Evidence map›Paper›PMID 18406636›Full record

ReviewBlood cells, molecules & diseases

Mast cell transcriptional networks.

Clifford M Takemoto, Youl-Nam Lee, Anil G Jegga, Daniella Zablocki, Stephanie Brandal, Amir Shahlaee, Suming Huang, Ying Ye, Sivakumar Gowrisankar, Jimmy Huynh and 1 more

Abstract readReview
In one paragraph

Review in Blood cells, molecules & diseases. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Review
  2. Review
  3. Mast Cell Activation in the Systemic Sclerosis Esophagus.Journal of scleroderma and related disorders · 2021
    Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. The gestational power of mast cells in the injured tissue.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2018
    Review
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. 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

11 authors.

Clifford M TakemotoDivision of Pediatric Hematology, The Johns Hopkins University, Baltimore, MD 21205, USA. ctakemot@jhmi.edu
Youl-Nam Lee
Anil G Jegga
Daniella Zablocki
Stephanie Brandal
Amir Shahlaee
Suming Huang
Ying Ye
Sivakumar Gowrisankar
Jimmy Huynh
Michael A McDevitt

Funding

Genetic networks that regulate the mast lineageR01HL077178 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI TAKEMOTO, CLIFFORD M · 2005 to 2009
$1.6M
NHLBI NIH HHS 5R01HL077178NHLBI NIH HHS R01 HL077178
6 · The paper itself

Abstract

Unregulated activation of mast cells can contribute to the pathogenesis of inflammatory and allergic diseases, including asthma, rheumatoid arthritis, inflammatory bowel disease, and multiple sclerosis. Absence of mast cells in animal models can lead to impairment in the innate immune response to parasites and bacterial infections. Aberrant clonal accumulation and proliferation of mast cells can result in a variety of diseases ranging from benign cutaneous mastocytosis to systemic mastocytosis or mast cell leukemia. Understanding mast cell differentiation provides important insights into mechanisms of lineage selection during hematopoiesis and can provide targets for new drug development to treat mast cell disorders. In this review, we discuss controversies related to development, sites of origin, and the transcriptional program of mast cells.

Indexed as

Gene Regulatory NetworksAnimalsGATA1 Transcription FactorHumansMast CellsProtein IsoformsTranscription FactorsGATA1 Transcription FactorProtein IsoformsTranscription Factors

Identifiers

PMID18406636
PMCPMC2478671

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.