Dorsal raphe tau pathology disrupts sleep-wake orchestration and sleep architecture in a sex-specific manner.

The accurate estimation of osteological sex in biological anthropology and allied research fields is fundamental for reconstructing demographic and mortality profiles, and quantifying variation between different populations or social groups (Krishan et al. ). It is a vital first step in forensic anthropology when dealing with unidentified skeletal remains. Sex estimates are conventionally compiled from the standardized assessment of multiple skeletal morphological traits that vary in expression between biologically female and biologically male individuals. Traits are scored on a scale from “most female” to “most male” and the overall impression provided by the assessment of all available traits results in a “skeletal” or “osteological sex estimation”. This approach is not, however, an exact science, and no traits are binary. While some traits have high accuracy (e.g., Phenice traits of the pubis (Inskip et al. ; Lovell ; Patriquin et al. ; Ubelaker and Volk )), this can differ between populations and time periods (see Table ). Estimates derived from the combined traits of the skull are demonstrably variable in accuracy, with rates as low as 53.5% (Gupta et al. ), and as high as 96.2% (Lewis and Garvin ). The development of forensic medicine has been key in the production of standardized approaches for sex estimation, with the first approach being developed by Krogman (). This has inspired the production of multiple standards for sex estimation which are regularly applied across the globe, with perhaps the most well‐known being the WEA (), superseded by that outlined by Buikstra and Ubelaker (). However, there has been limited systematic testing of the accuracy of these traits on collections other than those that were used to make the methods, especially on non‐contemporary populations (e.g., archaeological). Most accuracy tests have been performed on the Terry or Hamann–Todd collections, from which most of the methods were originally derived, or on other similar modern collections (see Table ). This can lead to overfitting of the data producing inflated accuracy rates. This is problematic since these methods are used worldwide (Ubelaker and DeGaglia ) and perhaps without consideration of global variation in trait expression. Research in forensic settings has highlighted a great deal of variation between contemporary groups of different ethnicities, demonstrating the need for population specific standards (Gupta et al. ; Krüger et al. ; Patriquin et al. ; Tallman ). Factors influencing expression could derive from secular change, population change, and variation in health and lifestyle, all of which would equally be at play in the past. Without knowing the accuracy of these traits in populations from different time periods, we cannot be sure that the estimation of sex in archaeological individuals is accurate. More targeted testing on archaeological groups is, therefore, needed to ensure the appropriate use of these traits for sex estimation in different populations. Ancient DNA (aDNA) studies using archaeological individuals have become more common and accessible in the past 15 years. Identification of chromosomal pairing for the sex chromosomes using genetic analysis provides evidence for the genetic and, subsequently inferred, biological sex of an individual (Skoglund et al. ). The comparison of genetic sex with estimated osteological sex can, therefore, provide greater insight into the accuracy of the morphological traits of the skeleton used to infer biological sex in archaeological populations. This can be used to validate and improve the accuracy of macroscopic sex estimations. This approach was utilized by Inskip et al. () on 66 adult individuals from thirteenth to sixteenth century Cambridge, United Kingdom. The agreement between genetic and osteological sex using traits of the pelvis was 91.8%, but only 76.7% when using traits of the skull. In a study of a medieval German sample from Lubeck ( = 43), Gupta et al. () found an accuracy of just 53.5% between genetic sex and skull‐based estimates.