Correlation between abnormal microvascular perfusion and quantitative flow ratio after primary PCI in patients with STEMI.

Aims: Timely assessment of abnormal microvascular perfusion (MVP) may improve prognosis in patients with ST-segment elevation myocardial infarction (STEMI). This study aimed to determine the clinical implications of contrast-flow quantitative flow ratio (cQFR) in evaluating abnormal MVP and subsequent outcomes among STEMI patients after successful primary percutaneous coronary intervention (PPCI).

Methods: The study population consisted of 2 independent cohorts.

Spatio-temporal envolutional graph neural network for traffic flow prediction in UAV-based urban traffic monitoring system.

With the advancement of modern UAV technology, UAVs have become integral to creating traffic management monitoring systems. Additionally, UAV-based traffic monitoring systems can predict traffic flow by integrating machine learning methods. Specifically, traffic flow data contains both spatial and temporal information, which can be effectively processed by graph neural networks (GNNs).

Electrochemical behavior and reaction mechanism of nano-BiOBr/rGO composite micro flower with strong interface coupling as potassium-ion battery anodes.

To explore the potential of bismuth oxybromide (BiOBr) as anodes for high-performance potassium (K)-ion batteries and understand its potassium storage mechanism, a novel nano-BiOBr/reduced graphene oxide (rGO) composite micro flower (labelled as SI-coupled nano-BiOBr/rGO micro flower), where nano-BiOBr slices are firmly anchored on rGO by strong interface coupling, is constructed. Unique microstructure accompanied by C-Bi bonds at the interface between BiOBr and rGO endows it with abundant high-speed charge transfer channels and excellent structural stability. As a result, it exhibits an excellent rate performance (a high reversible capacity of 278 mAh/g at 5 A/g) and a remarkable long-term cycling stability maintaining 95.

Enhancing precision in effective regurgitant orifice area estimation by transthoracic echocardiography for functional mitral regurgitation using computational fluid dynamics.

Computational fluid dynamics (CFD) was used to identify factors influencing the accuracy of the hemispherical proximal isovelocity surface area (PISA) method in calculating the effective regurgitant orifice area (EROA) for patients with functional mitral regurgitation (FMR). Ninety-nine CFD models were constructed to investigate the impact of regurgitant orifice shape and leaflet tethering on the EROA calculation using the PISA method. The correction factors for regurgitation orifice shape (CFs) and for leaflet tethering (CFt) were derived by comparing the 2D PISA method and the actual orifice area.

Adaptive Decision Spatio-temporal neural ODE for traffic flow forecasting with Multi-Kernel Temporal Dynamic Dilation Convolution.

Traffic flow prediction is crucial for efficient traffic management. It involves predicting vehicle movement patterns to reduce congestion and enhance traffic flow. However, the highly non-linear and complex patterns commonly observed in traffic flow pose significant challenges for this task.

Nutrition-Related Knowledge Graph Neural Network for Food Recommendation.

Food recommendation systems are becoming increasingly vital in modern society, given the fast-paced lifestyle and diverse dietary habits. Existing research and implemented solutions often rely on user preferences and past behaviors for recommendations, which poses significant issues. Firstly, this approach inadequately considers the nutritional content of foods, potentially leading to recommendations that are overly homogeneous and lacking in diversity.

Smart Biosensor for Breast Cancer Survival Prediction Based on Multi-View Multi-Way Graph Learning.

Biosensors play a crucial role in detecting cancer signals by orchestrating a series of intricate biological and physical transduction processes. Among various cancers, breast cancer stands out due to its genetic underpinnings, which trigger uncontrolled cell proliferation, predominantly impacting women, and resulting in significant mortality rates. The utilization of biosensors in predicting survival time becomes paramount in formulating an optimal treatment strategy.

Mental Stress-Induced Myocardial Ischemia Detected by Global Longitudinal Strain and Quantitative Myocardial Contrast Echocardiography in Women With Nonobstructive Coronary Artery Disease.

Background: The utility of radionuclide myocardial perfusion imaging including positron emission tomography (PET) for diagnosing mental stress-induced myocardial ischemia (MSIMI) is clinically restricted. This study aims to assess the diagnostic performance of novel echocardiographic techniques, including automated strain and quantitative myocardial contrast echocardiography (MCE) with dedicated software and deep neural network model, for MSIMI detection. The secondary objective was to explore the correlation between changes in myocardial blood flow and MSIMI.

Non-Contact Heart Rate Monitoring Method Based on Wi-Fi CSI Signal.

This paper introduces an innovative non-contact heart rate monitoring method based on Wi-Fi Channel State Information (CSI). This approach integrates both amplitude and phase information of the CSI signal through rotational projection, aiming to optimize the accuracy of heart rate estimation in home environments. We develop a frequency domain subcarrier selection algorithm based on Heartbeat to subcomponent ratio (HSR) and design a complete set of signal filtering and subcarrier selection processes to further enhance the accuracy of heart rate estimation.

Dissecting the chiral recognition of TLR4/MD2 with Neoseptin-3 enantiomers by molecular dynamics simulations.

Toll-like receptor 4 (TLR4) is a pivotal innate immune recognition receptor that regulates intricate signaling pathways within the immune system. Neoseptin-3 (Neo-3), a recently identified small-molecule agonist for mouse TLR4/MD2, exhibits chiral recognition properties. Specifically, the L-enantiomer of Neo-3 (L-Neo-3) effectively activates the TLR4 signaling pathway, while D-Neo-3 fails to induce TLR4 activation.

Per- and polyfluoroalkyl substances in waterbird feathers around Poyang Lake, China: Compound and species-specific bioaccumulation.

As a nondestructive means of environmental monitoring, bird feathers have been used to analyze levels of per- and polyfluoroalkyl substances (PFASs) in specific environments. In this study, feather samples from 10 waterbird species around Poyang Lake were collected, and a pretreatment method for PFASs in feathers was optimized. The results showed that a combined cleaning method using ultrapure water and n-hexane effectively removed external PFASs.

Numerical modeling of the effects of the shape and aspect ratio of 3D curved fiber on the percolation threshold and electrical conductivity of conductive polymer composites.

For designing conductive polymer composites (CPCs), understanding how the fiber curvature affects the percolation behavior of curved conductive fibers is essential for determining the effective electrical conductivity of the CPCs. In this work, CPCs were considered as a polymer matrix filled with the random packing of overlapped curved spherocylinders. The geometries of the curved spherocylinders were defined, and inter-curved spherocylinder contact-detecting and system-spanning fiber cluster searching algorithms were developed.

Routing Selection Algorithm for Mobile Ad Hoc Networks Based on Neighbor Node Density.

In the process of data transmission in mobile ad hoc networks, it is essential to establish optimal routes from source nodes to destination nodes. However, as network density increases, this process is often accompanied by a significant rise in network overhead. To address this issue, the ND-AODV (neighborhood density AODV) protocol has been introduced, which reduces the probability of transmitting control information in high-density node environments to mitigate network overhead.

A new mechanistic insight into the association between environmental perfluorooctane sulfonic acid (PFOS) exposure and attention deficit and hyperactivity disorder (ADHD)-like behavior.

Perfluorooctane sulfonic acid (PFOS) is one of the main residual environmental pollutants that threaten human health. PFOS exposure is positively correlated with the prevalence of attention deficit hyperactivity disorder (ADHD); however, the underlying mechanism is unknown. Given that dopamine (DA) is a crucial target for PFOS and that its dysfunction is a key role in ADHD development, it is speculated that PFOS exposure contributes to the occurrence of ADHD to some extent by disrupting DA homeostasis.

Percolation threshold and electrical conductivity of conductive polymer composites filled with curved fibers in two-dimensional space.

Quantifying the influence of fiber curvature on the percolation behavior of flexible conductive fiber and further on the electrical conductivity of conductive polymer composites (CPCs) is crucial for the design of CPCs. This study considers CPCs as a random packing of soft curved discorectangles (CDCRs) in a polymer matrix. The geometry of CDCR is developed, and an inter-CDCR contact detection algorithm is used to generate a random packing structure of CDCRs.

Novel PFOS alternative OBS inhibits body growth of developing zebrafish by triggering thyroid function disorder and osteoclast differentiation.

The extensive use of the perfluorooctane sulfonate (PFOS) alternative sodium p-perfluorous nonenoxybenzene sulfonate (OBS) has resulted in its widespread detection in the environment and enrichment in wildlife and humans. However, little is known about its potential toxicity, particularly in terms of body development. In this study, zebrafish embryos were acutely exposed to PFOS and OBS for a comparative developmental toxicity assessment.

Automatic Myocardial Contrast Echocardiography Image Quality Assessment Using Deep Learning: Impact on Myocardial Perfusion Evaluation.

Objective: The image quality of myocardial contrast echocardiography (MCE) is critical for precise myocardial perfusion evaluation but challenging for echocardiographers. Differences in quality may lead to diagnostic heterogeneity. This study was aimed at achieving automatic MCE image quality assessment using a deep neural network (DNN) and investigating its impact on myocardial perfusion evaluation.

Application of Deep Learning Algorithm to Monitor Upper Extremity Task Practice.

Upper extremity hemiplegia is a serious problem affecting the lives of many people post-stroke. Motor recovery requires high repetitions and quality of task-specific practice. Sufficient practice cannot be completed during therapy sessions, requiring patients to perform additional task practices at home on their own.

The Effects Analysis of Contact Stiffness of Double-Row Tapered Roller Bearing under Composite Loads.

Double-row tapered roller bearings have been widely used in various equipment recently due to their compact structure and ability to withstand large loads. The dynamic stiffness is composed of contact stiffness, oil film stiffness and support stiffness, and the contact stiffness has the most significant influence on the dynamic performance of the bearing. There are few studies on the contact stiffness of double-row tapered roller bearings.

Synthesis of Sb-pyromellitic acid metal-organic framework material and its sodium storage properties.

Developing electrode materials with high capacity and low cost is crucial for promoting the application of sodium-ion batteries. In this paper, a new Sb-PMA-300 metal-organic framework (MOF) material is synthesized by chelation of Sb and pyromellitic acid (PMA) followed by a heat treatment at 300 °C. As anodes for sodium-ion batteries, the Sb-PMA-300 composite exhibits a stable capacity of 443 mA h g at a current density of 0.

A novel risk stratification model for STEMI after primary PCI: global longitudinal strain and deep neural network assisted myocardial contrast echocardiography quantitative analysis.

Background: In ST-segment elevation myocardial infarction (STEMI) with the restoration of TIMI 3 flow by percutaneous coronary intervention (PCI), visually defined microvascular obstruction (MVO) was shown to be the predictor of poor prognosis, but not an ideal risk stratification method. We intend to introduce deep neural network (DNN) assisted myocardial contrast echocardiography (MCE) quantitative analysis and propose a better risk stratification model.

Methods: 194 STEMI patients with successful primary PCI with at least 6 months follow-up were included.