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Record W2243800326

Serial sarcomere loss in rabbit triceps surae muscles following a five hour low level electrical stimulation protocol

2013· article· en· W2243800326 on OpenAlexaffvenueabout
Sean Crooks

Bibliographic record

VenueJournal of undergraduate research in Alberta · 2013
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSarcomereStimulationTriceps surae muscleMedicineAnatomySkeletal muscleHindlimbContraction (grammar)Internal medicineMyocyte
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION Cerebral palsy (CP) is a condition where brain lesions cause involuntary contraction of skeletal muscles leading to the development of spasticity in these muscles. Spastic skeletal muscles are characterised by increased passive stiffness, shortened fibers and decreased serial sarcomere numbers, leading to a decrease in movement control and a loss of mobility in CP patients [1]. Skeletal muscles are highly adaptable where protein turnover and decreases in sarcomere number occur within 10 hours of active shortening of the muscle [1,2]. In order to artificially mimic the involuntary contractions found in CP patients, electrical stimulation can be used to induce continuous muscle contraction. In previous studies, a ~25% sarcomere loss was observed in New Zealand White Rabbits Triceps Surae muscles following ten hours of stimulation [2]. This sarcomere loss is fully recovered within two days, providing an experimental model of sarcomerogenesis. However, the ten hour stimulation protocol is hard on the rabbits, causing weakness and loss of appetite. Therefore, the purpose of this experiment was to quantify sarcomere loss following only five hours of muscle activation. We hypothesized that serial sarcomere loss is the same after five and ten hours of low level electrical stimulation.. METHODS A nerve stimulating electrode was surgically implanted on the tibial nerve of the experimental leg of New Zealand White rabbits (n=3) while the contralateral tibial nerve was transected in order to prevent any possibility of a cross training effect. Five hours of stimulation at 20 Hz and three times the α motor neuron threshold was applied to the nerve innervating the medial gastrocnemius (MG), plantaris (PLT), and soleus muscles (SOL). The extensor digitorum longus (EDL) muscle served as a non-stimulated control. After stimulation, animals were sacrificed and the hind limbs were placed in a 10% formalin solution with the knee and ankle joint at ~90°. The target muscles were separated into four to six regions. After nitric acid digestion, individual fascicles were isolated from each region and placed on slides for sarcomere length measurement by laser diffraction and fascicle length measurement using a specialized camera and software. RESULTS A 11 ± 13 % loss of sarcomeres in the experimental leg was observed in the MG, a 27 ± 1 % in PLT, 44 ± 4 % in SOL and 1 ± 5 % in EDL. DISCUSSION AND CONCLUSIONS PLT and SOL lost about the same percentage of serial sarcomeres in five hours of electrical stimulation as was found in previous works in ten or twelve hours, thereby confirming our hypothesis, However, sarcomere loss was substantially smaller in the MG for reasons that we do not understand at this point. If this result is confirmed once we have a solid number of independent observations, then we can use PLT and SOL, but not MG for studies of sarcomere loss and addition in the rabbit without causing the distress caused by ten hours of anesthesia and electrical muscle stimulation REFERENCES Tabary, J., Tardieu, C., Tardieu, G., Tabary, C., Muscle & Nerve , Issue 4 , 1981, pp. 198-203. Yamamato, M., T. Leonard, and W. Herzog. Journal of Undergraduate Research in Alberta 1 .1 (2011): 21.

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 score0.005

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 integrity0.0000.000
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 head0.066
GPT teacher head0.382
Teacher spread0.317 · 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".

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Citations0
Published2013
Admission routes3
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