Multiscale investigation of collagen structure in human skin and gel matrices using polarization resolved second harmonic generation microscopy
Bibliographic record
Abstract
Abstract Collagen is critical to the structure and function of skin tissues, with the collagen I/III ratios influencing fibrillogenesis, fiber organization, and skin mechanics. Abnormal collagen organization, such as in fibrosis or scar tissue, compromises both skin functionality and aesthetics. In this study, we employed label-free polarization resolved second harmonic generation (PSHG) microscopy to investigate collagen structure in artificial collagen matrices with various Col I/III ratios at the fibril scale ( $$\sim$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mo>∼</mml:mo> </mml:math> 1 to $$3\,\upmu \hbox {m}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>3</mml:mn> <mml:mspace/> <mml:mi>μ</mml:mi> <mml:mtext>m</mml:mtext> </mml:mrow> </mml:math> ) and in ex vivo human healthy and scarred skin at the fiber scale ( $$\sim 10$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>∼</mml:mo> <mml:mn>10</mml:mn> </mml:mrow> </mml:math> to $$20\,\upmu \hbox {m}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>20</mml:mn> <mml:mspace/> <mml:mi>μ</mml:mi> <mml:mtext>m</mml:mtext> </mml:mrow> </mml:math> ). Complementary third harmonic generation (THG) microscopy provided additional structural information. Our results indicate that an increasing Col I/III ratio is associated with longer fibril length, higher PSHG intensity, and a reduced effective $$\alpha$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>α</mml:mi> </mml:math> -helix pitch angle of fibrils. In pure Col I, the effective $$\alpha$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>α</mml:mi> </mml:math> -helix pitch angle is determined to be $$47.72^{\circ }$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>47</mml:mn> <mml:mo>.</mml:mo> <mml:msup> <mml:mn>72</mml:mn> <mml:mo>∘</mml:mo> </mml:msup> </mml:mrow> </mml:math> . These observations indicate alterations in fibril assembly. Furthermore, although the $$\alpha$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>α</mml:mi> </mml:math> -helix pitch angle of fibers in both healthy and scarred skin was approximately $$46.7^{\circ }$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>46</mml:mn> <mml:mo>.</mml:mo> <mml:msup> <mml:mn>7</mml:mn> <mml:mo>∘</mml:mo> </mml:msup> </mml:mrow> </mml:math> , healthy skin exhibited $$24\%$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>24</mml:mn> <mml:mo>%</mml:mo> </mml:mrow> </mml:math> greater variability in fiber orientation, suggesting a more randomized organization compared to scar tissue. THG imaging further revealed a higher cellular density in scar tissue, consistent with the inflammatory activity associated with wound healing. Immunohistochemical (IHC) staining using dermatansulphate and Col III-specific antibodies confirmed that the Col I/III ratio is higher in healthy skin (2.2) than in scarred skin (1.6). These findings underscore the potential of PSHG microscopy for label-free, quantitative assessment of collagen structure across multiple scales, with THG offering complementary cellular insights. This integrated approach represents a promising strategy for real-time, in vivo monitoring and automated quantification of collagen organization in clinical applications, including dermatology, burn treatment, and fibrosis monitoring.
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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 | 0.000 |
| 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) | 0.000 | 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".