, or other/unknown. Covariates included age, sex, race, Hispanic origin, and urbanization. We calculated Annual and Average Annual Percent Changes (AAPCs and APC) using Age-Adjusted Mortality Rates (AAMRs), and fit multinomial logistic regression (reference = inpatient) to obtain adjusted odds ratios (ORs, 95% CIs). Results Among 433,988 ventricular arrhythmia (VA) deaths, POD was inpatient 62.0%, outpatient/ED 18.1%, home 11.1%, hospice/nursing 5.8%, other 3.1%. Inpatient deaths increased from 57.8% (1999) to 66.1% (2024). AAMRs declined sharply from 13.3 per 100,000 in 1999 to 6.3–6.5 during 2010–2019, then rose to 7.4 in 2021 and fell to 6.8 in 2024. In home vs inpatient: ≥85 years, medium/small metropolitan counties and rural counties had higher odds of VA deaths, whereas younger age groups, females, Black, American Indian, Asian/Pacific Islander individuals and Hispanic individuals had lower odds. In outpatient/ED vs inpatient: 25–44 years, 45–64 years, males, Black, American Indian and Asian/Pacific Islander individuals had higher odds, whereas ≥85 years and females had lower odds. In hospice/nursing facilities: ≥85 years, females, Whites, non-Hispanic individuals, medium/small metropolitan counties and rural counties had higher odds of VA deaths, whereas younger age groups, Black, American Indian, Asian/Pacific Islander individuals and Hispanic individuals had markedly lower odds. Conclusion From 1999–2024, VA deaths shifted toward hospitals. Persistent disparities by age, sex, race/ethnicity, and rurality highlight the need to expand equitable advance care planning and device deactivation discussions.

Objectives: Smoking is a key risk factor for pancreatitis, contributing to pathogenesis and disease progression. Data regarding second-hand smoking, or passive smoking (PS) exposure, are lacking. We therefore aimed to assess the impact of PS exposure across the pancreatitis spectrum. Methods: We analyzed baseline data from the PROCEED study, a multicenter study in the United States including patients with acute (AP), recurrent acute (RAP), and chronic (CP) pancreatitis. Participants detailed their individual smoking history and PS exposure, which was compared between AP, RAP, and CP subgroups. Participant factors and clinical characteristics were compared by level of individual and PS exposure. Results: Among 1369 participants (190 AP, 498 RAP, 681 CP), 346 (25.3%) were current and 409 (29.9%) were former smokers. The CP subgroup had the highest proportion of current smokers (36.7% CP vs 15.1% RAP, 11.1% AP, P < 0.001). PS exposure was also significantly higher in the CP subgroup (68.6% CP vs 58.2% RAP, 55.3% AP, P < 0.001). A minority (16.3%) with CP reported no smoking exposure (by self or passive) while nearly half smoked ≥20 pack-years. The mean PS duration was significantly higher in CP participants (21.8 y) compared with those with AP (17.8 y) or RAP (18.9 y) ( P < 0.0166). Conclusions: In this multicenter study, we affirmed an association with smoking use and intensity with CP-related complications. For the first time, we report a high prevalence of prior exposure to passive smoking in all pancreatitis subtypes, which requires further study to understand the impact on disease outcomes.

Background. Although solid organ transplant prolongs survival in end-stage disease, recipients face high symptom burden and complex decisions at multiple junctures. Palliative care (PC) may address these needs, but referrals in transplant programs are infrequent, often reactive, and the benefits remain unclear. Methods. We retrospectively studied 12 676 heart, liver, lung, and kidney transplants across 3 Mayo Clinic sites (2018–2024). PC encounters were classified as pretransplant (≤1 y before admission), peritransplant (during hospitalization), or posttransplant (≤1 y after discharge). Results. Only 8.3% engaged PC, with patterns varying by organ and timing. Heart programs demonstrated the highest overall engagement, primarily pre- and peritransplant, whereas lung and kidney referrals occurred more often after discharge. Earlier timing coincided with longer survival, whereas peri- and posttransplant encounters occurred closer to death. In heart transplantation, pre- and peritransplant PC were observed in recipients with lower procedural volume and fewer short-term readmissions. Liver and lung cohorts displayed variable patterns. Kidney referrals occurred infrequently and were concentrated among recipients with higher morbidity. Timing of inpatient consultation showed a strong positive correlation with hospital length of stay, and pretransplant PC coincided with higher rates of goals-of-care discussions and fewer hospital interventions. Adapting screening criteria to focus on high-risk recipients, PC was associated with fewer short-term readmissions for heart and lung recipients. Conclusions. PC among solid organ transplant was infrequent and varied. Referral timing often aligned with patient morbidity and mortality. Structured, prospective validation of screening methods may identify patients most likely to benefit from palliative involvement.

Background: Knee injuries are among the most common injuries in female basketball players. Despite the growing popularity of professional women's basketball, particularly the Women's National Basketball Association (WNBA), there are limited recent data evaluating the incidence of and risk factors for knee injuries in WNBA athletes. Hypothesis: Older age, minutes played per game, number of games played, and player usage rate would be significantly associated with having a knee injury in WNBA players from the 2017 to 2022 seasons. Study Design: Descriptive epidemiology study. Methods: Publicly available data on the injury history and player records of active WNBA players between the 2017 and 2022 seasons were reviewed to identify players with a knee injury resulting in ≥1 games missed. The primary outcome was the incidence of knee injuries reported per 1000 minutes-exposures (MEs). Player demographics, statistics, and injury characteristics were recorded. Secondary analysis was conducted using bivariate and multivariable logistic regression to investigate risk factors associated with having a knee injury. Results: A total of 87 players (10.8% of all players) sustained a combined 104 knee injuries between the 2017 and 2022 seasons, indicating a rate of 6.03 knee injuries per 1000 MEs. Accounting for potential confounders, having a knee injury was significantly associated with older age (OR, 1.11; 95% CI, 1.05-1.18; P = .0002) and higher usage rate (OR, 1.06; 95% CI, 1.02-1.11; P = .02). Conclusion: This study showed that knee injuries occurred in 10.8% of players, with an overall rate of 6.03 injuries per 1000 MEs. The most significant risk factors associated with having a knee injury in WNBA athletes were older age and higher player usage rate. Implementing targeted load management strategies for players with higher usage rates or advanced age may help reduce the incidence of knee injuries among female basketball athletes.