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Introduction: Evaluation of the eruption of mandibular third molars in orthopantomograms (OPGs) is a method of forensic age assessment. The objective of our study was to provide valid reference data for this trait within a population of black South Africans. The study was guided by the criteria for reference studies in age assessment. Materials and methods: A study population from Pretoria, South Africa comprising 670 OPGs obtained from 338 black females and 332 black males aged between 15.00 and 25.97 years was analysed. All OPGs were performed for medical indication during the period from 2011 to 2022 and were retrospectively evaluated. From the 670 OPGs, a total of 1021 mandibular third molars were evaluated. The assessment of mandibular third molars was conducted using the staging scale presented by Olze et al. in 2012. Two experienced dentists evaluated the OPGs independently of each other. If the two examiners diverged in their assessments, a consensus stage was assigned. Results: As expected, the mean, median and minimal age increased with higher stages for both teeth and both sexes. The minimum age recorded for stage D, indicating complete tooth eruption, was 15.79 years in females and 16.62 years in males. Conclusion: As it is the case for previous reference studies in other countries, placing exclusive reliance on the evaluation of mandibular third molar eruption is inadequate for ascertaining the age of majority among Black South Africans. Future studies need to examine if our results are transferable to other countries in Sub-Saharan Africa. [ABSTRACT FROM AUTHOR]

This paper addresses a relevant problem in Forensic Sciences by integrating radiological techniques with advanced machine learning methodologies to create a non-invasive, efficient, and less examiner-dependent approach to age estimation. Our study includes a new dataset of 12,827 dental panoramic X-ray images representing the Brazilian population, covering an age range from 2.25 to 96.50 years. To analyze these exams, we employed a model adapted from InceptionV4, enhanced with data augmentation techniques. The proposed approach achieved robust and reliable results, with a Test Mean Absolute Error of 3.1 years and an R-squared value of 95.5%. Professional radiologists have validated that our model focuses on critical features for age assessment used in odontology, such as pulp chamber dimensions and stages of permanent teeth calcification. Importantly, the model also relies on anatomical information from the mandible, maxillary sinus, and vertebrae, which enables it to perform well even in edentulous cases. This study demonstrates the significant potential of machine learning to revolutionize age estimation in Forensic Science, offering a more accurate, efficient, and universally applicable solution. [ABSTRACT FROM AUTHOR]

A computer-based age estimation is a technique that predicts an individual's age based on visual traits derived by analyzing a 2D picture of the individual's face. Age estimation is critical for access control, e-government, and effective human–computer interaction. The other-race effect has the potential to cause techniques designed for white faces to underperform when used in a region with black faces. The outcome is the consequence of intermittent training with faces of the same race and the encoding structure of the trained face images, which is based on the feature extraction technique used. This study contributes to a constructive comparison of three feature-extraction techniques, namely, local binary pattern (LBP), Gabor Wavelet (GW), and wavelet transformation, used in the development of a genetic algorithm (GA)-artificial neural network (ANN)-based age estimation system. The feature extraction techniques used are proven to produce a wealth of shape and textural information. The GA-ANN constitutes the age classifier module. The correct classification rate was chosen as the performance metrics in this study. The results demonstrated that the LBP is a more robust representation of the black face than the GW and Wavelet transformations, as evidenced by its accuracy rate of 91.76 compared to 89.41 and 84.71 achieved with the GW and Wavelet transformation age estimation systems, respectively. [ABSTRACT FROM AUTHOR]

Background: Forensic anthropological examinations help in identification of unidentified human remains. This study aims to establish population-specific standards for age estimation from the sternal ends of left fourth ribs in the Nepalese population. A quantitative, observational study was conducted on 387 Nepalese deceased (106 females, 281 males) between November 2021 and March 2023. Left fourth ribs were collected, macerated and examined for the study. The variables examined included pit depth, pit shape, rim and wall configurations and rib phase. Results: Pit depth significantly predicted age, β = 0.642, t(385) = 16.42, p < 0.001. Pit depth also explained a significant proportion of variance in age, R2 = 0.41, F(1, 385) = 269.54, p < 0.001. The age estimates from pit depth stage were 7–36 (stage 0), 7–49 (stage 1), 16–51 (stage 2), 10–58 (stage 3), 22–70 (stage 4) and 32–81 (stage 5). Age estimates for pit shape were 17–20 (stage 0), 13–48 (stage 2), 15–55 (stage 3), 24–68 (stage 4) and 39–82 (stage 5). Age estimates for rim and wall configurations were 17–20 (stage 0), 13–47 (stage 2), 17–53 (stage 3), 24–68 (stage 4) and 40–82 (stage 5). Similarly, age estimates for rib phase were 17–20 (phase 0), 18–20 (phase 1), 13–46 (phase 2), 18–50 (phase 3), 23–60 (phase 4), 32–71 (phase 5), 50–76 (phase 6), 44–81 (phase 7) and 62–85 (phase 8). The study also examined the use of transitional analysis to develop posterior probability distributions for estimation of age using rib phases. Conclusion: This study found significant differences in the age estimates from previous studies and shows the importance of developing population-specific models for use in forensic anthropology. [ABSTRACT FROM AUTHOR]

Sex and chronological age estimation are crucial in forensic investigations and research on individual identification. Although manual methods for sex and age estimation have been proposed, these processes are labor-intensive, time-consuming, and error-prone. The purpose of this study was to estimate sex and chronological age from panoramic radiographs automatically and robustly using a multi-task deep learning network (ForensicNet). ForensicNet consists of a backbone and both sex and age attention branches to learn anatomical context features of sex and chronological age from panoramic radiographs and enables the multi-task estimation of sex and chronological age in an end-to-end manner. To mitigate bias in the data distribution, our dataset was built using 13,200 images with 100 images for each sex and age range of 15–80 years. The ForensicNet with EfficientNet-B3 exhibited superior estimation performance with mean absolute errors of 2.93 ± 2.61 years and a coefficient of determination of 0.957 for chronological age, and achieved accuracy, specificity, and sensitivity values of 0.992, 0.993, and 0.990, respectively, for sex prediction. The network demonstrated that the proposed sex and age attention branches with a convolutional block attention module significantly improved the estimation performance for both sex and chronological age from panoramic radiographs of elderly patients. Consequently, we expect that ForensicNet will contribute to the automatic and accurate estimation of both sex and chronological age from panoramic radiographs. [ABSTRACT FROM AUTHOR]

Age estimation methods through the metric study of bones in non-adult individuals are a frequently used tool in Biological and Forensic Anthropology; however, few methodological validation studies are available, given the limited number of adequate samples for their study. In this context, the aim of this work is to test the effectiveness of the methods of Fazekas and Kósa (1978), Saunders et al. (1993), Rissech and Black (2007) and Cardoso et al. (2017), for age estimation through the measurements of the scapula, in the non-adult osteological collection of the Anthropology Laboratory of the University of Granada (Spain), one of the most representative identified non-adult collections internationally. For this purpose, nine different measurements of the scapula were taken from a total of 149 non-adult individuals, applying the regression formulae proposed by the different authors and verifying their accuracy. Results have shown the existence of significant differences between the real age and the estimated age in almost all the tested methods, with degrees of error that differ from those obtained in the original study populations. Based on the obtained results, it is recommended to use the method of Cardoso et al. in postnatal individuals, always adjusting the degrees of error with those obtained in this work. [ABSTRACT FROM AUTHOR]

Various staging scales have been proposed for the assessment of the visibility of the periodontal ligament space of mandibular third molars on dental panoramic radiographs (PANs) for forensic age assessment in living individuals. However, up to now, there has been no systematic comparison between these staging scales available. We directly compared the 2010 staging scale proposed by Olze et al. with the 2017 staging by Lucas et al. and the 2020 staging by Guo et al. in a German study population. We evaluated 233 PANs from 115 females and 118 males aged 20.0 to 40.9 years using three independent examiners, with one examiner conducting two assessments. We examined the correlation between age and stage, as well as the inter- and intra-rater reliabilities. While the point estimates for the correlation coefficient and the reliability measures were lowest for the Guo scale and highest for the Olze scale, confidence intervals showed a large overlap, particularly for the scales of Olze et al. and Lucas et al. The correlation coefficients between stage and age were consistently lower in females than in males across all methods. In summary, we showed that the staging scales of Olze et al. and Lucas et al. were very similar. The Olze method showed higher point estimates across all analyses, and because there are more reference data available for this method, we argue that it should be preferred as the method of choice for further studies in the field. However, Guo method could be considered for instances, in which the inter-radicular periodontal ligament is not evaluable. [ABSTRACT FROM AUTHOR]

The human face is a valuable biomarker of aging, but the collection and use of its image raise significant privacy concerns. Here we present an approach for facial data masking that preserves age-related features using coordinate-wise monotonic transformations. We first develop a deep learning model that estimates age directly from non-registered face point clouds with high accuracy and generalizability. We show that the model learns a highly indistinguishable mapping using faces treated with coordinate-wise monotonic transformations, indicating that the relative positioning of facial information is a low-level biomarker of facial aging. Through visual perception tests and computational 3D face verification experiments, we demonstrate that transformed faces are significantly more difficult to perceive for human but not for machines, except when only the face shape information is accessible. Our study leads to a facial data protection guideline that has the potential to broaden public access to face datasets with minimized privacy risks. [ABSTRACT FROM AUTHOR]

Background: The aim of this study, which was based on this hypothesis, was to estimate sex and age by using a machine learning algorithm (ML) and artificial neural networks (ANN) with parameters obtained from the eyeball. The study was conducted on corneal topography images of 155 women and 155 men aged between 6 and 87 who did not have surgical intervention or pathology in their eyeballs. In the study, the individuals were divided into four different age groups 6–17, 18–34, 35–55, and 56–87. Sex and age estimation was carried out by using the numerical data of parameters obtained as a result of corneal topography imaging in ML and ANN inputs. Results: As a result of our study, in sex determination, a 0.98 accuracy rate (Acc) was obtained with the logistic regression algorithm, one of the ML algorithms, and 0.94 Acc was obtained with the MLCP model, one of the ANN algorithms; in age estimation, 0.84 Acc was obtained with RF algorithm, one of the ML algorithms. With the SHAP analyzer of the Random Forest algorithm, through which the effects of parameters on the overall result are evaluated, the parameter that made the highest contribution to sex estimation was found to be corneal volume, and the parameter that made the highest contribution to age estimation was found to be pupil Q parameter. Conclusion: As a result of our study, it was found that parameters obtained from the eyeball showed a high accuracy in sex and age estimation. [ABSTRACT FROM AUTHOR]

This paper presents a retrospective analysis of postmortem computed tomography (PMCT) scans of secondary ossification centers in the medial clavicular epiphysis, iliac crest apophysis, proximal humeral epiphysis, distal femoral epiphysis, proximal tibial epiphysis, and distal tibial epiphysis. At the same time, we analyzed PMCT scans of the maxillary and mandibular incisors, canines, premolars, and molars. We assessed 203 corpses, whose age ranged from 2 to 30 years, including 156 males and 47 females. The purpose of our study was to compare the processes of secondary ossification center fusion and permanent tooth maturation. Our research hypothesis was that certain stages of skeletal and dental maturation occur along consistent timelines that can be related to the chronological age. Secondary ossification center fusion was evaluated based on Kreitner and also McKern and Steward's classifications. The process of permanent tooth maturation was evaluated with Demirjian's method. Spearman's correlation coefficients (Rho) were positive in all analyses, which indicates that epiphyseal fusion progresses with age. The strongest relationship between the age and the stages of ossification was observed in the proximal tibial epiphysis (p < 0.001; Rho = 0.93) in females and in the medial clavicular epiphysis (p < 0.001; Rho = 0.77) in males. Studies show the importance of concomitant analysis of skeletal and dental maturation with a subsequent comparison of the results to achieve a greater precision in age estimation. A comparison of the results obtained in the study population of Polish children, adolescents, and young adults with the results of other studies in populations of similar ages showed a number of similarities in the time windows of dental and skeletal maturation. These similarities may help in age estimation. [ABSTRACT FROM AUTHOR]

The age estimation (AE) of human remains is a challenging task since it is dependent on the state in which these remains are found. Since the macroscopic evaluation of palatal sutures has been proposed as a method for AE, the aim of this study was to review the literature on this method, considering that the cases of edentulous elderly are among the greatest challenges in anthropological and forensic contexts. A scoping review was performed using a specific search strategy in PubMed, Web of Science, SciELO, LILACS, and Google Scholar. The search identified 13 articles, among which the USA yielded the most information with 3 articles. Only 1 study was identified in Latin America (Peru). There was great diversity regarding the origin of samples, and the studies were carried out on both historical and modern populations. Only 6 articles exceeded the average sample size (168.08) and 4 articles studied samples of fewer than 100 individuals. Although 6 different methods were identified, Mann et al.'s revised method was the most used. The selection of appropriate methods for AE depends on what skeletal elements are present and the general age of the specimens. Although evaluation of the obliteration of the palatal sutures has been found to be simple and promising for AE in individuals over 60 years of age, this method has been reported to have less precision than other more complex methods, which makes the use of a combination of methods necessary to increase the level of confidence and the percentage of success. Further research could resolve this weakness, and methodological refinement (perhaps the digitization and automation of processes, or the application of Bayesian methodology) could provide the necessary solidity to comply with international standards in the forensic scenario. [ABSTRACT FROM AUTHOR]

Age estimation constitutes one of the pillars of human identification. The auricular surface of the ilium presents as a durable and robust structure within the human skeletal framework, capable of enabling accurate age estimation in older adults. Amongst different documented auricular age estimation methods, the Buckberry-Chamberlain method offers greater objectivity through its component-based approach. The present study aimed to test the applicability of the Buckberry-Chamberlain method in an Indian population through a CT-based examination of the auricular surface. CT scans of 435 participants undergoing CT examinations following the advice of their treating physicians were scrutinized for different age-related auricular changes. Three of the five morphological features described by Buckberry-Chamberlain could be appreciated on CT scans, and thus further statistical analysis was restricted to these features. Transition analysis coupled with Bayesian inference was undertaken individually for each feature to enable age estimation from individual features, while circumventing age mimicry. A Bayesian analysis of individual features yielded highest accuracy percentages (98.64%) and error rates (12.99 years) with macroporosity. Transverse organization and apical changes yielded accuracy percentages of 91.67% and 94.84%, respectively, with inaccuracy computations of 10.18 years and 11.74 years, respectively. Summary age models, i.e. multivariate age estimation models, derived by taking this differential accuracy and inaccuracy into consideration yielded a reduced inaccuracy value of 8.52 years. While Bayesian analysis undertaken within the present study enables age estimation from individual morphological features, summary age models appropriately weigh all appreciable features to yield more accurate and reliable estimates of age. [ABSTRACT FROM AUTHOR]

Age assessment of migrants is crucial, particularly for unaccompanied foreign minors, a population facing legal, social, and humanitarian challenges. Despite existing guidelines, there is no unified protocol in Europe for age assessment. The Forensic Anthropology Society of Europe (FASE) conducted a comprehensive questionnaire to understand age estimation practices in Europe. The questionnaire had sections focusing on the professional background of respondents, annual assessment numbers, requesting parties and reasons, types of examinations conducted (e.g., physical, radiological), followed protocols, age estimation methods, and questions on how age estimates are reported. The questionnaire's findings reveal extensive engagement of the forensic community in age assessment in the living, emphasizing multidisciplinary approaches. However, there seems to be an incomplete appreciation of AGFAD guidelines. Commonalities exist in examination methodologies and imaging tests. However, discrepancies emerged among respondents regarding sexual maturity assessment and reporting assessment results. Given the increasing importance of age assessment, especially for migrant child protection, the study stresses the need for a unified protocol across European countries. This can only be achieved if EU Member States wholeheartedly embrace the fundamental principles outlined in EU Directives and conduct medical age assessments aligned with recognized standards such as the AGFAD guidelines. [ABSTRACT FROM AUTHOR]

The purpose of this study is to estimate chronological age and determine whether individuals were aged under or over 18 years using root pulp visibility (RPV) in cone-beam computed tomography (CBCT) images. The study included CBCT images of 699 individuals aged between 15 and 75 years. One thousand twenty-three mandibular second molar (2M) teeth were evaluated using Olze's RPV method in four stages. Descriptive statistics of the stages and the relationship between the stages and the chronological age were assessed. The distribution of the stages was analyzed according to the 18-year age threshold. There was a positive correlation between RPV stages and chronological ages in both sexes. For females and males, the mean ages of stage 0, stage 1, and stage 2, for females and males, were found as 27.21, 28.93, and 33.68 years, and 37.69, 40.9, and 44.88 years, respectively. Stage 0 and stage 1 were found both in individuals aged under and over 18 years, and stage 2 and stage 3 were not observed in individuals aged under 18 years. The presence of stage 2 and stage 3 may be an indication that an individual is aged over 18 years according to Olze's RPV age estimation method. For more reliable results, 2M teeth should be examined bilaterally in forensic science. [ABSTRACT FROM AUTHOR]

Third molar development is used for dental age estimation when all the other teeth are fully mature. In most medicolegal facilities, dental age estimation is an operator-dependent procedure. During the examination of unaccompanied and undocumented minors, this procedure may lead to binary decisions around age thresholds of legal interest, namely the ages of 14, 16 and 18 years. This study aimed to test the performance of artificial intelligence to classify individuals below and above the legal age thresholds of 14, 16 and 18 years using third molar development. The sample consisted of 11,640 panoramic radiographs (9680 used for training and 1960 used for validation) of males (n = 5400) and females (n = 6240) between 6 and 22.9 years. Computer-based image annotation was performed with V7 software (V7labs, London, UK). The region of interest was the mandibular left third molar (T38) outlined with a semi-automated contour. DenseNet121 was the Convolutional Neural Network (CNN) of choice and was used with Transfer Learning. After Receiver-operating characteristic curves, the area under the curve (AUC) was 0.87 and 0.86 to classify males and females below and above the age of 14, respectively. For the age threshold of 16, the AUC values were 0.88 (males) and 0.83 (females), while for the age of 18, AUC were 0.94 (males) and 0.83 (females). Specificity rates were always between 0.80 and 0.92. Artificial intelligence was able to classify male and females below and above the legal age thresholds of 14, 16 and 18 years with high accuracy. [ABSTRACT FROM AUTHOR]

Insects, especially blow flies, are forensically relevant to determine the minimal postmortem interval (PMImin), based on the fact that they are usually the first colonisers of a body. By estimating the age of immature blow flies, interferences can be made about the time since death. Whilst morphological parameters are valuable for age estimation of blow fly larvae, gene expression profiling is more applicable for blow fly pupae. Here, the age-dependent changes in the gene expression levels during the development are analysed. 28 temperature-independent markers have already been described for the age estimation of pupae of the forensically important blow fly Calliphora vicina and are analysed by RT-qPCR. To allow simultaneous analysis of these age markers, a multiplex assay was developed in the present study. After reverse transcription, the markers are analysed simultaneously in an endpoint PCR and subsequently separated by capillary electrophoresis (CE). This method is highly attractive due to its quick and easy procedure and interpretation. The present age prediction tool was adapted and validated. The multiplex PCR assay reproduced the same expression profiles as the RT-qPCR assay based on the same markers. The statistical evaluation shows that the new assay has a lower precision but a better trueness for age determination compared to the RT-qPCR assay. Since the new assay is also qualified to estimate the age of C. vicina pupae and is practical, cost-effective and, even more importantly, time-saving, it is attractive for use in forensic casework. [ABSTRACT FROM AUTHOR]

Purpose: Medical imaging can be used to estimate a patient's biological age, which may provide complementary information to clinicians compared to chronological age. In this study, we aimed to develop a method to estimate a patient's age based on their chest CT scan. Additionally, we investigated whether chest CT estimated age is a more accurate predictor of lung cancer risk compared to chronological age. Methods: To develop our age prediction model, we utilized composite CT images and Inception-ResNet-v2. The model was trained, validated, and tested on 13,824 chest CT scans from the National Lung Screening Trial, with 91% for training, 5% for validation, and 4% for testing. Additionally, we independently tested the model on 1849 CT scans collected locally. To assess chest CT estimated age as a risk factor for lung cancer, we computed the relative lung cancer risk between two groups. Group 1 consisted of individuals assigned a CT age older than their chronological age, while Group 2 comprised those assigned a CT age younger than their chronological age. Results: Our analysis revealed a mean absolute error of 1.84 years and a Pearson's correlation coefficient of 0.97 for our local data when comparing chronological age with the estimated CT age. The model showed the most activation in the area associated with the lungs during age estimation. The relative risk for lung cancer was 1.82 (95% confidence interval, 1.65–2.02) for individuals assigned a CT age older than their chronological age compared to those assigned a CT age younger than their chronological age. Conclusion: Findings suggest that chest CT age captures some aspects of biological aging and may be a more accurate predictor of lung cancer risk than chronological age. Future studies with larger and more diverse patients are required for the generalization of the interpretations. [ABSTRACT FROM AUTHOR]

Population irruptions of crown-of-thorns seastar (CoTS, Acanthaster spp.) represent a perennial threat to Indo-Pacific coral reefs. Age determination of CoTS is challenging, thereby hindering understanding and management of this nuisance species. Telomeres, which are protective DNA structure found at the ends of eukaryotic chromosomes that shorten at each cell division, have been used to estimate age in wild animals. To investigate the use of telomeres in CoTS, we optimized a quantitative PCR protocol to measure relative telomere length (rTL) in CoTS for the first time. Comparing rTL among four age groups (4, 7, 16, > 24 months post-settlement), we found that adult CoTS generally exhibit shorter rTL than juveniles, which is the first evidence of age-related telomere attrition in CoTS. However, there was large within-age class variation, and no significant relationships were found between adult CoTS rTL and potential age-indicating external features. Furthermore, we found accelerated telomere attrition under sub-optimal diet, where individuals that were fed crustose coralline algae for 16 months exhibited shorter rTL than their counterparts fed on coral. A positive correlation was found between rTL of tube feet and pyloric caeca, suggesting synchronization of telomere dynamics across somatic tissues in CoTS. Overall, our results suggest that rTL could be used to classify CoTS into broad age groups, though individual variation constrains the ability to resolve specific cohorts. The present study contributes to the understanding of telomere dynamics in marine invertebrates, while laying the groundwork for future research into rTL as biomarker for age and potentially stress for CoTS. [ABSTRACT FROM AUTHOR]

Background: Forensic age estimation using multiple maturity indicators necessitates investigation of correlation between various techniques. This study intended to compare and evaluate the correlation between skeletal age using Greulich-Pyle atlas, dental age by Acharya's modification of Demirjian's technique and London Atlas method of Tooth Development, and age estimated by body developmental index with chronological age. Orthopantomograms and left hand-wrist radiographs of one hundred seventy-four subjects (64 males and 70 females) in the age group of 8–20 years were evaluated by age estimation methods. Physical parameters including height, weight, biacromial breadth, and biliospinale breadth were measured. The data were entered in the SPSS software (Version 27.0). Comparison between age estimation methods was done using Student's t-test for paired samples. Unpaired t-test was utilized for gender-wise comparison of age. Pearson's correlation coefficient was calculated to assess correlation between the various methods. Results: Significant mean differences were noted between the chronological age and all the age estimation methods when Greulich-Pyle atlas method (− 0.43), modified Demirjian's method (− 0.31), London Atlas Method (− 0.62), and body developmental index (− 0.51) were employed respectively. Inter-group comparison between all methods yielded no significant differences except for modified Demirjian's method and London Atlas method (mean difference = 0.31). All the age estimation techniques showed strong correlation with chronological age; the best was provided by the Greulich-Pyle method (r = 0.92). Conclusion: All the assessed age estimation techniques show strong correlation with chronological age. Acharya's modified Demirjian's method (dental age) and Greulich-Pyle atlas method (skeletal age) showed good accuracy and strong correlation with chronological age, suggesting that these methods can be used simultaneously and/or interchangeably for age assessment in children and adolescents of Eastern Indian population. [ABSTRACT FROM AUTHOR]

Purpose: To investigate prediction of age older than 18 years in sub-adults using tooth tissue volumes from MRI segmentation of the entire 1st and 2nd molars, and to establish a model for combining information from two different molars. Materials and methods: We acquired T2 weighted MRIs of 99 volunteers with a 1.5-T scanner. Segmentation was performed using SliceOmatic (Tomovision©). Linear regression was used to analyse the association between mathematical transformation outcomes of tissue volumes, age, and sex. Performance of different outcomes and tooth combinations were assessed based on the p-value of the age variable, common, or separate for each sex, depending on the selected model. The predictive probability of being older than 18 years was obtained by a Bayesian approach using information from the 1st and 2nd molars both separately and combined. Results: 1st molars from 87 participants, and 2nd molars from 93 participants were included. The age range was 14-24 years with a median age of 18 years. The transformation outcome (high signal soft tissue + low signal soft tissue)/total had the strongest statistical association with age for the lower right 1st (p= 7.1*10-4 for males) and 2nd molar (p=9.44×10-7 for males and p=7.4×10-10 for females). Combining the lower right 1st and 2nd molar in males did not increase the prediction performance compared to using the best tooth alone. Conclusion: MRI segmentation of the lower right 1st and 2nd molar might prove useful in the prediction of age older than 18 years in sub-adults. We provided a statistical framework to combine the information from two molars. [ABSTRACT FROM AUTHOR]

This study proposes an assessment of the accuracy of the Fazekas and Kósa and Nagaoka methods by measuring the squamosal and petrous portions of the temporal bone, whose application in the Mediterranean population is not recommended. Therefore, our proposal is a new formula to estimate the age of skeletal remains from individuals at 5 months gestational age to 1.5 postnatal years with the temporal bone. The proposed equation was calculated on a Mediterranean sample identified from the cemetery of San José, Granada (n = 109). The mathematical model used is the exponential regression of the estimated age for each measure and sex, and both in combination, using an inverse calibration and cross-validation model. In addition, the estimation errors and the percentage of individuals within a 95% confidence interval were calculated. The lateral development of the skull, especially the growth of the length of the petrous portion, showed the greatest accuracy, while its counterpart, the width of the pars petrosa, showed the lowest accuracy, so its use is discouraged. The positive results from this paper should be useful in both forensic and bioarchaeological contexts. [ABSTRACT FROM AUTHOR]

In forensic investigations, age estimation is vital for determining whether a suspect is under or over the legally defined adult age. With breakthroughs in RNA sequencing technology, small noncoding RNAs have provided new ways to solve problems related to the age estimation of trace or aged samples, owing to their small molecular weight and better stability. In our previous study, we had applied miRNAs for the age estimation of bloodstains; however, further improvement of the existing model is needed. PIWI-interacting RNAs (PiRNAs), which are 24–32 nt noncoding small RNA molecules involved in the PIWI-piRNA pathway, play an important role in the aging process. In this study, we explored the possibility of simultaneously analyzing piRNAs and miRNAs for better age estimation purpose. Through massively parallel sequencing, five age-related piRNAs were identified in blood samples that had been stored for eight years. Further real-time PCR analysis revealed that two piRNAs (piR-000753 and piR-020548) showed relatively higher efficiency in age estimation. Additionally, two age-related miRNAs (miR-324-3p and miR-330-5p) were used to build the estimation model. Among all algorithms tested, gradient boosting showed the lowest mean absolute error (MAE) and root mean square error (RMSE) values (3.171 and 4.403 years, respectively) for the validation dataset (n = 110). The errors of the model were less than 5 years and 10 years for 81.82% and 96.36% of the samples, respectively. The results suggest that the combined use of piRNA and miRNA markers may increase the accuracy of age estimation, and our new model has great potential for application in forensic casework. [ABSTRACT FROM AUTHOR]

In forensic medicine practice, age estimation—both in living and deceased individuals—can be requested due to legal requirements. Radiologic methods, such as X-rays, for the estimation of bone age have been discussed, and ethical concerns have been raised. Given these factors, radiologic methods that reduce radiation exposure have gained importance and have become one of the research topics in forensic medicine. In this study, the MR images of the ankles of patients aged between 8 and 25 years, obtained with a 3.0 T MR scanner, were evaluated retrospectively according to the staging method defined by Vieth et al. In the study, the ankle MR images of 201 cases (83 females and 118 males) with sagittal T1-weighted turbo spin echo and T2-weighted short tau inversion recovery sequences were evaluated independently by two observers. According to the results of our study, the intra- and inter-observer agreements are at a very good level for both the distal tibial and calcaneal epiphyses. All the cases detected as stages 2, 3, and 4 in both sexes for both the distal tibial and the calcaneal epiphyses have been determined to be under the age of 18 years. According to the data obtained from our study, we consider that stage 5 for males and stage 6 for both sexes in the distal tibial epiphysis and stage 6 for males in the calcaneal epiphysis can be used to estimate the age of 15 years. As far as we know, our study is the first to evaluate ankle MR images with the method defined by Vieth et al. Further studies should be conducted to evaluate the validity of the procedure. [ABSTRACT FROM AUTHOR]

This article is a retrospective analysis of postmortem computed tomography scans of ossification stages of the anterior and posterior intra-occipital sutures, the anterior arch of the atlas, and the neurocentral junction of the axis. We also analyzed the development of secondary ossification centers in the proximal humeral, femoral, and tibial epiphyses, and the distal femoral and tibial epiphyses. Additionally, the development of primary ossification centers in the wrist and metacarpals, and maxillary and mandibular deciduous tooth maturation. A total of 58 cadavers (35 males, 23 females), whose age ranged from 3rd month of pregnancy to 14 years, were analyzed. The results of this study show that analysis of synchondrosis closure, primary, and secondary ossification center development and deciduous tooth changes are a good tool for age estimation in subadults group (fetuses, newborns, infants, and children). The results of the study in a Polish population are consistent with those reported by other authors. [ABSTRACT FROM AUTHOR]

This study sought to develop an age-estimation formula to evaluate the extent of median palatine suture (MP) closure using postmortem computed tomographic (PMCT) images. The PMCT images of 634 Japanese subjects (mean age, 54.5 years; standard deviation [SD], 23.2 years) with known age and sex were examined. The degree of suture closure of the MP, anterior median palatine suture (AMP), and posterior median palatine suture (PMP) was measured and scored (suture closure score, SCS), and a single linear regression analysis was conducted with age at death. On the analysis, SCS of MP, AMP, and PMP showed a significant correlation with age (p < 0.001). The correlation coefficient of MP was higher (0.760, male; 0.803, female; and 0.779, total) than that of AMP (0.726, male; 0.745, female; and 0.735, total) or PMP (0.457, male; 0.630, female; and 0.549, total). The regression formula and standard error of estimation (SEE) of MP were calculated as Age = 100.95 × SCS + 20.51 (SEE 14.87 years) for male subjects, Age = 91.93 × SCS + 26.65 (SEE 14.12 years) for female subjects, and Age = 95.17 × SCS + 24.09 (SEE 14.59 years) for the total, respectively. In addition, another 50 Japanese subjects were randomly selected to validate the age-estimation formula. In this validation, the actual age of 36 subjects (72%) was within the estimated age ± SEE. This study showed that the age estimation formula using PMCT images of MPs was potentially useful for estimating the age of unidentified corpses. [ABSTRACT FROM AUTHOR]

Background: The purpose of this study was to evaluate the accuracy of established mathematical regression models for estimating the age of Egyptian children, develop new models that would better match this population and to evaluate the validity and reliability of these new models. Results: One thousand one hundred fifteen children ranging in age between 6–14 years participated in the study. Group I consisted of 1000 children; 513 (51.3%) children were of the age group 6–< 9 years and 487 (48.7%) children were 9–14 years. Male children were 484 (48.4%) while female children were 516 (51.6%). Group II consisted of 115 children; 84 (73%) children were of the age group 6–< 9 years and 31 (27%) children were 9–14 years. Male children were 58 (50.4%) while Female children were 57 (49.6%). Foti regression models showed poor agreement of Intraclass Correlation Coefficient (ICC) with chronological age of children in the mixed dentition stage. The new regression models for estimating dental age showed ICC of more than 0.7 with chronological age suggesting better accuracy in age estimation than Foti models. Conclusions: The newly formulated regression models are reliable for estimating the age of Egyptian children during the mixed dentition stage. A good agreement was found between the estimated age obtained from the first two models and the chronological age. However, the third model had the least agreement, suggesting that age estimation may be more accurate using only the first two models. [ABSTRACT FROM AUTHOR]

Background: Age estimation has paramount importance for the forensic practitioner. Depending on the timing of fusion, the spheno-occipital synchondrosis will be open during childhood and then later fuse during adulthood. Since there have been a lot of inconsistencies in terms of fusion degree, that can be attributed to variability in population or methodology. The aim of the present study was to determine the age of beginning of the spheno-occipital synchondrosis in the South Indian population using computed tomography. Results: The study reported a mean age of 8.38 ± 1.21 for males and 8.2 ± 1.16 for females in the stage 0 (completely open) category. Spheno-occipital synchondrosis began to fuse (stage 1) at the mean age of 11.64 ± 1.19 for males and 10.21 ± 1.19 for females. Conclusions: Spheno-occipital synchondrosis begins to close at the age of less than 15 years in males. Similarly, for females, the spheno-occipital synchondrosis begins to close at the age of less than 14 years. Also, a strong sexual dimorphism is seen as each stage of synchondrosis and starts earlier in females compared to males. In addition, the study also showed the degree of fusion increasing with age. This estimation will not only help in forensic and anthropological studies but also in assessing craniofacial growth in orthodontics. [ABSTRACT FROM AUTHOR]

Background: The aim of this study is to obtain a highly accurate and objective sex and age estimation by using the parameters of maxillary molar and canine teeth obtained from cone beam computed tomography images in the input of machine learning algorithms. Cone beam computed tomography images of 240 people aged between 25 and 54 were randomly selected from the archive systems of the hospital and transferred to Horos Medikal. 3D curved multiplanar reconstruction was applied to these images and a 3D image was obtained. The resulting image was brought to the orthogonal plane and the measurements were made by superimposing them. Results: The results were grouped in four different age groups (25–30, 31–36, 37–49, 50–54) and recorded. As a result of our study, the highest accuracy rate was found as 0.81 in sex estimation with ADA Boost Classifier algorithm, while in age estimation, the highest accuracy rate was found as 0.84 between 25–30 and 31–36 age groups with random forest algorithm, as 0.74 between 25–30 and 37–49 age groups with random forest and ADA Boost Classifier algorithms and as 0.85 between 25–30 and 50–54 age groups with random forest algorithm. Conclusions: Our study differs from other studies in two aspects; the first is the selection of a sensitive method such as cone beam computed tomography, and the second is the selection of machine learning algorithms. As a result of our study, the highest accuracy rate was found as 0.81 in sex estimation and as 0.85 in age estimation with parameters of maxillary canine and molar teeth. [ABSTRACT FROM AUTHOR]

When investigating a death, post-mortem identification provides with results of great legal and humanitarian significance. The effectiveness of the methods used to estimate age depends on the reference population, considering variables such as sex and ancestry. The aim of this study was to validate the Iscan method to estimate age in a Spanish forensic population, comparing the estimates obtained in dry bones and 3D reconstructions created with a surface scanner. We carried out a cross-sectional study on 109 autopsied corpses (67% male), scanning the sternal end of the right fourth rib in a 3D mesh, using an EinScan-Pro® surface scanner (precision: 0.05 mm). Two observers estimated the phases in dry bones and 3D images according to the Iscan method and to the sex of the subject. The mean age was 57.73 years (SD = 19.12 years;18–93 years). The intra-observer agreement was almost perfect in bones (κ = 0.877–0.960) and 3D images (κ = 0.954), while the inter-observer agreement was almost perfect in bones (κ = 0.813) and substantial in 3D images (κ = 0.727). The correlation with the Iscan phases was very strong in bones (Rho = 0.794–0.820; p < 0.001) and strong in 3D images (Rho = 0.690–0.691; p < 0.001). Both sex-adjusted linear regression models were significant (dry bones: R2 = 0.65; SEE = ± 11.264 years; 3D images: R2 = 0.50; SEE = ± 13.537 years) from phase 4 onwards. An overestimation of age was observed in the first phases, and an underestimation in the later ones. Virtual analysis using a surface scanner in the fourth rib is a valid means of estimating age. However, the error values and confidence intervals were considerable, so the joint use of different methods and anatomical sites is recommended. [ABSTRACT FROM AUTHOR]

Purpose: Our aim was to investigate tissue volumes measured by MRI segmentation of the entire 3rd molar for prediction of a sub-adult being older than 18 years. Material and method: We used a 1.5-T MR scanner with a customized high-resolution single T2 sequence acquisition with 0.37 mm iso-voxels. Two dental cotton rolls drawn with water stabilized the bite and delineated teeth from oral air. Segmentation of the different tooth tissue volumes was performed using SliceOmatic (Tomovision©). Linear regression was used to analyze the association between mathematical transformation outcomes of the tissue volumes, age, and sex. Performance of different transformation outcomes and tooth combinations were assessed based on the p value of the age variable, combined or separated for each sex depending on the selected model. The predictive probability of being older than 18 years was obtained by a Bayesian approach. Results: We included 67 volunteers (F/M: 45/22), range 14–24 years, median age 18 years. The transformation outcome (pulp + predentine)/total volume for upper 3rd molars had the strongest association with age (p = 3.4 × 10−9). Conclusion: MRI segmentation of tooth tissue volumes might prove useful in the prediction of age older than 18 years in sub-adults. [ABSTRACT FROM AUTHOR]

As one of the critical biological characteristics of human age, the face has been widely studied for age prediction, which has broad application prospects in the fields of commerce, security, entertainment, etc. Duo to complicated multi-latent heterogeneous features(e.g. gender) bring valuable messages for the image-based age estimation. A variety of methods utilize heterogeneous information for age estimation. However, heterogeneous features may have uncertain noise, and exploiting them without evaluating the reliability of confidence influence may impact the estimation accuracy. Inspired by the observation that gender has a noticeable impact on face at some particular age stage, this paper proposes a Feature Constraint Reinforcement Network (FCRN) to take advantage of constraint gender influence on the age estimation. The model extracts multi-scale latent heterogeneous features and deduces their confidence of influence upon age estimation methods. Specifically, it gets the gender and age features by classification and regression. Then, the model uses the gender factors extracted from the constraint gender features to reinforce and calculate the influence of different genders on age predictions among different age groups and improve the result of age prediction. Extensive experiments were conducted on the existing public aging datasets. The results show the effectiveness and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

Handwritten image-based writer age estimation is a challenging task due to the various writing styles of different individuals, use of different scripts, varying alignment, etc. Unlike age estimation using face recognition in biometrics, handwriting-based age classification is reliable and inexpensive because of the plain backgrounds of documents. This paper presents a novel model for deriving the phase spectrum based on the Harmonic Wavelet Transform (HWT) for age classification on handwritten images from 11 to 65 years. This includes 11 classes with an interval of 5 years. In contrast to the Fourier transform, which provides a noisy phase spectrum due to loss of time variations, the proposed HWT-based phase spectrum retains time variations of phase and magnitude. As a result, the proposed HWT-based phase spectrum preserves vital information of changes in handwritten images. In order to extract such information, we propose new phase statistics-based features for age classification based on the understanding that as age changes, writing style also changes. The features and the input images are fed to a VGG-16 model for age classification. The proposed method is tested on our own dataset and three standard datasets, namely, IAM-2, KHATT and that of Basavaraja et al. to demonstrate the effectiveness of the proposed model compared to the existing methods in terms of classification rate. The results of the proposed and existing methods on different datasets show that the proposed method outperforms the existing methods in terms of classification rate. [ABSTRACT FROM AUTHOR]

Facial age estimation is promising for a wide range of applications including security access control, biometrics, and human–computer interaction. Current label distribution learning-based age estimation methods usually assume a prior probability distribution to handle the correlation among adjacent ages, and Gaussian distribution is the most widely used one. However, the Gaussian distribution is symmetrical, it does not conform to the diversified characteristic of age processing. In this paper, we propose an age encoding method called ALD (asymmetrical label distribution) by fusing the apparent bimodal distributions and chronological single distribution so that much more robust age label distribution can be found. Then, a lightweight multi-task learning network is designed to perform label distribution learning and regression learning for both global estimation and stagewise estimation. Unlike traditional cascade networks of label distribution learning, the parallel structure of multi-task is able to reduce the error propagation from predictive distribution to regression. Extensive experimental analyses on four benchmark datasets demonstrate the superior performance of the proposed method. [ABSTRACT FROM AUTHOR]

In this work we explore the use of structured-light imaging for face analysis. Towards this and due to lack of a publicly available structured-light face dataset, we (a) firstly generate a synthetic structured-light face dataset constructed based on the RGB-dataset London Face and the RGB-D dataset Bosphorus 3D Face. We then (b) propose a conditional adversarial network for depth map estimation from generated synthetic data. Associated quantitative and qualitative results suggest the efficiency of the proposed depth estimation technique. Further, we (c) study the estimation of gender and age directly from (i) structured-light, (ii) binarized structured-light, as well as (iii) estimated depth maps from structured-light. In this context we (d) study the impact of different subject-to-camera distances, as well as pose-variations. Finally, we (e) validate the proposed gender and age models that we train on synthetic data on a small set of real data, which we acquire. While these are early results, our findings clearly indicate the suitability of structured-light based approaches in facial analysis. [ABSTRACT FROM AUTHOR]

Age-at-death estimation is of great relevance for the identification of unknown deceased individuals. In skeletonised corpses, teeth and bones are theoretically available for age estimation, but in many cases, only single bones or even only bone fragments are available for examination. In these cases, conventional morphological methods may not be applicable, and the application of molecular methods may be considered. Protein-based molecular methods based on the D-aspartic acid (D-Asp) or pentosidine (Pen) content have already been successfully applied to bone samples. However, the impact of the analysed type of bone has not yet been systematically investigated, and it is still unclear whether data from samples of one skeletal region (e.g. skull) can also be used for age estimation for samples of other regions (e.g. femur). To address this question, D-Asp and Pen were analysed in bone samples from three skeletal regions (skull, clavicle, and rib), each from the same individual. Differences between the bone types were tested by t-test, and correlation coefficients (ρ) were calculated according to Spearman. In all types of bone, an age-dependent accumulation of D-Asp and Pen was observed. However, both parameters (D-Asp and Pen) exhibited significant differences between bone samples from different anatomical regions. These differences can be explained by differences in structure and metabolism in the examined bone types and have to be addressed in age estimation based on D-Asp and Pen. In future studies, bone type-specific training and test data have to be collected, and bone type-specific models have to be established. [ABSTRACT FROM AUTHOR]

Most existing state-of-the-art face aging models primarily focus on an adult or long-span aging and modeling age transformation in the image domain. This work proposes a child and adult face aging framework that captures more texture and shape information using attention with a wavelet-transformation-based generative adversarial network in the frequency domain. To facilitate child and adult age synthesis, we adopt a wavelet-based multi-scale patch discriminator, which increases the stability of model training and captures local texture details of the child and adult faces. Moreover, we introduce a modified convolutional block attention module, emphasizing only facial regions related to a target attribute and preserving the attribute-excluding details. Our new objective function, modified attention generator, and wavelet multi-scale patch discrimination has shown qualitative and quantitative improvements over the state-of-the-art approaches in terms of face recognition and age estimation on benchmarked children and adult datasets. [ABSTRACT FROM AUTHOR]

Background: Estimating age is essential in both the analysis of human skeletal remains and assessing live persons. The third molar develops over a longer period and is hence used in age estimation for subadults. Since dental age correlates with chronological age better than other growth markers, this study aims to assess the reliability of dental age assessed using the University of Texas (UT) age estimation method and modified Cameriere's method. Methods: It is a retrospective cross-sectional study in which the development and maturation of mandibular third molars were examined in 600 orthopantomograms (264 males and 336 females) of South Indian individuals (16–23 years). Dental age was estimated by using an Indian-specific formula based on maturity index value and the UT-age estimation software program. The results were evaluated using the Student's t-test for both methods and Pearson's correlation test to compare chronological age with estimated dental age. Results: Positive correlation was noted between chronological age and estimated dental age for males, females, and the total sample with highly statistically significant differences (p = 0.000). Modified Cameriere's method underestimated dental age in samples ranging from less than 1 year to more than 2 years. UT-age estimation method underestimated age in samples above 20 years and overestimated age in samples below 20 years. The predictive classification of utilizing the maturity index was 79.17% accurate. Conclusions: Dental age was negligibly over and underestimated in UT software method whereas it was overestimated in the modified Cameriere's method. To evaluate the reliability of these two methods, studies with larger sample sizes and population-specific data sets should be performed. [ABSTRACT FROM AUTHOR]

Gender classification and age estimation are tasks in which humans excel. If gender and age of human can be recognized automatically from images, it will be very helpful in many applications such as intelligent surveillance, micromarketing, etc. We propose a framework for gender and age classification through gait analysis. Gait-based recognition is a feasible approach as the gait of human subject can still be perceived at a long distance. The spatio-temporal gait features are concisely represented as Gait Energy Image (GEI), which is then input to a tree structure convolutional neural network (CNN). We train and test the first model on a single-view gait dataset. Based on the tree structure CNN framework, we propose a larger model for gender and age classification with the multi-view gait dataset. Our models can achieve gender classification accuracy of 97.42% and 99.11% on single-view gait and multi-view gait respectively. We then use our model to perform age group estimation and binary (young and elder groups) classification. Also, our models can achieve the best performance in specific age estimation in terms of various numerical measures than various recently proposed methods. [ABSTRACT FROM AUTHOR]

Introduction of large training datasets was essential for the recent advancement and success of deep learning methods. Due to the difficulties related to biometric data collection, facial image datasets with biometric trait labels are scarce and usually limited in terms of size and sample diversity. Web-scraping approaches for automatic data collection can produce large amounts of weakly labeled and noisy data. This work is focused on picking out the bad apples from web-scraped facial datasets by automatically removing erroneous samples that impair their usability. The unsupervised facial biometric data filtering method presented in this work greatly reduces label noise levels in web-scraped facial biometric data. Experiments on two large state-of-the-art web-scraped datasets demonstrate the effectiveness of the proposed method with respect to real and apparent age estimation based on five different age estimation methods. Furthermore, we apply the proposed method, together with a newly devised strategy for merging multiple datasets, to data collected from three major web-based data sources (i.e., IMDb, Wikipedia, Google) and derive the new Biometrically Filtered Famous Figure Dataset or B3FD. The proposed dataset, which is made publicly available, enables considerable performance gains for all tested age estimation methods and age estimation tasks. This work highlights the importance of training data quality compared to data quantity and selection of the estimation method. [ABSTRACT FROM AUTHOR]

Facial age and gender recognition have vital applications as consumer profile prediction, social media advertisement, human-computer interaction, image retrieval system, demographic profiling, customized advertisement systems, security and surveillance. This paper presents a study on Single Attribute (Attribute: either Gender or Age) and Multi-Attribute (both Gender and Age) prediction model. We present a review for facial age estimation and gender classification methods based on conventional as well as deep learning approaches developed so far with analysis of their pros, cons and insights for future research. Moreover, this study also enlists the databases used for benchmarking results with their properties for both constrained and unconstrained environment. [ABSTRACT FROM AUTHOR]

Age estimation from face images can be profitably employed in several applications, ranging from digital signage to social robotics, from business intelligence to access control. Only in recent years, the advent of deep learning allowed for the design of extremely accurate methods based on convolutional neural networks (CNNs) that achieve a remarkable performance in various face analysis tasks. However, these networks are not always applicable in real scenarios, due to both time and resource constraints that the most accurate approaches often do not meet. Moreover, in case of age estimation, there is the lack of a large and reliably annotated dataset for training deep neural networks. Within this context, we propose in this paper an effective training procedure of CNNs for age estimation based on knowledge distillation, able to allow smaller and simpler "student" models to be trained to match the predictions of a larger "teacher" model. We experimentally show that such student models are able to almost reach the performance of the teacher, obtaining high accuracy over the LFW+, LAP 2016 and Adience datasets, but being up to 15 times faster. Furthermore, we evaluate the performance of the student models in the presence of image corruptions, and we demonstrate that some of them are even more resilient to these corruptions than the teacher model. [ABSTRACT FROM AUTHOR]

Background: This study was aimed at establishing age estimates based on distal root development of the mandibular third molar for Ugandans aged 10–22 years. This was a cross-sectional study using orthopantomograms (OPGs) of 671 patients attending the Mulago Hospital Dental Clinic. The patients' chronological age and sex were obtained from either their national identity cards or birth certificates (females; n = 326, 48.6%). Third molar root development was assessed using Demirjian, Goldstein, and Tanner (DGT), modified Demirjian by Solari, Moorrees, Fanning, and Hunt (MFH), and Haavikko methods. Age was summarized using means/standard deviation (SD), medians, and lower and upper quartiles. Sex differences were assessed using Student's t-test. Results: Crown completion (stage D) and root initiation (stage Ri) were observed at 12.6 years for females and 13.5 years for males (P = 0.02), while complete apex closure occurred at 19.8 for females and 20.1 for males (P = 0.3). There were statistically significant differences in Demirjian root stages E, F, and G and MFH and Haavikko stages Ri, R1/4, and R1/2 between the sexes (P < 0.05). The difference in the mean age of root development between females and males ranged between 0.9 year at DGT/MFH root stages D and Ri (13.5–12.6) and 1.4 years at Solari, MFH, and Haavikko root stages F, R1/4, and R1/2 (16.3–14.9, 17.1–15.7). No differences were observed between the right and left mandibular molars. Conclusions: This study provides age reference standards based on third molar root development specific to the Ugandan adolescent and young adult population. The findings can be used to formulate contemporary standards and utilized as reference material to assess third molar maturity for forensic purposes. [ABSTRACT FROM AUTHOR]

Next-generation sequencing and single-cell RNA sequencing (scRNA-seq) technologies have advanced rapidly in recent years. scRNA-seq reveals the unique gene expression of each cell type, providing directions for exploring cell heterogeneity, cell type–specific responses to injury/disease, and the mechanisms underlying these processes. The development of sequencing technology and improved sequencing throughput have brought about a revolution in single-cell transcriptome study, bringing great benefits to the fields of medicine and biomedical science. From our perspective, certain issues in forensic medicine may potentially be addressed using single-cell transcriptome studies; however, this powerful technique has not yet attracted sufficient attention in forensic medicine-associated research. Therefore, examining and reviewing the latest developments and applications of single-cell transcriptome studies, we present our views on the future directions of forensic research using this technology, aiming to expand the frontiers of forensic science. [ABSTRACT FROM AUTHOR]

The acetabulum presents as a well-preserved evidence, resistant to taphonomic degradation changes and can thus aid in the age estimation process. A CT-based examination of the acetabulum can further help simplify the process of age estimation by overcoming the time-consuming process of maceration and by doing away with the interference resulting from tissue remnants. The aim of the present study was to evaluate the role of the acetabulum for age estimation in an Indian population through a CT-based examination, using principal component analysis and regression models. CT images of 400 individuals aged 10 years and above were evaluated according to the features defined in the San-Millán-Rissech method of age estimation. Five of the seven morphological features defined by San-Millán-Rissech were appreciable on CT scans, and, to enable further statistical analysis, a cumulative score was computed using these five features. A significant correlation of 0.835 and 0.830 for the right and left acetabulum, respectively, was obtained between computed cumulative scores and chronological age of individuals. No significant sex differences were observed in the scoring of different age-related morphological changes. Regression models were generated using individual features and cumulative scores. Regression models derived using the cumulative score yielded inaccuracy values of 9.67 years for the right acetabulum and 9.15 years for the left acetabulum. Inaccuracy and bias values were computed for each individual feature, as well as for each decade, using mean point ages established within the original study. Amongst the various features, acetabular rim porosity was seen to have the lowest values of inaccuracy (11.50 years) and bias (2.32 years) and activity on outer edge of acetabular fossa the highest (inaccuracy and bias values of 22.36 years and 21.50 years, respectively). Taking into consideration this differential contribution towards age estimation, weighted coefficients and mean point ages for different morphological features were determined using principal component analysis. Subsequently, summary age models were generated from the obtained weighted coefficients and mean age values. Summary age models derived in the present study yield lower estimates of inaccuracy of 7.60 years for the right acetabulum and 7.82 years for the left acetabulum. While regression models derived in the present study allow for age estimation using even a single appreciable feature, summary age models take into account the contribution of each feature and generate more accurate estimates of age. Both statistical computations yield reduced error rates and thus can render greater applicability to the acetabulum in forensic age estimation. [ABSTRACT FROM AUTHOR]

Although putting on a mask over our nose and mouth is a simple but powerful way to protect ourselves and others during a pandemic, face masks may interfere with how we perceive and recognize one another, and hence, may have far-reaching impacts on communication and social interactions. To date, it remains relatively unknown the extent to which wearing a face mask that conceals the bottom part of the face affects the extraction of different facial information. To address this question, we compared young adults' performance between masked and unmasked faces in four different tasks: (1) emotion recognition task, (2) famous face recognition and naming test, (3) age estimation task, and (4) gender classification task. Results revealed that the presence of face mask has a negative impact on famous face recognition and emotion recognition, but to a smaller extent on age estimation and gender classification tasks. More interestingly, we observed a female advantage in the famous face recognition and emotion recognition tasks and a female own-gender bias in gender categorisation and age estimation tasks. Overall, these findings allude to the lack of malleability of the adulthood face recognition and perceptual systems. [ABSTRACT FROM AUTHOR]

To investigate the potential of computed tomography (CT) images of median palatine suture (MP) for adult age estimation in the Northern and Southwestern Chinese populations. A total of 1110 cranial CT scans from individuals aged 10–79 years, including 557 northern Chinese and 553 southwestern Chinese, were collected for analysis. After volume reformation and multiplanar reconstruction, a total of 20 slices of median palatine suture were selected from each individual. The closure of sutures was analyzed into four stages, and the cumulative scores of 20 slices were recorded as the suture closure score (SCS). The correlations between SCS and age were compared among the two Chinese populations residing in diverse geographic regions. Regression models were established for age estimation. The estimation accuracy was evaluated based on the test set. The mean absolute error (MAE) and the correlation between predicted age and chronological age were calculated to evaluate estimation accuracy. The SCS of MP exhibited a significant correlation with age (0.613, northern male; 0.678, southwestern male; 0.730, northern female; 0.704, Southwestern female; 0.662, total). Furthermore, there were statistically significant differences in SCS among different regions and sex groups (p < 0.001). The cubic regression model had the highest R2 value in all subjects, especially among Northern females and Southwestern males, while the power and quadratic regression models showed the highest R2 value in Northern males and Southwestern females, respectively. In the test set, the Northern cohort demonstrated a lower MAE (9.06 ± 7.32 years, males; 9.17 ± 5.28 years, females) compared to the Southwestern cohort (9.19 ± 7.49 years, male; 10.61 ± 6.83 years, female). Additionally, it was observed that males exhibited a lower MAE than females in both regional groups. This study demonstrated the potential utility of CT images of the MP for age estimation in Chinese populations, emphasizing the significance of incorporating regional and sex factors within this context. [ABSTRACT FROM AUTHOR]

The identification of human fire victims is a challenging task in forensic medicine. The heat-induced alterations of biological tissues can make the conventional anthropological analyses difficult. Even if the DNA profile of the victim is achieved, it is possible that no match can be found in a forensic DNA database, thus hindering positive identification. In such cases, any information useful to nail down a possible identity should be collected, such as DNA methylation analysis which could provide useful investigative leads. In the present study, five age-related epigenetic markers (ELOVL2, FHL2, KLF14, C1orf132, and TRIM59) were initially analysed in blood samples of 72 living Italian individuals of known age, using a Single Base Extension (SBE) assay. An age prediction model was built by multiple linear regression including all the markers (Mean Absolute Error, MAE: 3.15 years). This model was tested on 29 blood samples collected during autopsies from burnt human remains, already identified through DNA analysis, providing a MAE of 6.92 years. The model allowed a correct prediction in 79.3% of the cases (95% prediction interval), while six cases were associated with inaccurate predictions (min-max prediction error: 9.8–37.3 years). Among the different sample variables considered to explain these results, only the DNA degradation index was a relevant factor affecting the reliability of the predictions. In conclusion, the SBE typing of blood from burnt remains proved to be a reliable tool to estimate chronological age of most of the samples, also in consideration of its cost-effectiveness and the availability of CE sequencers in every forensic genetics laboratory. [ABSTRACT FROM AUTHOR]

Age-at-death estimation is an important issue in forensic medicine and anthropology. Initially, methods relied on morphological criteria, but with the advancement of radiology, new techniques such as morphological studies on multi-slice computed tomography (CT) reconstructions have emerged. Recent studies have shown promising results by investigating the correlation between age and bone mineral density (BMD). However, there is currently a lack of data on post-mortem CTs (PMCT) involving decomposed bodies, and limited information exists regarding changes in Hounsfield Units measurement in a post-mortem context. In light of these gaps, our study aimed to examine the relationship between age at death and pubic and ilium BMD using a sample of forensic bodies. We also aimed to determine whether post-mortem processes, such as putrefaction, could interfere with this correlation. Our retrospective analysis encompassed 637 PMCTs conducted before medicolegal autopsies at Tours University Hospital. Utilizing simple and multiple linear regressions, we investigated the correlation between age and pubic and ilium BMD, as well as the relationship between BMD and the radiologic alteration index (RAI), a scale employed to quantify the degree of putrefaction. Our findings indicate promising outcomes in age-at-death estimation using pubic and/or ilium BMD for bodies exhibiting no or moderate decomposition (RAI < 80), particularly among individuals under 40 years old. However, for highly decomposed corpses (RAI ≥ 80), the presence of gas infiltration significantly influences the BMD of both the ilium and pubis. Consequently, we advocate for the incorporation of the RAI score into the age estimation equation to enhance the accuracy of our results in such cases. Further investigation involving a larger cohort of decomposed bodies could facilitate refinement and validation of our method within this specific population. [ABSTRACT FROM AUTHOR]

Necrophagous flies, particularly blowflies, serve as vital indicators in forensic entomology and ecological studies, contributing to minimum postmortem interval estimations and environmental monitoring. The study investigates variations in the predominant cuticular hydrocarbons (CHCs) viz. n-C25, n-C27, n-C28, and n-C29 of empty puparia of Calliphora vicina Robineau-Desvoidy, 1830, (Diptera: Calliphoridae) across diverse environmental conditions, including burial, above-ground and indoor settings, over 90 days. Notable trends include a significant decrease in n-C25 concentrations in buried and above-ground conditions over time, while n-C27 concentrations decline in buried and above-ground conditions but remain stable indoors. Burial conditions show significant declines in n-C27 and n-C29 concentrations over time, indicating environmental influences. Conversely, above-ground conditions exhibit uniform declines in all hydrocarbons. Indoor conditions remain relatively stable, with weak correlations between weathering time and CHC concentrations. Additionally, machine learning techniques, specifically Extreme Gradient Boosting (XGBoost), are employed for age estimation of empty puparia, yielding accurate predictions across different outdoor and indoor conditions. These findings highlight the subtle responses of CHC profiles to environmental stimuli, underscoring the importance of considering environmental factors in forensic entomology and ecological research. The study advances the understanding of insect remnant degradation processes and their forensic implications. Furthermore, integrating machine learning with entomological expertise offers standardized methodologies for age determination, enhancing the reliability of entomological evidence in legal contexts and paving the way for future research and development. [ABSTRACT FROM AUTHOR]

Background: This study is conducted to estimate age and sex from chest radiographs. The aim of this study was to determine (I) whether costal cartilage calcification pattern help in estimating sex in North Indian sample and (ii) whether there is any relation between age and costal cartilage calcification. Results: The statistical probability of estimating peripheral pattern in male was 99.3%, and for females, it was 100% for central type of calcification. The minimum age where lower costal calcification was present was 22-year-old female and 21 years old male. The degree of calcification and age showed positive correlation; similarly, the value of spearman's rho showed significant result (for whole sample rs = 0.911, p < 0.01 (for male subjects, it was rs = 0.921, p < 0.01; for females, it was rs = 0.905, p < 0.01)). Conclusions: The degree of calcification is useful in estimating age groups and becomes more determined with advancing age. Prediction of sex by using radiological method gives the advantages of simplicity, inexpensiveness, speed, and high accuracy. This method for age and sex estimation will play a useful role in screening test and in cases where the thoracic part of the body is found like dismembered body, putrefied dead remains, and unidentified bodies. [ABSTRACT FROM AUTHOR]