Comparison of growth features and cancer stem cell prevalence in intrahepatic and extrahepatic cholangiocarcinoma cell lines
Bibliographic record
Abstract
Aim of the study: Intra- and extrahepatic cholangiocarcinoma (I-CCA and E-CCA respectively) exhibit different growth features that contribute to different clinical outcomes. Cancer stem cells (CSCs) influence tumor growth and thereby may be responsible for these differences. The aim of this study was to document and compare the growth features of human I-CCA and E-CCA cell lines and determine whether any differences observed could be explained by differences in the prevalence and/or stem cell surface marker (SCSM) expression profiles of CSCs within the tumor cell lines. Material and methods: Six CCA cells lines, three I-CCA and three E-CCA, were studied. Tumor cell growth features including cell proliferation, colony/spheroid formation, migration and invasion were documented. CSC prevalence and SCSM expression profiles were examined by flow cytometry. Results: I-CCA cells had significantly increased proliferative activity, shorter doubling times and were more invasive than E-CCA cells, while colony/spheroid formation and migration were similar in the two cell populations. There were no significant differences in CSC prevalence rates or SCSM expression profiles. Conclusions: These findings suggest that I-CCA cells proliferate at a more rapid rate and are more invasive than E-CCA cells but the differences cannot be explained by differences in the prevalence or SCSM expression profiles of CSCs within the tumor cell population.
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.
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 | 0.001 | 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 | 0.000 |
| 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 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".