Primary Culture of Polarized Human Salivary Epithelial Cells for Use in Developing an Artificial Salivary Gland
Bibliographic record
Abstract
Therapeutic irradiation for head and neck cancer, and the autoimmune disease Sjogren's syndrome, lead to loss of salivary parenchyma. They are the two main causes of irreversible salivary gland hypofunction. Such patients cannot produce adequate levels of saliva, leading to considerable morbidity. We are working to develop an artificial salivary gland for such patients. A major problem in this endeavor has been the difficulty in obtaining a suitable autologous cellular component. This article describes a method of culturing and expanding primary salivary cells obtained from human submandibular glands (huSMGs) that is serum free and yields cells that are epithelial in nature. These include morphological (light and transmission electron microscopy [TEM]), protein expression (immunologically positive for ZO-1, claudin-1, and E-cadherin), and functional evidence. Under confocal microscopy, huSMG cells show polarization and appropriately localize tight junction proteins. TEM micrographs show an absence of dense core granules, but confirm the presence of tight and intermediate junctions and desmosomes between the cells. Functional assays showed that huSMG cells have high transepithelial electrical resistance and low rates of paracellular fluid movement. Additionally, huSMG cells show a normal karyotype without any morphological or numerical abnormalities, and most closely resemble striated and excretory duct cells in appearance. We conclude that this culture method for obtaining autologous human salivary cells should be useful in developing an artificial salivary gland.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".