Feasibility of a clinical-radiomics combined model to predict the occurrence of stroke-associated pneumonia.

Purpose: To explore the predictive value of radiomics in predicting stroke-associated pneumonia (SAP) in acute ischemic stroke (AIS) patients and construct a prediction model based on clinical features and DWI-MRI radiomics features.

Methods: Univariate and multivariate logistic regression analyses were used to identify the independent clinical predictors for SAP. Pearson correlation analysis and the least absolute shrinkage and selection operator with ten-fold cross-validation were used to calculate the radiomics score for each feature and identify the predictive radiomics features for SAP.

ZCHSound: Open-Source ZJU Paediatric Heart Sound Database With Congenital Heart Disease.

Unlabelled: Congenital heart disease (CHD) is a common birth defect in children. Intelligent auscultation algorithms have been proven to reduce the subjectivity of diagnoses and alleviate the workload of doctors. However, the development of this algorithm has been limited by the lack of reliable, standardized, and publicly available pediatric heart sound databases.

Prediction of recurrent ischaemic stroke using radiomics data and machine learning methods in patients with acute ischaemic stroke: protocol for a multicentre, large sample, prospective observational cohort study in China.

Introduction: Stroke is a leading cause of mortality and disability worldwide. Recurrent strokes result in prolonged hospitalisation and worsened functional outcomes compared with the initial stroke. Thus, it is critical to identify patients who are at high risk of stroke recurrence.

Comparison of the Predictive Value of Inflammatory Biomarkers for the Risk of Stroke-Associated Pneumonia in Patients with Acute Ischemic Stroke.

Purpose: To investigate the predictive value of various inflammatory biomarkers in patients with acute ischemic stroke (AIS) and evaluate the relationship between stroke-associated pneumonia (SAP) and the best predictive index.

Patients And Methods: We calculated the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), prognostic nutritional index (PNI), systemic inflammation response index (SIRI), systemic immune inflammation index (SII), Glasgow prognostic score (GPS), modified Glasgow prognostic score (mGPS), and prognostic index (PI). Variables were selectively included in the logistic regression analysis to explore the associations of NLR, PLR, MLR, PNI, SIRI, SII, GPS, mGPS, and PI with SAP.

A deep learning-based method for pediatric congenital heart disease detection with seven standard views in echocardiography.

Background: With the aggregation of clinical data and the evolution of computational resources, artificial intelligence-based methods have become possible to facilitate clinical diagnosis. For congenital heart disease (CHD) detection, recent deep learning-based methods tend to achieve classification with few views or even a single view. Due to the complexity of CHD, the input images for the deep learning model should cover as many anatomical structures of the heart as possible to enhance the accuracy and robustness of the algorithm.

Prediction of recurrence of ischemic stroke within 1 year of discharge based on machine learning MRI radiomics.

Purpose: This study aimed to investigate the value of a machine learning-based magnetic resonance imaging (MRI) radiomics model in predicting the risk of recurrence within 1 year following an acute ischemic stroke (AIS).

Methods: The MRI and clinical data of 612 patients diagnosed with AIS at the Second Affiliated Hospital of Nanchang University from March 1, 2019, to March 5, 2021, were obtained. The patients were divided into recurrence and non-recurrence groups according to whether they had a recurrent stroke within 1 year after discharge.

Short-term efficacy and safety of personalized antiplatelet therapy for patients with acute ischaemic stroke or transient ischaemic attack: A randomized clinical trial.

Aims: The aim of this study was to determine whether the testing strategy for clopidogrel and/or aspirin resistance using CYP2C19 genotyping or urinary 11-dhTxB2 testing has an impact on clinical outcomes.

Methods: A multicentre, randomized, controlled trial was conducted at 14 centres in China from 2019 to 2021. For the intervention group, a specific antiplatelet strategy was assigned based on the CYP2C19 genotype and 11-dhTxB2, a urinary metabolite of aspirin, and the control group received nonguided (ie, standard of care) treatment.

High-Performance Carbon Nanotube-Based Transient Complementary Electronics.

Transient electronics is an emerging class of electronic devices that can physically degrade or disintegrate after a stable period of service, showing a vast prospect in applications of "green" consumer electronics, hardware-secure devices, medical implants, etc. Complementary metal-oxide-semiconductor (CMOS) technology is dominant in integrated circuit design for its advantages of low static power consumption, high noise immunity, and simple design layout, which also work and are highly preferred for transient electronics. However, the performance of complementary transient electronics is severely restricted by the confined selection of transient materials and compatible fabrication strategies.

Personalized antiplatelet therapy based on clopidogrel/aspirin resistance tests in acute ischemic stroke and transient ischemic attack: Study protocol of a multi-center, single-blinded and randomized controlled trial.

Background: Clopidogrel and aspirin are key intervention for acute ischemic stroke (AIS) and transient ischemic attack (TIA). However, with increased clinical application, many patients have shown clopidogrel resistance (CR) and/or aspirin resistance (AR) that affect antiplatelet therapy on AIS/TIA. At present, there is no research reported on personalized antiplatelet therapy guidelines for patients with CR and/or AR.

A Flexible Integrated Bending Strain and Pressure Sensor System for Motion Monitoring.

Flexible sensors have attracted increasing research interest due to their broad application potential in the fields of human-computer interaction, medical care, sports monitoring, etc. Constructing an integrated sensor system with high performance and being capable of discriminating different stimuli remains a challenge. Here, we proposed a flexible integrated sensor system for motion monitoring that can measure bending strain and pressure independently with a low-cost and simple fabrication process.

Analysis of the spatial association of geographical detector-based landslides and environmental factors in the southeastern Tibetan Plateau, China.

Steep canyons surrounded by high mountains resulting from large-scale landslides characterize the study area located in the southeastern part of the Tibetan Plateau. A total of 1766 large landslides were identified based on integrated remote sensing interpretations utilizing multisource satellite images and topographic data that were dominated by 3 major regional categories, namely, rockslides, rock falls, and flow-like landslides. The geographical detector method was applied to quantitatively unveil the spatial association between the landslides and 12 environmental factors through computation of the q values based on spatially stratified heterogeneity.

Multiaction antibacterial nanofibrous membranes fabricated by electrospinning: an excellent system for antibacterial applications.

In this paper, novel multiaction antibacterial nanofibrous membranes containing apatite, Ag, AgBr and TiO2 as four active components were fabricated by an electrospinning technique. In this antibacterial membrane, each component serves a different function: the hydroxyapatite acts as the adsorption material for capturing bacteria, the Ag nanoparticles act as the release-active antibacterial agent, the AgBr nanoparticles act as the visible sensitive and release-active antibacterial agent, and the TiO2 acts as the UV sensitive antibacterial material and substrate for other functional components. Using E.