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: 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: 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.

In the field of dental aesthetics,digital aesthetic design plays a crucial role in helping dentists to predict treatment outcomes vis-ually,as well as in enhancing the consistency of knowledge and understanding of aesthetic goals between dentists and patients.It serves as the foundation for achieving ideal aesthetic effects.However,there is no clear standard for this digital process currently in China and abroad.Many dentists lack of systematic understanding of how to carry out digital aesthetic design for treatment.To establish standardized processes for dental aesthetic design and to improve the homogeneity of treatment outcomes,Chinese Society of Digital Dental Industry(CSD-DI)convened domestic experts in related field to compile this consensus.This article elaborates on the key aspects of digital aesthetic data collection,integration steps,and the digital aesthetic design process.It also formulates a decision tree for dental aesthetics at macro level and outlines corresponding workflows for various clinical scenarios,serving as a reference for clinicians.

Extracting extracts of secondary metabolites from the karst cave fungus Metarhizium anisopliae NHC-M3-2 from the Yilingyan Scenic Area in Guangxi. Ten compounds were isolated and purified from fungal secondary metabolites using thin-layer chromatography and high-performance liquid chromatography. 7-Hydroxy-3-hydroxypropyl-5,6-dimethylisochrome-1-one (1) and 7-hydroxy-3,5,6-trimethyl-isochromen-1-one (2) were new isocoumarin compounds, N-acetyl phenylalanine (3), chaetosumin J (4), 2-one-13-hydroxy-3,5,8,7(11)-eudesmatetraen-12,8-olide (5), 1H-indole-3-carboxaldehyde (6), irpexolaceus B (7), irlactin L (8), cytochalasin K (9), and helvolic acid (10), a total of 8 known compounds. The structure of the compound was determined using methods such as NMR and mass spectrometry. The tumor cytotoxicity of the compound was evaluated using the CCK-8 method. The results showed that the IC₅₀ of compound 2 on HepG2 cells was 29.83 µmol·L^-1, and compound 9 on HCT116 cells was 27.44 µmol·L^-1.

Prostate cancer (PCa) is the second most common cancers among men worldwide, with a rapidly increasing trend in incidence and mortality in recent years. The occurrence and development of PCa are closely related to autophagy, and autophagic cell death can promote or inhibit the proliferation and survival of PCa cells. This article reviewed the molecular pathways and related regulatory mechanisms of autophagic cell death inhibiting PCa progression, aiming to explore new PCa treatment methods.

Humans ; Nasal Cavity ; Melanoma ; Skin Neoplasms ; Paranasal Sinuses

In this study, we investigated the pharmacological effect and possible molecular mechanism of higenamine (HG) in isoproterenol (ISO)-induced myocardial infarction (MI). All procedures were approved by the Institutional Animal Care and Use Committee of the Guangzhou University of Chinese Medicine. ISO was used to induce MI model in rats and H9c2 cells. The effects of HG on biomarkers and cardiac function in MI rats were evaluated by enzyme linked immunosorbent assay (ELISA), echocardiography and hematoxylin-eosin staining (HE). The expression of apoptosis and autophagy related proteins were detected by Western blot in myocardial tissue and H9c2 cells, as well as methyltransferase-like 3 (METTL3) and transcription factor EB (TFEB) protein expression. Molecular docking was used to evaluate the interaction between HG and METTL3. The results showed that HG significantly improved cardiac function and pathologic changes in ISO-induced MI, and inhibited the levels of MI-related biomarkers such as creatine kinase Mb (CK-MB), creatine kinase (CK) and lactate dehydrogenase (LDH). Mechanism studies showed that HG inhibited the expression of apoptosis-related proteins (Bax/Bcl2, caspase3, cleaved-caspase3). Interestingly, HG up-regulated the expression of autophagy related protein Beclin1, promoted autophagy flux, and decreased the ratio of light chain 3B-I/light chain 3B-II (LC-3B-I/LC-3B-II). Further studies found that HG increased the autophagy regulator TFEB and inhibited METTL3 expression. Molecular docking results showed that HG had a good interaction with METTL3. Taken together, HG has a potential anti-MI effect via regulating METTL3/TFEB signaling pathway-mediated autophagy.

Objective To measure the prevalence of mental health symptoms and identify the associated factors among college students at the beginning of coronavirus disease 2019(COVID-19)outbreak in China. Methods We carried out a multi-center cross-sectional study via snowball sampling and convenience sampling of the college students in different areas of China.The rates of self-reported depression,anxiety,and stress and post-traumatic stress disorder(PTSD)were assessed via the 21-item Depression-Anxiety-Stress Scale(DASS-21)and the 6-item Impact of Event Scale-Revised(IES-6),respectively.Covariates included sociodemographic characteristics,health-related data,and information of the social environment.Data pertaining to mental health service seeking were also collected.Multivariate Logistic regression analyses were performed to identify the risk factors. Results A total of 3641 valid questionnaires were collected from college students.At the beginning of the COVID-19 outbreak,535(14.69%)students had negative emotions,among which 402(11.04%),381(10.49%),and 171(4.90%)students had the symptoms of depression,anxiety,and stress,respectively.Meanwhile,1245(34.19%)college students had PTSD.Among the risk factors identified,male gender was associated with a lower likelihood of reporting depression symptoms(AOR=0.755,P=0.037],and medical students were at higher risk of depression and stress symptoms than liberal arts students(AOR=1.497,P=0.003;AOR=1.494,P=0.045).Family support was associated with lower risks of negative emotions and PTSD in college students(AOR=0.918,P<0.001;AOR=0.913,P<0.001;AOR=0.899,P<0.001;AOR=0.971,P=0.021). Conclusions College students were more sensitive to public health emergencies,and the incidence of negative emotions and PTSD was significantly higher than that before the outbreak of COVID-19.More attention should be paid to female college students who were more likely to develop negative emotions.We should strengthen positive and proper propaganda via mass media and help college students understand the situation and impact of COVID-19.Furthermore,we should enhance family support for college students.The government and relevant agencies need to provide appropriate mental health services to the students under similar circumstances to avoid the deterioration of their mental well-being.
COVID-19/epidemiology* ; Cross-Sectional Studies ; Female ; Health Status ; Humans ; Male ; Students/psychology* ; Universities

Objective: To investigate the prevalence of suicidal ideation among MSM, and to explore the influence of perceived social support and depression on suicidal ideation and the possible pathway. Methods: MSM who are ≥18 years, HIV-negative, and ever had sex with men (oral sex/anal sex) in the last year participated in is study. Cross-sectional survey and convenient sampling method were used to recruit MSM through a male social interaction platform Blued 7.5 software from December 2020 to March 2021, with a questionnaire survey. Demographic questionnaire, Perceived Social Support Questionnaire and Center for Epidemiologic Studies Depression Scale were employed to collect data. Mplus 8.3 was used for data analysis. Results: Among 1 394 eligible MSM participants, 25.7% (358/1 394) had suicidal ideation. Perceived social support could have a direct effect on suicidal ideation (β=-0.11, P=0.009), and an indirect effect on suicidal ideation through depression (β=-0.18, P<0.001). Conclusions: Suicidal ideation was found to be lower in MSM with a higher level of perceived social support and a lower level of depression. Using social media to improve MSM's perceived social support and reduce depressive symptoms might be an effective means to prevent suicidal ideation.
Cross-Sectional Studies ; Depression/epidemiology* ; Homosexuality, Male ; Humans ; Male ; Sexual Behavior ; Sexual and Gender Minorities ; Social Support ; Suicidal Ideation