Variability in human tooth cementum thickness reflecting functional processes

OBJECTIVE

The aim of this study was to investigate the thickness of acellular extrinsic fibre cementum (AEFC) at four root positions of anterior and posterior teeth with special focus on functional aspects. Furthermore, the correlations between cementum thickness and chronological age and sex are investigated.

BACKGROUND

While numerous studies confirm continuous cementum apposition with age, masticatory forces as well as physiological and orthodontically induced tooth movements also have the potential to affect tooth cementum thickness.

MATERIALS AND METHODS

Undecalcified teeth were embedded in resin and transverse-sectioned in the cervical third of the root. Two sections per root were selected, and digital images at four positions were obtained (mesial, distal, oral, and vestibular) using light microscopy. The AEFC thickness of 99 teeth (anterior = 66, posterior = 33, male = 54, female = 45) were measured in both sections. The differences in mean values between root positions and the association of root position variation with tooth type, age, sex, and subject as well as the overall effects of age and sex were analysed using a mixed model.

RESULTS

First incisors and canines showed the greatest mean AFEC thickness, in contrast to premolars which had the lowest values. Differences were found across the four root positions, with a pattern varying considerably between anterior and posterior teeth and between maxilla and mandible in the anterior teeth. An interaction between root position and subject pointed to the existence of an individual component in the variation of AEFC thickness across the four root positions. There was an age trend with an almost linear increase in cementum thickness of 1 μm per year. Overall, females tended to exhibit a significantly lesser AEFC thickness compared to males.

CONCLUSIONS

Distinct differences in the pattern of thickness values across the four root positions in anterior and posterior teeth support the assumption that the AEFC is strongly affected by functional processes. In addition to sex-specific differences and age-related trends, the root position variation of AEFC thickness varies from individual to individual.

Forensic necropsies of cattle: a study of Danish cases from 2010 to 2021 and a guideline for forensic examination of cattle

Forensic post-mortem examinations of animals are carried out on suspicion of violation of European and national legislation. In Denmark, and probably also in other countries with large-scale cattle production, cattle are regularly submitted for forensic assessment. Unfortunately, only few studies of forensic pathology in cattle are available. This paper presents a retrospective study of forensic case files on Danish cattle from January 2010 to December 2021. The case files were characterized with respect to types of lesion, age assessments of lesions and other parameters such as age and sex. A total of 118 forensic case files had been archived and related to 132 cattle (14 weeks-20 years of age; 68% female, 30% male and 2% unknown sex) with 228 lesions. Locomotor disorders constituted the majority of lesions. However, cachexia/emaciation, skin ulcerations and overgrowth of cornual horn were also frequent. Most lesions were chronic (91%) and age assessments for more than 2 weeks were stated for 79% of the lesions. This indicates that in Denmark at least, there is a need to consider how cattle with locomotor disorders are treated in a timely manner in order to avoid prolonged futile treatment and, thereby, suffering. Grossly visible reparative granulation tissue and new bone formation were present in lesions of 1-2 weeks and longer duration. However, all age assessments were stated in broad time intervals due to the lack of scientifically based forensic studies of age assessments of lesions in cattle. Therefore, to improve age assessments in forensic cattle cases, studies concerning the chronology of tissue reparation in cattle are warranted. We also present a guideline for the forensic examination of cattle.

Environmental DNA methylation of Lymnaea stagnalis varies with age and is hypermethylated compared to tissue DNA

Environmental DNA (eDNA) approaches contributing to species identifications are quickly becoming the new norm in biomonitoring and ecosystem assessments. Yet, information such as age and health state of the population, which is vital to species biomonitoring, has not been accessible from eDNA. DNA methylation has the potential to provide such information on the state of a population. Here, we measured the methylation of eDNA along with tissue DNA (tDNA) of Lymnaea stagnalis at four life stages. We demonstrate that eDNA methylation varies with age and allows distinguishing among age classes. Moreover, eDNA was globally hypermethylated in comparison to tDNA. This difference was age-specific and connected to a limited number of eDNA sites. This differential methylation pattern suggests that eDNA release with age is partially regulated through DNA methylation. Our findings help to understand mechanisms involved in eDNA release and shows the potential of eDNA methylation analysis to assess age classes. Such age class assessments will encourage future eDNA studies to assess fundamental processes of population dynamics and functioning in ecology, biodiversity conservation and impact assessments.

Robust Estimation of the Chronological Age of Children and Adolescents Using Tooth Geometry Indicators and POD-GP

Determining the chronological age of children or adolescents is becoming an extremely necessary and important issue. Correct age-assessment methods are especially important in the process of international adoption and in the case of immigrants without valid documents confirming their identity. It is well known that traditional, analog methods widely used in clinical evaluation are burdened with a high error rate and are characterized by low accuracy. On the other hand, new digital approaches appear in medicine more and more often, which allow the increase of the accuracy of these estimates, and thus equip doctors with a tool for reliable estimation of the chronological age of children and adolescents. In this study, the work on a fast and effective metamodel is continued. Metamodels have one great advantage over all other analog and quasidigital methods—if they are well trained, a priori, on a representative set of samples, then in the age-assessment phase, results are obtained in a fraction of a second and with little error (reduced to ±7.5 months). In the here-proposed method, the standard deviation for each estimate is additionally obtained, which allows the assessment of the certainty of each result. In this study, 619 pantomographic photos of 619 patients (296 girls and 323 boys) of different ages were used. In the numerical procedure, on the other hand, a metamodel based on the Proper Orthogonal Decomposition (POD) and Gaussian processes (GP) were utilized. The accuracy of the trained model was up to 95%.

Deep Learning Neural Modelling as a Precise Method in the Assessment of the Chronological Age of Children and Adolescents Using Tooth and Bone Parameters

Dental age is one of the most reliable methods for determining a patient’s age. The timing of teething, the period of tooth replacement, or the degree of tooth attrition is an important diagnostic factor in the assessment of an individual’s developmental age. It is used in orthodontics, pediatric dentistry, endocrinology, forensic medicine, and pathomorphology, but also in scenarios regarding international adoptions and illegal immigrants. The methods used to date are time-consuming and not very precise. For this reason, artificial intelligence methods are increasingly used to estimate the age of a patient. The present work is a continuation of the work of Zaborowicz et al. In the presented research, a set of 21 original indicators was used to create deep neural network models. The aim of this study was to verify the ability to generate a more accurate deep neural network model compared to models produced previously. The quality parameters of the produced models were as follows. The MAE error of the produced models, depending on the learning set used, was between 2.34 and 4.61 months, while the RMSE error was between 5.58 and 7.49 months. The correlation coefficient R² ranged from 0.92 to 0.96.

Tooth and Bone Parameters in the Assessment of the Chronological Age of Children and Adolescents Using Neural Modelling Methods

The analog methods used in the clinical assessment of the patient's chronological age are subjective and characterized by low accuracy. When using those methods, there is a noticeable discrepancy between the chronological age and the age estimated based on relevant scientific studies. Innovations in the field of information technology are increasingly used in medicine, with particular emphasis on artificial intelligence methods. The paper presents research aimed at developing a new, effective methodology for the assessment of the chronological age using modern IT methods. In this paper, a study was conducted to determine the features of pantomographic images that support the determination of metric age, and neural models were produced to support the process of identifying the age of children and adolescents. The whole conducted work was a new methodology of metric age assessment. The result of the conducted study is a set of 21 original indicators necessary for the assessment of the chronological age with the use of computer image analysis and neural modelling, as well as three non-linear models of radial basis function networks (RBF), whose accuracy ranges from 96 to 99%. The result of the research are three neural models that determine the chronological age.

Age Assessment of Youth and Young Adults Using Magnetic Resonance Imaging of the Knee: A Deep Learning Approach

BACKGROUND

Bone age assessment (BAA) is an important tool for diagnosis and in determining the time of treatment in a number of pediatric clinical scenarios, as well as in legal settings where it is used to estimate the chronological age of an individual where valid documents are lacking. Traditional methods for BAA suffer from drawbacks, such as exposing juveniles to radiation, intra- and interrater variability, and the time spent on the assessment. The employment of automated methods such as deep learning and the use of magnetic resonance imaging (MRI) can address these drawbacks and improve the assessment of age.

OBJECTIVE

The aim of this paper is to propose an automated approach for age assessment of youth and young adults in the age range when the length growth ceases and growth zones are closed (14-21 years of age) by employing deep learning using MRI of the knee.

METHODS

This study carried out MRI examinations of the knee of 402 volunteer subjects-221 males (55.0%) and 181 (45.0%) females-aged 14-21 years. The method comprised two convolutional neural network (CNN) models: the first one selected the most informative images of an MRI sequence, concerning age-assessment purposes; these were then used in the second module, which was responsible for the age estimation. Different CNN architectures were tested, both training from scratch and employing transfer learning.

RESULTS

The CNN architecture that provided the best results was GoogLeNet pretrained on the ImageNet database. The proposed method was able to assess the age of male subjects in the range of 14-20.5 years, with a mean absolute error (MAE) of 0.793 years, and of female subjects in the range of 14-19.5 years, with an MAE of 0.988 years. Regarding the classification of minors-with the threshold of 18 years of age-an accuracy of 98.1% for male subjects and 95.0% for female subjects was achieved.

CONCLUSIONS

The proposed method was able to assess the age of youth and young adults from 14 to 20.5 years of age for male subjects and 14 to 19.5 years of age for female subjects in a fully automated manner, without the use of ionizing radiation, addressing the drawbacks of traditional methods.

The age estimation practice related to illegal unaccompanied minors immigration in Italy

The migrants arrived to the Italian coasts in 2016 were 181.436, 18% more than the previous year and 6% more than the highest number ever since. An "unaccompanied minor" (UAM) is a third-country national or a stateless person under eighteen years of age, who arrives on the territory of the Member State unaccompanied by an adult responsible for him/her whether by law or by the practice of the Member State concerned, and for as long as he or she is not effectively taken into the care of such a person; it includes a minor who is left unaccompanied after he/she entered the territory of the Member States. As many as 95.985 UAMs applied for international protection in an EU member country just in 2015, almost four times the number registered in the previous year. The UAMs arrived in Italy were 28.283 in 2016; 94% of them were males, 92% unaccompanied, 8% of them under 15; the 53,6% is 17; the individuals between 16 and 17 are instead the 82%. Many of them (50%), 6561 in 2016, escaped from the sanctuaries, thus avoiding to be formally identified and registered in Italy in the attempt to reach more easily northern Europe countries, since The Dublin Regulations (2003) state that the asylum application should be held in the EU country of entrance or where parents reside. The age assessment procedures can therefore be considered as a relevant task that weighs in on the shoulders of the forensic experts with all the related issues and the coming of age is the important threshold. In the EU laws on asylum, the minors are considered as one of the groups of vulnerable persons towards whom Member States have specific obligations. A proper EU common formal regulation in the matter of age estimation procedures still lacks. According to the Italian legal framework in the matter, a medical examination should have been always performed but a new law completely changed the approach to the procedures of age estimation of the migrant (excluding the criminal cases) with a better adherence to the notions and concepts of vulnerability and psychological and social maturity.

Comparisons between skeletal and dental age assessment in unaccompanied asylum seeking children

BACKGROUND

For children with disputed date of birth, age assessments based on skeletal and dental development are recommended.

AIM

The aim of this retrospective study was to compare and contrast the results of age assessments from these two methods performed on unaccompanied asylum seeking children in Norway. In addition the aim of the analysis was to see if the skeletal age assessment from hand-wrist was operator sensitive.

MATERIALS AND METHODS

Age assessments performed from January 2010 to December 2014 were analysed. Skeletal development of hand-wrist was graded according to Greulich and Pyle (1959). Dental development of the wisdom teeth was scored on orthopantomograms according to Moorrees, Fanning and Hunt (1963) and age assessed from tables published by Liversidge (2008) and Haavikko (1970). In the statistical analysis agreement between the two age assessments was defined according to the asylum seeker's age being assessed to be older or younger than 18 years. The statistical analysis included 3333 boys and 486 girls.

RESULTS

The agreement was 83% for boys and 79% for girls. Approximately 70% of the boys and girls were 18 years or older by both methods. It was more common that the skeletal age was assessed older than 18 years and dental age younger than 18 years for both genders. It could be demonstrated that the age assessment based on skeletal maturation was not operator sensitive.

CONCLUSION

The analyses demonstrate that there is good agreement between the two age assessments, but a method to combine the results would increase the reliability of the age assessments.