Breast cancer has become the malignant tumor with the highest incidence rate among women， seriously threatening the life and health of women all over the world. The pathogenic factors and development mechanisms of breast cancer are complex and diverse. The development of breast cells from ordinary hyperplasia to atypical hyperplasia， and from pre-cancerous lesions to cancerous lesions， is a long-term progressive process. Therefore， early screening and prevention of breast cancer is particularly important. Western medicine has a relatively mature treatment program for breast cancer， which is mainly based on surgery and systemic treatment， whereas the ensuing complications and adverse reactions often bring a heavy burden to patients. For the precancerous lesions of breast cancer， surgery is also the mainstay of treatment. In recent years， traditional Chinese medicine （TCM） has increasingly highlighted its advantages in the prevention and treatment of breast cancer. Increasing studies have shown that in the prevention and treatment of breast cancer and pre-cancerous lesions， TCM compound prescriptions， single herbs or herb pairs， and active components are able to regulate a variety of intracellular signaling pathways through multi-targets to inhibit the proliferation and invasion， promote the apoptosis and autophagy of tumor cells， and regulate the cell cycle and the immune microenvironment， thus exerting anti-tumor effects. At the same time， they can significantly attenuate the toxic side effects of radiotherapy and drug resistance of patients. However， the specific mechanisms of TCM in the prevention and treatment of breast cancer and precancerous lesions have not been fully clarified. The available studies are tanglesome regarding the TCM inhibition of tumor development through the regulation of classical signaling pathways such as phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt）/mammalian target of rapamycin （mTOR）， Wnt/β-catenin， and Notch， which still need to be verified by a large number of clinical and experimental studies. Therefore， this paper reviews the research progress in the prevention and treatment of breast cancer and precancerous lesions by TCM through interfering with the relevant signaling pathways in recent years， aiming to summarize the possible mechanisms of TCM in the prevention and treatment of breast cancer and provide references for subsequent studies.

ObjectiveTo observe the activation patterns and functional connectivity in the prefrontal cortex of patients with post-stroke anxiety (PSA) using functional near-infrared spectroscopy, in order to explore the underlying neural mechanism. MethodsFrom December, 2024 to September, 2025, 120 stroke patients were selected in Changzhou De'an Hospital. They were divided into PSA group (n = 60) and non-PSA group (n = 60) according to the score of Hamilton Anxiety Scale (HAMA). All patients wore an 18-channel fNIRS acquisition cap for detection. The differences in resting-state functional connectivity between the frontopolar cortex (FPC) and dorsolateral prefrontal cortex (DLPFC) were examined in both groups, as well as task-related activation in these brain regions. ResultsResting-state functional connectivity analysis revealed no statistically significant difference in network connectivity between two groups in the FPC and DLPFC regions (|t| < 1.301, P > 0.05). Task-related activation results revealed significantly reduced activation in the contralateral FPC of PSA group compared to the non-PSA group (Z = -2.063, P < 0.05). Activation levels in this region showed a negative correlation with the scores of HAMA (ρ = -0.201, P = 0.028). ConclusionActivation decreased in the contralateral frontal pole during the task state for patients with PSA, and the activation levels negatively correlates with anxiety severities.

ObjectiveTo observe the activation patterns and functional connectivity in the prefrontal cortex of patients with post-stroke anxiety (PSA) using functional near-infrared spectroscopy, in order to explore the underlying neural mechanism. MethodsFrom December, 2024 to September, 2025, 120 stroke patients were selected in Changzhou De'an Hospital. They were divided into PSA group (n = 60) and non-PSA group (n = 60) according to the score of Hamilton Anxiety Scale (HAMA). All patients wore an 18-channel fNIRS acquisition cap for detection. The differences in resting-state functional connectivity between the frontopolar cortex (FPC) and dorsolateral prefrontal cortex (DLPFC) were examined in both groups, as well as task-related activation in these brain regions. ResultsResting-state functional connectivity analysis revealed no statistically significant difference in network connectivity between two groups in the FPC and DLPFC regions (|t| < 1.301, P > 0.05). Task-related activation results revealed significantly reduced activation in the contralateral FPC of PSA group compared to the non-PSA group (Z = -2.063, P < 0.05). Activation levels in this region showed a negative correlation with the scores of HAMA (ρ = -0.201, P = 0.028). ConclusionActivation decreased in the contralateral frontal pole during the task state for patients with PSA, and the activation levels negatively correlates with anxiety severities.

ObjectiveTo observe the activation patterns and functional connectivity in the prefrontal cortex of patients with post-stroke anxiety (PSA) using functional near-infrared spectroscopy, in order to explore the underlying neural mechanism. MethodsFrom December, 2024 to September, 2025, 120 stroke patients were selected in Changzhou De'an Hospital. They were divided into PSA group (n = 60) and non-PSA group (n = 60) according to the score of Hamilton Anxiety Scale (HAMA). All patients wore an 18-channel fNIRS acquisition cap for detection. The differences in resting-state functional connectivity between the frontopolar cortex (FPC) and dorsolateral prefrontal cortex (DLPFC) were examined in both groups, as well as task-related activation in these brain regions. ResultsResting-state functional connectivity analysis revealed no statistically significant difference in network connectivity between two groups in the FPC and DLPFC regions (|t| < 1.301, P > 0.05). Task-related activation results revealed significantly reduced activation in the contralateral FPC of PSA group compared to the non-PSA group (Z = -2.063, P < 0.05). Activation levels in this region showed a negative correlation with the scores of HAMA (ρ = -0.201, P = 0.028). ConclusionActivation decreased in the contralateral frontal pole during the task state for patients with PSA, and the activation levels negatively correlates with anxiety severities.

Objective: To analyze the incidence of statutory and keymonitored infectious diseases among school students in Beijing from 2016 to 2020, so as to provide a reference for developing the prevention and control of infectious diseases in schools. Methods: A descriptive statistical analysis was conducted on student cases aged 6-22 years in Beijing from 2016 to 2020 selected from the China Disease Surveillance Information Reporting Management System. Rate comparisons were performed using the 2 test and trend 2 test. Results: From 2016 to 2020, the overall incidence of statutory and keymonitored infectious diseases among students in Beijing showed an upward trend (χ2trend=582.42), the incidence rates of Category B and other infectious diseases exhibited a downward trend (χ2trend=82.71, 18.34), while Category C infectious diseases demonstrated a significant upward trend (χ2trend=911.75) (P<0.01). Among Category B infectious diseases, scarlet fever, bacillary dysentery, tuberculosis, and HIV/AIDS were predominant, with annual average incidence rates of 61.33/100 000, 35.38/100 000, 13.88/100 000, and 3.78/100 000, respectively. Except for HIV/AIDS, the reported incidence rates of other infectious diseases showed a declining trend. Among Category C infectious diseases, influenza, other infectious diarrhea, hand-foot-mouth disease, and mumps were predominant, with annual average incidence rates of 956.13/100 000, 114.39/100 000, 111.37/100 000, and 28.24/100 000, respectively. Influenza showed a significant upward trend (χ2trend=1 508.30), while the other infectious diarrhea, hand-foot-mouth disease, and mumps exhibited a downward trend (χ2trend=13.84, 25.78, 6.13) (P<0.05). Among other infectious diseases, varicella was predominant (χ2trend=17.47, P<0.05). Scarlet fever, influenza, hand-foot-mouth disease, and mumps had higher incidence rates among primary and middle school students; other infectious diarrhea and varicella were more prevalent among high school students; tuberculosis and bacillary dysentery were more common among high school and college students; and HIV/AIDS had higher incidence rates among college and high school students. Conclusion From 2016 to 2020, the incidence of Category B infectious diseases among students in Beijing showed a declining trend, while influenza, a Category C infectious disease, exhibited a significant upward trend.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

[This corrects the article DOI: 10.1016/j.apsb.2018.08.009.].

Objective To analyze the predictive value of neurotrophic factors for cognitive impairment in the elderly after cerebral infarction.Methods The clinical data of 137 elderly patients with cerebral infarction who were admitted to Wujin Hospital of Traditional Chinese Medicine from February 2022 to January 2024 were retrospectively analyzed.At 7 days after the onset of cerebral infarction,the patients were classified into occurrence group(n=49)and non-occurrence group(n=88)according to the occurrence of cognitive impairment.The levels of nutrition-related factors,such as brain-derived neurotrophic factor(BDNF)and glial cell derived neurotrophic factor(GDNF),were compared between the two groups.The influencing factors of cognitive impairment in elderly patients with cerebral infarction were screened,and a risk prediction model for cognitive impairment in elderly patients with cerebral infarction was constructed and verified.Results The levels of serum BDNF and GDNF in the occurrence group were lower than those in the non-occurrence group(P<0.05).The proportion of females,the National Institutes of Health stroke scale(NIHSS)score and the level of low-density lipoprotein cholesterol(LDL-C)in the occurrence group were higher than those in the non-occurrence group(P<0.05).Logistic regression analysis showed that serum BDNF(OR=0.271,95%CI:0.128-0.662),serum GDNF(OR=0.227,95%CI:0.100-0.516),NIHSS score(OR=4.768,95%CI:2.096～10.847),and LDL-C(OR=3.955,95%CI:1.749-8.997)were the influential factors for cognitive impairment in elderly patients with cerebral infarction(P<0.05).The sensitivity,specificity and area under the curve of the nomogram model were 79.6%(95%CI:65.2%～89.3%),90.9%(95%CI:95%CI:82.4%～95.7%),and 0.903(95%CI:0.821-0.965)for the prediction of cognitive impairment in elderly patients with cerebral infarction.Conclusion The levels of BDNF and GDNF are related to cognitive impairment in elderly patients with cerebral infarction.The risk prediction model constructed based on BDNF,GDNF,NIHSS score and LDL-C can help to predict the risk of cognitive impairment in elderly patients with cerebral infarction.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.