In vitro kinetics of oxygen transport in erythrocyte suspension or unmodified hemoglobin solution from human and other animals
Bibliographic record
Abstract
Oxygen transport behavior in erythrocyte suspension or in hemoglobin solution was studied as a potential therapeutic model for the clinical treatment of blood loss, and this can also provide physiological data with which to evaluate blood substitutes. In the present project, we examined the in vitro kinetics of hemoglobin binding to and releasing oxygen, to provide detailed oxygen-flux measurements for unmodified hemoglobin solutions and erythrocyte suspensions in human, as well as other vertebrates. An in vitro method was used, based on a widely used artificial system, with the oxygen saturation level being detected in real time. Results from this study indicated that the kinetic curves of human erythrocyte suspensions and hemoglobin solutions were either S-shaped or hyperbolic, respectively. Based on these curves, the significance of T(50) emerged in our investigation, where T(50) is defined as the time needed for 50% hemoglobin to be saturated with oxygen, and reflects the efficiency with which hemoglobin carries oxygen. This parameter may be used to diagnose blood diseases, and could be a standard for evaluating blood substitutes. In this study, we also compared the T(50) of 4 species of vertebrates, and found that it shows a distinct efficiency of oxygen binding related to species, and potentially reveals the evolutionary function of hemoglobin and its possible adaptation to the environment.
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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".