Nutrient Modulation of Autophagy
Bibliographic record
Abstract
During nutrient deprivation, autophagy provides the constituents required to maintain the metabolism essential for survival. Recently, genome-wide association studies have identified genetic determinants for susceptibility to Crohn's disease (CD) such as ATG16L1 and IRGM that are involved in the autophagy pathway. Both disease-carrying NOD2 mutations and ATG16L1 mutations may result in impairment of autophagy. Impairment in autophagy results in impaired clearance of microbes. Ileal CD is associated with Paneth cell loss of function such as decreased production of α-defensins, which may arise from mutations in NOD2 or autophagy genes. Nutrients are able to modify several cellular pathways and in particular autophagy. We summarize the contribution of a variety of dietary components to activate autophagy. Understanding the crosstalk between nutrients and autophagy in the intestine may provide novel targets that have therapeutics potential in intestinal inflammation. Nutrient activation of autophagy may contribute to restoring the Paneth cell loss of function in ileal CD.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".