Evidence map›Paper›PMID 33716967›Full record

ArticleFrontiers in endocrinology2021

Using Single-Cell RNA-Seq Data to Trace Tissue Cells Responsive to Thyroid Hormones.

Liang Hu, Chao Wu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2021. 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
0.2field-weighted citation impact, top 49% of its field
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, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. T3 levels and thyroid hormone signaling.Frontiers in endocrinology · 2022
    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 at 1 institution in 1 country.

Liang HuDepartment of Thyroid Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Chao WuState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
First Affiliated Hospital Zhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thyroid hormones mediate a remarkable range of functions in many tissues and organ systems through the thyroid hormone receptors-THRA and THRB. Tissues and organs are composed of heterogeneous cells of different cell types. These different cell types have varying receptor expression abilities, which lead to variable responses in thyroid hormone regulation. The tissue-specific Thra and Thrb gene expression patterns help us understand the action of thyroid hormones at the tissue level. However, the situation becomes complicated if we wish to focus on tissues more closely to trace the responsive cells, which is a vital step in the process of understanding the molecular mechanism of diseases related to thyroid hormone regulation. Single-cell RNA sequencing technology is a powerful tool used to profile gene expression programs in individual cells. The Tabula Muris Consortium generates a single-cell transcriptomic atlas across the life span of

Indexed as

Organ SpecificityAnimalsBiomarkersCell LineageComputational BiologyData AnalysisFemaleGene ExpressionMaleMiceMice, Inbred C57BLOrganogenesisReceptors, Thyroid HormoneRNA-SeqSingle-Cell AnalysisThyroid HormonesBiomarkersReceptors, Thyroid HormoneThyroid HormonesTriiodothyroninebioinformatics analysiscell-type-specific expressionsingle-cell RNA-SeqThra/Thrbthyroid hormone

Identifiers

PMID33716967
PMCPMC7943891
OpenAlexW3129669178

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.