Association of obesity and diabetes with prostate cancer risk groups in a multiethnic population

Predicted body fat percentage, fat mass and lean body mass in relation to risk of prostate cancer: Results from the NHANES 1999 to 2010

The purpose of this study is to examine the relationship between fat mass (FM), body fat percentage (BF%), lean body mass (LM), and prostate cancer (PCa), and evaluate their potential impact on the risk of PCa. Data from the National Health and Nutrition Examination Survey (NHANES) of the United States were utilized. Adult male participants from 6 survey cycles between 1999 and 2010 were selected as the study sample. Multivariable logistic regression analysis was conducted to explore the association between BF%, LM, and PCa, while controlling for potential confounding variables. Among the 8440 participants, 359 cases of PCa were diagnosed. The relationship between BF%, LM, and PCa was nonlinear. In the multivariable logistic regression analysis, there was an independent association between BF% and PCa risk (OR: 1.04, 95% CI: 1.02-1.06), suggesting that higher BF% levels are associated with an increased risk of PCa. Conversely, higher LM levels were associated with a decreased risk of PCa (OR: 0.96, 95% CI: 0.95-0.98). The findings of this study demonstrate a correlation between BF% and LM with PCa, but do not provide direct evidence of a causal relationship. Higher BF% levels are associated with an increased risk of PCa, while higher LM levels are associated with a decreased risk. These results provide valuable insights for understanding and potentially preventing PCa, although further research is needed to fully comprehend the underlying mechanisms.

Health-aware food recommendation system with dual attention in heterogeneous graphs

Recommender systems (RS) have been increasingly applied to food and health. However, challenges still remain, including the effective incorporation of heterogeneous information and the discovery of meaningful relationships among entities in the context of food and health recommendations. To address these challenges, we propose a novel framework, the Health-aware Food Recommendation System with Dual Attention in Heterogeneous Graphs (HFRS-DA), for unsupervised representation learning on heterogeneous graph-structured data. HFRS-DA utilizes an attention technique to reconstruct node features and edges and employs a dual hierarchical attention mechanism for enhanced unsupervised learning of attributed graph representations. HFRS-DA addresses the challenge of effectively leveraging the heterogeneous information in the graph and discovering meaningful semantic relationships between entities. The framework analyses recipe components and their neighbours in the heterogeneous graph and can discover popular and healthy recipes, thereby promoting healthy eating habits. We compare HFRS-DA using the Allrecipes dataset and find that it outperforms all the related methods from the literature. Our study demonstrates that HFRS-DA enhances the unsupervised learning of attributed graph representations, which is important in scenarios where labelled data is scarce or unavailable. HFRS-DA can generate node embeddings for unused data effectively, enabling both inductive and transductive learning.

Diabetes mellitus and prostate cancer risk: A mendelian randomization analysis

BACKGROUND

Some studies have directed towards an association between diabetes mellitus (DM) and prostate cancer (PCa); however, this specific relationship remains inconclusive. In recent years, Mendelian randomization (MR) has become a widely used analytical method for inferring epidemiological causes.

AIM

To investigated the potential relationship between DM and PCa using MR.

METHODS

We downloaded relevant data on "diabetes" and "PCa" from the IEU OpenGWAS project database, performed three different methods to conduct MR, and carried out sensitivity analysis for verification.

RESULTS

The results indicated that DM was an independent risk factor for PCa. The odds ratio (OR) values obtained using the inverse variance weighted method in this study were as follows: OR = 1.018 (95% confidence interval: 1.004-1.032), P = 0.014.

CONCLUSION

We found that DM could increase the incidence rate of PCa.

Association between the Systemic Immune-Inflammation Index and Prostate Cancer

The systemic immune-inflammation index (SII) is a novel and integrated marker that has not been studied with prostate cancer. We aimed to ascertain the association between SII levels and prostate cancer. We utilized data from the 1999-2010 cycles of the National Health and Nutrition Examination Survey (NHANES). Multivariate logistic regression analyses were conducted to evaluate the relationship between SII and prostate cancer. Additionally, subgroup analyses stratified by age, BMI, history of hypertension and diabetes were performed. A total of 8,020 participants were included in our analysis. After full adjustment, SII was associated with a 7% increased risk of prostate cancer (OR 1.07, 95% CI 0.99-1.15, p = 0.094). We further categorized SII values into three segments and found that individuals in the highest SII group had a 33% increased risk of prostate cancer than those in the tertile 1 group (OR 1.33; 95% CI 1.01-1.81; p = 0.044; P for trend = 0.046). In addition, a higher SII level was associated with a 137% increased risk of prostate cancer in the diabetes subgroup (OR 2.37; 95% CI 1.08-5.21; p = 0.031). The current study suggested that SII was positively associated with increased risks of prostate cancer. The SII might be an easily accessible indicator for identifying prostate cancer.

Adipose Tissue-Derived Extracellular Vesicles Contribute to Phenotypic Plasticity of Prostate Cancer Cells

Metastatic prostate cancer is one of the leading causes of male cancer deaths in the western world. Obesity significantly increases the risk of metastatic disease and is associated with a higher mortality rate. Systemic chronic inflammation can result from a variety of conditions, including obesity, where adipose tissue inflammation is a major contributor. Adipose tissue endothelial cells (EC) exposed to inflammation become dysfunctional and produce a secretome, including extracellular vesicles (EV), that can impact function of cells in distant tissues, including malignant cells. The aim of this study was to explore the potential role of EVs produced by obese adipose tissue and the ECs exposed to pro-inflammatory cytokines on prostate cancer phenotypic plasticity in vitro. We demonstrate that PC3ML metastatic prostate cancer cells exposed to EVs from adipose tissue ECs and to EVs from human adipose tissue total explants display reduced invasion and increased proliferation. The latter functional changes could be attributed to the EV miRNA cargo. We also show that the functional shift is TWIST1-dependent and is consistent with mesenchymal-to-epithelial transition, which is key to establishment of secondary tumor growth. Understanding the complex effects of EVs on prostate cancer cells of different phenotypes is key before their intended use as therapeutics.

Study on the Effect and Mechanism of Huaji Jianpi Decoction on Simple Obesity

Background

As the major type of obesity in clinical, simple obesity has gained increasing attention in recent years. Depending on the etiology and pathogenesis of simple obesity and combined with clinical practice experience, Huaji Jianpi decoction (HJJPD) was established to invigorate the spleen and eliminate dampness; however, the underlying molecular mechanism is yet unclear.

Materials and Methods

A simple obesity mouse model was established by feeding a high-fat diet to the animals, and the related indexes were analyzed. The mice were divided into the normal, positive control (orlistat), and HJJPD high-dose, medium-dose, and low-dose groups. After 6 weeks of administration, the curative effect of HJJPD was observed. Simple obesity is associated with leptin resistance. The leptin signal transduction pathways mainly include the JAK2-STAT3, AMPK-ACC, LepRb-IRS-PI3K-PDE3B-cAMP, and LepRb-SHP2-MAPKs (ERK1/2) pathways. Therefore, the networks of HJJPD acting on these four pathway-related targets were constructed using the network pharmacology method, and the key nodes were identified.

Results

After 6 weeks of drug intervention, we found a good therapeutic effect of HJJPD on simple obesity in the mouse model. The biological network analysis showed that HJJPD plays a role in treating leptin resistance in simple obesity by acting on multiple targets in the JAK2-STAT3 pathway via various components. Also, HJJPD can improve leptin resistance in mice by enhancing the binding force of LEP and LEPRB and activating the LEP-mediated JAK2-STAT3 signaling pathway.

Conclusion

In this study, animal experiments, network pharmacology, and molecular biology were combined to establish a mouse model of simple obesity, confirm the role of HJJPD in the treatment of simple obesity, and preliminarily reveal the related mechanism. Relevant research results will provide a basis for the treatment of simple obesity and the drug discovery.