Immunogold Labeling for Igg, Immunoglobulin Light Chains and P-Component in Fibrillary and Immunotactoid Glomerular Nephritis
Bibliographic record
Abstract
Abstract Fibrillary and immunotactoid glomerulonephritis (FGN & IGN) are uncommon glomerular diseases, diagnosed by electron microscopic identification of fibril deposits which are negative by the Congo red stain. Micro-fibrils are similar to normal structures in glomerular basement membrane and matrix and they can be missed by EM. Pathogenesis of these glomerulopathies is unclear but they are not believed to be associated with monoclonal gammopathies as in AL amyloidosis. Immunofluorescense (IF) on FGN indicates the fibrils typically are positive for IgG and both immunoglobulin light chains while IGN fibrils are light chain monoclonal. We did immunogold labeling on four cases of FIGN in to improve the diagnosis of these diseases and investigate fibril protein composition. Renal biopsies from four patients consisted of one IGN and 3 FGN. Tests included frozen section IF (IgG, IgA, IgM, C3), paraffin section histology (Congo Red) and conventional EM (osmium fixation and epoxy embedding).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".