Environmental metabolomics: an emerging approach to study organism responses to environmental stressors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Metabolomics is the analysis of endogenous and exogenous low molecular mass metabolites within a cell, tissue, or biofluid of an organism in response to an external stressor. The sub-discipline of environmental metabolomics is the application of metabolomic techniques to analyze the interactions of organisms with their environment. There has been a rapid growth in environmental metabolomics over the past decade. This growth can be attributed to the comprehensive and rapid nature of nontargeted metabolomics and the ability to generate hypotheses involving complex environmental stressors, especially when the mode of action is unknown. Using a wide variety of model organisms, metabolomic studies have detected stress from abiotic factors such as xenobiotic exposure and temperature shifts as well as biotic stressors such as herbivory and competition. Nuclear magnetic resonance (NMR)-based metabolomics has been the dominant analytical platform used for environmental metabolomics studies, owing to its nonselectivity and ease of sample preparation. However, the number of mass spectrometry (MS)-based metabolomic studies is also increasing rapidly, owing to its high sensitivity for the detection of trace levels of metabolites. In this review, we provide an overview of the general experimental design, extraction methods, analytical instrumentation, and statistical methods used in environmental metabolomics. We then highlight some of the recent studies that have used metabolomics to elucidate hitherto unknown biochemical modes of actions of various environmental stressors to both terrestrial and aquatic organisms, as well as identify potential metabolite shifts as early bioindicators of these stressors. Through this, we emphasize the immense potential and versatility of environmental metabolomics as a routine tool for characterizing the responses of organisms to numerous types of environmental stressors.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 it