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Critical Role of Increased PTEN Nuclear Translocation in Excitotoxic and Ischemic Neuronal Injuries

2013· article· en· W1970021151 on OpenAlexafffund
Shu Zhang, Changiz Taghibiglou, Kimberly Girling, Zhifang Dong, Shinn‐Zong Lin, Wei Lee, Woei‐Cherng Shyu, Yu Tian Wang

Bibliographic record

VenueJournal of Neuroscience · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsVancouver Coastal Health Research InstituteUniversity of British ColumbiaVancouver Coastal Health
FundersCanadian Institutes of Health ResearchNovartis PharmaNational Science CouncilNational Natural Science Foundation of ChinaHeart and Stroke Foundation of British Columbia and YukonHoward Hughes Medical InstituteCHDI FoundationHeart and Stroke Foundation of Canada
KeywordsPTENChromosomal translocationTensinIschemiaPhosphataseBiologyCell biologyNeuroscienceCancer researchInternal medicineMedicinePhosphorylationGeneticsSignal transductionPI3K/AKT/mTOR pathwayGene

Abstract

fetched live from OpenAlex

Stroke is the leading cause of disability in developed countries. However, no treatment is available beyond 3 h post-ictus. Here, we report that nuclear translocation of PTEN (phosphatase and tensin homolog deleted on chromosome TEN) is a delayed step causatively leading to excitotoxic (in vitro) and ischemic (in vivo) neuronal injuries. We found that excitotoxic stimulation of N-methyl-d-aspartate (NMDA) resulted in PTEN nuclear translocation in cultured neurons, a process requiring mono-ubiquitination at the lysine 13 residue (K13), as the translocation was prevented by mutation of K13 or a short interfering peptide (Tat-K13) that flanks the K13 residue. More importantly, using a rat model of focal ischemia, we demonstrated that systemic application of Tat-K13, even 6 h after stroke, not only reduced ischemia-induced PTEN nuclear translocation, but also strongly protected against ischemic brain damage. Our study suggests that inhibition of PTEN nuclear translocation may represent a novel after stroke therapy.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.254
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 source (direct Gemma or distilled Codex), 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

Citations88
Published2013
Admission routes2
Has abstractyes

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