An <sup>1</sup>H-MRS evaluation of the phosphocreatine/creatine pool (tCr) in human muscle
Bibliographic record
Abstract
The human gastrocnemius was examined with and without creatine supplementation under the conditions of rest, ischemic fatigue (IF), and recovery to perturb the pool sizes and equilibrium between phosphocreatine (PCr) and creatine (Cr). (1)H- and (31)P-magnetic resonance spectroscopy (MRS) were used to examine the total creatine (tCr) pool in each of the metabolic states. (31)P-MRS monitored the depletion of the PCr peak during IF to <5% of that at rest. (1)H-MRS focused on the tCr methyl peak at 3.02 ppm (dipolar coupled triplet), at which point it was expected that the triplet peak intensity would be similar both in IF and rest. Initial (1)H-MRS data showed the peak intensity during IF decreased, suggesting a change in tCr pool size. Subsequent studies of transverse relaxation time (T(2)) revealed that this decline was primarily due to a more rapid T(2) decay of the tCr peak in IF (T(2) approximately 40 ms) compared with at rest (T(2) approximately 162 ms). Because Cr is the major contributor to tCr in IF, it is possible that there is a pool of Cr displaying reduced mobility in vivo. Moreover, the residual dipolar coupled triplet observed at rest collapsed into a broad singlet during IF, suggestive of significant changes in the ordered environment experienced at rest for PCr compared with when it is converted to Cr during IF. In addition, these data suggest that in (1)H-MRS studies whose goals include quantitative estimates of tCr pool sizes, standardized metabolic conditions or careful T(2) evaluations will be required.
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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) | 0.000 | 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".