Facial Mechanosensory Influence on Forelimb Movement in Newborn Opossums, Monodelphis domestica
Bibliographic record
Abstract
The opossum, Monodelphis domestica, is born very immature but crawls, unaided, with its forelimbs (FL) from the mother's birth canal to a nipple where it attaches to pursue its development. What sensory cues guide the newborn to the nipple and trigger its attachment to it? Previous experiments showed that low intensity electrical stimulation of the trigeminal ganglion induces FL movement in in vitro preparations and that trigeminal innervation of the facial skin is well developed in the newborn. The skin does not contain Vater-Pacini or Meissner touch corpuscles at this age, but it contains cells which appear to be Merkel cells (MC). We sought to determine if touch perceived by MC could exert an influence on FL movements. Application of the fluorescent dye AM1-43, which labels sensory cells such as MC, revealed the presence of a large number of labeled cells in the facial epidermis, especially in the snout skin, in newborn opossums. Moreover, calibrated pressure applied to the snout induced bilateral and simultaneous electromyographic responses of the triceps muscle in in vitro preparations of the neuraxis and FL from newborn. These responses increase with stimulation intensity and tend to decrease over time. Removing the facial skin nearly abolished these responses. Metabotropic glutamate 1 receptors being involved in MC neurotransmission, an antagonist of these receptors was applied to the bath, which decreased the EMG responses in a reversible manner. Likewise, bath application of the purinergic type 2 receptors, used by AM1-43 to penetrate sensory cells, also decreased the triceps EMG responses. The combined results support a strong influence of facial mechanosensation on FL movement in newborn opossums, and suggest that this influence could be exerted via MC.
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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".