BACKGROUND:Deep muscle stimulation has the effects of releasing muscle adhesion,relieving muscle spasm,improving and restoring muscle compliance and elasticity.Electromyographic biofeedback therapy can promote nerve recovery and improve lower limb motor function and gait. OBJECTIVE:To observe the effect of the effect of deep muscle stimulation combined with electromyographic biofeedback therapy on the spasm of the triceps surae and gait changes after stroke by using a digital muscle detector and three-dimensional gait analysis system. METHODS:A total of 72 patients who met the inclusion criteria were selected from the Rehabilitation Department of the First Affiliated Hospital of Guangdong Pharmaceutical University from October 2020 to October 2023.And they were enrolled and randomly divided into two groups(n=36 per group):a control group and a combined group.The control group received routine rehabilitation therapies,electromyographic biofeedback and pseudo deep muscle stimulation,while the combined group received true deep muscle stimulation treatment on the basis of the control group,five times per week,for 4 consecutive weeks.The oscillation frequency and dynamic stiffness of the affected gastrocnemius muscle,active range of motion of the ankle dorsiflexion muscle,electromyographic signal of the tibialis anterior muscle,Fugl-Meyer assessment of the lower limbs,and three-dimensional gait analysis parameters were statistically analyzed before and after treatment in two groups. RESULTS AND CONCLUSION:After treatment,oscillation frequency and dynamic stiffness values of the inner and outer sides of the affected gastrocnemius muscle in both groups of patients were significantly reduced compared with before treatment(P<0.05),and the combined group showed a more significant decrease compared with the control group(P<0.05).The active range of motion of the ankle dorsiflexion muscle,electromyographic signal of the tibialis anterior muscle,and Fugl-Meyer scores after treatment were significantly increased or improved compared with before treatment(P<0.05),while the combined group showed a more significant increase or improvement compared with the control group(P<0.05).In terms of gait parameters,the walking speed,frequency,and stride in both groups of patients were significantly increased compared with before treatment(P<0.05),while the combined group showed a more significant increase compared with the control group(P<0.05).The percentage time of support phase on the healthy side was shortened compared with before treatment(P<0.05),while the combined group showed a more significant decrease compared with the control group(P<0.05).In addition,there was no significant difference between the two groups except for the percentage of healthy side support(P>0.05).To conclude,the combination of deep muscle stimulation and electromyographic biofeedback can effectively alleviate triceps spasm in the short term after stroke,improve ankle dorsiflexion function,enhance lower limb motor function,and improve gait.The treatment effect is significant and worthy of clinical promotion and application.

Objective To construct a "disease-syndrome combination" mathematical representation model for pulmonary nodules based on oral microbiome data, utilizing a multimodal data algorithm framework centered on dynamic systems theory. Furthermore, to compare predictive models under various algorithmic frameworks and validate the efficacy of the optimal model in predicting the presence of pulmonary nodules. Methods A total of 213 subjects were prospectively enrolled from July 2022 to March 2023 at the Hospital of Chengdu University of Traditional Chinese Medicine, Sichuan Cancer Hospital, and the Chengdu Integrated Traditional Chinese and Western Medicine Hospital. This cohort included 173 patients with pulmonary nodules and 40 healthy subjects. A novel multimodal data algorithm framework centered on dynamic systems theory, termed VAEGANTF (Variational Auto Encoder-Generative Adversarial Network-Transformer), was proposed. Subsequently, based on a multi-dimensional integrated dataset of “clinical features-syndrome elements-microorganisms”, all subjects were divided into training (70%) and testing (30%) sets for model construction and efficacy testing, respectively. Using pulmonary nodules as dependent variables, and combining candidate markers such as clinical features, lesion location, disease nature, and microbial genera, the independent variables were screened based on variable importance ranking after identifying and addressing multicollinearity. Missing values were then imputed, and data were standardized. Eight machine learning algorithms were then employed to construct pulmonary nodule risk prediction models: random forest, least absolute shrinkage and selection operator (LASSO) regression, support vector machine, multilayer perceptron, eXtreme Gradient Boosting (XGBoost), VAE-ViT (Vision Transformer), GAN-ViT, and VAEGANTF. K-fold cross-validation was used for model parameter tuning and optimization. The efficacy of the eight predictive models was evaluated using confusion matrices and receiver operating characteristic (ROC) curves, and the optimal model was selected. Finally, goodness-of-fit testing and decision curve analysis (DCA) were performed to evaluate the optimal model. Results There were no statistically significant differences between the two groups in demographic characteristics such as age and sex. The 213 subjects were randomly divided into training and testing sets (7 : 3), and prediction models were constructed using the eight machine learning algorithms. After excluding potential problems such as multicollinearity, a total of 301 clinical feature information, syndrome elements, and microbial genera markers were included for model construction. The area under the curve (AUC) values of the random forest, LASSO regression, support vector machine, multilayer perceptron, and VAE-ViT models did not reach 0.85, indicating poor efficacy. The AUC values of the XGBoost, GAN-ViT, and VAEGANTF models all reached above 0.85, with the VAEGANTF model exhibiting the highest AUC value (AUC=0.923). Goodness-of-fit testing indicated good calibration ability of the VAEGANTF model, and decision curve analysis showed a high degree of clinical benefit. The nomogram results showed that age, sex, heart, lung, Qixu, blood stasis, dampness, Porphyromonas genus, Granulicatella genus, Neisseria genus, Haemophilus genus, and Actinobacillus genus could be used as predictors. Conclusion The “disease-syndrome combination” risk prediction model for pulmonary nodules based on the VAEGANTF algorithm framework, which incorporates multi-dimensional data features of “clinical features-syndrome elements-microorganisms”, demonstrates better performance compared to other machine learning algorithms and has certain reference value for early non-invasive diagnosis of pulmonary nodules.

A patient with osteomyelitis who developed a rash after previous treatment with vancomycin was admitted to the hospital due to a recurrence of osteomyelitis.After admission,the orthopedic doctor intended to perform a"calcium sulfate vancomycin implantation surgery"on him.Clinical pharmacist identified the patient's previous rash reaction as red man syndrome(RMS)rather than genuine drug allergy.At the same time,in response to the clinical doubt of whether patients with previous RMS can undergo"calcium sulfate vancomycin implantation surgery",clinical pharmacists reviewed and analyzed the literature,and suggested that the surgery can continue under close monitoring.The patient did not experience RMS or allergic reactions after surgery,and the condition improved.In this paper,the clinical pharmacists started with the identification of RMS and rapid allergic reactions,reviewed the literature on the local use of vancomycin and the risk of RMS,and provide suggestions for subsequent treatment,and also provide references for clinical safe drug use and treatment of similar diseases.

Objective To investigate the distribution and antimicrobial resistance of the bacterial strains isolated from blood samples of inpatients in Longgang Hospital,Beijing University of Chinese Medicine.Methods The bacterial identification and antimicrobial susceptibility test results for the strains isolated from 2018 to 2022 were retrospectively analyzed.Results A total of 910 strains of bacteria were isolated from blood samples,of which 63.2％(575/910)were gram-negative bacteria and 36.8％(335/910)were gram-positive bacteria.Escherichia coli,coagulase-negative Staphylococcus,Klebsiella pneumoniae,Staphylococcus aureus,and Enterococcus spp.were the top 5 pathogens.In the past 5 years,no carbapenem-resistant strains of E.coli or K.pneumoniae were found in the blood samples of the inpatients.A.baumannii had a resistance rate of 11.8％to carbapenems.The prevalence of methicillin-resistant strains in S.aureus,S.epidermidis and other Staphylococcus species was 16.7％,75.0％and 55.5％,respectively.No vancomycin-or linezolid-resistant staphylococcual isolates were found.No strains of Enterococcus faecalis or Enterococcus faecium were found resistant to high concentrations of gentamicin,linezolid,or vancomycin.Conclusions The bacteria isolated from blood samples in Longgang Hospital were mainly gram-negative bacteria.Carbapenem-resistant strain was identified in the strains of A.baumannii.Bacterial resistance surveillance should be strengthened for the isolates from blood samples and other specimens from the site of infection.Antimicrobial agents should be used rationally to prevent the spread of drug-resistant bacteria.

Objective In this study,we aimed to use network pharmacology techniques to predict the key targets of a prescription of Ziziphi spinosae semen formula(ZSSF)compound for depression,and to verify its mechanism of action using a zebrafish model of rifampicin-induced depression.Methods The drug targets of ZSSF were retrieved from the TCMSP database,and the target names were corrected using the UniProt database.Depression-related targets were identified using the GeneCards,OMIM,and NCBI databases.Protein-protein interaction information for the shared targets was predicted using the STRING database.The collected data were then analyzed using the Metascape database to determine GO and KEGG pathway enrichment,and the result were visualized using microbiotics.Behavioral experiments and reverse-transcription quantitative PCR experiments were conducted to verify the therapeutic effects of ZSSF on a zebrafish depression model induced by risperdal.Results 188 targets were screened to find the interactions between depression and ZSSF.The protein-protein interaction result showed that ZSSF primarily targeted TNF-α,IL-2,IL-6,IL-1β,and IL-10 to produce its antidepressant effect.KEGG pathway enrichment analysis revealed that ZSSF exerted its effects on depression through various signaling pathways,including the TNF,PI3K-Akt,and cGMP-PKG signaling pathways.The result of the animal experiments showed that the treatment groups given high,medium,and low doses of ZSSF exhibited significant improvements in movement distance under acoustic and light stimulation compared with the model group(P＜0.05).The speed of movement of the treatment groups was also significantly faster(P＜0.01).Additionally,the mRNA expression levels of TNF-α,IL-2,IL-6,IL-1β,and IL-10 were up-regulated in the brain tissues of zebrafish in the high-,medium-,and low-dosage groups of ZSSF compared those in the model group(P＜0.001).Conclusions ZSSF exerts its antidepressant effect through multiple components and targets,and its antidepressant effects may be associated with its inhibition of inflammatory factors.

Objective To investigate the effects of alcoholic extract of Hemerocallis citrina Baroni on the depressive-like behaviors in zebrafish larvae(Danio rerio)induced by reserpine.Methods Zebrafish larvae were divided into various groups:control(Con)group,reserpine group,fluoxetine group,H.citrina alcohol extract(HCE)low dose group(1.5 mg/L),HCE medium dose group(3 mg/L),and HCE high dose group(4.5 mg/L).Depressive-like behaviors were analyzed using sound and light stimulation.Real-time PCR was used to investigate the effects of HCE on depression related astrocyte markers(GFAP,C3,C4B,EMP-1,S100α-10)and the neurotrophic factor BDNF and its receptor genes(P75,TrkB).Results In comparison to the control group,the model group demonstrated significantly shorter movement distance and reduced movement time under sound and light stimulation(P＜0.05,P＜0.001,P＜0.0001).Following the administration of HCE,zebrafish larvae exhibited significantly heightened sensitivity to light and sound stimulation compared to the model group(P＜0.05,P＜0.0001).Astrocyte marker genes were up-regulated in the model group zebrafish brains compared to the control group(P＜0.0001).However,when the model group was administered HCE,the expression of astrocyte markers was significantly down-regulated compared to the model group(P＜0.0001).Neurotrophic factor and its receptor genes(BDNF,P75,TrkB)were down-regulated in zebrafish brains in the model group compared to those in the control group(P＜0.0001).However,in the group administered HCE,the expression of BDNF,P75,and TrkB was significantly up-regulated compared to that in the model group(P＜0.01,P＜0.0001).These findings suggest that HCE suppressed the inflammatory responses caused by astrocyte activation and promoted the production of neurotrophic factors and their receptor genes,thereby exerting an ameliorative effect on depression.Conclusions Alcoholic extracts of H.citrina can ameliorate the depression-like behavioral changes induced by reserpine in zebrafish larvae.They reduce the expression of astrocyte markers in the zebrafish brain and promote the production of neurotrophic factors and their receptor genes,playing an antidepressant role.

Objective To examine the hypoglycemic effect of Chinese yam polysaccharide on the 3T3-L1 insulin resistance cell model.Methods IR-3T3-L1 adipocytes were randomly divided into control group(Con),model group(DEX),metformin group(Met,positive drug group)and CYPS group(0.05,0.15,0.45 mg/mL).After the creation of the IR-3T3-L1 cell model by dexamethasone(DEX)(1 μmol/L)stimulation,Chinese yam polysaccharide treatment was applied.Glucose intake and the levels of TC,TG,LDL-C,HDL-C,GSH-Px,MDA,HK,and PK were then measured.AMPK-PI3K/Akt signaling pathway-associated gene expression was identified using qRT-PCR.Results The glucose consumption of IR-3T3-L1 cells was considerably decreased after 48 hours of treatment with 1 μmol/L DEX compared to that of the Con group(P＜0.01),and the reduction persisted for 60 hours.0.05,0.15,0.45 mg/mL CYPS treatment significantly increased glucose consumption(P＜0.01),HK,PK,GSH-Px enzyme activities(P＜0.01),HDL-C content(P＜0.01),and decreased MDA enzyme activity(P＜0.01),T-CHO,TG,LDL-C content(P＜0.01)in IR-3T3-L1 cells.01).Additionally,CYPS administration dramatically decreased PI3K,Akt,GLUT-4,AMPK,IRS-2,PPARa,and adiponectin mRNA expression levels(P＜0.05)and reduced IRS-1,GSK-3β,ACC,and FAS mRNA expression levels(P＜0.01).Conclusions In IR-3T3-L1 cells,CYPS can reduce oxidative stress,control lipid metabolism disorders,and enhance DEX-induced glucose intake.AMPK-PI3K/Akt signaling pathway-associated genes may be connected to the process.

Objective:To develop standards of hospice care specialized clinical training base for general practitioners.Methods:Twenty nine experts in fields of general practice and hospice care were invited to participate in two rounds of Delphi expert consultation from April 2022 to August 2022. Based the results of Delphi consultations the standards of clinical training base for general practitioner hospice care specialized training were developed through data analysis, synthesis and process.Results:The age of 29 consulting experts was (52.9±8.9) years old, and their working years were (17.0±7.2) years, 69.0% (20/29) of them had senior professional titles. In the two rounds of expert consultation, the expert positive coefficient was 100.0% (29/29) and 96.6% (28/29), the expert authority coefficient was 0.791 and 0.830, and the expert opinion coordination coefficient W of the importance of all indicators was 0.177 and 0.296, respectively ( χ2=133.54 , 223.46; P<0.01). Finally, a set of clinical base standards for general practitioner hospice care specialized training was established, which consisted of 4 first-level indicators and 23 second-level indicators. The 4 first-level indicators were basic conditions, teaching conditions, teacher conditions and teaching management, with the weight coefficients of 0.250, 0.250, 0.251 and 0.253, respectively. Conclusions:The clinical training base standards of hospice care specialized training for general practitioners have been established in this study, which will be helpful in selecting appropriate hospitals as the specialized clinical training base for general practitioners.

Objective:To develop standards of hospice care community training base for general practitioners.Methods:Twenty-nine experts in general practice and hospice care from different teaching hospitals and community health service centers were invited to participate in two rounds of Delphi consultation from April to August 2022. Based on the consultations a set of standards of hospice care community training base was developed.Results:The age of experts was 38-75 (52.9±8.9) years, and their working years were 5-32 (17.0±7.2)years. In the two rounds of expert consultation, the expert positive coefficient was 100.0% (29/29) and 96.6% (28/29), the expert authority coefficient was 0.791 and 0.830, and the expert opinion coordination coefficient W of the importance of all indicators was 0.137 and 0.289, respectively ( χ2=114.83, 226.94; P<0.05). A set of hospice care community training base standards for general practitioner was established, which consisted of 4 first-level indicators and 27 second-level indicators. The 4 first-level indicators were basic conditions, teaching conditions, teacher conditions and teaching management, with the weight coefficients of 0.247, 0.248, 0.250 and 0.252, respectively. Conclusion:The standards developed in this study may be used for constructing and evaluating hospice care community training base for general practitioners.

Objective:To investigate the expression of heterogeneous nuclear ribonucleoprotein A2B1 (HNRNPA2B1) in human esophageal cancer tissues and its clinical significance.Methods:Single-cell data for esophageal cancer were downloaded from the Gene Expression Omnibus (GEO) database (GSE160269 dataset, last updated on November 29, 2020) to analyze the expression of HNRNPA2B1. Transcriptional sequencing data for esophageal cancer from The Cancer Genome Atlas (TCGA) database, including the fragments per kilobase of transcript per million mapped reads (FPKM) quantitative data (173 samples, consisting of 162 esophageal cancer tissues and 11 adjacent normal tissues), and survival data in the phenotype category were downloaded. Analysis of FPKM quantitative data from the TCGA database for esophageal cancer was performed. The top 250 genes most correlated with HNRNPA2B1 were selected and the R4.3.0 clusterProfiler package was used to conduct Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses on the selected gene set. FPKM quantitative data from the TCGA database for esophageal cancer were imported into the CIBERSORTx website to obtain immune cell abundance scores, and the correlation between HNRNPA2B1 and the degree of immune cell infiltration was analyzed. The clinicopathological data of patients from esophageal cancer tissue microarrays including 114 cases of esophageal squamous cell carcinoma tissues and 66 cases of adjacent normal tissues were collected. The patients underwent surgery from January 2006 to December 2008, and the follow-up period extended until July 2015. Cytokeratin (CK) and HNRNPA2B1 expression in esophageal cancer tissue microarrays were detected by using multi-color immunohistochemical (mIHC) staining, and multispectral tissue imaging was conducted. The R4.3.0 survival package and survminer package in TCGA database were used to calculate the optimal cut-off value of HNRNPA2B1 expression and the proportion of CK + HNRNPA2B1 + cells in tissue microarrays was used to calculate the cut-off value of HNRNPA2B1 expression based on which patients were categorized into high and low expression groups. The overall survival (OS) of both groups was compared and the factors influencing OS were analyzed by using the Cox proportional hazards model. Results:In the GSE160269 dataset of single-cell data for esophageal cancer, the expression level of HNRNPA2B1 in tumor epithelial cells was higher than that in normal epithelial cells, and HNRNPA2B1 was highly expressed in various immune cell subtypes. The high expression level of HNRNPA2B1 was positively correlated with regulatory T cells, naive B cells and memory CD4 + T cells. GO enrichment analysis revealed that HNRNPA2B1 was primarily involved in the biological process of nuclear division, cellular components were mainly enriched in chromosomal regions, and molecular functions were mainly enriched in ATP hydrolysis activity. KEGG enrichment analysis indicated that HNRNPA2B1 was primarily involved in biological processes such as the cell cycle, spliceosome, and DNA replication. Results from mIHC and multispectral tissue imaging demonstrated that CK was predominantly expressed in the cell membranes of tumor cells and normal esophageal epithelial cells, while HNRNPA2B1 was primarily expressed in the nuclei of tumor cells and normal esophageal cells. The expression level of HNRNPA2B1 in esophageal cancer tissues was higher than that in the normal paracancerous tissues ( U = 2 984.00, P < 0.05). Results of tissue microarrays and the survival analysis on the data in the TCGA database indicated that esophageal cancer patients with low HNRNPA2B1 expression had a better OS compared to those with high expression (both P < 0.05). Cox multivariate regression analysis revealed that age ( HR = 1.919, 95% CI: 1.158-3.182, P = 0.011), TNM stage ( HR = 2.404, 95% CI: 1.374-4.207, P = 0.002), T stage ( HR = 2.349, 95% CI: 1.150-4.789, P = 0.019), and the expression of HNRNPA2B1 in tumor epithelial cells ( HR = 2.160, 95% CI: 1.280-3.647, P = 0.004) were independent factors influencing OS in esophageal cancer patients. Conclusions:The high expression of HNRNPA2B1 protein in esophageal cancer tissues may play a role in the developement and progression of esophageal cancer, serving as a crucial biological indicator for prognostic assessment of esophageal cancer.