法医学杂志最新文献

{"title":"[Identification of the causal relationship between lower limb fracture and cerebral infarction： A case report].","authors":"继 超 杨, 平 刘, 亦 斌 程","doi":"10.12116/j.issn.1004-5619.2023.230801","DOIUrl":"10.12116/j.issn.1004-5619.2023.230801","url":null,"abstract":"","PeriodicalId":12317,"journal":{"name":"法医学杂志","volume":"40 2","pages":"223-226"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141283396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Virtual autopsy combined with forensic autopsy to determine death from airgun bullet wounds： A case report].","authors":"光 陈, 小 龙 王, 慧 敏 项, 露 汪, 明 秦, 岫 刘, 祥 徐","doi":"10.12116/j.issn.1004-5619.2023.430410","DOIUrl":"10.12116/j.issn.1004-5619.2023.430410","url":null,"abstract":"","PeriodicalId":12317,"journal":{"name":"法医学杂志","volume":"40 2","pages":"196-199"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141283403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dental Age Estimation in Northern Chinese Han Children and Adolescents Using Demirjian's Method Combined with Machine Learning Algorithms.","authors":"Yu-Xin Guo, Wen-Qing Bu, Yu Tang, Di Wu, Hui Yang, Hao-Tian Meng, Yu-Cheng Guo","doi":"10.12116/j.issn.1004-5619.2023.231208","DOIUrl":"10.12116/j.issn.1004-5619.2023.231208","url":null,"abstract":"<p><strong>Objectives: </strong>To investigate the application value of combining the Demirjian's method with machine learning algorithms for dental age estimation in northern Chinese Han children and adolescents.</p><p><strong>Methods: </strong>Oral panoramic images of 10 256 Han individuals aged 5 to 24 years in northern China were collected. The development of eight permanent teeth in the left mandibular was classified into different stages using the Demirjian's method. Various machine learning algorithms, including support vector regression (SVR), gradient boosting regression (GBR), linear regression (LR), random forest regression (RFR), and decision tree regression (DTR) were employed. Age estimation models were constructed based on total, female, and male samples respectively using these algorithms. The fitting performance of different machine learning algorithms in these three groups was evaluated.</p><p><strong>Results: </strong>SVR demonstrated superior estimation efficiency among all machine learning models in both total and female samples, while GBR showed the best performance in male samples. The mean absolute error (MAE) of the optimal age estimation model was 1.246 3, 1.281 8 and 1.153 8 years in the total, female and male samples, respectively. The optimal age estimation model exhibited varying levels of accuracy across different age ranges, which provided relatively accurate age estimations in individuals under 18 years old.</p><p><strong>Conclusions: </strong>The machine learning model developed in this study exhibits good age estimation efficiency in northern Chinese Han children and adolescents. However, its performance is not ideal when applied to adult population. To improve the accuracy in age estimation, the other variables can be considered.</p>","PeriodicalId":12317,"journal":{"name":"法医学杂志","volume":"40 2","pages":"135-142"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141283448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adults Ischium Age Estimation Based on Deep Learning and 3D CT Reconstruction.","authors":"Huai-Han Zhang, Yong-Jie Cao, Ji Zhang, Jian Xiong, Ji-Wei Ma, Xiao-Tong Yang, Ping Huang, Yong-Gang Ma","doi":"10.12116/j.issn.1004-5619.2023.231003","DOIUrl":"https://doi.org/10.12116/j.issn.1004-5619.2023.231003","url":null,"abstract":"<p><strong>Objectives: </strong>To develop a deep learning model for automated age estimation based on 3D CT reconstructed images of Han population in western China, and evaluate its feasibility and reliability.</p><p><strong>Methods: </strong>The retrospective pelvic CT imaging data of 1 200 samples (600 males and 600 females) aged 20.0 to 80.0 years in western China were collected and reconstructed into 3D virtual bone models. The images of the ischial tuberosity feature region were extracted to create sex-specific and left/right site-specific sample libraries. Using the ResNet34 model, 500 samples of different sexes were randomly selected as training and verification set, the remaining samples were used as testing set. Initialization and transfer learning were used to train images that distinguish sex and left/right site. Mean absolute error (MAE) and root mean square error (RMSE) were used as primary indicators to evaluate the model.</p><p><strong>Results: </strong>Prediction results varied between sexes, with bilateral models outperformed left/right unilateral ones, and transfer learning models showed superior performance over initial models. In the prediction results of bilateral transfer learning models, the male MAE was 7.74 years and RMSE was 9.73 years, the female MAE was 6.27 years and RMSE was 7.82 years, and the mixed sexes MAE was 6.64 years and RMSE was 8.43 years.</p><p><strong>Conclusions: </strong>The skeletal age estimation model, utilizing ischial tuberosity images of Han population in western China and employing the ResNet34 combined with transfer learning, can effectively estimate adult ischium age.</p>","PeriodicalId":12317,"journal":{"name":"法医学杂志","volume":"40 2","pages":"154-163"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141283405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Estimation of postmortem interval based on scene environment and plant evidence： A case report].","authors":"杰 徐, 晓 明 薛, 玉 宝 王, 宇 岳, 阳 张","doi":"10.12116/j.issn.1004-5619.2022.420508","DOIUrl":"10.12116/j.issn.1004-5619.2022.420508","url":null,"abstract":"","PeriodicalId":12317,"journal":{"name":"法医学杂志","volume":"40 2","pages":"202-204"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141283393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biomarkers Screening and Mechanisms Analysis of the Restraint Stress-Induced Myocardial Injury in Hyperlipidemia ApoE^-/- Mice.","authors":"Shang-Heng Chen, Sheng-Zhong Dong, Zhi-Min Wang, Guang-Hui Hong, Xing Ye, Zi-Jie Lin, Jun-Yi Lin, Jie-Qing Jiang, Shou-Yu Wang, Han-Cheng Lin, Yi-Wen Shen","doi":"10.12116/j.issn.1004-5619.2023.430808","DOIUrl":"10.12116/j.issn.1004-5619.2023.430808","url":null,"abstract":"<p><strong>Objectives: </strong>To explore the biomarkers and potential mechanisms of chronic restraint stress-induced myocardial injury in hyperlipidemia ApoE^-/- mice.</p><p><strong>Methods: </strong>The hyperlipidemia combined with the chronic stress model was established by restraining the ApoE^-/- mice. Proteomics and bioinformatics techniques were used to describe the characteristic molecular changes and related regulatory mechanisms of chronic stress-induced myocardial injury in hyperlipidemia mice and to explore potential diagnostic biomarkers.</p><p><strong>Results: </strong>Proteomic analysis showed that there were 43 significantly up-regulated and 58 significantly down-regulated differentially expressed proteins in hyperlipidemia combined with the restraint stress group compared with the hyperlipidemia group. Among them, GBP2, TAOK3, TFR1 and UCP1 were biomarkers with great diagnostic potential. KEGG pathway enrichment analysis indicated that ferroptosis was a significant pathway that accelerated the myocardial injury in hyperlipidemia combined with restraint stress-induced model. The <i>mmu_circ_0001567</i>/<i>miR-7a</i>/<i>Tfr-1</i> and <i>mmu_circ_0001042</i>/<i>miR-7a</i>/<i>Tfr-1</i> might be important circRNA-miRNA-mRNA regulatory networks related to ferroptosis in this model.</p><p><strong>Conclusions: </strong>Chronic restraint stress may aggravate myocardial injury in hyperlipidemia mice via ferroptosis. Four potential biomarkers are selected for myocardial injury diagnosis, providing a new direction for sudden cardiac death (SCD) caused by hyperlipidemia combined with the restraint stress.</p>","PeriodicalId":12317,"journal":{"name":"法医学杂志","volume":"40 2","pages":"172-178"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141283408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research Progress on Dental Age Estimation Based on MRI Technology.","authors":"Lei Shi, Ye Xue, Li-Rong Qiu, Ting Lu, Fei Fan, Yu-Chi Zhou, Zhen-Hua Deng","doi":"10.12116/j.issn.1004-5619.2023.231204","DOIUrl":"10.12116/j.issn.1004-5619.2023.231204","url":null,"abstract":"<p><p>Dental age estimation is a crucial aspect and one of the ways to accomplish forensic age estimation, and imaging technology is an important technique for dental age estimation. In recent years, some studies have preliminarily confirmed the feasibility of magnetic resonance imaging (MRI) in evaluating dental development, providing a new perspective and possibility for the evaluation of dental development, suggesting that MRI is expected to be a safer and more accurate tool for dental age estimation. However, further research is essential to verify its accuracy and feasibility. This article reviews the current state, challenges and limitations of MRI in dental development and age estimation, offering reference for the research of dental age assessment based on MRI technology.</p>","PeriodicalId":12317,"journal":{"name":"法医学杂志","volume":"40 2","pages":"112-117"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141283451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Postmortem Diffusion of Aconitum Alkaloids and Their Metabolites in Rabbits.","authors":"Jia-Hao Liang, Ming Cheng, Xiao-Jun Lu, Yan-Hua Shi, Yun Sun, Qing-Lin Guan, Tao Wang, Meng Hu, Ke-Ming Yun, Hai-Yan Cui","doi":"10.12116/j.issn.1004-5619.2022.421205","DOIUrl":"https://doi.org/10.12116/j.issn.1004-5619.2022.421205","url":null,"abstract":"<p><strong>Objectives: </strong>To explore the postmortem diffusion rule of Aconitum alkaloids and their metabolites in poisoned rabbits, and to provide a reference for identifying the antemortem poisoning or postmortem poisoning of Aconitum alkaloids.</p><p><strong>Methods: </strong>Twenty-four rabbits were sacrificed by tracheal clamps. After 1 hour, the rabbits were administered with aconitine LD₅₀ in decocting aconite root powder by intragastric administration. Then, they were placed supine and stored at 25 ℃. The biological samples from 3 randomly selected rabbits were collected including heart blood, peripheral blood, urine, heart, liver, spleen, lung and kidney tissues at 0 h, 4 h, 8 h, 12 h, 24 h, 48 h, 72 h and 96 h after intragastric administration, respectively. Aconitum alkaloids and their metabolites in the biological samples were analyzed by high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS).</p><p><strong>Results: </strong>At 4 h after intragastric administration, Aconitum alkaloids and their metabolites could be detected in heart blood, peripheral blood and major organs, and the contents of them changed dynamically with the preservation time. The contents of Aconitum alkaloids and their metabolites were higher in the spleen, liver and lung, especially in the spleen which was closer to the stomach. The average mass fraction of benzoylmesaconine metabolized in rabbit spleen was the highest at 48 h after intragastric administration. In contrast, the contents of Aconitum alkaloids and their metabolites in kidney were all lower. Aconitum alkaloids and their metabolites were not detected in urine.</p><p><strong>Conclusions: </strong>Aconitum alkaloids and their metabolites have postmortem diffusion in poisoned rabbits, diffusing from high-content organs (stomach) to other major organs and tissues as well as the heart blood. The main mechanism is the dispersion along the concentration gradient, while urine is not affected by postmortem diffusion, which can be used as the basis for the identification of antemortem and postmortem Aconitum alkaloids poisoning.</p>","PeriodicalId":12317,"journal":{"name":"法医学杂志","volume":"40 2","pages":"186-191"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141283450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Crush death caused by compression garbage truck： A case report].","authors":"旦 宋, 华 鑫 单, 福 远 王, 正 东 李","doi":"10.12116/j.issn.1004-5619.2023.430318","DOIUrl":"10.12116/j.issn.1004-5619.2023.430318","url":null,"abstract":"","PeriodicalId":12317,"journal":{"name":"法医学杂志","volume":"40 2","pages":"205-207"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141283392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of Medical Statistical and Machine Learning Methods in the Age Estimation of Living Individuals.","authors":"Dan-Yang Li, Yu Pan, Hui-Ming Zhou, Lei Wan, Cheng-Tao Li, Mao-Wen Wang, Ya-Hui Wang","doi":"10.12116/j.issn.1004-5619.2023.231103","DOIUrl":"10.12116/j.issn.1004-5619.2023.231103","url":null,"abstract":"<p><p>In the study of age estimation in living individuals, a lot of data needs to be analyzed by mathematical statistics, and reasonable medical statistical methods play an important role in data design and analysis. The selection of accurate and appropriate statistical methods is one of the key factors affecting the quality of research results. This paper reviews the principles and applicable principles of the commonly used medical statistical methods such as descriptive statistics, difference analysis, consistency test and multivariate statistical analysis, as well as machine learning methods such as shallow learning and deep learning in the age estimation research of living individuals, and summarizes the relevance and application prospects between medical statistical methods and machine learning methods. This paper aims to provide technical guidance for the age estimation research of living individuals to obtain more scientific and accurate results.</p>","PeriodicalId":12317,"journal":{"name":"法医学杂志","volume":"40 2","pages":"118-127"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141283407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}