Evidence map›Paper›PMID 41279074›Full record

ArticlebioRxiv : the preprint server for biology2025

Coevolutionary dynamics of viruses and their defective interfering particles.

Shiv Muthupandiyan, John Yin

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

5 · Who and what money

Authors and funding

2 authors.

Shiv MuthupandiyanWisconsin Institute for Discovery, Chemical and Biological Engineering, University of Wisconsin-Madison, 330 N Orchard St, Madison, Wisconsin 53715, USA.
John YinWisconsin Institute for Discovery, Chemical and Biological Engineering, University of Wisconsin-Madison, 330 N Orchard St, Madison, Wisconsin 53715, USA.ORCID 0000-0001-6146-0594

Funding

A new hybrid modeling framework combining biophysics and deep learning to predict and optimize peripheral neuromodulation outcomes in lower urinary tract diseaseR01DK133605 · NIDDK · FLORIDA INTERNATIONAL UNIVERSITY · PI Zachary C Danziger · 2022 to 2026
$3.1M
A New Paradigm for Systems Physiology Modeling: Biomechanistic Learning Augmentation with Deep Differential Equation Representations (BLADDER)OT2OD030524 · OD · FLORIDA INTERNATIONAL UNIVERSITY · PI DANZIGER, ZACHARY C · 2020 to 2021
$1.9M
NIDDK NIH HHS R01 DK133605NIH HHS OT2 OD030524
6 · The paper itself

Abstract

Defective interfering particles (DIPs) are viral mutants that arise naturally during infection. Because they lack one or more essential functions, DIPs cannot replicate on their own, but they can parasitize intact viruses during co-infection by competing for growth resources, thereby interfering with viral replication. The evolutionary interplay between viruses and their DIPs involves growth, mutation, interference, and resource trade-offs, but the mechanisms shaping population-level outcomes remain poorly understood. To address this, we developed a continuous phenotype-space model using coupled partial differential equations that incorporate mutation, phenotype-dependent interference, intrinsic fitness costs, and

Identifiers

PMID41279074
PMCPMC12633390

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.