Author response: Akt-mTORC1 signaling regulates Acly to integrate metabolic input to control of macrophage activation
Bibliographic record
Abstract
Macrophages are immune cells that are found in most of the tissues of the body. Exactly what the macrophages do depends on which tissue they are in, and the state of the tissue. For example, M2 macrophages can multiply in numbers, heal wounds or help to fight off parasites depending on the signals they receive from their environment. Conversely, when macrophages sense pathogens such as bacteria they can also become M1 macrophages, which produce inflammatory molecules that help kill the invading bacteria. As a macrophage transforms into a more specialized state, its metabolism – the set of chemical reactions the cell performs in order to survive and thrive – also changes. This shift appears to play an important role in activating the macrophages and determining how they’ll specialize. However, little is known about how metabolism exerts this control. The metabolism of a cell can be investigated in part by studying the molecules, or “metabolites”, that the cell produces. Covarrubias et al. studied what happens when unspecialized macrophages from mice were activated by a signaling molecule called IL-4. This signaling molecule causes the cells to become M2 macrophages, and the experiments revealed that IL-4 signaling controls the amount of a metabolite called acetyl-CoA in the cells. Acetyl-CoA can influence how the DNA of a gene is packaged in a cell, and thus affect whether a gene is switched on and “expressed” or not. Covarrubias et al. therefore also analyzed a major metabolic sensing pathway – the Akt-mTORC1 pathway – and showed how this pathway was able to act as a nutrient sensor for the macrophage and control the enzyme responsible for making acetyl-CoA. Therefore, the Akt-mTORC1 pathway can control the level of gene expression changes in the macrophages as a result of IL-4 signaling. The analysis showed that the increase in acetyl-CoA levels increases the expression of some of the genes that cause the M2 macrophages to change state and develop their specialist behaviors. However, only a subset of these genes – those that encode metabolically demanding activities such as immune cell trafficking – have their expression controlled in this way. Further studies are now needed to investigate whether other macrophage types use the same pathways to control their responses.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.151 | 0.062 |
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".