NF-κB signaling and its anti-apoptotic effects in liver & skeletal muscle of dehydrated Xenopus laevis
Bibliographic record
Abstract
The African clawed frog, Xenopus laevis, is able to survive prolonged arid conditions during seasonal droughts. During these conditions, X. laevis enters aestivation whereby its metabolic rate is suppressed, urea and ammonia levels increase, and its physiological functions slow. Various molecular mechanisms are employed by X. laevis to mitigate the deleterious effects of severe dehydration and hypometabolism, including pro-survival cellular processes that protect cells and tissues from damage and atrophy. While previous research has focused on antioxidant proteins' role in preventing oxidative stress, information on the role of anti-apoptotic signaling in X. laevis is lacking. As such, we investigated the role of nuclear factor-kappa B (NF-κB) signaling and its downstream target genes in liver and skeletal muscle tissue of X. laevis. The transcription factor, NF-κB, and its downstream target genes work to inhibit apoptotic machinery and promote cell survival. Herein, we found that NF-κB signaling activation in liver tissue leads to the selective upregulation of downstream anti-apoptotic proteins. In contrast, this upregulation occurs independently of NF-κB signaling in skeletal muscle tissue. Overall, our results serve to expand our knowledge of the anti-apoptotic mechanisms underlying the natural dehydration-tolerance of X. laevis, including its likely use in mitigating tissue atrophy during aestivation.
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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 | 0.000 |
| 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".