Person:
Clavero Ibarra, Pedro Luis

Profile Picture

Email Address

person.page.identifierURI

https://academica-e.unavarra.es/handle/2454/50249

Birth Date

Job Title

Last Name

Clavero Ibarra

First Name

Pedro Luis

person.page.departamento

Ciencias de la Salud

person.page.instituteName

ORCID

0000-0002-6873-7063

person.page.observainves

1175488

person.page.upna

812692

Name

Filters

2023 - 20243
Reset filters

Settings

Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    PublicationOpen Access
    Subspace corrected relevance learning with application in neuroimaging
    (Elsevier, 2024) Veen, Rick van; Bari Tamboli, Neha Rajendra; Lövdal, Sofie; Meles, Sanne K.; Renken, Remco J.; Vries, Gert-Jan de; Arnaldi, Dario; Morbelli, Silvia; Clavero Ibarra, Pedro Luis; Obeso, José A.; Rodríguez Oroz, María Cruz; Leenders, Klaus L.; Villmann, Thomas; Biehl, Michael; Ciencias de la Salud; Osasun Zientziak
    In machine learning, data often comes from different sources, but combining them can introduce extraneous variation that affects both generalization and interpretability. For example, we investigate the classification of neurodegenerative diseases using FDG-PET data collected from multiple neuroimaging centers. However, data collected at different centers introduces unwanted variation due to differences in scanners, scanning protocols, and processing methods. To address this issue, we propose a two-step approach to limit the influence of center-dependent variation on the classification of healthy controls and early vs. late-stage Parkinson’s disease patients. First, we train a Generalized Matrix Learning Vector Quantization (GMLVQ) model on healthy control data to identify a “relevance space” that distinguishes between centers. Second, we use this space to construct a correction matrix that restricts a second GMLVQ system’s training on the diagnostic problem. We evaluate the effectiveness of this approach on the real-world multi-center datasets and simulated artificial dataset. Our results demonstrate that the approach produces machine learning systems with reduced bias - being more specific due to eliminating information related to center differences during the training process - and more informative relevance profiles that can be interpreted by medical experts. This method can be adapted to similar problems outside the neuroimaging domain, as long as an appropriate “relevance space” can be identified to construct the correction matrix.
  • Thumbnail Image
    PublicationOpen Access
    Nigrostriatal degeneration determines dynamics of glial inflammatory and phagocytic activity
    (BMC, 2024) Ayerra, Leyre; Abellanas, Miguel Ángel; Basurco, Leyre; Tamayo Uria, Ibon; Conde, Enrique; Tavira, Adriana; Trigo, Amaya; Vidaurre, Clara; Vilas, Amaia; San Martin-Uriz, Patxi; Luquin, Esther; Clavero Ibarra, Pedro Luis; Mengual, Elisa; Aymerich, María Soledad; Ciencias de la Salud; Osasun Zientziak
    Glial cells are key players in the initiation of innate immunity in neurodegeneration. Upon damage, they switch their basal activation state and acquire new functions in a context and time-dependent manner. Since modulation of neuroinflammation is becoming an interesting approach for the treatment of neurodegenerative diseases, it is crucial to understand the specific contribution of these cells to the inflammatory reaction and to select experimental models that recapitulate what occurs in the human disease. Previously, we have characterized a region-specific activation pattern of CD11b(+) cells and astrocytes in the alpha-synuclein overexpression mouse model of Parkinsons disease (PD). In this study we hypothesized that the time and the intensity of dopaminergic neuronal death would promote different glial activation states. Dopaminergic degeneration was induced with two administration regimens of the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), subacute (sMPTP) and chronic (cMPTP). Our results show that in the sMPTP mouse model, the pro-inflammatory phenotype of striatal CD11b(+) cells was counteracted by an anti-inflammatory astrocytic profile. In the midbrain the roles were inverted, CD11b(+) cells exhibited an anti-inflammatory profile and astrocytes were pro-inflammatory. The overall response generated resulted in decreased CD4 T cell infiltration in both regions. Chronic MPTP exposure resulted in a mild and prolonged neuronal degeneration that generated a pro-inflammatory response and increased CD4 T cell infiltration in both regions. At the onset of the neurodegenerative process, microglia and astrocytes cooperated in the removal of dopaminergic terminals. With time, only microglia maintained the phagocytic activity. In the ventral midbrain, astrocytes were the main phagocytic mediators at early stages of degeneration while microglia were the major phagocytic cells in the chronic state. In this scenario, we questioned which activation pattern recapitulates better the features of glial activation in PD. Glial activation in the cMPTP mouse model reflects many pathways of their corresponding counterparts in the human brain with advanced PD. Altogether, our results point toward a context-dependent cooperativity of microglia/myeloid cells and astrocytes in response to neuronal damage and the relevance of selecting the right experimental models for the study of neuroinflammation.
  • Thumbnail Image
    PublicationOpen Access
    Microglia and astrocyte activation is region-dependent in the α-synuclein mouse model of Parkinson's disease
    (Wiley, 2023) Basurco, Leyre; Abellanas, Miguel Ángel; Ayerra, Leyre; Conde, Enrique; Vinueza-Gavilanes, Rodrigo; Luquin, Esther; Vales, Africa; Vilas, Amaia; San Martin-Uriz, Patxi; Tamayo Uria, Ibon; Alonso Roldán, Marta; Hernaez, Mikel; González-Aseguinolaza, Gloria; Clavero Ibarra, Pedro Luis; Mengual, Elisa; Arrasate, Montserrat; Hervás Stubbs, Sandra; Aymerich, María Soledad; Ciencias de la Salud; Osasun Zientziak
    Inflammation is a common feature in neurodegenerative diseases that contributes to neuronal loss. Previously, we demonstrated that the basal inflammatory tone differed between brain regions and, consequently, the reaction generated to a pro-inflammatory stimulus was different. In this study, we assessed the innate immune reaction in the midbrain and in the striatum using an experimental model of Parkinson's disease. An adeno-associated virus serotype 9 expressing the alpha-synuclein and mCherry genes or the mCherry gene was administered into the substantia nigra. Myeloid cells (CD11b(+)) and astrocytes (ACSA2(+)) were purified from the midbrain and striatum for bulk RNA sequencing. In the parkinsonian midbrain, CD11b(+) cells presented a unique anti-inflammatory transcriptomic profile that differed from degenerative microglia signatures described in experimental models for other neurodegenerative conditions. By contrast, striatal CD11b(+) cells showed a pro-inflammatory state and were similar to disease-associated microglia. In the midbrain, a prominent increase of infiltrated monocytes/macrophages was observed and, together with microglia, participated actively in the phagocytosis of dopaminergic neuronal bodies. Although striatal microglia presented a phagocytic transcriptomic profile, morphology and cell density was preserved and no active phagocytosis was detected. Interestingly, astrocytes presented a pro-inflammatory fingerprint in the midbrain and a low number of differentially displayed transcripts in the striatum. During alpha-synuclein-dependent degeneration, microglia and astrocytes experience context-dependent activation states with a different contribution to the inflammatory reaction. Our results point towards the relevance of selecting appropriate cell targets to design neuroprotective strategies aimed to modulate the innate immune system during the active phase of dopaminergic degeneration.