Preosteoblasts behavior in contact with single‐walled carbon nanotubes synthesized by radio frequency induction thermal plasma using various catalysts
Bibliographic record
Abstract
The influence of single-walled carbon nanotubes (SWCNTs) produced by radio frequency (RF) induction thermal plasma with three catalyst mixtures (Ni-Co-Y2 O3 , Ni-Y2 O3 and Ni-Mo-Y2 O3 ) was evaluated on the behavior of murine MC3T3-E1 preosteoblasts. After analyzing SWCNTs properties, mitochondrial enzymatic (MTS) and lactate dehydrogenase (LDH) activities as well as neutral red (NR) uptake were measured to assess the cellular viability. To ascertain that the cytotoxicity was not merely as a result of the mechanical disturbance, either SWCNTs were added on the attached cells or cells were seeded on the SWCNT-covered plates. Regardless of the catalyst mixtures used for their production, SWCNTs added on the attached cells reduced cell viability drastically in a dose-dependent manner. However, the viability of cells seeded on SWCNTs even on those produced with Ni-Co-Y2 O3 was slightly decreased at 24 h and besides cells could proliferate within 48 h. Furthermore, cells were able to organize normal filamentous actin cytoskeleton and no apoptotic cells were detected in the cultures. Thus except mechanical disturbance, thermal plasma grown SWCNTs seem to induce no severe cytotoxicity on MC3T3-E1 preosteoblasts and therefore are considered promising CNTs to be studied more deeply for future applications in bone tissue engineering.
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.
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) | 0.000 | 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 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".