Proton <i>T</i><sub>1</sub> relaxation times of cerebral metabolites differ within and between regions of normal human brain
Bibliographic record
Abstract
Saturation recovery spectra (STEAM) were acquired at 1.5 T with 7 TRs ranging from 530 to 5000 ms and a constant TE of 30 ms in voxels (7.2 ml) located in occipital grey, parietal white and frontal white matter (10 subjects each location). Spectra were also acquired at 7, 21 and 37 degrees C from separate 100 mm solutions of inositol (Ins), choline-containing compounds (Cho), N-acetyl-aspartate (NAA) and creatine. Simulations of T(1) fits with 2, 3 and 7 TRs demonstrated that at typical SNR there is potential for both inaccurate and biased results. In vivo, different metabolites had significantly different T(1)s within the same brain volume. The same order from shortest to longest T(1) (Ins, Cho, NAA, creatine) was found for all three brain regions. The order (Ins, NAA, creatine, Cho) was found in the metabolite solutions and was consistent with a simple model in which T(1) is inversely proportional to molecular weight. For all individual metabolites, T(1) increased from occipital grey to parietal white to frontal white matter. This study demonstrates that, in spectra acquired with TR near 1 s, T(1) weightings are substantially different for metabolites within a single tissue and also for the same metabolites in different tissues.
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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 | 0.001 |
| 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) | 0.002 | 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".