Edited MRS is sensitive to changes in lactate concentration during inspiratory hypoxia
Bibliographic record
Abstract
PURPOSE: To demonstrate the application of Mescher-Garwood (MEGA) point-resolved spectroscopy sequence (PRESS) editing to the detection of lactate in the brain at 3T and to investigate changes in lactate concentration associated with inspiratory gas challenges. MATERIALS AND METHODS: Edited lactate measurements were made in six healthy volunteers while the subjects breathed normoxic (21% O(2)), hypoxic (12% O(2)), and hyperoxic (40% O(2)) gas mixtures. Lactate concentration was quantified relative to the unsuppressed water signal from the same volume. RESULTS: Lactate concentration was elevated in all subjects during hypoxia in a highly significant fashion (mean increase = 39%; P = 0.0003). There was no significant change seen in hyperoxia. CONCLUSION: MEGA-PRESS editing at 3T is sufficiently sensitive to detect lactate in the healthy brain with good signal-to-noise ratio (SNR), and can be used to investigate changes in cerebral metabolism arising during inspiratory gas challenges.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".