Bibliographic record
Abstract
Enteric symptomology seen in early-stage severe acute respiratory syndrome (SARS)-2003 and COVID-19 is evidence of virus replication occurring in the intestine, liver and pancreas. Aberrant lipid metabolism in morbidly obese individuals adversely affects the COVID-19 immune response and increases disease severity. Such observations are in line with the importance of lipid metabolism in COVID-19, and point to the gut as a site for intervention as well as a therapeutic target in treating the disease. Formation of complex lipid membranes and palmitoylation of coronavirus proteins are essential during viral replication and assembly. Inhibition of fatty acid synthase (FASN) and restoration of lipid catabolism by activation of AMP-activated protein kinase (AMPK) impede replication of coronaviruses closely related to SARS-coronavirus-2 (CoV-2). In vitro findings and clinical data reveal that the FASN inhibitor, orlistat, and the AMPK activator, metformin, may inhibit coronavirus replication and reduce systemic inflammation to restore immune homeostasis. Such observations, along with the known mechanisms of action for these types of drugs, suggest that targeting fatty acid lipid metabolism could directly inhibit virus replication while positively impacting the patient's response to COVID-19.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".