Neuroprotective Effect of Inhaled Nitric Oxide on Excitotoxic-Induced Brain Damage in Neonatal Rat

BACKGROUND: Inhaled nitric oxide (iNO) is one of the most promising therapies used in neonates. However, little information is known about its impact on the developing brain submitted to excitotoxic challenge. METHODOLOGY/PRINCIPAL FINDINGS: We investigated here the effect of iNO in a neonatal model of excitotoxic brain lesions. Rat pups and their dams were placed in a chamber containing 20 ppm NO during the first week of life. At postnatal day (P)5, rat pups were submitted to intracranial injection of glutamate agonists. At P10, rat pups exposed to iNO exhibited a significant decrease of lesion size in both the white matter and cortical plate compared to controls. Microglia activation and astrogliosis were found significantly decreased in NO-exposed animals. This neuroprotective effect was associated with a significant decrease of several glutamate receptor subunits expression at P5. iNO was associated with an early (P1) downregulation of pCREB/pAkt expression and induced an increase in pAkt protein concentration in response to excitotoxic challenge (P7). CONCLUSION: This study is the first describe and investigate the neuroprotective effect of iNO in neonatal excitotoxic-induced brain damage. This effect may be mediated through CREB pathway and subsequent modulation of glutamate receptor subunits expression

Annotation d’électroencéphalogrammes (EEG) néonataux pour l’apprentissage supervisé

National audienc

Annotation d'électroencéphalogrammes néonataux pour l'apprentissage supervisé

National audienc

Étude volumétrique des régions cérébrales de nouveau-nés prématurés

National audienc

SLAM – A thin-client for interoperable annotation and biomedical signal handling

International audienceDesigning artificial intelligence tools dedicated to biosignal data (e.g. electroencephalography, EEG) analysis is an increasingly considered topic, motivated by clinical needs. In this context, data annotation is a crucial task, as a prerequisite to supervised machine learning / deep learning approaches. However, annotation is a tedious, time consuming and error-prone task, that has generally to be carried out in a limited time by clinicians. Based on these considerations, we propose a software tool dedicated to a clinical use, that aims to tackle the main difficulties encountered by clinicians. It is designed as a thin-client, that can be run on a web interface without requiring complex technical dependencies. It allows user-friendly, interactive visualization and annotation, while minimizing the manual interactions. It relies on an extensible data exchange format specifically tailored for storing biosignal data, associated metadata and annotations. A semantic web paradigm is considered for metadata modeling, which allows to aggregate independent features from different sources, users, and to valorize information from different experimental protocols. This strategy allows many users to collaborate on the annotation task whereas reducing their coordination effort and optimizing the quality of the annotations

Étude volumétrique des régions cérébrales de nouveau-nés prématurés

National audienc

Étude volumétrique des régions cérébrales de nouveau-nés prématurés

National audienc

SLAM – A thin-client for interoperable annotation and biomedical signal handling

esigning artificial intelligence tools dedicated to biosignal data (e.g. electroencephalography, EEG) analysis is an increasingly considered topic, motivated by clinical needs. In this context, data annotation is a crucial task, as a prerequisite to supervised machine learning / deep learning approaches. However, annotation is a tedious, time consuming and error-prone task, that has generally to be carried out in a limited time by clinicians. Based on these considerations, we propose a software tool dedicated to a clinical use, that aims to tackle the main difficulties encountered by clinicians. It is designed as a thin-client, that can be run on a web interface without requiring complex technical dependencies. It allows user-friendly, interactive visualization and annotation, while minimizing the manual interactions. It relies on an extensible data exchange format specifically tailored for storing biosignal data, associated metadata and annotations. A semantic web paradigm is considered for metadata modeling, which allows to aggregate independent features from different sources, users, and to valorize information from different experimental protocols. This strategy allows many users to collaborate on the annotation task whereas reducing their coordination effort and optimizing the quality of the annotations