Minimizing Visceral Fat Delocalization on Tissue Sections with Porous Aluminum Oxide Slides for Imaging Mass Spectrometry
Bibliographic record
Abstract
A high correlation of bioanalytes with their corresponding histologies is the landmark feature of matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry (IMS). Lipids are one of the most studied classes of biomolecules, and monitoring lipid distribution and abundance in tissue samples can lead to major inputs in the understanding of disease. Lipid delocalization and ion suppression are two major effects that can lead to misinterpretation of the IMS results to an unaware analyst. We and others have observed that tissue specimens containing high amounts of visceral fat are challenging to analyze because of fat delocalization on and off section leading to significant triacylglyceride and phospholipid delocalization and major ion suppression effects. In this work, we introduce a novel and easy to produce reusable porous aluminum oxide sample slide that minimizes visceral fat delocalization after thaw-mounting of tissue sections. Using fatty mouse kidneys and other tissues, we demonstrate its efficacy in minimizing delocalization of triacylglycerides, the primary constituents of fat, and the resulting beneficial effects on phospholipid MALDI IMS.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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 teacher head, 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".