Abstracts from the 9th International Conference for Healthcare and Medical Students (ICHAMS)
Bibliographic record
Abstract
Melanoma, a cancer of melanocytes, is one of the most common cancers in the world.In living tissues, it grows surrounded by a 3D microenvironment, which provides physical support and determines disease progression and prognosis.The aim of this project was to determine how different melanoma cell lines M14 and SK-MEL-28 behave, grow and expand in 3D in vitro models using collagen-based scaffolds.Collagen scaffolds contained either chondroitin to mimic skin tissue, hyaluronic acid or nano-hydroxyapatite to mimic bone tissue.All tested scaffolds were populated with melanoma M14 and SK-MEL-28 cells that were left to grow for 28 days.Scaffold infiltrations by cells were assessed on day 1, 7, 14, 21 and 28.Populated scaffolds were then processed with a tissue processor, embedded in paraffin wax, sliced up with a microtome and stained with H&E followed by bright field microscopy.The images were put together in chronological order to see the growth progression.Both SK-MEL-28 and M14 cell lines have demonstrated most penetration when grown on chondroitin scaffolds, followed by hyaluronic acid scaffolds.Cells grown on nano-hydroxyapatite scaffolds showed the least colonisation and tended to accumulate around the edges of the scaffold.M14 cells growing on chondroitin scaffolds demonstrated rapid infiltration when compared with SK-MEL28 cells probably due to intrinsic aggressive growth properties.In conclusion, we have demonstrated for the first time the ability of collagen-based scaffolds to support melanoma cell growth and colonisation.Our findings can aid the development of a 3D in vitro scaffold-based platform to study melanoma biology.
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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 | 0.000 | 0.001 |
| 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 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".