Development and validation of machine learning-augmented algorithm for insulin sensitivity assessment in the community and primary care settings: a population-based study in China.

Objective: Insulin plays a central role in the regulation of energy and glucose homeostasis, and insulin resistance (IR) is widely considered as the "common soil" of a cluster of cardiometabolic disorders. Assessment of insulin sensitivity is very important in preventing and treating IR-related disease. This study aims to develop and validate machine learning (ML)-augmented algorithms for insulin sensitivity assessment in the community and primary care settings.

Framingham risk score conventional risk factors are potent to predict all-cause mortality using machine learning algorithms: a population-based prospective cohort study over 40 years in China.

Predicting all-cause mortality using available or conveniently modifiable risk factors is potentially crucial in reducing deaths precisely and efficiently. Framingham risk score (FRS) is widely used in predicting cardiovascular diseases, and its conventional risk factors are closely pertinent to deaths. Machine learning is increasingly considered to improve the predicting performances by developing predictive models.

Predictive modeling the probability of suffering from metabolic syndrome using machine learning: A population-based study.

Background: There is an increasing trend of Metabolic syndrome (MetS) prevalence, which has been considered as an important contributor for cardiovascular disease (CVD), cancers and diabetes. However, there is often a long asymptomatic phase of MetS, resulting in not diagnosed and intervened so timely as needed. It would be very helpful to explore tools to predict the probability of suffering from MetS in daily life or routinely clinical practice.

Development and validation of a machine learning-augmented algorithm for diabetes screening in community and primary care settings: A population-based study.

Background: Opportunely screening for diabetes is crucial to reduce its related morbidity, mortality, and socioeconomic burden. Machine learning (ML) has excellent capability to maximize predictive accuracy. We aim to develop ML-augmented models for diabetes screening in community and primary care settings.

Catch-up fat in male adults induces low testosterone and consequently promotes metabolic abnormalities and cognitive impairment.

Background: Catch-up fat in adults (CUFA) caused by rapid nutrition promotion after undernutrition plays an important role in the epidemic of insulin resistance (IR)-related diseases in developing societies. Insulin resistance is considered to be closely associated with reduced testosterone levels and cognitive function. However, the effects of CUFA on testosterone levels and cognitive function are unclear in males.

Suppression of the hypothalamic-pituitary-thyroid axis is associated with the severity of prognosis in hospitalized patients with COVID-19.

Background: The outbreak of severe acute respiratory syndrome novel coronavirus 2 (SARS-CoV-2) has spread rapidly worldwide. SARS-CoV-2 has been found to cause multiple organ damage; however, little attention has been paid to the damage to the endocrine system caused by this virus, and the subsequent impact on prognosis. This may be the first research on the hypothalamic-pituitary-thyroid (HPT) axis and prognosis in coronavirus disease 2019 (COVID-19).

Short-Term Changes in Metabolically Healthy Overweight/Obesity Status Impact the Susceptibility to Type 2 Diabetes in Chinese Adults.

Purpose: Changes in transition from metabolically healthy overweight/obesity (MHO) to metabolically unhealthy overweight/obesity (MUO) are associated with the risk for cardiometabolic complications. This study aims to investigate the effects of short-term dynamic changes in body mass index (BMI) and metabolic status on the risk of type 2 diabetes (T2D) and to identify biological predictors for the MHO-to-MUO transition.

Patients And Methods: A total of 4604 subjects from the REACTION study were included for a 3-year follow-up.

Newly diagnosed diabetes is associated with a higher risk of mortality than known diabetes in hospitalized patients with COVID-19.

Aim: To evaluate the association between different degrees of hyperglycaemia and the risk of all-cause mortality among hospitalized patients with COVID-19.

Materials And Methods: In a retrospective study conducted from 22 January to 17 March 2020, 453 patients were admitted to Union Hospital in Wuhan, China, with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 infection. Patients were classified into four categories: normal glucose, hyperglycaemia (fasting glucose 5.

Not performing an OGTT results in underdiagnosis, inadequate risk assessment and probable cost increases of (pre)diabetes in Han Chinese over 40 years: a population-based prospective cohort study.

Objective: To explore the influence by not performing an oral glucose tolerance test (OGTT) in Han Chinese over 40 years.

Design: Overall, 6682 participants were included in the prospective cohort study and were followed up for 3 years.

Methods: Fasting plasma glucose (FPG), 2-h post-load plasma glucose (2h-PG), FPG and 2h-PG (OGTT), and HbA1c testing using World Health Organization (WHO) or American Diabetes Association (ADA) criteria were employed for strategy analysis.

Alcohol consumption and diabetes risk in a Chinese population: a Mendelian randomization analysis.

Aim: To assess the causality between alcohol intake, diabetes risk and related traits.

Design: Mendelian randomization (MR) study. Subgroup analysis, standard instrumental variable analysis and local average treatment effect (LATE) methods were applied to assess linear and non-linear causality.

Correction: A Chinese version of the Language Screening Test (CLAST) for early-stage stroke patients.

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

A Chinese version of the Language Screening Test (CLAST) for early-stage stroke patients.

There is a severe lack of aphasia screening tools for bedside use in Chinese. A number of aphasia assessment tools have recently been developed abroad, but some of these scales were not suitable for patients with acute stroke. The Language Screening Test (which includes two parallel versions [a/b]) in French has been proven to be an effective and time-saving aphasia screening scale for early-stage stroke patients.

Non-high-density lipoprotein cholesterol: High-density lipoprotein cholesterol ratio is an independent risk factor for diabetes mellitus: Results from a population-based cohort study.

Background: Dyslipidemia predicts the development and progression of diabetes. A higher non-high-density lipoprotein cholesterol (HDL-C):  HDL-C ratio is reportedly associated with metabolic syndrome and insulin resistance, but its relationship with glycemic levels and diabetes remains unclear.

Methods: In all, 4882 subjects aged ≥40 years without diabetes and not using lipid-lowering drugs were enrolled in the study.

Upregulation of pyruvate kinase M2 expression by fatty acid synthase contributes to gemcitabine resistance in pancreatic cancer.

Pancreatic cancer has one of the highest mortality rates of all cancer types. Fatty acid synthase (FASN) is a multifunctional protein homodimer that can convert acetyl coenzyme A (CoA) and malonyl-CoA into palmitate, thus regulating lipogenesis. FASN overexpression has also been shown to cause resistance to gemcitabine, a chemotherapy treatment for pancreatic cancer; however, the mechanism by which this happens is unclear.

Histone Acetyltransferase 1 Promotes Cell Proliferation and Induces Cisplatin Resistance in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common malignant diseases in the world. Mutations, overexpression, and improper recruitment of HATs can lead to tumorigenesis. HAT1 is the first histone acetyltransferase identified and is related with developing HCC, but the mechanism is still unclear.