Electrical stimulation modulates osteoblast proliferation and bone protein production through heparin‐bioactivated conductive scaffolds
Bibliographic record
Abstract
Electrical fields are known to interact with human cells. This principle has been explored to regulate cellular activities for bone tissue regeneration. In this work, Saos-2 cells were cultured on conductive scaffolds made of biodegradable poly(L-lactide) and the heparin-containing, electrically conducting polypyrrole (PPy/HE) to study their reaction to electrical stimulation (ES) mediated through such scaffolds. Both the duration and intensity of ES enhanced cell proliferation, generating a unique electrical intensity and temporal "window" within which osteoblast proliferation was upmodulated in contrast to the downmodulation or ineffectiveness in other ES regions. The favourable ES intensity (200 mV/mm) was further investigated in terms of the gene activation and protein production of two important osteoblast markers characterised by extracellular matrix maturation and mineralisation, that is alkaline phosphatase (ALP) and osteocalcin (OC). Both genes were found activated and the relevant protein production increased significantly following ES. In contrast, ES in the down-modulation region (400 mV/mm) suppressed the production of both ALP and OC. This work demonstrated that important osteoblast markers can be modulated with specific ES parameters mediated through conductive polymer substrates, providing a unique strategy for 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) | 0.001 | 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".