Neuropsychiatric lupus is lipocalin-2 dependent
Bibliographic record
Abstract
Abstract Neuropsychiatric manifestations of systemic lupus erythematosus (NPSLE) affect approximately 40% of patients. Lipocalin-2 (LCN2), an acute-phase reactant protein, is an established urinary biomarker in lupus patients. Previous studies using LCN2-deficient mice have demonstrated its role in glial migration and chemokine regulation in the brain. We therefore hypothesized that LCN2 is involved in NPSLE pathogenesis. We investigated the lupus prone B6.Sle1.Sle3 (Sle1,3) mouse and the effects of LCN2 deficiency on the development of the neuropsychiatric phenotype exhibited by this strain. Sle1,3, B6.LCN2KO, B6, and Sle1,3-LCN2KO mice (6–10 month old; n=5–10/group) underwent comprehensive neurobehavioral assessment, and brains were evaluated by flow cytometry and RNA sequencing. Sle1,3 mice exhibited significant impairment in spatial (p<0.04) and recognition (p<0.02) memory when compared with B6 mice, and these deficits were attenuated in Sle1,3-LCN2KO mice (p<0.001, p<0.02). Furthermore, Sle1,3 mice demonstrated anhedonia, and this depression-like behavior was significantly reduced with LCN2 deficiency (p=0.01). Flow cytometry showed a significant increase in brain infiltrating CD8+ T cells in Sle1,3 mice, with a reduction in infiltration in the Sle1,3-LCN2KO strain (p=0.06). Preliminary analysis of RNA sequencing from sorted microglia revealed genes involved in cognition and memory that were differentially expressed in Sle1,3 mice were restored to background B6 expression levels in Sle1,3-LCN2KO mice. Our findings establish the Sle1,3 mouse as an NPSLE model and demonstrate that LCN2 deficiency attenuates neurobehavioral deficits and regulates microglial expression of genes essential to NPSLE development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.001 |
| 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".