Evidence map›Paper›PMID 34413487›Full record

ReviewCellular & molecular immunology2022

Metabolic programming in dendritic cells tailors immune responses and homeostasis.

Sofie Hedlund Møller, Limei Wang, Ping-Chih Ho

Open access · hybridAbstract readReview
In one paragraph

Review in Cellular & molecular immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 98 papers.

0numbers the graph read from it
0cells of the map it votes in
98citing papers in PubMed
6.0field-weighted citation impact, top 3% 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

98 citing papers in PubMed, 140 citations in OpenAlex.

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  16. Identification and Screening of Lactate-Related Genes as Molecular Markers for Early Diagnosis of Steroid-Induced Osteonecrosis of the Femoral Head.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
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38 more citing papers are in PubMed but not listed here.

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

3 authors at 1 institution in 1 country.

Sofie Hedlund Møller *Department of Fundamental Oncology, University of Lausanne, Lausanne, Switzerland.
Limei Wang *Department of Fundamental Oncology, University of Lausanne, Lausanne, Switzerland.
Ping-Chih HoDepartment of Fundamental Oncology, University of Lausanne, Lausanne, Switzerland. ping-chih.ho@unil.ch.ORCID http://orcid.org/0000-0003-3078-3774
Ludwig Cancer Research · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is being increasingly acknowledged that immune cells depend on certain metabolic traits to perform their functions and that the extracellular environment can influence cell metabolism and vice versa. Dendritic cell (DC) subsets traffic through highly diverse environments from the bone marrow, where they develop, to the various peripheral tissues, where they differentiate and capture antigens, before they migrate to the lymph node to present antigens and prime T cells. It is plausible that DC subsets modulate their stimulatory abilities in response to unique metabolic programming. The metabolic requirements of DCs are just recently being discovered, and subset- and context-specific metabolic phenotypes in DCs are highly intertwined with DC functions. In this review, we present the current knowledge on the intrinsic and extrinsic determinants of DC metabolism, how they regulate DC function with examples from tumor biology and in interaction with the microbiota, and discuss how this can be applied therapeutically.

Indexed as

Dendritic CellsT-LymphocytesHomeostasisImmunityLymph NodesDendritic cellsHomeostasisImmunometabolismMicrobiotaTumor immunity

Identifiers

PMID34413487
PMCPMC8891341
OpenAlexW3195667519

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.