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 investigate the differences in personality traits between the patients with anx-ious depression(AND)and non-anxious depression(NAD)in order to provide the possible basis for early find of the patients with AND.Methods A total of 572 adult patients with depression visiting in the psychiatric outpatient department of the First Affiliated Hospital of Chongqing Medical University from January 2022 to December 2022 were selected to conduct the questionnaire survey.General demographic questionnaire,Self-rating Depression Scale(SDS),Generalized Anxiety Disorder Scale(GAD-7)and Minnesota Multiphasic Per-sonality Inventory(MMPI)were collected and analyzed.The patients with GAD-7 total score ≥5 points served as the AND group(n=499)and those with GAD total score＜5 points served as the NAD group(n=73).The correlation between the general demographic questionnaire,SDS and GAD-7 with MMPI was ana-lyzed.Results There were statistically significant differences in the place of residence,number of children in a family,education years,MMPI total score and high score proportions of psychopathy,athopia,hysteria,depres-sion,hypochondriasis,paranoea,schizophrenia,social introversion and hypomania dimensions between the two groups(P＜0.05).The SDS and GAD-7 scores in the AND group were higher than those in the NAD group(P＜0.05).The MMPI total score,athopia,hysteria,depression,hypochondriasis,paranoea,schizophrenia,so-cial introversion and hypomania were positively correlated with SDS and GAD-7(P＜0.05).Conclusion The patients with depression accompanied by anxiety symptom could be early identified by the MMPI testing results.

Objective To investigate the value of early maternal serological indicators in predic-ting the delivery of full-term small-for-gestational-age(SGA)infants.Methods The clinical data of pregnant women who delivered at Beijing Tongzhou District Maternal and Child Health Hospital from August 2023 to August 2024 were analyzed.A total of 180 pregnant women who delivered full-term SGA infants were included in case group,and 180 pregnant women who delivered full-term appropri-ate-for-gestational-age(AGA)infants during the same period were included in control group.The levels of serum pregnancy-associated plasma protein A(PAPP-A),placenta growth factor(PLGF),and soluble fms-like tyrosine kinase-1(sFlt-1)in the first trimester(11 to 13 weeks+6 days of ges-tation)of the two groups were compared.Receiver operating characteristic(ROC)curves were used to analyze the predictive value of early maternal serological indicators for the delivery of full-term SGA infants.Results The levels of serum PAPP-A and PLGF in the first trimester of the case group were lower than those in the control group,while the level of sFlt-1 was higher(P＜0.05).The area un-der the ROC curve(AUC)for the combined detection of serum PAPP-A,PLGF,and sFlt-1 levels in the first trimester in predicting the delivery of full-term SGA infants was 0.823,which was higher than the AUCs for detection of each indicator(0.738,0.720,0.724)(P＜0.05).Conclusion The detection of early maternal PAPP-A,PLGF,and sFlt-1 levels can reflect the fetal growth status in utero.The combined detection of these three indicators has a higher predictive value for the delivery of full-term SGA infants by pregnant women,which is helpful for clinicians to take intervention measures in advance.

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 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 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 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.