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Identification of Antigens Recognized by Murine Intestinal IgAs by a Gel-Independent Immunoproteomic Approach.

J Proteome Res

January 2025

Departamento de Microbiología y Parasitología, Facultad de Farmacia, Universidad Complutense de Madrid, Plaza de Ramón y Cajal s/n, 28040 Madrid, Spain.

As part of the intestinal microbiota, can elicit a humoral response in the gastrointestinal tract (GIT) that is mainly directed toward hyphal antigens. This response has been implicated in controlling the invasive form of the fungus and maintaining the yeast as an innocuous commensal. However, the specific targets of this response are still unknown.

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Cerebral microbleeds (CMBs) are small, hypointense hemosiderin deposits in the brain measuring 2-10 mm in diameter. As one of the important biomarkers of small vessel disease, they have been associated with various neurodegenerative and cerebrovascular diseases. Hence, automated detection, and subsequent extraction of clinically useful metrics (e.

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Background And Purpose: Endovascular thrombectomy (EVT) is the standard for acute ischemic stroke from large vessel occlusion, but post-EVT functional independence varies. Brain atrophy, linked to higher cerebrospinal fluid volume (CSFV), may affect outcomes. Baseline CSFV could predict EVT benefit by assessing brain health.

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Background: The main goal of the study was to find the magnetic resonance imaging (MRI) parameters that optimize contrast between tissue and thermal lesions produced by focused ultrasound (FUS) using T1-weighted (T1-W) and T2-weighted (T2-W) fast spin echo (FSE) sequences.

Methods: FUS sonications were performed in porcine tissue using a single-element FUS transducer of 2.6 MHz in 1.

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Background: Single-subject voxel-based morphometry (VBM) is a powerful technique for reader-independent detection of brain atrophy in structural magnetic resonance imaging (MRI) to support the (differential) diagnosis and staging of neurodegenerative diseases in individual patients. However, VBM is sensitive to the MRI scanner platform and details of the acquisition sequence. To mitigate this limitation, we recently proposed and validated a convolutional neural network (CNN)-based VBM which does not rely on a normative reference database.

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