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Record W162945516

Effect of local administration of cyclosporine A on peripheral nerve regeneration in a rat sciatic nerve transection model.

2014· article· en· W162945516 on OpenAlexaff
Rahim Mohammadi, Hadi Heydarian, Keyvan Amini

Bibliographic record

VenuePubMed · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSciatic nerveRegeneration (biology)PeripheralMedicineChitosanPeripheral nerveAnesthesiaGastrocnemius muscleAnatomySurgeryChemistryInternal medicineBiologySkeletal muscle
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the effect of cyclosporine A (CsA) loaded in chitosan conduit on bridging the sciatic nerve defects in a rat model. METHODS: A 10 mm sciatic nerve defect was bridged using a chitosan conduit filled with 10 μl carrier-drug dilution (10 μg/L CsA). In control group, the conduit was filled with the same volume of carrier dilution alone. The regene-rated fibers were studied 4, 8 and 12 weeks after surgery. RESULTS: The functional study confirmed faster recovery of the regenerated axons in treatment group than control group (P<0.05). There was statistically significant difference of the gastrocnemius muscle weight ratios between treatment and control groups (P<0.05). Morphometric indices of regenerated fibers showed that the number and diameter of the myelinated fibers in CsA-treated animals were significantly higher than those in control group. In immunohistochemistry, the location of reactions to S-100 in CsA group was clearly more positive than control group. CONCLUSION: CsA loaded in a chitosan conduit results in improvement of functional recovery and quantitative morphometric indices of sciatic nerve. It is easily available without any complications compared with its systemic administration.

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 score0.004

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 integrity0.0000.001
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 head0.019
GPT teacher head0.248
Teacher spread0.229 · 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

Citations11
Published2014
Admission routes1
Has abstractyes

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Same venuePubMed→Same topicNerve injury and regeneration→French-language works237,207→