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Record W7027326363

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

2015· dissertation· en· W7027326363 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2015
Typedissertation
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchSavoy FoundationUniversities Space Research AssociationNational Health and Medical Research CouncilNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsSynapseHippocampal formationBrain-derived neurotrophic factorNeurotrophic factorsNeurotrophinCiliary neurotrophic factorNeuromuscular junction
DOInot available

Abstract

fetched live from 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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.255
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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