Citations

Chronic hepatitis B (CHB), a major global public health burden, is characterized by the presence of high circulating levels of non-infectious subviral particles (SVPs). These SVPs are mainly composed of small hepatitis B surface antigen (SHBs) and are associated with a dysfunctional HBV-specific immune response. Previous studies exploring the cellular mechanisms and molecular pathways by which SVPs are secreted from hepatocytes have utilized either non-hepatic cells or whole-genome HBV-integrated hepatoma cell lines in which SHBs can also be secreted as a component of the virion envelope. In this study, we provide a detailed examination of SHBs trafficking using biochemical approaches coupled with high-resolution confocal microscopy and live-cell imaging via a novel fluorophore-tagged SHBs probe in both HepG2 and primary human hepatocytes stably expressing SHBs. Our results provide evidence that SHBs utilize a modified ER-Golgi secretory pathway with transit from the ER to the multivesicular body and lysosomal/late endosomal compartments. Importantly, we identified the autophagy adapters ATG5 and LC3B, and the ER-phagy protein atlastin 3 (ATL3), central to mediating SHBs secretion. These findings suggest that SHBs is trafficked through a non-canonical path for secretion and provides new potential therapeutic targets for the treatment of CHB.

Background REM sleep behaviour disorder (RBD) is a prodrome of α -synucleinopathy, yet mechanistic pathways are unresolved. Narcolepsy type 1 with RBD (NT1-RBD) provides a human model of orexin deficiency. We tested whether REM motor semiology differs categorically between isolated RBD (iRBD) and NT1-RBD. Methods We retrospectively analyzed blinded video-polysomnographic scorings from 57 patients (iRBD n = 34; NT1-RBD n = 23). Across 857 REM events (iRBD 717; NT1-RBD 140), we classified topography (head/neck, trunk, upper, lower limbs), complexity (elementary vs. complex), content (scenic, violent, self-referential), vocal/orofacial features, spatial distribution and laterality using a pre-specified codebook. The patient was the primary unit of inference. Binary features used Fisher’s exact tests with Cohen’s h ; the per-patient complex-event proportion used Mann–Whitney and Cliff’s δ (bootstrap 95% CI). Robustness checks comprised Beta-Binomial posteriors (Beta [1,1]) and patient-label permutation tests (10,000 permutations). Results REM motor phenotypes diverged categorically. Lower-limb dominance occurred in 18/23 (78.3%) NT1-RBD vs. 7/34 (20.6%) iRBD (Fisher p < 0.0001; Cohen’s h ≈ +1.23), whereas upper-limb dominance occurred in 24/34 (70.6%) iRBD vs. 2/23 (8.7%) NT1-RBD ( p < 0.0001; h ≈ −1.40). Any complex event was present in 27/34 (79.4%) iRBD vs. 3/23 (13.0%) NT1-RBD ( p < 0.0001; h ≈ −1.46); violent enactments in 16/34 (47.1%) vs. 0/23 (0%) ( p < 0.0001; h ≈ −1.51). The per-patient complex-event proportion was higher in iRBD [median 0.21 (0.05–0.33)] than NT1-RBD [0.00 (0.00–0.00)] (Mann–Whitney p < 0.0001; Cliff’s δ = −0.665; 95% CI −0.853 to −0.441). Event-level summaries were concordant; permutation p -values were 0.0001 for upper-limb involvement and 0.0083 for complex behaviour. Conclusion iRBD and NT1-RBD exhibit qualitatively distinct REM motor phenotypes: upper-body-dominant, complex/scenic behaviours in iRBD versus elementary, predominantly bilateral lower-limb behaviours with notable trunk recruitment in NT1-RBD, supported by large effect sizes and convergent robustness checks. These findings motivate mechanistic studies of hypothalamic-brainstem-cortical integration in REM and suggest that semiological profiling may aid stratification in prodromal neurodegeneration.

ABSTRACT Background Kidney disease significantly increases the risk of dementia, including among kidney transplant (KTx) recipients. To date, the cost implications of dementia after KTx are not well described. Methods We performed a retrospective cohort study of US Renal Data System (USRDS) data (2006–2020) to estimate cost of care for ≥65‐year‐old Medicare insured KTx recipients (2006–2020) with newly diagnosed dementia ( n = 3285), compared to propensity‐matched controls without dementia ( n = 6570). KTx recipients age 65+ years with post‐KTx dementia were identified by diagnosis codes, and costs were computed based on payments on Medicare claims. Average costs per month, marginal costs per month, and cumulative costs were compared after dementia diagnosis versus after the equivalent time post‐KTx in controls. Results Dementia was diagnosed at a mean of 5.1 ± 3.4 years post‐KTx. Patients' characteristics were well matched in cases versus controls, including age (mean: 70.1 vs. 69.9 years), sex (38.4% vs. 37.9% women), race (23.7% vs. 22.2% African American), and cause of ESKD (45.4% vs. 43.7% diabetes). Over 4 years post‐KTx, dementia was associated with reduced survival (27% vs. 68%) along with $66 145 (95% CI $51 560‐$78 489) higher Medicare spending. Average monthly costs in dementia patients reached a maximum of $12 713 and exceeded the cost of unaffected patients by up to $9789 per month. Conclusions Post‐KTx dementia dramatically increased resource utilization and reduced post‐KTx surivival. These findings highlight the need for care pathways that better integrate cognitive health assessment and management into the care of KTx candidates and recipients.

ABSTRACTObjectivesThis final post hoc analysis evaluated patient‐reported outcomes from the Phase 3 MAIA study of daratumumab, lenalidomide, and dexamethasone (D‐Rd) versus lenalidomide and dexamethasone (Rd) after median 64.5‐month follow‐up in transplant‐ineligible patients with newly diagnosed multiple myeloma (NDMM), including patient subgroups.MethodsKey scales from the EORTC QLQ‐C30 (global health status [GHS], physical functioning, pain, and fatigue) were assessed. Scores were evaluated every 3 months for 1 year, then every 6 months until disease progression.ResultsThe intent‐to‐treat population (n = 737) included 46.3% frail, 35.4% 70 to < 75 years old, and 43.6% ≥ 75 years old. D‐Rd‐treated patients showed improvements from baseline that were sustained over 5 years in the intent‐to‐treat population and across subgroups by age, frailty, and bone lesions. Greater proportions of patients treated with D‐Rd versus Rd achieved minimally important changes for improvement at cycle 36 (year ~3) in GHS (odds ratio, 1.84 [95% CI, 1.16–2.91]), physical functioning (1.93 [1.18–3.14]), pain (1.41 [0.90–2.22]), and fatigue (2.00 [1.24–3.23]). Greater proportions of patients with bone lesions improved with D‐Rd versus Rd on GHS and physical functioning.ConclusionsIn transplant‐ineligible patients with NDMM, D‐Rd improved health‐related quality of life over a 5‐year period versus Rd. Trial Registration: ClinicalTrials.gov: NCT02252172

Background. Pancreas transplant biopsy practices for the diagnosis of rejection or other pathologies are not well described. Methods. We conducted a survey of staff at US pancreas transplant programs (March 22, 2022, to August 22, 2022) to assess current program practices and perceptions about the utility and challenges in the performance and interpretation of pancreas allograft biopsies. Results. Respondents represented 65% (76/117) of active adult pancreas transplant programs, capturing 66% of recent pancreas transplant volume in the United States. Participants were most often nephrologists (52%), followed by surgeons (46%), and other staff (4%). Pancreas allograft biopsies were performed mostly by interventional radiologists (74%), followed by surgeons (11%), nephrologists (8%), and gastroenterologists (1%). Limitations in the radiologist’s or biopsy performer’s comfort level or expertise to safely perform a biopsy, or to obtain sufficient/adequate samples were the two most common challenges with pancreas transplant biopsies. Pancreas transplant biopsies were read by local pathologists at a majority (86%) of centers. Challenges reported with pancreas biopsy interpretation included poor reliability, lack of reporting of C4d staining, lack of reporting of rejection grading, and inconclusive interpretation of the biopsy. Staff at a third of responding programs (34%) stated that they rarely or never perform pancreas allograft biopsies and treat presumed rejection empirically. Conclusions. This national survey identified significant variation in clinical practices related to pancreas allograft biopsies and potential barriers to pancreas transplant utilization across the United States. Consideration of strategies to improve program experience with percutaneous pancreas biopsy and to support optimal management of pancreas allograft rejection informed by histology is warranted.

Accurate prediction of progression in subjects at risk of Alzheimer's disease is crucial for enrolling the right subjects in clinical trials. However, a prospective comparison of state-of-the-art algorithms for predicting disease onset and progression is currently lacking. We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international teams at predicting the future trajectory of 219 individuals at risk of Alzheimer's disease. Challenge participants were required to make a prediction, for each month of a 5-year future time period, of three key outcomes: clinical diagnosis, Alzheimer's Disease Assessment Scale Cognitive Subdomain (ADAS-Cog13), and total volume of the ventricles. The methods used by challenge participants included multivariate linear regression, machine learning methods such as support vector machines and deep neural networks, as well as disease progression models. No single submission was best at predicting all three outcomes. For clinical diagnosis and ventricle volume prediction, the best algorithms strongly outperform simple baselines in predictive ability. However, for ADAS-Cog13 no single submitted prediction method was significantly better than random guesswork. Two ensemble methods based on taking the mean and median over all predictions, obtained top scores on almost all tasks. Better than average performance at diagnosis prediction was generally associated with the additional inclusion of features from cerebrospinal fluid (CSF) samples and diffusion tensor imaging (DTI). On the other hand, better performance at ventricle volume prediction was associated with inclusion of summary statistics, such as the slope or maxima/minima of patient-specific biomarkers. On a limited, cross-sectional subset of the data emulating clinical trials, performance of the best algorithms at predicting clinical diagnosis decreased only slightly (2 percentage points) compared to the full longitudinal dataset. The submission system remains open via the website https://tadpole.grand-challenge.org, while TADPOLE SHARE (https://tadpole-share.github.io/) collates code for submissions. TADPOLE's unique results suggest that current prediction algorithms provide sufficient accuracy to exploit biomarkers related to clinical diagnosis and ventricle volume, for cohort refinement in clinical trials for Alzheimer's disease. However, results call into question the usage of cognitive test scores for patient selection and as a primary endpoint in clinical trials.