Regulation of kynurenine biosynthesis during influenza virus infection
Bibliographic record
Abstract
Influenza A viruses (IAVs) remain serious threats to public health because of the shortage of effective means of control. Developing more effective virus control modalities requires better understanding of virus-host interactions. It has previously been shown that IAV induces the production of kynurenine, which suppresses T-cell responses, enhances pain hypersensitivity and disturbs behaviour in infected animals. However, the regulation of kynurenine biosynthesis during IAV infection remains elusive. Here we showed that IAV infection induced expression of interferons (IFNs), which upregulated production of indoleamine-2,3-dioxygenase (IDO1), which catalysed the kynurenine biosynthesis. Furthermore, IAV attenuated the IDO1 expression and the production of kynurenine through its NS1 protein. Interestingly, inhibition of viral replication prior to IFN induction limited IDO1 expression, while inhibition after did not. Finally, we showed that kynurenine biosynthesis was activated in macrophages in response to other stimuli, such as influenza B virus, herpes simplex virus 1 and 2 as well as bacterial lipopolysaccharides. Thus, the tight regulation of the kynurenine biosynthesis by host cell and, perhaps, pathogen might be a basic signature of a wide range of host-pathogen interactions, which should be taken into account during development of novel antiviral and antibacterial drugs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".