Evidence map›Paper›PMID 39266958›Full record

ReviewBMC infectious diseases2024

Hepatitis E virus immunosuppressed animal models.

Kush Kumar Yadav, Scott P Kenney

Abstract readReview
In one paragraph

Review in BMC infectious diseases, 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.

No citing paper in PubMed yet.

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

2 authors.

Kush Kumar YadavCenter for Food Animal Health, Department of Animal Sciences, The Ohio State University, 1680 Madison Ave, Wooster, OH, 44691, USA.
Scott P KenneyCenter for Food Animal Health, Department of Animal Sciences, The Ohio State University, 1680 Madison Ave, Wooster, OH, 44691, USA. kenney.157@osu.edu.

Funding

Evaluating hepatitis E virus ribavirin resistance clinical outcomes in the immunosuppressed pig modelR21AI151736 · NIAID · OHIO STATE UNIVERSITY · PI JUNG, KWONIL, KENNEY, SCOTT P · 2021 to 2022
$410k
National Institutes of Allergy and Infectious Diseases R21AI151736NIAID NIH HHS R21 AI151736
6 · The paper itself

Abstract

Hepatitis E virus (HEV) is an important emerging pathogen producing significant morbidity in immunosuppressed patients. HEV has been detrimental to solid organ transplant (SOT) patients, cancer patients, and HIV-positive patients, where chronic HEV infections occur. Blood-borne transfusions and multiple cases of chronic HEV infection in transplant patients have been reported in the past few decades, necessitating research on HEV pathogenesis using immunosuppressed animal models. Numerous animal species with unique naturally occurring HEV strains have been found, several of which have the potential to spread to humans and to serve as pathogenesis models. Host immunosuppression leads to viral persistence and chronic HEV infection allows for genetic adaptation to the human host creating new strains with worse disease outcomes. Procedures necessary for SOT often entail blood transfusions placing immunosuppressive patients into a "high risk group" for HEV infection. This scenario requires an appropriate immunosuppressive animal model to understand disease patterns in these patients. Hence, this article reviews the recent advances in the immunosuppressed animal models for chronic HEV infection with emphasis on pathogenesis, immune correlates, and the liver pathology associated with the chronic HEV infections.

Indexed as

Disease Models, AnimalHepatitis EHepatitis E virusImmunocompromised HostAnimalsHumansAnimalChronicHepatitisHumansImmunosuppressedInfectionModels

Identifiers

PMID39266958
PMCPMC11395946

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.