TAOK3 limits age-associated inflammation by negatively modulating macrophage differentiation and their production of TNFα
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
Abstract Background Human aging is characterized by a state of chronic inflammation, termed inflammaging, for which the causes are incompletely understood. It is known, however, that macrophages play a driving role in establishing inflammaging by promoting pro-inflammatory rather than anti-inflammatory responses. Numerous genetic and environmental risk factors have been implicated with inflammaging, most of which are directly linked to pro-inflammatory mediators IL-6, IL1Ra, and TNFα. Genes involved in the signaling and production of those molecules have also been highlighted as essential contributors. TAOK3 is a serine/threonine kinase of the STE-20 kinase family that has been associated with an increased risk of developing auto-immune conditions in several genome-wide association studies (GWAS). Yet, the functional role of TAOK3 in inflammation has remained unexplored. Results We found that mice deficient in the serine/Threonine kinase Taok3 developed severe inflammatory disorders with age, which was more pronounced in female animals. Further analyses revealed a drastic shift from lymphoid to myeloid cells in the spleens of those aged mice. This shift was accompanied by hematopoietic progenitor cells skewing in Taok3 −/− mice that favored myeloid lineage commitment. Finally, we identified that the kinase activity of the enzyme plays a vital role in limiting the establishment of proinflammatory responses in macrophages. Conclusions Essentially, Taok3 deficiency promotes the accumulation of monocytes in the periphery and their adoption of a pro-inflammatory phenotype. These findings illustrate the role of Taok3 in age-related inflammation and highlight the importance of genetic risk factors in this condition.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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