An interpretable machine learning-assisted diagnostic model for Kawasaki disease in children.

Kawasaki disease (KD) is a syndrome of acute systemic vasculitis commonly observed in children. Due to its unclear pathogenesis and the lack of specific diagnostic markers, it is prone to being confused with other diseases that exhibit similar symptoms, making early and accurate diagnosis challenging. This study aimed to develop an interpretable machine learning (ML) diagnostic model for KD.

Rapid and accurate detection of f. sp. Lycopersici using one-pot, one-step LAMP-CRISPR/Cas12b method.

Introduction: f. sp. (Fol) is one of the most devastating plant pathogenic fungi, the causal agent of root rot for tractylides macrocephala Koidz (AMK).

Atractylenolide II combined with Interferon-γ synergistically ameliorates colorectal cancer progression and by blocking the NF-kB p65/PD-L1 pathway.

Koidz is a widely used classical traditional Chinese herbal medicine, that has shown remarkable efficacy in cancers. Colorectal cancer (CRC) is the most common malignant tumor globally. Interferon (IFN)-γ, a prominent cytokine involved in anti-tumor immunity that has cytostatic, pro-apoptotic, and immune-stimulatory properties for the detection and removal of transformed cells.

The association between renal pelvis urine density and the risk of severe infectious complications in patient with symptom-free hydronephrosis after shock wave lithotripsy: a multi-center prospective study.

Finding reliable and easy-to-obtain predictors of severe infectious complications after shock wave lithotripsy (SWL) is a major clinical need, particular in symptom-free hydronephrosis. Therefore, we aim to prospectively investigate the predictive value of Hounsfield units (HU) in renal pelvis urine for the risk of severe infectious complications in patients with ureteral stones and symptom-free hydronephrosis after SWL. This multi-center prospective study was conducted from June 2020 to December 2023.

Machine Learning-Based Approach to Predict Last-Minute Cancellation of Pediatric Day Surgeries.

The last-minute cancellation of surgeries profoundly affects patients and their families. This research aimed to forecast these cancellations using EMR data and meteorological conditions at the time of the appointment, using a machine learning approach. We retrospectively gathered medical data from 13 440 pediatric patients slated for surgery from 2018 to 2021.

Continuous age- and sex-specific reference ranges of liver enzymes in Chinese children and application in pediatric non-alcoholic fatty liver disease.

Background: Alanine aminotransferase (ALT) is widely used to screen patients with hepatic diseases. However, the current reference ranges (< 50 U/L) were developed by laboratories and have not been validated in populations with a large number of healthy individuals.

Methods: This study collected venous blood and anthropometric data from a total of 13,287 healthy children aged 3 months to 18 years who underwent routine physical examinations in the Department of Pediatric Healthcare.

Scutellarin Alleviates Diabetic Retinopathy via the Suppression of Nucleotide-Binding Oligomerization Domain (NOD)-Like Receptor Pyrin Domain Containing Protein 3 Inflammasome Activation.

Purpose: Diabetic retinopathy, a prevalent complication of diabetes, represents the leading cause of vision loss and blindness among middle-aged and elderly populations. Recent research has demonstrated the ameliorating effects of scutellarin on diabetes-associated complications such as diabetic retinopathy and type 2 diabetic cardiomyopathy. However, investigations into its protective impact and underlying mechanisms on diabetic retinopathy are scant.

Total Glucosides of Paeony Ameliorate Myocardial Injury in Chronic Heart Failure Rats by Suppressing PARP-1.

Total glucosides of paeony (TGP) have a potential protective effect on chronic heart failure (CHF) rats, but the mechanism remains unclear. PARP inhibition prevents the decrease in myocardial contractility. Therefore, we aim to investigate the effects and mechanisms of TGP on CHF and the role of PARP-1 in CHF.

Analyzing and Forecasting Pediatric Fever Clinic Visits in High Frequency Using Ensemble Time-Series Methods After the COVID-19 Pandemic in Hangzhou, China: Retrospective Study.

Background: The COVID-19 pandemic has significantly altered the global health and medical landscape. In response to the outbreak, Chinese hospitals have established 24-hour fever clinics to serve patients with COVID-19. The emergence of these clinics and the impact of successive epidemics have led to a surge in visits, placing pressure on hospital resource allocation and scheduling.

The potential effect of salvianolic acid B against rat ischemic brain injury in combination with mesenchymal stem cells.

Background: Mesenchymal stem cells (MSCs) and Salvianolic acid B (SAB) are known to exert potent anti-inflammatory and anti-oxidative properties. But the effect of SAB and MSCs combination treatment on the cerebral ischemia/reperfusion injury (CI/RI) is not clear.

Methods: After the CI/RI animal model established, rats were administered with MSCs and SAB individually or combination treatment.

M2 tumor-associated macrophage promoted DNA methylation in lung cancer metastasis via intensifying EZH2.

This study aimed to explore the interaction between the tumor-associated macrophage (TAM) and enhancer of zeste homolog 2 (EZH2) in tumor microenvironment of lung cancer are obscure. M2 type of TAM was induced by interleukin-4 (IL-4) and interleukin-13 (IL-13) in RAW264.7 cells.

The influence of media use degree on public depressive symptoms: mediating role of big five personality.

Background: Mixed results have been found regarding the relationship between media use degree and depressive symptoms. The purpose of this study is to explore the relationship between media use degree, big five personality and depressive symptoms with a mediation model.

Method: This was a cross-sectional study.

Development of lung segmentation method in x-ray images of children based on TransResUNet.

Background: Chest x-ray (CXR) is widely applied for the detection and diagnosis of children's lung diseases. Lung field segmentation in digital CXR images is a key section of many computer-aided diagnosis systems.

Objective: In this study, we propose a method based on deep learning to improve the lung segmentation quality and accuracy of children's multi-center CXR images.

Cytocompatibility of TiCT MXene with Red Blood Cells and Human Umbilical Vein Endothelial Cells and the Underlying Mechanisms.

Two-dimensional (2D) nanomaterials have been widely used in biomedical applications because of their biocompatibility. Considering the high risk of exposure of the circulatory system to TiCT, we studied the cytocompatibility of TiCT MXene with red blood cells (RBCs) and human umbilical vein endothelial cells (HUVECs) and showed that TiCT had excellent compatibility with the two cell lines. TiCT at a concentration as high as 200 μg/mL caused a negligible percent hemolysis of 0.

Artesunate Alleviates Hyperoxia-Induced Lung Injury in Neonatal Mice by Inhibiting NLRP3 Inflammasome Activation.

Bronchopulmonary dysplasia (BPD) is a chronic respiratory disease in preterm infants that may cause persistent lung injury. Artesunate exhibits excellent anti-inflammatory in lung injury caused by various factors. This study aimed to investigate the effect of the artesunate on hyperoxia-induced lung injury in neonatal mice and its mechanism.

Pressure Drop Performance of Porous Composites Based on Cotton Cellulose Nanofiber and Aramid Nanofiber for Cigarette Filter Rod.

Porous composites have been widely used in the adsorption and catalysis field due to their special structure, abundant sites, and light weight. In this work, an environmentally friendly porous composite was successfully prepared via a facile freeze-drying method, in which cotton cellulose nanofiber (CCNF) was adopted as the main framework to construct the connected flue structure, and aramid nanofiber (ANF) was used as a reinforcer to enhance its thermal property. As-prepared porous materials retained a regulated inter-connected hole structure and controllable porosity after ice template evolution and possessed improved resistance to thermal collapse with the introduction of a small amount of aramid nanofiber, as evaluated and verified by FTIR, SEM, and TGA measurements.

Research on CT Lung Segmentation Method of Preschool Children based on Traditional Image Processing and ResUnet.

Lung segmentation using computed tomography (CT) images is important for diagnosing various lung diseases. Currently, no lung segmentation method has been developed for assessing the CT images of preschool children, which may differ from those of adults due to (1) presence of artifacts caused by the shaking of children, (2) loss of a localized lung area due to a failure to hold their breath, and (3) a smaller CT chest area, compared with adults. To solve these unique problems, this study developed an automatic lung segmentation method by combining traditional imaging methods with ResUnet using the CT images of 60 children, aged 0-6 years.

Alliance chain-based simulation on a new clinical research data pricing model.

Background: Multicenter clinical research faces many challenges, including how to quantitatively evaluate the data contribution of each research center. However, few data pricing model meets the requirements to the scenario. Thus, a suitable mechanism to measure the data value for clinical research is required.

Performance of Deep Learning-Based Algorithm for Detection of Pediatric Intussusception on Abdominal Ultrasound Images.

Background And Aims: Diagnosing pediatric intussusception from ultrasound images can be a difficult task in many primary care hospitals that lack experienced radiologists. To address this challenge, this study developed an artificial intelligence- (AI-) based system for automatic detection of "concentric circles" signs on ultrasound images, thereby improving the efficiency and accuracy of pediatric intussusception diagnosis.

Methods: A total of 440 cases (373 pediatric intussusception and 67 normal cases) were retrospectively collected from Children's Hospital affiliated to Zhejiang University School of Medicine from January 2020 to December 2020.

An intelligent prediagnosis system for disease prediction and examination recommendation based on electronic medical record and a medical-semantic-aware convolution neural network (MSCNN) for pediatric chronic cough.

Background: Due to the phenotypic similarities among different pediatric respiratory diseases with chronic cough, primary doctors often misdiagnose and the misuse of examinations is prevalent. In the pre-diagnosis stage, the patients' chief complaints and other information in the electronic medical record (EMR) provide a powerful reference for respiratory experts to make preliminary disease judgment and examination plan. In this paper, we proposed an intelligent prediagnosis system to predict disease diagnosis and recommend examinations based on EMR text.

Baicalin Inhibits Inflammation in Rats with Chronic Obstructive Pulmonary Disease by the TLR2/MYD88/NF-Bp65 Signaling Pathway.

Objective: Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disease with a relatively high morbidity and death rate. This study aimed to investigate the inhibitory effect of baicalin (BA) on inflammation in COPD rats and its possible mechanism.

Methods: The experimental COPD of SD rats were induced by LPS, smoking, and cold stimulation, and they were randomly divided into the control group, COPD group, COPD + LB group, COPD + MB group, and COPD + HB group.

Detection of Diseases Using Machine Learning Image Recognition Technology in Artificial Intelligence.

With the continuous development and improvement of artificial intelligence technology, machine learning technology has also been extensively developed, which has promoted the development of computer vision, image processing, natural language processing, and other fields. . This article aims to apply the image processing technology based on machine learning in the detection of childhood diseases and propose the application of image processing technology to the detection of childhood diseases.

Integrated Analysis of miRNA and mRNA Expression Profiles Reveals the Molecular Mechanism of Posttraumatic Stress Disorder and Therapeutic Drugs.

Purpose: Post-traumatic stress disorder (PTSD) is a result of trauma exposure and is related to psychological suffering as a long-lasting health issue. Further analysis of the networks and genes involved in PTSD are critical to the molecular mechanisms of PTSD.

Methods: In this study, we aimed to identify key genes and molecular interaction networks involved in the pathogenesis of PTSD by integrating mRNA and miRNA data.