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Record W1591915710 · doi:10.5772/32850

Delayed Neuronal Death in Ischemic Stroke: Molecular Pathways

2012· book-chapter· en· W1591915710 on OpenAlexafffund
Victor Li, Xiaoying Bi, Paul Szelemej, Jiming Kong

Bibliographic record

VenueInTech eBooks · 2012
Typebook-chapter
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsUniversity of Manitoba
FundersCanadian Institutes of Health ResearchCanadian Stroke NetworkManitoba Health Research Council
KeywordsPenumbraIschemiaBlood flowProgrammed cell deathMedicineCerebral blood flowStroke (engine)Ischemic strokeInternal medicineCardiologyApoptosisNeuroscienceBiologyBiochemistry

Abstract

fetched live from OpenAlex

Ischemic stroke is caused by a loss of blood flow and deficiency in glucose and oxygen to the brain. The lack of sufficient glucose and oxygen results in varying degrees of tissue damage and cell death following stroke. Reperfusion of blood flow after ischemia often compounds tissue damage that is sustained during the initial drop in local blood availability. The size and position of the affected region depends on which vessel is occluded. A complete loss of blood flow is rare, as rich networks of nearby blood vessels often compensate for reduced flow. The centre of the ischemic region, the core, is characterized by acute and mostly necrotic cell death resulting from severe anoxia and hypoglycemia. The region enveloping the core is known as the penumbra, which experiences a milder ischemic insult. The penumbra should be targeted for treatment strategies; it is usually much larger than the core and has a longer window of opportunity during which neurons can be prevented from dying. Many studies elucidate the molecular pathways of delayed neuronal death. This chapter presents the pathways and strategies that have been investigated to date.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.709
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.045
GPT teacher head0.246
Teacher spread0.202 · 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.

Study designBench or experimental
Domainnot available
GenreOther

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

Citations3
Published2012
Admission routes2
Has abstractyes

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