Cross‐contamination of the human salivary gland <scp>HSG</scp> cell line with HeLa cells: A <scp>STR</scp> analysis study
Bibliographic record
Abstract
OBJECTIVES: The human salivary gland (HSG) cell line, labeled as a submandibular ductal cell line, is commonly used as in vitro models to study radiation therapy, Sjögren's syndrome, pleomorphic adenoma, mucocele, epithelial-to-mesenchymal transition, and epigenetics. However, the American Type Culture Collection (ATCC) has recently released a list of cross-contaminated cell lines that included HSG. Despite this notice, some research laboratories still use HSG as a salivary cell model. Therefore, this study examined the authenticity of HSG sampled from three different laboratories. METHODS: DNA was extracted from HSG and additional salivary cell lines (NS-SV-AC, NS-SV-DC, A253, HSY) and submitted for cell line authentication with short tandem repeat (STR) analysis. RESULTS: All HSG samples had STR profiles indicating >80% match with HeLa in both the ATCC and Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSMZ) databases. This confirmed that HSG sampled from three different laboratories and HSY shared a common ancestry (host) with HeLa, whereas NS-SV-AC, NS-SV-DC, and A253 had unique STR profiles. CONCLUSION: Short tandem repeat analysis revealed that HSG was contaminated by the HeLa cell line. Furthermore, because genotyping of the original HSG cell line was not performed during its establishment, it will be difficult to authenticate an uncontaminated sample of HSG.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".