Assessing Neurotransmitter Levels in Zebrafish Brains following differential CO2 exposure through LC/MS Analysis
Bibliographic record
Abstract
Neurotransmitters are endogenous chemicals that enable neurotransmission, which is the transmission of nerve impulses between neurons, or a neuron and a muscle fiber or other structure. Therefore, neurotransmission is important in affecting actions as well as behaviours and it is crucial that the balance of neurotransmitters is maintained in an organism for proper functioning. Climate change is increasing atmospheric concentration of carbon dioxide (CO2) at a drastic rate. This has led to a cascade of negative effects, one of which is the absorption of CO2 into aquatic systems resulting in a decrease in pH and turning the water more acidic. Previous studies found that zebrafish exhibit increased anxiety-like behaviour when exposed to increased levels of CO2. To determine if the changes in anxiety-like behaviour observed were due to alterations in neurotransmitter levels induced by the increased concentrations of CO2, this project will quantify the concentrations of various neurotransmitters in the brains of these CO2 exposed zebrafish. We will use high performance liquid chromatography to separate neurotransmitters based on chemical properties, paired with mass spectrometry to quantify neurotransmitter concentrations. Comparison between the neurotransmitter concentration profiles and the observed behaviour will not only help better the understanding of the effects of acidification on zebrafish behaviour, but the potential impacts of acidification caused by climate change on other aquatic organisms as well. Department: Biology Faculty Mentor: Dr. Matthew Ross
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".