Evidence map›Paper›PMID 38721600›Full record

ArticleFrontiers in microbiology2024

Unraveling the dynamic transcriptomic changes during the dimorphic transition of

Minghao Du, Changyu Tao, Xueyan Hu, Yun Zhang, Jun Kan, Juan Wang, Ence Yang

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. ClinicalFrontiers in fungal biology · 2026
    Article
  3. Article
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

7 authors.

Minghao Du *Department of Microbiology and Infectious Disease Center, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.
Changyu Tao *Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.
Xueyan HuDepartment of Medical Bioinformatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.
Yun ZhangDepartment of Medical Bioinformatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.
Jun KanDepartment of Medical Bioinformatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.
Juan WangDepartment of Microbiology and Infectious Disease Center, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.
Ence YangDepartment of Microbiology and Infectious Disease Center, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Systemic dimorphic fungi pose a significant public health challenge, causing over one million new infections annually. The dimorphic transition between saprophytic mycelia and pathogenic yeasts is strongly associated with the pathogenesis of dimorphic fungi. However, despite the dynamic nature of dimorphic transition, the current omics studies focused on dimorphic transition primarily employ static strategies, partly due to the lack of suitable dynamic analytical methods. Methods: We conducted time-course transcriptional profiling during the dimorphic transition of Results: By using DyGAM-NS, model, we identified 5,223 DTIGs of Discussion: Our study elucidates the dynamic transcriptional profile changes during the dimorphic transition of

Indexed as

dimorphic transitiongeneralized additive modelgene regulatory network (GRN)Talaromyces marneffeitime-course transcriptomics

Identifiers

PMID38721600
PMCPMC11076716

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.