Real-Time Cell-Electronic Sensing of Coal Fly Ash Particulate Matter for Toxicity-Based Air Quality Monitoring
Bibliographic record
Abstract
The development of a unique bioassay for cytotoxicity analysis of coal fly ash (CFA) particulate matter (PM) and its potential application for air quality monitoring is described. Using human cell lines, A549 and SK-MES-1, as live probes on microelectrode-embedded 96-well sensors, impedance changes over time are measured as cells are treated with varying concentrations (1 μg/mL-20 mg/mL) of CFA samples. A dose-dependent impedance change is determined for each CFA sample, from which an IC50 histogram is obtained. The assay was successfully applied to examine CFA samples collected from three coal-fired power plants (CFPs) in China. The samples were separated into three size fractions: PM2.5 (<2.5 μm), PM10-2.5 (2.5 μm < x < 10 μm), and PM10 (>10 μm). Dynamic cell-response profiles and temporal IC50 histograms of all samples show that CFA cytotoxicity depends on concentration, exposure time (0-60 h), and cell-type (SK-MES-1 > A549). The IC50 values differentiate the cytotoxicity of CFA samples based on size fraction (PM2.5 ≈ PM10-2.5 ≫ PM10) and the sampling location (CFP2 > CFP1 ≈ CFP3). Differential cytotoxicity measurements of particulates in human cell lines using cell-electronic sensing provide a useful tool for toxicity-based air quality monitoring and risk assessment.
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 | 0.004 | 0.001 |
| 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 | 0.001 |
| 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 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".