Ma, Xueling

Abstract Objective: This study aimed to develop a machine learning model for the diagnosis of chronic renal failure (CRF) with spleen–kidney qi deficiency (SKQD) syndrome by investigating facial chromatic biomarkers based on traditional Chinese medicine (TCM) theory. Materials and Methods: This cross-sectional study analyzed TCM-defined facial regions in 303 patients with CRF (166 SKQD and 137 non-SKQD) and 25 healthy controls using active appearance models and RGB/Lab color spaces. Key chromatic features were selected using Chi-square automatic interaction detection (CHAID) decision trees to construct a multibranch deep convolutional neural network (CNN), nomogram, and hybrid model. The model performances were compared using the DeLong test. Results: The SKQD group showed a higher glomerular filtration rate, albumin level, and facial R-value with a lower serum creatinine level (all P < 0.05), accompanied by a higher prevalence of shortness of breath with reluctance to speak, and cold extremities ( P < 0.05) compared with the non-SKQD group. Chromatic analysis revealed elevated R/a values in the kidney region using the natural facial color region method ( P < 0.05), and distinctively higher R -values in the bladder-uterus region and a -values in the right small intestine region using the Mingtang facial color region method ( P < 0.05). The CHAID algorithm selected four diagnostic determinants, including the overall facial R -values. The CNN achieved superior discriminative performance (test area under the receiver operating characteristic curve = 0.74 vs. nomogram 0.68, DeLong test P < 0.001) with no added benefit from model integration ( P > 0.05). Conclusions: Facial chromatic biomarkers effectively differentiated SKQD in patients with CRF when analyzed using TCM-defined regions. The superior performance of the CNN validates AI-driven TCM diagnostics as a clinically actionable tool for precise syndrome classification.

Context: Traditional Chinese medicine (TCM) techniques, grounded in TCM theory, offer flexible and personalized therapeutic strategies. Increasing evidence indicates that gut microbiota dysbiosis is closely associated with the onset and progression of various diseases, highlighting a complex mutual relationship. Investigating the interaction between TCM techniques and gut microbiota may provide both a theoretical and practical foundation for clinical application. However, comprehensive systematic analyses remain limited. Objective: This study aimed to identify core themes and emerging trends in research on the interactions between TCM techniques and gut microbiota. In addition, it sought to explore underlying correlations using data mining approaches to provide insights supporting clinical applications and mechanistic studies. Materials and Methods: A systematic literature review was conducted using the Web of Science Core Collection and China National Knowledge Infrastructure for bibliometric analysis. Co-occurrence analysis was performed using CiteSpace software to identify research characteristics and development trends. Key data were extracted and visualized through an interactive network diagram generated with Cytoscape. Results: Current research predominantly focuses on acupoint application, moxibustion, and TCM enema, all of which exhibit significant effects in promoting beneficial microbiota and suppressing pathogenic strains. The regulatory impact of these TCM techniques on gut microbiota is closely associated with inflammatory response pathways and immunity. Conclusions: TCM techniques are extensively applied in disease management. Among them, moxibustion, acupoint application, TCM enema, and Tuina remain prominent and evolving areas of interest. Further empirical research is warranted to elucidate the biological mechanism underpinning these effects within the guidance of TCM pattern theory.

ABSTRACT While BAG3 has been identified as a causative gene for dilated cardiomyopathy, the major pathological events in BAG3‐ related cardiomyopathy that could be targeted for therapeutic benefit remain to be discovered. Here, we aim to uncover novel pathological events through genetic studies in a zebrafish bag3 cardiomyopathy model. Given the known cardioprotective effects of mtor inhibition and the fact that transcription factor EB (tfeb ) encodes a direct downstream phosphorylation target of mTOR signaling, we generated a cardiomyocyte‐specific transgenic line overexpressing tfeb ( Tg[cmlc2:tfeb] ). This overexpression was sufficient to restore defective proteostasis and rescue cardiac dysfunction in the bag3 cardiomyopathy model. Importantly, we detected accelerated cardiac senescence in the bag3 cardiomyopathy model, which can be mitigated by Tg(cmlc2:tfeb) . We compared cardiac transcriptomes between the Tg(cmlc2:tfeb) transgenic fish and the mtor xu015/+ mutant and found that inhibition of the fatty acid binding protein a ( fabp7a ) gene exerts therapeutic effects. Consistent with this genetic evidence, we detected elevated fabp7a expression in the bag3 cardiomyopathy model, whereas cardiomyocyte‐specific overexpression of fabp7a induced dysregulated proteostasis, accelerated cardiac senescence, and cardiac dysfunction. To elucidate the functions of Fabp7a in normative cardiac aging, we turned to the African Turquoise Killifish. We noted elevated Fabp7a expression in the hearts of aged killifish, and pharmacological inhibition of Fabp7a mitigated the cardiac aging process. Together, this study uncovered accelerated cardiac senescence as a key pathological event in bag3 cardiomyopathy and reveals that manipulating the mTOR‐Tfeb‐Fabp7a axis can mitigate this pathology and confer cardioprotective effects.