Preliminary Findings of Structure and Expression of Opioid Receptor Genes in a Peregrine Falcon (<i>Falco peregrinus</i>), a Snowy Owl (<i>Bubo scandiacus</i>), and a Blue-fronted Amazon Parrot (<i>Amazona aestiva</i>)
Bibliographic record
Abstract
To further knowledge of the physiology of opioid receptors in birds, the structure and expression of the μ-, δ-, and κ-opioid receptor genes were studied in a peregrine falcon ( Falco peregrinus), a snowy owl ( Bubo scandiacus), and a blue-fronted Amazon parrot ( Amazona aestiva). Tissue samples were obtained from birds that had been euthanatized for poor release prognosis or medical reasons. Samples were taken from the brain (telencephalon, thalamus, pituitary gland, cerebellum, pons, medulla oblongata, mesencephalon), the spinal cord and dorsal root ganglions, and plantar foot skin. Messenger RNA was recovered, and reverse transcription polymerase chain reaction (RT-PCR) was performed to generate complementary DNA (cDNA) sequences. Gene structures were documented by directly comparing cDNA sequences with recently published genomic sequences for the peregrine falcon and the blue-fronted Amazon parrot or by comparisons with genomic sequences of related species for the snowy owl. Structurally, the avian μ-opioid receptor messenger RNA (mRNA) species were complex, displaying differential splicing, alternative stop codons, and multiple polyadenylation signals. In comparison, the structure of the avian κ-receptor mRNA was relatively simple. In contrast to what is seen in humans, the avian δ-receptor mRNA structure was found to be complex, demonstrating novel 3-prime coding and noncoding exons not identified in mammals. The role of the δ-opioid receptor merits further investigation in avian species.
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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) | 0.000 | 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) | 0.001 | 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 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".