Objective To analyze the literature on artificial intelligence in forensic research from 2012 to 2022 in the Web of Science Core Collection Database,to explore research hotspots and developmen-tal trends.Methods A total of 736 articles on artificial intelligence in forensic medicine in the Web of Science Core Collection Database from 2012 to 2022 were visualized and analyzed through the litera-ture measuring tool CiteSpace.The authors,institution,country(region),title,journal,keywords,cited references and other information of relevant literatures were analyzed.Results A total of 736 articles published in 220 journals by 355 authors from 289 institutions in 69 countries(regions)were identi-fied,with the number of articles published showing an increasing trend year by year.Among them,the United States had the highest number of publications and China ranked the second.Academy of Forensic Science had the highest number of publications among the institutions.Forensic Science Inter-national,Journal of Forensic Sciences,International Journal of Legal Medicine ranked high in publica-tion and citation frequency.Through the analysis of keywords,it was found that the research hotspots of artificial intelligence in the forensic field mainly focused on the use of artificial intelligence technol-ogy for sex and age estimation,cause of death analysis,postmortem interval estimation,individual identification and so on.Conclusion It is necessary to pay attention to international and institutional cooperation and to strengthen the cross-disciplinary research.Exploring the combination of advanced ar-tificial intelligence technologies with forensic research will be a hotspot and direction for future re-search.

The air at high altitude is thin and belongs to the environment of low temperature, low oxygen and low pressure. The human brain is the most sensitive to hypoxia. Hypoxia will cause dysfunction of the central nervous system, resulting in high-altitude hypoxic brain injury, including mild high altitude headache and more destructive high altitude cerebral edema (HACE). Recently, with more and more people work and live in high altitude areas, the development of high-altitude hypoxic brain injury drugs would produce great economic value and social significance. Non clinical pharmacodynamic evaluation is the basic of drug development, which plays a key role in improving the success rate of clinical transformation and reducing the risk of clinical research. This review summarizes the cell models and animal models, and the evaluation indicators usually used to explore the candidates of high-altitude hypoxic brain injury. We aim at establishing a standardized non clinical efficacy evaluation system for high altitude hypoxic encephalopathy, and provide a standardized reference for drug development in hypoxic encephalopathy at high altitude at nonclinical stage.

OBJECTIVE: We aimed to assess the feasibility and superiority of machine learning (ML) methods to predict the risk of Major Adverse Cardiovascular Events (MACEs) in chest pain patients with NSTE-ACS. METHODS: Enrolled chest pain patients were from two centers, Beijing Anzhen Emergency Chest Pain Center Beijing Bo'ai Hospital, China Rehabilitation Research Center. Five classifiers were used to develop ML models. Accuracy, Precision, Recall, F-Measure and AUC were used to assess the model performance and prediction effect compared with HEART risk scoring system. Ultimately, ML model constructed by Naïve Bayes was employed to predict the occurrence of MACEs. RESULTS: According to learning metrics, ML models constructed by different classifiers were superior over HEART (History, ECG, Age, Risk factors, & Troponin) scoring system when predicting acute myocardial infarction (AMI) and all-cause death. However, according to ROC curves and AUC, ML model constructed by different classifiers performed better than HEART scoring system only in prediction for AMI. Among the five ML algorithms, Linear support vector machine (SVC), Naïve Bayes and Logistic regression classifiers stood out with all Accuracy, Precision, Recall and F-Measure from 0.8 to 1.0 for predicting any event, AMI, revascularization and all-cause death ( vs. HEART ≤ 0.78), with AUC from 0.88 to 0.98 for predicting any event, AMI and revascularization ( vs. HEART ≤ 0.85). ML model developed by Naïve Bayes predicted that suspected acute coronary syndrome (ACS), abnormal electrocardiogram (ECG), elevated hs-cTn I, sex and smoking were risk factors of MACEs. CONCLUSION Compared with HEART risk scoring system, the superiority of ML method was demonstrated when employing Linear SVC classifier, Naïve Bayes and Logistic. ML method could be a promising method to predict MACEs in chest pain patients with NSTE-ACS.
Humans ; Acute Coronary Syndrome/epidemiology* ; Bayes Theorem ; Feasibility Studies ; Risk Assessment/methods* ; Chest Pain/etiology* ; Myocardial Infarction/diagnosis*

Aim To explore the mechanism of process¬ing and increasing efficiency of Arisaematis rhizomz preparatum. Methods UPLC-Q-TOF-MS/MS tech¬nology was used to detect the chemical components be¬fore and after processing of Arisaematis rhizomz prepara¬tum, and its mechanism of action was analysed in the treatment of 44 asthma and phlegm " by using network pharmacology. A rat model of allergic asthma was es- tablished to compare the efficacy of Arisaematis rliizoma before and after processing. Results A total of 27 chemical components were identified, among which cur- cumin ,6-gingerol and other components increased after processing. Combined with the database prediction, the action mechanism of the 36 chemical components in the treatment of 44 asthma and phlegm" diseases was dis¬cussed and predicted through network pharmacology. The results of animal experiments showed that the effect of processed Arisaematis rhizoma on allergic asth¬ma was better than that of Arisaematis rhizoma, but there was no significant difference. Conclusions The addition of curcumin, 6-gingerol, camphor, demethyl- curcumin and other components after the processed Ari¬saematis rhizomz preparatum may be the reason for the synergistic effect of Arisaematis rhizomz preparatum in the treatment of allergic asthma.

Objective: To study the impact of regional positive lymph node ratio (LNR) on prognosis of patients with gallbladder carcinoma. Methods: The clinicopathological and survival data of 53 patients with gallbladder carcinoma who underwent radical resection with regional lymph node metastasis in Ningbo University Affiliated Lihuili Hospital from May 2012 to December 2020 were collected, and receiver operating characteristic curve (ROC) was used to determine the optimal cut-off value of LNR for predicting postoperative survival status in patients with gallbladder carcinoma. According to the critical value, the patients were divided into low LNR group and high LNR group. The clinicopathological features and prognosis of the two groups were compared. Log rank test was used for univariate analysis of prognostic factors in patients with gallbladder carcinoma, and Cox proportional hazards model was used for multivariate analysis. Results: A total of 417 regional lymph nodes were dissected in 53 patients, of which 144 lymph nodes were positive, with a positive rate of 34.5%. The optimal cut-off value of LNR for predicting postoperative survival status of patients with gallbladder carcinoma was 0.33. According to this cut-off value, patients were divided into low LNR group (LNR≤0.33, 28 cases) and high LNR group (LNR>0.33, 25 cases). The recurrence rates were 64.3% (18/28) and 88.0 % (22/25) in low LNR group and high LNR group, respectively. The median recurrence-free survival (RFS) was 8 and 7 months, respectively (P=0.032). In the low LNR group, the 1-, 3-, and 5-year survival rates were 56.2%, 38.4%, and 32.0%, respectively, and the median overall survival (OS) was 16 months. In the high LNR group, the 1-, 3-, and 5-year survival rates were 37.9%, 5.4%, and 0, respectively, and the median OS was 9 months. The postoperative survival rate of patients in the low LNR group was better than that in the high LNR group (P=0.008). Univariate analysis showed that LNR was even associated with RFS and OS in patients with gallbladder carcinoma (P<0.05). Multivariate analysis showed that LNR>0.33 was an independent risk factor for postoperative RFS (HR=1.977, 95% CI: 1.045-3.740), but not for OS (HR=1.561, 95% CI: 0.685-3.553). Conclusion: On the basis of clearing a sufficient number of regional lymph nodes, patients with gallbladder carcinoma with regional LNR>0.33 are more likely to relapse after operation, but the predictive value of LNR>0.33 OS is insufficient.
Humans ; Lymph Node Ratio ; Gallbladder Neoplasms/pathology* ; Lymph Node Excision ; Lymphatic Metastasis/pathology* ; Neoplasm Staging ; Retrospective Studies ; Lymph Nodes/pathology* ; Prognosis

Objective: To evaluate the feasibility and effectiveness of the application of internet-based HIV testing in men who have sex with men (MSM) in practical application and provide evidence for its application in the future. Methods: MSM who visited the internet-based intervention platform for at least one time from June to December 2020 were selected for the study. The information about platform visit, the number of self-test kits provided, the basic characteristics of the MSM and their satisfactory level were collected. And multivariable logistic regression analyses were conducted to identify the potential factors associated with the reporting of self-test results. Results: By the end of December 31^th, 2020, a total of 132 267 platform visits had been recorded, and 3 511 HIV self-test kits had been provided upon the MSM's requests, and 3 237 MSM (92.2%) reported self-test results. The HIV positive rate was 2.4% (69/2 855) and the confirmation rate of positive HIV test results was 86.7% (52/60). The MSM who asked for self-test kits online were mainly aged ≤30 years, had education level of college or above, and found their sexual partners through internet or dating software. Multivariable logistic regression analyses showed that repeat of online HIV self-test kits application (OR=3.50,95%CI:2.10-5.83), guarantee deposit of 50 yuan at application (OR=2.55,95%CI:1.33-4.89), monthly economic income 1-3 000 yuan (OR=1.54,95%CI:1.05-2.28) or no income (OR=1.71,95%CI:1.20-2.42) and online sexual partners finding (OR=1.49,95%CI:1.13-1.95) were associated with higher reporting rate of self-test results. The satisfactory rate the MSM to the service of platform was 99.5% (217/218). Conclusions: The study confirmed the feasibility and effectiveness of internet-based intervention for HIV tests in MSM, which could promote the self-test of HIV in MSM and facilitate the early detection of HIV infection through social media platforms and multi-channel promotion.
Male ; Humans ; Homosexuality, Male ; HIV Infections/prevention & control* ; Feasibility Studies ; Sexual and Gender Minorities ; HIV Testing ; Internet

OBJECTIVES: To study the serum levels of insulin-like growth factor-1 (IGF-1) and insulin-like growth factor binding protein-3 (IGFBP-3) in children with autism spectrum disorder (ASD) and their association with the core symptoms of ASD. METHODS: A total of 150 ASD children aged 2-7 years (ASD group) and 165 healthy children matched for age and sex (control group) who were recruited at the outpatient service of Chongqing Health Center for Women and Children were enrolled as subjects. Autism Behavior Checklist (ABC) and Childhood Autism Rating Scale (CARS) were used to evaluate the core symptoms of the ASD children. Chemiluminescence was used to measure the serum levels of IGF-1 and IGFBP-3 in both groups. RESULTS: The ASD group had a significantly lower serum level of IGF-1 than the control group (P<0.05). The children with severe ASD had significantly lower serum levels of IGF-1 and IGFBP-3 than those with mild-to-moderate ASD (P<0.001). For the children aged 2-3 years, the ASD group had a significantly lower serum level of IGF-1 than the control group (P<0.05). Boys had a significantly lower serum level of IGF-1 than girls in both ASD and control groups (P<0.05). The serum levels of IGF-1 and IGFBP-3 were negatively correlated with the total score of CARS (r=-0.32 and -0.40 respectively, P<0.001). CONCLUSIONS The reduction in serum IGF-1 level in early childhood may be associated with the development of ASD, and the serum levels of IGF-1 and IGFBP-3 are associated with the core symptoms of ASD children.
Autism Spectrum Disorder ; Autistic Disorder ; Child ; Child, Preschool ; Female ; Humans ; Insulin-Like Growth Factor Binding Protein 3 ; Insulin-Like Growth Factor I ; Male

Objective:To investigate the relationship of triglyceride (TG), fasting blood glucose (FPG) and triglyceride glucose product index (TyG) with the incidence of hypertension, and provide basic data for the prevention and treatment of hypertension in the population.Methods:A total of 23 581 individuals who met the research criteria in Jinchang cohort were selected as the research subjects, the Cox proportional hazard model was used to analyze the relationship of TG, FPG, and TyG with the risk of hypertension. A stratified analysis was conducted by sex.Results:After adjusting for confounding factors, compared with the normal TG group, the HR(95% CI) of the elevated TG margin group and the elevated group were 1.16 (1.01-1.34) and 1.49 (1.30-1.70), respectively in the total population. Among men, they were 1.13 (1.01-1.27) and 1.17 (1.06-1.30), and among women, they were 1.05 (0.88-1.26) and 1.06 (0.88-1.28). Compared with the normal FPG group, the HR (95% CI) of the FPG-impaired group were 1.29 (1.13-1.48) in the total population, 1.26 (1.08-1.48) in men and 1.59 (1.14-2.21) in women. Taking the lowest quartile array as a reference, the HR (95% CI) of the highest quartile array of TyG was 1.73 (1.45-2.07) in the total population, 1.32 (1.14-1.53) in men and 1.87 (1.37-2.54) in women. TG, FPG had a nonlinear dose-response relationship with the risk of hypertension, while TyG had a linear correlation with the risk of hypertension. Conclusions:Higher TG, FPG, and TyG levels are independent risk factors for the incidence of hypertension. People with higher TG, FPG and TyG are at high risk for hypertension, to which close attention should be paid in the prevention and treatment of hypertension.

Objective:To explore the relationship between lipid indicators and the incidence of diabetes, and to compare the diabetes prediction and identification power of traditional lipid combined lipid indicators, in order to explore the best alternative indicators for identifying and predicting diabetes.Methods:Based on the Jinchang cohort, a nested case-control study was conducted in 1 025 new cases of diabetes after excluding patients with malignant tumor and related endocrine, circulatory system disease, then an age (±2 years), gender matched 1∶1 control group of 1 025 cases was set to analyze the relationship between the incidence of diabetes and lipid parameters.Results:Among the traditional lipid parameters, the fourth quartile of TG, TC, and LDL-C indicated higher risks of developing diabetes, which was 14.00 times (95% CI: 9.73-20.15), 2.15 times (95% CI: 1.65-2.79) and 1.66 times (95% CI: 1.29-2.14) than that of the first quartile, respectively. The risk of developing diabetes indicated by the fourth quartile of HDL-C was 0.21 times than that indicated by the first quartile (95% CI: 0.15-0.28). In the combined lipid parameters, the fourth quartile of TG/HDL-C, TC/HDL-C, LDL-C/HDL-C and non-HDL-C indicated higher risks of developing diabetes, which was 14.86 times (95% CI: 10.35-21.34), 8.12 times (95% CI: 5.94-11.01), 5.85 times (95% CI:4.34-7.88) and 5.20 times (95% CI: 3.85-7.03) than that indicated by the first quartile, respectively. The areas under the ROC curve of TG, TC, HDL-C, LDL-C, TG/HDL-C, TC/HDL-C, LDL-C/HDL-C and non-HDL-C were 0.76 (95% CI: 0.74-0.78), 0.59 (95% CI: 0.57-0.61), 0.67 (95% CI: 0.65-0.69), 0.57 (95% CI: 0.55-0.59), 0.77 (95% CI: 0.75-0.78), 0.73 (95% CI: 0.71-0.75), 0.69 (95% CI: 0.67-0.71) and 0.66 (95% CI: 0.64-0.68), respectively. The optimal diabetes predicting point cuts of TG, TC, HDL-C, LDL-C, TG/HDL-C, TC/HDL-C, LDL-C/HDL-C and non-HDL-C were 1.40, 4.70, 1.28, 3.25, 1.17, 3.43, 2.46, and 3.58 mmol/L, respectively. Conclusions:Lipid metabolic disorder is a risk factor for diabetes. TG and TG/HDL-C are the good lipid metabolism indicators for the prediction of diabetic.

Objective:To explore the relationship of body mass index and blood pressure with the incidence of diabetes in Jinchang cohort.Methods:We designed a nested case-control study, a total of 29 572 workers who had no history of diabetes in baseline survey in Jinchang cohort were selected as the study cohort from June 2011 to December 2013. After 2 year follow-up, 1 021 workers with first diagnosed diabetes were selected as the case group, after 1∶1 matching according to the same gender and age ±2 years among those without diabetes, circulatory system, or endocrine system diseases during the same follow-up period, 1 021 controls was selected and 2 042 subjects were finally included. We used multivariate conditional logistic regression model, additive interaction model and multiplicative interaction model to explore the relationship of body mass index and blood pressure with the incidence of diabetes.Results:After adjusting for factors such as occupation, alcohol use, family history of diabetes, hyperuricemia, hypercholesterolemia, hypertriglyceridemia, low-HDL cholesterolemia and high-LDL cholesterolemia, multivariate conditional logistic regression analysis showed that the risk of diabetes increased with body mass index and blood pressure. Hypertension and overweight/obesity had a multiplicative interaction on the incidence of diabetes. The risks of diabetes in men and women with hypertension and overweight/obese were 2.04 times (95% CI: 1.54-2.69) and 3.88 times (95% CI: 2.55-5.91) higher than those in men and women with normal body weight and blood pressure, respectively. In the combination of BMI and blood pressure, obese individuals with SBP≥160 mmHg were 4.57 times (95% CI: 2.50-8.34) more likely to have diabetes than those with normal BMI and SBP, obese individuals with DBP≥90 mmHg were 3.40 times (95% CI: 2.19-5.28) more likely to have diabetes than those with normal BMI and DBP. Conclusions:Overweight/obesity and hypertension can increase the risk of diabetes. Health education about body weight and blood pressure controls should be strengthened to reduce the risk of diabetes.