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Record W2800552256 · doi:10.1111/1440-1681.12950

Rapamycin protects against early brain injury independent of cerebral blood flow changes in a mouse model of subarachnoid haemorrhage

2018· letter· en· W2800552256 on OpenAlexaff
Kazumasu Sasaki, Shuzo Yamamoto, Tatsushi Mutoh, Yoshiharu Tsuru, Yasuyuki Taki, Ryuta Kawashima

Bibliographic record

VenueClinical and Experimental Pharmacology and Physiology · 2018
Typeletter
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsInstitute of Aging
FundersJapan Society for the Promotion of ScienceUniversity of Tokyo
KeywordsHypoactivityCerebral blood flowPI3K/AKT/mTOR pathwayHypoxia (environmental)NeuroprotectionMedicineAnesthesiaIschemiaPharmacologyInternal medicineChemistrySignal transductionBiochemistry

Abstract

fetched live from OpenAlex

We evaluated the neuroprotective role of rapamycin, a mammalian target of rapamycin (mTOR) kinase inhibitor, in cerebral ischaemia and locomotor function in a mouse model of subarachnoid haemorrhage (SAH). Pretreatment with rapamycin, an mTOR kinase inhibitor, resulted in better recovery from cerebral hypoxia early after SAH than control (P < .05), while the values of peak flow velocity in the middle cerebral artery did not change significantly (P > .05). Average distance travelled and the ratio of central-area distance/total travelled distance determined by open-field test after day 14 was significantly higher in mice pretreated with rapamycin than in control mice (P < .05). Inhibition of the mTOR pathway could be protective against post-SAH early brain injury, ameliorating brain tissue hypoxia and locomotor hypoactivity.

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: Commentary · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.038
GPT teacher head0.340
Teacher spread0.302 · 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
GenreCommentary

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

Citations8
Published2018
Admission routes1
Has abstractyes

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