Early Differentiated CD138highMHCII+IgG+ Plasma Cells Express CXCR3 and Localize into Inflamed Kidneys of Lupus Mice
Bibliographic record
Abstract
Humoral responses are central to the development of chronic autoimmune diseases such as systemic lupus erythematosus. Indeed, autoantibody deposition is responsible for tissue damage, the kidneys being one of the main target organs. As the source of pathogenic antibodies, plasma cells are therefore critical players in this harmful scenario, both at systemic and local levels. The aim of the present study was to analyze plasma cells in NZB/W lupus mice and to get a better understanding of the mechanisms underlying their involvement in the renal inflammation process. Using various techniques (i.e. flow cytometry, quantitative PCR, ELISpot), we identified and extensively characterized three plasma cell intermediates, according to their B220/CD138/MHCII expression levels. Each of these cell subsets displays specific proliferation and antibody secretion capacities. Moreover, we evidenced that the inflammation-related CXCR3 chemokine receptor is uniquely expressed by CD138(high)MHCII(+) plasma cells, which encompass both short- and long-lived cells and mostly produce IgG (auto)antibodies. Expression of CXCR3 allows efficient chemotactic responsiveness of these cells to cognate chemokines, which production is up-regulated in the kidneys of diseased NZB/W mice. Finally, using fluorescence and electron microscopy, we demonstrated the presence of CD138(+)CXCR3(+)IgG(+) cells in inflammatory areas in the kidneys, where they are very likely involved in the injury process. Thus, early differentiated CD138(high)MHCII(+) rather than terminally differentiated CD138(high)MHCII(low) plasma cells may be involved in the renal inflammatory injury in lupus, due to CXCR3 expression and IgG secretion.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".