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Record W2050487189 · doi:10.1161/strokeaha.106.475129

BNIP3 Upregulation and EndoG Translocation in Delayed Neuronal Death in Stroke and in Hypoxia

2007· article· en· W2050487189 on OpenAlexaff
Zhengfeng Zhang, Xuefen Yang, Surong Zhang, Xiuli Ma, Jiming Kong

Bibliographic record

VenueStroke · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell death mechanisms and regulation
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineHypoxia (environmental)Downregulation and upregulationStroke (engine)NeuroscienceCardiologyOxygenGene

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Delayed neuronal death is a hallmark feature of stroke and the primary target of neuroprotective strategies. Caspase-independent apoptosis pathways are suggested as a mechanism for the delayed neuronal injury. Here we test the hypothesis that one of the caspase-independent apoptosis pathways is activated by BNIP3 and mediated by EndoG. METHODS: We performed immunohistochemistry, Western blotting, cell transfection, subcellular fractionation, and RNA interfering to analyze the expression and localization of BNIP3 and EndoG in degenerating neurons in models of stroke and hypoxia. RESULTS: BNIP3 was upregulated in brain neurons in a rat model of stroke and in cultured primary neurons exposed to hypoxia. The expressed BNIP3 was localized to mitochondria. Both forced expression of BNIP3 by plasmid transfection and induced expression of BNIP3 by hypoxia in neurons resulted in mitochondrial release and nuclear translocation of EndoG and neuronal cell death. Knockdown of BNIP3 by RNAi inhibited EndoG translocation and protected against hypoxia-induced neuronal death. CONCLUSIONS: BNIP3 plays a role in delayed neuronal death in hypoxia and stroke and EndoG is a mediator of the BNIP3-activated neuronal death pathway. The results suggest that BNIP3 may be a new target for neuronal rescue strategies.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.867
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.009
GPT teacher head0.234
Teacher spread0.225 · 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

Citations92
Published2007
Admission routes1
Has abstractyes

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