Evidence map›Paper›PMID 39605344›Full record

ArticlebioRxiv : the preprint server for biology2024

Rhinovirus as a Driver of Airway T-Cell Dynamics in Children with Severe Asthma.

Naomi Bryant, Lyndsey M Muehling, Kristin Wavell, W Gerald Teague, Judith A Woodfolk

Abstract 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.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Lyndsey M MuehlingORCID 0000-0003-3203-3264
Kristin Wavell
W Gerald Teague
Judith A WoodfolkORCID 0000-0002-8915-4334

Funding

Immune Programs and Related T Cell Mechanisms of Pulmonary Complications After COVID-19 IllnessR56AI178669 · NIAID · UNIVERSITY OF VIRGINIA · PI WOODFOLK, JUDITH A · 2023 to 2023
$410k
NIAID NIH HHS R56 AI178669
6 · The paper itself

Abstract

Severe asthma in children is notoriously difficult to treat, and its immunopathogenesis is complex. In particular, the contribution of T cells and relationships to anti-viral immunity, remain enigmatic. Here, we coupled deep phenotyping with machine learning methods to resolve the dynamics of T cells in the diseased lower airways, and examined rhinovirus (RV) as a driver. Our strategy revealed a T-cell landscape dominated by type 1 and type 17 CD8+ signatures. Interrogation of phenotypic relationships coupled with trajectory mapping identified T-cell migratory and differentiation pathways spanning the blood and airways that culminated in tissue residency, and included transitions between type 1 and type 17 tissue-resident types. These T-cell dynamics were reflected in cytokine polyfunctionality

Identifiers

PMID39605344
PMCPMC11601360

What OpenQuestion holds

Textmetadata
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.