Fabrication of a Crystalline Nanocellulose Embedded Agarose Biomaterial Ink for Bone Marrow-Derived Mast Cell Culture
Bibliographic record
Abstract
Three-dimensional (3D) bioprinting utilizes hydrogel-based composites (or biomaterial inks) that are deposited in a pattern, forming a substrate onto which cells are deposited. Because many biomaterial inks can be potentially cytotoxic to primary cells, it is necessary to determine the biocompatibility of these hydrogel composites prior to their utilization in costly 3D tissue engineering processes. Some 3D culture methods, including bioprinting, require that cells be embedded into a 3D matrix, making it difficult to extract and analyze the cells for changes in viability and biomarker expression without eliciting mechanical damage. This protocol describes as proof of concept, a method to assess the biocompatibility of a crystalline nanocellulose (CNC) embedded agarose composite, fabricated into a 24-well culture system, with mouse bone marrow-derived mast cells (BMMCs) using flow cytometric assays for cell viability and biomarker expression. After 18 h of exposure to the CNC/agarose/D-mannitol matrix, BMMC viability was unaltered as measured by propidium iodide (PI) permeability. However, BMMCs cultured on the CNC/agarose/D-mannitol substrate appeared to slightly increase their expression of the high-affinity IgE receptor (FcεRI) and the stem cell factor receptor (Kit; CD117), although this does not appear to be dependent on the amount of CNC in the bioink composite. The viability of BMMCs was also assessed following a time course exposure to hydrogel scaffolds that were fabricated from a commercial biomaterial ink composed of fibrillar nanocellulose (FNC) and sodium alginate using a 3D extrusion bioprinter. Over a period of 6-48 h, the FNC/alginate substrates did not adversely affect the viability of the BMMCs as determined by flow cytometry and microtiter assays (XTT and lactate dehydrogenase). This protocol describes an efficient method to rapidly screen the biochemical compatibility of candidate biomaterial inks for their utility as 3D scaffolds for post-print seeding with mast cells.
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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".