Review and perspectives on the applications of mass spectrometry imaging under ambient conditions
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
Ambient mass spectrometry (AMS)-based techniques are performed under ambient conditions in which the ionization and desorption occur in the open environment allowing the direct analysis of molecules with minimal or no sample preparation. A selected group of AMS techniques demonstrate imaging capabilities that can provide information about the localization of molecules on complex sample surfaces such as biological tissues. 2D, 3D, and multimodal imaging have unlocked an array of applications to systematically address complex problems in many areas of research such as drug monitoring, natural products, forensics, and cancer diagnostics. In the present review, we summarize recent advances in the field with respect to the implementation of new ambient ionization techniques and current applications in the last 5 years. In more detail, we mainly focus on imaging applications in topics related to animal whole bodies and tissues, single cells, cancer diagnostics and biomarkers, microbial cultures and co-cultures, plant and natural product metabolomics, and forensic applications. Finally, we discuss new areas of research, future perspectives, and the overall direction that the field may take in the years to come.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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