Genomic Insights into Hypoxia Tolerance Mechanisms in Channa spp.
Bibliographic record
Abstract
The study summarizes the current genomic results on how Channa fish adapt to hypoxia. We performed high-quality genome assembly and transcriptome analysis on Channa asiatica . The results showed that it has more gene families related to oxygen binding and transport. When it is exposed to air, many pathways related to oxidative stress are activated. This shows that it has the genetic ability to adapt to hypoxia and also reveals some of the molecular mechanisms. We also studied gene expression in the liver of Channa striatus under long-term hypoxia. We found that many genes involved in transcription, translation, signal transduction, electron transport and immune response were activated. Several transcripts related to hypoxia tolerance were also identified, such as heat shock protein 90 and fatty acid binding protein, and we also obtained their complete sequences. These research results provide important genomic and transcriptome resources, which will help us to better understand how Channa fish adapt to low oxygen environments. At the same time, it also lays a foundation for future research on hypoxia tolerance breeding and ecological adaptation.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".