Upregulation of HSP90α in the lungs and circulation in sarcoidosis
Bibliographic record
Abstract
Background Sarcoidosis is a systemic granulomatous disease of unknown cause. Natural improvement with favorable outcome is common, but a significant number of patients present with difficult to manage and progressive disease. The identification of biomarkers associated with disease activity and progression is warranted. Extracellular heat shock protein 90 (HSP90) α is a signaling molecule released by cells that induces proinflammatory signaling through interaction with certain receptors, such as lipoprotein receptor–related protein 1. Materials and methods HSP90α protein expression in lung tissues derived from patients diagnosed with sarcoidosis and control subjects was assessed by immunohistochemistry. Serum HSP90α concentration was measured in sarcoidosis patients and healthy controls and correlated with clinical outcomes. Bronchoalveolar lavage fluid (BALF) was collected and analyzed for HSP90α expression. Extracellular HSP90α released from macrophages was examined in human primary cells and an immortalized cell line. Results Macrophages and granulomas in sarcoidosis-affected lungs showed high HSP90α expression. Serum HSP90α levels were elevated in sarcoidosis patients compared with controls and correlated with BALF HSP90α levels. HSP90α concentrations in the circulation were correlated with biomarkers of disease stage. Both primary and immortalized macrophages showed a high capacity for secreting extracellular HSP90α. Conclusion These results demonstrate that macrophages in the lungs of sarcoidosis patients produce high levels of HSP90α, suggesting HSP90α as a potential biomarker and therapeutic target.
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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 | 0.000 | 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".