Multi-color Immunofluorescence Procedure for Rapid Identification of MHC Expression in Human Skeletal Muscle
Bibliographic record
Abstract
We have previously outlined an immunofluorescence staining protocol for evaluating the fiber type composition of rat and mouse skeletal muscles. The main advantage of this protocol compared to typical myosin ATPase and immunoperoxidase procedures is that multiple myosin heavy chain (MHC) isoforms can be identified on a single cross-section, eliminating the need for multiple incubations. Additionally, detection of MHC expression directly allows for more accurate fiber type identification as differential pH-dependant inactivation of myosin ATPase has been noted across species. However, antibody cross-reactivity with human muscle must also be considered. PURPOSE: To examine the effectiveness of a rapid immunofluorescence fiber-typing procedure on human skeletal muscle. METHODS: Cross-sections of vastus lateralis muscle from eight subjects were incubated with antibodies against MHCI (BA-F8), IIa (SC-71 or 2F7), and IIx (6H1). An additional antibody, specific for all MHC isoforms except IIx (BF-35) was also used. Fiber-type specific oxidative and glycolytic capacity was measured by metabolic enzyme activity staining for succinate dehydrogenase (SDH) and glycerophosphate dehydrogenase (GPD), respectively. RESULTS: Fibers demonstrating strong reactivity with BA-F8 were classified as type I (48.9%). A considerable number of fibers stained intensely for SC-71 and 2F7 and were classified as type IIA (42.8%). A very small subset of fibers stained intermediate for both BA-F8 and SC-71 and were classified as type I/IIA (0.1%). A population of fibers displayed reactivity against 6H1; however, this population also showed intermediate staining for both MHCIIa antibodies. These fibers were identified either as pure type IIX based on their non-reactivity with BF-35 (5.6%), or as type IIAX hybrid fibers based on intermediate staining for both 6H1 and BF-35 (2.6%). Type I fibers were observed as being most oxidative and type IIX fibers as being most glycolytic, with hybrid fibers displaying enzyme activity between their respective pure counterparts. CONCLUSIONS: These results suggest that a multi-color approach using three commercially available antibodies simultaneously is effective for identifying both pure and hybrid fibers in human muscle.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".