Pathogen inactivation of red cell concentrates and whole blood: <scp>II</scp> . In vivo human recovery studies, clinical trials and future directions
Bibliographic record
Abstract
Three technologies are currently under active development for pathogen inactivation of red cell concentrates or whole blood (WB): the Intercept technology using S-303 as an inactivating chemical; the Theraflex technology using UV-C illumination; and the Mirasol technology using riboflavin and UV light. For the UV-C technology, no in vivo data are available. For the other two technologies, recovery, survival and life span of the treated red blood cells (RBCs) are shortened but are within objective requirements, including a 24-h recovery >75%. S-303-treated RBCs were transfused in various patient groups and, so far, showed no relevant differences in the clinical endpoints. In early studies, S-303-reactive antibodies were observed, which prompted changes in the inactivation process, and no further antibody formation was seen. The one published study with the riboflavin/UV procedure showed good effectiveness of treated WB, with haemoglobin increment similar to that of untreated WB. When considering potential implementation of pathogen inactivation strategies, a balance should be struck between microbiological safety, component quality and cost. None of the current technologies is in a stage for large-scale blood bank application, either because of limited availability of evidence of satisfactory in vitro quality data or because of the ongoing requirement of clinical trials in a broad spectrum of patients.
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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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".