Transparent 3-Layered Bacterial Nanocellulose as a Multicompartment and Biomimetic Scaffold for Co-Culturing Cells
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
Three-dimensional (3D) cell culture models are widely used to provide a more physiologically relevant microenvironment in which to host and study desired cell types. These models vary in complexity and cost, ranging from simple and inexpensive to highly sophisticated and costly systems. In this study, we introduce a novel translucent multi-compartmentalized stacked multilayered nanocellulose scaffold and describe its fabrication, characterization, and potential application for co-culturing multiple cell types. The scaffold consists of bacterial nanocellulose (BNC) layers separated by interlayers of a lower density of nanocellulose fibers. Using this system, we co-cultured the MDA-MB-231 cell line with two tumor-associated cell types, namely BC-CAFs and M2 macrophages, to simulate the tumor microenvironment (TME). Cells remained viable and metabolically active for up to 15 days. Confocal microscopy showed no signs of cell invasion. However, BC-CAFs and MDA-MB-231 cells were frequently observed within the same layer. The expression of breast cancer-related genes was analyzed to assess the downstream functionality of the cells. We found that the E-cadherin expression was 20% lower in cancer cells co-cultured in the multi-compartmentalized scaffold than in those cultured in 2D plates. Since E-cadherin plays a critical role in preventing the initial dissociation of epithelial cells from the primary tumor mass and is often downregulated in the tumor microenvironment in vivo, this finding suggests that our scaffold more effectively recapitulates the complexity of a tumor microenvironment.
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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 | 0.001 | 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