In vivo proton observed carbon edited (POCE) <sup>13</sup>C magnetic resonance spectroscopy of the rat brain using a volumetric transmitter and receive‐only surface coil on the proton channel
Bibliographic record
Abstract
Purpose In vivo carbon‐13 (13C) MR spectroscopy (MRS) is capable of measuring energy metabolism and neuroenergetics, noninvasively in the brain. Indirect (1H‐[13C]) MRS provides sensitivity benefits compared with direct 13C methods, and normally includes a 1H surface coil for both localization and signal reception. The aim was to develop a coil platform with homogenous and use short conventional pulses for short echo time proton observed carbon edited (POCE) MRS. Methods A 1H‐[13C] MRS coil platform was designed with a volumetric resonator for 1H transmit, and surface coils for 1H reception and 13C transmission. The Rx‐only 1H surface coil nullifies the requirement for a T/R switch before the 1H preamplifier; the highpass filter and preamplifier can be placed proximal to the coil, thus minimizing sensitivity losses inherent with POCE‐MRS systems described in the literature. The coil platform was evaluated with a PRESS‐POCE sequence (TE = 12.6 ms) on a rat model. Results The coil provided excellent localization, uniform spin nutation, and sensitivity. 13C labeling of Glu‐H4 and Glx‐H3 peaks, and the Glx‐H2 peaks were observed approximately 13 and 21 min following the infusion of 1‐13C glucose, respectively. Conclusion A convenient and sensitive platform to study energy metabolism and neurotransmitter cycling is presented. Magn Reson Med 79:628–635, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".