Biology subjects

Montesinos, P.

Publications and source records attributed to Montesinos, P..

3 recordsLinked to original sources

bioRxiv2025

Precon_all: A species-agnostic automated pipeline for non-human cortical surface reconstruction

Cortical surface reconstruction has changed how we study brain morphology and geometry. However, extending these methods to non-human species has been limited by the lack of standardized pipelines, anatomical templates, and variability in imaging protocols. To address these challenges, we present Precon_all, an open-source, species-agnostic pipeline that automates cortical surface reconstruction for non-human neuroimaging. It runs reliably across a wide range of anatomical structures and imaging conditions and has been successfully applied to datasets from primates, carnivores, and artiodactyls. Its modular framework mirrors human neuroimaging workflows, supports manual quality control, and produces outputs compatible with FreeSurfer and Connectome Workbench. In doing so, it substantially reduces technical barriers to non-human neuroimaging. As data-sharing initiatives continue to expand access to non-human imaging datasets, Precon_all provides a scalable and standardized solution that supports the broader adoption of surface-based methods for studying cortical evolution through comparative neuroscience.

neuroscience↗

bioRxiv2022

Identification of leukemia-associated immunophenotypes by database-guided flow cytometry provides a highly sensitive and reproduciblestrategy for the study of measurable residual disease in acutemyeloblastic leukemia

BackgroundMultiparametric Flow Cytometry (MFC) is an essential tool to study the involved cell lineages, the aberrant differentiation/maturation patterns and the expression of aberrant antigens in acute myeloid leukemia (AML). The characterization of leukemia-associated immunophenotypes (LAIPs) at the moment of diagnosis is critical to establish reproducible strategies for the study of measurable residual disease using MFC (MFC-MRD). MethodsIn this study, we identified and characterized LAIPs by comparing the leukemic populations of 145 AML patients, using the EuroFlow AML/ MDS MFC panel, with 6 databases of normal myeloid progenitors (MPCs). Principal component analysis was used to identify and characterize the LAIPs, which were then used to generate individual profiles for MFC-MRD monitoring. Furthermore, we investigated the relationship between the expression patterns of LAIPs and the different subtypes of AML. The MFC-MRD study was performed by identifying residual AML populations that matched with the LAIPs at diagnosis. To further validate this approach, the presence of MRD was also assessed by qPCR (qPCR-MRD). Finally, we studied the association between MFC-MRD and progression-free survival (PFS). ResultsThe strategy used in this study allowed us to describe more than 300 different LAIPs and facilitated the association of specific phenotypes with certain subtypes of AML. The MFC-MRD monitoring based on LAIPs with good/strong specificity was applicable to virtually all patients and showed a good correlation with qPCR-MRD and PFS. ConclusionsThe described methodology provides an objective method to identify and characterize LAIPs. Furthermore, it provides a theoretical basis to develop highly sensitive MFC-MRD strategies.

cancer biology↗

bioRxiv2020

A White Matter Atlas and Common Connectivity Space Facilitate the Pig as a Translational Model in Neuroscience

Neuroimagings capability to quickly and rapidly phenotype the cortical organization of the whole brain brings with it the possibility to extend our understanding of cortical organization across the mammalian lineage. However, neuroimaging has thus far generally limited itself to a small number of species, with most animal studies being performed in either rodents or Non-Human Primates. Here we perform a first pass characterization of an animal which has recently seen its stock rise in the neuroscience community with the development of new models of neurological disease; the domestic pig. Characterizing the structural connectome of the pig, we create a white matter atlas, and an anatomical template which we use to build a horizontal translation between the pig and human based on a connectivity blueprint approach. We find that conserved trends of structural connectivity across species enabled spatial prediction of regions of interest between the pig and human, showing the potential horizontal translations have as a tool to assess the translational validity of porcine models of neurological disease. Releasing the anatomical template, white matter atlas, and connectivity blueprints, we hope to ease and promote the acceptance of the pig as an alternative large-animal model by the neuroimaging community.

neuroscience↗