Types of cell death and apoptotic stages in Chinese Hamster Ovary cells distinguished by Raman spectroscopy
Bibliographic record
Abstract
Abstract Cell death is the ultimate cause of productivity loss in bioreactors that are used to produce therapeutic proteins. We investigated the ability of Raman spectroscopy to detect the onset and types of cell death for Chinese Hamster Ovary (CHO) cells—the most widely used cell type for therapeutic protein production. Raman spectroscopy was used to compare apoptotic, necrotic, autophagic, and control CHO cells. Several specific nucleic acid‐, protein‐, and lipid‐associated marker bands within the 650–850 cm −1 spectral region were identified that distinguished among cells undergoing different modes of cell death; supporting evidence was provided by principal component analysis (PCA) of the full spectral data. In addition to comparing the different modes of cell death, normal cells were compared to cells sorted at several stages of apoptosis, in order to explore the potential for early detection of apoptosis. Different stages of apoptosis could be distinguished via Raman spectroscopy, with multiple changes observed in nucleic acid peaks at early stages whereas an increase in lipid signals was a feature of late apoptosis/secondary necrosis.
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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".