Toll-Interacting Protein in Pulmonary Diseases. Abiding by the Goldilocks Principle
Bibliographic record
Abstract
Abstract TOLLIP (Toll-interacting protein) is an intracellular adaptor protein with diverse actions throughout the body. In a context- and cell type–specific manner, TOLLIP can function as an inhibitor of inflammation and endoplasmic-reticulum stress, an activator of autophagy, or a critical regulator of intracellular vacuole trafficking. The distinct functions of this protein have been linked to innate immune responses and lung epithelial-cell apoptosis. TOLLIP genetic variants have been associated with a variety of chronic lung diseases, including idiopathic pulmonary fibrosis, asthma, and primary graft dysfunction after lung transplantation, and with infections, such as tuberculosis, Legionella pneumonia, and respiratory viruses. TOLLIP exists in a delicate homeostatic balance, with both positive and negative effects on the trajectory of pulmonary diseases. This translational review summarizes the genetic and molecular associations that link TOLLIP to the development and progression of noninfectious and infectious pulmonary diseases. We highlight current limitations of in vitro and in vivo models in assessing the role of TOLLIP in these conditions, and we describe future approaches that will enable a more nuanced exploration of the role of TOLLIP in pulmonary conditions. There has been a surge in recent research evaluating the role of this protein in human diseases, but critical mechanistic pathways require further exploration. By understanding its biologic functions in disease-specific contexts, we will be able to determine whether TOLLIP can be therapeutically modulated to treat pulmonary 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".