Impact of adjustable cryogel properties on the performance of prostate cancer cells in 3D
Bibliographic record
Abstract
BACKGROUND: Biochemical and physical characteristics of extracellular environment play a key role in assisting cell behavior over different molecular pathways. In this study, we investigated how the presence of chemical binding sites, the pore network and the stiffness of designed scaffolds affected prostate cancer cells. METHODS: A blend of poly hydroxyethyl methacrylate-alginate-gelatin scaffold was synthesized by cryogelation process using polyethyleneglycol diacrylate (PEGda) and glutaraldehyde as cross linkers. The chemical and mechanical scaffold properties were varied by concentration of gelatin and PEGda, respectively. The pore network was modified by applying different 'freezing time'. Growth, spheroid formation and localization of androgen receptor (AR) were measured to evaluate cell response within various cryogel types. RESULTS: Insufficient porosity in combination with a brittle nature affects cell growth negatively. Spheroid size was reduced by porosity, elasticity as well as by the absence of the cell adhesive motif composed of arginine, glycine und aspartic acid (RGD). Localization of AR indicates its activity and should be under normal culture conditions in the nucleus. But in this study, we could investigate for the first time that AR remains in the cytoplasm when AR positive prostate cancer cells are cultured in scaffolds without RGD as well as in case of an insufficient pore network (total porosity under 10 %) and a too less stiffness of around 10 kPa. CONCLUSIONS: The results indicate that for getting a reliable preclinical drug screening a three-dimensional prostate model system with appropriate biochemical and physical surrounding is needed.
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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) | 0.001 | 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".