The Quartz Crystal Microbalance as a Continuous Monitoring Tool for the Study of Endothelial Cell Surface Attachment and Growth
Bibliographic record
Abstract
The quartz crystal microbalance (QCM) was used to monitor endothelial cell (EC) adhesion on the gold surface of an oscillating quartz crystal contained in a QCM device. A number of parameters were investigated. First, we observed differential QCM O-ring toxicities for ECs. Second, appropriate conditions for cell culture and QCM cell environment were identified that can eliminate large-scale frequency oscillations in the measurements. These artifacts are not due to added cells but originate in the time-dependent evaporation of water. Having eliminated these artifacts, we then demonstrated that the measured steady-state crystal frequency shift, Delta f, and motional resistance shift, DeltaR, were determined by the number of firmly attached ECs requiring trypsinization from the crystal surface. Last, following steady-state attachment of ECs, the EC growth stimulation by fibroblast growth factor was monitored in a continuous fashion by measuring f and R values over a 72 h. period. We observed the Delta f values to increase in a way that reflected the increase in EC number bound to the QCM surface. Following addition of ECs to the QCM, the time-dependent increase in DeltaR can be interpreted in terms of increase by the ECs of the energy dissipation properties of the solution at the solution-gold surface interface. This effect is due to their rapid surface attachment and the elaboration of their cytoskeletal properties. These results indicate that the QCM technique can be used for the study of EC attachment and growth and suggest its potential for the real time study of per unit surface area cell mass distribution dynamics and viscoelastic properties and the cells' responses to stresses or perturbations brought about using biologically active molecules.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".