Cell-electronic sensing of particle-induced cellular responses
Bibliographic record
Abstract
We report a new technique for the continuous and real-time measurement of microparticle-induced cellular responses using a real-time cell-electronic sensing (RT-CES) technology. The method involves the use of microelectrode-embedded microwells seeded with one of two lung cancer carcinoma cell lines (A549 and SK-MES-1), allowing for continuous measurements of impedance. The change in impedance that is automatically converted to the cell index is linearly correlated with the numbers of the seeding cells during the log phase, providing quantitative measurement of cytotoxicity. After 24 h of initial incubation in 96 microwells, the cultures are treated with microparticles, and changes in the cell index are monitored in real time. Multiple data, including dose response curves, IC(50) (a concentration inhibiting 50% cell growth), and cell-specific and particulate-specific cell responses, are obtained from a single set of experiments. SK-MES-1 cells consistently showed more severe effects and lower IC(50) values than A549 cells when they were treated with quartz particle suspensions. The different effects detected using the RT-CES technique were related to morphological change and apoptosis, supported by the scanning electronic microscopy and flow cytometry results. The method is further used to test the cytotoxicity of two PM(10) standard reference materials of urban air dust and diesel particulates, demonstrating the potential application of this new technique for biomonitoring of air particulates.
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".