Evidence map›Paper›PMID 29657255›Full record

ArticleJournal of clinical and experimental hematopathology : JCEH2018

Genome-wide siRNA screening in mouse bone marrow-derived macrophages revealed that knockdown of ribosomal proteins suppresses IL-10 and enhances TNF-α production.

Yoshihiko Okamura, Naoyuki Makita, Yoshiyuki Hizukuri, Yasuhiro Hayashi

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical and experimental hematopathology : JCEH, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 97% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 2 institutions in 2 countries.

Yoshihiko Okamura
Naoyuki Makita
Yoshiyuki Hizukuri
Yasuhiro Hayashi
Kobe Asahi Hospital · JPDaiichi Sankyo (Germany) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Macrophages play a central role in the immune response, and their diverse functions are attributed to the spectrum of their functional states. To elucidate molecules involved in modulating the balance between the anti-inflammatory cytokine IL-10 and the pro-inflammatory cytokine TNF-α, we conducted genome-wide siRNA screening. First, we established an siRNA screening system using mouse bone marrow-derived macrophages, which are a suitable model for studying functional states of macrophages in vitro. In the primary screen and the subsequent reproducibility assay, 112 siRNA pools demonstrated enhancement of IL-10 production and 497 siRNA pools suppressed IL-10 production. After a deconvolution assay for IL-10-up-regulating siRNA pools, 8 genes were identified as IL-10 repressors, including Cnot1 and Rc3h1, components of the CCR4-NOT complex known to degrade cytokine mRNAs. On the other hand, siRNA pools targeting ribosomal proteins were frequently found among those that down-regulated IL-10 production and up-regulated TNF-α production. Four pools were assayed using deconvoluted siRNAs and identified as high-confidence hits. Thus, we found that the genome-wide knockdown of 19 ribosomal proteins resulted in decreased IL-10 and increased TNF-α production.

Indexed as

Gene Expression RegulationGene Knockdown TechniquesAnimalsBone Marrow CellsGenome-Wide Association StudyInterleukin-10MacrophagesMiceRibosomal ProteinsTumor Necrosis Factor-alphaIL10 protein, mouseInterleukin-10Ribosomal ProteinsTumor Necrosis Factor-alphagenome-wide siRNA screeninterleukin-10macrophagesribosomal proteins

Identifiers

PMID29657255
PMCPMC6413152
OpenAlexW2797332156

What OpenQuestion holds

Textmetadata
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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.