Spontaneous aggregation of the anti-viral MAVS protein in systemic lupus erythematosus: a possible cause of excessive type I interferon production
Bibliographic record
Abstract
Peripheral blood mononuclear cells (PBMC) were isolated from 17 patients fulfilling ACR criteria for SLE, and from nine controls. Thirty million PBMC were lysed and pellets loaded onto semi-denaturing detergent vertical 1.5% agarose gels. After electrophoresis, the proteins were transferred to Immobilon membranes for immunoblotting with anti-MAVS antibody or anti-β-actin. Six of 17 SLE patients showed clear MAVS aggregation, with essentially all of their MAVS protein in a high-molecular-weight form. None of nine controls had abnormal MAVS. Three of the four SLE patients had nephritis and the fourth had lung involvement. SLEDAI scores of MAVS-aggregate positive SLE patients did not differ from patients with normal molecular weight MAVS. Patient 4 (P-4) shows the aggregated MAVS phenotype in the western blot (Figure 1 ). MAVS immunoblotting is shown in panel B and actin immunoblotting in panel C. N-1 and N-2 are normal controls. P-1 has less protein loaded and no MAVS band is discernible. Figure 1 This is the first report of aggregated MAVS in human cells. The relationship of this abnormality to disease needs further investigation, but suggests the possibility that prolonged and increased IFN-I production could result from MAVS aggregation, with the formation of poorly degradable prion-like protein that could signal IFN-I production for prolonged periods.
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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 | 0.001 |
| 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 | 0.000 |
| 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".