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Geochemical distribution and genesis of selenium-rich soils in Maojie Town on the Yunnan low-selenium belt
The Role of Intrinsically Disordered Domains in Regulating G Protein-Coupled Receptor Signaling
Temporal proteomic profiling of iPSC-derived human liver organoids reveals optimal maturation for drug metabolism and toxicology
Abstract Liver organoids have emerged as an innovative three-dimensional model system that effectively recapitulates the structural and functional complexities of human liver tissue, addressing limitations of traditional two-dimensional culture systems. This study presents a comprehensive temporal proteomic characterization of iPSC-derived human liver organoids (iHLOs) by profiling 5,736 proteins across their four developmental stages, Days 7, 15, 30, and 45, to identify optimal timepoints for drug metabolism and toxicological applications. The analysis revealed that Day 30 represents the peak of functional maturity, marked by the highest expression of key-metabolizing enzymes, such as cytochrome P450 3A4 (CYP3A4), along with cholangiocyte-specific proteins and hepatic metabolic enzymes. Functional validation of CYP3A4 activity through rifampicin induction and ketoconazole inhibition demonstrated metabolic competence comparable to existing in vitro liver models, including HepaRG cells and primary human hepatocytes. Interestingly, Day 45 organoids exhibited a shift toward a mesenchymal cell profile, with increased markers of hepatic stellate cells, suggesting utility for disease modeling applications. These findings indicate Day 30 of liver organoids as the optimal stage for drug metabolism and toxicological investigations, providing a proteomic framework that enhances their utility of iHLOs as physiologically relevant liver models.
Incorporating Carbamate Groups into Polyolefin Elastomers for High Performance and Closed-Loop Recyclability
NiCd/ZnO nanocomposites: novel materials for photocatalytic degradation of Allura Red dye
Bubble Management via Synergy of Dual-Gradient Electrodes and Electrolytes for High-Efficiency Water Electrolysis
An explainable real time sensor graph transformer for dance recognition
Harnessing Aggregation-Induced Quantum Interference in Molecular Junctions for Enhanced Electron Transport
Skin advanced glycation end-products do not predict pulmonary function trajectories in adults from the ILERVAS cohort
Unveiling Exciton-Molecular Crosstalk Mediating Photocatalysis on Perovskite Quantum Dots via <i>In-Situ</i> SERS
A Lightweight Sequential AI Framework for Real Time Intrusion Detection in Dynamic Vehicular Networks
Proton-Transfer Isomerization Driven by Strong Electric Fields in Aqueous Microdroplets
Stochastic LASSO for extremely high-dimensional genomic data
Intrinsic Electric Field Triggers Phenol Oxidative Degradation at Microbubble Interfaces
Identification and validation of a refined CAF-Associated diagnostic signature in breast cancer
Anomalous Saturation of CO Adsorption at 26% on Cu(111) Governed by Nanometer-Scale Substrate-Mediated Interactions
Assessing the relationships between capability, opportunity, and motivation in influencing self-isolation behaviour during pandemics
Abstract Adherence to self-isolation was a central measure for controlling the spread of COVID-19; however, compliance varied widely. Understanding the behavioural determinants that drive adherence is critical for informing future public health intervention. This study applied the COM-B model to examine the associations between capability, opportunity, motivation, and self-isolation behaviour during the COVID-19 pandemic in the United Kingdom. A retrospective analysis was conducted using secondary data from the UK Office for National Statistics 2019 Opinions and Lifestyle Survey, which was not originally designed to measure COM-B constructs. Structural equation modelling (SEM) was used to examine the relationships between capability, opportunity, motivation, and self-isolation behaviour. Opportunity and motivation were significantly associated with self-isolation, while capability was linked to behaviour indirectly through its association with motivation, reflecting a possible pathway suggested by the structural model. Although some measurement indicators demonstrated lower reliability owing to the use of secondary data, the overall model fit was good (RMSEA = 0.049, CFI = 0.966, TLI = 0.944, SRMR = 0.040). These findings highlight the dominant influence of social and motivational factors in shaping adherence. This study demonstrates the utility of the COM-B model for understanding self-isolation behaviour despite the constraints of secondary data. The findings highlight opportunity and motivation as key levers for promoting adherence and offer actionable insights for policymakers to design interventions that enhance motivation, strengthen social support, and sustain compliance during future public health emergencies.