Ameliorative effects of Trichosanthes kirilowii Maxim. seed oil on hyperlipidemia rats associated with the regulation of gut microbiology and metabolomics.

The mechanisms underlying the ameliorative effects of polyunsaturated fatty acids (PUFAs) on metabolic disorders induced by a high-fat diet (HFD) remain poorly unclear. In this study, we investigated the anti-hyperlipidemic effects of Trichosanthes kirilowii Maxim. (T.

Gestational diabetes and future cardiovascular diseases: associations by sex-specific genetic data.

Background And Aims: Observational studies have highlighted that gestational diabetes mellitus is associated with a higher risk of cardiovascular diseases, but the causality remains unclear. Herein, the causality between genetic predisposition to gestational diabetes mellitus and the risk of cardiovascular diseases was investigated using sex-specific Mendelian randomization analysis.

Methods: Linkage disequilibrium score regression analysis and two-sample Mendelian randomization analysis were applied to infer the genetic correlation and causality, respectively.

Novel Classification of Cardiovascular Disease Subtypes Reveals Associations Between Mortality and Polyunsaturated Fatty Acids: Insights from the United Kingdom Biobank Study.

Background: Traditional association studies of cardiovascular disease (CVD) categorizations and polyunsaturated fatty acids (PUFAs) yielded conflicting findings. We propose a novel classification system based on fundamental characteristics of cardiovascular patients, such as age, body mass index, waist-hip ratio, to more accurately assess the impact of PUFAs (plasma measures) such as omega (ω)-3 (n-3) and ω-6 on mortality in cardiovascular patients.

Methods: Principal component analysis and -means clustering were used to determine the CVD subtype.

A multimodal physiological and psychological dataset for human with mental stress induced myocardial ischemia.

Accurate differentiation between angina with no obstructive coronary arteries (ANOCA) and mental stress-induced myocardial ischemia (MSIMI) is crucial for tailored treatment strategies, yet public data scarcity hampers understanding. Given the higher incidence of both conditions in women, this study prospectively enrolled 80 female ANOCA and 39 age-matched female controls, subjecting them to three types of mental stress tasks. ECGs were continuously monitored across Rest, Stress, and Recover stages of the mental stress tasks, with PET/CT imaging during the Stress stage to evaluate myocardial perfusion.

Effects of different early cardiac rehabilitation exercise treatments on the prognosis of acute myocardial infarction patients receiving percutaneous coronary intervention.

Objectives: Exercise rehabilitation is the core of Cardiac Rehabilitation (CR) and will improve the prognosis of patients receiving Percutaneous Coronary Intervention (PCI surgery). The current study retrospectively analyzed the effects of different exercise-based CR strategies on the prognosis of AMI patients receiving PCI treatment.

Methods: Clinicopathological information from 127 patients was collected and divided into different groups based on the exercise-based CR received, including Continuous Resistance Exercise (COR), Continuous Aerobic Exercise (COA), Interval Resistance Exercise (IVR), Interval Aerobic Exercise (IVA), Inspiratory Muscle Exercises (ITM), and Control.

Precise detection of awareness in disorders of consciousness using deep learning framework.

Diagnosis of disorders of consciousness (DOC) remains a formidable challenge. Deep learning methods have been widely applied in general neurological and psychiatry disorders, while limited in DOC domain. Considering the successful use of resting-state functional MRI (rs-fMRI) for evaluating patients with DOC, this study seeks to explore the conjunction of deep learning techniques and rs-fMRI in precisely detecting awareness in DOC.

[Longitudinal study on catch-up growth in preterm infants with small for gestational age at corrected ages 0-24 months].

Objectives: To understand the growth and development status and differences between small for gestational age (SGA) and appropriate for gestational age (AGA) preterm infants during corrected ages 0-24 months, and to provide a basis for early health interventions for preterm infants.

Methods: A retrospective study was conducted, selecting 824 preterm infants who received regular health care at the Guangzhou Women and Children's Medical Center from July 2019 to July 2022, including 144 SGA and 680 AGA infants. The growth data of SGA and AGA groups at birth and corrected ages 0-24 months were analyzed and compared.

Association of fresh vegetable and salt-preserved vegetable consumptions with estimated glomerular filtration rate.

Objective: This study aimed to investigate the relationship between the consumption of fresh and salt-preserved vegetables and the estimated glomerular filtration rate (eGFR), which requires further research.

Methods: For this purpose, the data of those subjects who participated in the 2011-2012 and 2014 surveys of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and had biomarker data were selected. Fresh and salt-preserved vegetable consumptions were assessed at each wave.

A cardiologist-like computer-aided interpretation framework to improve arrhythmia diagnosis from imbalanced training datasets.

Arrhythmias can pose a significant threat to cardiac health, potentially leading to serious consequences such as stroke, heart failure, cardiac arrest, shock, and sudden death. In computer-aided electrocardiogram interpretation systems, the inclusion of certain classes of arrhythmias, which we term "aggressive" or "bullying," can lead to the underdiagnosis of other "vulnerable" classes. To address this issue, a method for arrhythmia diagnosis is proposed in this study.

A novel image deep learning-based sub-centimeter pulmonary nodule management algorithm to expedite resection of the malignant and avoid over-diagnosis of the benign.

Objectives: With the popularization of chest computed tomography (CT) screening, there are more sub-centimeter (≤ 1 cm) pulmonary nodules (SCPNs) requiring further diagnostic workup. This area represents an important opportunity to optimize the SCPN management algorithm avoiding "one-size fits all" approach. One critical problem is how to learn the discriminative multi-view characteristics and the unique context of each SCPN.

MRI-based brain age prediction model for children under 3 years old using deep residual network.

Early identification and intervention of abnormal brain development individual subjects are of great significance, especially during the earliest and most active stage of brain development in children aged under 3. Neuroimage-based brain's biological age has been associated with health, ability, and remaining life. However, the existing brain age prediction models based on neuroimage are predominantly adult-oriented.

Diagnosis of generalized joint hypermobility with gait patterns using a deep neural network.

Generalized joint hypermobility (GJH) describes the situation that the range of joint motion exceeds the normal range. GJH is found to increase the risk of knee-related injury and osteoarthritis, challenging the athletic ability of the population. Gait signals are directly related to hip and knee athletic conditions, and have been shown to have significant changes with GJH by our previous research.

The Association between Emergency Department Length of Stay and In-Hospital Mortality in Older Patients Using Machine Learning: An Observational Cohort Study.

The association between emergency department (ED) length of stay (EDLOS) with in-hospital mortality (IHM) in older patients remains unclear. This retrospective study aims to delineate the relationship between EDLOS and IHM in elderly patients. From the ED patients (n = 383,586) who visited an urban academic tertiary care medical center from January 2010 to December 2016, 78,478 older patients (age ≥60 years) were identified and stratified into three age subgroups: 60-74 (early elderly), 75-89 (late elderly), and ≥90 years (longevous elderly).

Combining deep learning and intelligent biometry to extract ultrasound standard planes and assess early gestational weeks.

Objectives: To develop and validate a fully automated AI system to extract standard planes, assess early gestational weeks, and compare the performance of the developed system to sonographers.

Methods: In this three-center retrospective study, 214 consecutive pregnant women that underwent transvaginal ultrasounds between January and December 2018 were selected. Their ultrasound videos were automatically split into 38,941 frames using a particular program.

EBD: an eye biomarker database.

Motivation: Many ophthalmic disease biomarkers have been identified through comprehensive multiomics profiling, and hold significant potential in advancing the diagnosis, prognosis, and management of diseases. Meanwhile, the eye itself serves as a natural biomarker for several systemic diseases including neurological, renal, and cardiovascular systems. We aimed to collect and standardize this eye biomarkers information and construct the eye biomarker database (EBD) to provide ophthalmologists with a platform to search, analyze, and download these eye biomarker data.

Identification of Distinct Clinical Phenotypes of Heterogeneous Mechanically Ventilated ICU Patients Using Cluster Analysis.

This retrospective study aimed to derive the clinical phenotypes of ventilated ICU patients to predict the outcomes on the first day of ventilation. Clinical phenotypes were derived from the eICU Collaborative Research Database (eICU) cohort via cluster analysis and were validated in the Medical Information Mart for Intensive Care (MIMIC-IV) cohort. Four clinical phenotypes were identified and compared in the eICU cohort (n = 15,256).

The predictive value of YAP-1 and POU2F3 for the efficacy of immuno-chemotherapy in extensive-stage SCLC patients.

Introduction: Recently, several clinical trials of immunotherapy for extensive-stage small-cell lung cancer (ES-SCLC) have shown limited benefits because of unselected patients. Thus, we aimed to explore whether YES-associated protein 1 (YAP-1) and POU domain class 2 transcription factor 3 (POU2F3) could identify SCLC patients with durable benefits from immunotherapy as potential biomarkers.

Methods: We performed IHC of YAP-1 and POU2F3, and RNA-seq on tissues of ES- SCLC patients.

New comprehensive reference values for kidney function indexes across adult and geriatric ages in Chinese popuplation.

Background And Aims: China has the largest number of chronic kidney disease (CKD) patients. Current CKD definition has been challenged recently. We aim to reassess kidney function in healthy Chinese population, to provide a more appropriate reference range (RIs) for diagnosis, treatment, monitoring (or screening) of kidney disease and related research.

Tacrolimus in the treatment of childhood nephrotic syndrome: Machine learning detects novel biomarkers and predicts efficacy.

Study Objective: The pharmacokinetics and pharmacodynamics of tacrolimus (TAC) vary greatly among individuals, hindering its precise utilization. Moreover, effective models for the early prediction of TAC efficacy in patients with nephrotic syndrome (NS) are lacking. We aimed to identify key factors affecting TAC efficacy and develop efficacy prediction models for childhood NS using machine learning algorithms.

Quantifying the dynamic transmission of COVID-19 asymptomatic and symptomatic infections: Evidence from four Chinese regions.

The dynamic transmission of asymptomatic and symptomatic COVID-19 infections is difficult to quantify because asymptomatic infections are not readily recognized or self-identified. To address this issue, we collected data on asymptomatic and symptomatic infections from four Chinese regions (Beijing, Dalian, Xinjiang, and Guangzhou). These data were considered reliable because the government had implemented large-scale multiple testing during the outbreak in the four regions.

Correction: SARS-CoV-2 infection in China-Before the pandemic.

[This corrects the article DOI: 10.1371/journal.pntd.