Genetic Characterization of the Immortalized Human Nasopharyngeal Carcinoma Cell Line <scp>NPC</scp>/<scp>HK1</scp>
Bibliographic record
Abstract
BACKGROUND: Human nasopharyngeal carcinoma (NPC) cell lines are in vitro model systems that are widely available, easy to handle, and provide an unlimited supply of material. They also bypass ethical concerns associated with the use of primary human cells or tissue. However, many of these cell lines including 5-8F, 6-10B, CNE-1, CNE-2, HNE-1, HONE-1, SUNE1, SUNE2, and NPC-TW01 have been shown to be misidentified or cross-contaminated. While simple molecular genotyping techniques such as short tandem repeat profiling of human cell lines are available to confirm cell line identity, scientists often do not implement strategies to avoid misidentification. This has resulted in a large volume of publications containing incorrect information. METHODS: In this paper, we have established a cell line karyogram that contains several marker chromosomes and a set of typical aberrations characteristic of NPC/HK1. RESULTS AND CONCLUSIONS: Combined with the typical multiloci short tandem repeat signature of NPC/HK1, the cytogenetic analysis provides an effective means to avoid unreliable experimental outcomes and scientific misinterpretation.
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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 | 0.000 |
| 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".