Inhibition of PI3Kδ Reduces Kidney Infiltration by Macrophages and Ameliorates Systemic Lupus in the Mouse
Bibliographic record
Abstract
Systemic lupus erythematosus (SLE) is a human chronic inflammatory disease generated and maintained throughout life by autoreactive T and B cells. Class I phosphoinositide 3-kinases (PI3K) are heterodimers composed of a regulatory and a catalytic subunit that catalyze phosphoinositide-3,4,5-P3 formation and regulate cell survival, migration, and division. Activity of the PI3Kδ isoform is enhanced in human SLE patient PBLs. In this study, we analyzed the effect of inhibiting PI3Kδ in MRL/lpr mice, a model of human SLE. We found that PI3Kδ inhibition ameliorated lupus progression. Treatment of these mice with a PI3Kδ inhibitor reduced the excessive numbers of CD4(+) effector/memory cells and B cells. In addition, this treatment reduced serum TNF-α levels and the number of macrophages infiltrating the kidney. Expression of inactive PI3Kδ, but not deletion of the other hematopoietic isoform PI3Kγ, reduced the ability of macrophages to cross the basement membrane, a process required to infiltrate the kidney, explaining MRL/lpr mice improvement by pharmacologic inhibition of PI3Kδ. The observations that p110δ inhibitor prolonged mouse life span, reduced disease symptoms, and showed no obvious secondary effects indicates that PI3Kδ is a promising target for SLE.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".