Testing Neurotransmitters for Toxicity with a Luminescent Biosensor: Implications for Microbial Endocrinology
Bibliographic record
Abstract
Background: The human organism is a complex superorganism including numerous eukaryotic, eubacterial, and archaean cells. The qualitative and quantitative assessment of the microbiota toxicity of chemical agents, i.e., their inhibitory effects on the microbial inhabitants of the human organism in health and disease, seems to hold much value in this context. In this work, a bacterial luminescence-based express test system for microbiota toxicity is applied to neurotransmitters such as serotonin, dopamine, norepinephrine, and histamine. Methods: The biosensor was based on a GM Escherichia coli K12 strain (TGI) that contained the lux operon of the luminescent soil bacterium Photorhabdus luminescencens ZMI. The biosensor was exposed to the action of the tested neurotransmitters for 5 to 60 minutes The intensity of bacterial luminescence (counts.sec-1) was monitored in the control and the experimental samples with a Biotoks 6 ms luminometer (Russia); the toxicity index (T) of the neurotransmitters was determined. Results: A marked toxic effect on bioluminescence was produced by serotonin, histamine, and dopamine at concentrations exceeding 80 µg/ml, 100 µg/ml, and 1 mg/ml, respectively. At lower concentration, these neurotransmitters were “negatively toxic”, i.e. stimulatory in terms of the effect on bacterial luminescence. In contrast, norepinephrine inhibited luminescence at all concentrations tested. Conclusions: The bacterial luminescence-based testing method is applicable to the assessment of the destructive and stimulatory effects of neurotransmitters; the data obtained are of microbiological and clinical relevance.
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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 | 0.001 | 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) | 0.000 | 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".