Metric analysis of the patella for sex estimation in a Portuguese sample.

The biological profile estimation is the first step toward positive identification. However, it is not always possible to access a complete and well-preserved skeleton due to postmortem damage and taphonomic changes. As such, there is a need to develop new alternatives to analyze different bones of the human skeleton.

Peopling of the Americas: A new approach to assessing dental morphological variation in Asian and Native American populations.

Objectives: Through biodistance analyses, anthropologists have used dental morphology to elucidate how people moved into and throughout the Americas. Here, we apply a method that focuses on individuals rather than sample frequencies through the application rASUDAS2, based on a naïve Bayes' algorithm.

Materials And Methods: Using the database of C.

DXAGE 2.0 - adult age at death estimation using bone loss in the proximal femur and the second metacarpal.

The accurate age at death assessment of unidentified adult skeletal individuals is a critical research task in forensic anthropology, being a key feature for the determination of biological profiles of individual skeletal remains. We have previously shown that the age-related decrease of bone mineral density (BMD) in the proximal femur could be used to assess age at death in women (Navega et al., J Forensic Sci 63:497-503, 2018).

Adult Skeletal Age-at-Death Estimation through Deep Random Neural Networks: A New Method and Its Computational Analysis.

Age-at-death assessment is a crucial step in the identification process of skeletal human remains. Nonetheless, in adult individuals this task is particularly difficult to achieve with reasonable accuracy due to high variability in the senescence processes. To improve the accuracy of age-at-estimation, in this work we propose a new method based on a multifactorial macroscopic analysis and deep random neural network models.

New data about the 21st Century Identified Skeletal Collection (University of Coimbra, Portugal).

After the publication of the first article in 2014, 21st Century Identified Skeletal Collection, housed in the Laboratory of Forensic Anthropology, Department of Life Sciences at the University of Coimbra, Portugal, has been growing. Currently, the collection is composed of 302 complete adult skeletons of both sexes, which means that in 5 years it has doubled. The collection consists mostly of elderly individuals, with only 12.

Sub-adult aging method selection (SAMS): A decisional tool for selecting and evaluating sub-adult age estimation methods based on standardized methodological parameters.

Objectives: A decisional tool was developed to select sub-adult age estimation methods referenced in a centralized database. Through a freely accessible webpage interface, this tool allows users to evaluate how much the sampling and statistical protocols of these referenced methods comply with methodological recommendations published for building and applying methods in forensic anthropology.

Materials And Methods: 261 publications on sub-adult age estimation were collected.

Application and validation of Diagnose Sexuelle Probabiliste V2 tool in a miscegenated population.

The hip bone (os coxae) is the skeletal element that presents the greatest level of sexual dimorphism. Therefore, methods involving the analysis of the os coxae provide the most accurate sex estimation, and DSP2 (Diagnose Sexuelle Probabiliste v.2) is one of the most accurate tools used in this identification.

A test and analysis of Calce (2012) method for skeletal age-at-death estimation using the acetabulum in a modern skeletal sample.

In forensic anthropology, the age-at-death of an adult individual is one of the most complex parameters of the biological profile to estimate. The present study aims to evaluate the reliability of the Calce (2012) method for the estimation of age-at-death through acetabulum changes in a sample of Portuguese origin. This method consists of the global analysis of acetabular age-related morphology with focus on three specific traits, namely the acetabular groove, the osteophyte development of the acetabular rim, and the apex growth.

Age estimation of adult human remains from hip bones using advanced methods.

The assessment of age-at-death is an important and challenging part of investigations of human skeletal remains. The main objective of the present study was to apply different mathematical approaches in order to reach more accurate and reliable results in age estimation. A multi-ethnic dataset (n=941) of evaluated age-related changes on the pubic symphysis and the auricular surface of the hip bone was used.

DXAGE: A New Method for Age at Death Estimation Based on Femoral Bone Mineral Density and Artificial Neural Networks.

Age at death estimation in adult skeletons is hampered, among others, by the unremarkable correlation of bone estimators with chronological age, implementation of inappropriate statistical techniques, observer error, and skeletal incompleteness or destruction. Therefore, it is beneficial to consider alternative methods to assess age at death in adult skeletons. The decrease in bone mineral density with age was explored to generate a method to assess age at death in human remains.

Luminol chemiluminescence: contribution to postmortem interval determination of skeletonized remains in Portuguese forensic context.

Postmortem interval (PMI) determination is one of the main challenges of forensic anthropology, and there are several referenced methods that consider intrinsic and extrinsic factors to the skeletonized remains. Therefore, there is an important need to develop a precise, economic, easy and reproducible technique, which will operate as a presumptive test. The chemical reaction that occurs in the presence of luminol, chemiluminescence, is used as a work tool to evaluate the PMI.

A method for sex estimation using the proximal femur.

The assessment of sex is crucial to the establishment of a biological profile of an unidentified skeletal individual. The best methods currently available for the sexual diagnosis of human skeletal remains generally rely on the presence of well-preserved pelvic bones, which is not always the case. Postcranial elements, including the femur, have been used to accurately estimate sex in skeletal remains from forensic and bioarcheological settings.

A new forensic collection housed at the University of Coimbra, Portugal: The 21st century identified skeletal collection.

The purpose of this study is to characterize and contextualize the new collection of identified skeletons housed in the Department of Life Sciences at the University of Coimbra, Portugal. The 21st Century Identified Skeletal Collection, which is still being enlarged, is currently composed of 159 complete adult skeletons (age at death range: 29-99 years) of both sexes. The skeletons consist almost exclusively of Portuguese nationals who died between 1995 and 2008.

Sex estimation using the second cervical vertebra: a morphometric analysis in a documented Portuguese skeletal sample.

Biological sex estimation is one of the main parameters required in the construction of a biological profile of an unknown deceased person. In corpses in an advanced state of decomposition, skeletonized or severely mutilated, bone analysis may provide the only way to access biological sex. Although the hip bones are the most dimorphic and useful bones for sex estimation, they are often badly preserved and/or fragmented or may not even be present in some cases.

Sex estimation from the tarsal bones in a Portuguese sample: a machine learning approach.

Sex estimation is extremely important in the analysis of human remains as many of the subsequent biological parameters are sex specific (e.g., age at death, stature, and ancestry).

AncesTrees: ancestry estimation with randomized decision trees.

In forensic anthropology, ancestry estimation is essential in establishing the individual biological profile. The aim of this study is to present a new program--AncesTrees--developed for assessing ancestry based on metric analysis. AncesTrees relies on a machine learning ensemble algorithm, random forest, to classify the human skull.