Intermittent fasting activates macrophage migration inhibitory factor and alleviates high-fat diet-induced nonalcoholic fatty liver disease
Bibliographic record
Abstract
Switching to normal diet (ND) is the regular therapy for high-fat diet (HFD)-induced nonalcoholic fatty liver disease (NAFLD). Intermittent fasting (IF) is a unique treatment which may exhibits better therapeutic efficacy. Thus, we aim to investigate the therapeutic effects of these treatments and exploring the mechanisms. In the present study, NAFLD mouse model was induced by a 10-week HFD. Thereafter, mice adopted continued HFD, ND, or IF for the next 12 weeks. Finally, the liver was then harvested to assess lipid deposition, lipid metabolism, apoptosis, and autophagy, while blood was collected to determine blood glucose and insulin. The results showed that IF and ND treatment improved lipid deposition and metabolic disorder of NAFLD mice; the increasing body weight, liver weight, and HOMA-IR index of HFD mice were also alleviated by IF and ND. Furthermore, IF and ND treatment activated the macrophage migration inhibitory factor (MIF)/AMPK pathway and regulated its downstream autophagy and apoptosis. However, the efficacy of IF was better than ND. Both IF and ND activates MIF signaling and alleviate the lipotoxicity of NAFLD while IF therapy is more effective than ND. The different MIF up-regulation might be the underlying mechanism of why IF benefits more than ND.
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".