Evidence map›Paper›PMID 38585853›Full record

ArticlebioRxiv : the preprint server for biology2024

Three Modes of Viral Adaption by the Heart.

Cameron D Griffiths, Millie Shah, William Shao, Cheryl A Borgman, Kevin A Janes

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Cameron D GriffithsDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA.
Millie ShahDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA.
William ShaoDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA.
Cheryl A BorgmanDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA.
Kevin A JanesDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA.ORCID 0000-0002-8028-6138
University of Virginia · US

Funding

Biotechnology Training ProgramT32GM136615 · NIGMS · UNIVERSITY OF VIRGINIA · PI Silvia Salinas Blemker, Kimberly A. Kelly · 2020 to 2026
$3.4M
Systems-biology Approaches for Decoding Persistent Coxsackievirus B3 InfectionR21AI105970 · NIAID · UNIVERSITY OF VIRGINIA · PI JANES, KEVIN A · 2013 to 2014
$426k
NIAID NIH HHS R21 AI105970NIGMS NIH HHS T32 GM136615
6 · The paper itself

Abstract

Viruses elicit long-term adaptive responses in the tissues they infect. Understanding viral adaptions in humans is difficult in organs such as the heart, where primary infected material is not routinely collected. In search of asymptomatic infections with accompanying host adaptions, we mined for cardio-pathogenic viruses in the unaligned reads of nearly one thousand human hearts profiled by RNA sequencing. Among virus-positive cases (~20%), we identified three robust adaptions in the host transcriptome related to inflammatory NFκB signaling and post-transcriptional regulation by the p38-MK2 pathway. The adaptions are not determined by the infecting virus, and they recur in infections of human or animal hearts and cultured cardiomyocytes. Adaptions switch states when NFκB or p38-MK2 are perturbed in cells engineered for chronic infection by the cardio-pathogenic virus, coxsackievirus B3. Stratifying viral responses into reversible adaptions adds a targetable systems-level simplification for infections of the heart and perhaps other organs.

Identifiers

PMID38585853
PMCPMC10996681
OpenAlexW4393344318

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.