Median SCP (Spain)

Background:Cirrhosis and cirrhosis-related deaths have risen in the United States in recent years. Ascites is a common complication, often requiring large-volume paracentesis (LVP). The American Association for the Study of Liver Diseases (AASLD) recommends the administration of albumin in conjunction with LVP to prevent further complications of cirrhosis. Emerging research in cirrhosis care reveals significant variations in outcomes among different demographics. Therefore, we assessed the use of guideline-adherent albumin and outcomes in U.S. patients undergoing LVPs, particularly at the intersection of race, ethnicity, socioeconomic disparities, and cirrhosis.Methods:This retrospective study utilized Cerner Real World Data to identify adults with cirrhosis and ascites undergoing LVP between January 2016 and June 2022. We assessed albumin utilization patterns across racial and ethnic groups and payor types, and their overall impact on acute kidney injury (AKI)-related hospitalization using an adjusted generalized linear model (aGLM).Results:We identified 736 patients: 301 in the LVP + albumin group and 435 in the LVP-only group. Despite clinical recommendations, only 41% undergoing LVPs received albumin. White patients and commercially insured patients received albumin at higher rates (p=0.042 and p=0.009, respectively). The overall rate of AKI-related admissions within the 30-day post-procedure period was 26%. However, patients who received albumin during LVP had a 36% lower risk of short-term AKI-related hospitalization (OR: 0.64; p=0.03).Conclusions:These findings indicate a potential for broader albumin utilization in U.S. patients with refractory ascites undergoing repeated LVPs to reduce AKI-related admissions.

Canvases and preparation layers consist of diverse materials that respond differently to mechanical stress. In a canvas painting, elongations and shrinkages can cause deformations—either recoverable or permanent—as well as shear stresses and potential cracks, which may weaken the overall structure. This study aims to better understand the interaction between the canvas and preparatory strata in terms of mechanical behavior. To achieve this, a set of canvases and the same types of canvases with preparation layers were selected. Two types of linen and two types of polycotton were chosen to represent contemporary materials currently available in fine-art stores. Additionally, an accelerated aging process was applied to the samples to compare their mechanical response before and after aging. By examining the mechanical behavior of both primed and unprimed canvases through dynamometric tests, a method to evaluate the mechanical degradation attributable to the ground layer has been developed and explained in detail. This method is applicable to cases with similar characteristics. Analysis of the force/elongation graphs for the ground layer allows for the calculation of how this layer evolves with increasing elongation and how the mechanical degradation worsens. The results highlight the differing mechanical behaviors among the analyzed canvas types in both the warp and weft directions, as well as the degradation values resulting from both the aging process and the dynamometric testing of the canvases and ground layers.

Introduction and Objective: AI-driven glucose predictions help CGM users manage glucose levels more proactively. The Accu-Chek® SmartGuide Predict app notifies of low glucose levels within 30 minutes (LGP), nighttime hypoglycemia risk (NLP), and provides a continuous 2-hour glucose forecast (GP). This study evaluates the potential glycemic benefits of the app via in-silico analysis. Methods: Using UVa's digital twin methodology, 2458 days from 20 individuals in the REPLACE-BG dataset were simulated. Interventions: 15g fast-acting carbs after LGP notifications, 30g slow-absorbing carbs for high NLP risk at 22:30, and advancing/adding correction boli if GP forecast >220 mg/dL. Baseline intervention used a GP-like hyperglycemia mitigation strategy, substituting predictions with current CGM data. All hypoglycemia interventions are aligned with ADA guidelines. Nighttime meals/boli were omitted to better assess NLP. Results: LGP reduced %time <70mg/dL (4.2±1.5 vs 0.46±0.28 p<1e-4). GP reduced %time >180mg/dL (25.3±10.2 vs 22.0±8.6 p<1e-4). NLP decreased overnight %time <70mg/dL (5.6±2.2 vs 3.8±1.2 p<1e-4). Combining all features significantly reduced time outside range. Conclusion: The Accu-Chek® SmartGuide Predict app has the potential to enhance glycemic control in T1D. Limitations include the in-silico nature of the study and assumptions made in the user behaviour models. Disclosure P. Herrero: Employee; Roche Diabetes Care. M. Andorrà: Employee; Roche Diagnostics. Stock/Shareholder; Roche Diagnostics. M.D. Breton: Speaker's Bureau; Sinocare Inc, Tandem Diabetes Care, Inc. Consultant; Roche Diabetes Care, Boydsense. Y. Klopfenstein: Consultant; Roche Diagnostics. T. Glatzer: Employee; Roche Diabetes Care. Stock/Shareholder; Roche Diabetes Care, Abbott, Dexcom, Inc. Funding The research has been funded by Roche Diabetes Care GmbH

Abstract Tracing lipid metabolism in mammalian cells presents a significant technological challenge due to the vast structural diversity of lipids involved in multiple metabolic routes. Bioorthogonal approaches based on click chemistry have revolutionized analytical performance in lipid tracing. When adapted for mass spectrometry (MS), they enable highly specific and sensitive analyses of lipid transformations at the lipidome scale. Here, we advance this approach by integrating liquid chromatography (LC) prior to MS detection and developing a software‐assisted workflow for high‐throughput data processing. LC separation resolved labeled and unmodified lipids, enabling qualitative and quantitative analysis of both lipidome fractions, as well as isomeric lipid species. Using synthetic standards and endogenously produced alkyne lipids, we characterized LC‐MS behavior, including preferential adduct formation and the extent of in‐source fragmentation. Specific fragmentation rules, derived from tandem MS experiments for 23 lipid subclasses, were implemented in Lipostar2 software for high‐throughput annotation and quantification of labeled lipids. Applying this platform, we traced metabolic pathways of palmitic and oleic acid alkynes, revealing distinct lipid incorporation patterns and metabolic bottlenecks. Altogether, here we provide an integrated analytical and bioinformatics platform for high‐throughput tracing of lipid metabolism using LC‐MS workflow.

A chromosomal rearrangement such as a reciprocal translocation (RT) in a breeding boar can produce unbalanced gametes during meiosis, leading to a decreased litter size with detrimental economic implications for breeders. FISH and standard karyotyping are currently used to detect RTs, but a fresh sample is required, limiting the shipping conditions. Here, we investigated Hi-C as an alternative technique to diagnose chromosome rearrangements. We show that Hi-C can be used to detect such RTs from either a fresh or a frozen blood sample and therefore this technique represents an alternative to FISH for RT detection.

Disease progression in Alzheimer's Dementia (AD) is typically characterized by accelerated cognitive and functional decline, where heterogeneous trajectories can impact the observed treatment response. We hypothesized that unobserved heterogeneity could obscure treatment benefits in AD. The effect of unobserved heterogeneity was empirically quantified within the Alzheimer's Management By Albumin Replacement (AMBAR) phase 2b trial data. The ADAS-Cog 12 cognition endpoint was reanalyzed in a 2-class latent growth mixture model initially fit to the treatment arm. The model with the best fit was then applied across both treatment arms to a larger (n=1000) simulated dataset that was representative of AMBAR trial cognitive data. Two classes of patients were observed: a stable cognitive trajectory class and a highly variable class. Removal of the latter (n=48, 22%) from the analysis and refitting efficacy models comparing the stable class to full placebo yielded significant treatment efficacy on cognition (p=0.007, Cohen's D=-0.4). Comparison of the stable class of each arm within the simulated dataset revealed a significant difference in treatment efficacy favoring the simulated stable treatment arm. This post hoc exploratory analysis suggests that prespecified strategies for addressing unobserved heterogeneity may yield improved effect detection in AD trials. The generalizability of the analytic strategy is limited by latent stratification in only the treatment arm, a requirement given the small placebo arm in AMBAR. This limitation was partially addressed by the simulation modeling.