Cx3cr1 deficiency alters renal-infiltrating immune cell transcriptional landscape in lupus-prone MRL/lpr mice 2274
Bibliographic record
Abstract
Abstract Description Systemic lupus erythematosus (SLE) is an autoimmune disorder characterized by aberrant immune responses and chronic inflammation. CX3CR1, a chemokine receptor, plays a critical role in immune cell trafficking and lupus pathogenesis. We previously found that Cx3cr1 deficiency exacerbates murine lupus nephritis, but the mechanisms remain unclear. Using single-cell RNA sequencing (scRNA-seq), we analyzed renal-infiltrating CD45+ leukocytes from wild-type (WT) and Cx3cr1-knockout (KO) lupus-prone MRL/lpr mice. scRNA-seq revealed transcriptional changes in T cells, B cells, NK cells, neutrophils, monocytes, macrophages, and dendritic cells. In KO mice, macrophages exhibited upregulation of complement-related genes, including C1qa, C1qb, C1qc, and C3ar1, indicating enhanced complement activation. In addition, Egfr was upregulated in CD4 T cells, dendritic cells, B cells, NK cells, neutrophils, double negative T cells, and macrophages, suggesting a role for epidermal growth factor (EGF) in autoimmune activation and proliferation. Pathway analysis showed activation of complement, coagulation, and EGF-associated pathways in various immune cell subsets. These findings suggest that Cx3cr1 deficiency alters the transcriptional landscape of renal-infiltrating immune cells to exacerbate lupus nephritis in MRL/lpr mice. Topic Categories Basic Autoimmunity (BA)
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".