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Deep External Rotator Muscles of the Hip: An Anatomical and Architectural Study

2018· article· en· W2943806427 on OpenAlexaff
Ian A. Scagnetti, Lorraine Jadeski, Stephen H.M. Brown

Bibliographic record

VenueThe FASEB Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSarcomereMuscle architectureFascicleAnatomyCadaverMedicineRotator cuffMuscle bellyMyocyteTendon

Abstract

fetched live from OpenAlex

The arrangement of sarcomeres within a muscle (referred to as the muscle architecture) can be used to predict a muscle's functional capability. Parameters that are measured when studying muscle architecture are muscle fascicle length, sarcomere length, and the mass of the contractile tissue. Using these measured values, physiological cross‐Sectional Area (PCSA, representative of sarcomeres arranged in‐parallel) and normalized fascicle length (LFn, representative of sarcomeres arranged in‐series) can be calculated. PCSA is currently the best predictor of the relative force production capability of a muscle, and LFn is the best predictor of the excursion potential of a muscle. Additionally, based on the well‐known force‐length relationship for human muscle, sarcomere length at a given posture can be used to predict the percentage of maximal force generating capability that the muscle can produce. In this study, the architectural parameters of six deep external rotator muscles of the hip (Piriformis, Quadratus Femoris, Obturator Internus, Obturator Externus, Gemellus Superior and Gemellus Inferior) were measured, and each muscle's anatomical pathway was photographed using high quality digital imaging. These muscles are primarily external rotators and stabilizers of the hip joint, and may be affected during hip surgery if the anatomical attachments or pathways are altered. Previously, there had been no detailed architectural data measured for these six deep hip external rotator muscles. The six muscles were removed from 12 embalmed cadavers on one side of the body (n=12, 6 male and 6 female, age 56–88 years). Each muscle was carefully removed from the cadaver using dissection hand tools and had all external fat, fascia and tendon removed. Muscle mass was measured using a digital scale. Three fascicles were isolated from different locations on the muscle and fascicle length was measured using a digital caliper. Three small biopsies were taken from each fascicle and were subjected to laser diffraction to measure sarcomere length. Table 1 shows all measured and calculated results. Obturator Internus is predicted to have the highest force generating capability (based on PCSA), and Piriformis is predicted to have the highest excursion potential (based on LFn). All of the six deep hip external rotator muscles have an average sarcomere length, measured in the neutral cadaveric posture, ranging between 2.41 um – 2.54 um. This suggests an ability for the muscles to produce 91 – 95% of their maximal force, on the ascending limb of the force‐length curve, in this posture. These data, in conjunction with modelling software, can be used to predict force generating capabilities throughout the hip range of motion, and will be valuable to predict changes in the muscles' behavior after being displaced from their respective anatomical attachments during hip surgery. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
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
Bibliometrics0.0020.001
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 head0.016
GPT teacher head0.288
Teacher spread0.272 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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