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Record W2019645362 · doi:10.5414/npp29262

Tubuloreticular inclusions in inclusion body myositis

2010· article· en· W2019645362 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Neuropathology · 2010
Typearticle
Languageen
FieldMedicine
TopicInflammatory Myopathies and Dermatomyositis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInclusion body myositisPathologyMyocyteCytoplasmElectron microscopeInclusion bodiesImmunostainingCytoplasmic inclusionVacuoleMyositisMuscle biopsyStainingEndoplasmic reticulumAnatomyBiologyBiopsyChemistryMedicineCell biologyImmunohistochemistryBiochemistry

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate whether patients with inclusion body myositis (IBM) can have tubuloreticular inclusions present in muscle endothelial cells. MATERIAL AND METHODS: Light microscopy with histochemical staining and electron microscopy of a right quadriceps muscle biopsy were used to identify the pathological features in an 83-year-old patient with a clinical diagnosis of IBM. RESULTS: Light microscopy showed rimmed vacuoles. Immunostaining for HLA-1 revealed widespread membrane labeling and for TDP-43 multiple areas of subsarcolemmal and sarcoplasmic staining. Electron microscopy revealed tubuloreticular inclusions in the cytoplasm of endothelial cells. Electron microscopy also showed the presence of myeloid bodies and aggregates of tubolo filaments in the nucleus and cytoplasm of myocytes which confirmed the diagnosis of inclusion body myositis. CONCLUSION: Tubuloreticular inclusions may be found in the muscle endothelial cells of patients with a clinical and pathological diagnosis of IBM.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.223
Threshold uncertainty score0.741

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.002
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.340
Teacher spread0.327 · 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