Analysis of Polyethylene‐glycol‐polylactide Nano‐Dimension Artificial Red Blood Cells in Maintaining Systemic Hemoglobin Levels and Prevention of Methemoglobin Formation
Bibliographic record
Abstract
We have recently reported our study on novel nano-dimension red blood cell (rbc) substitute based on ultrathin PEG-PLA membrane nanocapsules (80-150 nanometer diameter) containing hemoglobin (Hb) and enzymes. These have a markedly increased the circulation half-times as compared to our earlier PLA membrane nanocapsules. In the present study to be reported here, instead of looking at this from a pharmacodynamic point of view, we design the Hb nanocapsules from the point of view of transfusion medicine. For instance, the maximal levels of systemic non-red blood cell (rbc) Hb that can be attained after one infusion of 30% blood volume of 10 gm/dl Hb in the form of different types of PEG-PLA Hb nanocapsules or polyHb. Also the length of time one infusion can maintain a given systemic non-rbc hemoglobin Hb level. Of the two types of polyhemoglobins similar to those in clinical trials but prepared in this laboratory, the maximal levels of Hb reached were 3.35 gm/dl and 3.10 gm/dl respectively. The times for the hemoglobin level to fall to 1.67 gm/dl were 14 hours and 10. hours respectively, corresponding to 24 hours and 17 hours in human. The best PEG-PLA Hb nanocapsules are prepared using a combination of the following 4 factors: use of polymerized Hb, the use of higher M.W. PLA, the use of higher concentrations of PEG-PLA and the crosslinking of the newly formed PEG-PLA Hb nanocapsules. With this, the maximal non-rbc systemic Hb reached was 3.66 gm/dl and the time to reach 1.67 gm/dl was 24.2 hours, or 41.5 hours in human if extrapolated using the results obtained with polyHb in rats.
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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) | 0.000 | 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 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".