The effect of dissolved oxygen on the relaxation rates of blood plasma: Implications for hyperoxia calibrated BOLD
Bibliographic record
Abstract
Purpose To determine the contribution of paramagnetic dissolved oxygen in blood plasma to blood‐oxygenation‐level‐dependent (BOLD) signal changes in hyperoxic calibrated BOLD studies. Methods Bovine blood plasma samples were prepared with partial pressures of oxygen (pO 2 ) ranging from 110 to 600 mmHg. R 1 , R 2 , and R 2 * of the plasma with dissolved oxygen were measured using quantitative MRI sequences at 3 Tesla. Simulations were performed to predict the relative effects of dissolved oxygen and deoxyhemoglobin changes in hyperoxia calibrated BOLD. Results The relaxivities of dissolved oxygen in plasma were found to be r 1, O2 =1.97 ± 0.09 ×10 ‐4 s ‐1 mmHg ‐1 , r 2, O2 =2.3 ± 0.7 ×10 ‐4 s ‐1 mmHg ‐1 , and r 2, O2 * = 2.3 ± 0.7 ×10 ‐4 s ‐1 mmHg ‐1 . Simulations predict that neither the transverse nor longitudinal relaxation rates of dissolved oxygen contribute significantly to the BOLD signal during hyperoxia. Conclusion During hyperoxia, the increases in R 2 and R 2 * of blood from dissolved oxygen in plasma are considerably less than the decreases in R 2 and R 2 * from venous deoxyhemoglobin. R 1 effects due to dissolved oxygen are also predicted to be negligible. As a result, dissolved oxygen in arteries should not contribute significantly to the hyperoxic calibrated BOLD signal. Magn Reson Med 76:1905–1911, 2016. © 2015 International Society for Magnetic Resonance in Medicine
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 | 0.002 |
| 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 | 0.001 |
| 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".