Objective To use AI-assisted motor dysfunction assessment for quantitative evaluation of motor function in Parkinson's disease(PD)and multiple system atrophy-Parkinsonian type(MSA-P)in order to achieve accurate differential diagnosis.Methods A total of 105 participants aged ≥60 years were consecutively enrolled from the First and Third Medical Centers of Chinese PLA General Hospital between January and September 2024.Based on diagnostic criteria,they were divided into a PD group(48 cases),a MSA-P group(31 cases),and a control group(26 cases).The general information was collected,and the motor function was evaluated with Move-ment Dysfunction Assessment Software in order to assess the diagnostic value of the AI-assisted assessment in differentiating between PD and MSA-P.Results Significantly differences were observed among the three groups in terms of facial expression indicators,bilateral finger tapping frequency,bilateral hand movement frequency,right hand movement amplitude change rate,bilat-eral palm flipping frequency,bilateral toe tapping frequency,freezing load of bilateral toe tapping,bilateral leg flexibility frequency,right leg flexibility amplitude change rate,freezing load of bilat-eral leg flexibility,upright extension angular velocity,turnaround time,forward step frequency,backward step frequency,forward average stride length,backward average stride length,forward average walking speed,backward average walking speed,forward average step width,backward average step width,bilateral postural tremor frequency,bilateral postural tremor maximum am-plitude,bilateral action tremor frequency,bilateral action tremor maximum amplitude,and com-parison of bilateral resting tremor frequency(P＜0.05,P＜0.01).The MSA-P group exhibited significantly lower blink frequency,maximum amplitude and frequency of facial tremors,upright extension angular velocity,and step frequency,while higher ratio of mouth opening duration and longer turnaround time when compared with the PD group(P＜0.05,P＜0.01).The AUC value of the combined nine motor function indicators and the five facial expression indicators in differ-entiating PD from MSA-P was 0.943(95％CI:0.895-0.991,P=0.000)and 0.925(95％CI:0.870-0.981,P=0.000),respectively,both better than that of individual indicators.Conclusion Combi-nation assessment of facial expression,posture,gait with AI assistance can contribute to the dif-ferential diagnosis of PD and MSA-P.

Drug addiction is a chronic disease that causes serious physical and psychological harm to the individual,as well as damage to society.Biomarkers are indicators that differ significantly between healthy people and patients and are important for the diagnosis and treatment of diseases.The increasing incidence of drug addiction in recent years and the wider variety and number of new drugs has led to an increase in the study of biomarkers of drug addiction and their analysis in different biological samples.This paper reviews biomarkers of drug addiction in hair,blood,urine,and feces,to help to explore the biological signatures of drug addiction and facilitate its clinical diagnosis and treatment.

Drug addiction is a chronic disease that causes serious physical and psychological harm to the individual,as well as damage to society.Biomarkers are indicators that differ significantly between healthy people and patients and are important for the diagnosis and treatment of diseases.The increasing incidence of drug addiction in recent years and the wider variety and number of new drugs has led to an increase in the study of biomarkers of drug addiction and their analysis in different biological samples.This paper reviews biomarkers of drug addiction in hair,blood,urine,and feces,to help to explore the biological signatures of drug addiction and facilitate its clinical diagnosis and treatment.

Objective To use AI-assisted motor dysfunction assessment for quantitative evaluation of motor function in Parkinson's disease(PD)and multiple system atrophy-Parkinsonian type(MSA-P)in order to achieve accurate differential diagnosis.Methods A total of 105 participants aged ≥60 years were consecutively enrolled from the First and Third Medical Centers of Chinese PLA General Hospital between January and September 2024.Based on diagnostic criteria,they were divided into a PD group(48 cases),a MSA-P group(31 cases),and a control group(26 cases).The general information was collected,and the motor function was evaluated with Move-ment Dysfunction Assessment Software in order to assess the diagnostic value of the AI-assisted assessment in differentiating between PD and MSA-P.Results Significantly differences were observed among the three groups in terms of facial expression indicators,bilateral finger tapping frequency,bilateral hand movement frequency,right hand movement amplitude change rate,bilat-eral palm flipping frequency,bilateral toe tapping frequency,freezing load of bilateral toe tapping,bilateral leg flexibility frequency,right leg flexibility amplitude change rate,freezing load of bilat-eral leg flexibility,upright extension angular velocity,turnaround time,forward step frequency,backward step frequency,forward average stride length,backward average stride length,forward average walking speed,backward average walking speed,forward average step width,backward average step width,bilateral postural tremor frequency,bilateral postural tremor maximum am-plitude,bilateral action tremor frequency,bilateral action tremor maximum amplitude,and com-parison of bilateral resting tremor frequency(P＜0.05,P＜0.01).The MSA-P group exhibited significantly lower blink frequency,maximum amplitude and frequency of facial tremors,upright extension angular velocity,and step frequency,while higher ratio of mouth opening duration and longer turnaround time when compared with the PD group(P＜0.05,P＜0.01).The AUC value of the combined nine motor function indicators and the five facial expression indicators in differ-entiating PD from MSA-P was 0.943(95％CI:0.895-0.991,P=0.000)and 0.925(95％CI:0.870-0.981,P=0.000),respectively,both better than that of individual indicators.Conclusion Combi-nation assessment of facial expression,posture,gait with AI assistance can contribute to the dif-ferential diagnosis of PD and MSA-P.

The psychoactive properties of cannabinoids are well known,and there are controversies over whether cannabinoids can be used for therapeutic purposes worldwide.Δ9-tetrahydrocannabinol(THC)is the main psychoactive substance in cannabis.The neurological mechanisms of THC were only recently discovered,and its neurological mechanism of action is still not fully understood.The blood-brain barrier(BBB)is a very important structure protecting the brain and is the first line of defense preventing foreign substances from entering the brain.THC's lipophilic nature and its interaction with the endocannabinoid system make it more likely to act on the BBB.In this paper,we review the neurotoxic effects of THC,focusing on its effect and mechanism of action on the BBB,and provide a theoretical basis for studies elucidating the neural mechanism of THC.

Objective:To analyze and predict the future trend of the premature mortality of major chronic and non-communicable diseases in Anhui Province, evaluate the implementation of the "Healthy China 2030" Plan, and explore its influencing factors.Methods:Using data from death-cause surveillance and statistical yearbooks in Anhui, the trend prediction and analysis on influencing factors were conducted by using methods such as time series accumulation and logarithmic linear Joinpoint regression, principal component regression.Results:In Anhui, 28.10% of the deaths were premature ones, of which 84.40% were attributed to chronic and non-communicable diseases. In premature deaths attributed to chronic and non-communicable diseases, the deaths caused by malignant tumor and cardiovascular disease accounted for 45.88% and 41.65% respectively. The prediction results showed that the premature mortality of major chronic and non-communicable diseases would decrease in Anhui in the future, and by 2030, the goal in the "Healthy China 2030" Plan would be reached only in rural area. To reduce premature death, it is necessary to pay attention to the prevention and control of malignant tumor and cardiovascular disease. Men in urban area are the key population. Factors that reflect urban infrastructure had a significant impact on premature mortality of major chronic non-communicable diseases, such as garden and green space area per capita. Factors such as concentration of PM 2.5 had a negative impact on premature mortality of chronic non-communicable diseases, while factors such as garden and green space area per capita had a positive impact. Conclusions:Disease burden caused by chronic and non-communicable diseases, such as malignant tumor, exits in Anhui. Men in urban area are key population in the prevention and control of chronic and non-communicable diseases in the future.

Traumatic brain injury(TBI)is caused by the direct or indirect effects of external factors that result in structural or functional loss of brain tissue.Astrocytes are homeostatic cells in the central nervous system that proliferate and activate rapidly in the early stages of TBI.They then participate in a series of pathological processes,such as neuroinflammation,blood-brain barrier disruption,glial scarring,and excitotoxicity after injury,and thus play a crucial role in secondary neurological injury following TBI.This paper reviews the role of astrocytes in the repair of TBI damage,with the aim of providing new strategies for the prevention and treatment of TBI.

Traumatic brain injury(TBI)is caused by the direct or indirect effects of external factors that result in structural or functional loss of brain tissue.Astrocytes are homeostatic cells in the central nervous system that proliferate and activate rapidly in the early stages of TBI.They then participate in a series of pathological processes,such as neuroinflammation,blood-brain barrier disruption,glial scarring,and excitotoxicity after injury,and thus play a crucial role in secondary neurological injury following TBI.This paper reviews the role of astrocytes in the repair of TBI damage,with the aim of providing new strategies for the prevention and treatment of TBI.

Objective To explore the correlation between changes of gray matter volume and related cognitive impairment domains in patients with cognitive impairment of cerebral small vessel disease(CSVD)based on 7.0T magnetic resonance imaging(MRI)and voxel-based morphometry(VBM).Methods All subjects were recruited from the study on Correlation between Cerebral Deep Medullary Vein Morphology and Cognitive Impairment due to Cerebral Small Vessel Disease(registration No.:ChiCTR2100045136)from September 2021 to June 2023.We retrospectively enrolled CSVD patients with cognitive impairment as CSVD group and healthy controls with matched age,gender and education level as control group according to inclusion and exclusion criteria.Montreal cognitive assessment(MoCA)scale(Beijing version)score＜26 was divided into cognitive impairment.All subjects was assessed with MoCA,digit span test(DST),digit symbol substitution test(DSST),trail making test-A(TMT-A),verbal fluency test(VFT),Boston naming test(BNT)and auditory verbal learning test(AVLT).All subjects underwent 7.0T brain MRI scan to acquire T1-weighted three-dimensional magnetization prepared 2 rapid gradient echo(T1WI-MP2RAGE)for VBM analysis.General data and above cognitive function scores were compared between 2 groups.VBM analysis was used to compare the gray matter volume(GMV)between 2 groups and get mean GMV of significant brain regions of CSVD to explore the correlation between regions and cognitive function scores.Results(1)There were 18 individuals in control group,aged 55-70 years,and 19 individuals in CSVD group,aged 57-75 years.There was no significant difference in age,gender,education,body mass index,history of coronary heart disease,history of hyperlipidemia,smoking,drinking,total cholesterol,triglyceride,low density lipoprotein and high density lipoprotein between the two groups(all P＞0.05).But the proportion of hypertension and diabetes history in the CSVD group was higher than control group,and there were significant differences between the two groups(12/19 vs.5/18,7/19 vs.0;all P＜0.05).(2)The scores of MoCA scale(22.0[20.0,23.0]vs.27.0[26.0,28.0],Z=-5.242),DSST(18±9 vs.40±4,t=5.212),DST(10.6±2.5 vs.13.9±2.0,t=4.364),VFT(38±11 vs.47±8,t=3.224),AVLT-immediate memory(13±3 vs.21±4,t=6.877),AVLT-short delay recall(3.4±2.5 vs.6.9±2.2,t=4.555)and BNT(22.7±3.6 vs.27.0±2.1,t=4.357)in CSVD group were lower than those in the control group.The time taken to complete TMT-A in CSVD group was longer than the control group(93.00[76.04,125.69]s vs.29.77[25.75,40.97]s,Z=-4.832).The difference of the above between two group was statistically significant(all P＜0.01).(3)Brain parenchymal fraction in CSVD group was lower than control group,and there was significant difference between two group([78.2±4.3]％vs.[80.9±3.7]％,t=2.079,P＜0.05).VBM analysis showed that gray matter volume of right inferior temporal gyrus(rITG)and right Crus 2 of cerebellar hemisphere(rCERCRU2)in CSVD group was significantly lower than control group(both P＜0.05 and corrected by false discovery rate).(4)Partial correlation analysis showed a positive correlation between gray matter volume in rITG and AVLT-short delay recall score(r=0.543,P=0.036).Conclusions CSVD patients with cognitive impairment had gray matter atrophy in rITG and rCERCRU2 and the gray matter volume in rITG was correlated with delayed memory impairment.The results of this study need to be further verified.