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Record W1968127513 · doi:10.1016/j.ijsu.2013.05.034

Local administration of prostaglandin E1 combined with silicone chamber improves peripheral nerve regeneration

2013· article· en· W1968127513 on OpenAlexaff
Alireza Najafpour, Rahim Mohammadi, Darab Faraji, Keyvan Amini

Bibliographic record

VenueInternational Journal of Surgery · 2013
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsUniversity of Saskatchewan
FundersScience Foundation Ireland
KeywordsMedicineSciatic nerveSalineRegeneration (biology)ProstaglandinSiliconeProstaglandin E1Peripheral nerve injuryPeripheral nerveAnesthesiaGastrocnemius muscleAnatomySurgeryInternal medicineSkeletal muscleChemistryBiology

Abstract

fetched live from OpenAlex

The aim of this study was to assess the effect of locally administered prostaglandin E1 on peripheral nerve regeneration and functional recovery. Sixty male healthy white Wistar rats were divided into four experimental groups (n = 15), randomly: In transected group (TC), left sciatic nerve was transected and stumps were fixed in the adjacent muscle. In treatment group defect was bridged using silicone graft (SIL/PE) filled with 10 μL prostaglandin E1. In silicone graft group (SIL), the graft was filled with phosphate-buffered saline alone. In sham-operated group (SHAM), sciatic nerve was exposed and manipulated. Each group was subdivided into three subgroups of five animals each and regenerated nerve fibers were studied 4, 8 and 12 weeks after surgery. Behavioral testing, sciatic nerve functional study, gastrocnemius muscle mass and morphometric indices confirmed faster recovery of regenerated axons in SIL/PE than SIL group (p < 0.05). In immunohistochemistry, location of reactions to S-100 in SIL/PE was clearly more positive than that in SIL group. When loaded in a silicone graft, prostaglandin E1 improved functional recovery and morphometric indices of sciatic nerve. Local application of prostaglandin E1 improved functional recovery and morphometric indices of sciatic nerve.

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 score0.005
Threshold uncertainty score0.371

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.027
GPT teacher head0.264
Teacher spread0.237 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

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