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Enregistrement W7027326363

Cellular mechanisms of brain-derived neurotrophic factor mediated synapse reorganization following hippocampal injury

2015· dissertation· en· W7027326363 sur OpenAlexfundno aff

Notice bibliographique

RevueeScholarship@McGill (McGill) · 2015
Typedissertation
Langueen
DomaineNeuroscience
ThématiqueNerve injury and regeneration
Établissements canadiensnon disponible
Organismes subventionnairesCanadian Institutes of Health ResearchSavoy FoundationUniversities Space Research AssociationNational Health and Medical Research CouncilNatural Sciences and Engineering Research Council of CanadaMcGill University
Mots-clésSynapseHippocampal formationBrain-derived neurotrophic factorNeurotrophic factorsNeurotrophinCiliary neurotrophic factorNeuromuscular junction
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Brain injury and neurological disorders can adversely impact the way that we communicate with the environment and therefore detrimentally affect quality of life for patients.Synapses, which are important neuronal structures that mediate communication between neurons, can become dysfunctional after brain injury.It is generally thought that synaptic dysfunction underlies the cognitive deficits that patients experience following brain injury and disease.As such, synapses represent an interesting target for therapeutic intervention in order to limit the damage that brain insults have on cognition.In the case of post-traumatic epilepsy and ischemia, both excitatory and inhibitory synapses are remodelled, which can have devastating effects to existing functional neuronal networks.Though there are some theories on how trauma can lead to long-term functional deficits through neurocircuitry reorganization, there is still a paucity of information on the cellular mechanisms underlying synapse remodeling.In this thesis, I studied the role of the neurotrophin, brain-derived neurotrophic factor (BDNF) in synaptic reorganization following hippocampal injury, a brain region which is important for learning and memory.BDNF plays a crucial role in development of both excitatory glutamatergic and inhibitory GABAergic synapses.Interestingly, BDNF is highly upregulated after many different types of brain injury, including stroke and epilepsy.Some neuroscientists believe that this increase in BDNF is an attempt by the brain to ameliorate injury, but may actually revert the central nervous system to a more juvenile and aberrant state thereby provoking further injury.In my thesis I hypothesized that (1) BDNF can downregulate excitatory and inhibitory neurotransmission following ischemia, (2) BDNF mediates axonal reorganization and network hyperexcitability in a model of post-traumatic epilepsy and (3) BDNF-mediated axonal reorganization is due to a misappropriation of activity-dependent transcription of the Bdnf gene.v In order to test my hypotheses, I used organotypic hippocampal slice cultures and subjected them to two well-established in vitro models of hippocampal injury for long-term studies on neuronal networks: (1) oxygen-glucose deprivation, focusing on area CA1, the hippocampal region most susceptible to ischemia and (2) Schaffer collateral lesion, focusing on area CA3, the region where axon sprouting and hyperexcitability occurs in response to Schaffer collateral injury.I then combined confocal microscopy, immunofluorescence, molecular biology and electrophysiology to study synapse function, morphology and signaling.I found that after ischemia to organotypic hippocampal slices, BDNF can downregulate GABAergic synapses structurally and functionally through the high-affinity TrkB receptor.Moreover, I found that proBDNF, the precursor protein of BDNF, can downregulate glutamatergic synapses structurally and functionally through the low-affinity p75 NTR receptor.Accordingly, my findings identify distinct signaling cascades that specifically provoke acute excitatory or inhibitory synapse loss after ischemia.Therefore, these signaling cascades represent putative therapeutic targets for prevention of cognitive deficits following ischemic stroke.I next wanted to determine if BDNF played a role in another type of hippocampal injury such as post-traumatic epilepsy.Using the Schaffer collateral transection model, I found that bdnf mRNA expression is upregulated shortly following a lesion and that scavenging BDNF with TrkB-Fc prevented lesion-induced axonal remodeling and inhibited the formation of a recurrent network.Given that axonal remodelling is a classic hallmark of post-traumatic epilepsy, my data identifies a specific therapeutic pathway that may prevent epileptogenesis in patients following traumatic brain injury.Lastly, in order to better understand the source of this BDNF and also identify other therapeutic targets to prevent injury-induced synaptic reorganization, I tested the involvement of vi methyl CpG binding protein 2 (MeCP2) regulation of activity-dependent transcription of Bdnf on CA3 pyramidal neuron hyperexcitability.I found that MeCP2 became phosphorylated at serine 421, a molecular switch for activating bdnf transcription, shortly following Schaffer collateral lesion.In addition, I found that this injury-induced pMeCP2 upregulation could be prevented by inhibiting Ca 2+ /Calmodulin kinase II (CaMKII).Interestingly, I found that inhibiting CaMKII did not prevent CA3 pyramidal neuron hyperexcitability, suggesting that Ca 2+ -dependent regulation of pMeCP2 does not underlie synaptic reorganization induced by BDNF.Taken together, my results enhance our understanding of how BDNF-mediated synaptic plasticity can be misappropriated after hippocampal injury and that this underlies synaptic reorganization and dysfunction.In conclusion, my work provides a mechanistic basis for further study of BDNF signaling after acquired brain injuries in rodents and higher mammals in vivo.Consequently, findings from my work may lead to the development of specific therapeutic targets that enhance cognitive recovery following brain injury.vii

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,010

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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.

Tête enseignante Opus0,023
Tête enseignante GPT0,255
Écart entre enseignants0,232 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission1
Résumé présentoui

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