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Record W2107907085 · doi:10.1113/jphysiol.2014.282426

Pannexin channels and ischaemia

2014· review· en· W2107907085 on OpenAlexaff
Roger Thompson

Bibliographic record

VenueThe Journal of Physiology · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnexins and lens biology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPannexinExcitotoxicityGlutamate receptorNMDA receptorNeuroscienceProto-oncogene tyrosine-protein kinase SrcHippocampal formationKinaseAllosteric regulationCell biologyPhosphorylationIon channelIschemiaChemistryBiologyBiophysicsReceptorBiochemistryMedicineInternal medicineIntracellular

Abstract

fetched live from OpenAlex

An ischaemic stroke occurs during loss of blood flow in the brain from the occlusion of a blood vessel. The ischaemia itself comprises a complex array of insults, including oxygen and glucose deprivation (OGD), glutamate excitotoxicity, acidification/hypercapnia, and loss of sheer forces. A substantial amount of knowledge has accumulated that define the excitotoxic cascade downstream of N-methyl-d-aspartate receptors (NMDARs). While the NMDAR can influence numerous downstream elements, one critical target during ischaemia is the ion channel, pannexin-1 (Panx1). The C-terminal region of Panx1 appears critical for its regulation under a host of physiological and pathological stimuli. We have shown using hippocampal brain slices that Panx1 is activated by NMDARs through Src family kinases. However, it is not yet certain if this involves direct phosphorylation of Panx1 or an allosteric interaction between the channel's C-terminal tail and Src. Interestingly, Panx1 opening during ischaemia and NMDAR over-activation is antagonized by an interfering peptide that comprises amino acids 305-318 of Panx1. Thus, targeting the activation of Panx1 by NMDARs and Src kinases is an attractive mechanism to reduce anoxic depolarizations and neuronal death.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.023
GPT teacher head0.305
Teacher spread0.282 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations52
Published2014
Admission routes1
Has abstractyes

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