Notice bibliographique
Résumé
For the past century, the nervous system has been divided into active and passive elements. The active elements, the neurons, have drawn the lion's share of attention from researchers. Our understanding of how they operate, their connections and how they remember information is reasonably (albeit not fully) well developed. By contrast, we know relatively little about the ‘passive’ elements, the glia. Although first evident in early drawings by Ramon y Cajal, glia have largely evaded the attention of researchers. Apart from studies suggesting roles for them as supporting elements, little was known about glia until about 20 years ago when reports began ascribing various roles for these cells in regulating neuronal excitability and controlling synaptic strength. Since these seminal papers, interest in ‘gliobiology’ has assuredly increased. In the current issue, a number of young investigators who have made seminal findings on glia in the nervous system offer an update on the latest findings. Included among these are updates on the role of glia in the control of cerebrovasculature. Anusha Mishra provides a review of the role of astrocytes in balancing energy demands of neurons with the availability of oxygen and nutrients (Mishra, 2017). Since many of the functional signals in human imaging rely on changes in blood flow, changes in astrocyte function may antecede diagnosis of brain dysfunction based on functional imaging approaches. Nicola Allen and colleagues examine the role of astrocytes in regulating synapses (Blanco-Suárez et al. 2017). Beginning with their role in synaptogenesis and then extending through physiological regulation to a variety of disorders, they provide a detailed and mechanistic overview of astrocyte–synapse function. One of these disorders, epilepsy, is the focus of a review by Christian Henneberger who explains how long-term dysfunction of distinct astrocyte processes such as potassium buffering, gap junction coupling and metabolism may contribute to the pathophysiology of epilepsy (Henneberger, 2017). In addition to astrocytes, the microglia have been the focus of studies examining their role in pathological processes such as inflammation, and also as the brain's resident ‘gardeners’ that prune synaptic contacts and maintain appropriate neuronal function. Marie-Eve Tremblay and colleagues highlight recent work that showcases our emerging understanding of the key roles played by these cells in brain development, plasticity and cognition (Tay et al. 2017). In addition, they propose a number of important implications for microglia dysfunction in the pathogenesis of multiple brain diseases. Glial cells also play critical roles in the gut. Vladimir Grubišić and Brian Gulbransen highlight many of these in their overview of glia in the enteric nervous system (Grubišić & Gulbransen, 2017). They summarize findings on the role of glia in a diversity of gut functions ranging from motility to epithelial barrier function to inflammation. Understanding the key signalling pathways may provide important targets for therapeutic intervention in gut pathophysiology. This renewed interest in glia is long overdue. One of the reasons for the current surge may be the availability of new tools that allow unprecedented access to the nervous system. These include high resolution imaging tools that, when combined with fluorescent biological reporters, allow investigators a peek into the brain of awake, behaving animals. With the widespread adoption of genetic tools that allow for cell-targeted manipulations to causally link glial function to nervous system physiology, we are now at the cusp of making groundbreaking discoveries regarding the role of these non-neuronal entities in the nervous system. The authors who have contributed these reviews will play a major role in leading this charge and training the next generation of glio-scientists who begin to change our view of how the nervous system works.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,007 |
| Communication savante | 0,008 | 0,016 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,008 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,006 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».