Digital technology has revolutionized the traditional model of quality evaluation for traditional Chinese medicine(TCM).This article systematically reviews the research hotspots and practical applications of digital-driv-en quality evaluation of TCM.Simultaneously,this paper analyzes and assesses the challenges faced by the digitiza-tion of TCM quality evaluation from multiple perspectives,including data acquisition,model construction,applica-tion promotion and market acceptance,and puts forward targeted strategies.Addressing the existing issues in the field of TCM quality,this paper proposes a series of innovative concepts,including the mining and application of TCM property data,the construction of a large database of TCM components,the integration of digital technology and emerging biotechnology for biological effect evaluation of TCM and clinical intelligent evaluation based on real-world data.Based on these,it further proposes a multi-dimensional quality analysis model for grading TCM,which encompasses TCM property data,chemical composition analysis,biological effect assessment and clinical evalua-tion.It aims to provide a useful reference for the modernization,scientification,and standardization of TCM quality evaluation.

Objective:To establish a rapid quantitative model for the determination of moisture,extractives,and content in Pollen Typhae.Methods:Near-infrared spectra of 91 batches of Pollen Typhae samples were collected.Spectral preprocessing was performed using S-G,MSC,SNV,and CWT methods.Variable selection was conducted using CARS,SPA,and VIP methods,and compared with full-spectrum modeling.Partial least squares(PLS)mod-els were established for the quantitative determination of moisture,total ash,extractives,and content.The model performance was evaluated by calculating the coefficient of determination for the calibration set and validation set(R2 c,R2v),root mean square error of calibration and validation(RMSEc,RMSEv),and residual prediction devia-tion(RPD).Results:The PLS models for moisture,extractives,and content in Pollen Typhae showed R2c and R2v values greater than 0.9,RMSEc and RMSEv values approaching 0,and RPD values greater than 3.Conclusion:In this study,near-infrared spectroscopy was used to construct quantitative prediction models for moisture,extractives,typhaneoside,and isorhamnetin-3-O-neohesperidoside content in Pollen Typhae.This method enables rapid detection of the main quality control indicators of Pollen Typhae,providing strong technical support for its quality supervision.

Objective To investigate the predictive value of serum vasoactive intestinal peptide(VIP)and 5-hydroxytryptamine(5-HT)levels on the outcome of spinal cord electrical stimulation(SCS)in patients with postherpetic neuralgia(PHN).Methods A total of 96 PHN patients who received SCS treatment in Ziy-ang Central Hospital from January 2022 to December 2023 were selected.According to the disease outcomes of all PHN patients after 6 months of treatment,a good group(n=71)and a poor group(n=25)were set up.The clinical data of the two groups were collected and the serum VIP and 5-HT levels were detected in all pa-tients before treatment.The predictive value of serum VIP and 5-HT on disease outcome after SCS treatment in PHN patients was evaluated by receiver operating characteristic(ROC)curve,and the influencing factors of disease outcome after SCS treatment in PHN patients was explored by multivariate Logistic steppe gression a-nalysis.Results The levels of serum VIP and 5-HT in poor group were higher than those in good group(P＜0.05).The area under the curve(AUC)of serum VIP and 5-HT for predicting the disease outcome of PHN patients after SCS treatment were 0.829(95％CI:0.779-0.874)and 0.743(95％CI:0.693-0.793),respec-tively,and the AUC of combined prediction was 0.941(0.891-0.986).There were no significant differences in age,gender,body moss index,education,location of onset,hypertension and drinking history between the two groups(P＞0.05).The time of initial hospital admission in the poor group was longer than that in the good group,skin rash area in the poor group was larger than that in the good group,and diabetes mellitus and smoking history in the poor group were higher than those in the good group(P＜0.05).The time of admis-sion for initial treatment＞3 d(OR=2.188,95％CI:1.383-3.461),skin rash area＞10 cm2(OR=2.018,95％CI:1.283-3.173),diabetes mellitus(OR=2.264,95％CI:1.379-3.717),serum VIP level ≥41.78 ng/L(OR=3.022,95％CI:1.685-5.420),serum 5-HT level ≥99.27 ng/mL(OR=3.579,95％CI:1.885-6.793)were the influencing factors of disease outcome after SCS treatment in PHN patients(P＜0.05).Con-clusion The elevated levels of serum VIP and 5-HT before treatment are associated with poor outcomes after SCS in patients with PHN,and could be used as potential markers to predict the outcomes of SCS in patients with PHN.

Digital technology has revolutionized the traditional model of quality evaluation for traditional Chinese medicine(TCM).This article systematically reviews the research hotspots and practical applications of digital-driv-en quality evaluation of TCM.Simultaneously,this paper analyzes and assesses the challenges faced by the digitiza-tion of TCM quality evaluation from multiple perspectives,including data acquisition,model construction,applica-tion promotion and market acceptance,and puts forward targeted strategies.Addressing the existing issues in the field of TCM quality,this paper proposes a series of innovative concepts,including the mining and application of TCM property data,the construction of a large database of TCM components,the integration of digital technology and emerging biotechnology for biological effect evaluation of TCM and clinical intelligent evaluation based on real-world data.Based on these,it further proposes a multi-dimensional quality analysis model for grading TCM,which encompasses TCM property data,chemical composition analysis,biological effect assessment and clinical evalua-tion.It aims to provide a useful reference for the modernization,scientification,and standardization of TCM quality evaluation.

Objective:To establish a rapid quantitative model for the determination of moisture,extractives,and content in Pollen Typhae.Methods:Near-infrared spectra of 91 batches of Pollen Typhae samples were collected.Spectral preprocessing was performed using S-G,MSC,SNV,and CWT methods.Variable selection was conducted using CARS,SPA,and VIP methods,and compared with full-spectrum modeling.Partial least squares(PLS)mod-els were established for the quantitative determination of moisture,total ash,extractives,and content.The model performance was evaluated by calculating the coefficient of determination for the calibration set and validation set(R2 c,R2v),root mean square error of calibration and validation(RMSEc,RMSEv),and residual prediction devia-tion(RPD).Results:The PLS models for moisture,extractives,and content in Pollen Typhae showed R2c and R2v values greater than 0.9,RMSEc and RMSEv values approaching 0,and RPD values greater than 3.Conclusion:In this study,near-infrared spectroscopy was used to construct quantitative prediction models for moisture,extractives,typhaneoside,and isorhamnetin-3-O-neohesperidoside content in Pollen Typhae.This method enables rapid detection of the main quality control indicators of Pollen Typhae,providing strong technical support for its quality supervision.

Objective To investigate the prognostic value of mitochondrial autophagy-related genes(MRGs)in prostate cancer(PCa),and to reveal their regulatory relationship with interstitial epidermal transforming factor(C-Met)based on the Gene Expression Database(GEO).Methods Single-cell RNA sequencing(scRNA-seq)data of three PCa samples were obtained from the GSE153892 dataset of GEO,and MRGs were collected from the Genecards database and previous literature.The scRNA-seq data were processed and analyzed using the Seurat software package,including quality control,gene expression screening,cell type annotation,differentially expressed genes(DEGs)identification,and intersection analysis with MRGs.The transcriptome data of PCa and control samples were downloaded from the Cancer Genome Atlas Database(TCGA)-PRAD cohort,and differential expression analysis and copy number variation analysis were conducted.The non-negative matrix factorization algorithm is adopted to conduct cluster analysis on PCa samples to identify different PCa subtypes.A prognostic risk model based on intersection genes was constructed,and the predictive ability of the model was analyzed through Kaplan-Meier survival curve analysis and time-dependent receiver operating characteristic(ROC)curve analysis.Conduct independent prognostic analysis,construct a nomogram model based on risk scores and clinical characteristics,and evaluate its ability to predict patient survival rates.The possibility of immune infiltration and tumor immune escape in PCa samples was evaluated by using the single-sample Gene Set Enrichment analysis(ssGSEA)algorithm and the TIDE database.The relationship between intersection genes and C-Met expression was analyzed using Pearson correlation analysis.Results scRNA-seq data analysis identified five cell types including B lymphocytes,epithelial cells,monocytes,natural killer cells and T lymphocytes,and discovered the intersection genes that were highly expressed in different cell types.Through differential expression analysis,genes significantly related to the prognosis of PCa patients were screened out,and a prognostic risk model was constructed.Six genes such as ADH5 and CAT were retained through LASSO analysis.A diagnostic model was constructed and grouped.There was a significant difference in survival time between the two groups in the internal test set(P<0.05).ROC curve evaluation showed that the model had a good predictive ability for 1-,3-,and 5-year survival rates.The external test set verified that there was a statistically significant difference in the expression of intersection genes(P<0.05).Independent prognostic analysis identified T stage and risk score as independent prognostic factors.A nomogram model was constructed.Calibration curve and ROC curve analyses showed that the predictive ability of this model was superior to that of the simple risk model.ssGSEA analysis revealed differences in the abundance of immune cell inflammation and immune function scores between the two groups.Most immune cells,immune function,and risk scores were related to the modeling genes.There were significant differences in TIDE scores and multiple immune checkpoints between the high-risk and low-risk groups(P<0.05).BCAT2,DCXR,OGT and FUS were positively correlated with the expression of C-Met,while ADH5 and CAT were negatively correlated with the expression of C-Met(P<0.05).Conclusion The prognostic risk model based on intersection genes can effectively predict the prognosis of patients with PCa,and the risk score and T stage are independent prognostic factors for PCa.The correlation analysis of intersection genes and C-Met expression provides a new idea for the targeted therapy of PCa.

Objective To investigate the prognostic value of mitochondrial autophagy-related genes(MRGs)in prostate cancer(PCa),and to reveal their regulatory relationship with interstitial epidermal transforming factor(C-Met)based on the Gene Expression Database(GEO).Methods Single-cell RNA sequencing(scRNA-seq)data of three PCa samples were obtained from the GSE153892 dataset of GEO,and MRGs were collected from the Genecards database and previous literature.The scRNA-seq data were processed and analyzed using the Seurat software package,including quality control,gene expression screening,cell type annotation,differentially expressed genes(DEGs)identification,and intersection analysis with MRGs.The transcriptome data of PCa and control samples were downloaded from the Cancer Genome Atlas Database(TCGA)-PRAD cohort,and differential expression analysis and copy number variation analysis were conducted.The non-negative matrix factorization algorithm is adopted to conduct cluster analysis on PCa samples to identify different PCa subtypes.A prognostic risk model based on intersection genes was constructed,and the predictive ability of the model was analyzed through Kaplan-Meier survival curve analysis and time-dependent receiver operating characteristic(ROC)curve analysis.Conduct independent prognostic analysis,construct a nomogram model based on risk scores and clinical characteristics,and evaluate its ability to predict patient survival rates.The possibility of immune infiltration and tumor immune escape in PCa samples was evaluated by using the single-sample Gene Set Enrichment analysis(ssGSEA)algorithm and the TIDE database.The relationship between intersection genes and C-Met expression was analyzed using Pearson correlation analysis.Results scRNA-seq data analysis identified five cell types including B lymphocytes,epithelial cells,monocytes,natural killer cells and T lymphocytes,and discovered the intersection genes that were highly expressed in different cell types.Through differential expression analysis,genes significantly related to the prognosis of PCa patients were screened out,and a prognostic risk model was constructed.Six genes such as ADH5 and CAT were retained through LASSO analysis.A diagnostic model was constructed and grouped.There was a significant difference in survival time between the two groups in the internal test set(P<0.05).ROC curve evaluation showed that the model had a good predictive ability for 1-,3-,and 5-year survival rates.The external test set verified that there was a statistically significant difference in the expression of intersection genes(P<0.05).Independent prognostic analysis identified T stage and risk score as independent prognostic factors.A nomogram model was constructed.Calibration curve and ROC curve analyses showed that the predictive ability of this model was superior to that of the simple risk model.ssGSEA analysis revealed differences in the abundance of immune cell inflammation and immune function scores between the two groups.Most immune cells,immune function,and risk scores were related to the modeling genes.There were significant differences in TIDE scores and multiple immune checkpoints between the high-risk and low-risk groups(P<0.05).BCAT2,DCXR,OGT and FUS were positively correlated with the expression of C-Met,while ADH5 and CAT were negatively correlated with the expression of C-Met(P<0.05).Conclusion The prognostic risk model based on intersection genes can effectively predict the prognosis of patients with PCa,and the risk score and T stage are independent prognostic factors for PCa.The correlation analysis of intersection genes and C-Met expression provides a new idea for the targeted therapy of PCa.

Objective:To analyze the robustness of the dose of clinical target volume (CTV) and tolerance dose of normal tissues after applying in-room CT before carbon ion radiotherapy for prostate cancer.Methods:Thirty prostate cancer patients treated with carbon ion in Shanghai Proton and Heavy Ion Center from January 2020 to June 2021 were enrolled in this study. Five in-room CT images of each patient were selected randomly before treatment. Dose distributions were recalculated using the original plan on in-room CT images and dose volume histogram (DVH) parameters were obtained, including V 95% and V 90% of CTV and V 80% of rectum. The values were compared with the dosimetric parameters of the original plan. Statistical analysis was performed by paired or two independent samples t-tests. Results:The dose distribution was recalculated by applying in-room CT. The mean values of V 95% and V 90% of CTV and V 80% of rectum were 98.1%±1.2% ( P<0.001), 99.9%±0.2% ( P=0.001) and (5.8±1.6) ml ( P<0.001), respectively. The differences were statistically significant compared with those of the original plan. The frequency of V 95%≥95%, V 90%≥98% of CTV, and V 80%<10 ml of rectum was 148 (98.7%), 150 (100.0%) and 147 (98.0%), respectively. Conclusion:Based on in-room CT analysis and the patient management and positioning methods of our research center, the uncertainty of target dose and normal tissue dose in the entire process of prostate cancer carbon ion therapy is small, and the robustness is good.

OBJECTIVE: To investigate the accuracy, safety, and short-term effectiveness of a domestic robot-assisted system in total knee arthroplasty (TKA) by a multicenter randomized controlled trial. METHODS: Between December 2021 and February 2023, 138 patients with knee osteoarthritis who received TKA in 5 clinical centers were prospectively collected, and 134 patients met the inclusion criteria were randomly assigned to either a trial group ( n=68) or a control group ( n=66). Seven patients had lost follow-up and missing data, so they were excluded and the remaining 127 patients were included for analysis, including 66 patients in the trial group and 61 patients in the control group. There was no significant difference ( P>0.05) in gender, age, body mass index, side, duration of osteoarthritis, Kellgren-Lawrence grading, preoperative Knee Society Score (KSS) and Western Ontario and McMaster University Osteoarthritis Index (WOMAC) score between the two groups. The trial group completed the TKA by domestic robot-assisted osteotomy according to the preoperative CT-based surgical planning. The control group was performed by traditional osteotomy plate combined with soft tissue release. Total operation time, osteotomy time of femoral/tibial side, intraoperative blood loss, and postoperative complications were recorded and compared between the two groups. The radiographs were taken at 5 and 90 days after operation, and hip-knee-ankle angle (HKA), lateral distal angle of femur (LDFA), and posterior tibial slope (PTS) were measured. The difference between the measured values of the above indexes at two time points after operation and the preoperative planning target values was calculated, and the absolute value (absolute error) was taken for comparison between the two groups. The postoperative recovery of lower limb alignment was judged and the accuracy was calculated. KSS score and WOMAC score were used to evaluate the knee joint function of patients before operation and at 90 days after operation. The improvement rates of KSS score and WOMAC score were calculated. The function, stability, and convenience of the robot-assisted system were evaluated by the surgeons. RESULTS: The total operation time and femoral osteotomy time of the trial group were significantly longer than those of the control group ( P<0.05). There was no significant difference in the tibial osteotomy time and the amount of intraoperative blood loss between the two groups ( P>0.05). The incisions of both groups healed by first intention after operation, and there was no infection around the prosthesis. Nine patients in the trial group and 8 in the control group developed lower extremity vascular thrombosis, all of which were calf intermuscular venous thrombosis, and there was no significant difference in the incidence of complications ( P>0.05). All patients were followed up 90 days. There was no significant difference in KSS score and WOMAC score between the two groups at 90 days after operation ( P>0.05). There was significant difference in the improvement rate of KSS score between the two groups ( P<0.05), while there was no significant difference in the improvement rate of WOMAC score between the two groups ( P>0.05). Radiological results showed that the absolute errors of HKA and LDFA in the trial group were significantly smaller than those in the control group at 5 and 90 days after operation ( P<0.05), and the recovery accuracy of lower limb alignment was significantly higher than that in control group ( P<0.05). The absolute error of PTS in the trial group was significantly smaller than that in the control group at 5 days after operation ( P<0.05), but there was no significant difference at 90 days between the two groups ( P>0.05). The functional satisfaction rate of the robot-assisted system was 98.5% (65/66), and the satisfaction rates of stability and convenience were 100% (66/66). CONCLUSION Domestic robot-assisted TKA is a safe and effective surgical treatment for knee osteoarthritis, which can achieve favorable lower limb alignment reconstruction, precise implant of prosthesis, and satisfactory functional recovery.
Humans ; Arthroplasty, Replacement, Knee/methods* ; Osteoarthritis, Knee/surgery* ; Blood Loss, Surgical ; Robotics ; Knee Joint/surgery* ; Knee Prosthesis ; Retrospective Studies

Objective:To study and analyze the uncertainty of active breathing coordinator (ABC) technology for liver and lung cancer therapy using proton and heavy ion.Methods:Before each treatment, each patient received a verification radiograph through the supporting imaging frame in treatment room. 200 verification radiographs were taken for 20 lung cancer patients and 200 for 20 liver cancer patients. Ipiodol markers, which were fixed relative to the location of the tumor, were injected into the liver cancer patients. The position changes of ipiodol markers could reflect the position changes of liver tumors. Verification radiographs were registered with the vertebral body as the main target, and the change value of tumor location was recorded.Results:For liver cancer cases, the values of position change in the left and right, head and foot, and dorsal abdomendirection were (-0.05± 0.28) cm, (0.15±0.33) cm, (-0.12±0.27) cm, and (-0.03±0.13) cm, (-0.05±0.14) cm and (0.02±0.16) cmfor lung cancer cases, respectively ( P=0.280, <0.001, <0.001). For liver cancer cases, the dispersionin the left and right, head and foot, and dorsal abdomendirectionwas (0.20±0.09) cm, (0.25±0.06) cm, (0.19±0.09) cm, and (0.09±0.03) cm, (0.10±0.03) cm and (0.13±0.03) cm for lung cancer cases, respectively ( P<0.001, <0.001, 0.008). The proportion of tumor location changes of≤5 mm in three directions in liver and lung cancer patientswas (92%, 83%, 93%) vs. (99%, 99%, 100%)( P=0.030, 0.002, 0.007). Conclusion:The application of ABC technology in the proton heavy ion therapy of lung and liver cancer has good reproducibility, and the stability of ABC technology in the treatment of lung cancer is better than that of liver cancer.