Labial Stem Cell Extract Mitigates Injury to Irradiated Salivary Glands
Bibliographic record
Abstract
Stem cell–based therapies could provide a permanent treatment for salivary gland (SG) hypofunction caused by ionizing radiation (IR) injury. However, current challenges for SG stem cells to reach the clinic include surgical invasiveness, amount of tissue needed, cell delivery, and storage methods. The objective of this study was to develop a clinically less invasive method to isolate and expand human SG stem cells and then to obtain a cell-free extract to be used as a therapy for IR-injured SGs. Human labial glands were biopsied, and labial stem cells (LSCs) were expanded by explant culture. The LSC extract (LSCE) was obtained by releasing the cellular components after 3 freeze-thaw cycles and 17,000 g force centrifugation. LSCE was injected intravenously into mice that had their SGs injured with 13-Gy IR. Positive (non-IR) and negative (IR) control mice received injections of saline (vehicle control). Three pieces of labial glands (0.1 g weight) could expand 1 to 2 million cells. LSCs had a doubling time of 18.8 h; could differentiate into osteocytes, adipocytes, and chondrocytes; and were positive for mesenchymal stem cell markers. Both angiogenic (FGF-1, FGF-2, KGF, angiopoietin, uPA, VEGF) and antiangiogenic factors (PAI-1, TIMP-1, TSP-1, CD26) were detected in LSCE. In addition, some angiogenic factors (PEDF, PTX3, VEGF) possessed neurotrophic functions. Mice treated with LSCE had 50% to 60% higher salivary flow rate than saline-treated mice at 8 and 12 wk post-IR. Saliva lag time measurements also confirmed that LSCE restored SG function. Histologic analyses of parotids and submandibular glands reported comparable numbers of acinar cells, blood vessels, and parasympathetic nerves and cell proliferation rates in sham IR and LSCE-treated mice, though significantly lower in saline-treated mice. An explant culture method can harvest a large number of LSCs from small pieces of labial glands. LSCE showed clinical potential to mitigate IR-injured SGs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".