The effectiveness and safety of Chinese Patent Medicines based on syndrome differentiation in patients following percutaneous coronary intervention due to acute coronary syndrome (CPM trial): A nationwide Cohort Study

Traditional Chinese medicine diagnostic prediction model for holistic syndrome differentiation based on deep learning

Background

With the development of traditional Chinese medicine (TCM) syndrome knowledge accumulation and artificial intelligence (AI), this study proposes a holistic TCM syndrome differentiation model for the classification prediction of multiple TCM syndromes based on deep learning and accelerates the construction of modern foundational TCM equipment.

Methods

We searched publicly available TCM guidelines and textbooks for expert knowledge and validated these sources using ten-fold cross-validation. Based on the BERT and CNN models, with the classification constraints from TCM holistic syndrome differentiation, the TCM-BERT-CNN model was constructed, which completes the end-to-end TCM holistic syndrome text classification task through symptom input and syndrome output. We assessed the performance of the model using precision, recall, and F1 scores as evaluation metrics.

Results

The TCM-BERT-CNN model had a higher precision (0.926), recall (0.9238), and F1 score (0.9247) than the BERT, TextCNN, LSTM RNN, and LSTM ATTENTION models and achieved superior results in model performance and predictive classification of most TCM syndromes. Symptom feature visualization demonstrated that the TCM-BERT-CNN model can effectively identify the correlation and characteristics of symptoms in different syndromes with a strong correlation, which conforms to the diagnostic characteristics of TCM syndromes.

Conclusions

The TCM-BERT-CNN model proposed in this study is in accordance with the TCM diagnostic characteristics of holistic syndrome differentiation and can effectively complete diagnostic prediction tasks for various TCM syndromes. The results of this study provide new insights into the development of deep learning models for holistic syndrome differentiation in TCM.

A Powerful Tool in the Treatment of Myocardial Ischemia-Reperfusion Injury: Natural and Nanoscale Modified Small Extracellular Vesicles Derived from Mesenchymal Stem Cells

Myocardial ischemia-reperfusion injury (MI/RI) constitutes a pivotal determinant impacting the long-term prognosis of individuals afflicted by ischemic cardiomyopathy subsequent to reperfusion therapy. Stem cells have garnered extensive application within the realm of MI/RI investigation, yielding tangible outcomes. Stem cell therapy encounters certain challenges in its application owing to the complexities associated with stem cell acquisition, a diminished homing rate, and a brief in vivo lifespan. Small extracellular vesicles (sEV) originating from mesenchymal stem cells (MSCs) have been demonstrated to possess the benefits of abundant availability, reduced immunogenicity, and a diminished tumorigenic incidence. They can exert their effects on damaged organs, improving injuries by transporting a lot of constituents, including proteins, RNA, lipid droplets, and more. This phenomenon has garnered substantial attention in the context of MI/RI treatment. Simultaneously, MSC-derived sEV (MSC-sEV) can exhibit enhanced therapeutic advantages through bioengineering modifications, biomaterial incorporation, and natural drug interventions. Within this discourse, we shall appraise the utilization of MSC-sEV and their derivatives in the context of MI/RI treatment, aiming to offer valuable insights for future research endeavors related to MI/RI.

QiShenYiQi pill inhibits atherosclerosis by promoting reverse cholesterol transport PPARγ-LXRα/β-ABCA1 pathway

ETHNOPHARMACOLOGICAL RELEVANCE

QiShenYiQi pill (QSYQ), a Chinese compound medicine, originate from BuYangHuanWu decoction in the Qing dynasty, and has been used to treat ischemic cardiovascular diseases for more than two hundred years in China. Multi-central randomized double-blind controlled studies have proved that QSYQ has similar efficacy as enteric coated aspirin in the secondary prevention of myocardial infarction.

AIM OF STUDY

The aim of study was to explore the effect of QSYQ on reverse cholesterol transport (RCT) pathway during atherosclerosis.

MATERIALS AND METHODS

Eight-week-old male apoE-/- mice (on the gene background of C57BL/6J) were fed with a high-fat western diet and treated with low dose and high dose of QSYQ, as well as the positive control agent, liver X receptor-α (LXR-α) agonist GW3965. Eight weeks later, mice were sacrificed and the aorta was collected for atherosclerotic analysis. The aortic root was stained with Oil red O to evaluate the area of atherosclerotic lesion, and stained with immunohistochemistry to analyze the intra-plaque component and RCT protein in atherosclerotic plaque. The thoracic aorta was used to detect differentially expressed genes by comparative transcriptome RNA-seq and the protein expression of RCT pathway by western blotting.

RESULTS

After eight weeks of treatment, we found that both of QSYQ and LXR-α agonist reduced atherosclerotic plaque area significantly, and decreased the intra-plaque component, including the lipid, the smooth muscle cell and the macrophage. Compared with the control group, there were 49 differentially expressed genes in low-dose QSYQ group, including 21 up-regulated genes and 28 down-regulated genes. The results of GO and KEGG analysis showed that the differentially expressed genes mainly concentrated in the negative regulation of lipid biosynthesis, positive regulation of lipid metabolism, cell response to lipids, negative regulation of lipid storage, fatty acid degradation, and glycerol ester metabolism. Both of QSYQ and LXR-α agonist reduced the protein expression of CD36 and increased the protein expression of PPARγ-LXRα/β-ABCA1 in atherosclerotic plaque.

CONCLUSION

The anti-atherosclerotic mechanism of QSYQ was involved in inhibiting lipid phagocytosis and promoting reverse cholesterol transport, therefore reducing lipid deposition and inflammatory cells in plaque.