Proteomic Signature of Dysfunctional Circulating Endothelial Colony‐Forming Cells of Young Adults
Bibliographic record
Abstract
Background A subpopulation of endothelial progenitor cells called endothelial colony-forming cells (ECFCs) may offer a platform for cellular assessment in clinical studies because of their remarkable angiogenic and expansion potentials in vitro. Despite endothelial cell function being influenced by cardiovascular risk factors, no studies have yet provided a comprehensive proteomic profile to distinguish functional (ie, more angiogenic and expansive cells) versus dysfunctional circulating ECFCs of young adults. The aim of this study was to provide a detailed proteomic comparison between functional and dysfunctional ECFCs. Methods and Results Peripheral blood ECFCs were isolated from 11 subjects (45% men, aged 27±5 years) using Ficoll density gradient centrifugation. ECFCs expressed endothelial and progenitor surface markers and displayed cobblestone-patterned morphology with clonal and angiogenic capacities in vitro. ECFCs were deemed dysfunctional if <1 closed tube formed during the in vitro tube formation assay and proliferation rate was <20%. Hierarchical functional clustering revealed distinct ECFC proteomic signatures between functional and dysfunctional ECFCs with changes in cellular mechanisms involved in exocytosis, vesicle transport, extracellular matrix organization, cell metabolism, and apoptosis. Targeted antiangiogenic proteins in dysfunctional ECFCs included SPARC (secreted protein acidic and rich in cysteine), CD36 (cluster of differentiation 36), LUM (lumican), and PTX3 (pentraxin-related protein PYX3). Conclusions Circulating ECFCs with impaired angiogenesis and expansion capacities have a distinct proteomic profile and significant phenotype changes compared with highly angiogenic endothelial cells. Impaired angiogenesis in dysfunctional ECFCs may underlie the link between endothelial dysfunction and cardiovascular disease risks in young adults.
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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) | 0.001 | 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".