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Record W2746871388 · doi:10.1002/mus.25775

Messenger RNA profiling of rabbit quadriceps femoris after repeat injections of botulinum toxin: Evidence for a dynamic pattern without further structural alterations

2017· article· en· W2746871388 on OpenAlexafffund
David A. Hart, Rafael Fortuna, Walter Herzog

Bibliographic record

VenueMuscle & Nerve · 2017
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsAlberta Bone and Joint Health InstituteUniversity of Calgary
FundersCanadian Institutes of Health ResearchCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorCanada Research ChairsCerebral Palsy International Research Foundation
KeywordsMedicineQuadriceps femoris muscleBotulinum toxinMuscle atrophyAtrophyAnesthesiaAdverse effectPathologyInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Onabotulinum toxin type A (BoNT-A) is widely used clinically, but it may cause adverse effects. Earlier studies showed repeat BoNT-A injections did not cause progressive atrophy or function loss. The purpose of this study was to assess the influence of repeat BoNT-A injections into rabbit muscle on subsequent molecular alterations. METHODS: Twenty-two rabbits received 0, 1, 2, or 3 BoNT-A injections in the quadriceps femoris muscle at 3-month intervals and were euthanized 6 months after the last injection. Aliquots of both injected and contralateral muscle were frozen, and the total RNA quantified. RESULTS: Total RNA per illigram wet weight tissue was significantly elevated compared with control after 1, 2, or 3 BoNT-A injections. Analysis of mRNA levels for inflammatory molecules, proteinases, adipokines, and mesenchymal stem cells were elevated with increasing BoNT-A injections in injected leg and contralateral leg. DISCUSSION: Future studies should focus on the safety and possible complications of repeat BoNT-A treatments. Muscle Nerve 57: 487-493, 2018.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score0.642

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 communication0.0000.000
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 head0.046
GPT teacher head0.343
Teacher spread0.297 · 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

Citations10
Published2017
Admission routes2
Has abstractyes

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