Mapping the fly Malpighian tubule lipidome by imaging mass spectrometry
Bibliographic record
Abstract
Matrix-assisted laser/desorption ionization imaging mass spectrometry (MALDI IMS) is an analytical technique for understanding the spatial distribution of biomolecules across a sample surface. Originally employed for mammalian tissues, this technology has been adapted to study specimens as diverse as microbes and cell cultures, food such as strawberries, and invertebrates including the vinegar fly Drosophila melanogaster. As an ideal model organism, Drosophila has brought greater understanding about conserved biological processes, organism development, and diseased states and even informed management practices of agriculturally and environmentally important species. Drosophila displays anatomically separated renal (Malpighian) tubules that are the physiological equivalent to the vertebrate nephron. Insect Malpighian tubules are also responsible for pesticide detoxification. In this article, we first describe an effective workflow and sample preparation method to study the phospholipid distribution of the Malpighian tubules that initially involves the manual microdissection of the tubules in saline buffer followed by a series of washes to remove excess salt and enhances the phospholipid signals prior to matrix deposition and IMS at 25-μm spatial resolution. We also established a complementary methodology for lipid IMS analysis of whole-body fly sections using a dual-polarity data acquisition approach at the same spatial resolution after matrix deposition by sublimation. Both procedures yield rich signal profiles from the major phospholipid classes. The reproducibility and high-quality results offered by these methodologies enable cohort studies of Drosophila through MALDI IMS.
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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 | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".