Age Estimation by Machine Learning and CT-Multiplanar Reformation of Cranial Sutures in Northern Chinese Han Adults.

OBJECTIVES: To establish age estimation models of northern Chinese Han adults using cranial suture images obtained by CT and multiplanar reformation (MPR), and to explore the applicability of cranial suture closure rule in age estimation of northern Chinese Han population. METHODS: The head CT samples of 132 northern Chinese Han adults aged 29-80 years were retrospectively collected. Volume reconstruction (VR) and MPR were performed on the skull, and 160 cranial suture tomography images were generated for each sample. Then the MPR images of cranial sutures were scored according to the closure grading criteria, and the mean closure grades of sagittal suture, coronal sutures (both left and right) and lambdoid sutures (both left and right) were calculated respectively. Finally taking the above grades as independent variables, the linear regression model and four machine learning models for age estimation (gradient boosting regression, support vector regression, decision tree regression and Bayesian ridge regression) were established for northern Chinese Han adults age estimation. The accuracy of each model was evaluated. RESULTS: Each cranial suture closure grade was positively correlated with age and the correlation of sagittal suture was the highest. All four machine learning models had higher age estimation accuracy than linear regression model. The support vector regression model had the highest accuracy among the machine learning models with a mean absolute error of 9.542 years. CONCLUSIONS: The combination of skull CT-MPR and machine learning model can be used for age estimation in northern Chinese Han adults, but it is still necessary to combine with other adult age estimation indicators in forensic practice.

Forensic age estimation in adults by pubic bone mineral density using multidetector computed tomography.

Radiology plays a crucial role in forensic anthropology for age estimation. However, most studies rely on morphological methods. This study aims to investigate the feasibility of using pubic bone mineral density (BMD) as a new age estimation method in the Chinese population. 468 pubic bone CT scans from living individuals in a Chinese hospital aged 18 to 87 years old were used to measure pubic BMD. The BMD of the bilateral pubic bone was measured using the Mimics software on cross-sectional CT images and the mean BMD of the bilateral pubic bone was also calculated. Regression analysis was performed to assess the correlation between pubic BMD and chronological age and to develop mathematical models for age estimation. We evaluated the accuracy of the best regression model using an independent validation sample by calculating the mean absolute error (MAE). Among all established models, the cubic regression model had the highest R2 value in both genders, with R2 = 0.550 for males and R2 = 0.634 for females. The results of the best model test showed that the MAE for predicting age using pubic BMD was 8.66 years in males and 7.69 years in females. This study highlights the potential of pubic BMD as a useful objective indicator for adult age estimation and could be used as an alternative in forensic practice when other better indicators are lacking.

[Microbial Community Structure of Waste Water Treatment Plants in Different Seasons].

Wastewater treatment plants (WWTPs) have different treatment effects during different seasons due to changes in water quality and temperature. To understand bacterial community structure and diversity dynamics in the WWTPs, this study employed high-throughput sequencing technology during winter and summer. A total of 60 activated sludge samples were collected in five WWTPs in Beijing with different treatment processes in summer (temperature=28℃±2℃, water temperature=24.9℃±1.1℃) and winter (temperature=0℃±3℃, water temperature=16.8℃±1.3℃). The relative abundances of dominant bacterial genera in activated sludge varied significantly between the WWTPs but microbial community structure was typically similar between different treatment units (i.e., the anaerobic tank, anoxic tank, and aerobic tank) at each WWTP. At the same time, different bacteria dominated in winter and summer, when the relative abundance of SJA-15, Ferruginibacter, and Blasocatellaceae was 6.07%, 4.50%, and 4.44% respectively, when the relative abundance of Nitrospira, Methylotenera, and RBG-13-54-9 in winter was 10.17%, 3.96%, and 3.28%, respectively. Correlation analysis showed that temperature, total nitrogen (TN), NH4+-N, total phosphorus (TP), and chemical oxygen demand (COD) were the main environmental factors affecting microbial community structure, of which temperature had the greatest effect on species composition followed by TN. Furthermore, a predictive analysis of functional enzymes indicated that the abundance of key enzymes involved in the nitrogen cycle in the activated sludge of WWTPs is higher in winter than that in summer. These results show that temperature, water quality, and treatment process affect bacterial community structure (i.e., dominance and abundance) in WWTP activated sludge.