Adult age estimation from the sternum using maximum intensity projection images of CT and data mining in a Chinese population.

This study aimed to explore and develop data mining models for adult age estimation based on CT reconstruction images from the sternum. Maximum intensity projection (MIP) images of chest CT were retrospectively collected from a modern Chinese population, and data from 2700 patients (1349 males and 1351 females) aged 20 to 70 years were obtained. A staging technique within four indicators was applied. Several data mining models were established, and mean absolute error (MAE) was the primary comparison parameter. The intraobserver and interobserver agreement levels were good. Within internal validation, the optimal data mining model obtained the lowest MAE of 9.08 in males and 10.41 in females. For the external validation (N = 200), MAEs were 7.09 in males and 7.15 in females. In conclusion, the accuracy of our model for adult age estimation was among similar studies. MIP images of the sternum could be a potential age indicator. However, it should be combined with other indicators since the accuracy level is still unsatisfactory.

Research Progress on Dental Age Estimation Based on MRI Technology.

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.

Toward Estimating CO2 Solubility in Pure Water and Brine Using Cascade Forward Neural Network and Generalized Regression Neural Network: Application to CO2 Dissolution Trapping in Saline Aquifers.

Predicting carbon dioxide (CO2) solubility in water and brine is crucial for understanding carbon capture and storage (CCS) processes. Accurate solubility predictions inform the feasibility and effectiveness of CO2 dissolution trapping, a key mechanism in carbon sequestration in saline aquifers. In this work, a comprehensive data set comprising 1278 experimental solubility data points for CO2-brine systems was assembled, encompassing diverse operating conditions. These data encompassed brines containing six different salts: NaCl, KCl, NaHCO3, CaCl2, MgCl2, and Na2SO4. Also, this databank encompassed temperature spanning from 273.15 to 453.15 K and a pressure range spanning 0.06-100 MPa. To model this solubility databank, cascade forward neural network (CFNN) and generalized regression neural network (GRNN) were employed. Furthermore, three optimization algorithms, namely, Bayesian Regularization (BR), Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton, and Levenberg-Marquardt (LM), were applied to enhance the performance of the CFNN models. The CFNN-LM model showcased average absolute percent relative error (AAPRE) values of 5.37% for the overall data set, 5.26% for the training subset, and 5.85% for the testing subset. Overall, the CFNN-LM model stands out as the most accurate among the models crafted in this study, boasting the highest overall R2 value of 0.9949 among the other models. Based on sensitivity analysis, pressure exerts the most significant influence and stands as the sole parameter with a positive impact on CO2 solubility in brine. Conversely, temperature and the concentration of all six salts considered in the model exhibited a negative impact. All salts exert a negative impact on CO2 solubility due to their salting-out effect, with varying degrees of influence. The salting-out effects of the salts can be ranked as follows: from the most pronounced to the least: MgCl2 > CaCl2 > NaCl > KCl > NaHCO3 > Na2SO4. By employing the leverage approach, only a few instances of potential suspected and out-of-leverage data were found. The relatively low count of identified potential suspected and out-of-leverage data, given the expansive solubility database, underscores the reliability and accuracy of both the data set and the CFNN-LM model's performance in this survey.

A comparative assessment of time-consuming and laborious diatom analysis：Brief experimentation with suggestion of automatic identification.

Diatom testing is considered a useful method for providing supportive evidence for the diagnosis of drowning in forensic pathology. However, various factors remain controversial for recognizing diatoms, such as being time-consuming and laborious and influencing the consistency of the results. Given the absence of precise and well-defined studies on this subject, this study aimed to determine the relationship between the ability to identify diatoms and researchers with different technical backgrounds. A total of 55 samples from 18 cases, including water, lungs, liver, and kidneys, were treated using the microwave digestion-vacuum filtration-automated scanning electron microscopy (MD-VF-Auto SEM), which was used to compare diatom analyses among three groups of well-trained forensic pathologists (FPs), trained junior employees (JEs), and new trainees (TEs). In addition to achieving similar accuracy of positive findings from drowning cases, counting efficiency was evaluated based on taxonomy records and counting time after viewing more than 5500 diatom images. In contrast to the higher counting efficiency of the JE group than that of the TE group, we observed a statistically significant difference (p < 0.05) in the diatom classification between these two groups. Based on our experiments, an efficient analysis for automatically identifying and classifying diatoms is urgently required.

Dental age estimation of Tibetan children and adolescents: Comparison of Demirjian, Willems methods and a newly modified Demirjian method.

Tibetan ethnic group is one of the oldest ethnic groups in China and South Asia. This study set out to analyze the dental development and validate Demirjian method and Willems method in estimating dental age of Tibetan children and adolescents, and to modify Demirjian method based on Tibetan population to provide ethnic-specific reference data and a more reliable method for forensic age assessment in Tibetan ethnic group. In this study, 1951 samples aged between 4 and 15 years were retrospectively collected and analyzed. Multiple linear regression was used to establish relationship between chronological age (CA) and developmental stages of left mandibular permanent teeth. The accuracy of the modified method was tested and compared with that of Demirjian and Willems method. Results showed that dental maturity score (DMS) was significantly greater in girls than in boys in all age groups except for the 4-year age group (p < 0.05). Mean absolute error (MAE) was 0.96 years for both boys and girls by Demirjian method, and 1.06 and 1.16 years for boys and girls respectively by Willems method. Adjusted scores table was established and tested. The age of boys was overestimated by 0.13 years and the age of girls was underestimated by 0.06 years by the adjusted scores table. MAE was lower than that of the other two methods. In conclusion, Demirjian method and Willems method was not sufficiently accurate in estimating dental age of Tibetan population. The modified method was more suitable for dental age estimation of Tibetan population than Demirjian and Willems method.

Recent progress of collagen, chitosan, alginate and other hydrogels in skin repair and wound dressing applications.

Human understanding of skin is constantly ongoing. Great progress has been made in skin repair, wound dressing regeneration biomaterials research in recent years. This review introduced the clinical research and guiding principles of skin repair, wound dressing biomaterials at home and abroad, introduced the classification of various skin repair and wound dressing, listed the composition and performance of different dressing biomaterials, including traditional, natural, synthetic, tissue-engineered dressing materials were extensively reviewed. The biological molecular structures and biological function characteristics of different dressing biomaterials are comprehensively reviewed. Collagen, chitosan, alginate hydrogels et al. as the most popular biological macromolecules in skin repair and wound dressing applications were reviewed. The future development direction is also prospected. This paper reviews the research progress of advanced functional skin repair and wound dressing, which provides a reference for the modifications and applications of wound dressings.

Application of metastatic biopsy based on "When, Who, Why, Where, How (4W1H)" principle in diagnosis and treatment of metastatic castration-resistance prostate cancer.

BACKGROUND: To determine the feasibility of secondary biopsy of metastatic castration-resistance prostate cancer based on the "4W1H-When, Who, Why, Where, How" principle and analyze the factors that affect tumor detection. Its application will further direct the patients for individualized precision therapy. METHODS: A total of 55 patients were collected for secondary biopsy (27 prostate biopsies and 55 metastases biopsies). The parameters of biopsy location, computed tomography attenuation coefficient, lesion size, core number, laboratory tests, and the use of bone protection were evaluated. Histopathological data and the pathogenesis and etiology classification were used to guide precision treatment. RESULTS: Fifteen/27 patients had a positive prostate biopsy, and 47/55 had positive metastasis biopsy. Bone metastasis biopsy was positive in 21/29 of cases. Also, parenchymal organs and lymph node biopsies were positive. In the prostate rebiopsy, significant differences were observed between total prostate volume (P=0.028), prostate-specific antigen (PSA) density (P=0.047), PSA velocity (P=0.036), and positive biopsy results. In the bone metastasis biopsy, we divided the patients into biopsy-positive and -negative groups. The computed tomography attenuation coefficient, PSA, alkaline phosphatase, and hemoglobin were related to tumor positive detection. However, the lesion size, core number, bone-sparing agents and previous treatments did not affect tumor detection. CONCLUSIONS: In metastatic castration-resistant prostate cancer (mCRPC) patients, the "4W1H" principle was applied in the second biopsy. The biopsy site, image, and laboratory variables affected the positive of tumor tissue. Further pathological analysis of tumor tissue is essential to guide the precision medicine of mCRPC etiological classification.