Comparison of two-dimensional and three-dimensional culture systems and their responses to chemotherapy in cells representing disease progression of high-grade serous ovarian cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
High-grade serous cancer is the most common type of ovarian cancer and is usually diagnosed at advanced stages with high mortality due to recurrence and eventual resistance to standard platinum therapy. The aim of this study was to compare two-dimensional (2D) versus tridimensional (3D) cell culture as a preclinical model of response to carboplatin, paclitaxel and niraparib using PEO1, PEO4 and PEO6 cell lines, which were generated from the same patient along disease progression. Morphologically, cells formed flat adherent layers versus spheroidal structures with different compaction patterns in 2D and 3D respectively. In 2D, apoptosis was rare whereas in 3D cells formed a multilayered structure with an outer layer of live proliferating cells and an inner core of apoptotic cells. Furthermore, a differential capacity to produce ATP was observed among the cell lines in 3D but not in 2D. While response to carboplatin, paclitaxel and niraparib in both settings followed a similar trend, a lower sensitivity was observed in 3D with respect to 2D. Overall, 3D cell culture is likely more reflective of the in vivo cellular tumor behavior and more suitable of therapeutic evaluation given its added complexity absent in 2D. • In an anchorage-free 3D model, cells formed spheroidal structures with different compaction patterns. • In 3D, cells mimicked a poor vascularized tumor by acquiring a viability gradient. • A dissimilar capacity of the cells to produce ATP along disease progression was found in 3D. • Cells in 3D culture conditions had a lower sensitivity to chemotherapeutic agents than in 2D.
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.
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 | 0.000 |
| 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) | 0.000 | 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 it