Differential type I IFN signaling is involved in regulating neutrophil anti-fungal host responses to Aspergillus fumigatus 3902
Bibliographic record
Abstract
Abstract Description Invasive pulmonary aspergillosis (IPA), caused by the fungus Aspergillus fumigatus, generally occurs in patients with non-functioning immune systems. The recent rise in influenza and SARS-Cov-2-infected patients acquiring IPA suggests that anti-viral host responses, like type I IFNs, create an environment susceptible to fungal infection. We recently showed that absence of type I interferon receptor 2 (IFNAR) results in increased fungal clearance and damage during A. fumigatus infection compared to absence of IFNAR1. Currently, we are determining whether anti-fungal responses are involved in this. Here, we show that Ifnar2-/- PMNs killed significantly more conidia than Ifnar1-/- PMNs and this killing directly correlated with increased ROS levels. We next sought to determine the ROS response of the Ifnar2-/- PMNs to hyphae (Ifnar2-/- mice develop invasive disease) using bone-marrow (BM) derived PMNs. We found that Ifnar2-/- BM-PMNs had a faster and larger ROS burst in response to A. fumigatus hyphae compared to Ifnar1-/- and WT BM-PMNs. These results suggest that the ROS response of Ifnar2-/- PMNs may be dysregulated (hyperresponsive) and is involved in both the increased clearance and damage response occurring in the Ifnar2-/- mice during A. fumigatus infection. Together, our results expand our understanding of how anti-viral mechanisms, via IFNAR2 and IFNAR1, are creating a permissive environment for fungal infections to occur through regulation anti-fungal responses. Funding Sources Supported by NIH/NIAID K22AI153671. Topic Categories Microbial, Parasitic, and Fungal Immunology (MPF)
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".