Based on LI Gao's Academic Thought， focusing on the process of qi transformation and taking the regulation and restoration of metabolism and immunity as the entry point， a "source-pivot-convergence" diagnostic and therapeutic model for malignant tumors is constructed. In this model， spleen and stomach internal injury is the source of malignant tumor occurrence， while the disorder of ascending and descending is the pivot of the disease development， and the generation of yin fire is the convergence of malignant tumor progression. Based on this， the three major therapeutic methods of clearing the source， harmonizing the pivot， and resolving the convergence are established. To fortify spleen and boost qi， consolidate the root and clear the source， modified Buzhong Yiqi Decoction（补中益气汤）can be used. To raise the clear and direct the turbid downward， regulate qi and harmonize the pivot， modified Shengyang Yiwei Decoction （升阳益胃汤） is suggested. To restore balance and promote circulation， disperse accumulation and resolve convergence， modified Shengyang Sanhuo Decoction （升阳散火汤） is selected. In clinical practice， these formulas can be used in combination according to the complexity of the pathogenesis， and further adapted with prescriptions for promoting dispersion and penetrating pathogenic factors， resolving phlegm and promoting circulation， activating blood and eliminating concretions， which can provide a reference for the prevention and treatment of tumor diseases.

Based on LI Gao's Academic Thought， focusing on the process of qi transformation and taking the regulation and restoration of metabolism and immunity as the entry point， a "source-pivot-convergence" diagnostic and therapeutic model for malignant tumors is constructed. In this model， spleen and stomach internal injury is the source of malignant tumor occurrence， while the disorder of ascending and descending is the pivot of the disease development， and the generation of yin fire is the convergence of malignant tumor progression. Based on this， the three major therapeutic methods of clearing the source， harmonizing the pivot， and resolving the convergence are established. To fortify spleen and boost qi， consolidate the root and clear the source， modified Buzhong Yiqi Decoction（补中益气汤）can be used. To raise the clear and direct the turbid downward， regulate qi and harmonize the pivot， modified Shengyang Yiwei Decoction （升阳益胃汤） is suggested. To restore balance and promote circulation， disperse accumulation and resolve convergence， modified Shengyang Sanhuo Decoction （升阳散火汤） is selected. In clinical practice， these formulas can be used in combination according to the complexity of the pathogenesis， and further adapted with prescriptions for promoting dispersion and penetrating pathogenic factors， resolving phlegm and promoting circulation， activating blood and eliminating concretions， which can provide a reference for the prevention and treatment of tumor diseases.

Objective: To systematically evaluate the application effectiveness of the full disinfection process in blood stations, identify key optimization links, and provide a scientific evidence for the formulation of specialized disinfection and hygiene standards for blood collection and supply institutions. Methods: On-site microbiological monitoring was conducted using techniques such as the plate settling method and cotton swab method. Stratified random sampling was performed on eight key control points: including evironmental air, hand hygiene, skin disinfection, blood transport boxes, pressure steam sterilization, sewage treatment, ultraviolet disinfection, and sterile swabs. Statistical analysis was performed using SPSS 20.0. Measurement data were expressed as mean ± standard deviation(x-±s), and inter-group comparisons were conducted using t-tests or analysis of variance (ANOVA). Count data were expressed as rates, and inter-group comparisons were conducted using the χ test. Trend analysis was performed using the Cochran-Armitage test, with a significance level of α=0.05. Results: The colony removal rate of plasma air disinfection machines (94.2%±0.8%) was significantly higher than that of the ultraviolet group (P<0.05). The qualification rate of quick-drying disinfectant hand was 100% within 30 days after opening the bottle, but decreased to 93.3% after 40 days (P<0.01). The qualification rate of disinfection for blood transport boxes using 500 mg/L chlorine-containing disinfectant (100%) was significant higher 75% alcohol (60%, P< 0.05). Skin disinfection with 2% alcoholic chlorhexidine gluconate balanced effectiveness and user experience (satisfaction score 4.8±0.3). The qualification rates for core procedures such as pressure steam sterilization and sewage treatment were both 100%. Conclusion: The current disinfection procedures in blood collection and supply institutions are reliable. The effective usage period of hand disinfectants, disinfection methods for transport boxes, and usage duration of sterile swabs are the main points for optimization. It is recommended that the opened hand disinfectants be used for ≤30 days and that chlorine-containing disinfectants be prioritized for wiping transport boxes, providing empirical support for the revision of protocols and the formulation of standards.

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 elucidate how spinal manipulative therapy (SMT) exerts its analgesic effects through regulating brain function in lumbar disc herniation (LDH) patients by utilizing resting-state functional magnetic resonance imaging (rs-fMRI). METHODS: From September 2021 to September 2023, we enrolled LDH patients (LDH group, n=31) and age- and sex-matched healthy controls (HCs, n=28). LDH group underwent rs-fMRI at 2 distinct time points (TPs): prior to the initiation of SMT (TP1) and subsequent to the completion of the SMT sessions (TP2). SMT was administered once every other day for 30 min per session, totally 14 treatment sessions over a span of 4 weeks. HCs did not receive SMT treatment and underwent only one fMRI scan. Additionally, participants in LDH group completed clinical questionnaires on pain using the Visual Analog Scale (VAS) and the Japanese Orthopedic Association (JOA) score, whereas HCs did not undergo clinical scale assessments. The effects on the brain were jointly characterized using the amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo). Correlation analyses were conducted between specific brain regions and clinical scales. RESULTS: Following SMT treatment, pain symptoms in LDH patients were notably alleviated and accompanied by evident activation of effects in the brain. In comparison to TP1, TP2 exhibited the most significant increase in ALFF values for Temporal_Sup_R and the most notable decrease in ALFF values for Paracentral_Lobule_L (voxelwise P<0.005; clusters >30; FDR correction). Additionally, the most substantial enhancement in ReHo values was observed for the Cuneus_R, while the most prominent reduction was noted for the Olfactory_R (voxelwise P<0.005; clusters >30; FDR correction). Moreover, a comparative analysis revealed that, in contrast to HCs, LDH patients at TP1 exhibited the most significant increase in ALFF values for Temporal_Pole_Sup_L and the most notable decrease in ALFF values for Frontal_Mid_L (voxelwise P<0.005; clusters >30; FDR correction). Furthermore, the most significant enhancement in ReHo values was observed for Postcentral_L, while the most prominent reduction was identified for ParaHippocampal_L (voxelwise P<0.005; clusters >30; FDR correction). Notably, correlation analysis with clinical scales revealed a robust positive correlation between the Cuneus_R score and the rate of change in the VAS score (r=0.9333, P<0.0001). CONCLUSIONS Long-term chronic lower back pain in patients with LDH manifests significant activation of the "AUN-DMN-S1-SAN" neural circuitry. The visual network, represented by the Cuneus_R, is highly likely to be a key brain network in which the analgesic efficacy of SMT becomes effective in treating LDH patients. (Trial registration No. NCT06277739).
Humans ; Magnetic Resonance Imaging ; Intervertebral Disc Displacement/diagnostic imaging* ; Male ; Female ; Brain/diagnostic imaging* ; Adult ; Manipulation, Spinal/methods* ; Middle Aged ; Lumbar Vertebrae/physiopathology* ; Pain Management ; Rest ; Case-Control Studies

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent inflammation and joint damage, accompanied by the accumulation of plasma cells, which contributes to its pathogenesis. Understanding the genetic alterations occurring during plasma cell differentiation in RA can deepen our comprehension of its pathogenesis and guide the development of targeted therapeutic interventions. Here, our study elucidates the intricate molecular mechanisms underlying plasma cell differentiation by demonstrating that PRDX1 interacts with DOK3 and modulates its degradation by the autophagy-lysosome pathway. This interaction results in the inhibition of plasma cell differentiation, thereby alleviating the progression of collagen-induced arthritis. Additionally, our investigation identifies Salvianolic acid B (SAB) as a potent small molecular glue-like compound that enhances the interaction between PRDX1 and DOK3, consequently impeding the progression of collagen-induced arthritis by inhibiting plasma cell differentiation. Collectively, these findings underscore the therapeutic potential of developing chemical stabilizers for the PRDX1-DOK3 complex in suppressing plasma cell differentiation for RA treatment and establish a theoretical basis for targeting PRDX1-protein interactions as specific therapeutic targets in various diseases.

Objective To investigate the predictive value of heparin-binding protein(HBP)in Kawasaki disease complicated with bacterial infection.Methods A total of 148 children with Kawasaki disease in this hospital from April 2021 to June 2022 were selected as Kawasaki disease group.According to the results of pathogen detection during hospitalization,the children were divided into three subgroups:Mycoplasma pneu-moniae group(36 cases),bacteria group(19 cases),and non-infection group(93 cases).In addition,35 chil-dren with fever and upper respiratory tract infection were randomly selected as the case control group.HBP and other inflammatory markers[white blood cell count(WBC),neutrophil percentage(NE％),procalcitonin(PCT),C reactive protein(CRP),interleukin-6(IL-6)]in each group were detected and analyzed.Receiver operating characteristic(ROC)curve was used to analyze the predictive value of HBP and PCT for bacterial infection in children with Kawasaki disease.Results The levels of HBP,WBC,NE％,CRP and IL-6 in the Ka-wasaki disease group were significantly higher than those in the case control group(P＜0.05),while there was no significant difference in PCT level between the two groups(P＞0.05).The levels of HBP,WBC,NE％,PCT,CRP and IL-6 in children with Kawasaki disease after treatment were significantly lower than those at admission(P＜0.05).The levels of HBP and PCT in the bacterial group were higher than those in the Mycoplasma pneumoniae group and the non-infection group,and the differences were statistically signifi-cant(P＜0.05),while there were no statistically significant differences in WBC,NE％,CRP and IL-6 levels a-mong the three groups(P＞0.05).ROC curve results showed that the area under the curve(AUC)and 95％CI of HBP for predicting bacterial infection in children with Kawasaki disease was 0.77(0.68-0.86),when HBP was 499.65 ng/mL,the sensitivity and specificity were 84.2％and 66.7％,respectively.When PCT was 0.85 ng/mL,the AUC(95％CI)for predicting bacterial infection in children with Kawasaki disease was 0.65(0.52-0.78),and the sensitivity and specificity were 63.2％and 65.9％,respectively.Conclusion HBP is associated with Kawasaki disease,and it has certain predictive value for Kawasaki disease complicated with bacterial infection.

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.

Objective To investigate the molecular mechanism of hepatic fibrosis(HF)regulation by liver sinusoidal endothelial cells(LSECs)via endothelial mesenchymal transition(EnMT),and to predict the natural active components using bioinformatics,machine learning,and cellular experiments.Methods HF and EnMT gene matrices were obtained and the intersecting genes were extracted and enriched using Limma difference analysis and weighted gene co-expression network analysis(WGCNA).The diagnostic genes were screened using a combination of random forest method,support vector machine-recursive feature elimination and network topology analysis,and immune infiltration analysis and prediction of natural active ingredients were performed.The expression of diagnostic genes and the pharmacological effects of the predicted ingredients were finally verified by cellular experiments.Results Differential analysis yielded 3034 EnMT-associated and 4133 HF-associated differential genes.WGCNA analysis yielded 4589 EnMT-associated Hub genes and 763 HF-associated Hub genes.Thirty-eight intersecting genes were extracted,which were mainly enriched in the pathways of basement membrane and extracellular matrix receptor interaction.Four diagnostic genes,CFP,COL4A2,ITGA1,and GRPEL1,were screened by multidimensional analysis.Immune infiltration analysis showed that the diagnostic genes were closely associated with mast cell resting state,memory B cells,and memory CD4+T cells.Reverse transcription-polymerase chain reaction analysis showed significantly increased mRNA expression levels of the four diagnostic genes in the Jagged1-induced model group(P＜0.05).The predicted components,sterol,kaempferol,and quercetin,all had good binding activities with the diagnostic genes.Enzyme-linked immunosorbent assay result confirmed that all three active components significantly reduced the expression of collagen type Ⅳ α2 chain protein in Jagged1-induced LSECs,with quercetin having the most significant effect(P＜0.01).Conclusions This study elucidated the molecular mechanism of hepatic sinusoidal endothelial cells involved in the pathological process of HF through mesenchymal transition.We also propose a diagnostic marker system including CFP,COL4A2,ITGA1,and GRPEL1 as core genes.The result also suggest that natural active ingredients,such as quercetin,may exert anti-HF pharmacological effects by targeting these diagnostic genes.

Objective To design an intelligent airborne soldier physical training system based on human body composition analysis to solve the problems in diversity of training mode,targeted training plan and high incidence of military training-related injuries.Methods The intelligent airborne military physical training system was designed with B/S architecture and developed with Python language,which was composed of four functional modules for airborne soldier information acquisition,trainee physical fitness state assessment,physical fitness training program recommendation and airborne soldier physical fitness training program evaluation.The airborne soldier information acquisition module collected and analyzed the trainee physiological parameter information with a human body composition analyzer,clarified the parameter characteristics related to physical training with considerations on military physical training requirements and constructed a trainee physical fitness assessment parameter model;the trainee physical fitness state assessment module established an evaluation model based on machine learning to realize stage-by-stage physical fitness evaluation for airborne soldiers;the physical fitness training program recommendation module was constructed based on the physical training feature similarity algorithm and graph embedding theory to provide decision making assistance for program development of airborne military physical training;the airborne soldier physical fitness training program evaluation module compared the physical fitness and evaluation results before and after training by means of list and chart,and updated the training program based on the evaluation results by calling the physical training program recommendation module.Results The intelligent airborne soldier physical training system contributed to forming an individualized physical fitness training recommendation mechanism after trainee body evaluation,modifying training program based on comparison and feedback for stage-by-stage training evaluation,so as to decrease the incidence of military training-related injuries while increasing the training efficiency.Conclusion The system developed improves airborne soldier physical training in rationality and reliability,and provides references for intelligent military training of the PLA.[Chinese Medical Equipment Journal,2025,46(2):16-23]