Bik promotes proteasomal degradation to control low-grade inflammation
Bibliographic record
Abstract
Although chronic low-grade inflammation does not cause immediate clinical symptoms, over the longer term, it can enhance other insults or age-dependent damage to organ systems and thereby contribute to age-related disorders, such as respiratory disorders, heart disease, metabolic disorders, autoimmunity, and cancer. However, the molecular mechanisms governing low-level inflammation are largely unknown. We discovered that Bcl-2-interacting killer (Bik) deficiency causes low-level inflammation even at baseline and the development of spontaneous emphysema in female but not male mice. Similarly, a single nucleotide polymorphism that reduced Bik levels was associated with increased inflammation and enhanced decline in lung function in humans. Transgenic expression of Bik in the airways of Bik-deficient mice inhibited allergen- or LPS-induced lung inflammation and reversed emphysema in female mice. Bik deficiency increased nuclear but not cytosolic p65 levels because Bik, by modifying the BH4 domain of Bcl-2, interacted with regulatory particle non-ATPase 1 (RPN1) and RPN2 and enhanced proteasomal degradation of nuclear proteins. Bik deficiency increased inflammation primarily in females because Bcl-2 and Bik levels were reduced in lung tissues and airway cells of female compared with male mice. Therefore, controlling low-grade inflammation by modifying the unappreciated role of Bik and Bcl-2 in facilitating proteasomal degradation of nuclear proteins may be crucial in treating chronic age-related diseases.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".