Abstract 15641: Profiling the Altered Cellular and Secreted Proteome of Cardiac Fibroblasts in Hypoxia Through Label-free Quantitation
Bibliographic record
Abstract
Introduction: Cardiac fibroblasts (CF) are key contributers to pathophysiology of the heart after ischemic injury and disease progression, such as fibrosis, which ultimately lead to heart failure Cardiomyocyte (CM) and CF intercellular communication can occur through paracrine interactions and modulate to myocyte stress response. In addition to soluble factors, cardiac cells secrete exosomes (EXO), with evidence suggesting CF EXO modulate pathophysiology in vitro . Detailed proteomic analysis of the fibroblast secretome in normal and stressed conditions will offer insights into the role of CF in heart disease. Methods: Primary mouse CF were cultured for 24h in 21% (normoxic) or 2% (hypoxic) O 2 for 24h in serum-free media. Conditioned media was differentially centrifuged and ultracentrifuged to obtain EXO and EXO-depleted secretome (SEC) fractions. Successful EXO isolation was verified biochemically and via electron microscopy. 6-step MuDPIT was performed on four biological replicates in duplicate. Whole cell lysate data (WCL) was also generated to provide subcelluar context to the CF secretome. Data was searched using multi-search algorithm platform. Protein relative abundance was compared using QSpec. Results: Proteomic analysis identified 6163 unique proteins in total, with 5655, 1752, and 715 in normoxic WCL, EXO, and SEC, respectively and 5158, 1616, and 1042 in hypoxic WCL, EXO, and SEC, respectively. QSpec analysis identified 494 proteins differentially expressed between normoxic fractions, 430 proteins between hypoxic fractions, 122 proteins between normoxic and hypoxic SEC, and 144 proteins between normoxic and hypoxic EXO. Gene Ontology revealed hypoxic conditions increase expression of ECM and signalling annotations, suggesting an activated secretory phenotype. Proteins enriched in EXO and in SEC were associated with cytoskeleton and glycoprotein annotations, respectively. For functional assessment, we subjected cardiomyocytes pretreated with either CF EXO or SEC for 24h, to 60 μM H 2 O 2 for 24h to mimic oxidative stress. Viability assays suggest reduced viability due to CF-derived secreted factors. Conclusions: CF secretome proteomics reveal differential expression based on mode of secretion and oxygen-levels in vitro .
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".