Antigens Protected Functional Red Blood Cells By The Membrane Grafting Of Compact Hyperbranched Polyglycerols
Bibliographic record
Abstract
Red blood cell (RBC) transfusion is vital for the treatment of a number of acute and chronic medical problems such as thalassemia major and sickle cell anemia. Due to the presence of multitude of antigens on the RBC surface (~308 known antigens), patients in the chronic blood transfusion therapy develop alloantibodies due to the miss match of minor antigens on transfused RBCs. Grafting of hydrophilic polymers such as polyethylene glycol (PEG) and hyperbranched polyglycerol (HPG) forms an exclusion layer on RBC membrane that prevents the interaction of antibodies with surface antigens without affecting the passage of small molecules such as oxygen, glucose, and ions. At present no method is available for the generation of universal red blood donor cells in part because of the daunting challenge presented by the presence of large number of antigens (protein and carbohydrate based) on the RBC surface and the development of such methods will significantly improve transfusion safety, and dramatically improve the availability and use of RBCs. In this report, the experiments that are used to develop antigen protected functional RBCs by the membrane grafting of HPG and their characterization are presented. HPGs are highly biocompatible compact polymers, and are expected to be located within the cell glycocalyx that surrounds the lipid membrane and mask RBC surface antigens.
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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".