Frog Skin Innate Immune Defences: Sensing and Surviving Pathogens
Bibliographic record
Abstract
Amphibian skin is a mucosal surface in direct and continuous contact with a microbially diverse and laden aquatic and/or terrestrial environment. As such, frog skin is an important innate immune organ and first line of defence against pathogens in the environment. Critical to the innate immune functions of frog skin are the maintenance of physical, chemical, cellular, and microbiological barriers and the complex network of interactions that occur across all the barriers. Despite the global decline in amphibian populations, largely as a result of emerging infectious diseases, we understand little regarding the cellular and molecular mechanisms that underlie the innate immune function of amphibian skin and defence against pathogens. In this review, we discuss the structure, cell composition and cellular junctions that contribute to the skin physical barrier, the antimicrobial peptide arsenal that, in part, comprises the chemical barrier, the pattern recognition receptors involved in recognizing pathogens and initiating innate immune responses in the skin, and the contribution of commensal microbes on the skin to pathogen defence. We briefly discuss the influence of environmental abiotic factors (natural and anthropogenic) and pathogens on the immunocompetency of frog skin defences. Although some aspects of frog innate immunity, such as antimicrobial peptides are well-studied; other components and how they contribute to the skin innate immune barrier, are lacking. Elucidating the complex network of interactions occurring at the interface of the frog's external and internal environments will yield insight into the crucial role amphibian skin plays in host defence and the environmental factors leading to compromised barrier integrity, disease, and host mortality.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".