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Record W1972495012 · doi:10.1002/mus.21945

Suction‐modified Bergström muscle biopsy technique: Experience with 13,500 procedures

2011· article· en· W1972495012 on OpenAlexaff
Mark A. Tarnopolsky, Erin Pearce, Katelyn Smith, Bolesław Lach

Bibliographic record

VenueMuscle & Nerve · 2011
Typearticle
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBicepsSuctionMuscle biopsyDeltoid curveBiopsyMedicineChemistryAnatomyPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Bergström needle muscle biopsies have been used by exercise physiologists for over 35 years but have been less accepted by neuromuscular clinicians due to size concerns. METHODS: We retrospectively reviewed over 13,500 muscle Bergström needle biopsies done over a 21-year period to determine sampling success, patient/subject experience, and complications. We compared sample yield between two different needles (Bergström vs. UCH), with and without suction modifications. RESULTS: Needle biopsies adequate for histology and enzymology were obtainable from the vastus lateralis, deltoid, biceps brachii, soleus, and medial gastrocnemius muscles, with a success rate of >99.9% and a minor complication rate of 0.15%. Approximately 450 muscle fibers were submitted for histologic assessment; suction modification and use of the Bergström vs. UCH needle were associated with larger sample size (P < 0.05). CONCLUSIONS: The suction-modified Bergström needle muscle biopsy technique is safe and provides an adequate sample size for histologic, ultrastructural, DNA, and enzyme analysis.

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)0.003
metaresearch head score (Gemma)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.044
GPT teacher head0.285
Teacher spread0.241 · 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

Citations240
Published2011
Admission routes1
Has abstractyes

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