Quantitative and simultaneous measurement of oxygen consumption rates in rat brain and skeletal muscle using <sup>17</sup>O MRS imaging at 16.4T
Bibliographic record
Abstract
Purpose Oxygen‐17 (17O) MRS imaging, successfully used in the brain, is extended by imaging the oxygen metabolic rate in the resting skeletal muscle and used to determine the total whole‐body oxygen metabolic rate in the rat. Methods During and after inhalations of 17O2 gas, dynamic 17O MRSI was performed in rats (n = 8) ventilated with N2O or N2 at 16.4 T. Time courses of the H217O concentration from regions of interest located in brain and muscle tissue were examined and used to fit an animal‐adapted 3‐phase metabolic model of oxygen consumption. CBF was determined with an independent washout method. Finally, body oxygen metabolic rate was calculated using a global steady‐state approach. Results Cerebral metabolic rate of oxygen consumption was 1.97 ± 0.19 μmol/g/min on average. The resting metabolic rate of oxygen consumption in skeletal muscle was 0.32 ± 0.12 μmol/g/min and >6 times lower than cerebral metabolic rate of oxygen consumption. Global oxygen consumed by the body was 24.2 ± 3.6 mL O2/kg body weight/min. CBF was estimated to be 0.28 ± 0.02 mL/g/min and 0.34 ± 0.06 mL/g/min for the N2 and N2O ventilation condition, respectively. Conclusion We have evaluated the feasibility of 17O MRSI for imaging and quantifying the oxygen consumption rate in low metabolizing organs such as the skeletal muscle at rest. Additionally, we have shown that CBF is slightly increased in the case of ventilation with N2O. We expect this study to be beneficial to the application of 17O MRSI to a wider range of organs, although further validation is advised.
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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) | 0.001 | 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".