Evidence map›Paper›PMID 39921941›Full record

ArticleComputers in biology and medicine2025

Identifying novel therapeutic targets in cystic fibrosis through advanced single-cell transcriptomics analysis.

George Sun, Yi-Hui Zhou

Abstract read
In one paragraph

Article in Computers in biology and medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
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.

George SunBioinformatics Research Center, North Carolina State University, 1 Lampe Drive, Raleigh, 27695, NC, USA.
Yi-Hui ZhouBioinformatics Research Center, North Carolina State University, 1 Lampe Drive, Raleigh, 27695, NC, USA; Departments of Biological Sciences and Statistics, North Carolina State University, 1 Lampe Drive, Raleigh, 27695, NC, USA. Electronic address: yihui_zhou@ncsu.edu.

Funding

Characterizing Gene-Environment Interactions that Affect Individual Susceptibility to an Expanding Chemical ExposomeR01ES033243 · NIEHS · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI Fred A. Wright · 2022 to 2026
$2.1M
NIEHS NIH HHS R01 ES033243
6 · The paper itself

Abstract

backgroundLung disease remains a leading cause of morbidity and mortality in individuals with cystic fibrosis (CF). Despite significant advances, the complex molecular mechanisms underlying CF-related airway pathology are not fully understood. Building upon previous single-cell transcriptomics studies in CF patients and healthy controls, this study employs enhanced analytical methodologies to deepen our understanding of CF-associated gene expression.

methodsWe employed advanced single-cell transcriptomics techniques, integrating data from multiple sources and implementing rigorous normalization and mapping strategies using a comprehensive lung reference panel. These sophisticated methods were designed to enhance the accuracy and depth of our analysis, with a focus on elucidating differential gene expression and characterizing co-expression network dynamics associated with cystic fibrosis (CF).

resultsOur analysis uncovered novel genes and regulatory networks that had not been previously associated with CF airway disease. These findings highlight new potential therapeutic targets that could be exploited to develop more effective interventions for managing CF-related lung conditions.

conclusionThis study provides critical insights into the molecular landscape of CF airway disease, offering new avenues for targeted therapeutic strategies. By identifying key genes and networks involved in CF pathogenesis, our research contributes to the broader efforts to improve the prognosis and quality of life for patients with CF. These discoveries pave the way for future studies aimed at translating these findings into clinical practice.

Indexed as

Cystic FibrosisGene Expression ProfilingSingle-Cell AnalysisTranscriptomeFemaleGene Regulatory NetworksHumansLungMaleAirway epitheliumCystic fibrosisTherapeutic targetsTranscriptomics

Identifiers

PMID39921941
PMCPMC13175635

What OpenQuestion holds

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Registered trials

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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.