Glucocorticoid treatment facilitates development of a metabolic syndrome in ovariectomized Macaca Mulatta fed a high fat diet

Development of an assessment method for freely moving nonhuman primates' eating behavior using manual and deep learning analysis

Purpose

Although eating is imperative for survival, few comprehensive methods have been developed to assess freely moving nonhuman primates' eating behavior. In the current study, we distinguished eating behavior into appetitive and consummatory phases and developed nine indices to study them using manual and deep learning-based (DeepLabCut) techniques.

Method

The indices were utilized to three rhesus macaques by different palatability and hunger levels to validate their utility. To execute the experiment, we designed the eating behavior cage and manufactured the artificial food. The total number of trials was 3, with 1 trial conducted using natural food and 2 trials using artificial food.

Result

As a result, the indices of highest utility for hunger effect were approach frequency and consummatory duration. Appetitive composite score and consummatory duration showed the highest utility for palatability effect. To elucidate the effects of hunger and palatability, we developed 2D visualization plots based on manual indices. These 2D visualization methods could intuitively depict the palatability perception and hunger internal state. Furthermore, the developed deep learning-based analysis proved accurate and comparable with manual analysis. When comparing the time required for analysis, deep learning-based analysis was 24-times faster than manual analysis. Moreover, temporal and spatial dynamics were visualized via manual and deep learning-based analysis. Based on temporal dynamics analysis, the patterns were classified into four categories: early decline, steady decline, mid-peak with early incline, and late decline. Heatmap of spatial dynamics and trajectory-related visualization could elucidate a consumption posture and a higher spatial occupancy of food zone in hunger and with palatable food.

Discussion

Collectively, this study describes a newly developed and validated multi-phase method for assessing freely moving nonhuman primate eating behavior using manual and deep learning-based analyses. These effective tools will prove valuable in food reward (palatability effect) and homeostasis (hunger effect) research.

MicroRNA expression profile and identification of novel microRNA biomarkers for metabolic syndrome

The lack of efficient biomarkers is the main reason for the inaccurate early diagnosis and poor treatment outcomes of patients with metabolic syndrome (MetS). The current study aimed to identify several novel microRNA (miRNA) biomarkers for metabolic syndrome via high-throughput sequencing and comprehensive bioinformatics analysis. Through high-throughput sequencing and differentially expressed miRNA (DEM) analysis, we first identified two upregulated and 36 downregulated DEMs in the plasma samples of patients with MetS compared to the healthy volunteers. Additionally, we also predicted 379 potential target genes and subsequently carried out enrichment analysis and protein–protein interaction network analysis to investigate the signaling pathways and functions of the identified DEMs as well as the interactions between their target genes. Furthermore, we selected two upregulated and top 10 downregulated DEMs with the highest |log2FC| values as the key microRNAs, which may serve as potential biomarkers for MetS. RT-qPCR was performed to validated these result. Finally, hsa-miR-526b-5p, hsa-miR-6516-5p was identified as the novel biomarkers for MetS.

Association between chronic obstructive pulmonary disease and serum lipid levels: a meta-analysis

Background

Metabolic syndrome is a common extrapulmonary comorbidity in patients with chronic obstructive pulmonary disease (COPD). However, the reported relationship of COPD with dyslipidemia, an important component of metabolic syndrome, is ambiguous. The aim of this meta-analysis is to investigate the association between COPD and the serum levels of high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), total cholesterol (TC), and triglyceride (TG).

Methods

The PubMed and Embase databases were searched to find potential studies using the search terms of (“dyslipidemia” or “HDL” or “LDL” or “cholesterol” or “triglyceride”) and COPD. We also performed subgroup analysis enrolling patients who were not receiving treatment for dyslipidemia. Mean differences (MD) with 95% confidence intervals (CI) were estimated with random effects models.

Results

A total of 11 studies comprising 615 cases and 471 controls were included in the study. No significant differences were found in the HDL (MD = −2.55, 95% CI [−6.03, 0.93], P = 0.15), LDL (MD = −2.25, 95% CI [−13.36, 8.86], P = 0.69), TC (MD = −2.69, 95% CI [−13.30, 7.92], P = 0.62), and TG (MD = 6.90, 95% CI [−2.81, 16.60], P = 0.16) levels of the 2 groups. However, subgroup analysis enrolling patients who were not receiving treatment for dyslipidemia showed that TG levels were higher in patients with stable COPD than in healthy individuals (MD = 16.35, 95% CI [5.90, 26.80], P = 0.002).

Conclusions

Excluding the impact of hypolipidemic treatment on serum lipid profile, TG levels were higher in patients with COPD than in healthy individuals. This meta-analysis suggested that physicians should screen COPD patients for elevated TG levels to reduce the risk of cardiovascular morbidity and mortality.