BACKGROUND:Cerebral ischemic stroke is one of the main fatal and disabling diseases in the clinic,but only a few patients benefit from vascular recanalization in time,so it is urgent to explore new and effective therapy.As one of the critical pathological changes of ischemic stroke,the glial scar formed mainly by astrocytes is one major cause that hinders axonal regeneration and neurological recovery at the late stage of stroke. OBJECTIVE:To elucidate the pathological process and crucial signal regulatory mechanism of astrocytes in the formation of glial scar after ischemic stroke,as well as the potential therapeutic targets,to provide a theoretical reference for intervening astrocytic scar formation against ischemic stroke effectively,and novel strategies for promoting post-stroke rehabilitation. METHODS:The relevant articles published in CNKI,PubMed and Web of Science databases from 2010 to 2022 were retrieved.The search terms were"Ischemic stroke,Brain ischemi*,Cerebral ischemi*,Astrocyt*,Astroglia*,Glial scar,Gliosis,Astrogliosis"in Chinese and English.Finally,78 articles were included after screening and summarized. RESULTS AND CONCLUSION:(1)Astrocytes play an important role in the maintenance of central nervous system homeostasis.After ischemic stroke,astrocytes change from a resting state to an active state.According to the different severities of cerebral ischemic injury,astrocyte activation changes dynamically from swelling and proliferation to glial scar formation.(2)Mature astrocytes are stimulated to restart the cell cycle,then proliferate and migrate to lesions,which is the main source of the glial scar.Neural stem cells in the subventricular zone,neuron-glial antigen 2 precursor cells and ependymal precursor cells in the brain parenchyma can also differentiate into astrocytes.Endothelin-1,aquaporin 4,ciliary neurotrophic factor and connexins are involved in this process.In addition,chondroitin sulfate proteoglycan,as the main component of the extracellular matrix,forms the dense glial scar barrier with proliferated astrocytes,which hinders the polarization and extension of axons.(3)Activation or inhibition of crucial signal molecules involved in astrocyte activation,proliferation,migration and pro-inflammation functions regulate the glial scar formation.Transforming growth factor beta 1/Smad and Janus kinase/signal transducer and activator of transcription 3 are classical pathways related to astrogliosis,while receptor-interacting protein 1 kinase and glycogen synthase kinase 3β are significant molecules regulating the inflammatory response.However,there are relatively few studies on Smad ubiquitination regulatory factor 2 and Interleukin-17 and their downstream signaling pathways in glial scar formation,which are worthy of further exploration.(4)Drugs targeting astrogliosis-related signaling pathways,cell proliferation regulatory proteins and inflammatory factors effectively inhibit the formation of glial scar after cerebral ischemic stroke.Among them,the role of commonly used clinical drugs such as melatonin and valproic acid in regulating glial scar formation has been verified,which makes it possible to use drugs that inhibit glial scar formation to promote the recovery of neurological function in patients with stroke.(5)Considering the protective effects of glial scar in the acute phase,how to choose the appropriate intervention chance of drugs to maintain the protective effect of the glial scar while promoting nerve regeneration and repair in the local microenvironment is the direction of future efforts.

BACKGROUND:Ischemic stroke is a highly prevalent disease associated with apoptosis.Neuronal death occurs after cerebral ischemia,including necrosis and apoptosis.The ischemic core region is dominated by necrosis,while delayed neuronal death in the penumbra is dominated by apoptosis.The penumbra has become a target for the treatment of ischemic stroke.This bibliometric analysis was used to identify the characteristics,hotspots,and frontiers of global scientific output related to apoptosis in ischemic stroke over the past 5 years. OBJECTIVE:To analyze the role of apoptosis and its mechanisms in the pathological process of ischemic stroke through a bibliometric approach. METHODS:A total of 927 relevant literature records from 2018 to 2022 were retrieved from Science Citation Index Expanded(SCI-Expanded)and Social Science Citation Index Expanded(SSCI-Expanded)of the Web of Science Core Collection.Research trends and hotspots of apoptosis in ischemic stroke were visualized using Citespace,VOSviewer and Bibliometrix. RESULTS AND CONCLUSION:From 2018 to 2020,the number of papers on the role of apoptosis in ischemic stroke showed an upward trend,but in 2020,the number of papers began to reduce.China had the largest number of publications,and the United States ranked the second.Capital Medical University and BRAIN RESEARCH BULLETIN were the institutions and journals with the most articles,respectively.In recent years,the two keywords"expression"and"oxidative stress"have appeared more frequently.The bibliometric study showed that in the past 5 years,most of the studies focused on basic research,in which research on the role of apoptosis in ischemic stroke has gradually decreased in the last 3 years,showing a downward trend.On the contrary,nerve regeneration has gradually become a research hotspot,especially the regulation of neurotrophic factors under the influence of different mechanisms,and the research on angiogenesis and glial cell repair is on the rise.At the same time,apoptosis in nerve regeneration is a potential point of discovery.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective:To investigate the association of exposure to PM 2.5 and its constituents during pregnancy and fetal growth and to further identify critical windows of exposure for fetal growth. Methods:We included 4 089 mother-child pairs from the Jiangsu Birth Cohort Study between January 2016 and October 2019. Data of general characteristics, clinical information, daily average PM 2.5 exposure, and its constituents during pregnancy were collected. Fetal growth parameters, including head circumference (HC), abdominal circumference (AC), and femur length (FL), were measured by ultrasound after 20 weeks of gestation, and then estimated fetal weight (EFW) was calculated. Generalized linear mixed models were adopted to examine the associations of prenatal exposure to PM 2.5 and its constituents with fetal growth. Distributed lag nonlinear models were used to identify critical exposure windows for each outcome. Results:A 10 μg/m 3 increase in PM 2.5 exposure during pregnancy was associated with a decrease of 0.025 ( β=-0.025, 95% CI: -0.048- -0.001) in HC Z-score, 0.026 ( β=-0.026, 95% CI: -0.049- -0.003) in AC Z-score, and 0.028 ( β=-0.028, 95% CI:-0.052--0.004) in EFW Z-score, along with an increased risk of 8.5% ( RR=1.085, 95% CI: 1.010-1.165) and 13.5% ( RR=1.135, 95% CI: 1.016-1.268) for undergrowth of HC and EFW, respectively. Regarding PM 2.5 constituents, prenatal exposure to black carbon, organic matter, nitrate, sulfate (SO 42-) and ammonium consistently correlated with decreased HC Z-score. SO 42- exposure was also associated with decreased FL Z-scores. In addition, we found that gestational weeks 2-5 were critical windows for HC, weeks 4-13 and 19-40 for AC, weeks 4-13 and 23-37 for FL, and weeks 4-12 and 20-40 for EFW. Conclusions:Our findings demonstrated that exposure to PM 2.5 and its constituents during pregnancy could adversely affect fetal growth and the critical windows for different fetal growth parameters are not completely consistent.

Objective:To evaluate the efficacy and safety of oliceridine for treatment of moderate to severe pain after surgery with general anesthesia in patients.Methods:The patients with moderate to severe pain (numeric pain rating scale ≥4) after abdominal surgery with general anesthesia from 14 hospitals between July 6, 2021 and November 9, 2021 were included in this study. The patients were assigned to either experiment group or control group using a random number table method. Experiment group received oliceridine, while control group received morphine, and both groups were treated with a loading dose plus patient-controlled analgesia and supplemental doses for 24 h. The primary efficacy endpoint was the drug response rate within 24 h after giving the loading dose. Secondary efficacy endpoints included early (within 1 h after giving the loading dose) drug response rates and use of rescue medication. Safety endpoints encompassed the development of respiratory depression and other adverse reactions during treatment.Results:After randomization, both the full analysis set and safety analysis set comprised 180 cases, with 92 in experiment group and 88 in control group. The per-protocol set included 170 cases, with 86 in experiment group and 84 in control group. There were no statistically significant differences between the two groups in 24-h drug response rates, rescue analgesia rates, respiratory depression, and incidence of other adverse reactions ( P>0.05). The analysis of full analysis set showed that the experiment group had a higher drug response rate at 5-30 min after giving the loading dose compared to control group ( P<0.05). The per-protocol set analysis indicated that experiment group had a higher drug response rate at 5-15 min after giving the loading dose than control group ( P<0.05). Conclusions:When used for treatment of moderate to severe pain after surgery with general anesthesia in patients, oliceridine provides comparable analgesic efficacy to morphine, with a faster onset.

Objective:To explore the prognostic value of BRCA1-associated protein 1 (BAP1) expression loss in patients with malignant mesothelioma (MM) .Methods:A total of 82 MM patients from January 1998 to December 2017 in Zhejiang Province were selected to detect the expression of BAP1 protein by immunohistochemical analysis. Kaplan-Meier method was used to draw the survival curve, and multivariate Cox proportional risk model was used to analyze the factors affecting the survival rate.Results:Among 82 MM patients, 61 (74.4%) were female, aged (57±11) years. BAP1 protein expression was deficient in 39 patients (47.6%). The survival rate was correlated with the loss of BAP1 protein expression and age (χ 2=5.27, 5.66, P=0.022, 0.017). Subgroup analysis showed that loss of BAP1 protein expression was associated with better prognosis in MM patients <57 years of age, female, pleural MM, epithelial MM, and treated with drugs or surgery ( P<0.05). Multivariate model results showed that positive expression of BAP1 protein ( HR=3.75, 95% CI: 2.23-6.30, P<0.001) and age ≥57 years ( HR=1.66, 95% CI: 1.01-2.72, P=0.049) were risk factors for survival in patients with MM. Conclusion:Loss of BAP1 protein expression may be an independent prognostic factor in patients with MM, which is associated with longer survival.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.