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.

ObjectiveTo present the exploration and application of a prospective follow-up research method for acute infectious disease surveillance based on natural community populations， using COVID-19 infection as an example， and to provide a reference for improving the infectious disease surveillance and early warning system. MethodsA multi-stage probability proportional sampling method was employed to sample residents from all communities of 16 administrative districts in Shanghai， with households as the units. A cohort for acute infectious diseases based on natural community populations was established. The baseline survey was conducted for all cohort subjects， and COVID-19 antigen test kits were distributed. From December 21， 2022 to September 30， 2023， prospective follow-up monitoring of COVID-19 antigen and nucleic acid was carried out on the study subjects on a weekly basis. The baseline characteristics and follow-up information of the cohort subjects were described. ResultsThe cohort for acute infectious diseases included a total of 12 881 subjects， comprising 6 098 males （47.3%） and 6 783 females （52.7%）. The baseline survey revealed that 35.2% （4 540/12 881） of the subjects had a history of COVID-19 infection. During the follow-up period from December 21， 2022 to September 30， 2023， the average incidence density in the cohort was 0.61/person-year， with a higher incidence density in females （0.63/person-year） compared to males （0.59/person-year）. Individuals aged 60 and above （0.64/person-year） and those with underlying health conditions （0.67/person-year） had a higher incidence density. Healthcare workers showed a notably higher incidence density （0.84/person-year） than that in other occupational groups. As of September 30， 2023， a total of 340 subjects in the cohort experienced secondary infections， with a median interval of 170 days between the first and second infections. ConclusionThis study applies cohort study method to acute infectious disease surveillance， providing crucial data support for estimating infection rates and forecasting alerts for acute infectious diseases in the community. This method can be promoted and applied as a new approach for acute infectious disease surveillance.

Objective To summarize the epidemiological and clinical features of infectious diseases of the central nervous system(CNS)by a single-center analysis.Methods A retrospective analysis was conducted on the data of 1247 cases of CNS infectious diseases diagnosed and treated in the First Medical Center of PLA General Hospital from 2001 to 2020.Results The data for this group of CNS infectious diseases by disease type in descending order of number of cases were viruses 743(59.6％),Mycobacterium tuberculosis 249(20.0％),other bacteria 150(12.0％),fungi 68(5.5％),parasites 18(1.4％),Treponema pallidum 18(1.4％)and rickettsia 1(0.1％).The number of cases increased by 177 cases(33.1％)in the latter 10 years compared to the previous 10 years(P<0.05).No significant difference in seasonal distribution pattern of data between disease types(P>0.05).Male to female ratio is 1.87︰1,mostly under 60 years of age.Viruses are more likely to infect students,most often at university/college level and above,farmers are overrepresented among bacteria and Mycobacterium tuberculosis,and more infections of Treponema pallidum in workers.CNS infectious diseases are characterized by fever,headache and signs of meningeal irritation,with the adductor nerve being the more commonly involved cranial nerve.Matagenomic next-generation sequencing improves clinical diagnostic capabilities.The median hospital days for CNS infectious diseases are 18.00(11.00,27.00)and median hospital costs are ￥29,500(￥16,000,￥59,200).The mortality rate from CNS infectious diseases is 1.6％.Conclusions The incidence of CNS infectious diseases is increasing last ten years,with complex clinical presentation,severe symptoms and poor prognosis.Early and accurate diagnosis and standardized clinical treatment can significantly reduce the morbidity and mortality rate and ease the burden of disease.

Objective To assess the effectiveness of Healthcare Failure Mode and Effect Analysis(HFMEA)in the intravenous thrombolysis process for patients with Acute Ischemic Stroke(AIS).Methods The targeted and comprehensive emergency care plan was constructed using HFMEA methodology.This plan was then applied to optimize the intravenous thrombolysis process in the target hospitals.Key indicators were evaluated before and after the intervention using t-tests,chi-square tests,and non-parametric tests.Results After the implementation of HFMEA,the mean Risk Priority Number value for the intravenous thrombolysis process in AIS decreased compared to before implementation.Additionally,the rate of intravenous thrombolysis within 4.5 hours of onset increased to 54％.The HFMEA model management group showed an 8％improvement compared to the conventional management group.The median time between patient admission and the start of intravenous thrombolysis door to needle time(DNT)was shorter,hospitalisation costs were lower,and National Institutes of Health Stroke Scale scores were reduced at 1 and 2 weeks post-treatment,as well as at discharge.However,there was no significant difference in the number of hospital days between the two groups.Conclusion The use of HFMEA management tools can effectively improve the intravenous thrombolysis process in patients with AIS.This can increase the rate of reperfusion therapy in AIS,shorten the time to DNT,and improve early neurological function.Additionally,it can promote patient health and reduce the burden on families.

Objective To assess the effectiveness of Healthcare Failure Mode and Effect Analysis(HFMEA)in the intravenous thrombolysis process for patients with Acute Ischemic Stroke(AIS).Methods The targeted and comprehensive emergency care plan was constructed using HFMEA methodology.This plan was then applied to optimize the intravenous thrombolysis process in the target hospitals.Key indicators were evaluated before and after the intervention using t-tests,chi-square tests,and non-parametric tests.Results After the implementation of HFMEA,the mean Risk Priority Number value for the intravenous thrombolysis process in AIS decreased compared to before implementation.Additionally,the rate of intravenous thrombolysis within 4.5 hours of onset increased to 54％.The HFMEA model management group showed an 8％improvement compared to the conventional management group.The median time between patient admission and the start of intravenous thrombolysis door to needle time(DNT)was shorter,hospitalisation costs were lower,and National Institutes of Health Stroke Scale scores were reduced at 1 and 2 weeks post-treatment,as well as at discharge.However,there was no significant difference in the number of hospital days between the two groups.Conclusion The use of HFMEA management tools can effectively improve the intravenous thrombolysis process in patients with AIS.This can increase the rate of reperfusion therapy in AIS,shorten the time to DNT,and improve early neurological function.Additionally,it can promote patient health and reduce the burden on families.

ObjectiveHuman Ku70 protein mainly involves the non-homologous end joining (NHEJ) repair of double-stranded DNA breaks (DSB) through its DNA-binding properties, and it is recently reported having an RNA-binding ability. This paper is to explore whether Ku70 has RNA helicase activity and affects miRNA maturation. MethodsRNAs bound to Ku protein were analyzed by RNA immunoprecipitation sequencing (RIP-seq) and bioinfomatic anaylsis. The expression relationship between Ku protein and miRNAs was verified by Western blot (WB) and quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) assays. Binding ability of Ku protein to the RNAs was tested by biolayer interferometry (BLI) assay. RNA helicase activity of Ku protein was identified with EMSA assay. The effect of Ku70 regulated miR-124 on neuronal differentiation was performed by morphology analysis, WB and immunofluorescence assays with or without Zika virus (ZIKV) infection. ResultsWe revealed that the Ku70 protein had RNA helicase activity and affected miRNA maturation. Deficiency of Ku70 led to the up-regulation of a large number of mature miRNAs, especially neuronal specific miRNAs like miR-124. The knockdown of Ku70 promoted neuronal differentiation in human neural progenitor cells (hNPCs) and SH-SY5Y cells by boosting miR-124 maturation. Importantly, ZIKV infection reduced the expression of Ku70 whereas increased expression of miR-124 in hNPCs, and led to morphologically neuronal differentiation. ConclusionOur study revealed a novel function of Ku70 as an RNA helicase and regulating miRNA maturation. The reduced expression of Ku70 with ZIKV infection increased the expression of miR-124 and led to the premature differentiation of embryonic neural progenitor cells, which might be one of the causes of microcephaly.

ObjectiveExisting artificial vision devices can be divided into two types: implanted devices and extracorporeal devices, both of which have some disadvantages. The former requires surgical implantation, which may lead to irreversible trauma, while the latter has some defects such as relatively simple instructions, limited application scenarios and relying too much on the judgment of artificial intelligence (AI) to provide enough security. Here we propose a system that has voice interaction and can convert surrounding environment information into tactile commands on head and neck. Compared with existing extracorporeal devices, our device can provide a larger capacity of information and has advantages such as lower cost, lower risk, suitable for a variety of life and work scenarios. MethodsWith the latest remote wireless communication and chip technologies, microelectronic devices, cameras and sensors worn by the user, as well as the huge database and computing power in the cloud, the backend staff can get a full insight into the scenario, environmental parameters and status of the user remotely (for example, across the city) in real time. In the meanwhile, by comparing the cloud database and in-memory database and with the help of AI-assisted recognition and manual analysis, they can quickly develop the most reasonable action plan and send instructions to the user. In addition, the backend staff can provide humanistic care and emotional sustenance through voice dialogs. ResultsThis study originally proposes the concept of “remote virtual companion” and demonstrates the related hardware and software as well as test results. The system can not only achieve basic guide functions, for example, helping a person with visual impairment to shop in supermarkets, find seats at cafes, walk on the streets, construct complex puzzles, and play cards, but also can meet the demand for fast-paced daily tasks such as cycling. ConclusionExperimental results show that this “remote virtual companion” is applicable for various scenarios and demands. It can help blind people with their travels, shopping and entertainment, or accompany the elderlies with their trips, wilderness explorations, and travels.

Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95％ confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.