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Da Silva, S. M.

Publications and source records attributed to Da Silva, S. M..

2 recordsLinked to original sources

{micro}CT Scanning Effects on DNA and a Multi-Step Workflow for Archaeological Petrous Bones

The petrous portion of the temporal bone is a key element in human evolutionary studies due to its exceptional preservation of biomolecules and morphological information. However, intensive and often redundant sampling has raised concerns about sustainability and long-term conservation. Here we present the first systematic evaluation of whether micro-Computed Tomography ({micro}CT)--a widely used tool for digital preservation--affects ancient DNA (aDNA) integrity in human petrous bones. We analyzed 93 archaeological samples from Argentina, of which 50 had been scanned using {micro}CT and 43 had not. We compared six molecular parameters, including endogenous content, read length, cytosine deamination patterns and contamination estimates. No statistically significant differences were observed between scanned and unscanned samples across any parameter (Mann-Whitney/Wilcoxon tests, p <0.05). Although mitochondrial contamination was marginally higher in scanned samples (p = 0.051), this was not driven by contamination estimates above the widely accepted 5% threshold for genomic analysis, Moreover, this pattern was not observed when considering nuclear contamination. These results indicate that, under appropriate scanning conditions, {micro}CT imaging does not compromise DNA preservation. Building on this evidence, we propose a sustainable, multi-step workflow that integrates biological profiling, osteobiography, imaging, and compositional pre-screening prior to molecular sampling. This interdisciplinary approach maximizes the scientific information obtained from skeletal collections while minimizing destructive practices, thereby promoting ethical and sustainable research on irreplaceable anthropological remains, and fosters collaboration across research fields.

paleontology↗

Stochastic Regression and Peak Delineation with Flow Cytometry Data

Many modern molecular analysis methods utilize DNA content values as part of the measurement process, and thus, the distribution of genome copies per cell within a population of cells is important. Genome copy distributions can be measured via flow cytometry by thresholding (or "gating") a subset of cells from which estimates of the targeted properties (e.g., genome copy number) can be calculated. This manuscript introduces a new approach that gives separate estimates of signal and noise, the former of which is used for gating and analysis, and the latter is used to quantify uncertainty. In this approach stochastic regression was used to quantify subpopulations of cells that have distinctly different genome copies per cell within a heterogenous population of Escherichia coli (E. coli) cells. By separating the signal and noise components, they can be used independently to evaluate measurement quality across different experimental conditions.

microbiology↗