NFAT5-Mediated Signalling Pathways in Viral Infection and Cardiovascular Dysfunction
Bibliographic record
Abstract
The nuclear factor of activated T cells 5 (NFAT5) is well known for its sensitivity to cellular osmolarity changes, such as in the kidney medulla. Accumulated evidence indicates that NFAT5 is also a sensitive factor to stress signals caused by non-hypertonic stimuli such as heat shock, biomechanical stretch stress, ischaemia, infection, etc. These osmolality-related and -unrelated stimuli can induce NFAT5 upregulation, activation and nuclear accumulation, leading to its protective role against various detrimental effects. However, dysregulation of NFAT5 expression may cause pathological conditions in different tissues, leading to a variety of diseases. These protective or pathogenic effects of NFAT5 are dictated by the regulation of its target gene expression and activation of its signalling pathways. Recent studies have found a number of kinases that participate in the phosphorylation/activation of NFAT5 and related signal proteins. Thus, this review will focus on the NFAT5-mediated signal transduction pathways. As for the stimuli that upregulate NFAT5, in addition to the stresses caused by hyperosmotic and non-hyperosmotic environments, other factors such as miRNA, long non-coding RNA, epigenetic modification and viral infection also play an important role in regulating NFAT5 expression; thus, the discussion in this regard is another focus of this review. As the heart, unlike the kidneys, is not normally exposed to hypertonic environments, studies on NFAT5-mediated cardiovascular diseases are just emerging and rapidly progressing. Therefore, we have also added a review on the progress made in this field of research.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".