An Optimized Approach to Recover Secreted Proteins from Fibroblast Conditioned-Media for Secretomic Analysis
Bibliographic record
Abstract
The proteins secreted by a particular type of cell, the secretome, play important roles in the regulation of many physiological processes via paracrine/autocrine mechanisms, and they are of increasing interest to help understanding rare diseases and to identify potential biomarkers and therapeutic targets. To facilitate ongoing research involving secreted proteins, we revisited cell culture protocols and whole secreted protein enrichment protocols. A reliable method for culturing and precipitating secreted protein from patient-derived fibroblast conditioned-medium was established. The method is based on the optimization of cell confluency and incubation time conditions. The well-established carrier-based TCA-DOC protein precipitation method was consistently found to give higher protein recovery yield. According to our results, we therefore propose that protein enrichment should be performed by TCA-DOC precipitation method after 48 h at 95% of confluence in a serum-deprived culture medium. Given the importance of secreted proteins as a source to elucidate the pathogenesis of rare diseases, especially neurological disorders, this approach may help to discover novel candidate biomarkers with potential clinical significance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".