UNASSIGNED: In recent years, the incidence of Endometrial cancer (EC) has been on the rise due to high-fat, high-calorie diets and low-exercise lifestyles. However, the relationships between metabolic disorders and the progression of EC remain uncertain. The purpose of our study was to explore the potential association between obesity, hypertension, hyperglycemia and clinicopathologic characteristics in EC patients.
UNASSIGNED: In categorical variables, Chi-square tests were used to calculate P values. Univariate logistic regression and multivariate logistic regression were used to identify the risk factors of myometrial invasion>1/2 and lymph node metastasis. Overall survival (OS) was estimated using the Kaplan-Meier method.
UNASSIGNED: The study included 406 individuals with EC, 62.6% had type I and 37.4% had type II. Hypertension was seen in 132 (32.5%), hyperglycemia in 75 (18.5%), and overweight or obesity in 217 (53.4%). Hypertension, hyperglycemia, and obesity are strongly associated with the clinicopathologic features of EC. Multivariate logistic regression revealed that hyperglycemia (OR=2.439,95% CI: 1.025-5.804, P = 0.044) was a risk factor for myometrial invasion depth >1/2 in patients with type I EC, and hypertension (OR=32.124,95% CI: 3.287-313.992, P = 0.003) was a risk factor for lymph node metastasis in patients with type I EC. Survival analysis found that hyperglycemia (P < 0.001) and hypertension (P = 0.002) were associated with OS in type I EC. Neither hyperglycemia, hypertension, nor obesity were associated with the prognosis in type II EC.
UNASSIGNED: Hyperglycemia was a risk factor for myometrial invasion depth >1/2 in patients with type I EC and hypertension was a risk factor for lymph node metastasis in patients with type I EC. Hypertension and hyperglycemia were associated with poor prognosis in patients with type I EC.

Sex characteristics exhibit significant disparities in various human diseases, including prevalent cardiovascular diseases, cancers, metabolic disorders, autoimmune diseases, and neurodegenerative diseases. Risk profiles and pathological manifestations of these diseases exhibit notable variations between sexes. The underlying reasons for these sex disparities encompass multifactorial elements, such as physiology, genetics, and environment. Recent studies have shown that human body systems demonstrate sex-specific gene expression during critical developmental stages and gene editing processes. These genes, differentially expressed based on different sex, may be regulated by androgen or estrogen-responsive elements, thereby influencing the incidence and presentation of cardiovascular, oncological, metabolic, immune, and neurological diseases across sexes. However, despite the existence of sex differences in patients with human diseases, treatment guidelines predominantly rely on male data due to the underrepresentation of women in clinical trials. At present, there exists a substantial knowledge gap concerning sex-specific mechanisms and clinical treatments for diverse diseases. Therefore, this review aims to elucidate the advances of sex differences on human diseases by examining epidemiological factors, pathogenesis, and innovative progress of clinical treatments in accordance with the distinctive risk characteristics of each disease and provide a new theoretical and practical basis for further optimizing individualized treatment and improving patient prognosis.

Metabolic dysfunction-associated diseases often refer to various diseases caused by metabolic problems such as glucose and lipid metabolism disorders. With the improvement of living standards, the increasing prevalence of metabolic diseases has become a severe public health problem, including metabolic dysfunction-associated steatotic liver disease (MASLD), alcohol-related liver disease (ALD), diabetes and obesity. These diseases are both independent and interdependent, with complex and diverse molecular mechanisms. Therefore, it is urgent to explore the molecular mechanisms and find effective therapeutic targets of these diseases. MicroRNAs (miRNAs) have emerged as key regulators of metabolic homoeostasis due to their multitargets and network regulatory properties within the past few decades. In this review, we discussed the latest progress in the roles of miRNA-mediated regulatory networks in the development and progression of MASLD, ALD, diabetes and obesity.

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Insulin resistance is the primary contributor to the disruption in glucose homeostasis in the body, playing a significant causative role in many metabolic diseases. Insulin resistance is characterized by compensatory insulin secretion and reduced insulin responsiveness in target organs. Dysregulation of the interaction between insulin-secreting cells and insulin-responsive target organs is an important factor driving the progression of insulin resistance. Circulating endocrine hormones are important mediators mediating the interaction between insulin-secreting cells and insulin-responsive target organs. In addition to the classical hormones secreted by endocrine glands and organ-specific hormones secreted by metabolism-related organs (adipose tissue, muscle, liver, etc.), extracellular vesicles have been recognized as a novel class of endocrine hormones with a complex composition. Extracellular vesicles can transport signaling molecules, such as miRNAs and LncRNAs, to vital organs related to insulin resistance, in a manner akin to conventional hormones. The significant role in regulating the development of insulin resistance underscores the increasing interest in extracellular vesicles as essential contributors to this process. In this review, we summarize the three types of hormones (classical hormones, organokines and extracellular vesicles) that play a regulatory role in insulin resistance, and focus on the novel endocrine hormones, extracellular vesicles, to elaborate the mechanism of extracellular vesicles\' regulation of insulin resistance progress from two aspects: the impact on insulin-secreting cells and the influence on insulin-responsive target organs. In addition, this paper outlines the clinical applications of extracellular vesicles in insulin resistance. A comprehensive understanding of the regulatory mechanisms and diagnostic status of the inter-organ network in insulin resistance has great potential to advance targeted therapeutic interventions and diagnostic markers, thereby benefiting both the prevention and treatment of insulin resistance.

Artificial intelligence (AI) has been applied in healthcare for diagnosis, treatments, disease management, and for studying underlying mechanisms and disease complications in diseases like diabetes and metabolic disorders. This review is a comprehensive overview of various applications of AI in the healthcare system for managing diabetes. A literature search was conducted on PubMed to locate studies integrating AI in the diagnosis, treatment, management and prevention of diabetes. As diabetes is now considered a pandemic now so employing AI and machine learning approaches can be applied to limit diabetes in areas with higher prevalence. Machine learning algorithms can visualize big datasets, and make predictions. AI-powered mobile apps and the closed-loop system automated glucose monitoring and insulin delivery can lower the burden on insulin. AI can help identify disease markers and potential risk factors as well. While promising, AI\'s integration in the medical field is still challenging due to privacy, data security, bias, and transparency. Overall, AI\'s potential can be harnessed for better patient outcomes through personalized treatment.

This study offers insights into the genetic and biological connections between nine common metabolic diseases using data from genome-wide association studies. Our goal is to unravel the genetic interactions and biological pathways of these complex diseases, enhancing our understanding of their genetic architecture. We employed a range of advanced analytical techniques to explore the genetic correlations and shared genetic variants of these diseases. These methods include Linked Disequilibrium Score Regression, High-Definition Likelihood (HDL), genetic analysis combining multiplicity and annotation (GPA), two-sample Mendelian randomization analyses, analysis under the multiplicity-complex null hypothesis (PLACO), and Functional mapping and annotation of genetic associations (FUMA). Additionally, Bayesian co-localization analyses were used to examine associations of specific loci across traits. Our study discovered significant genomic correlations and shared loci, indicating complex genetic interactions among these metabolic diseases. We found several shared single nucleotide variants and risk loci, notably highlighting the role of the immune system and endocrine pathways in these diseases. Particularly, rs2476601 and its associated gene PTPN22 appear to play a crucial role in the connection between type 2 diabetes mellitus, hypothyroidism/mucous oedema and hypoglycaemia. These findings enhance our understanding of the genetic underpinnings of these diseases and open new potential avenues for targeted therapeutic and preventive strategies. The results underscore the importance of considering pleiotropic effects in deciphering the genetic architecture of complex diseases, especially metabolic ones.

The gut microbiota influences aspects of metabolic disease, including tissue inflammation, adiposity, blood glucose, insulin, and endocrine control of metabolism. Prebiotics or probiotics are often sought to combat metabolic disease. However, prebiotics lack specificity and can have deleterious bacterial community effects. Probiotics require live bacteria to find a colonization niche sufficient to influence host immunity or metabolism. Postbiotics encompass bacterial-derived components and molecules, which are well-positioned to alter host immunometabolism without relying on colonization efficiency or causing widespread effects on the existing microbiota. Here, we summarize the potential for beneficial and detrimental effects of specific postbiotics related to metabolic disease and the underlying mechanisms of action. Bacterial cell wall components such as lipopolysaccharides, muropeptides, lipoteichoic acids and flagellin have context-dependent effects on host metabolism by engaging specific immune responses. Specific types of postbiotics within broad classes of compounds such as lipopolysaccharides, muropeptides can have opposing effects on endocrine control of host metabolism where certain postbiotics are insulin sensitizers and others promote insulin resistance. Bacterial metabolites such as short chain fatty acids, bile acids, lactate, glycerol, succinate, ethanolamine, and ethanol can be substrates for host metabolism. Postbiotics can fuel host metabolic pathways directly or influence endocrine control of metabolism through immunomodulation or mimicking host-derived hormones. The interaction of postbiotics in the host-microbe relationship should be considered during metabolic inflammation and metabolic disease.

BACKGROUND: Lipid droplet (LD) is a metabolically active organelle, which changes dynamically with the metabolic state and energy requirements of cells. Proteins that either insert into the LD phospholipid monolayer or are present in the cytoplasm, playing a crucial role in lipid homeostasis and signaling regulation, are known as LD-associated proteins.
METHODS: The keywords \"lipid droplets\" and \"metabolic diseases\" were used to obtain literature on LD metabolism and pathological mechanism. After searching databases including Scopus, OVID, Web of Science, and PubMed from 2013 to 2024 using terms like \"lipid droplets\", \"lipid droplet-associated proteins\", \"fatty liver disease\", \"diabetes\", \"diabetic kidney disease\", \"obesity\", \"atherosclerosis\", \"hyperlipidemia\", \"natural drug monomers\" and \"natural compounds\", the most common natural compounds were identified in about 954 articles. Eventually, a total of 91 studies of 10 natural compounds reporting in vitro or in vivo studies were refined and summarized.
RESULTS: The most frequently used natural compounds include Berberine, Mangostin, Capsaicin, Caffeine, Genistein, Epigallocatechin-3-gallate, Chlorogenic acid, Betaine, Ginsenoside, Resveratrol. These natural compounds interact with LD-associated proteins and help ameliorate abnormal LDs in various metabolic diseases.
CONCLUSIONS: Natural compounds involved in the regulation of LDs and LD-associated proteins hold promise for treating metabolic diseases. Further research into these interactions may lead to new therapeutic applications.

The management of noninfectious complications in kidney transplant recipients includes a broad spectrum of conditions, including metabolic issues, cardiovascular diseases, and malignancies, each presenting unique challenges for nephrologists managing these patients. Unlike infectious complications, these noninfectious issues require nuanced, multidisciplinary approaches for prevention, diagnosis, and management, emphasizing the need for personalized care plans. Cardiovascular disease is particularly significant, standing as the primary cause of death post-transplantation, with recent data indicating an overtaking of cancer death rates over infections among kidney transplant recipients. The intricacies of managing these patients, influenced by the burden of kidney disease and immunosuppression, highlight the importance of a collaborative care model. Although nephrologists may not directly treat all these conditions, their understanding of the unique aspects of transplant recipients is crucial. They play a pivotal role in coordinating care with specialists such as cardiologists, endocrinologists, hematologists, and oncologists, ensuring comprehensive management that addresses these specific post-transplant complications. This review discusses the epidemiology, underlying mechanisms, clinical manifestations, and management strategies of various noninfectious complications post-kidney transplant, with a focus on cardiovascular, metabolic, oncologic, and hematologic complications.