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Record W2805816152 · doi:10.1186/s12987-018-0099-0

Nimodipine treatment does not benefit juvenile ferrets with kaolin-induced hydrocephalus

2018· article· en· W2805816152 on OpenAlexafffund
Domenico L. Di Curzio, Xiaoyan Mao, Aidan Baker, Marc R. Del Bigio

Bibliographic record

VenueFluids and Barriers of the CNS · 2018
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsUniversity of ManitobaChildren's Hospital Research Institute of Manitoba
FundersHydrocephalus AssociationUniversity of Manitoba
KeywordsNimodipineVentriculomegalyMedicineHydrocephalusCorpus callosumAnesthesiaWhite matterBrain damageInternal medicinePathologySurgeryMagnetic resonance imagingBiologyRadiologyFetusCalcium

Abstract

fetched live from OpenAlex

channel blocker nimodipine. We hypothesized that treatment with nimodipine would be also beneficial to young ferrets with kaolin-induced hydrocephalus. Hydrocephalus was induced at 14 days of age and animals were treated either with vehicle, low dose nimodipine (3.2 mg/kg/day), or high dose nimodipine (16 mg/kg/day) for 2 weeks from 38 to 52 days age. Hydrocephalic ferrets developed progressive ventriculomegaly, behavioral changes, and in some cases cortical blindness. These changes were not ameliorated by nimodipine. Histological examination showed damage in periventricular white matter, corpus callosum thinning, axonal damage, reactive astroglial changes, and suppressed cell proliferation compared to non-hydrocephalic controls. Treatment with nimodipine was not beneficial for any of the pathological changes mentioned above; only low dose nimodipine treatment was associated with normalized content of glial fibrillary acidic protein, despite larger ventricles. We conclude that young hydrocephalic ferrets experience behavioral impairments and structural brain damage that are not consistently improved by intermittent nimodipine treatment. Continuous delivery should be considered in further preclinical studies.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.552

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.018
GPT teacher head0.248
Teacher spread0.230 · 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 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

Citations6
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueFluids and Barriers of the CNSSame topicCerebrospinal fluid and hydrocephalusFrench-language works237,207