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Record W2041521527 · doi:10.1089/neu.2006.003615

Hypoxia Alters The Expression of Inhibitor of Apoptosis Proteins after Brain Trauma in The Mouse

2007· article· en· W2041521527 on OpenAlexaff
Angelo Mikrogianakis, Rachel E. Shaye, Phillip T. Griffin, Sarah Kawesa, Julia Lockwood, Nathalie H. Gendron, Isabelle Gaboury, Zul Merali, Alex MacKenzie, James S. Hutchison

Bibliographic record

VenueJournal of Neurotrauma · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell death mechanisms and regulation
Canadian institutionsUniversity of TorontoChildren's Hospital of Eastern OntarioUniversity of OttawaHospital for Sick Children
Fundersnot available
KeywordsHypoxia (environmental)ApoptosisNeuroscienceTraumatic brain injuryCell biologyMedicineBiologyChemistryGenetics

Abstract

fetched live from OpenAlex

Hypoxia worsens brain injury following trauma, but the mechanisms remain unclear. The purpose of this study was to determine the effect of traumatic brain injury (TBI) and secondary hypoxia (9% oxygen) on apoptosis-related protein expression, cell death, and behavior. Using a murine weight-drop model, TBI led to an early (6 h) increase followed by a later (24 h) decrease in neuronal apoptosis inhibitor protein (NAIP) expression in the olfactory and motor cortex; in contrast, TBI led to a sustained (6 h to 7 days) increase in NAIP in the striatum. The peak increase in the expression of NAIP (6-12 h) following TBI alone was delayed (1-7 days) when hypoxia was added to TBI. Hypoxia following TBI further depleted other apoptosis inhibitor proteins (IAPs) and activated caspases, as well as increased contusion size and worsened cell death. Hypoxia added to TBI also increased motor and feeding activity on days 2 and 4 compared to TBI alone. Hypoxia without TBI had no effect on the expression of IAPs or cell death. These findings show that IAPs have a potential role in the increased vulnerability of brain cells to hypoxia following TBI, and have implications for configuring future therapies for TBI.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.018
Threshold uncertainty score0.194

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.019
GPT teacher head0.266
Teacher spread0.247 · 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 teacher head, 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

Citations18
Published2007
Admission routes1
Has abstractyes

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