Electrospun Carboxymethylcellulose as a Scaffold for Biomedical Applications
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
Abstract Electrospinning of pure carboxymethylcellulose (CMC) and its derivatives for biomedical applications is attractive due to their interesting biology and biomimetic properties. However, the main challenges in electrospinning pure CMC are strong electrostatic repulsions and its highly viscous nature. In this research, electrospun membranes consisting of grafted CMC-polyethylene glycol (CMC-PEG) and polycaprolactone (PCL) were successfully fabricated using emulsion electrospinning. Membranes with a PCL:CMC-PEG ratio of 80:20 formed uniform fiber with an average diameter of 930.2 ± 31.0 nm. Furthermore, PCL/CMC-PEG membranes demonstrated excellent mechanical properties suitable for use as scaffolds for soft tissue repair and skin wound healing. Water contact angle analysis showed that the incorporation of grafted CMC-PEG improved the membrane wettability. Electrospun membranes with a PCL: CMC-PEG ratio of 80:20 exhibited the highest in vitro degradation, with 82.0 ± 8.7% weight loss over 10 weeks of incubation. In vitro studies confirmed the non-cytotoxic properties of PCL:CMC-PEG (80:20) membranes when tested with normal human dermal fibroblast (NHDF) cells. Morphological analysis further confirmed the attachment of NHDF cells followed by cell proliferation and migration. These membranes demonstrated optimal mechanical properties, hydrophilicity, and biocompatibility, making them promising tissue scaffolds for tissue engineering and regenerative medicine applications. Graphical Abstract
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 | 0.001 |
| 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