Nanofibrous Composites Reinforced by MoS <sub>2</sub> Nanosheets as a Conductive Scaffold for Cardiac Tissue Engineering
Bibliographic record
Abstract
Abstract Mimicking the structure of extracellular matrix and electrical conductivity of myocardium are required to regenerate the functional cardiac tissue. In this study, Molybdenum disulfide, MoS 2 , nanosheets were synthesized and incorporated into nylon6 electrospun nanofibers in order to enhance the mechanical properties and electrical conductivity of the scaffolds. Then, the mouse embryonic cardiac cells, mECCs, were seeded on the scaffolds for in vitro studies. The MoS 2 nanosheets were studied by scanning electron microscopy (SEM) and Raman spectroscopy. Nylon/MoS 2 nanofibers were characterized by SEM, transmission electron microscopy (TEM), water contact angle measurement, electrical conductivity, and tensile test. Furthermore, cytocompatibility of scaffolds was confirmed by 3‐(4, 5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyl tetrazolium bromide, MTT, assay. SEM images showed more elongated morphology for mECCs attached to the nylon/MoS 2 scaffold. Also, the Real‐Time PCR and immunostaining studies indicated the maturation and upregulation of cardiac functional genes including GATA‐4, c‐TnT, Nkx 2.5 and α‐MHC in the nylon/MoS 2 scaffold in comparison to the bare nylon. Therefore, MoS 2 reinforced nylon nanofibrous scaffolds can be considered as a suitable candidate in cardiac tissue engineering.
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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".