Evidence map›Paper›PMID 35632648›Full record

ArticleViruses2022

Mathematical Modeling Finds Disparate Interferon Production Rates Drive Strain-Specific Immunodynamics during Deadly Influenza Infection.

Emily E Ackerman, Jordan J A Weaver, Jason E Shoemaker

Open access · goldAbstract read
In one paragraph

Article in Viruses, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Quantitatively Mapping Immune Control during Influenza.Current opinion in systems biology · 2024
    Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Emily E AckermanDepartment of Chemical & Petroleum Engineering, University of Pittsburgh, Pittsburgh, PA 15260, USA.
Jordan J A WeaverDepartment of Chemical & Petroleum Engineering, University of Pittsburgh, Pittsburgh, PA 15260, USA.
Jason E ShoemakerDepartment of Chemical & Petroleum Engineering, University of Pittsburgh, Pittsburgh, PA 15260, USA.ORCID 0000-0003-3315-7103
University of Pittsburgh · US

Funding

Howard Hughes Medical Institute
6 · The paper itself

Abstract

The timing and magnitude of the immune response (i.e., the immunodynamics) associated with the early innate immune response to viral infection display distinct trends across influenza A virus subtypes in vivo. Evidence shows that the timing of the type-I interferon response and the overall magnitude of immune cell infiltration are both correlated with more severe outcomes. However, the mechanisms driving the distinct immunodynamics between infections of different virus strains (strain-specific immunodynamics) remain unclear. Here, computational modeling and strain-specific immunologic data are used to identify the immune interactions that differ in mice infected with low-pathogenic H1N1 or high-pathogenic H5N1 influenza viruses. Computational exploration of free parameters between strains suggests that the production rate of interferon is the major driver of strain-specific immune responses observed in vivo, and points towards the relationship between the viral load and lung epithelial interferon production as the main source of variance between infection outcomes. A greater understanding of the contributors to strain-specific immunodynamics can be utilized in future efforts aimed at treatment development to improve clinical outcomes of high-pathogenic viral strains.

Indexed as

Influenza A Virus, H1N1 SubtypeInfluenza A Virus, H5N1 SubtypeInfluenza, HumanInterferon Type IAnimalsHumansMiceVirus ReplicationInterferon Type IODE modelingsystems biologyviral strains

Identifiers

PMID35632648
PMCPMC9147528
OpenAlexW4224986394

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.