Public Health.

Background: Delirium is a common neurological complication in older adults after a major illness or surgery and is characterized by acute dysfunction in cognition, attention, and awareness. Once diagnosed, it is associated with an increased risk for dementia. Frailty is an age-related syndrome and is associated with poorer postoperative outcomes, and is an emerging risk factor for delirium.

Large-scale multicenter study reveals anticitrullinated SR-A peptide antibody as a biomarker and exacerbator for rheumatoid arthritis.

Current diagnosis and treatment of rheumatoid arthritis (RA) is still challenging. More than one-third of patients with RA could not be accurately diagnosed because of lacking biomarkers. Our recent study reported that scavenger receptor-A (SR-A) is a biomarker for RA, especially for anticyclic citrullinated peptide antibody (anti-CCP)-negative RA.

The mechanism of LQTS related CaM mutation E141G interfering with Ca1.2 channels function through its C-lobe.

Mutations in the CALM1-3 genes, which encode calmodulin (CaM), have been reported in clinical cases of long QT syndrome (LQTS). Specifically, the CaM mutant E141G (CaM) in the variant CALM1 gene has been identified as a causative factor in LQTS. This mutation disrupts the normal Ca-dependent inactivation (CDI) function of Ca1.

Topography immune-responsive silk films for skin regeneration.

Scar formation and chronic refractory wounds pose a significant threat to public health, with abnormal immune regulation as a key characteristic. However, topography, a crucial factor influencing immune responses, has not been adequately considered in the design of wound dressings. In this study, we constructed a hierarchical structure on silk fibroin (SF) films by combining soft lithography and femtosecond laser ablation, without altering the intrinsic properties of SF.

Co-culture Model Using Two Types of Adherent Cell Lines.

Embryo implantation is affected by the interactions among different cell types in the mother-embryo interface. The direct and indirect communications between various cell types within the decidua are crucial for regulating endometrial receptivity; however, the molecular mechanisms mediating this interaction are still unclear. In this regard, a model to study the implantation process is needed to establish a comprehensive in vitro model that can recapitulate the biology of endometrial epithelium-stroma interaction.

growth of MnO nanoparticles on supramolecular polyaniline as chiral nanozymes for effective enantioselective catalysis.

growth of MnO nanoparticles (NPs) onto chiral /-polyaniline (/-PANI) scaffolds efficiently regulates the supramolecular chirality, making them function as chiral nanozymes for controllable enantioselective catalysis. Compared with the loaded MnO NPs onto /-PANI scaffolds, the enantioselectivity of the growth system is significantly enhanced due to the stronger bonding between catalytic centers and supramolecular scaffolds.

Vehicular Mini-LED backlight display inspection based on residual global context mechanism.

Mini-LED backlight has emerged as a promising technology for high performance LCDs, yet the massive detection of dead pixels and precise LEDs placement are constrained by the miniature scale of the Mini-LEDs. The high-resolution network (Hrnet) with mixed dilated convolution and dense upsampling convolution (MDC-DUC) module and a residual global context attention (RGCA) module has been proposed to detect the quality of vehicular Mini-LED backlights. The proposed model outperforms the baseline networks of Unet, Pspnet, Deeplabv3+, and Hrnet, with a mean intersection over union (Miou) of 86.

Enhancing Space-Based Tracking of Fossil Fuel CO Emissions via Synergistic Integration of OCO-2, OCO-3, and TROPOMI Measurements.

Top-down estimates of fossil fuel CO (FFCO) emissions are crucial for tracking emissions and evaluating mitigation strategies. However, their practical application is hindered by limited data coverage and overreliance on NOx-to-CO emission ratios from emission inventories. We developed the Machine Learning-Driven Mapping Satellite-based XCO (ML-MSXE) model using the column-averaged dry-air mole fraction of CO enhancement (XCO) derived from OCO-2 and OCO-3 measurements to reconstruct the XCO distribution for monitoring FFCO emissions.

Assessing IgG4-related autoimmune pancreatitis with contrast-enhanced ultrasonography based on time-intensity curve: a single-centre prospective study.

Objectives: The aim of this study was to investigate the changes in various parameters of contrast-enhanced ultrasound (CEUS) before and after treatment in patients with IgG4-related autoimmune pancreatitis (IgG4-AIP), and to identify potential indicators that can assist in evaluating disease activity.

Methods: In this prospective study, we enrolled patients diagnosed with IgG4-AIP from June 2021 to November 2022. Demographic characteristics, clinical features, laboratory tests were recorded.

Machine learning-derived peripheral blood transcriptomic biomarkers for early lung cancer diagnosis: Unveiling tumor-immune interaction mechanisms.

Lung cancer continues to be the leading cause of cancer-related mortality worldwide. Early detection and a comprehensive understanding of tumor-immune interactions are crucial for improving patient outcomes. This study aimed to develop a novel biomarker panel utilizing peripheral blood transcriptomics and machine learning algorithms for early lung cancer diagnosis, while simultaneously providing insights into tumor-immune crosstalk mechanisms.

Decoding Missense Variants by Incorporating Phase Separation via Machine Learning.

Computational models have made significant progress in predicting the effect of protein variants. However, deciphering numerous variants of uncertain significance (VUS) located within intrinsically disordered regions (IDRs) remains challenging. To address this issue, we introduce phase separation, which is tightly linked to IDRs, into the investigation of missense variants.

Associations of Rest-Activity Rhythm Disturbances With Stroke Risk and Poststroke Adverse Outcomes.

Background: Many disease processes are influenced by circadian clocks and display ~24-hour rhythms. Whether disruptions to these rhythms increase stroke risk is unclear. We evaluated the association between 24-hour rest-activity rhythms, stroke risk, and major poststroke adverse outcomes.

Advances in macrophage metabolic reprogramming in myocardial ischemia-reperfusion.

Acute myocardial infarction (AMI) is the leading cause of death worldwide, and reperfusion therapy is a critical therapeutic approach to reduce myocardial ischemic injury and minimize infarct size. However, ischemia/reperfusion (I/R) itself also causes myocardial injury, and inflammation is an essential mechanism by which it leads to myocardial injury, with macrophages as crucial immune cells in this process. Macrophages are innate immune cells that maintain tissue homeostasis, host defence during pathogen infection, and repair during tissue injury.

Limited impact of the sidewall effect in dependence of temperature for InGaN-based blue micro-LEDs grown on a silicon substrate.

The electroluminescence (EL) properties of InGaN-based micro-LEDs grown on a silicon substrate are investigated in this Letter to reveal the dominant mechanism in dependence on different temperatures and dimensions. The invalidation of sidewall nonradiative recombination and the impact of localization-induced carrier tunneling on the external quantum efficiency (EQE) are analyzed systematically to realize high performance silicon-based micro-LEDs. Microscopic EL mapping exhibits that the localized carriers in the silicon-grown micro-LED mainly recombine in the central region of mesa.

A citrullinated antigenic vaccine in treatment of autoimmune arthritis.

Rheumatoid arthritis (RA) is an inflammatory autoimmune disease triggered by antigenic peptides with environmental and genetic risk factors. It has been shown that antigen-specific targeting could be a promising therapeutical strategy for RA by restoring immune tolerance to self-antigens without compromising normal immunity. Citrullination of antigens enhances antigenic properties and induces autoimmune responses.

Analysis of factors influencing pregnancy and its outcomes in women undergoing in vitro fertilization-embryo transfer/frozen embryo transfer cycles: A retrospective study.

The relationship between clinical outcomes and various factors influencing pregnancy was analyzed to provide reference data for patients and clinicians when selecting embryo transfer protocols. This was a retrospective study of 1309 transfer cycles between June 1, 2018, and May 1, 2023, in the Reproductive Medicine Center. Univariate analysis was performed on various factors that may have affected pregnancy outcomes, and further regression analysis was performed on those factors found by univariate analysis to correlate positively with clinical pregnancy outcomes.

Impacts of the Chengdu 2021 world university games on NO pollution: Implications for urban vehicle electrification promotion.

Emissions of nitrogen oxides (NOx) are a dominant contributor to ambient nitrogen dioxide (NO) concentrations, but the quantitative relationship between them at an intracity scale remains elusive. The Chengdu 2021 FISU World University Games (July 22 to August 10, 2023) was the first world-class multisport event in China after the COVID-19 pandemic which led to a substantial decline in NOx emissions in Chengdu. This study evaluated the impact of variations in NOx emissions on NO concentrations at a fine spatiotemporal scale by leveraging this event-driven experiment.

Rheumatoid arthritis patients harbour aberrant enteric bacteriophages with autoimmunity-provoking potential: a paired sibling study.

Objectives: Viruses have been considered as important participants in the development of rheumatoid arthritis (RA). However, the profile of enteric virome and its role in RA remains elusive. This study aimed to investigate the atlas and involvement of virome in RA pathogenesis.

Precise Localization for Anatomo-Physiological Hallmarks of the Cervical Spine by Using Neural Memory Ordinary Differential Equation.

In the evaluation of cervical spine disorders, precise positioning of anatomo-physiological hallmarks is fundamental for calculating diverse measurement metrics. Despite the fact that deep learning has achieved impressive results in the field of keypoint localization, there are still many limitations when facing medical image. First, these methods often encounter limitations when faced with the inherent variability in cervical spine datasets, arising from imaging factors.