The morphology of the human cranium allows for reconstructing important information about the identity of an individual, such as age, ancestry, sex, and health status. The estimation of sex from morphology is a key component of the work of physical anthropologists, and in the last decade, the field has witnessed an increase in the use of novel algorithm-based methodologies to tackle the aforementioned task. Nevertheless, several limitations (e.g., small training/testing sample size, training-test data relatedness, limited population inclusiveness, overfitting) have hampered the application of such methods as a standardised procedure in the field. Here, we propose a population-inclusive protocol for estimating sex from a small set of cranial metric traits (10 measurements) based on a neural network architecture trained to maximise the probability of sex attribution and prevent overfitting. The cross-validation returned an accuracy of 86.7% ± 0.02% and log loss of 0.34 ± 0.03. The protocol developed was tested on data unrelated to that of the training and validation phase and returned an estimated accuracy of 84.3% and log loss of 0.348. The model and the related code to use it are made publicly available.

The nasal septum has been postulated to have an intrinsic growth power and act as a pacemaker for facial development, its interactions with local craniofacial structures likely to influence facial anatomy and morphology. Recent studies have begun to investigate the link between nasal septum deviation and facial asymmetry; however, the magnitude and mechanisms of this relation are still unclear. This study aimed to analyse the degree of nasal septum deviation in a sample of infants and children (males and females from 0 to 8 years old) and its correlation with the three-dimensional structure of the facial skeleton. The scope was to test whether septal deviation is linked, and might cause, the development of a more asymmetric face. For this aim, 41 3D landmarks (homologous points) were collected on the nasal septum and cranial surface of 46 specimens extracted from medical CT-scans and were analysed using Geometric Morphometrics, Multiple Linear regressions, Multivariate ANOVAs, and Principal Component Analysis (PCA). Results showed no significant correlation between magnitude of septal deviation and the ontogeny (changes in age) or sex of the sample, but a significant association was found between side of deviation and septal deviation magnitude and frequency. The asymmetric PCA reveals that most of the asymmetry identified is fluctuating, and that changes in the asymmetric morphology of the face are not associated to a specific side of septal deviation. In addition, a series of Multivariate ANOVAs showed that age, sex, and septal deviation have no impact on facial asymmetry, with only age impacting the symmetric development of the facial morphology. When looking at factors impacting the general morphology of the face, age is again the only major driving component, with fluctuating asymmetry and sex only approaching significance. These results could imply a certain degree of dissociation between the mechanisms of facial and septal growth and development; however, an investigation of other key developmental stages in facial morphology is needed to further understand the relation between septal deviation and facial growth.