Identification of Disease Resistance Genes and CRISPR-Based Ge-nome Editing in Channa spp.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study analyzed the hazards and immune response mechanisms of common diseases of snakehead fish in recent years (such as nocardia, Aeromonas hydrophila , viral hemorrhagic septicemia, etc.), and summarized the mining methods and functional research progress of key genes for disease resistance of snakehead fish, including screening of immune genes such as IL-17 and TRAF through whole genome scanning and transcriptomics. At the same time, the application status and advantages of CRISPR/Cas9 gene editing technology in aquaculture were discussed, such as efficient site-directed mutagenesis and introduction of exogenous antimicrobial peptide genes to enhance fish disease resistance. Through case analysis of the successful experience of disease-resistant gene editing in related fish (such as Atlantic salmon and catfish), this study prospected the potential path and results of disease-resistant gene editing breeding of snakehead fish, and discussed its ecological and ethical impacts (such as off-target effects, food safety and public acceptance, etc.), which is of great significance to improving aquaculture production and disease prevention and control, and also provides the latest theoretical basis and practical reference for disease-resistant breeding of snakehead fish.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it