Droplet probe: coupling chromatography to the <i>in situ</i> evaluation of the chemistry of nature
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Bibliographic record
Abstract
Covering: up to 2019The chemistry of nature can be beautiful, inspiring, beneficial and poisonous, depending on perspective. Since the isolation of the first secondary metabolites roughly two centuries ago, much of the chemical research on natural products has been both reductionist and static. Typically, compounds were isolated and characterized from the extract of an entire organism from a single time point. While there could be subtexts to that approach, the general premise has been to determine the chemistry with very little in the way of tools to differentiate spatial and/or temporal changes in secondary metabolite profiles. However, the past decade has seen exponential advances in our ability to observe, measure, and visualize the chemistry of nature in situ. Many of those techniques have been reviewed in this journal, and most are tapping into the power of mass spectrometry to analyze a plethora of sample types. In nearly all of the other techniques used to study chemistry in situ, the element of chromatography has been eliminated, instead using various ionization sources to coax ions of the secondary metabolites directly into the mass spectrometer as a mixture. Much of that science has been driven by the great advances in ambient ionization techniques used with a suite of mass spectrometry platforms, including the alphabet soup from DESI to LAESI to MALDI. This review discusses the one in situ analysis technique that incorporates chromatography, being the droplet-liquid microjunction-surface sampling probe, which is more easily termed "droplet probe". In addition to comparing and contrasting the droplet probe with other techniques, we provide perspective on why scientists, particularly those steeped in natural products chemistry training, may want to include chromatography in in situ analyses. Moreover, we provide justification for droplet sampling, especially for samples with delicate and/or non-uniform topographies. Furthermore, while the droplet probe has been used the most in the analysis of fungal cultures, we digest a variety of other applications, ranging from cyanobacteria, to plant parts, and even delicate documents, such as herbarium specimens.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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