NMR assignment of the<i>in vivo</i>daphnia magna metabolome
Bibliographic record
Abstract
Daphnia (freshwater fleas) are among the most widely used organisms in regulatory aquatic toxicology/ecology, while their recent listing as an NIH model organism is stimulating research for understanding human diseases and processes. Daphnia are small enough to fit inside high field NMR spectrometers and can be kept alive indefinitely using flow systems that deliver food and oxygen. As such, in vivo NMR holds the potential to monitor when/if environmental stress is occurring, understand "why" chemicals are toxic (biochemical pathways impacted and toxic-mode-of-action), and differentiate between a temporary flux response (i.e. return to homeostasis) and a permanent change in biochemistry (likely a precursor to disease). At present however, such studies are limited as the in vivo NMR data of Daphnia are highly complex and the lack of spectral assignments makes extracting metabolic information difficult. In this study, Daphnia are 13C enriched to >97% 13C and numerous 1H and 13C 1D, 2D, and 3D NMR approaches are combined to provide, as complete as possible, an assignment of the Daphnia magna metabolome in vivo. Assignments are transferred (where possible) back to line narrowed susceptibility suppressed 1H 1D NMR spectra in order to permit the maximum amount of information to be gained in the future without the need for 13C enrichment. To our knowledge, this work represents the first time a comprehensive metabolic assignment of any small living organism has been performed using high field flow-based NMR.
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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 | 0.001 |
| 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".