In Vivo Ultraslow MAS <sup>2</sup>H/<sup>13</sup>C NMR Emphasizes Metabolites in Dynamic Flux
Bibliographic record
Abstract
NMR spectroscopy is a powerful tool for metabolite screening, and owing to its noninvasive nature, it can be applied in vivo. However, the magnetic susceptibility mismatches within the intact organisms, lead to broad signals and loss of spectral information. Magic-angle spinning (MAS) is the most robust way to reduce these distortions, enhancing line shapes and providing a wealth of metabolic information, in vivo. Unfortunately, mainly due to overlapping water sidebands, relatively fast spinning is required (∼2500 Hz), which induces stress on the organism, leading to mortality within a relatively short time frame. Here, a novel approach is introduced utilizing 2H/13C isotopic enrichment that demonstrates the following advantages. (1) 2H is a quadrupolar nucleus; hence, in 2H/13C two-dimensional (2D) NMR only the most dynamic molecules (mobile metabolites) are observed in vivo, whereas structural components are broadened beyond detection. In turn, this results in a well-resolved and unique window into the dynamic metabolite pool that includes newly released or synthesized molecules correlated to a biological response/process. (2) 2H shares the same chemical shift window as 1H, making assignment relatively easy. (3) 2H detection reduces problems associated with the water peak, and as the dynamic molecules are selectively detected, no sidebands are observed. (4) As such, samples can be spun slowly (50 Hz), reducing the stress and increasing 100% survivability to 24 h for Daphnia magna and 48 h for Hyalella azteca. To our knowledge, this represents the only MAS-based NMR approach that can provide high-resolution 2D NMR in vivo metabolic fingerprint at slow spinning rates.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".