Evidence map›Paper›PMID 39211854›Full record

ArticlemedRxiv : the preprint server for health sciences2024

The transcriptome of CD14

Theodoros Karampitsakos, Bochra Tourki, Minxue Jia, Carole Y Perrot, Bogdan Visinescu, Amy Zhao, Avraham Unterman, Argyris Tzouvelekis, Debabrata Bandyopadhyay, Brenda M Juan-Guardela and 6 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors.

Theodoros KarampitsakosORCID 0000-0003-0804-6292
Bochra Tourki
Carole Y Perrot
Bogdan Visinescu
Amy Zhao
Avraham Unterman
Argyris Tzouvelekis
Debabrata Bandyopadhyay
Brenda M Juan-Guardela
Antje Prasse
Imre Noth
Stephen Liggett
Panayiotis V BenosORCID 0000-0003-3172-3132
Jose D Herazo-Maya

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rationale: The association between immune-cell-specific transcriptomic profiles and Idiopathic Pulmonary Fibrosis (IPF) mortality is unknown. Objectives: To determine immune-cell-specific transcriptomic profiles associated with IPF mortality. Methods: We profiled peripheral blood mononuclear cells (PBMC) in 18 participants [University of South Florida: IPF, COVID-19, post-COVID-19 Interstitial Lung Disease (Post-COVID-19 ILD), controls] by single-cell RNA sequencing (scRNA-seq) and identified 16 immune-cell-specific transcriptomic profiles. The Scoring Algorithm of Molecular Subphenotypes (SAMS) was used to calculate Up-scores based on these 16 gene profiles. Their association with outcomes was investigated in peripheral blood, Bronchoalveolar Lavage (BAL) and lung tissue of N=416 IPF patients from six cohorts. Findings were validated in an independent IPF, PBMC scRNA-seq dataset (N=38). Measurements and main results: Cox-regression models demonstrated that 230 genes from CD14 Conclusions: The transcriptome of CD14

Identifiers

PMID39211854
PMCPMC11361223

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.