Establishment of a Transgenic Zebrafish Line for Superficial Skin Ablation and Functional Validation of Apoptosis Modulators In Vivo
Bibliographic record
Abstract
BACKGROUND: Zebrafish skin is composed of enveloping and basal layers which form a first-line defense system against pathogens. Zebrafish epidermis contains ionocytes and mucous cells that aid secretion of acid/ions or mucous through skin. Previous studies demonstrated that fish skin is extremely sensitive to external stimuli. However, little is known about the molecular mechanisms that modulate skin cell apoptosis in zebrafish. METHODOLOGY/PRINCIPAL FINDINGS: This study aimed to create a platform to conduct conditional skin ablation and determine if it is possible to attenuate apoptotic stimuli by overexpressing potential apoptosis modulating genes in the skin of live animals. A transgenic zebrafish line of Tg(krt4:NTR-hKikGR)(cy17) (killer line), which can conditionally trigger apoptosis in superficial skin cells, was first established. When the killer line was incubated with the prodrug metrodinazole, the superficial skin displayed extensive apoptosis as judged by detection of massive TUNEL- and active caspase 3-positive signals. Great reductions in NTR-hKikGR(+) fluorescent signals accompanied epidermal cell apoptosis. This indicated that NTR-hKikGR(+) signal fluorescence can be utilized to evaluate apoptotic events in vivo. After removal of metrodinazole, the skin integrity progressively recovered and NTR-hKikGR(+) fluorescent signals gradually restored. In contrast, either crossing the killer line with testing lines or transiently injecting the killer line with testing vectors that expressed human constitutive active Akt1, mouse constitutive active Stat3, or HPV16 E6 element displayed apoptosis-resistant phenotypes to cytotoxic metrodinazole as judged by the loss of reduction in NTR-hKikGR(+) fluorescent signaling. CONCLUSION/SIGNIFICANCE: The killer/testing line binary system established in the current study demonstrates a nitroreductase/metrodinazole system that can be utilized to conditionally perform skin ablation in a real-time manner, and provides a valuable tool to visualize and quantify the anti-apoptotic potential of interesting target genes in vivo. The current work identifies a potential use for transgenic zebrafish as a high-throughput platform to validate potential apoptosis modulators in vivo.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".