Xela DS2 and Xela VS2: two novel skin epithelial-like cell lines from adult African clawed frog ( <i>Xenopus laevis</i> ) and their response to an extracellular viral dsRNA analogue
Bibliographic record
Abstract
Abstract The skin epithelial layer acts as an important immunological barrier against pathogens and is capable of recognizing and responding to pathogen associated molecular patterns (PAMPs) in human and mouse models. Although presumed, it is unknown whether amphibian skin epithelial cells exhibit the ability to respond to PAMPs such as viral double-stranded RNA (dsRNA). To address this, two cell lines from the dorsal skin (Xela DS2) and ventral skin (Xela VS2) of the African clawed frog ( Xenopus laevis ) were established. Xela DS2 and Xela VS2 cells have an epithelial-like morphology, express genes associated with epithelial cells, and lack senescence-associated beta-galactosidase activity. Cells grow optimally in 70% Leibovitz’s L-15 medium supplemented with 15% fetal bovine serum at 26°C. Upon treatment with poly(I:C), a synthetic viral dsRNA analogue and known type I interferon inducer, Xela DS2 and Xela VS2 exhibit marked upregulation of key pro-inflammatory and antiviral transcripts suggesting frog epithelial cells participate in the recognition of extracellular viral dsRNA and production of local inflammatory signals; similar to human and mouse models. Currently, these are the only known Xenopus laevis skin epithelial-like cell lines and will be important for future research in amphibian epithelial cell biology, initial host-pathogen interactions, and rapid screening of the effects of environmental stressors, including contaminants, on frog skin epithelial cells.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".