Caveolin-initiated macropinocytosis is required for efficient silica nanoparticles’ transcytosis across the alveolar epithelial barrier
Why this work is in the frame
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Bibliographic record
Abstract
Removal of particulate materials that would otherwise cumulate within the airspace and hinder the gas exchange is one of the central processes of maintaining lung homeostasis. While the importance of the particle uptake by alveolar macrophages and their expulsion via the airways mucociliary escalator is well established, very little is known about the alternative route for removing the particles via direct crossing the lung epithelium for transfer into the pulmonary lymph and bloodstream. This study dissected sequential mechanisms involved in nanoparticle transcytosis through the alveolar epithelial cell layer. By a combination of live cell, super resolution, and electron microscopy and RNA interference study, we have dissected temporal steps of nanoparticle transcytosis through alveolar epithelium. Our study revealed that caveolin is essential for the firm adhesion of the silica nanoparticle agglomerates to the apical membrane and their subsequent rapid internalization with the help of macropinocytic elements C-terminal-binding protein1 and Rabankyrin-5 but not dynamin. Actin, but not microtubules, played a major role in nanoparticle uptake and subsequent transportation. The compartments with nanoparticles were tethered to trans-Golgi network to be jointly transported along actin stress fibers across the cytoplasm, employing a myosin-dependent mechanism. The trans-Golgi nanoparticle transport machinery was positive to Rab6A, a marker linked to vesicle exocytosis. Exocytosis was primarily occurring at the basolateral plane of the alveolar epithelial cells. The high-proficiency novel caveolin and Rabankyrin-5 associated uptake and transcellular transport of nanoparticles across the AEC barrier supports its importance in clearance of amorphous silica and other types of non-inflammatory nanoparticles that are rapidly removed from the lungs following their inhalation.
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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 | 0.002 | 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 | 0.002 | 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 it