Latent-transforming growth factor beta-binding protein-2 (LTBP-2) is required for longevity but not for development of zonular fibers
Bibliographic record
Abstract
Latent-transforming growth factor beta-binding protein 2 (LTBP-2) is a major component of arterial and lung tissue and of the ciliary zonule, the system of extracellular fibers that centers and suspends the lens in the eye. LTBP-2 has been implicated previously in the development of extracellular microfibrils, although its exact role remains unclear. Here, we analyzed the three-dimensional structure of the ciliary zonule in wild type mice and used a knockout model to test the contribution of LTBP-2 to zonule structure and mechanical properties. In wild types, zonular fibers had diameters of 0.5-1.0 micrometers, with an outer layer of fibrillin-1-rich microfibrils and a core of fibrillin-2-rich microfibrils. LTBP-2 was present in both layers. The absence of LTBP-2 did not affect the number of fibers, their diameters, nor their coaxial organization. However, by two months of age, LTBP-2-depleted fibers began to rupture, and by six months, a fully penetrant ectopia lentis phenotype was present, as confirmed by in vivo imaging. To determine whether the seemingly normal fibers of young mice were compromised mechanically, we compared zonule stress/strain relationships of wild type and LTBP-2-deficient mice and developed a quasi-linear viscoelastic engineering model to analyze the resulting data. In the absence of LTBP-2, the ultimate tensile strength of the zonule was reduced by about 50%, and the viscoelastic behavior of the fibers was altered significantly. We developed a harmonic oscillator model to calculate the forces generated during saccadic eye movement. Model simulations suggested that mutant fibers are prone to failure during rapid rotation of the eyeball. Together, these data indicate that LTBP-2 is necessary for the strength and longevity of zonular fibers, but not necessarily for their formation.
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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 | 0.000 | 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) | 0.001 | 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 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".