Gene Expression of Catalytic Proteasome Subunits and Resistance Toward Proteasome Inhibition of B Lymphocytes from Patients with Primary Sjögren Syndrome
Bibliographic record
Abstract
OBJECTIVE: Dysregulation of proteasome subunit β1i expression has been shown in total blood mononuclear cells (PBMC) from patients with primary Sjögren syndrome (pSS), a B cell-driven systemic autoimmune disorder. METHODS: Proteasome activation was investigated in sorted blood cells from patients with pSS and controls by measuring transcript levels of constitutive (β1/β2/β5) and corresponding immunoproteasome catalytic subunits (β1i/β2i/β5i) using real-time PCR. At protein level, β1i protein expression was analyzed by immunoblotting. Functional effects of proteasome inhibition on proteolytic activity and induction of apoptosis were also evaluated in cellular subsets. RESULTS: The proteasome was found to be activated in pSS, with upregulation of gene expression of catalytic proteasome subunits. Western blot analysis revealed decreased β1i protein expression in pSS B lymphocytes, with decreased protein despite increased messenger RNA (mRNA) levels. After proteasome inhibition in vitro, proteolytic activity was less reduced and resistance to apoptosis was increased in B lymphocytes compared to other cells. CONCLUSION: In pSS, catalytic subunits of the proteasome are upregulated at the mRNA level, while dysregulation of subunit β1i is attributed to B lymphocytes. B cell resistance after proteasome inhibition differs from the classical concept of increased susceptibility toward inhibition in activated cells, supporting the novel notion that susceptibility depends on cellular intrinsic factors and on proteasome activation.
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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) | 0.000 | 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) | 0.002 | 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".