Hierarchical Porous Aggregate-Enabled Chromatography-Inspired Single-Sensor E-Nose for Volatile Monitoring.

Monitoring volatile organic compounds (VOCs) is crucial for ensuring safety and health. In this study, we introduce a strategy to engineer a chromatography-inspired single-sensor (CISS) e-nose tailored for VOC monitoring. This approach overcomes the limitations of traditional methodologies and conventional e-noses.

Association Between Liver Fibrosis and Risk of Incident Stroke and Mortality: A Large Prospective Cohort Study.

Background: There is a well-established relationship between liver conditions and cardiovascular diseases. However, uncertainty persists regarding the contribution of liver fibrosis to major stroke types including ischemic stroke, intracerebral hemorrhage, and subarachnoid hemorrhage at the population level.

Methods: In this large prospective cohort study, participants without previous stroke or coronary heart disease at baseline from the UK Biobank were included.

Intraoperative circulation predict prolonged length of stay after head and neck free flap reconstruction: a retrospective study based on machine learning.

Background: Head and neck free flap reconstruction presents challenges in managing intraoperative circulation, potentially leading to prolonged length of stay (PLOS). Limited research exists on the associations between intraoperative circulation and PLOS given the difficulty of manual quantification of intraoperative circulation time-series data. Therefore, this study aimed to quantify intraoperative circulation data and investigate its association with PLOS after free flap reconstruction utilizing machine learning algorithms.

Variational Autoencoder-based Model Improves Polygenic Prediction in Blood Cell Traits.

Genetic prediction of complex traits, enabled by large-scale genomic studies, has created new measures to understand individual genetic predisposition. Polygenic Risk Scores (PRS) offer a way to aggregate information across the genome, enabling personalized risk prediction for complex traits and diseases. However, conventional PRS calculation methods that rely on linear models are limited in their ability to capture complex patterns and interaction effects in high-dimensional genomic data.

Dual opposing quadrature-PT symmetry.

Our recent research on type-I quadrature parity-time (PT) symmetry, utilizing an open twin-beam system, not only enables observing genuine quantum photonic PT symmetry amid phase-sensitive amplification (PSA) and loss in the presence of Langevin noise but also reveals an additional classical-to-quantum (C2Q) transition in noise fluctuations. In contrast to the previous setup, our exploration of an alternative system assuming no loss involves a type-II PSA-only scheme. This scheme facilitates dual opposing quadrature-PT symmetry, offering a comprehensive and complementary comprehension of C2Q transitions and PT-enhanced quantum sensing with optimal performance in the symmetry unbroken region.