<i>In Vitro</i> Model for Studying Malignancy Associated Changes
Bibliographic record
Abstract
Malignancy associated changes (MAC) can be defined as subtle morphological and physiologic changes that are found in ostensibly normal cells of patients harboring malignant disease. It has been postulated that MAC have a potential to become a useful tool in detection, diagnosis and prognosis of malignant diseases. An in vitro cell culture model system was designed to study interactions between non-small cell lung cancer (NSCLC) and the normal bronchial epithelium of the human respiratory tract in vivo to see if the MAC-like phenomenon can be detected in such a system. In this study we examined changes in nuclear features of normal human bronchial epithelial cells (NHBE) when they were co-cultured with cells derived from a lung cancer cell line NCI-H460. Using discriminant function analysis, nuclear features were determined which allow maximal discrimination between normal cells incubated with or without cancerous cells. Our results demonstrate that MAC appear to be specific to changes induced by malignancy, and that these changes differ from those induced by growth factors in the serum. This study provides evidence in support to the hypothesis that MAC are induced by a soluble factor(s) released by malignant cells. Colour figure can be viewed on http://www.esacp.org/acp/2003/25-2/sun.htm
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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) | 0.001 | 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 | 0.001 |
| 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".