Altered Expression of TNF-α Signaling Pathway Proteins in Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: To investigate the expression of tumor necrosis factor receptors (TNFR1 and TNFR2) and adapter proteins (TRADD, RIP, and TRAF2) in peripheral blood mononuclear cell (PBMC) subsets from patients with systemic lupus erythematosus (SLE). METHODS: PBMC were isolated from 45 SLE patients and 25 controls, and stained with labeled antibodies that enabled identification of various T cell, B cell, and monocyte subpopulations. Expression of TNF-related signaling molecules was measured by staining with labeled antibodies either directly or following fixation and permeabilization. Apoptosis was quantified using an anti-active caspase 3 antibody. RNA expression of TNF-related signaling molecules was assessed by quantitative RT-PCR and serum levels of TNF-alpha by ELISA. RESULTS: SLE patients had increased levels of TNFR1, TNFR2, and TRAF2, together with decreased levels of RIP, on various B, CD4+ T, and CD8+ T cell subsets as compared to controls. This altered expression was seen in both naive and memory subpopulations, and reflected altered staining of the whole population rather than a subset of cells that were activated. The levels of these molecules were not significantly correlated with serum TNF-alpha levels or their RNA expression in whole peripheral blood. TNFR1 and TNFR2 expression was negatively correlated with disease activity. There was no association between the proportion of apoptotic cells in any of the subpopulations and serum TNF-alpha levels or expression of TNF-related signaling molecules. CONCLUSION: Patients with SLE had altered expression of TNF-related signaling molecules, suggesting that there may be an imbalance in TNF-alpha signaling favoring cellular activation as opposed to proapoptotic pathways.
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) | 0.000 | 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".