Cell culture of differentiated human salivary epithelial cells in a serum‐free and scalable suspension system: The salivary functional units model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Saliva aids in digestion, lubrication, and protection of the oral cavity against dental caries and oropharyngeal infections. Reduced salivary secretion, below an adequate level to sustain normal oral functions, is unfortunately experienced by head and neck cancer patients treated with radiotherapy and by patients with Sjögren's syndrome. No disease-modifying therapies exist to date to address salivary gland hypofunction (xerostomia, dry mouth) because pharmacotherapies are limited by the need for residual secretory acinar cells, which are lost at the time of diagnosis, whereas novel platforms such as cell therapies are yet immature for clinical applications. Autologous salivary gland primary cells have clinical utility as personalized cell therapies, if they could be cultured to a therapeutically useful mass while maintaining their in vivo phenotype. Here, we devised a serum-free scalable suspension culture system that grows partially digested human salivary tissue filtrates composing of acinar and ductal cells attached to their native extracellular matrix components while retaining their 3D in vivo spatial organization; we have coined these salivary spheroids as salivary functional units (SFU). The proposed SFU culture system was sub-optimal, but we have found that the cells could still survive and grow into larger salivary spheroids through cell proliferation and aggregation for 5 to 10 days within the oxygen diffusion rates in vitro. In summary, by using a less disruptive cell isolation procedure as the starting point for primary cell culture of human salivary epithelial cells, we demonstrated that aggregates of cells remained proliferative and continued to express acinar and ductal cell-specific markers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it