Biology subjects

De Benedictis, A.

Publications and source records attributed to De Benedictis, A..

3 recordsLinked to original sources

bioRxiv2025

The end of the American dream: a hard to Swallow reality - How the Barn Swallow (Hirundo rustica) returned from America, a complete mtDNA phylogeny

The barn swallow (Hirundo rustica, H.r.) is one of the most iconic and fascinating migratory birds since ancient times, their philopatry and pair bonding have been the symbol of travellers and lovers throughout history. The barn swallow subspecies complex has been the main focus of many latest papers, focusing mainly on the Eurasian and Levant subspecies (H.r. rustica and H.r. transitiva). The remaining subspecies have either not been studied or few complete mitogenome sequences have been obtained. We present a comprehensive phylogeographic analysis of 580 complete mitochondrial genomes of barn swallows representing all recognized subspecies. We identified 553 unique haplotypes, 166 of which are novel, with high haplotype diversity and notable nucleotide diversity among subspecies. Phylogenetic analysis by maximum parsimony supports a single maternal ancestor and reveals five main haplogroups, confirming and refining prior classifications. A novel, distinct haplogroup (E) was identified for H.r. tytleri, previously classified as a sub-branch of H.r. erythrogaster. The inclusion of 66 hybrid individuals confirmed extensive maternal introgression and revealed multiple cases of mitogenome-subspecies mismatches, notably in savignii, transitiva, and tytleri populations. We further integrated 13 mitogenomes from 12 other Hirundo species, three of which are newly sequenced, to contextualize H. rustica evolution within the genus. Our findings support a southern African origin with subsequent diversification and a northward expansion. This study significantly enhances resolution of barn swallow mitogenomic diversity, revises phylogenetic relationships, identifies new haplogroups, hints at inter-subspecies gene flow and refines coalescent-based divergence times, offering key insights into the evolutionary history and hybridisation patterns of this iconic migratory species.

evolutionary biology↗

bioRxiv2020

Classifyber, a robust streamline-based linear classifier for white matter bundle segmentation

Virtual delineation of white matter bundles in the human brain is of paramount importance for multiple applications, such as pre-surgical planning and connectomics. A substantial body of literature is related to methods that automatically segment bundles from diffusion Magnetic Resonance Imaging (dMRI) data indirectly, by exploiting either the idea of connectivity between regions or the geometry of fiber paths obtained with tractography techniques, or, directly, through the information in volumetric data. Despite the remarkable improvement in automatic segmentation methods over the years, their segmentation quality is not yet satisfactory, especially when dealing with datasets with very diverse characteristics, such as different tracking methods, bundle sizes or data quality. In this work, we propose a novel, supervised streamline-based segmentation method, called Classifyber, which combines information from atlases, connectivity patterns, and the geometry of fiber paths into a simple linear model. With a wide range of experiments on multiple datasets that span from research to clinical domains, we show that Classifyber substantially improves the quality of segmentation as compared to other state-of-the-art methods and, more importantly, that it is robust across very diverse settings. We provide an implementation of the proposed method as open source code, as well as web service.

neuroscience↗

bioRxiv2019

Tractostorm: Rater reproducibility assessment in tractography dissection of the pyramidal tract

Investigative studies of white matter (WM) brain structures using diffusion MRI (dMRI) tractography frequently require manual WM bundle segmentation, often called \"virtual dissection\". Human errors and personal decisions make these manual segmentations hard to reproduce, which have not yet been quantified by the dMRI community. The contribution of this study is to provide the first large-scale, international, multi-center variability assessment of the \"virtual dissection\" of the pyramidal tract (PyT). Eleven (11) experts and thirteen (13) non-experts in neuroanatomy and \"virtual dissection\" were asked to perform 30 PyT segmentation and their results were compared using various voxel-wise and streamline-wise measures. Overall the voxel representation is always more reproducible than streamlines ({approx}70% and {approx}35% overlap respectively) and distances between segmentations are also lower for voxel-wise than streamline-wise measures ([3/4]3mm and [3/4]umm respectively). This needs to be seriously considered before using tract-based measures (e.g. bundle volume versus streamline count) for an analysis. We show and argue that future bundle segmentation protocols need to be designed to be more robust to human subjectivity. Coordinated efforts by the diffusion MRI tractography community are needed to quantify and account for reproducibility of WM bundle extraction techniques in this era of open and collaborative science.

neuroscience↗