Direct Analysis and MALDI Imaging of Formalin-Fixed, Paraffin-Embedded Tissue Sections
Why this work is in the frame
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Bibliographic record
Abstract
Formalin fixation, generally followed by paraffin embedding, is the standard and well-established processing method employed by pathologist. This treatment conserves and stabilizes biopsy samples for years. Analysis of FFPE tissues from biopsy libraries has been, so far, a challenge for proteomics biomarker studies. Herein, we present two methods for the direct analysis of formalin-fixed, paraffin-embedded (FFPE) tissues by MALDI-MS. The first is based on the use of a reactive matrix, 2,4-dinitrophenylhydrazine, useful for FFPE tissues stored less than 1 year. The second approach is applicable for all FFPE tissues regardless of conservation time. The strategy is based on in situ enzymatic digestion of the tissue section after paraffin removal. In situ digestion can be performed on a specific area of the tissue as well as on a very small area (microdigestion). Combining automated microdigestion of a predefined tissue array with either in situ extraction prior to classical nanoLC/MS-MS analysis or automated microspotting of MALDI matrix according to the same array allows the identification of both proteins by nanoLC-nanoESI and MALDI imaging. When adjacent tissue sections are used, it is, thus, possible to correlate protein identification and molecular imaging. These combined approaches, along with FFPE tissue analysis provide access to massive amounts of archived samples in the clinical pathology setting.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it