Moringa oleifera, widely utilized in Ayurvedic medicine, is recognized for its leaves, seeds, and velamen possessing traditional effects such as vātahara(wind alleviation), sirovirecaka(brain clearing), and hridya(mental nourishment). This study aims to identify the medicinal part of ■ in the Sārasvata ghee formulation as described in the Bower Manuscript, while investigating the ameliorative effects of different medicinal parts of M. oleifera on learning and memory deficits in mice and elucidating the underlying molecular mechanisms. A total of 144 male ICR mice were randomly assigned to the following groups: control, model(scopolamine hydrobromide, Sco, 2 mg·kg~(-1)), donepezil(donepezil hydrochloride, Don, 3 mg·kg~(-1)), M. oleifera leaf low-, medium-, and high-dose groups(0.5, 1, 2 g·kg~(-1)), M. oleifera seeds low-, medium-, and high-dose groups(0.25, 0.5, 1 g·kg~(-1)), and M. oleifera velamen low-, medium-, and high-dose groups(0.31, 0.62, 1.24 g·kg~(-1)). Learning and memory abilities were assessed using the passive avoidance test and Morris water maze. Nissl and HE staining were employed to examine histopathological changes in the hippocampus. Transcriptomics and targeted metabolomics were used to screen differential genes and metabolites, with MetaboAnalyst 6.0 and O2PLS methods applied to identify key disease-related targets and pathways. RESULTS:: demonstrated that M. oleifera leaf(1 g·kg~(-1)) significantly ameliorated Sco-induced learning and memory deficits, outperforming M. oleifera seeds(0.25 g·kg~(-1)) and M. oleifera velamen(1.24 g·kg~(-1)). This was evidenced by improved behavioral performance, reversal of neuronal damage, and reduced acetylcholinesterase(AChE) activity. Multi-omics analysis revealed that M. oleifera leaf upregulated Tuba1c gene expression through the synaptic vesicle cycle, enhancing glutamate(Glu), dopamine(DA), and acetylcholine(ACh) release via Tuba1c-Glu associations for neuroprotection. M. oleifera seeds targeted the dopaminergic synapse pathway, promoting memory consolidation through Drd2-ACh associations. M. oleifera velamen was associated with the cocaine addiction pathway, modulating dopamine metabolism via Adora2a-DOPAC, with limited relevance to learning and memory. In conclusion, M. oleifera leaf exhibits superior efficacy and mechanistic advantages over M. oleifera seeds and velamen, suggesting that the ■ in the Sārasvata ghee formulation is likely M. oleifera leaf, providing scientific evidence for its identification in ancient texts.
Animals ; Moringa oleifera/chemistry* ; Male ; Mice ; Seeds/chemistry* ; Plant Leaves/chemistry* ; Mice, Inbred ICR ; Memory Disorders/psychology* ; Transcriptome/drug effects* ; Memory/drug effects* ; Learning/drug effects* ; Metabolomics ; Humans ; Drugs, Chinese Herbal/administration & dosage* ; Maze Learning/drug effects*

OBJECTIVE: To evaluate the clinical efficacy and safety of Yangxue Qingnao Pills (YXQNP) combined with amlodipine in treating patients with grade 1 hypertension. METHODS: This is a multicenter, randomized, double-blind, and placebo-controlled study. Adult patients with grade 1 hypertension of blood deficiency and Gan (Liver)-yang hyperactivity syndrome were randomly divided into the treatment or the control groups at a 1:1 ratio. The treatment group received YXQNP and amlodipine besylate, while the control group received YXQNP's placebo and amlodipine besylate. The treatment duration lasted for 180 days. Outcomes assessed included changes in blood pressure, Chinese medicine (CM) syndrome scores, symptoms and target organ functions before and after treatment in both groups. Additionally, adverse events, such as nausea, vomiting, rash, itching, and diarrhea, were recorded in both groups. RESULTS: A total of 662 subjects were enrolled, of whom 608 (91.8%) completed the trial (306 in the treatment and 302 in the control groups). After 180 days of treatment, the standard deviations and coefficients of variation of systolic and diastolic blood pressure levels were lower in the treatment group compared with the control group. The improvement rates of dizziness, headache, insomnia, and waist soreness were significantly higher in the treatment group compared with the control group (P<0.05). After 30 days of treatment, the overall therapeutic effects on CM clinical syndromes were significantly increased in the treatment group as compared with the control group (P<0.05). After 180 days of treatment, brachial-ankle pulse wave velocity, ankle brachial index and albumin-to-creatinine ratio were improved in both groups, with no statistically significant differences (P>0.05). No serious treatment-related adverse events occurred during the study period. CONCLUSIONS Combination therapy of YXQNP with amlodipine significantly improved symptoms such as dizziness and headache, reduced blood pressure variability, and showed a trend toward lowering urinary microalbumin in hypertensive patients. These findings suggest that this regimen has good clinical efficacy and safety. (Registration No. ChiCTR1900022470).
Humans ; Amlodipine/adverse effects* ; Drugs, Chinese Herbal/adverse effects* ; Male ; Female ; Hypertension/complications* ; Middle Aged ; Treatment Outcome ; Drug Therapy, Combination ; Adult ; Blood Pressure/drug effects* ; Double-Blind Method ; Aged ; Antihypertensive Agents/adverse effects*

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

Objective To optimize the design of the existing water conductivity control system for pharmaceutical water equipment of full membrane process so as to solve its problems in precision and long cycle time due to water source,ambient temperature and intermittent working mode.Methods The optimized water conductivity control system was composed of an alkali metering pump,a conductivity sensor and a programmable logic controller(PLC),which used a fuzzy proportional-integral-derivative(PID)controller to regulate the water conductivity of pharmaceutical water equipment of full membrane process,and the particle swarm optimization(PSO)algorithm to optimize the parameters of the fuzzy PID controller.A simulation model was established with MATLAB software to verify the performance of the optimized control system.Results Simulation results showed the optimized control system had reductions in overshoot(by 19％)and adjustment time(by 29％)when compared with the fuzzy PID control system,and enhanced control efficiency effectively.Conclusion The optimized control system optimized by the PSO algorithm improves the quality of produced water,and can meet the demands for rapid and safe production of pharmaceutical water by pharmaceutical water equipment of full membrane process in different conditions.[Chinese Medical Equipment Journal,2025,46(6):14-19]

Objective To investigate the effect of miR-185-5p-mediated targeted negative regulation of transmembrane 9 superfamily member 1(TM9SF1)on proliferation,migration and autophagy in lung adenocarcinoma cells.Methods The expression of miR-185-5p in lung adenocarcinoma tissues was analyzed using dataset GSE51853 downloaded from the Gene Expression Omnibus(GEO)database.Potential target proteins of miR-185-5p were predicted using online databases(miRTargetLink,miRTarbase,and DIANA-microT-CD),and autophagy-related proteins were obtained from HADb.The intersected results from these four databases was identified,and survival curves of vascular endothelial growth factor A(VEGFA)and TM9SF1 within the overlapping candidates were analyzed using the StarBase database.TM9SF1 3'UTR wild-type(WT)or TM9SF1 3'UTR mutant(MUT)reporter plasmids were separately co-transfected with miR-185-5p control plasmid(CON)or miR-185-5p overexpression plasmid(over-miR-185-5p)into HEK-293T cells.A dual-luciferase reporter gene assay was employed to assess the binding interaction between miR-185-5p and TM9SF1 and quantify the subsequent luciferase activity.Western blotting was used to assess TM9SF1 protein expression levels in A549 cells transfected with over-miR-185-5p.A549 cells were divided into three groups:(1)CON+NC group,co-transfected with miR-185-5p control plasmid and TM9SF1 control plasmid;(2)over-miR-185-5p+NC group,co-transfected with over-miR-185-5p and TM9SF1 control plasmid;(3)over-miR-185-5p+over-TM9SF1 group,co-transfected with both miR-185-5p and TM9SF1 overexpression plasmids.EdU cell proliferation assay,wound healing assay,and Transwell migration assay were performed to validate the effects of miR-185-5p targeted binding to TM9SF1 on proliferation and migration capacities in lung adenocarcinoma.Changes in autophagic flux and mitochondrial membrane potential(MMP)of lung adenocarcinoma cells were detected using stubRFP-sensGFP-LC3 lentivirus and JC-1 assays,respectively.Results In the GSE51853 dataset,miR-185-5p expression level was significantly lower in lung adenocarcinoma tissues compared with normal lung tissues(P<0.01).qRT-PCR analysis revealed that miR-185-5p expression was downregulated in lung adenocarcinoma cell lines NCI-H1299 and A549 compared with normal lung epithelial cells BEAS-2B(P<0.01).Bioinformatics predictions using miRTargetLink,miRTarbase,DIANA-microT-CD,and HADb databases indicated that miR-185-5p could target and regulate the autophagy-related protein TM9SF1.Dual-luciferase reporter assays and Western blotting demonstrated that miR-185-5p directly bound to the 3'UTR region of TM9SF1 mRNA,and overexpression of miR-185-5p significantly reduced the expression of target protein TM9SF1(P<0.05).EdU cell proliferation,wound healing,and Transwell migration assays demonstrated that miR-185-5p overexpression inhibited proliferation and migration capacities of lung adenocarcinoma cells,whereas TM9SF1 overexpression could attenuate this inhibition effect(P<0.05).Results of stubRFP-sensGFP-LC3 for autophagic flux analysis demonstrated that overexpression of miR-185-5p enhanced autophagic flux in A549 cells,whereas co-overexpression of miR-185-5p and TM9SF1 suppressed autophagic flux.JC-1 assays showed a decreased MMP level in A549 cells after miR-185-5p overexpression,with higher MMP level observed when miR-185-5p and TM9SF1 were co-overexpressed.Conclusion miR-185-5p may suppress proliferation,migration,and autophagy capacities in lung adenocarcinoma cells by targeting TM9SF1 through negative regulation.

BACKGROUND:The pathogenesis of inflammatory bowel disease involves inflammation,immune activation,visceral hypersensitivity,and dysbiosis of the gut microbiota.Inflammation promotes the release of inflammatory mediators by immune cells,damaging the enteric nervous system.Enteric glial cells are an important component of the intestinal nervous system and are excellent cells for studying intestinal neuroinflammation.Primary enteric glial cells play a crucial role in exploring cell therapies for intestinal nervous system diseases.Currently,the methods for obtaining these cells are mostly cumbersome.Therefore,finding a convenient and fast method for extracting this cell is crucial.OBJECTIVE:To establish a method for optimizing the isolation,culture,and identification of mouse enteric glial cells.METHODS:0-7-day-old C57BL/6 neonatal mice were euthanized by excessive inhalation of isoflurane.After soaking in 75％alcohol for disinfection,the duodenum(1 cm below the pylorus to 1 cm above the Qu's ligament)was removed by laparotomy at the midline of the abdomen.A 1 mL syringe was filled with DPBS and the intestinal contents were repeatedly rinsed until the intestine became translucent,and the mesentery and blood vessels were peeled off.The duodenum was cut to a size of 1 mm and digested in 0.25％EDTA trypsin for 20 minutes.Then an equal amount of DMEM/F12 complete culture medium was added to terminate digestion.The liquid was filtered through a 100 μm cell filter,centrifuged,and the cells were resuspended in 1 mL of DMEM/F12 complete culture medium.When the cell adhesion growth density reached 80％,cells were digested for subculture.When cells were cultured to the third generation,glial fibrillary acid protein labeled with enteric glial cells was used for identification by immunofluorescence method.RESULTS AND CONCLUSION:The isolated and cultured cells were full of colloids,with protrusions extending outward and passable.Glial fibrillary acid protein staining was positive.This method can successfully isolate and culture enteric glial cells and is easy to operate,providing a stable model for the study of the pathophysiology of the enteric nervous system.

Objective To investigate the efficacy of an interpretable integrated learning model combining clinical indicators,CT image features and radiomics features for the differential diagnosis of lung squamous cell carcinoma and adenocarcinoma,so as to provide references for clincal treatment decisions.Methods A retrospective analysis was conducted on clinical and imaging data from 220 patients(231 lesions)with primary non-small cell lung cancer at Jiangjin Central Hospital of Chongqing(Center 1)and 83 patients(84 lesions)at Chongqing General Hospital(Center 2).In Center 1,the squamous cell carcinoma group consisted of 60 patients(60 lesions),while the adenocarcinoma group included 160 patients(171 lesions).In Center 2,the squamous cell carcinoma group comprised 18 patients(18 lesions),and the adenocarcinoma group involved 65 patients(66 lesions).The patients were categorized into squamous cell carcinoma and adenocarcinoma groups based on pathological findings.Center 1 was randomly partitioned into a training set and a validation set at a 7∶3 ratio,while Center 2 served as the independent test set.Firstly,a deep learning model,VB-Net,was used to automatically segment the tumor region on the lung window image;secondly,the SMOTE(synthetic minority oversampling technique)method was used to balance the categories in the training set and standardize the extracted features with Z-scores;thirdly,the least absolute shrinkage and selection operator(LASSO)were used to select the optimal radiomics features and calculate the radiomics score(Radscore),and univariate and multivariate logistic regression was used to screen clinical indicators and independent clinical factors for differentiating lung squamous cell carcinoma and adenocarcinoma in CT image features;finally,three ensemble learning algorithms(AdaBoost,Bagging decision tree and XGBoost)were used to combine independent clinical factors and Radscore to construct the model.The receiver operating characteristic(ROC)curve was used to evaluate the diagnostic performance of the models.SHAP technique was used to analyze the feature contribution and model decision-making process.Results Among the evaluated ensemble models,AdaBoost and Bagging decision trees demonstrated overfitting tendencies.In contrast,the XGBoost model showed the best performance,achieving AUC values of 0.939,0.887 and 0.853 in the training,validation and independent test sets,respectively.SHAP indicated that Radscore was the most important feature affecting the performance of the model.The decision diagram enabled the visualization of the diagnostic process of the model.Conclusion The interpretable integrated learning model based on clinical indicators,CT image and radiomics features is expected to non-invasively diagnose lung squamous cell carcinoma and adenocarcinoma before treatment and assist clinicians make treatment decisions as early as possible.[Chinese Medical Equipment Journal,2025,46(7):12-20]

Objective To optimize the design of the existing water conductivity control system for pharmaceutical water equipment of full membrane process so as to solve its problems in precision and long cycle time due to water source,ambient temperature and intermittent working mode.Methods The optimized water conductivity control system was composed of an alkali metering pump,a conductivity sensor and a programmable logic controller(PLC),which used a fuzzy proportional-integral-derivative(PID)controller to regulate the water conductivity of pharmaceutical water equipment of full membrane process,and the particle swarm optimization(PSO)algorithm to optimize the parameters of the fuzzy PID controller.A simulation model was established with MATLAB software to verify the performance of the optimized control system.Results Simulation results showed the optimized control system had reductions in overshoot(by 19％)and adjustment time(by 29％)when compared with the fuzzy PID control system,and enhanced control efficiency effectively.Conclusion The optimized control system optimized by the PSO algorithm improves the quality of produced water,and can meet the demands for rapid and safe production of pharmaceutical water by pharmaceutical water equipment of full membrane process in different conditions.[Chinese Medical Equipment Journal,2025,46(6):14-19]

BACKGROUND:The pathogenesis of inflammatory bowel disease involves inflammation,immune activation,visceral hypersensitivity,and dysbiosis of the gut microbiota.Inflammation promotes the release of inflammatory mediators by immune cells,damaging the enteric nervous system.Enteric glial cells are an important component of the intestinal nervous system and are excellent cells for studying intestinal neuroinflammation.Primary enteric glial cells play a crucial role in exploring cell therapies for intestinal nervous system diseases.Currently,the methods for obtaining these cells are mostly cumbersome.Therefore,finding a convenient and fast method for extracting this cell is crucial.OBJECTIVE:To establish a method for optimizing the isolation,culture,and identification of mouse enteric glial cells.METHODS:0-7-day-old C57BL/6 neonatal mice were euthanized by excessive inhalation of isoflurane.After soaking in 75％alcohol for disinfection,the duodenum(1 cm below the pylorus to 1 cm above the Qu's ligament)was removed by laparotomy at the midline of the abdomen.A 1 mL syringe was filled with DPBS and the intestinal contents were repeatedly rinsed until the intestine became translucent,and the mesentery and blood vessels were peeled off.The duodenum was cut to a size of 1 mm and digested in 0.25％EDTA trypsin for 20 minutes.Then an equal amount of DMEM/F12 complete culture medium was added to terminate digestion.The liquid was filtered through a 100 μm cell filter,centrifuged,and the cells were resuspended in 1 mL of DMEM/F12 complete culture medium.When the cell adhesion growth density reached 80％,cells were digested for subculture.When cells were cultured to the third generation,glial fibrillary acid protein labeled with enteric glial cells was used for identification by immunofluorescence method.RESULTS AND CONCLUSION:The isolated and cultured cells were full of colloids,with protrusions extending outward and passable.Glial fibrillary acid protein staining was positive.This method can successfully isolate and culture enteric glial cells and is easy to operate,providing a stable model for the study of the pathophysiology of the enteric nervous system.

Objective To investigate the efficacy of an interpretable integrated learning model combining clinical indicators,CT image features and radiomics features for the differential diagnosis of lung squamous cell carcinoma and adenocarcinoma,so as to provide references for clincal treatment decisions.Methods A retrospective analysis was conducted on clinical and imaging data from 220 patients(231 lesions)with primary non-small cell lung cancer at Jiangjin Central Hospital of Chongqing(Center 1)and 83 patients(84 lesions)at Chongqing General Hospital(Center 2).In Center 1,the squamous cell carcinoma group consisted of 60 patients(60 lesions),while the adenocarcinoma group included 160 patients(171 lesions).In Center 2,the squamous cell carcinoma group comprised 18 patients(18 lesions),and the adenocarcinoma group involved 65 patients(66 lesions).The patients were categorized into squamous cell carcinoma and adenocarcinoma groups based on pathological findings.Center 1 was randomly partitioned into a training set and a validation set at a 7∶3 ratio,while Center 2 served as the independent test set.Firstly,a deep learning model,VB-Net,was used to automatically segment the tumor region on the lung window image;secondly,the SMOTE(synthetic minority oversampling technique)method was used to balance the categories in the training set and standardize the extracted features with Z-scores;thirdly,the least absolute shrinkage and selection operator(LASSO)were used to select the optimal radiomics features and calculate the radiomics score(Radscore),and univariate and multivariate logistic regression was used to screen clinical indicators and independent clinical factors for differentiating lung squamous cell carcinoma and adenocarcinoma in CT image features;finally,three ensemble learning algorithms(AdaBoost,Bagging decision tree and XGBoost)were used to combine independent clinical factors and Radscore to construct the model.The receiver operating characteristic(ROC)curve was used to evaluate the diagnostic performance of the models.SHAP technique was used to analyze the feature contribution and model decision-making process.Results Among the evaluated ensemble models,AdaBoost and Bagging decision trees demonstrated overfitting tendencies.In contrast,the XGBoost model showed the best performance,achieving AUC values of 0.939,0.887 and 0.853 in the training,validation and independent test sets,respectively.SHAP indicated that Radscore was the most important feature affecting the performance of the model.The decision diagram enabled the visualization of the diagnostic process of the model.Conclusion The interpretable integrated learning model based on clinical indicators,CT image and radiomics features is expected to non-invasively diagnose lung squamous cell carcinoma and adenocarcinoma before treatment and assist clinicians make treatment decisions as early as possible.[Chinese Medical Equipment Journal,2025,46(7):12-20]