Emptying and refilling of slime glands in Atlantic (<i>Myxine glutinosa</i>) and Pacific (<i>Eptatretus stoutii</i>) hagfishes
Bibliographic record
Abstract
Hagfishes are known for their unique defensive slime, which they use to ward off gill-breathing predators. Although much is known about the slime cells (gland thread cells and gland mucous cells), little is known about how long slime gland refilling takes, or how slime composition changes with refilling or repeated stimulation of the same gland. Slime glands can be individually electrostimulated to release slime, and this technique was used to measure slime gland refilling times for Atlantic and Pacific hagfish. The amount of exudate produced, the composition of the exudate and the morphometrics of slime cells were analyzed during refilling, and as a function of stimulation number when full glands were stimulated in rapid succession. Complete refilling of slime glands for both species took 3-4 weeks, with Pacific hagfish achieving faster absolute rates of exudate recovery than Atlantic hagfish. We found significant changes in the composition of the exudate and in the morphometrics of slime cells from Pacific hagfish during refilling. Over successive stimulations of full Pacific hagfish glands, multiple boluses of exudate were released, with exudate composition, but not thread cell morphometrics, changing significantly. Finally, histological examination of slime glands revealed slime cells retained in glands after exhaustion. Discrepancies in the volume of cells released suggest that mechanisms other than contraction of the gland musculature alone may be involved in exudate ejection. Our results provide a first look at the process and timing of slime gland refilling in hagfishes, and raise new questions about how refilling is achieved at the cellular level.
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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 | 0.001 |
| 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 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".