Activation of the dsRNA-Activated Protein Kinase PKR in Mitochondrial Dysfunction and Inflammatory Stress in Metabolic Syndrome
Bibliographic record
Abstract
BACKGROUND: The double stranded RNA (dsRNA)-activated protein kinase PKR is a well-established protein kinase that is activated by dsRNA during viral infection, and it inhibits global protein synthesis by phosphorylating the alpha subunit of eukaryotic initiation factor 2α (eIF2α). Recent studies have greatly broadened the recognized physiological activities of PKR by demonstrating its fundamental role in inflammatory signaling, particularly in chronic, low-grade inflammation induced by metabolic disorders, known as metaflammation. Metaflammation is initiated by the activation of the NOD-like receptor (NLR), leucine-rich repeat, pyrin domaincontaining 3 (NLRP3) gene by mitochondrial reactive oxygen species (ROS). A protein complex defined as the metaflammasome is assembled in the course of metaflammation. This complex integrates nutritional signaling with cellular stress, inflammatory components, and insulin action and is essential in maintaining metabolic homeostasis. PKR is a key constituent of the metaflammasome and interacts directly with several inflammatory kinases, such as inhibitor κB (IκB) kinase (IKK) and c-Jun N-terminal kinase (JNK), insulin receptor substrate 1 (IRS1), and component of the translational machinery such as eIF2α. CONCLUSION: This review highlights recent findings in PKR-mediated metaflammation and its association with the onset of metabolic syndrome in both human and animal models, with a focus on the molecular and biochemical pathways that underlie the progression of obesity, insulin resistance, and type-2 diabetes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.002 | 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".