Publications by authors named "Alexandra Abos"

Accurate prediction of a new compound's pharmacokinetic (PK) profile is pivotal for the success of drug discovery programs. An initial assessment of PK in preclinical species and humans is typically performed through allometric scaling and mathematical modeling. These methods use parameters estimated from in vitro or in vivo experiments, which although helpful for an initial estimation, require extensive animal experiments.

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Background And Purpose: Multiple system atrophy(MSA) is a rare adult-onset synucleinopathy that can be divided in two subtypes depending on whether the prevalence of its symptoms is more parkinsonian or cerebellar (MSA-P and MSA-C, respectively). The aim of this work is to investigate the structural MRI changes able to discriminate MSA phenotypes.

Methods: The sample includes 31 MSA patients (15 MSA-C and 16 MSA-P) and 39 healthy controls.

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Probabilistic tractography, in combination with graph theory, has been used to reconstruct the structural whole-brain connectome. Threshold-free network-based statistics (TFNBS) is a useful technique to study structural connectivity in neurodegenerative disorders; however, there are no previous studies using TFNBS in Parkinson's disease (PD) with and without mild cognitive impairment (MCI). Sixty-two PD patients, 27 of whom classified as PD-MCI, and 51 healthy controls (HC) underwent diffusion-weighted 3T magnetic resonance imaging.

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Background: In the absence of verbal communication, it is challenging to infer an individual's sensory and emotional experience. In communicative adults, functional MRI (fMRI) has been used to develop multivariate brain activity signatures, which reliably capture elements of human pain experience. We aimed to translate whole-brain fMRI signatures that encode pain perception in adults to the newborn infant brain, to advance understanding of functional brain development and pain perception in early life.

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We provide T2*-weighted and T1-weighted images acquired on a 3T MRI scanner obtained from 17 transwomen and 29 transmen with gender incongruence; and 22 ciswomen and 19 cismen that identified themselves to the sex assigned at birth. Data from three different techniques that describe global and regional connectivity differences within functional resting-state networks in transwomen and transmen with early-in-life onset gender incongruence are provided: (1) we obtained spatial maps from data-driven independent component analysis using the melodic tool from FSL software; (2) we provide the functional networks interactions of two functional atlases' seeds from a seed-to-seed approach; (3) and global graph-theoretical metrics such as the smallworld organization, and the segregation and integration properties of the networks. Interpretations of the present dataset can be found in the original article, [1].

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Functional brain organization in transgender persons remains unclear. Our aims were to investigate global and regional connectivity differences within functional networks in transwomen and transmen with early-in-life onset gender incongruence; and to test the consistency of two available hypotheses that attempted to explain gender variants: (i) a neurodevelopmental cortical hypothesis that suggests the existence of different brain phenotypes based on structural MRI data and genes polymorphisms of sex hormone receptors; (ii) a functional-based hypothesis in relation to regions involved in the own body perception. T2*-weighted images in a 3-T MRI were obtained from 29 transmen and 17 transwomen as well as 22 cisgender women and 19 cisgender men.

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Recent studies combining diffusion tensor-derived metrics and machine learning have shown promising results in the discrimination of multiple system atrophy (MSA) and Parkinson's disease (PD) patients. This approach has not been tested using more complex methodologies such as probabilistic tractography. The aim of this work is assessing whether the strength of structural connectivity between subcortical structures, measured as the number of streamlines (NOS) derived from tractography, can be used to classify MSA and PD patients at the single-patient level.

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Background: Structural connectivity is a promising methodology to detect patterns of neural network dysfunction in neurodegenerative diseases. This approach has not been tested in progressive supranuclear palsy (PSP).

Objectives: The aim of this study is reconstructing the structural connectome to characterize and detect the pathways of degeneration in PSP patients compared with healthy controls and their correlation with clinical features.

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Neural substrates of empathy are mainly investigated through task-related functional MRI. However, the functional neural mechanisms at rest underlying the empathic response have been poorly studied. We aimed to investigate neuroanatomical and functional substrates of cognitive and affective empathy.

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Background: Three cortical atrophy patterns were previously identified in non-demented Parkinson's disease patients using a data-driven approach based on cortical thickness data: i) parieto-temporal pattern of atrophy with worse cognitive performance (pattern 1), ii) occipital and frontal cortical atrophy with younger disease onset (pattern 2), and iii) non-detectable cortical atrophy (pattern 3). We aimed to investigate the evolution of these three patterns over time.

Methods: Magnetic resonance imaging and neuropsychological assessment were obtained at baseline and follow-up (3.

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In this study we investigate cortical and subcortical gray matter structure in patients with Idiopathic REM-sleep behavior disorder (IRBD), and their relation to cognitive performance. This study includes a sample of 20 patients with polysomnography-confirmed IRBD and 27 healthy controls that underwent neuropsychological and T1-weighted MRI assessment. FreeSurfer was used to estimate cortical thickness, subcortical volumetry (version 5.

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Background: Recent studies using resting-state functional connectivity and machine-learning to distinguish patients with neurodegenerative diseases from other groups of subjects show promising results. This approach has not been tested to discriminate between Parkinson's disease (PD) and multiple system atrophy (MSA) patients.

Objectives: Our first aim is to characterize possible abnormalities in resting-state functional connectivity between the cerebellum and a set of intrinsic-connectivity brain networks and between the cerebellum and different regions of the striatum in PD and MSA.

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Hippocampal subfields have different vulnerability to the degenerative processes related to aging, amnestic mild cognitive impairment (MCI) and Alzheimer's disease (AD), but the temporal evolution in Parkinson's disease (PD) is unknown. The purposes of the current work are to describe regional hippocampal changes over time in a sample of PD patients classified according to their baseline cognitive status and to relate these changes to verbal memory loss. T1-weighted images and verbal memory assessment were obtained at two separate time points (3.

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Gray/white matter contrast (GWC) decreases with aging and has been found to be a useful MRI biomarker in Alzheimer's disease (AD), but its utility in Parkinson's disease (PD) patients has not been investigated. The aims of the study were to test whether GWC is sensitive to aging changes in PD patients, if PD patients differ from healthy controls (HCs) in GWC, and whether the use of GWC data would improve the sensitivity of cortical thickness analyses to differentiate PD patients from controls. Using T1-weighted structural images, we obtained individual cortical thickness and GWC values from a sample of 90 PD patients and 27 controls.

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The description of brain networks as graphs where nodes represent different brain regions and edges represent a measure of connectivity between a pair of nodes is an increasingly used approach in neuroimaging research. The development of powerful methods for edge-wise group-level statistical inference in brain graphs while controlling for multiple-testing associated false-positive rates, however, remains a difficult task. In this study, we use simulated data to assess the properties of threshold-free network-based statistics (TFNBS).

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Introduction: Cortical brain atrophy detectable with MRI in non-demented advanced Parkinson's disease (PD) is well characterized, but its presence in early disease stages is still under debate. We aimed to investigate cortical atrophy patterns in a large sample of early untreated PD patients using a hypothesis-free data-driven approach.

Methods: Seventy-seven de novo PD patients and 50 controls from the Parkinson's Progression Marker Initiative database with T1-weighted images in a 3-tesla Siemens scanner were included in this study.

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Background: Diagnosis of mild cognitive impairment in Parkinson's disease (PD) is relevant because it is a marker for evolution to dementia. However, the selection of suitable tests to evaluate separate cognitive domains in mild cognitive impairment related to PD remains an open question. The current work aims to investigate the neuroanatomical correlates of several visuospatial/visuoperceptual tests using the same sample and a multimodal MRI approach.

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Background: Olfactory dysfunction is present in a large proportion of patients with Parkinson's disease (PD) upon diagnosis. However, its progression over time has been poorly investigated. The few available longitudinal studies lack control groups or MRI data.

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There is growing interest in the potential of neuroimaging to help develop non-invasive biomarkers in neurodegenerative diseases. In this study, connection-wise patterns of functional connectivity were used to distinguish Parkinson's disease patients according to cognitive status using machine learning. Two independent subject samples were assessed with resting-state fMRI.

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Background: Clinical variability in the Parkinson's disease phenotype suggests the existence of disease subtypes. We investigated whether distinct anatomical patterns of atrophy can be identified in Parkinson's disease using a hypothesis-free, data-driven approach based on cortical thickness data.

Methods: T1-weighted 3-tesla MRI and a comprehensive neuropsychological assessment were performed in a sample of 88 nondemented Parkinson's disease patients and 31 healthy controls.

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