Development of Flow Based In vivo NMR for Understanding Metabolic Indicators of Stress
Bibliographic record
Abstract
In vivo nuclear magnetic resonance (NMR) has proven to be an excellent tool for probing complex biological processes inside living organisms. In order for 2D NMR work in this thesis to be carried out, model organisms routinely used in aquatic toxicity screening, including D.magna and H.azteca were applied in these studies once fully 13C enriched (99 % 13 C enrichment). In Chapter 2, a selective NMR experiment, termed the (H)CbCa(COCa)Ha experiment, was implemented here to explicitly target free amino acids inside living 13C enriched D.magna. By applying this experiment, it was also possible to discern oxidative stress inside the organisms due to sub-lethal BPA (bisphenol-A) exposure. In Chapter 3, a quantitative 2D NMR experiment (perfect-HSQC) was tested and the results showed that it could be used to achieve excellent quantitation of key metabolites inside living 13C enriched D.magna when integrated with 2D ERETIC (Electronic Reference To access In vivo Concentrations) protocols. In Chapter 4, a 1H detect experiment combined with a 13C filter that only detects the probe molecules (1H attached to 12C) was successfully used to follow lipid assimilation (12C algal food source, C.reinhardtii) and biotransformation (natural abundance nicotine) in vivo using living 13C enriched D.magna and living 13C enriched H.azteca respectively. For Chapter 5, a time resolved variant of the standard (H)CbCa(COCa)Ha NMR experiment used in Chapter 2 was applied here using living 13 C enriched D.magna and BPA as the model contaminant. By simultaneously tracking the metabolic flux in the 13C enriched daphnids along with a concentration sweep of > 1000 different concentration measurements (of BPA) in a single NMR experiment, it was then possible to discern the lowest concentration that elicits a statistically significant response in the organism’s metabolome. This is denoted here as the LCDR and is an important metric for establishing proper environmental policies and regulations. In summary, the four research-based Chapters that constitute this thesis should help in the future to produce a more robust, and meaningful foundation for understanding aquatic toxicity in general.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".