Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Hepatocellular carcinoma(HCC)is difficult to detect in its early stages and current treatment methods are associated with significant side effects and a high risk of developing drug resistance.This study aims to investigate the effect of phycocyanin(PC)on the apoptosis of human HCC HepG2 cells and its potential mechanism.HepG2 cells were treated with PC at concentrations of 0.1,0.25,0.5,1,2.5,5,and 10 μg/mL for 12 h,and with 10 μg/mL PC and 2.5 μmol/L Wip1 inhibitor(Wip1i)alone or in combination for 12 and 24 h,respectively.Cell proliferation levels were assessed using the CCK-8 cell proliferation-toxicity assay kit.Apoptosis levels were measured by Annexin V-FITC/Propidium Iodide double staining combined with flow cytometry.TMT(Tandem Mass Tag)proteomics quantitative technol-ogy was applied to analyze differential protein expression.Western blotting was used to detect the expres-sion levels of Wip1,p53,and phosphorylated-p53(Ser15)proteins.The CCK-8 assay revealed that PC effectively inhibited HepG2 cell proliferation in a concentration-dependent manner,with a half-maximal inhibitory concentration(IC50)of 19.37 μg/mL.Flow cytometry results showed that PC significantly in-duced apoptosis,with an apoptosis rate of 30.40％.Quantitative proteomics analysis indicated that PC induced activation of the p53 pathway.The CCK-8 assay showed that Wip1i enhanced the cytotoxic effect of PC on HepG2 cells.Western blotting confirmed that PC inhibited Wip1 expression,induced p53 pro-tein phosphorylation,and promoted the expression of total p53 protein.Additionally,Wip1i further en-hanced PC-mediated activation of the p53 pathway,increasing the expression of p53 and pP53(S15).In conclusion,PC may induce apoptosis by inhibiting the activity of the p53 negative regulator Wip1,thereby promoting apoptosis through the Wip1/p53 pathway.

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

Objective To compare the application effects of plankton multiplex polymerase chain reac-tion-capillary electrophoresis(PCR-CE),SYBR Green Ⅰ real-time quantitative PCR(qPCR)and microwave digestion-vacuum filtration-automated scanning electron microscopy(MD-VF-Auto SEM)in the diagnosis of drowning.Methods Lung,liver and kidney tissues from 212 drowned corpses and 30 non-drowned corpses were examined respectively by the three drowning-related plankton testing methods,and the detection rates of plankton in each tissue by three methods were compared.Results In drowned corpses,the total detection rates of PCR-CE,qPCR,and MD-VF-Auto SEM were 93.9%,96.2%,and 95.3%,respectively,with no statistically significant difference(P>0.05).The detection rate of lung tissue by MD-VF-Auto SEM(100%)was higher than those of PCR-CE and qPCR(P<0.05),and there was no significant difference in the detection rates of the three methods in liver or kidney tissues(P>0.05).In non-drowning corpses,a small number of diatoms(less than 10 cells/10 g)were detected by MD-VF-Auto SEM method,only in liver and kidney tissues,while the other two methods yielded negative results for all tissues.Conclusion All three methods have good efficacy in the examination of drowned corpses.The MD-VF-Auto SEM method directly observes diatom morpho-logical characteristics through scanning electron microscopy,and the qualitative and quantitative analy-ses are intuitive and accurate.It has great advantages in the examination of difficult degradation samples.The PCR-CE method and qPCR method have a low sample demand(0.5 g),are easy to operate and have short detection time(4-7 h).They are easy to be applied in the grassroots depart-ments and are suitable for the rapid determination of drowned corpses in routin cases.The combina-tion of the two DNA methods with the MD-VF-Auto SEM method can increase the detection rate of plankton,ensuring the reliability of examination results.This combined use is of significant importance in the application of drowning diagnosis.

Objective:To investigate the influence and mechanism of bone marrow mesenchymal stem cells (BMSCs) overexpressing growth arrest specific 6, i.e. GAS6/BMSCs on full-thickness skin defect wounds in diabetic mice.Methods:This study was an experimental study. Twelve 8-week-old male C57BL/6J mice were divided into a control wound group with only full-thickness skin defects and a diabetic wound group with diabetic full-thickness skin defects according to the random number table method, with 6 mice in each group. The wound healing rates were calculated at 3, 7, 14, and 21 days after injury. At 21 days after injury, wound tissue specimens were collected for hematoxylin-eosin staining to observe the histopathological conditions; Masson staining was performed to detect collagen deposition; immunohistochemical staining was performed to detect the number of proliferating cell nuclear antigen (PCNA)-positive cells and CD31-positive cells, representing cell proliferation and capillary density, respectively; immunofluorescence staining was performed to detect the number of F4/80 and myeloperoxidase (MPO) double-positive cells, indicating efferocytosis. Two 4-week-old male C57BL/6J mice were used to extract BMSCs, and GAS6/BMSCs were constructed through adenovirus transfection and successfully identified. Eighteen 8-week-old male C57BL/6J mice were used to create diabetic full-thickness skin defect wound models and divided into phosphate buffered solution (PBS) group, BMSC group, and GAS6/BMSC group (with 6 mice in each group) according to the random number table method. Immediately after injury, PBS, BMSC single-cell suspension, and GAS6/BMSC single-cell suspension were injected locally into the wounds of the three groups of mice, respectively. The wound healing rates were calculated, and the cell proliferation, capillary density, and efferocytosis were detected at the same time points as the previous experiments.Results:At 3, 7, 14, and 21 days after injury, the wound healing rates of mice in diabetic wound group were significantly lower than those in control wound group (with t values of 7.99, 8.62, 9.80, and 5.85, respectively, P<0.05). Compared with those in control wound group, the wound tissue of mice in diabetic wound group showed the infiltration of a large number of inflammatory cells and reduced collagen deposition at 21 days after injury. At 21 days after injury, the number of PCNA-positive cells and CD31-positive cells in the wound tissue of mice in diabetic wound group were significantly less than that in control wound group (with t values of 6.61 and 5.38, respectively, P<0.05). At 21 days after injury, the number of F4/80 and MPO double-positive cells in the wound tissue of mice in diabetic wound group was 3.3±0.8, which was significantly less than 12.7±1.8 in control wound group ( t=11.00, P<0.05). At 14 and 21 days after injury, the wound healing rates of mice in BMSC group were significantly higher than those in PBS group ( P<0.05); at 3, 7, 14, and 21 days after injury, the wound healing rates of mice in GAS6/BMSC group were significantly higher than those in BMSC group ( P<0.05). At 21 days after injury, the number of PCNA-positive cells in the wound tissue of mice in BMSC group was significantly higher than that in PBS group ( P<0.05), and the number of PCNA-positive cells and CD31-positive cells in the wound tissue of mice in GAS6/BMSC group were significantly higher than that in BMSC group ( P<0.05). At 21 days after injury, the number of F4/80 and MPO double-positive cells in the wound tissue of mice in BMSC group was 4.2±1.2, which was similar to 3.5±1.1 in PBS group ( P>0.05); the number of F4/80 and MPO double-positive cells in the wound tissue of mice in GAS6/BMSC group was 8.2±1.2, which was significantly more than that in BMSC group ( P<0.05). Conclusions:Dysfunctional efferocytosis of macrophage exists in the full-thickness skin defect wounds of diabetic mice, while GAS6/BMSC can promote wound healing by restoring the efferocytosis of macrophages.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

BACKGROUND: The association of systemic inflammatory response index (SIRI) with prognosis of coronary artery disease (CAD) patients has never been investigated in a large sample with long-term follow-up. This study aimed to explore the association of SIRI with all-cause and cause-specific mortality in a nationally representative sample of CAD patients from United States. METHODS: A total of 3386 participants with CAD from the National Health and Nutrition Examination Survey (NHANES) 1999-2018 were included in this study. Cox proportional hazards model, restricted cubic spline (RCS), and receiver operating characteristic curve (ROC) were performed to investigate the association of SIRI with all-cause and cause-specific mortality. Piece-wise linear regression and sensitivity analyses were also performed. RESULTS: During a median follow-up of 7.7 years, 1454 all-cause mortality occurred. After adjusting for confounding factors, higher lnSIRI was significantly associated with higher risk of all-cause (HR = 1.16, 95% CI: 1.09-1.23) and CVD mortality (HR = 1.17, 95% CI: 1.05-1.30) but not cancer mortality (HR = 1.17, 95% CI: 0.99-1.38). The associations of SIRI with all-cause and CVD mortality were detected as J-shaped with threshold values of 1.05935 and 1.122946 for SIRI, respectively. ROC curves showed that lnSIRI had robust predictive effect both in short and long terms. CONCLUSIONS SIRI was independently associated with all-cause and CVD mortality, and the dose-response relationship was J-shaped. SIRI might serve as a valid predictor for all-cause and CVD mortality both in the short and long terms.

The importance of gait assessment in the rehabilitation of cancer patients is gradually being recognized. However, quantitative analysis of balance ability in cancer patients is still limited. A total of 102 cancer patients meeting the inclusion criteria were recruited from Hefei Cancer Hospital, Chinese Academy of Sciences. Their balance ability was evaluated using the Berg Balance Scale (BBS). Gait data were collected by an electronic walkway and an IMU sensor system, including spatial-temporal and kinematic gait features such as step length, cadence, support time, and range of motion. Recursive feature elimination was used for feature selection. Ridge, Elastic Net, SVR, RF, and AdaBoost models were used to predict balance ability scores. Five-fold cross-validation was used to evaluate the performance of these models. Results show that the SVR model achieves the best performance with fifteen features (RMSE=3.22, R ²=0.91), followed by Ridge (RMSE=3.63, R ²=0.89). A method for evaluating balance ability based on gait features is proposed, providing a quantitative tool for personalized rehabilitation interventions in cancer patients.
Humans ; Postural Balance ; Neoplasms/rehabilitation* ; Gait ; Gait Analysis ; Biomechanical Phenomena ; Female

OBJECTIVE: To assess the efficacy of Qingda Granule (QDG) in ameliorating hypertension-induced cardiac damage and investigate the underlying mechanisms involved. METHODS: Twenty spontaneously hypertensive rats (SHRs) were used to develope a hypertension-induced cardiac damage model. Another 10 Wistar Kyoto (WKY) rats were used as normotension group. Rats were administrated intragastrically QDG [0.9 g/(kg•d)] or an equivalent volume of pure water for 8 weeks. Blood pressure, histopathological changes, cardiac function, levels of oxidative stress and inflammatory response markers were measured. Furthermore, to gain insights into the potential mechanisms underlying the protective effects of QDG against hypertension-induced cardiac injury, a network pharmacology study was conducted. Predicted results were validated by Western blot, radioimmunoassay immunohistochemistry and quantitative polymerase chain reaction, respectively. RESULTS: The administration of QDG resulted in a significant decrease in blood pressure levels in SHRs (P<0.01). Histological examinations, including hematoxylin-eosin staining and Masson trichrome staining revealed that QDG effectively attenuated hypertension-induced cardiac damage. Furthermore, echocardiography demonstrated that QDG improved hypertension-associated cardiac dysfunction. Enzyme-linked immunosorbent assay and colorimetric method indicated that QDG significantly reduced oxidative stress and inflammatory response levels in both myocardial tissue and serum (P<0.01). CONCLUSIONS Both network pharmacology and experimental investigations confirmed that QDG exerted its beneficial effects in decreasing hypertension-induced cardiac damage by regulating the angiotensin converting enzyme (ACE)/angiotensin II (Ang II)/Ang II receptor type 1 axis and ACE/Ang II/Ang II receptor type 2 axis.
Animals ; Drugs, Chinese Herbal/therapeutic use* ; Hypertension/pathology* ; Renin-Angiotensin System/drug effects* ; Rats, Inbred SHR ; Oxidative Stress/drug effects* ; Male ; Rats, Inbred WKY ; Blood Pressure/drug effects* ; Myocardium/pathology* ; Rats ; Inflammation/pathology*