Association of hyperuricemia with coronary heart disease: Protocol for an updated systematic review and dose-response meta-analysis.

Introduction: Hyperuricemia, characterized by elevated serum uric acid levels, has garnered significant attention in cardiovascular research due to its potential association with coronary heart disease (CHD). While some studies suggest hyperuricemia as a risk factor of CHD, others present conflicting findings. A systematic review and dose-response meta-analysis is warranted to comprehensively summarize the previous studies and determine the association between hyperuricemia and CHD, thereby supporting clinical practice and future studies in this field.

The role of coffee and potential mediators in subclinical atherosclerosis: insights from Mendelian randomization study.

Background And Aims: Coffee contains many bioactive compounds, and its inconsistent association with subclinical atherosclerosis has been reported in observational studies. In this Mendelian randomization study, we investigated whether genetically predicted coffee consumption is associated with subclinical atherosclerosis, as well as the role of potential mediators.

Methods: We first conducted a two-sample Mendelian randomization analysis to examine the causal effect of coffee and its subtypes on subclinical atherosclerosis inferred from coronary artery calcification (CAC).

Deep learning-based differentiation of ventricular septal defect from tetralogy of Fallot in fetal echocardiography images.

Background: Congenital heart disease (CHD) seriously affects children's health and quality of life, and early detection of CHD can reduce its impact on children's health. Tetralogy of Fallot (TOF) and ventricular septal defect (VSD) are two types of CHD that have similarities in echocardiography. However, TOF has worse diagnosis and higher morality than VSD.

Anemia in Heart Failure: A Perspective from 20-Year Bibliometric Analysis.

Background & Objective: Anemia in patients with heart failure (HF) is a growing concern. However, there has no bibliometric analysis in this area up to now. The aim of this study is to explore the status and trends in the field of anemia in HF through the bibliometric analysis, and to provide an outlook on future research.

Design and Implementation of a Four-Unit Array Piezoelectric Bionic MEMS Vector Hydrophone.

High-performance vector hydrophones have been gaining attention for underwater target-monitoring applications. Nevertheless, there exists the mutual constraint between sensitivity and bandwidth of a single hydrophone. To solve this problem, a four-unit array piezoelectric bionic MEMS vector hydrophone (FPVH) was developed in this paper, which has a cross-beam and a bionic fish-lateral-line-nerve-cell-cilia unit array structure.

Deep learning-based anatomical position recognition for gastroscopic examination.

Background: The gastroscopic examination is a preferred method for the detection of upper gastrointestinal lesions. However, gastroscopic examination has high requirements for doctors, especially for the strict position and quantity of the archived images. These requirements are challenging for the education and training of junior doctors.

Gas-Sensing Properties and Mechanisms of 3D Networks Composed of ZnO Tetrapod Micro-Nano Structures at Room Temperature.

Metal oxide semiconductors (MOSs) hold great promise for electronic devices such as gas sensors. The utilization of ZnO as a conductometric gas sensor material can be traced back to its early stages; however, its application has primarily been limited to high-temperature environments. A gas sensor based on highly porous and interconnected 3D networks of ZnO tetrapod (ZnO-T) micro-nano structures was fabricated via an easy chemical vapor deposition (CVD) method.

The impact of the time factors on the exercise-based cardiac rehabilitation outcomes of the patients with acute myocardial infarction after percutaneous coronary intervention: a systematic review and meta-analysis.

Background And Objective: Cardiac rehabilitation (CR) has been demonstrated to improve outcomes in patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI). However, the optimal CR initiation time and duration remain to be determined. This study aimed to explore the impact of the time factors on the CR outcomes in AMI patients who received PCI by the method of meta-regression analysis.

Molecular targets and mechanisms of Guanxinning tablet in treating atherosclerosis: Network pharmacology and molecular docking analysis.

Background: Guanxinning tablet (GXNT), a Chinese patent medicine, is composed of salvia miltiorrhiza bunge and ligusticum striatum DC, which may play the role of endothelial protection through many pathways. We aimed to explore the molecular mechanisms of GXNT against atherosclerosis (AS) through network pharmacology and molecular docking verification.

Methods: The active ingredients and their potential targets of GXNT were obtained in traditional Chinese medicine systems pharmacology database and analysis platform and bioinformatics analysis tool for molecular mechanism of traditional Chinese medicine databases.

High-Sensitivity Piezoelectric MEMS Accelerometer for Vector Hydrophones.

In response to the growing demand for high-sensitivity accelerometers in vector hydrophones, a piezoelectric MEMS accelerometer (PMA) was proposed, which has a four-cantilever beam integrated inertial mass unit structure, with the advantages of being lightweight and highly sensitive. A theoretical energy harvesting model was established for the piezoelectric cantilever beam, and the geometric dimensions and structure of the microdevice were optimized to meet the vibration pickup conditions. The sol-gel and annealing technology was employed to prepare high-quality PZT thin films on silicon substrate, and accelerometer microdevices were manufactured by using MEMS technology.

Evaluation of deep learning methods for early gastric cancer detection using gastroscopic images.

Background: A timely diagnosis of early gastric cancer (EGC) can greatly reduce the death rate of patients. However, the manual detection of EGC is a costly and low-accuracy task. The artificial intelligence (AI) method based on deep learning is considered as a potential method to detect EGC.

Deep learning for differentiating benign from malignant tumors on breast-specific gamma image.

Background: Breast diseases are a significant health threat for women. With the fast-growing BSGI data, it is becoming increasingly critical for physicians to accurately diagnose benign as well as malignant breast tumors.

Objective: The purpose of this study is to diagnose benign and malignant breast tumors utilizing the deep learning model, with the input of breast-specific gamma imaging (BSGI).

Emerging trends and hotspots evolution in cardiotoxicity: A bibliometric and knowledge-Map analysis From 2010 to 2022.

Background: There is growing emphasis on the cardiotoxicity research over the past 12 years. To look for the hotspots evolution and to explore the emerging trends in the field of cardiotoxicity, publications related to cardiotoxicity were acquired from the Web of Science Core Collection on August 2, 2022.

Methods: We used the CiteSpace 5.

Bioresorbable scaffolds vs. drug-eluting stents for patients with myocardial infarction: A systematic review and meta-analysis of randomized clinical trials.

Objective: To compare the efficacy and safety of bioresorbable scaffolds (BRS) with drug-eluting stents (DES) in patients with myocardial infarction undergoing percutaneous coronary interventions (PCI).

Methods: We performed a systematic review and meta-analysis of randomized controlled trials (RCTs) comparing BRS with DES on clinical outcomes with at least 12 months follow-up. Electronic databases of PubMed, CENTRAL, EMBASE, and Web of Science from inception to 1 March 2022 were systematically searched to identify relevant studies.

Fatigue Fracture Analysis on 2524 Aluminum Alloy with the Influence of Creep-Aging Forming Processes.

The different creep-aging forming processes of 2524 aluminum alloy were taken as the research object, and the effects of creep-aging temperature and creep stress on the fatigue-crack propagation properties of the alloy were studied. The research results showed the following under the same sintering time of 9 h, at creep-aging temperatures of 100 °C, 130 °C, 160 °C, and 180 °C, respectively, with an increase in creep-aging temperature: the fatigue-crack propagation rate was promoted, the spacing of fatigue striations increased, and the sizes of dimples decreased while the number was enlarged; this proves that the fatigue property of the alloy was weakened. Compared with the specimens with creep deformation radii of 1000 mm and 1500 mm, the creep deformation stress was the smallest when the forming radius was 1800 mm, with a higher threshold value of fatigue-crack growth in the near-threshold region of fatigue-crack propagation (Δ ≤ 8 MPa·m).

Elastography ultrasound with machine learning improves the diagnostic performance of traditional ultrasound in predicting kidney fibrosis.

Background: Noninvasively predicting kidney tubulointerstitial fibrosis is important because it's closely correlated with the development and prognosis of chronic kidney disease (CKD). Most studies of shear wave elastography (SWE) in CKD were limited to non-linear statistical dependencies and didn't fully consider variables' interactions. Therefore, support vector machine (SVM) of machine learning was used to assess the prediction value of SWE and traditional ultrasound techniques in kidney fibrosis.

Effect of Pressure and Temperature on Densification in Electric Field-Assisted Sintering of Inconel 718 Superalloy.

Electric field-assisted sintering has ubiquitous merits over conventional sintering technology for the fabrication of difficult-to-deform materials. To investigate the effect of sintering pressure and temperature on the densification of Inconel 718 superalloy, a numerical simulation model was established based on the Fleck-Kuhn-McMeeking (FKM) and Gurson-Tvergaard-Needleman (GTN) models, which covers a wide range of porosity. At a sintering pressure below 50 MPa or a sintering temperature below 950 °C, the average porosity of the sintered superalloy is over 0.

The efficacy and safety of acupuncture for patients with post-percutaneous coronary intervention depression: A protocol for systematic review and meta analysis.

Background: Percutaneous coronary intervention (PCI) has been increasingly applied as an effective revascularization strategy in patients with coronary artery disease (CAD). However, recent studies had indicated a higher incidence of depression on post-PCI patients. Acupuncture therapy is effective for depression.

Full three-dimensional segmentation and quantification of tumor vessels for photoacoustic images.

Quantitative analysis of tumor vessels is of great significance for tumor staging and diagnosis. Photoacoustic imaging (PAI) has been proven to be an effective way to visualize comprehensive tumor vascular networks in three-dimensional (3D) volume, while previous studies only quantified the vessels projected in one plane. In this study, tumor vessels were segmented and quantified in a full 3D framework.

Diagnosis of Renal Diseases Based on Machine Learning Methods Using Ultrasound Images.

Background: The incidence rate of renal disease is high, which can cause end-stage renal disease. Ultrasound is a commonly used imaging method, including conventional ultrasound, color ultrasound, elastography, etc. Machine learning is a potential method which has been widely used in clinical practices.

Detection of Thyroid Nodules with Ultrasound Images Based on Deep Learning.

Background: Thyroid nodules are a common clinical entity with high incidence. Ultrasound is often employed to detect and evaluate thyroid nodules. The development of an efficient automated method to detect thyroid nodules using ultrasound has the potential to reduce both physician workload and operator-dependence.

Thyroid Diagnosis from SPECT Images Using Convolutional Neural Network with Optimization.

Thyroid disease has now become the second largest disease in the endocrine field; SPECT imaging is particularly important for the clinical diagnosis of thyroid diseases. However, there is little research on the application of SPECT images in the computer-aided diagnosis of thyroid diseases based on machine learning methods. A convolutional neural network with optimization-based computer-aided diagnosis of thyroid diseases using SPECT images is developed.

New locus reveals the genetic architecture of sex reversal in the Chinese tongue sole (Cynoglossus semilaevis).

Sex reversal in insects, amphibians, reptiles, and fishes is a complicated and interesting biological phenomenon. Sex reversal changes the sex ratio of populations and may complicate breeding schemes. In the Chinese tongue sole (Cynoglossus semilaevis), genetic females may change into pseudomales, thereby increasing aquaculture costs because of the lower growth rate of the males than that of the females.

A Volterra series-based method for extracting target echoes in the seafloor mining environment.

The purpose of this research was to evaluate the applicability of the Volterra adaptive method to predict the target echo of an ultrasonic signal in an underwater seafloor mining environment. There is growing interest in mining of seafloor minerals because they offer an alternative source of rare metals. Mining the minerals cause the seafloor sediments to be stirred up and suspended in sea water.

Cavitation erosion mechanism of titanium alloy radiation rods in aluminum melt.

Ultrasound radiation rods play a key role in introducing ultrasonic to the grain refinement of large-size cast aluminum ingots (with diameter over 800 mm), but the severe cavitation corrosion of radiation rods limit the wide application of ultrasonic in the metallurgy field. In this paper, the cavitation erosion of Ti alloy radiation rod (TARR) in the semi-continuous direct-chill casting of 7050 Al alloy was investigated using a 20 kHz ultrasonic vibrator. The macro/micro characterization of Ti alloy was performed using an optical digital microscopy and a scanning electron microscopy, respectively.