Metabolite concentrations in supraventricular white matter from teenage to early old age: A short echo time <sup>1</sup> h magnetic resonance spectroscopy (MRS) study
Bibliographic record
Abstract
BACKGROUND: Age- and sex-related changes of metabolites in healthy adult brains have been examined with different (1)H magnetic resonance spectroscopy (MRS) methods in varying populations, and with differing results. A long repetition time and short echo time technique reduces quantification errors due to T(1) and T(2) relaxation effects and makes it possible to measure metabolites with short T(2) relaxation times. PURPOSE: To examine the effect of age on the metabolite concentrations measured by (1)H MRS in normal supraventricular white matter using a long repetition time (TR) and a short echo time (TE). MATERIAL AND METHODS: Supraventricular white matter of 57 healthy subjects (25 women, 32 men), aged 13 to 72 years, was examined with a single-voxel MRS at 1.5T using a TR of 6000 ms and a TE of 22 ms. Tissue water was used as a reference in quantification. RESULTS: Myoinositol increased slightly and total N-acetyl aspartate (NAA) decreased slightly with increasing age. Glutamine/glutamate complex (Glx) showed U-shaped age dependence, with highest concentrations in the youngest and oldest subjects. No significant age dependence was found in total choline and total creatine. No gender differences were found. Macromolecule/ lipid (ML) fractions were reliably measurable only in 36/57 or even fewer subjects and showed very large deviations. CONCLUSION: The concentrations of several metabolites in cerebral supraventricular white matter are age dependent on (1)H MRS, even in young and middle-aged people, and age dependency can be nonlinear. Each (1)H MRS study of the brain should therefore take age into account, whereas sex does not appear to be so important. The use of macromolecule and lipid evaluations is compromised by less successful quantification and large variations in healthy people.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".