Natural products (NPs) are an important source of new drugs for the treatment of stroke. Identifying cellular targets for bioactive molecules is a major challenge and critical issue in the development of new drugs for stroke. Small-molecule probes play a unique role in target discovery. However, drawbacks to these probes include non-specificity, unstable activity, and difficulty in synthesis. Small-molecule probes based on NPs at least partially compensate for these shortcomings. NPs feature rich chemical and structural diversity, biocompatibility, and unique biological activities. These features could be exploited to provide new ideas and tools for target discovery. Small-molecule probes based on NPs provide a precise and direct search for interacting protein targets of NPs-active small molecules. This review explores the properties of small-molecule probes based on NPs and their applications in mechanistic studies of stroke and other diseases. We hope that this review will bring new perspectives to the mechanistic study of NPs-active small molecules and accelerate the translation of these ingredients into drug candidates for the treatment of stroke.

Objective To enhance the quality of medical services in the intensive care unit(ICU)of provincial traditional Chinese medicine(TCM)hospitals.Methods In November 2023,Sichuan Provincial Critical Care Medicine Quality Control Center of TCM launched the"quality control supervision project scoring standard for critical care medicine of TCM"to conduct quality control evaluation and business guidance for all TCM hospitals with independent ICU.The survey covered structural indicators,control indicators,participation of TCM,development of new technologies,and diagnosis and treatment programs for dominant diseases.Results In terms of structural indicators:a total of 110 TCM hospitals in the province have independent ICU,an increase of 1.12 times compared with 2019.The control indicators showed that the ICU patients admission rate was higher than that of the national ICU admission rate in 2017,and the admission rate of patients with acute physiology and chronic health evaluation Ⅱ(APACHEⅡ)score≥15 points increased.However,the mortality of ICU exceeded the national average.The implementation of core indicators had been significantly improved,but the incidence of outcome indicators such as ICU ventilator-associated pneumonia(VAP),ICU intravascular catheter-related bloodstream infection(CRBSI),and ICU catheter-related urinary tract infection(CAUTI)had increased since 2019,mainly in secondary hospitals.The average number of new technologies was about(5.5±3.4),the participation rate of TCM decreased,and the dominant diseases increased compared with 2019,mainly sepsis,respiratory failure and hemorrhagic stroke.Conclusions The number of ICU units in TCM hospitals at all levels in Sichuan province has grown rapidly,and key performance indicators have also improved compared to previous periods.However,greater efforts are still needed in preventing the occurrence rates of VAP,CRBSI,and CAUTI.There is a shortage of medical resources allocation,and the imbalance in regional medical resources and professional training remains an urgent issue to be addressed.Additionally,the participation rate of TCM and the dominant diseases need further enhancement.

Objective:To establish a brain metastasis (BM) prediction model for limited-stage small cell lung cancer (LS-SCLC) patients who achieved complete response (CR) or partial response (PR) after thoracic chemoradiotherapy, and to explore the value of prophylactic cranial irradiation (PCI) in different risk groups.Methods:Clinical data of 274 patients with LS-SCLC who achieved CR/PR after thoracic chemoradiotherapy in Tianjin Medical University Cancer Institute & Hospital from January 2010 to December 2021 were retrospectively analyzed, including 144 cases in the PCI group and 130 in the non-PCI group. The nomogram was developed based on variables determined by univariate and multivariate analyses in the non-PCI group. The bootstrap method, receiver operating characteristics (ROC) curve, calibration curve and decision curve analysis (DCA) were employed to evaluate the predictive power and clinical benefits of the model. Patients were stratified into high- and low-risk groups based on risk scores. The brain metastases-free survival (BMFS), progression-free survival (PFS), extracranial progression-free survival (ePFS) and overall survival (OS) were compared between patients with and without PCI in different risk-stratified populations using the log-rank test.Results:The nomogram included five variables: systemic immune inflammation index (SII), lymphocyte-to-monocyte ratio (LMR), pro-gastrin-releasing peptide precursor (ProGRP), neuron-specific enolase (NSE), and blood calcium. The area under the ROC curve (AUC) of the nomogram in predicting 1- and 2-year BMFS was 0.761 and 0.822. In the low-risk group, there was no significant difference in the BMFS ( P=0.374), PFS ( P=0.551), ePFS ( P=0.508) and OS ( P=0.767) between the PCI and non-PCI groups. In the high-risk group, PCI could significantly increase the BMFS ( P<0.001) and PFS ( P=0.022), while there was no significant difference in the ePFS ( P=0.963) and OS ( P=0.632). And propensity score-matching (PSM) analysis showed similar results. Conclusions:PCI does not improve OS in LS-SCLC patients regardless of high or low risk of BM. However, PCI significantly prolong the BMFS and PFS in patients at a high risk of BM.

Objective To investigate the effect of interleukin-9(IL-9)on the growth of lung adenocarcinoma in mice and its possible mechanism of action.Methods Mouse lung adenocarcinoma CMT167 cells were inoculated subcutaneously in BALB/C mice to construct a subcutaneous transplantation tumor model of mouse lung adenocarcinoma and to observe the effect of IL-9 on the growth of mouse tumors.Flow cytometry(FCM)and Western blot(WB)were used to detect the expression of IL-9 recep-tor(IL-9R)in mouse lung adenocarcinoma CMT167 cells.CMT167 cells were treated with different concentrations of IL-9 in vitro,and changes in cell viability and apoptosis were observed at different time points.Changes in the percentages of myeloid-derived immunosuppressive cells(MDSCs),CD4+T cells,and CD8+T cells in the tumor tissues of mice were analyzed by using FCM.Results Compared with mice in control group,the growth of mouse lung subcutaneous graft tumors was significantly in-hibited,and the weight of graft tumor was reduced after IL-9 treatment(both P＜0.01).Compared with the control group,the expression of IL-9R in mouse lung adenocarcinoma CMT167 cells was significantly increased(P＜0.01).After treatment with different concentrations of IL-9 in vitro,there were no significant changes in the viability and apoptosis of mouse lung adenocar-cinoma CMT167 cells compared to the control group.The number of MDSCs in mouse tumor tissues was decreased after IL-9 treatment(P＜0.05),while proportions of CD4+T cells and CD8+T cells in tumor tissues were increased(P＜0.01).Conclu-sion IL-9Reduces the number of MDSCs and increases the proportions of CD4+T cells and CD8+T cells in mouse tumor tis-sues,therefore inhibits the growth of lung adenocarcinoma tumors in mice.

Objective: To assess the efficacy and safety of combining traditional Chinese medicine (TCM), specifically Chinese herbal medicine (CHM), with Western medicine (WM), compared to WM alone to treat breast cancer endocrine therapy-related osteoporosis (BCET-OP) by meta-analysis. Methods: Thirty-eight randomized controlled trials involving 2170 participants were analyzed. Eight databases were searched for articles published between inception and December 2023. Quality assessment was performed using the Risk of Bias 2 tool. Results: Significant increases were observed in the TCM-WM group in lumbar vertebrae bone mineral density (BMD) (P < .001, mean difference (MD) = 0.07, 95% confidence interval (CI): 0.06 to 0.08), lumbar vertebrae T-score (P = .0005, MD = 0.21, 95%CI: 0.09 to 0.33) and collum femoris BMD (P = .01, MD = 0.10, 95%CI: 0.02 to 0.19). No significant difference was observed between the groups in the collum femoris T-score and estradiol levels. Bone gla-protein levels were significantly increased in the TCM-WM group (P = .0002, MD = 0.52, 95%CI: 0.25 to 0.79). Beta-CrossLaps decreased significantly in the TCM-WM group (P = .0008, MD = −0.10, 95%CI: −0.16 to −0.04). No significant difference was observed between the TCM-WM and WM groups in alkaline phosphatase, in procollagen type I N-terminal propeptide, and in the Kupperman index. The visual analog score (VAS) was decreased in the TCM-WM group compared to the WM group (P < .001, MD = −1.40, 95%CI: −1.94 to −0.87). No significant difference in adverse events was observed between the two groups. Conclusion Combining CHM with WM in patients with BCET-OP significantly improved BMD, T-score, and certain bone turnover markers and reduced the VAS score, indicating potential benefits for bone health and related pain. Adverse event analysis revealed no differences between the groups, supporting the feasibility of the combination therapy. However, further research, particularly in diverse populations, is required.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.