Minimally invasive measurement of carotid artery and brain temperature in the mouse
Bibliographic record
Abstract
Abstract Purpose Brain temperature is tightly regulated and reflects a balance between cerebral metabolic heat production and heat transfer between the brain, blood, and external environment. Blood temperature and flow are critical to the regulation of brain temperature. Current methods for measuring in vivo brain and blood temperature are invasive and impractical for use in small animals. This work presents a methodology to measure both brain and arterial blood temperature in anesthetized mice by MRI using a paramagnetic lanthanide complex: thulium tetramethyl‐1,4,7,10‐tetraazacyclododecane‐1,4,7,10‐tetraacetic acid (TmDOTMA‐). Methods A phase‐based imaging approach using a multi‐TE gradient echo sequence was used to measure the temperature‐dependent chemical shift difference between thulium tetramethyl‐1,4,7,10‐tetraazacyclododecane‐1,4,7,10‐tetraacetic acid methyl protons and water, and from this calculate absolute temperature using calibration data. Results In a series of mice in which core body temperature was held stable but at different values within the range of 33° to 37°C, brain temperature away from the midline was independent of carotid artery blood temperature. In contrast, midline voxels correlated with carotid artery blood temperature, likely reflecting the preponderance of larger arteries and veins in this region. Conclusion These results are consistent with brain temperature being actively regulated. A limitation of the present implementation is that the spatial resolution in the brain is coarse relative to the size of the mouse brain, and further optimization is required for this method to be applied for finer spatial scale mapping or to characterize focal pathology.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".