Glycomic analysis of host response reveals high mannose as a key mediator of influenza severity
Bibliographic record
Abstract
Influenza virus infections cause a wide variety of outcomes, from mild disease to 3 to 5 million cases of severe illness and ∼290,000 to 645,000 deaths annually worldwide. The molecular mechanisms underlying these disparate outcomes are currently unknown. Glycosylation within the human host plays a critical role in influenza virus biology. However, the impact these modifications have on the severity of influenza disease has not been examined. Herein, we profile the glycomic host responses to influenza virus infection as a function of disease severity using a ferret model and our lectin microarray technology. We identify the glycan epitope high mannose as a marker of influenza virus-induced pathogenesis and severity of disease outcome. Induction of high mannose is dependent upon the unfolded protein response (UPR) pathway, a pathway previously shown to associate with lung damage and severity of influenza virus infection. Also, the mannan-binding lectin (MBL2), an innate immune lectin that negatively impacts influenza outcomes, recognizes influenza virus-infected cells in a high mannose-dependent manner. Together, our data argue that the high mannose motif is an infection-associated molecular pattern on host cells that may guide immune responses leading to the concomitant damage associated with severity.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".