<scp>Aptamer‐Based</scp> Screen of Neuropsychiatric Lupus Cerebrospinal Fluid Reveals Potential Biomarkers That Overlap With the Choroid Plexus Transcriptome
Bibliographic record
Abstract
OBJECTIVE: As no gold-standard diagnostic test exists for neuropsychiatric systemic lupus erythematosus (NPSLE), we undertook this study to execute a broad screen of NPSLE cerebrospinal fluid (CSF) using an aptamer-based platform. METHODS: CSF was obtained from NPSLE patients and subjected to proteomic assay using the aptamer-based screen. Potential biomarkers were identified and validated in independent NPSLE cohorts in comparison to other neurologic diseases. RESULTS: Forty proteins out of the 1,129 screened were found to be elevated in NPSLE CSF. Based on enzyme-linked immunosorbent assay validation, CSF levels of angiostatin, α2-macroglobulin, DAN, fibronectin, hepatocellular carcinoma clone 1, IgM, lipocalin 2, macrophage colony-stimulating factor (M-CSF), and serine protease inhibitor G1 were significantly elevated in a predominantly White NPSLE cohort (n = 24), compared to patients with other neurologic diseases (n = 54), with CSF IgM (area under the curve [AUC] 0.95) and M-CSF (AUC 0.91) being the most discriminatory proteins. In a second Hong Kong-based NPSLE cohort, CSF IgM (AUC 0.78) and lipocalin 2 (AUC 0.85) were the most discriminatory proteins. Several CSF proteins exhibited high diagnostic specificity for NPSLE in both cohorts. Elevated CSF complement C3 was associated with an acute confusional state. Eleven molecules elevated in NPSLE CSF exhibited concordant elevation in the choroid plexus, suggesting shared origins. CONCLUSION: Lipocalin 2, M-CSF, IgM, and complement C3 emerge as promising CSF biomarkers of NPSLE with diagnostic potential.
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 | 0.001 |
| 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".