ObjectiveBased on ultra-performance liquid chromatography-quadrupole-electrostatic field orbitrap high resolution mass spectrometry（UPLC-Q-Orbitrap-MS）， the chemical constituents of Qili Qiangxin capsules was identified， and their distribution in vivo was analyzed. MethodsUPLC-Q-Orbitrap-MS was used to detect the sample solution of Qili Qiangxin capsules， as well as the serum， brain， heart， lung， spleen， liver and kidney tissues of mice after oral administration. Using the Thermo Xcalibur 2.2 software， the compound information database was constructed， and the molecular formulas of compounds corresponding to the quasi-molecular ions were fitted. Based on the information of retention time， accurate relative molecular mass and fragments， the compounds and their distribution in vivo were analyzed by comparing with the data of reference substances and literature. ResultsA total of 233 compounds， including 70 terpenoids， 60 flavonoids， 23 organic acids， 17 alkaloids， 20 steroids， 7 coumarins and 36 others， were identified or predicted from Qili Qiangxin capsules， 73 of which were identified matching with standard substances. Tissue distribution results showed that 71， 17， 38， 33， 32， 58 and 43 migrating components were detected in blood， brain， heart， lung， spleen， liver and kidney， respectively. Thirty-seven components were absorbed into the blood and heart， including quinic acid， benzoylaconitine benzoylmesaconine and so on. Fourteen components were absorbed into the blood and six tissues， including calycosin， methylnissolin， formononetin， alisol B， alisol A and so on. ConclusionThis study comprehensively analyzes the chemical components of Qili Qiangxin capsules and their distribution in vivo. Among them， astragaloside Ⅳ， salvianolic acid B， ginsenoside Rb₁， ginsenoside Rb₃， ginsenoside Rd， ginsenoside Rg₃， calycosin-7-glucoside， and sinapine may be the important components for the treatment of heart failure， which can provide useful reference for its quality control and research on pharmacodynamic material basis.

Objective: To identify core acupoint patterns and elucidate the molecular mechanisms of acupuncture for primary depressive disorder (PDD) through data mining and network analysis. Methods: A comprehensive literature search was conducted across PubMed, Embase, Ovid Technologies (OVID), Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), China National Knowledge Infrastructure Database (VIP), Wanfang Data, and SinoMed Database from database foundation to January 31, 2025, for clinical studies on acupuncture treatment of PDD. Descriptive statistics, high-frequency acupoint analysis, degree and betweenness centrality evaluation, and core acupoint prescription mining identified predominant therapeutic combinations for PDD. Network acupuncture was used to predict therapeutic target for the core acupoint prescription. Subsequent protein-protein interaction (PPI) network and molecular complex detection (MCODE) analyses were conducted to identify the key targets and functional modules. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses explored the underlying biological mechanisms of the core acupoint prescription in treating PDD. Results: A total of 57 acupoint prescriptions underwent systematic analysis. The core therapeutic combinations comprised Baihui (GV20), Yintang (GV29), Neiguan (PC6), Hegu (LI4), and Shenmen (HT7). Network acupuncture analysis identified 88 potential therapeutic targets (79 overlapping with PDD), while PPI network analysis revealed central regulatory nodes, including interleukin (IL)-6, IL-1β, tumor necrosis factor (TNF)-α, toll-like receptor 4 (TLR4), IL-10, brain-derived neurotrophic factor (BDNF), transforming growth factor (TGF)-β1, C-X-C motif chemokine ligand 10 (CXCL10), mitogen-activated protein kinase 3 (MAPK3), and nitric oxide synthase 1 (NOS1). MCODE-based modular analysis further elucidated three functionally coherent clusters: inflammation-homeostasis (score = 6.571), plasticity-neurotransmission (score = 3.143), and oxidative stress (score = 3.000). GO and KEGG analyses demonstrated significant enrichment of the MAPK, phosphoinositide 3-kinase/protein kinase B (PI3K/Akt), and hypoxia-inducible factor (HIF)-1 signaling pathways. These mechanistic insights suggested that the antidepressant effects mediated through mechanisms of neuroinflammatory regulation, neuroplasticity restoration, and immune-oxidative stress homeostasis. Conclusion This study reveals that acupuncture alleviates depression through a multi-level mechanism, primarily involving the neuroinflammation suppression, neuroplasticity enhancement, and oxidative stress regulation. These findings systematically clarify the underlying mechanisms of acupuncture’s antidepressant effects and identify novel therapeutic targets for further mechanistic research.

Objective:To explore the effect of continuous improvement model with Definition,Measure,Analyze,Improve,and Control(DMAIC)on the management for equipment of diagnosing and treating chronic respiratory diseases.Method:To address the management issues of diagnosis and treatment equipment for chronic respiratory diseases,multiple management strategies were formulated on the basis of definition,measurement,analysis,improvement and control stages of the DMAIC continuous improvement model.Selected 80 diagnostic and therapeutic equipment used at the department of respiratory in People's Hospital of Xinjiang Uygur Autonomous Region from August 2021 to July 2023.The conventional management method was used to manage them during August 2021 to July 2022,and the management method of DMAIC continuous improvement management model(continuous improvement management method)for chronic respiratory diseases was adopted to manage them during August 2022 to July 2023.The ratio of failure equipment,score of risk assessment,qualified rate of examination,and satisfaction score of users who operated equipment by using the two kinds of management methods were compared.Result:The average failure ratios of shutdown due to failure,injury that caused external environment,abnormal self-examination at power on,unqualified quality inspection,and poorly operational quality in treatment in equipment of diagnosing and treating respiratory disease by using continuous improvement management method were respectively(1.58±0.51)%,(0.34±0.10)%,(0.65±0.20)%,(2.08±0.53)%and(1.61±0.52)%,which were all lower than those by using conventional management method,and the differences of them were significant(t=14.512,11.205,24.354,17.169,17.663,P<0.05).The degree of detectability,severity,and probability scores of occurrence of the equipment by using continuous improvement management method were lower than those of conventional management method,and the differences were statistically significant(t=10.478,6.930,9.407,P<0.05).The qualified rate of equipment inspection of continuous improvement management method was higher than that of conventional management method,and the difference was statistically significant(x2=9.642,P<0.05).The performance,cleanliness of equipment,and timeliness scores of operators,who used equipment,for diagnosis and treatment equipment that were managed by using continuous improvement management method were all higher than those by using conventional management method,and the differences were statistically significant(t=2.204,2.268,2.604,P<0.05).Conclusion:The DMAIC continuous improvement management model method for equipment of diagnosing and treating chronic respiratory disease can significantly improve management level for equipment,and reduce failure risk of equipment,and increase the utilization efficiency of equipment and the users'satisfaction.

OBJECTIVE To investigate the impact of Tongxinluo capsules on the pharmacokinetics of rivaroxaban in rats. METHODS Rats were randomly divided into rivaroxaban alone group （2.70 mg/kg）， low-dose Tongxinluo capsules combined with rivaroxaban group （Tongxinluo capsules 0.28 g/kg+rivaroxaban 2.70 mg/kg）， and high-dose Tongxinluo capsules combined with rivaroxaban group （Tongxinluo capsules 0.84 g/kg+rivaroxaban 2.70 mg/kg）， with five rats in each group. Following seven consecutive days of gavage with normal saline or the corresponding doses of Tongxinluo capsules， the rats were subjected to a final gavage administration of rivaroxaban. Blood samples were collected at 0 h prior to the final administration and at 0.16， 0.33， 0.50， 0.75， 1， 1.5， 2， 4， 8， 12 and 24 h post-final administration. The plasma concentration of rivaroxaban in rats was determined by high-performance liquid chromatography-tandem mass spectrometry. The pharmacokinetic parameters [peak concentration （cmax）， half-life （t1/2）， area under the drug concentration time curve （AUC）， mean residence time （MRT）， clearance （CL）， apparent volume of distribution （Vd） and peak time （tmax）] of each group were calculated using a non-compartmental model of MonolixSuite 2023R1 pharmacokinetic software. RESULTS Compared with rivaroxaban alone group， AUC₀₋ₜ and AUC0-∞ of rivaroxaban in rats were increased significantly in high-dose Tongxinluo capsules+rivaroxaban group （P＜0.05）， while CL was decreased significantly （P＜0.05）； t1/2 and MRT were shortened， tmax was extended， cmax was increased， while Vd was decreased， but there was no statistical significance （P＞0.05）. CONCLUSIONS Rivaroxaban combined with Tongxinluo capsules significantly increases the plasma exposure of rivaroxaban in rats. Potential drug-drug interactions should be considered in clinical practice based on the co-administration conditions.

[Summary]Glucagon-like peptide-1 receptor agonist(GLP-1RA)has been widely applied in clinic,and the possible correlation between GLP-1RA and the progression of retinopathy in clinical trials has attracted much attention.The existing basic research suggests that GLP-1RA has a certain neuroprotective effect on retina at animal level and cell level.The results of basic research and clinical trials are not completely consistent,and the exact mechanism needs further research.This paper reviews the relationship between GLP-1RA and retinopathy,pays attention to the possible risk of retinopathy and the best use strategy.

[Summary]Glucagon-like peptide-1 receptor agonist(GLP-1RA)has been widely applied in clinic,and the possible correlation between GLP-1RA and the progression of retinopathy in clinical trials has attracted much attention.The existing basic research suggests that GLP-1RA has a certain neuroprotective effect on retina at animal level and cell level.The results of basic research and clinical trials are not completely consistent,and the exact mechanism needs further research.This paper reviews the relationship between GLP-1RA and retinopathy,pays attention to the possible risk of retinopathy and the best use strategy.

Thoracolumbar trauma, including fractures, dislocations and spinal cord injuries, often result from high-energy injuries such as traffic accidents and falls from heights. It not only causes severe pain and restricted movement for patients, but also leads to neurological damage and even permanent disability. Currently, the diagnosis and treatment of thoracolumbar trauma are faced with many problems, such as possible missed diagnosis and misdiagnosis, lack of individualized and standardized treatment plans, and lack of objective and quantitative metrics for postoperative assessment. Artificial intelligence (AI) technology offers innovative ideas to these problems. Among them, the core AI technology such as machine learning (ML), deep learning (DL), computer vision, and robotics has demonstrated outstanding capabilities in medical image analysis, clinical decision support, etc., which can significantly improve the diagnostic precision, surgical planning efficiency, and postoperative management level of thoracolumbar trauma. At present, application of AI technology in cross-modal data integration, clinical decision support, and long-term efficacy prediction in the field of thoracolumbar trauma remains to be systematically sorted out. To this end, the authors reviewed the research progress of AI technology in the diagnosis, treatment, and postoperative management of thoracolumbar trauma, providing a reference for a wide application of AI technology in the management of thoracolumbar trauma.

Thoracolumbar trauma, including fractures, dislocations and spinal cord injuries, often result from high-energy injuries such as traffic accidents and falls from heights. It not only causes severe pain and restricted movement for patients, but also leads to neurological damage and even permanent disability. Currently, the diagnosis and treatment of thoracolumbar trauma are faced with many problems, such as possible missed diagnosis and misdiagnosis, lack of individualized and standardized treatment plans, and lack of objective and quantitative metrics for postoperative assessment. Artificial intelligence (AI) technology offers innovative ideas to these problems. Among them, the core AI technology such as machine learning (ML), deep learning (DL), computer vision, and robotics has demonstrated outstanding capabilities in medical image analysis, clinical decision support, etc., which can significantly improve the diagnostic precision, surgical planning efficiency, and postoperative management level of thoracolumbar trauma. At present, application of AI technology in cross-modal data integration, clinical decision support, and long-term efficacy prediction in the field of thoracolumbar trauma remains to be systematically sorted out. To this end, the authors reviewed the research progress of AI technology in the diagnosis, treatment, and postoperative management of thoracolumbar trauma, providing a reference for a wide application of AI technology in the management of thoracolumbar trauma.

Objective:To explore the effect of continuous improvement model with Definition,Measure,Analyze,Improve,and Control(DMAIC)on the management for equipment of diagnosing and treating chronic respiratory diseases.Method:To address the management issues of diagnosis and treatment equipment for chronic respiratory diseases,multiple management strategies were formulated on the basis of definition,measurement,analysis,improvement and control stages of the DMAIC continuous improvement model.Selected 80 diagnostic and therapeutic equipment used at the department of respiratory in People's Hospital of Xinjiang Uygur Autonomous Region from August 2021 to July 2023.The conventional management method was used to manage them during August 2021 to July 2022,and the management method of DMAIC continuous improvement management model(continuous improvement management method)for chronic respiratory diseases was adopted to manage them during August 2022 to July 2023.The ratio of failure equipment,score of risk assessment,qualified rate of examination,and satisfaction score of users who operated equipment by using the two kinds of management methods were compared.Result:The average failure ratios of shutdown due to failure,injury that caused external environment,abnormal self-examination at power on,unqualified quality inspection,and poorly operational quality in treatment in equipment of diagnosing and treating respiratory disease by using continuous improvement management method were respectively(1.58±0.51)%,(0.34±0.10)%,(0.65±0.20)%,(2.08±0.53)%and(1.61±0.52)%,which were all lower than those by using conventional management method,and the differences of them were significant(t=14.512,11.205,24.354,17.169,17.663,P<0.05).The degree of detectability,severity,and probability scores of occurrence of the equipment by using continuous improvement management method were lower than those of conventional management method,and the differences were statistically significant(t=10.478,6.930,9.407,P<0.05).The qualified rate of equipment inspection of continuous improvement management method was higher than that of conventional management method,and the difference was statistically significant(x2=9.642,P<0.05).The performance,cleanliness of equipment,and timeliness scores of operators,who used equipment,for diagnosis and treatment equipment that were managed by using continuous improvement management method were all higher than those by using conventional management method,and the differences were statistically significant(t=2.204,2.268,2.604,P<0.05).Conclusion:The DMAIC continuous improvement management model method for equipment of diagnosing and treating chronic respiratory disease can significantly improve management level for equipment,and reduce failure risk of equipment,and increase the utilization efficiency of equipment and the users'satisfaction.

Abstract: Ulcerative colitis (UC) is a chronic intestinal disease caused by a variety of factors. Severe intestinal inflammation can also cause liver injury. Based on the previous research, microbial dysbiosis in the inflammatory state leads to the conversion of excess choline into trimethylamine (TMA) by the intestinal flora, which competes with the host for the use of the nutrient choline, and induces liver injury. 3, 3-dimethyl-1-butanol (DMB), a structural analogue of choline, can reduce TMA levels from choline conversion. The aim of this study was to investigate the protective effect and possible mechanism of DMB on UC and secondary liver injury. Dextran sulfate sodium-induced acute colitis model in mice was established. The weight of mice, and collected serum, liver and intestinal contents after mice sacrifice were measured. The morphological changes of colon and liver were observed; liver function was detected with the kit of biochemical indexes; UHPLC-MS/MS was applied to detect changes in choline metabolism in vivo. The experimental results showed that DMB could attenuate body weight loss index, improve colonic inflammation, and reduce liver injury in UC mice. The detection of choline-related metabolites in serum, intestinal contents and liver showed that DMB could effectively inhibit the production of trimethylamine in the intestine, improve the availability of host choline, effectively alleviate colitis deterioration, and reduce liver damage caused by severe intestinal lesions.