BACKGROUND:Curcumin is the main active ingredient of turmeric and has significant medicinal value in anti-tumor,anti-inflammatory,antioxidant and other aspects.However,its poor water solubility,unstable chemical properties and easy decomposition lead to difficulty in extracting curcumin and low extraction yield.Therefore,it is particularly important to optimize the curcumin extraction method.OBJECTIVE:To enhance the extraction yield and utilization value of curcumin and optimize the curcumin extraction process and curcumin nanoparticle preparation process.METHODS:Curcumin was extracted from turmeric by ethanol extraction,ultrasonic extraction,ionic liquid extraction,enzyme extraction,and ionic liquid combined with ultrasonic assisted enzyme extraction.The curcumin extraction yield was detected by high performance liquid chromatography;the best extraction method was determined,and subsequent process optimization experiments were carried out.The curcumin extraction yield was the response value with the type of ionic liquid,reaction temperature,ultrasonic time,liquid-to-solid ratio,ionic liquid concentration,and enzyme-drug mass ratio as parameters.The optimal production process of ionic liquid combined with ultrasonic assisted enzyme extraction was determined by single factor combined response surface experiment.The optimal process for preparing curcumin nanoparticles by ionic crosslinking method was determined by single factor combined response surface experiment with acetic acid concentration,chitosan to sodium tripolyphosphate mass ratio,stirring rate,curcumin mass concentration,sodium tripolyphosphate mass concentration,and chitosan mass concentration as parameters,and drug encapsulation efficiency as response value.Curcumin nanoparticles were prepared under the optimal process,and the particle size,polydispersity index,Zata potential value,drug loading,stability,hemolysis rate,and antioxidant capacity in vivo and in vitro of the nanoparticles were detected.RESULTS AND CONCLUSION:(1)Among the five extraction methods,the curcumin yield of ionic liquid combined with ultrasound-assisted enzyme extraction was the highest,and this method was selected as the curcumin extraction method for subsequent experiments.The results of single factor combined response surface experiment showed that the optimal process for curcumin extraction was:ionic liquid selected 1-hexyl-3-methylimidazolium chloride,reaction temperature 55 ℃,liquid-to-solid ratio 40 mL/g,ultrasound time 57 minutes,ionic liquid concentration 57％,enzyme-drug mass ratio 3.5:10,and the obtained turmeric extraction yield was 3.10％.The optimal preparation process of curcumin nanoparticles was:glacial acetic acid concentration 0.5％,chitosan and sodium tripolyphosphate mass ratio 5.0:1,stirring speed 150 r/min,curcumin mass concentration 2.23 mg/mL,sodium tripolyphosphate mass concentration 1.45 mg/mL,chitosan mass concentration 3.63 mg/mL,and the obtained drug encapsulation efficiency was 90.61％.(2)The drug loading of curcumin nanoparticles was(14.49±0.23)％,the average particle size was(76.95±1.65)nm,the polydispersity coefficient was 0.15±0.02,and the Zata potential value was(32.37±1.46)mV.The curcumin nanoparticles had good stability and blood compatibility,did not induce hemolysis,and had stronger antioxidant capacity in vivo and in vitro than free curcumin.(3)The results show that the process optimization not only solves the problems of low extraction yield,poor solubility,and low bioavailability of curcumin,but also enhances its antioxidant activity in vivo and in vitro.

BACKGROUND:Curcumin is the main active ingredient of turmeric and has significant medicinal value in anti-tumor,anti-inflammatory,antioxidant and other aspects.However,its poor water solubility,unstable chemical properties and easy decomposition lead to difficulty in extracting curcumin and low extraction yield.Therefore,it is particularly important to optimize the curcumin extraction method.OBJECTIVE:To enhance the extraction yield and utilization value of curcumin and optimize the curcumin extraction process and curcumin nanoparticle preparation process.METHODS:Curcumin was extracted from turmeric by ethanol extraction,ultrasonic extraction,ionic liquid extraction,enzyme extraction,and ionic liquid combined with ultrasonic assisted enzyme extraction.The curcumin extraction yield was detected by high performance liquid chromatography;the best extraction method was determined,and subsequent process optimization experiments were carried out.The curcumin extraction yield was the response value with the type of ionic liquid,reaction temperature,ultrasonic time,liquid-to-solid ratio,ionic liquid concentration,and enzyme-drug mass ratio as parameters.The optimal production process of ionic liquid combined with ultrasonic assisted enzyme extraction was determined by single factor combined response surface experiment.The optimal process for preparing curcumin nanoparticles by ionic crosslinking method was determined by single factor combined response surface experiment with acetic acid concentration,chitosan to sodium tripolyphosphate mass ratio,stirring rate,curcumin mass concentration,sodium tripolyphosphate mass concentration,and chitosan mass concentration as parameters,and drug encapsulation efficiency as response value.Curcumin nanoparticles were prepared under the optimal process,and the particle size,polydispersity index,Zata potential value,drug loading,stability,hemolysis rate,and antioxidant capacity in vivo and in vitro of the nanoparticles were detected.RESULTS AND CONCLUSION:(1)Among the five extraction methods,the curcumin yield of ionic liquid combined with ultrasound-assisted enzyme extraction was the highest,and this method was selected as the curcumin extraction method for subsequent experiments.The results of single factor combined response surface experiment showed that the optimal process for curcumin extraction was:ionic liquid selected 1-hexyl-3-methylimidazolium chloride,reaction temperature 55 ℃,liquid-to-solid ratio 40 mL/g,ultrasound time 57 minutes,ionic liquid concentration 57％,enzyme-drug mass ratio 3.5:10,and the obtained turmeric extraction yield was 3.10％.The optimal preparation process of curcumin nanoparticles was:glacial acetic acid concentration 0.5％,chitosan and sodium tripolyphosphate mass ratio 5.0:1,stirring speed 150 r/min,curcumin mass concentration 2.23 mg/mL,sodium tripolyphosphate mass concentration 1.45 mg/mL,chitosan mass concentration 3.63 mg/mL,and the obtained drug encapsulation efficiency was 90.61％.(2)The drug loading of curcumin nanoparticles was(14.49±0.23)％,the average particle size was(76.95±1.65)nm,the polydispersity coefficient was 0.15±0.02,and the Zata potential value was(32.37±1.46)mV.The curcumin nanoparticles had good stability and blood compatibility,did not induce hemolysis,and had stronger antioxidant capacity in vivo and in vitro than free curcumin.(3)The results show that the process optimization not only solves the problems of low extraction yield,poor solubility,and low bioavailability of curcumin,but also enhances its antioxidant activity in vivo and in vitro.

With rapid development of artificial intelligence(AI)technology,AI is reshaping new ecology in field of educa-tion.With promotion of AI,AI digital teaching materials will further clearly present knowledge context and build a new paradigm and new form of digital teaching materials.In context of general health,integration of medicine and prevention has become an important trend in medical and health field.However,at present,there is a lack of medical and preventive integration resources,and a single paper textbook cannot achieve depth and breadth of knowledge system of medical and preventive integration,which is difficult to adapt to development trend of AI enabling education.Therefore,it is urgent to use AI technology to develop and expand digital teaching materials for medical and prevention integration and realize resource penetration.Immune system is an important defense line of physi-cal diseases,and there is a close relationship between integration of medical and prevention.This paper aims to explore application path of developing digital teaching materials in medical education by AI technology.This concept of medical integration runs through every chapter and case analysis of AI textbooks,strengthening shift from"treatment-centered"to"health-centered"concept.Taking immune system as an example,this paper conducts in-depth analysis,develops and shares digital teaching materials by integrating medical knowledge,prevention strategies and AI technology,and provides new ideas and methods for medical education.

OBJECTIVE To explore the effects of meropenem exposure and degradation levels on clinical efficacy in patients with purulent meningitis （PM）. METHODS A total of 131 PM patients treated with meropenem at the Affiliated Suzhou Hospital of Nanjing Medical University from January 2022 to June 2025 were prospectively included. Relevant data were collected and divided into a cured group （91 cases） and a non-cured group （40 cases） based on the efficacy. High-performance liquid chromatography-tandem mass spectrometry was used to determine the concentration of meropenem and its open-loop metabolites. Risk factors that affect efficacy were screened， and their predictive power and correlation were evaluated by univariate analysis， and multivariate Logistic regression analysis， receiver operating characteristic （ROC） curves， and correlation analysis. RESULTS Univariate analysis showed that serum creatinine， creatinine clearance rate， minimum inhibitory concentration of meropenem ≥16 μg/mL， cerebrospinal fluid red blood cell count， cerebrospinal fluid white blood cell count， cerebrospinal fluid glucose content， blood trough concentration， blood open-loop metabolite concentration/trough concentration ratio， and intrathecal injection were all correlated with efficacy （P＜0.05）. The results of multiple Logistic regression analysis showed that serum creatinine blood open-loop metabolite concentration/trough concentration ratio， intrathecal injection， and cerebrospinal fluid glucose content were influencing factors for suboptimal anti-infective ltt efficacy （P＜0.05）. ROC curve analysis showed that when the blood open-loop metabolite concentration/trough concentration ratio was greater than 2.854 （AUC＝0.647）， serum creatinine was less than 59.5 μmol/L （AUC＝0.647）， and cerebrospinal fluid glucose content was less than 3.37 mmol/L （AUC＝0.709）， the risk of treatment failure significantly increased （P＜0.05）. Correlation analysis showed that the blood trough concentration of meropenem was positively correlated with the concentration of its open-loop metabolites （R 2＝0.134 5， P＜0.000 1）. CONCLUSIONS Insufficient exposure level and rapid degradation of meropenem are key mechanisms affecting the anti-infective efficacy of PM. Elevated blood open-loop metabolite concentration/ trough concentration ratio， low serum creatinine level， lack of intrathecal injection， and low cerebrospinal fluid glucose content are independent risk factors for poor efficacy.

Objective:To explore the distribution characteristics of HBsAg levels in treatment-na?ve and treatment-experienced patients with chronic hepatitis B (CHB) in China.Methods:Data were obtained from the China Registry of Hepatitis B (CR-HepB) platform from the establishment of the platform to April 11, 2024. Patients with CHB who were treatment-na?ve and treatment-experienced with nucleos(t)ide analogs (NAs) were included. Relevant clinical data were collected. The distribution of hepatitis B surface antigen (HBsAg) status, as well as the levels in populations of different age groups after different antiviral treatment durations, were retrospectively analyzed. Normally and non-normally distributed measured data were represented by Mean± SD, and M( Q1, Q3). Results:A total of 13 505 treatment-na?ve patients and 6 390 treatment-experienced patients were included in the analysis. The proportions of treatment-na?ve patients with HBsAg<100, <500, and <1 500 IU/mL were 10.51%, 28.47%, and 46.85%, and the corresponding proportions of treatment-experienced patients were 12.88%, 29.84%, and 52.07%. The proportions of treatment-na?ve patients with HBsAg levels≥1 500, ≥3 000, and≥8 000 IU/mL were 53.15%, 38.17%, and 15.62%, and the corresponding proportions of treatment-experienced patients were 47.93%, 31.77%, and 10.39%. HBsAg level showed a trend of gradual decrease with the increase of antiviral treatment time. The proportion of treatment-experienced patients with HBsAg<100 IU/mL increased from 12.73% when the treatment duration was less than three years to 26.92% when the treatment duration was≥10 years, while the proportion of patients with HBsAg levels≥3 000 IU/mL or≥8 000 IU/mL decreased from 34.66% to 23.08% and from 12.19% to 5.77%, respectively. The proportion of patients with HBsAg<100, <500, and<1 500 IU/mL increased with age, while the proportion of patients with HBsAg≥1 500, ≥3 000, and ≥8 000 IU/mL decreased sequentially.Conclusions:The CR-HepB platform provides a basis for clarifying the serum HBsAg levels in treatment-na?ve and treatment-experienced CHB patients in China. The HBsAg status indicates that with a prolonged antiviral treatment duration, there is a gradual decline trend in HBsAg level.

Objective:To investigate the role of dynamic changes in liver stiffness measurement (LSM) in predicting liver-related end-point events (LREs) occurrence in patients with chronic hepatitis B (CHB) with liver fibrosis during long-term antiviral therapy.Methods:Data were collected from CHB patients whose liver biopsy results showed Metavir fibrosis stage F2～F4 or clinically diagnosed cirrhosis. Entecavir antiviral therapy was mainly administered. Follow-up was conducted once every six months. Clinical data such as demographic information, blood routine tests, liver biochemical parameters, HBV virological and serological test results, and LSM were collected. Dynamic changes in LSM were categorized into four types based on LSM levels before treatment (0y) and following two years of antiviral therapy (2y) : (1) LSM 0y < 10 kPa and LSM 2y < 10 kPa, i.e., LSM persisted < 10 kPa; (2) LSM 0y < 10 kPa and LSM 2y ≥ 10 kPa, i.e., LSM increased to ≥ 10 kPa; (3) LSM 0y ≥ 10 kPa and LSM 2y < 10 kPa, i.e., LSM decreased to < 10 kPa; (4) LSM 0y ≥ 10 kPa and LSM 2y ≥ 10 kPa, i.e., LSM persisted ≥ 10 kPa. The predictive role of the dynamic changes of LSM in the occurrence of LREs was analyzed. The Wilcoxon rank-sum test was used for quantitative data. Fisher's exact test was used for categorical data. Multivariate analysis was performed using the Cox proportional hazards regression model. Survival curves were plotted and compared using the Kaplan-Meier. Results:A total of 713 CHB cases with liver fibrosis were included, among whom 512 had cirrhosis. The cumulative incidence of LREs following two years of antiviral therapy was low in patients with LSM 0y < 10 kPa during follow-up (all patients: LSM persisted < 10 kPa 1.6% vs. LSM increased to ≥ 10 kPa 0%; cirrhosis subgroup: LSM persisted < 10 kPa 0% vs. LSM increased to ≥ 10 kPa 0%). The 5-year cumulative incidence of LREs following two years of antiviral treatment was significantly higher in patients with LSM0y ≥ 10 kPa than in those with LSM persisting ≥ 10 kPa and those with LSM decreasing to < 10 kPa during follow-up (all patients: LSM persisted ≥ 10 kPa 12.4% vs. LSM decreased to < 10 kPa 3.6%; cirrhosis subgroup: LSM persisted ≥ 10 kPa 12.6% vs. LSM decreased to < 10 kPa 4.3%). Patients with LSM persisting at ≥ 10 kPa had a significantly increased risk of LREs following two years of antiviral treatment compared with those whose LSM decreased to <10 kPa during follow-up after adjusting for age, gender, baseline body mass index, platelet count, and alanine aminotransferase (all patients, aHR=2.96, 95% CI: 1.41～6.24, P=0.005; cirrhosis subgroup, aHR=2.74, 95% CI:1.26～5.95, P=0.011). Conclusions:LSM<10 kPa before antiviral treatment had a lower risk of liver-related endpoint events following two years of treatment among CHB patients with liver fibrosis. LSM ≥10 kPa before antiviral treatment and LSM persisted ≥10 kPa two years following treatment had a significantly higher occurrence risk of liver-related endpoints than LSM<10 kPa following treatment among CHB patients with liver fibrosis.

With rapid development of artificial intelligence(AI)technology,AI is reshaping new ecology in field of educa-tion.With promotion of AI,AI digital teaching materials will further clearly present knowledge context and build a new paradigm and new form of digital teaching materials.In context of general health,integration of medicine and prevention has become an important trend in medical and health field.However,at present,there is a lack of medical and preventive integration resources,and a single paper textbook cannot achieve depth and breadth of knowledge system of medical and preventive integration,which is difficult to adapt to development trend of AI enabling education.Therefore,it is urgent to use AI technology to develop and expand digital teaching materials for medical and prevention integration and realize resource penetration.Immune system is an important defense line of physi-cal diseases,and there is a close relationship between integration of medical and prevention.This paper aims to explore application path of developing digital teaching materials in medical education by AI technology.This concept of medical integration runs through every chapter and case analysis of AI textbooks,strengthening shift from"treatment-centered"to"health-centered"concept.Taking immune system as an example,this paper conducts in-depth analysis,develops and shares digital teaching materials by integrating medical knowledge,prevention strategies and AI technology,and provides new ideas and methods for medical education.

BACKGROUND:Previous studies found that the proliferative scar-specific long non-coding RNA lncRNA HSFAS is a novel biomarker that can be used in the diagnosis of hypertrophic scar,but how it functions in hypertrophic scar is not clear. OBJECTIVE:To investigate the role and mechanism of lncRNA HSFAS in hypertrophic scar.METHODS:Fresh scar tissue and surrounding normal skin tissue samples from three patients with hypertrophic scar were collected,and tissue immunofluorescence was used to detect the expression of lncRNA HSFAS in frozen sections of two skin tissues. Primary fibroblasts were isolated from proliferative scarred skin tissue and normal skin tissue and cultured by enzyme digestion method. Quantitative real-time PCR was used to detect the mRNA expression of lncRNA HSFAS in cells. The proteins bound to lncRNA HSFAS were detected by RNA pull-down combined mass spectrometry. GO and KEGG were used to analyze the main functions and pathways of lncRNA HSFAS involved in hypertrophic scar progression. The targeted binding of lncRNA HSFAS to proteins was determined by catRAPID and RPISeq website analysis. RESULTS AND CONCLUSION:Compared with normal skin tissue and fibroblasts from normal skin tissue,the expression of lncRNA HSFAS in human hypertrophic scar tissue and primary fibroblasts from hypertrophic scar tissue was significantly increased (P<0.05). There were 510 proteins clearly bound to lncRNA HSFAS by RNA pull-down combined mass spectrometry. The results of GO and KEGG analyses showed that these proteins were mainly involved in RNA splicing and processing,chromosome synthesis and separation,and cell cycle. Among them,the proteins involved in RNA splicing and processing included scaffold attachment factor B2 and DICER1,and the binding fraction with lncRNA HSFAS was higher. The results of bioinformatics analysis showed that lncRNA HSFAS was bound to scaffold attachment factor B2 and DICER1 proteins. To conclude,lncRNA HSFAS may affect gene expression by interacting with scaffold attachment factor B2 and DICER1 proteins to regulate RNA splicing and processing modification,thus promoting the occurrence and development of hypertrophic scar.

Objective:To characterize the brain structure of Chinese children with autism spectrum disorder (ASD) using artificial intelligence automatic brain segmentation technique, and to analyze the correlation between the characteristics of the brain structure and the degree of brain development.Methods:A case-control study.The data of 52 children who were diagnosed with ASD according to the diagnostic criteria for ASD in the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition of the United States at the Department of Psychology of Qingdao University Affiliated Women and Children′s Hospital from January 2023 to April 2024 were prospectively analyzed.Meanwhile, 48 gender- and age-matched typically developing (TD) children in Qingdao were also included.The three-dimensional T1 weighted imaging sequences of all patients were obtained using a GE 3.0T magnetic resonance imaging scanner.Automated brain segmentation techniques were used to obtain the standardized volumes of each brain structure (the ratio of the absolute volume of the brain structure to the whole brain volume).Two-independent-samples t and Mann-Whitney U tests were used to compare the standardized volumes of different brain regions between the 2 groups.Pearson and Spearman correlation analyses were used to depict the correlations between volume data of brain areas with significant differences and Gesell Developmental Scale scores. Results:Compared with those in the TD group, the volumes of the left grey matter[25.45%(0.70%) vs.25.16%(1.05%)], the right grey matter [(25.89±0.71)% vs.(25.51±0.73)%], the right lateral orbitofrontal cortex [(0.62±0.03)% vs.(0.59±0.05)%], the right medial orbitofrontal cortex[(0.48±0.04)% vs.(0.46±0.04)%], the right pars triangularis [(0.38±0.07)% vs.(0.35±0.05)%], the left hippocampus [0.22%(0.04%) vs.0.20%(0.02%)], the right hippocampus [0.23%(0.04%) vs.0.22%(0.02%)], the left parahippocampal gyrus [0.15%(0.03%) vs.0.14%(0.02%)], the right parahippocampal gyrus [(0.15±0.02)% vs.(0.14±0.02)%], the left fusiform gyrus [(0.82±0.08)% vs.(0.78±0.08)%], the right superior temporal gyrus [(0.96±0.10)% vs.(0.90±0.09)%], the left insular lobe [(0.54±0.03)% vs.(0.53±0.04)%], the right insular lobe [(0.55±0.03)% vs.(0.53±0.04)%], the right inferior parietal cortex [(1.40±0.16)% vs.(1.33±0.12)%], the right precuneus cortex [(0.99±0.09)% vs.(0.94±0.09)%], the right putamen [(0.37±0.04)% vs.(0.35±0.03)%], the left pallidum [(0.14±0.01)% vs.(0.13±0.01)%], the right pallidum [0.14%(0.02%) vs.0.13%(0.01%)], and the right thalamus [(0.51±0.04)% vs.(0.49±0.03)%] were significantly increased in the ASD group (all P<0.05).Nonetheless, the volumes of the left pericalcarine cortex [(0.19±0.04)% vs.(0.20±0.04)%] and the corpus callosum posterior region [0.05%(0.01%) vs.0.06%(0.01%)] in the ASD group were considerably smaller than those in the TD group (all P<0.05).Correlation analysis showed that the right thalamus volume was negatively correlated with the Gesell-adaptation development quotient in children with ASD ( r=-0.276, P=0.048).The volumes of the left fusiform gyrus and left pericalcarine cortex were negatively correlated with the Gesell-fine motor development quotient in children with ASD ( r=-0.290, P=0.037; r=-0.368, P=0.007). The right precuneus cortex volume was negatively correlated with the Gesell-personal and social competence development quotient in children with ASD ( r=-0.396, P=0.007). Conclusions:Children with ASD show abnormalities in the volumes of multiple brain regions, and some brain regions are related to the degree of brain development.Automatic brain segmentation technology based on artificial intelligence can rapidly and directly measure and display the volume of brain structures in both ASD and TD children.

Objective:To characterize the brain structure of Chinese children with autism spectrum disorder (ASD) using artificial intelligence automatic brain segmentation technique, and to analyze the correlation between the characteristics of the brain structure and the degree of brain development.Methods:A case-control study.The data of 52 children who were diagnosed with ASD according to the diagnostic criteria for ASD in the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition of the United States at the Department of Psychology of Qingdao University Affiliated Women and Children′s Hospital from January 2023 to April 2024 were prospectively analyzed.Meanwhile, 48 gender- and age-matched typically developing (TD) children in Qingdao were also included.The three-dimensional T1 weighted imaging sequences of all patients were obtained using a GE 3.0T magnetic resonance imaging scanner.Automated brain segmentation techniques were used to obtain the standardized volumes of each brain structure (the ratio of the absolute volume of the brain structure to the whole brain volume).Two-independent-samples t and Mann-Whitney U tests were used to compare the standardized volumes of different brain regions between the 2 groups.Pearson and Spearman correlation analyses were used to depict the correlations between volume data of brain areas with significant differences and Gesell Developmental Scale scores. Results:Compared with those in the TD group, the volumes of the left grey matter[25.45%(0.70%) vs.25.16%(1.05%)], the right grey matter [(25.89±0.71)% vs.(25.51±0.73)%], the right lateral orbitofrontal cortex [(0.62±0.03)% vs.(0.59±0.05)%], the right medial orbitofrontal cortex[(0.48±0.04)% vs.(0.46±0.04)%], the right pars triangularis [(0.38±0.07)% vs.(0.35±0.05)%], the left hippocampus [0.22%(0.04%) vs.0.20%(0.02%)], the right hippocampus [0.23%(0.04%) vs.0.22%(0.02%)], the left parahippocampal gyrus [0.15%(0.03%) vs.0.14%(0.02%)], the right parahippocampal gyrus [(0.15±0.02)% vs.(0.14±0.02)%], the left fusiform gyrus [(0.82±0.08)% vs.(0.78±0.08)%], the right superior temporal gyrus [(0.96±0.10)% vs.(0.90±0.09)%], the left insular lobe [(0.54±0.03)% vs.(0.53±0.04)%], the right insular lobe [(0.55±0.03)% vs.(0.53±0.04)%], the right inferior parietal cortex [(1.40±0.16)% vs.(1.33±0.12)%], the right precuneus cortex [(0.99±0.09)% vs.(0.94±0.09)%], the right putamen [(0.37±0.04)% vs.(0.35±0.03)%], the left pallidum [(0.14±0.01)% vs.(0.13±0.01)%], the right pallidum [0.14%(0.02%) vs.0.13%(0.01%)], and the right thalamus [(0.51±0.04)% vs.(0.49±0.03)%] were significantly increased in the ASD group (all P<0.05).Nonetheless, the volumes of the left pericalcarine cortex [(0.19±0.04)% vs.(0.20±0.04)%] and the corpus callosum posterior region [0.05%(0.01%) vs.0.06%(0.01%)] in the ASD group were considerably smaller than those in the TD group (all P<0.05).Correlation analysis showed that the right thalamus volume was negatively correlated with the Gesell-adaptation development quotient in children with ASD ( r=-0.276, P=0.048).The volumes of the left fusiform gyrus and left pericalcarine cortex were negatively correlated with the Gesell-fine motor development quotient in children with ASD ( r=-0.290, P=0.037; r=-0.368, P=0.007). The right precuneus cortex volume was negatively correlated with the Gesell-personal and social competence development quotient in children with ASD ( r=-0.396, P=0.007). Conclusions:Children with ASD show abnormalities in the volumes of multiple brain regions, and some brain regions are related to the degree of brain development.Automatic brain segmentation technology based on artificial intelligence can rapidly and directly measure and display the volume of brain structures in both ASD and TD children.