Non-Thermal Atmospheric Pressure Plasma-Conditioned Root Dentin Promotes Attraction and Attachment of Primary Human Dental Pulp Stem Cells in Real-Time Ex Vivo
Bibliographic record
Abstract
This study investigated if non-thermal atmospheric pressure plasma (NTAPP) treatment of root dentin surfaces promotes human dental pulp stem cell (hDPSCs) adhesion. Freshly extracted human single-rooted teeth (n = 36) were decoronated and cut (first vertically, then horizontally) into root dentin slices (3 mm thick). Primary hDPSCs cultures were seeded onto slices randomly assigned to pretreatment groups (n = 9/group): NaOCl (1.5%), EDTA (17%) then NTAPP (Group I); NaOCl then NTAPP (Group II); NaOCl then EDTA (Group III); and NaOCl alone (Group IV). Cell viability and proliferation were measured using MTT assay with log-linear statistical analysis. Cell attachment and spreading morphologies on dentin slices (n = 3/group) were examined through scanning electron microscopy. Early cell adhesion events and subcellular activities were observed in real time by live-cell imaging through holotomographic microscopy. Cell viability and proliferation were significantly higher on NTAPP-treated dentin (p < 0.05), without interactions with EDTA (p > 0.05). The attachment, spreading, extensions and multiple layers of hDPSCs were heightened on NTAPP-treated dentin. Cell adhesion, spreading, and dentinal tubule penetration were hastened on NTAPP-treated dentin surfaces in real-time, with elevated subcellular activities and intracellular lipid droplet formation. NTAPP-treated root dentin surfaces support enhanced cellular responses, potentially promoting pulp-dentin regeneration.
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 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 | 0.000 |
| 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 teacher head, 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".