The Identification of Sea Lamprey Pheromones Using Bioassay-Guided Fractionation
Bibliographic record
Abstract
Bioassay-guided fractionation is an iterative approach that uses the results of physiological and behavioral bioassays to guide the isolation and identification of an active pheromone compound. This method has resulted in the successful characterization of the chemical signals that function as pheromones in a wide range of animal species. Sea lampreys rely on olfaction to detect pheromones that mediate behavioral or physiological responses. We use this knowledge of fish biology to posit functions of putative pheromones and to guide the isolation and identification of active pheromone components. Chromatography is used to extract, concentrate, and separate compounds from the conditioned water. Electro-olfactogram (EOG) recordings are conducted to determine which fractions elicit olfactory responses. Two-choice maze behavioral assays are then used to determine if any of the odorous fractions are also behaviorally active and induce a preference. Spectrometric and spectroscopic methods provide the molecular weight and structural information to assist with the structure elucidation. The bioactivity of the pure compounds is confirmed with EOG and behavioral assays. The behavioral responses observed in the maze should ultimately be validated in a field setting to confirm their function in a natural stream setting. These bioassays play a dual role to 1) guide the fractionation process and 2) confirm and further define the bioactivity of isolated components. Here, we report the representative results of a sea lamprey pheromone identification that exemplify the utility of the bioassay-guided fractionation approach. The identification of sea lamprey pheromones is particularly important because a modulation of its pheromone communication system is among the options considered to control the invasive sea lamprey in the Laurentian Great Lakes. This method can be readily adapted to characterize the chemical communication in a broad array of taxa and shed light on waterborne chemical ecology.
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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 | 0.000 |
| 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".