Highly Concentrated Nitrogen‐Doped Carbon Nanotubes in Alginate–Gelatin 3D Hydrogels Enable in Vitro Breast Cancer Spheroid Formation
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
Carbon nanotubes’ (CNTs) physicochemical and mechanical properties make them ideal reinforcement materials for hydrogels, but distributing CNTs homogeneously in hydrogels remains a challenge. Chemical modifications to CNTs are used to facilitate nanomaterial dispersion, thus improving hydrogels’ physicochemical properties. Among CNTs, nitrogen‐doped CNTs (CN x ) possess both great dispersibility in solution and biocompatibility properties. By formulating a method to incorporate CN x within alginate (i.e., covalently grafting alginate to the CN x surface versus noncovalently adsorbing alginate to the CN x surface) creates extrudable materials with tunable physical, chemical, and thermal properties. Herein, three new composites of alginate‐CN x are created. The results indicate that all composites present different physicochemical and thermal properties, suggesting that alginate is reorganized according to their degree of oxidation. These composites show cytocompatibility with MDA‐MB‐231 and regulation over the size of spheroids formed within the matrix. CN x within the matrix negatively affects MCF‐7 cells viability, spheroid formation rate, and the quantity of spheroids developed during culture. These materials provide a useful 3D hydrogel that can be used to develop in vitro models to understand the role of microenvironmental factors such as stiffness or surface roughness on the development of spheroids and their subsequent phenotypic behavior.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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