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Record W4362575968 · doi:10.22215/etd/2023-15452

Role of TrkB.T1 in Glial Inflammatory Response Elicited by MHV

2023· dissertation· en· W4362575968 on OpenAlexaff
Noora Heiratifar

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsCarleton University
Fundersnot available
KeywordsTropomyosin receptor kinase BMicrogliaAstrocyteNeurotrophic factorsNeuroscienceNeurogliaBrain-derived neurotrophic factorBiologyNeuroinflammationNeurotrophinNeurotoxicityReceptorImmunologyInflammationMedicineToxicityCentral nervous systemInternal medicineGenetics

Abstract

fetched live from OpenAlex

In the present thesis, we used a rodent analogous coronavirus, murine hepatitis virus (MHV), in culture to directly assess its impact on astrocytic and microglial cells. Given the increasing importance of the brain neurotrophic factor (BDNF)-TrkB signaling system in glial functioning, we also assessed whether the unique TrkB.T1 truncated isoform (the only BDNF receptor on astrocytes) would modulate glial reactivity to MHV viral infection. Our results largely support the notion that MHV readily infects astrocytes and caused a degree of toxicity of these cells. The addition of microglia to the astrocytic culture modulated the magnitude of this effect and greatly increased pro-inflammatory cytokine release. Furthermore, TrkB.T1 deficiency appeared to greatly reduce astrocyte viability and microglial morphology. These data may have useful implications for better understanding the nature of glial responses to coronaviral infection and the importance of TrkB in such responses.

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 score0.001
Threshold uncertainty score0.003

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.269
Teacher spread0.254 · 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
Published2023
Admission routes1
Has abstractyes

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