Serum cytochrome c indicates <i>in vivo</i> apoptosis and can serve as a prognostic marker during cancer therapy
Bibliographic record
Abstract
Despite significant progress in cancer therapy, the outcome of the treatment is often unfavorable. Better treatment monitoring would not only allow an individual more effective, patient-adjusted therapy, but also it would eliminate some of the side effects. Using a cytochrome c ELISA that was modified to increase sensitivity, we demonstrate that serum cytochrome c is a sensitive apoptotic marker in vivo reflecting therapy-induced cell death burden. Furthermore, increased serum cytochrome c level is a negative prognostic marker. Cancer patients whose serum cytochrome c level was normal 3 years ago have a twice as high probability to be still alive, as judged from sera samples collected for 3 years, analyzed recently and matched with survival data. Moreover, we show that serum cytochrome c and serum LDH-activity reflect different stages and different forms of cell death. Cellular cytochrome c release is specific for apoptosis, whereas increased LDH activity is an indicator of (secondary) necrosis. Whereas serum LDH activity reflects the "global" degree of cell death over a period of time, the sensitive cytochrome c-based method allows confirmation of the individual cancer therapy-induced and spontaneous cell death events. The combination of cytochrome c with tissue-specific markers may provide the foundation for precise monitoring of apoptosis in vivo, by "lab-on-the-chip" technology.
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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 | 0.000 |
| 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".