Sex determination from the femur in Portuguese populations with classical and machine-learning classifiers.

The assessment of sex is of paramount importance in the establishment of the biological profile of a skeletal individual. Femoral relevance for sex estimation is indisputable, particularly when other exceedingly dimorphic skeletal regions are missing. As such, this study intended to generate population-specific osteometric models for the estimation of sex with the femur and to compare the accuracy of the models obtained through classical and machine-learning classifiers. A set of 15 standard femoral measurements was acquired in a training sample (100 females; 100 males) from the Coimbra Identified Skeletal Collection (University of Coimbra, Portugal) and models for sex classification were produced with logistic regression (LR), linear discriminant analysis (LDA), support vector machines (SVM), and reduce error pruning trees (REPTree). Under cross-validation, univariable sectioning points generated with REPTree correctly estimated sex in 60.0-87.5% of cases (systematic error ranging from 0.0 to 37.0%), while multivariable models correctly classified sex in 84.0-92.5% of cases (bias from 0.0 to 7.0%). All models were assessed in a holdout sample (24 females; 34 males) from the 21st Century Identified Skeletal Collection (University of Coimbra, Portugal), with an allocation accuracy ranging from 56.9 to 86.2% (bias from 4.4 to 67.0%) in the univariable models, and from 84.5 to 89.7% (bias from 3.7 to 23.3%) in the multivariable models. This study makes available a detailed description of sexual dimorphism in femoral linear dimensions in two Portuguese identified skeletal samples, emphasizing the relevance of the femur for the estimation of sex in skeletal remains in diverse conditions of completeness and preservation.

Quantitative determinations and imaging in different structures of buried human bones from the XVIII-XIXth centuries by energy dispersive X-ray fluorescence - Postmortem evaluation.

In this work, a non-commercial triaxial geometry energy dispersive X-ray Fluorescence (EDXRF) setup and a benchtop µ-XRF system were used to identify postmortem contamination in buried bones. For two of the individuals, unusually high concentrations of Cu and Pb, but also Zn (in one individual) were observed. The pigments of the burial shroud coverings have been identified as the source of contamination. Accurate and precise quantitative results were obtained by nondestructive process using fundamental parameters method taking into account the matrix absorption effects. A total of 30 bones from 13 individuals, buried between the mid-XVIIIth to early XIXth centuries, were analyzed to study the elemental composition and elemental distribution. The bones were collected from a church in Almada (Portugal), called Ermida do Espírito Santo, located near the Tagus River and at the sea neighbourhood. The triaxial geometry setup was used to quantify Ca, Fe, Cu, Zn, Br, Sr and Pb of powder pressed bone pellets (n=9 for each bone). Cluster analysis was performed considering the elemental concentrations for the different bones. There was a clear association between some bones regarding Fe, Cu, Zn, Br and Pb content but not a categorization between cortical and trabecular bones. The elemental distribution of Cu, Zn and Pb were assessed by the benchtop µ-analysis, the M4 Tornado, based on a polycapillary system which provides multi-elemental 2D maps. The results showed that contamination was mostly on the surface of the bone confirming that it was related to the burial shroud covering the individuals.

Radiographic fetal osteometry: approach on age estimation for the Portuguese population.

The estimation of gestational age (GA) on fetal remains can be an important forensic issue. Forensic specialists usually use reference tables and regression equations derived from reference collections, which are quite rare in what fetuses are concerned. Since these tools are mostly grounded on ultrasonographic measurements, which are known to differ from real bones measurements or are based on ancient literature, this study aimed the construction of tables and regression equations for the Portuguese population on the basis of diaphyseal bone length measurements (femur, tibia and humerus) of 100 fetuses of known GA, using post-mortem radiographs. There is a strong correlation between the longitudinal length of studied bones and GA; the femur exhibits the strongest correlation (r=0.969; p=0.000), followed by the tibia (r=0.966; p=0.000) and the humerus (r=0.963; p=0.000). Therefore it was possible to obtain regression equations and to build tables with reference values for each of the diaphysis analyzed.