A window into intracellular events in myositis through subcellular proteomics
Bibliographic record
Abstract
OBJECTIVE AND DESIGN: Idiopathic inflammatory myopathies (IIM) are a heterogeneous group of inflammatory muscle disorders of unknown etiology. It is postulated that mitochondrial dysfunction and protein aggregation in skeletal muscle contribute to myofiber degeneration. However, molecular pathways that lead to protein aggregation in skeletal muscle are not well defined. SUBJECTS: Here we have isolated membrane-bound organelles (e.g., nuclei, mitochondria, sarcoplasmic/endoplasmic reticulum, Golgi apparatus, and plasma membrane) from muscle biopsies of normal (n = 3) and muscle disease patients (n = 11). Of the myopathy group, 10 patients displayed mitochondrial abnormalities (IIM (n = 9); mitochondrial myopathy (n = 1)), and one IIM patient did not show mitochondrial abnormalities (polymyositis). METHODS: Global proteomic analysis was performed using an Orbitrap Fusion mass spectrometer. Upon unsupervised clustering, normal and mitochondrial myopathy muscle samples clustered separately from IIM samples. RESULTS: We have confirmed previously known protein alterations in IIM and identified several new ones. For example, we found differential expression of (i) nuclear proteins that control cell division, transcription, RNA regulation, and stability, (ii) ER and Golgi proteins involved in protein folding, degradation, and protein trafficking in the cytosol, and (iii) mitochondrial proteins involved in energy production/metabolism and alterations in cytoskeletal and contractile machinery of the muscle. CONCLUSIONS: Our data demonstrates that molecular alterations are not limited to protein aggregations in the cytosol (inclusions) and occur in nuclear, mitochondrial, and membrane compartments of IIM skeletal 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".