Label-Free Determination of the Cell Cycle Phase in Human Embryonic Stem Cells by Raman Microspectroscopy
Bibliographic record
Abstract
The cell cycle is a series of integrated and coordinated physiological events that results in cell growth and replication. Besides observing the event of cell division it is not feasible to determine the cell cycle phase without fatal and/or perturbing invasive procedures such as cell staining, fixing, and/or dissociation. Raman microspectroscopy (RMS) is a chemical imaging technique that exploits molecular vibrations as a contrast mechanism; it can be applied to single living cells noninvasively to allow unperturbed analysis over time. We used RMS to determine the cell cycle phase based on integrating the composite 783 cm(-1) nucleic acid band intensities across individual cell nuclei. After correcting for RNA contributions using the RNA 811 cm(-1) band, the measured intensities essentially reflected DNA content. When quantifying Raman images from single cells in a population of methanol-fixed human embryonic stem cells, the histogram of corrected 783 cm(-1) band intensities exhibited a profile analogous to that obtained using flow-cytometry with nuclear stains. The two population peaks in the histogram occur at Raman intensities corresponding to a 1-fold and 2-fold diploid DNA complement per cell, consistent with a distribution of cells with a population peak due to cells at the end of G1 phase (1-fold) and a peak due to cells entering M phase (2-fold). When treated with EdU to label the replicating DNA and block cell division, cells with higher EdU-related fluorescence generally had higher integrated Raman intensities. This provides proof-of-principle of an analytical method for label-free RMS determination in situ of cell cycle phase in adherent monolayers or even single adherent cells.
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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 | 0.000 | 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 | 0.001 |
| 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".