Minimally invasive imaging method based on second harmonic generation and multiphoton excitation fluorescence in translational respiratory research
Bibliographic record
Abstract
For translational respiratory research including in the development of clinical diagnostic tools, a minimally invasive imaging method, which can provide both cellular and extracellular structural details with sufficient specificity, sensitivity and spatial resolution, is particularly useful. Multiphoton microscopy causes excitation of endogenously fluorescent macromolecular systems and induces highly specific second harmonic generation signals from non-centrosymmetric macromolecules such as fibrillar collagens. Both these signals can be captured simultaneously to provide spatially resolved 3D structural organization of extracellular matrix as well as the cellular morphologies in their native states. Besides briefly discussing the fundamentals of multiphoton excitation fluorescence and harmonic generation signals and the instrumentation details, this review focuses on the specific applications of these imaging modalities in lung structural imaging, particularly morphological features of alveolar structures, visualizing and quantifying extracellular matrix remodelling accompanying emphysematous destructions as well as the IPF, detecting lung cancers and the potential use in the tissue engineering applications.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".