Protein Dynamics in Cytosolic DNA-Sensing Antiviral Innate Immune Signaling Pathways
Bibliographic record
Abstract
Antiviral innate immunity works as the first line of host defense against viral infection. Pattern recognition receptors (PRRs) and adaptor proteins involved in the innate immune signaling pathways play critical roles in controlling viral infections via the induction of type I interferon and its downstream interferon-stimulated genes. Dynamic changes of adaptor proteins contribute to precise regulation of the activation and shut-off of signaling transduction, though numerous complex processes are involved in achieving dynamic changes to various proteins of the host and viruses. In this review, we will summarize recent progress on the trafficking patterns and conformational transitions of the adaptors that are involved in the antiviral innate immune signaling pathway during viral DNA sensing. Moreover, we aim to dissect the relationships between protein dynamics and DNA-sensing antiviral innate immune responses, which will reveal the underlying mechanisms controlling protein activity and maintaining cell homeostasis. By comprehensively revealing protein dynamics in cytosolic DNA-sensing antiviral innate immune signaling pathways, we will be able to identify potential new targets for the therapies of certain autoimmune diseases.
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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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".