Revealing Developmental Transitions in Perinatal and Infant Individuals Through Microanatomical Analysis
Loading...
Official URL
Full text at PDC
Publication date
2025
Advisors (or tutors)
Editors
Journal Title
Journal ISSN
Volume Title
Publisher
John Wiley & Sons
Citation
Moreno, M. M., Doe, D. M., González, N. C., Martínez, D. G., Martín, A. G., & Cambra-Moo, O. (2025). Revealing Developmental Transitions in Perinatal and Infant Individuals Through Microanatomical Analysis. American Journal of Human Biology, 37(7). https://doi.org/10.1002/AJHB.70101
Abstract
Objectives. Identifying signs of birth in perinatal human remains of past populations is challenging due to the lack of direct markers of this event on bones. This research aims to identify distinct events in humeral cross-sections microanatomy related to perinatal development and to integrate the findings into infant mortality trends. Material and Methods. The sample consists of infants (N = 106) ranging from prenatal to 1.5 years, with microanatomical analysis of nine selected individuals. Age-at-death estimation and microanatomical characterization were conducted, combined with quantitative analysis of microanatomical features. Results. Biological age-at-death presents high variability and overlap across prenatal to postnatal stages. Microanatomical analysis reveals a higher percentage of mineralized areas (60%–80%) within the total cross-sectional area in the youngest individuals up to the first neonatal month. Conclusions. Based on the integration of microanatomical analysis in an extensive infant sample, this study highlights the evidence of developmental transitions from prenatal to neonatal stages. These findings suggest that, unlike biological age estimation methods, the full-term period can be identified microanatomically in bone. This provides a valuable approach for analyzing fragmented skeletal remains, secondary deposits, and other funerary or osteological contexts, opening new pathways to understand gestational development and postnatal survival in past populations.
Description
This work was supported by JDC2022-049244-I, (Ministerio de Ciencia, Innovación y Universidades and Next Generation UE) UAM CA4/RSUE/2022-00292 (Ministerio de Universidades, Plan de Recuperación, Transformación y Resiliencia) and FPI-UAM 2017 predoctoral funding. The Laboratorio de Poblaciones del Pasado (LAPP) has been supported by Projects PGC2018-099405-B-100, HAR2017-82755-P, HAR2017-83004-P, HAR2016-78036-P, HAR2016-74846-P (Spanish Government), a grant (ref. 38360) from The Leakey Foundation and SI4/PJI/2024-00104 (Comunidad de Madrid) and by the Ministerio de Ciencia, Innovación y Universidades.












