Gut microbiome metabolites as key actors in atherosclerosis co-depression disease

Predicting metabolite-disease associations based on dynamic adaptive feature learning architecture

BACKGROUND AND OBJECTIVE

In recent years, the association between metabolites and complex human diseases has increasingly been recognized as a major research focus. Traditional wet-lab experiments are considered time-consuming and labor-intensive, while computational methods have been shown to significantly enhance research efficiency. However, existing methods for predicting metabolite-disease associations primarily depend on predefined similarity metrics and static network structures, often failing to capture the complex interactions among node neighborhoods within metabolite and disease networks. This limitation hinders the capture of deeper dynamic relationships between metabolites and diseases, resulting in information loss and noise that deteriorate prediction performance.

METHODS

An innovative dynamic adaptive feature learning architecture (DAF-LA) is proposed to predict metabolite-disease associations. This architecture integrates dynamic subgraph construction and an adaptive feature enhancement mechanism, enabling high-precision feature learning and association prediction through progressive optimization from initial to high-order feature representations.

RESULTS

The architecture was evaluated through five-fold cross-validation, achieving an AUC of 0.9742 and an AUPR of 0.9734. Additionally, the case study demonstrates that DAF-LA accurately predicts metabolites associated with Alzheimer's disease, Type 2 diabetes mellitus and Parkinson's disease.

CONCLUSIONS

The results demonstrate that our method effectively uncovers potential associations between metabolites and diseases through dynamic topological modeling and multi-scale collaborative learning. It enables faster identification of likely metabolite-disease relationships, reduces the time and resource costs associated with inefficient large-scale screening in traditional wet-lab experiments, and provides more targeted guidance for subsequent biological validation.

Ozone controls the metabolism of tryptophan protecting against sepsis-induced intestinal damage by activating aryl hydrocarbon receptor

BACKGROUND

Intestinal injury is the most common complication of sepsis, and the mitigation of intestinal damage is crucial for treating sepsis.

AIM

To examine the use of ozone-rich water and its action in preventing intestinal damage caused by sepsis.

METHODS

Through histological analysis, immunohistochemistry, immunofluorescence assays, and Western blot detection, we evaluated the therapeutic efficacy of ozone in mitigating intestinal injury during sepsis. Additionally, by conducting 16S rRNA sequencing and untargeted metabolomics analysis on fecal samples, we identified alterations in the gut microbiota and specific metabolites in septic mice following ozone treatment. This comprehensive approach aims to further elucidate the mechanistic underpinnings of ozone therapy in alleviating sepsis-induced intestinal damage.

RESULTS

Our results demonstrate that ozonated water significantly ameliorates pathological damage in intestinal tissues, enhances the expression of tight junction proteins, and inhibits the polarization of intestinal macrophages, thereby reducing the expression of inflammatory cytokines in intestinal tissues of cecal ligation and puncture-induced septic mice. 16S rRNA sequencing analysis revealed that ozonated water increased the abundance of beneficial bacteria and alleviated gut microbiota dysbiosis. Studies using broad-spectrum antibiotic-treated mice indicated that the protective effects of ozonated water on intestinal injury are dependent on the gut microbiota. Furthermore, metabolomic analysis identified an increase in the tryptophan metabolite DL-tryptophan in the ozonated water treatment group. This suggests that ozonated water protects against intestinal injury by activating the aryl hydrocarbon receptor and suppressing necroptosis in intestinal epithelial cells.

CONCLUSION

Ozone protected against sepsis-induced intestinal injury through regulation of the gut microbiota and tryptophan metabolism, inhibiting necrotic apoptosis of intestinal epithelial cells through activation of the aryl hydrocarbon receptor.

Astragaloside IV Alleviates Depression in Rats by Modulating Intestinal Microbiota, T-Immune Balance, and Metabolome

This study aims to explore the effects of Astragaloside IV (AS-IV) on abnormal behaviors, intestinal microbiota, intestinal T-immune balance, and fecal metabolism of a model of depression in rats. Herein, we integrally applied 16S rRNA sequencing, molecular biological techniques, and 1H NMR-based fecal metabolomics to demonstrate the antidepression activity of AS-IV. The results suggested that AS-IV regulated the depression-like behaviors of rats, which are presented by an increase of body weight, upregulation of sucrose preference rates, and a decrease of immobility time. Additionally, AS-IV increased the abundances of beneficial bacteria (Lactobacillus and Oscillospira) in a model of depression in rats. Moreover, AS-IV regulated significantly the imbalance of Th17/Treg cells, and the abnormal contents of both anti-inflammatory factors and pro-inflammatory factors. Besides, fecal metabolomics showed that AS-IV improved the abnormal levels of short-chain fatty acids and amino acids. Collectively, our research supplemented new data, supporting the potential of AS-IV as an effective diet or diet composition to improve depression-like behaviors, dysfunctions of microbiota, imbalance of T immune, and the abnormality of fecal metabolome. However, the causality of the other actions was not proven because of the experimental design and the methodology used. The current findings suggest that AS-IV could function as a promising diet or diet composition to alleviate depressed symptoms.

Depression Following Acute Coronary Syndrome: A Review

Depression is common among patients with acute coronary syndrome (ACS). Although multiple studies have confirmed that depression is an independent risk factor for poor outcomes in ACS, general awareness of this issue is still limited. Ongoing research has described detailed aspects of depression in ACS, with various mechanistic hypotheses put forward to explain the complexity of this comorbidity. Several investigations have explored management strategies in this subgroup of patients, including screening for depression, antidepressant treatment, and cardiac rehabilitation. However, evidence of long-term improvement in clinical outcomes is still scarce, and a more comprehensive understanding of the underlying mechanisms that link depression with ACS is required to further improve disease management.