Non-invasive spectroscopy of transfusable red blood cells stored inside sealed plastic blood-bags
Bibliographic record
Abstract
After being separated from (donated) whole blood, red blood cells are suspended in specially formulated additive solutions and stored (at 4 °C) in polyvinyl chloride (PVC) blood-bags until they are needed for transfusion. With time, the prepared red cell concentrate (RCC) is known to undergo biochemical changes that lower effectiveness of the transfusion, and thus regulations are in place that limit the storage period to 42 days. At present, RCC is not subjected to analytical testing prior to transfusion. In this study, we use Spatially Offset Raman Spectroscopy (SORS) to probe, non-invasively, the biochemistry of RCC inside sealed blood-bags. The retrieved spectra compare well with conventional Raman spectra (of sampled aliquots) and are dominated by features associated with hemoglobin. In addition to the analytical demonstration that SORS can be used to retrieve RCC spectra from standard clinical blood-bags without breaking the sterility of the system, the data reveal interesting detail about the oxygenation-state of the stored cells themselves, namely that some blood-bags unexpectedly contain measurable amounts of deoxygenated hemoglobin after weeks of storage. The demonstration that chemical information can be obtained non-invasively using spectroscopy will enable new studies of RCC degeneration, and points the way to a Raman-based instrument for quality-control in a blood-bank or hospital setting.
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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 | 0.000 |
| 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".