Annexin A1 as a key modulator of lung inflammation during coronavirus infections
Bibliographic record
Abstract
Exacerbated inflammation is a major contributor to tissue damage and mortality in infectious diseases, including SARS-CoV-2. The resolution phase of inflammation is critical for restoring tissue homeostasis following an injury. Annexin A1 (AnxA1) is a ubiquitous protein that plays a fundamental role in the resolution of inflammation, including in preclinical models of infectious disease. Here, we investigated the role of AnxA1 in coronavirus infection and its potential as a host-targeted therapeutic strategy against SARS-CoV-2. Wildtype (WT) and AnxA1 knockout (AnxA1KO) mice were intranasally infected with the murine betacoronavirus MHV-3 to study the endogenous role of AnxA1. Immunohistochemistry and Western blot analyses in the lungs of MHV-3-infected mice revealed increased AnxA1 expression and its cleavage, which was associated with neutrophilic infiltration (Ly6G+ cells) mainly in peribronchiolar and perivascular regions. AnxA1-deficient mice exhibited higher neutrophilic infiltration and lung damage, alongside increased CXCL1 production in the lungs, when compared with WT-infected mice. In a murine model of SARS-CoV-2 infection in K18-hACE2 mice, we found increased AnxA1 cleavage associated with lung inflammation. Treatment of SARS-CoV-2-infected K18-hACE2 mice with the AnxA1-mimetic peptide, Ac2-26, reduced lung damage and lethality, without altering the host ability to deal with viral replication. Notably, Ac2-26-treated mice exhibited similar levels of protection to that afforded by the nucleotide analog Remdesivir, following SARS-CoV-2 infection. Our findings highlight the protective role of the endogenous AnxA1 in mitigating coronavirus-induced lung inflammation and underscore the therapeutic potential of AnxA1 mimetic Ac2-26 as a host-targeted therapy against SARS-CoV-2.
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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 | 0.000 | 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".