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Record W1978900023 · doi:10.1159/000075259

Tacrolimus and Cyclosporine A Are of No Benefit to Young Rats with Kaolin-Induced Hydrocephalus

2003· article· en· W1978900023 on OpenAlexaff
Osaama H. Khan, Terry Enno, Marc R. Del Bigio

Bibliographic record

VenuePediatric Neurosurgery · 2003
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsUniversity of ManitobaChildren's Hospital Research Institute of Manitoba
Fundersnot available
KeywordsCisterna magnaMedicineTacrolimusCalcineurinHydrocephalusAnesthesiaSubcutaneous injectionPharmacologyNeuroprotectionPathologyInternal medicineTransplantationSurgeryCerebrospinal fluid

Abstract

fetched live from OpenAlex

Hydrocephalus causes damage to periventricular axons. Tacrolimus, cyclosporine A (CsA) and calpain inhibitors have been shown to protect axons in rat models of acute traumatic brain injury. We hypothesized that these agents would ameliorate the axon damage and behavioral effects in experimental hydrocephalus. Hydrocephalus was induced in 3-week-old rats by injection of kaolin into the cisterna magna. Tests of cognitive and motor function were performed on a weekly basis. In a blinded and randomized manner, tacrolimus (FK506; 3.6 mg/kg body weight) or CsA (10 mg/kg) was administered once daily by subcutaneous injection for 2 weeks, beginning 2 weeks after induction of hydrocephalus. In a separate experiment, calpain inhibitor I (10 mg/kg/day) was administered by continuous subcutaneous infusion. The brains were subjected to histopathological and biochemical analyses after 2 weeks of treatment. There was no statistically significant protection in regard to behavior, brain structure or brain composition in any of the experiments. However, there was biochemical and histological evidence of renal injury following chronic tacrolimus and CsA administration. Calcineurin inhibition does not offer significant protection in this rat model of hydrocephalus.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.884

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.232
Teacher spread0.217 · 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 designObservational
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

Citations9
Published2003
Admission routes1
Has abstractyes

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