Phosphatases in toll-like receptors signaling: the unfairly-forgotten
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
Over the past 2 decades, pattern recognition receptors (PRRs) have been shown to be on the front line of many illnesses such as autoimmune, inflammatory, and neurodegenerative diseases as well as allergies and cancer. Among PRRs, toll-like receptors (TLRs) are the most studied family. Dissecting TLRs signaling turned out to be advantageous to elaborate efficient treatments to cure autoimmune and chronic inflammatory disorders. However, a broad understanding of TLR effectors is required to propose a better range of cures. In addition to kinases and E3 ubiquitin ligases, phosphatases emerge as important regulators of TLRs signaling mediated by NF-κB, type I interferons (IFN I) and Mitogen-Activated Protein Kinases signaling pathways. Here, we review recent knowledge on TLRs signaling modulation by different classes and subclasses of phosphatases. Thus, it becomes more and more evident that phosphatases could represent novel therapeutic targets to control pathogenic TLRs signaling. Video Abstract.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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