Mitochondria, functioning not only as the central hub of cellular energy metabolism but also as semi-autonomous organelles, orchestrate cellular fate decisions through their endogenous mitochondrial DNA (mtDNA), which encodes core components of the electron transport chain. Emerging research has identified microRNAs localized within mitochondria, termed mitochondria-located microRNAs (mitomiRs). Recent studies have revealed that mitomiRs are transcribed from nuclear DNA (nDNA), processed and matured in the cytoplasm, and subsequently transported into mitochondria. mitomiRs regulate mtDNA through diverse mechanisms, including modulation of mtDNA expression at the translational level and direct binding to mtDNA to influence transcription. Aberrant expression of mitomiRs leads to mitochondrial dysfunction and contributes to the pathogenesis of metabolic diseases. Restoring mitomiR expression to physiological levels using mitomiRs mimics or inhibitors has been shown to improve mitochondrial function and alleviate related diseases. Consequently, the regulatory mechanisms of mitomiRs have become a major focus in mitochondrial research. Given that mitomiRs are located in mitochondria, targeted delivery strategies designed for mtDNA can be adapted for the delivery of mitomiRs mimics or inhibitors. However, numerous intracellular and extracellular barriers remain, highlighting the need for more precise and efficient delivery systems in the future. The regulation of mtDNA expression mediated by mitomiRs not only expands our understanding of miRNA functions in post-transcriptional gene regulation but also provides promising molecular targets for the treatment of mitochondrial-related diseases. This review systematically summarizes recent research progress on mitomiRs in regulating mtDNA expression and discusses the underlying mechanisms of mitomiRs-mtDNA interactions. Additionally, it provides new perspectives on precision therapeutic strategies, with a particular emphasis on mitomiRs-based regulation of mitochondrial function in mitochondrial-related diseases.

A novel series of 2-aryl substituted benzothiopyranone compounds was designed and synthesized based on our previously obtained benzothiopyranone scaffold with significant antituberculosis activity. All target compounds were evaluated for their antimycobacterial activity and preliminary druggability was subsequently investigated for some selected compounds with good activity. The results indicated that most compounds showed good activity against Mycobacterium tuberculosis H₃₇Rv. Among them, compounds 8g, 8h, 8q and 9f showed potent activity with MIC ranged from 0.2 to 0.4 μg·mL^-1. Furthermore, some active compounds exhibited low cytotoxicity and cardiotoxicity risk. It is worth noting that compounds 8h and 8q with good liver microsome stability and low inhibition of CYPs 3A4/5 and 2C9 were suitable for combination drug regimen to treat tuberculosis.

The unique advantages of traditional Chinese medicine (TCM) in treating late onset hypogonadism in male have gradually emerged with the continuous deepening of the understanding and research on late onset hypogonadism in male. Time sequence is a general summary of the natural growth and operational laws. Tian gui and testosterone have their normal time sequences, and they may be associated with each other. A man′s tian gui follows the regular time sequence from " inception" to " exhaustion" throughout " eight" under normal physiological conditions. " Tian gui out of time sequence" includes the loss of tian gui exuberance (dysfunction of viscera dominated by the liver) and exhaustion in the time sequence (pathological deficiency of viscera dominated by the kidney), resulting in " tian gui exhaustion" in advance of " eight eight". Tian gui and testosterone are key concepts in Chinese and Western medicine for understanding late onset hypogonadism in male. The theory of " tian gui out of time sequence" may be closely related to the core pathogenesis of this condition, particularly in cases of liver depression and kidney deficiency. This study suggests that restoring the normal time sequence of tian gui while treating the liver and kidney simultaneously through time-sharing treatment should be effective. The use of Xiongcan Yishen Formula has shown promising therapeutic result, offering new insights and references for treating late onset hypogonadism in male using TCM.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

OBJECTIVE To analyze and identify the chemical components of Weite’an tablet which is a hospital preparation by UHPLC-Q-TOF-MS, and to find the drug migration components in rat plasma. METHODS In 0.05% formic acid water acetonitrile mobile phase system, after chromatographic separation of the Acquire UPLC BEH C18 column, Q-TOF positive and negative ion scanning was performed, and data processing was performed in SWATH collection mode. At the same time, quantitative analysis of various components in plasma samples was conducted through MRMHR data processing function during qualitative identification. RESULTS A total of 52 chemical components were isolated and identified in the experiment, including 22 flavonoids, 6 phenolic acids, 5 terpenoids, 3 coumarins, 2 alkaloids, amino acids and other compounds. Eight components were introduced into the blood: 6-hydroxy-7-methoxycoumarin, hesperidin, tangerine, stachydrine, berberine, scutellarin and quercetin. CONCLUSION This method is accurate and stable, and is suitable for the analysis and identification of chemical components in Weite’an tablets. The experimental results lay a solid foundation for clinical rational drug use, follow-up drug tissue distribution and basic research of effectors.

OBJECTIVE To improve the quality evaluation method of Platycodonis Radix, to study the differences in the quality of three-years-old Platycodonis Radix under different harvesting periods, and to determine the optimal harvesting period of Platycodonis Radix. METHODS The leachate, ash, moisture, refractive index and the content of six saponins were used as the quality evaluation indexes. The differences between the herbs of Platycodonis Radix at different harvesting periods were characterized with the help of mathematical and statistical methods. And link the entropy weight method, gray correlation analysis and TOPSIS method were combined to obtain the statistical analysis of the relevant indexes and the quality ranking information of the herbs in different harvesting periods. RESULTS There were significant differences between the quality evaluation indexes of three-years-old Platycodonis Radix at different harvesting periods. The added multi-indicator testing had improved the quality evaluation system of Platycodonis Radix and enhanced the "Drug properties-Effectiveness" linkage of the herbs. And the results of the comprehensive quality evaluation model showed that the herbs harvested around October 21 (Frost’s Descent) were ranked best in terms of comprehensive index. CONCLUSION In order to ensure the quality of Platycodonis Radix, the best harvesting period for three-years-old Platycodonis Radix is determined around the "Frost’s Descent" season, taking into account the characteristics of the herbs' appearance and the material basis of herbs.

The early response of plant auxin gene family Aux/IAA (auxin/indole-3-acetic acid) and its interaction with auxin response factor (ARF) are important pattern to regulate plant growth and development. This work identified 28 StoIAA and 24 StoARF members based on the whole genome data of the medicinal plant Senna tora L., which were classified into 10 and 8 subfamilies, respectively. Phylogenetic tree and collinearity analysis showed that S. tora has close evolutionary relationship with the IAA and ARF homologous genes of Glycine max, Medicago truncatula, and the segment duplication events dominate the expansion of StoIAA and StoARF. Gene structure analysis showed that the vast majority of StoIAA and StoARF contain characteristic conserved domain. Transcriptome data showed that StoIAAs and StoARFs were expressed in leaves, roots and seeds, some members had tissue specific expression. The StoIAA and StoARF promoter region most contain functional elements related to stress response, growth and development, hormone induction and secondary metabolism. In addition, gene expression analysis showed that many StoIAAs and StoARFs can quickly respond to drought and salt stress and exhibited same expression patterns under both stress condition. The yeast two-hybrid experiment confirmed that StoARF8 and StoARF10 exhibit varying degrees of interaction with multiple StoIAA proteins, respectively. The above results provide a basis for further biological functional analysis of the Aux/IAA and ARF gene family of S. tora.