Noninvasive Probing of Inhibitory Effects of Cylindrospermopsin and Microcystin-LR Using Cell-Based Impedance Spectroscopy
Bibliographic record
Abstract
In an effort to develop a noninvasive method for assessment of cyanobacterial toxins in drinking water, plausible cytotoxicity/inhibition of microcystin-LR and cylindrospermopsin was evaluated by cell-substrate impedance sensing (ECIS) using three different cell lines. Sf9 insect cells were attached to concanavalin A coated gold electrodes, whereas Chinese hamster ovary (CHO) and human embryo kidney (HEK) cells were attached to a fibronectin or laminin coated gold surface. Cytotoxic or inhibitory effects were dependent upon the cell line and the extracellular matrix (ECM) coating. Neither toxin exhibited any appreciable effect on the insect cells. In contrast, cytotoxicity of cylindrospermopsin on CHO cells was attested by both ECIS and viability tests. The half-inhibition concentration (ECIS50) of cylindrospermopsin for CHO cells was approximately 2 microg/mL (ppm) after 20 h of exposure and 4 microg/mL (ppm) after 30 h of exposure for a laminin or fibronectin coated surface. ECIS confirmed no significant effect of cylindrospermopsin on HEK cells. Microcystin-LR was also tested with CHO cells, resulting in an ECIS50 value of approximately 12 microg/mL (ppm) after 25 h of exposure for a laminin coated gold surface. The effect of microcystin-LR on CHO cells probed by ECIS was inhibitory rather than cytotoxic, as confirmed by cell viability assays.
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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) | 0.001 | 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 | 0.001 | 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 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".