Pre-Clinical Translation of Second Harmonic Microscopy of Meniscal and Articular Cartilage Using a Prototype Nonlinear Microendoscope
Bibliographic record
Abstract
Previous studies using nonlinear microscopy have demonstrated that osteoarthritis (OA) is characterized by the gradual replacement of Type II collagen with Type I collagen. The objective of this study was to develop a prototype nonlinear laser scanning microendoscope capable of resolving the structural differences of collagen in various orthopaedically relevant cartilaginous surfaces. The current prototype developed a miniaturized femtosecond laser scanning instrument, mounted on an articulated positioning system, capable of both conventional arthroscopy and second-harmonic laser-scanning microscopy. Its optical system includes a multi-resolution optical system using a gradient index objective lens and a customized multi-purpose fiber optic sheath to maximize the collection of backscattered photons or provide joint capsule illumination. The stability and suitability of the prototype arthroscope to approach and image cartilage were evaluated through preliminary testing on fresh, minimally processed, and partially intact porcine knee joints. Image quality was sufficient to distinguish between hyaline cartilage and fibrocartilage through unique Type I and Type II collagen-specific characteristics. Imaging the meniscus revealed that the system was able to visualize differences in the collagen arrangement between the superficial and lamellar layers. Such detailedin vivoimaging of the cartilage surfaces could obviate the need to perform biopsies forex vivohistological analysis in the future, and provide an alternative to conventional external imaging to characterize and diagnose progressive and degenerative cartilage diseases such as OA. Moreover, this system is readily customizable and may provide a suitable and modular platform for developing additional tools utilizing femtosecond lasers for tissue cutting within the familiar confines of two or three portal arthroscopy techniques.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".