Vimentin is a dominant target of in situ humoral immunity in human lupus tubulointerstitial nephritis
Bibliographic record
Abstract
In lupus nephritis (LuN), severe tubulointerstitial inflammation (TII) predicts progression to renal failure. Severe TII is associated with tertiary lymphoid neogenesis and in situ antigen-driven clonal B-cell selection. The dominant autoantigen(s) driving in situ B-cell selection in TII are not known. Single CD38 or Ki-67 B cells were laser captured from seven LuN biopsies. Twenty clonally expanded immunoglobulin heavy and light chain variable region pairs were cloned and expressed as antibodies. Seven more antibodies were cloned from flow-sorted CD38 cells from an eighth biopsy. Antigen characterization was performed using a combination of confocal microscopy, ELISA, screening protoarrays, immunoprecipitation and mass spectrometry. Serum IgG titers to the dominant antigen were determined in 45 LuN and 38 non-nephritic lupus samples using purified antigen-coated arrays. Autoantigen expression was localized by immunohistochemistry and immunofluorescence on normal and LuN kidney. Thirteen of 27 antibodies reacted with cytoplasmic structures, four reacted with nuclei and none with dsDNA, Sm or RNP. Vimentin was the only autoantigen identified by both mass spectrometry and on protoarray. Eleven anticytoplasmic TII antibodies directly bound vimentin. Vimentin was highly expressed by tubulointerstitial inflammatory cells, and tested TII antibodies preferentially bound inflamed tubulointerstitium. Finally, high titers of serum anti-vimentin antibodies were associated with severe TII ( P = 0.0001). Vimentin, an antigenic feature of inflammation, is a dominant autoantigen targeted in situ in LuN TII. This adaptive autoimmune response probably feeds forward to worsen TII and renal damage.
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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 | 0.000 | 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".