Blood replacement with nanobiotechnologically engineered hemoglobin and hemoglobin nanocapsules
Bibliographic record
Abstract
Unlike donor red blood cells (RBCs), blood substitutes can be treated to remove infective agents and can be used on the spot or in the ambulance in emergency without the time-consuming typing and cross-matching. Donor RBC requires storage at 4 degrees and is only good for 42 days, but blood substitutes can be stored for much longer time. For example, a bovine polyhemoglobin (PolyHb) can be stored at room temperature for more than 1 year. It has been shown as far back as 1957 that artificial RBC can be prepared with ultrathin polymer membranes of nanodimension thickness. To increase the circulation time, the first-generation engineered hemoglobin (Hb) is formed by using glutaraldehyde to crosslink Hb into soluble nanodimension PolyHb that has been tested clinically in patients. Further extension includes conjugated Hb, intramolecularly crosslinked Hb and recombinant Hb. For certain clinical uses, in addition to engineered Hb, we also need antioxidants to remove oxygen radicals to prevent injury from ischemia reperfusion. Thus, we use nanobiotechnology to prepare second-generation engineered Hb by assembling Hb together with superoxide dismutase (SOD) and catalase (CAT) to form a nanodimension soluble complex of polyhemoglobin (PolyHb)-CAT-SOD. A third generation system is to prepare nanodimension complete artificial RBCs that can circulate for sufficient length of time after infusion. One approach uses lipid vesicles to encapsulate hemoglobin (Hb). Another approach is to use biodegradable polymer-like polylactic acid or a copolymer of polyethylene glycol-polylactide (PEG-PLA) to form the membrane of nanodimension complete artificial RBC (www.artcell.mcgill.ca).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".