MétaCan
Menu
Back to cohort
Record W1904500917 · doi:10.1038/cddis.2015.272

Targeting caspase-6 and caspase-8 to promote neuronal survival following ischemic stroke

2015· article· en· W1904500917 on OpenAlexafffund
Alireza P. Shabanzadeh, Philippe M. D’Onofrio, Philippe P. Monnier, Paulo D. Koeberle

Bibliographic record

VenueCell Death and Disease · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell death mechanisms and regulation
Canadian institutionsToronto Western HospitalToronto Rehabilitation InstituteUniversity of Toronto
FundersCanadian Institutes of Health ResearchHeart and Stroke Foundation of Canada
KeywordsCaspase 3Retinal ganglion cellIschemiaApoptosisCaspasePharmacologyMedicineCaspase 2BiologyNeuroscienceInternal medicineRetinaProgrammed cell deathBiochemistry

Abstract

fetched live from OpenAlex

Previous studies show that caspase-6 and caspase-8 are involved in neuronal apoptosis and regenerative failure after trauma of the adult central nervous system (CNS). In this study, we evaluated whether caspase-6 or -8 inhibitors can reduce cerebral or retinal injury after ischemia. Cerebral infarct volume, relative to appropriate controls, was significantly reduced in groups treated with caspase-6 or -8 inhibitors. Concomitantly, these treatments also reduced neurological deficits, reduced edema, increased cell proliferation, and increased neurofilament levels in the injured cerebrum. Caspase-6 and -8 inhibitors, or siRNAs, also increased retinal ganglion cell survival at 14 days after ischemic injury. Caspase-6 or -8 inhibition also decreased caspase-3, -6, and caspase-8 cleavage when assayed by western blot and reduced caspase-3 and -6 activities in colorimetric assays. We have shown that caspase-6 or caspase-8 inhibition decreases the neuropathological consequences of cerebral or retinal infarction, thereby emphasizing their importance in ischemic neuronal degeneration. As such, caspase-6 and -8 are potential targets for future therapies aimed at attenuating the devastating functional losses that result from retinal or cerebral stroke.

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 score0.552
Threshold uncertainty score0.623

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 head0.013
GPT teacher head0.232
Teacher spread0.219 · 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

Citations67
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueCell Death and DiseaseSame topicCell death mechanisms and regulationFrench-language works237,207