READ ME File For Newham et al. (2021) Data repository

Dataset DOI: 10.5258/SOTON/D1722

This dataset supports the publication:
AUTHORS: Elis Newham, Pamela G. Gill, Kate Robson Brown, Neil J. Gostling, Ian J. Corfe, & Philipp Schneider.
TITLE: A robust, semi-automated approach for counting cementum increments imaged with X-ray computed tomography
JOURNAL: PloS one
Abstract of the paper: Cementum, the tissue attaching mammal tooth roots to the periodontal ligament, grows appositionally throughout life, displaying a series of circum-annual incremental features. These have been studied for decades as a direct record of chronological lifespan. The majority of previous studies on cementum have used traditional thin-section histological methods to image and analyse increments. However, several caveats have been raised in terms of studying cementum increments in thin-sections. Firstly, the limited number of thin-sections and the two-dimensional perspective they impart provide an incomplete interpretation of cementum structure, and studies often struggle or fail to overcome complications in increment patterns that complicate or inhibit increment counting. Increments have been repeatedly shown to both split and coalesce, creating accessory increments that can bias increment counts. Secondly, identification and counting of cementum increments using human vision is subjective, and it has led to inaccurate readings in several experiments studying individuals of known age. Here, we have attempted to optimise a recently introduced imaging modality for cementum imaging; X-ray propagation-based phase-contrast imaging (PPCI). X-ray PPCI was performed for a sample of rhesus macaque (Macaca mulatta) lower first molars (n=10) from a laboratory population of known age. A new method for semi-automatic increment counting was then integrated into a purpose-built software package for studying cementum increments. Comparison with data from conventional cementochronology, based on histological examination of tissue sections, confirmed that X-ray PPCI reliably records cementum increments. Validation of the increment counting algorithm suggests that it is robust and provides accurate estimates of increment counts. In summary, we show that our new increment counting method has the potential to overcome caveats of conventional cementochronology approaches, when used to analyse 3D images provided by X-ray PPCI.

This dataset contains:

*8 bit straightened (folder)
Folder containing example 8-bit .tiff files of isolated and straightened cementum synchrotron data created for each specimen.

*Appendix1.m
Matlab script for counting increments in straightened 8Bit CT cementum data (using five cutoffs).

*Appendix2.m
Matlab script for robustness testing of the increment counting algorithm.

*Appdendix3.m
Matlab script fro increment counting using seven cutoffs.

*Appendix4.m
Matlab script fro increment counting using three cutoffs.

*Appendix5.m
Steerable gaussian filter script. Requires downloading and installing the "steerGauss.m" function from "https://uk.mathworks.com/matlabcentral/fileexchange/9645-steerable-gaussian-filters".

Data was collected between 2016 and 2020.

Synchrotron data in "8 bit straightened" folder collected at the TOMCAT beamline of the Swiss Light Source Synchrotron.

All other data was created as part of the Ph.D project of Elis Newham at the University of Southampton, UK.

Data collection was funded by a Natural Environmental Research Council/Engineering and Physical Sciences Research Council doctoral candidateship (UK; grant number NE/R009783/1). Funding was also provided by Ginko Investments Ltd (Bristol, UK). 

"README" file created in March, 2021 and released under "CC BY-NC-ND" licence.