The liver, skeletal muscle, and adipose tissue are central energy-metabolizing organs and insulin-sensitive tissues, playing a crucial role in maintaining glucose homeostasis. As the powerhouse of the cell, mitochondria not only regulate insulin secretion but also oversee the oxidative phosphorylation and β-oxidation of fatty acids, processes vital for the metabolism of carbohydrates and fats, as well as the synthesis of ATP. The mitochondrial quality control system is of paramount importance for sustaining mitochondrial homeostasis, achieved through mechanisms such as protein homeostasis, mitochondrial dynamics, mitophagy, and biogenesis. Evidence suggests that dysfunctional mitochondria may significantly contribute to insulin resistance and ectopic fat storage in the liver, offering new insights into the strong correlation between mitochondrial dysfunction and the development of obesity, diabetes mellitus type 2 (T2DM), and non-alcoholic fatty liver disease (NAFLD). This manuscript aims to delve into the precise mechanisms by which imbalances in mitochondrial quality control lead to metabolic disorders in the liver, skeletal muscle, and adipose tissue, the 3 major insulin-sensitive organs. In the liver, mitochondrial dysfunction can lead to disturbances in glucose and lipid metabolism, resulting in insulin resistance and fat accumulation—a key factor in the development of NAFLD. In skeletal muscle, reduced mitochondrial function can decrease ATP production, weakening the muscle’s ability to uptake glucose, thereby exacerbating insulin resistance. In adipose tissue, mitochondrial dysfunction can impair adipocyte function, leading to lipotoxicity and inflammatory responses,which further contribute to insulin resistance and the onset of metabolic syndrome. Moreover, the interorgan crosstalk among these 3 tissues is essential for overall metabolic homeostasis. For instance, hepatic gluconeogenesis and glucose utilization in skeletal muscle are both influenced by the health status of their respective mitochondrial populations. The conversion between different types of adipose tissue and the ability to store lipids depend on normal mitochondrial function to avert ectopic fat accumulation in other organs. In summary, this manuscript emphasizes the critical role of mitochondrial quality control in maintaining the metabolic stability of the liver, skeletal muscle, and adipose tissue. It elucidates the specific mechanisms by which mitochondrial dysfunction in these organs contributes to the development of metabolic diseases, providing a foundation for future research and the development of therapeutic strategies targeting mitochondrial dysfunction.

Alzheimer’s disease (AD) is a chronic, progressive, and irreversible neurodegenerative disorder that typically begins with a subtle onset and progresses slowly. Pathologically, it is characterized by two hallmark features: the extracellular accumulation of amyloid β-protein (Aβ), forming senile plaques, and the intracellular hyperphosphorylation of tau protein, resulting in neurofibrillary tangles (NFTs). These pathological changes are accompanied by substantial neuronal and synaptic loss, particularly in critical brain regions such as the cerebral cortex and hippocampus. Clinically, AD presents as a gradual decline in memory, language abilities, and spatial orientation, significantly impairing the quality of life of affected individuals. With the aging population steadily increasing in China, the incidence of AD is rising, making it a major public health concern that requires urgent attention. The growing societal and economic burden of AD underscores the pressing need to identify effective diagnostic biomarkers and develop novel therapeutic strategies. Among the various molecular signaling pathways involved in neurological disorders, the Notch signaling pathway is especially noteworthy due to its evolutionary conservation and regulatory roles in cell proliferation, differentiation, development, and apoptosis. In the central nervous system, Notch signaling is essential for neurodevelopment and synaptic plasticity and has been implicated in several neurodegenerative processes. Although some studies suggest that Notch signaling may influence AD-related pathology, its precise role in AD remains poorly understood. In particular, the interaction between Notch signaling and non-coding RNAs (ncRNAs)—key regulators of gene expression—has received limited attention. NcRNAs, including long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), are known to exert extensive regulatory functions at both transcriptional and post-transcriptional levels. Dysregulation of these molecules has been widely associated with various diseases, including cancers, cardiovascular conditions, and neurodegenerative disorders. Notably, interactions between ncRNAs and major signaling pathways such as Notch can produce widespread biological effects. While such interactions have been increasingly reported in several disease models, comprehensive studies investigating the regulatory relationship between Notch signaling and ncRNAs in the context of AD remain scarce. Given the capacity of ncRNAs to modulate signaling cascades and form complex regulatory networks, a deeper understanding of their crosstalk with the Notch pathway could provide novel insights into AD pathogenesis and reveal potential targets for diagnosis and treatment. In this study, we investigated the regulatory landscape involving the Notch signaling pathway and associated ncRNAs in AD using bioinformatics approaches. By integrating data from multiple public databases, we systematically identified significantly dysregulated Notch pathway-related genes and their interacting ncRNAs in AD. Based on this analysis, we constructed a lncRNA-miRNA-mRNA regulatory network to elucidate the potential mechanisms linking Notch signaling to ncRNA-mediated gene regulation in AD pathogenesis. Furthermore, we explored the internal relationships and molecular mechanisms within this network and assessed the feasibility and clinical relevance of these molecules as early diagnostic biomarkers and potential therapeutic targets for AD. This study aims to deepen our understanding of the molecular basis of AD and offer novel strategies for its diagnosis and treatment.

OBJECTIVES: To investigate the effects of formulated granules of Tianma Gouteng Yin (TGY) on motor deficits in a mouse model of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced subacute Parkinson's disease (PD) and explore the possible molecular mechanisms. METHODS: Ninety C57BL/6 mice were randomized equally into 6 groups, including a control group, a PD model group, a NEC-1 (6.5 mg/kg) treatment group, two TGY treatment groups at 5 and 2.5 g/kg, and a Madopar (76 mg/kg) treatment (positive control) group. Mouse models of PD were established by intraperitoneal injection of MPTP (30 mg/kg) for 5 consecutive days with the corresponding treatments for 15 days. The mice were randomly selected for motor function tests. Western blotting was used to detect the changes in expressions of TH, α-syn, RIPK1, RIPK3 and MLKL in the striatum of the mice. Network pharmacology analysis and molecular docking studies were performed to explore TGY-mediated regulation of the necroptosis pathway for PD treatment. RESULTS: Compared with those in the control group, the PD model mice exhibited obvious motor deficits with significantly increased α-syn protein expression and lowered TH protein expression in the striatum. Treatment with NEC-1 obviously improved motor deficits, inhibited the necroptosis pathway, and alleviated the changes in TH and α‑syn proteins in PD mice. Network pharmacology and molecular docking analyses suggested that the therapeutic effect of TGY in PD was associated with the modulation of RIPK1, a key protein in the necroptosis pathway. In PD mouse models, TGY treatment at the two doses significantly improved motor deficits of the mice, increased TH expression, and decreased the expressions of α-syn and necroptosis-related proteins in the striatum. CONCLUSIONS TGY can effectively inhibit the necroptosis pathway, increase TH expression and decrease α-syn expression in the striatum to improve motor deficits in PD mice.
Animals ; Mice, Inbred C57BL ; Mice ; Necroptosis/drug effects* ; Drugs, Chinese Herbal/therapeutic use* ; Parkinson Disease/drug therapy* ; Disease Models, Animal ; Male

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.