Biology subjects

Pedraza, S.

Publications and source records attributed to Pedraza, S..

4 recordsLinked to original sources

bioRxiv2026

FGF signaling induces disease-associated oligodendrocyte states and drives myelin pathology

Myelin integrity is essential for normal central nervous system (CNS) function and is disrupted in neuroinflammatory and neurodegenerative disorders, including multiple sclerosis and Alzheimer's disease. In these settings, myelin-forming oligodendrocytes adopt a conserved disease-associated transcriptional state, termed disease-associated oligodendrocytes (DAOs). How DAOs arise, the signals that drive their induction, and whether they actively contribute to pathology remain poorly understood. Here we show that FGF signaling instructs mature oligodendrocytes to enter disease-associated states that are sufficient to trigger myelin pathology. By screening disease-linked secreted factors, we identify FGF1 and FGF2 as potent inducers of a DAO-like state in purified oligodendrocyte cultures, characterized by transcriptional reprogramming and myelin-membrane shedding. In vivo, activating oligodendrocyte FGF signaling is sufficient to elicit DAO programs and myelin disruption, whereas inhibiting FGF signaling suppresses DAO induction in a mouse model of multiple sclerosis. Finally, analysis of post-mortem multiple sclerosis tissue reveals a concordant DAO-like state associated with increased engagement of the FGF/FGFR axis. Collectively, these studies define a regulated mechanism of DAO formation linked to myelin disruption and position mature oligodendrocytes as active contributors to myelin pathology in CNS disease.

neuroscience↗

bioRxiv2021

The effect of external stimulation on functional networks in the aging healthy human brain

Understanding the brain changes occurring during aging can provide new insights for developing treatments that alleviate or reverse cognitive decline. Neurostimulation techniques have emerged as potential treatments for brain disorders and to improve cognitive functions. Nevertheless, given the ethical restrictions of neurostimulation approaches, in silico perturbation protocols based on causal whole-brain models are fundamental to gaining a mechanistic understanding of brain dynamics. Furthermore, this strategy could serve as a more specific biomarker relating local activity with global brain dynamics. Here, we used a large resting-state fMRI dataset divided into middle-aged (N=310, aged < 65 years) and older adults (N=310, aged[≥] 65) to characterize brain states in each group as a probabilistic metastable substate (PMS) space, each with a probabilistic occurrence and frequency. Then, we fitted the PMS to a whole-brain model and applied in silico stimulations with different intensities in each node to force transitions from the brain states of the older group to the middle-age group. We found that the precuneus, a brain area belonging to the default mode network and the rich club, was the best stimulation target. These findings might have important implications for designing neurostimulation interventions to revert the effects of aging on whole-brain dynamics.

neuroscience↗

bioRxiv2020

Whole-brain dynamics in aging: disruptions in functional connectivity and the role of the rich club

Normal aging causes disruptions in the brain that can lead to cognitive decline. Resting-state fMRI studies have found significant age-related alterations in functional connectivity across various networks. Nevertheless, most of the studies have focused mainly on static functional connectivity. Studying the dynamics of resting-state brain activity across the whole-brain functional network can provide a better characterization of age-related changes. Here we employed two data-driven whole-brain approaches based on the phase synchronization of blood-oxygen-level-dependent (BOLD) signals to analyze resting-state fMRI data from 620 subjects divided into two groups ( middle-age group (n=310); age range, 50-65 years vs. older group (n=310); age range, 66-91 years). Applying the Intrinsic-Ignition Framework to assess the effect of spontaneous local activation events on local-global integration, we found that the older group showed higher intrinsic ignition across the whole-brain functional network, but lower metastability. Using Leading Eigenvector Dynamics Analysis, we found that the older group showed reduced ability to access a metastable substate that closely overlaps with the so-called rich club. These findings suggest that functional whole-brain dynamics are altered in aging, probably due to a deficiency in a metastable substate that is key for efficient global communication in the brain.

neuroscience↗

bioRxiv2019

Comparison of classification methods for tissue outcome after ischemic stroke

In acute ischemic stroke, identifying brain tissue at high risk of infarction is important for clinical decision-making. This tissue may be identified with suitable classification methods from magnetic resonance imaging (MRI) data. The aim of the present study was to assess comparatively the performance of five popular classification methods (Adaptive Boosting (ADA), Logistic Regression (LR), Artificial Neural Networks (ANN), Random Forest (RF), and Support Vector Machine (SVM)) in identifying tissue at high risk of infarction on human voxel-based brain imaging data. The classification methods were used with eight MRI parameters including diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI) obtained in 55 patients. Sensitivity, specificity, the area under the receiver operating curve (ROC) as well as the area under the precision-recall curve criteria were used to compare the method performances. The methods performed equally in terms of sensitivity and specificity while the results of the area under the ROC were significantly better for ADA, LR, ANN and RF. However, there was no statistically significant difference between the performances of these five classification methods regarding the area under the precision-recall curve, which was the main comparison metric.

neuroscience↗