Characterization of heat shock protein 27 in extracellular vesicles: a potential anti‐inflammatory therapy
Bibliographic record
Abstract
Previously, we reported that elevated serum levels of heat shock protein 27 (HSP27) are predictive of a lower risk of having a heart attack, stroke, or death from cardiovascular disease. Moreover, augmenting HSP27 (or the murine ortholog, HSP25) attenuated experimental atherogenesis, reduced inflammation, and lowered cholesterol levels. Recently, we noted that HSP27 activates NF-κB via TLR-4, resulting in attenuation of plaque inflammation; however, the precise anti-atherosclerosis mechanisms mediated by extracellular HSP27 are incompletely understood. Our purpose in this study was to investigate the existence of HSP27 in extracellular vesicles (EVs) and whether HSP27 elicited atheroprotective effects on target cells. Here, we provide evidence that HSP27 localizes to EVs derived from THP-1 cells using transmission electron microscopy (TEM) and immunogold labeling, Western blotting, ELISA, and fluorescence-activated cell sorting. TEM imaging indicated that HSP27 is found at the exosomal membrane. Multiple reactor monitor-mass spectrometric analysis of large vesicles, which included microparticles and exosomes, isolated from human plasma, also led to detection of HSP27 using the unique signature peptide, R.LFDQAFGLPR.L. Studies using THP-1 and human embryonic kidney cells show that HSP27-laden exosomes significantly stimulated NF-κB activation ( P < 0.001) and release of IL-10 ( P < 0.0001), suggesting that HSP27 may be important exosomal cargo with beneficial anti-inflammatory effects.-Shi, C., Ulke-Lemée, A., Deng, J., Batulan, Z., O'Brien, E. R. Characterization of heat shock protein 27 in extracellular vesicles: a potential anti-inflammatory therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".