Evidence map›Paper›PMID 27048814›Full record

ReviewCellular and molecular life sciences : CMLS2016

Necroptosis-independent signaling by the RIP kinases in inflammation.

Kenta Moriwaki, Francis Ka-Ming Chan

Open access · greenAbstract readReview
In one paragraph

Review in Cellular and molecular life sciences : CMLS, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed
5.7field-weighted citation impact, top 4% 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

60 citing papers in PubMed, 93 citations in OpenAlex.

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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.

Kenta MoriwakiDepartment of Pathology, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA, 01605, USA.
Francis Ka-Ming ChanDepartment of Pathology, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA, 01605, USA. francis.chan@umassmed.edu.
University of Massachusetts Chan Medical School · US

Funding

Necroptosis signaling adaptors in inflammatory diseasesR01AI119030 · NIAID · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI CHAN, FRANCIS KAMING · 2016 to 2019
$1.6M
Programmed necrosis in Immune ResponsesR01AI083497 · NIAID · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI CHAN, FRANCIS KAMING · 2010 to 2013
$1.6M
NIAID NIH HHS R01 AI083497NIAID NIH HHS R01 AI119030
6 · The paper itself

Abstract

Recent advances have identified a signaling cascade involving receptor interacting protein kinase 1 (RIPK1), RIPK3 and the pseudokinase mixed lineage kinase domain-like (MLKL) that is crucial for induction of necroptosis, a non-apoptotic form of cell death. RIPK1-RIPK3-MLKL-mediated necroptosis has been attributed to cause many inflammatory diseases through the release of cellular damage-associated molecular patterns (DAMPs). In addition to necroptosis, emerging evidence suggests that these necroptosis signal adaptors can also facilitate inflammation independent of cell death. In particular, the RIP kinases can drive NF-κB and inflammasome activation independent of cell death. In this review, we will discuss recent discoveries that led to this realization and present arguments why cell death-independent signaling by the RIP kinases may have a more important role in inflammation than necroptosis.

Indexed as

AnimalsApoptosisInflammasomesInflammationMiceMice, KnockoutNecrosisNF-kappa BProtein KinasesReceptor-Interacting Protein Serine-Threonine KinasesInflammasomesMLKL protein, mouseNF-kappa BProtein KinasesReceptor-Interacting Protein Serine-Threonine KinasesRipk1 protein, mouseRipk3 protein, mouseIL-1βNF-κBRelBRIPK1RIPK3

Identifiers

PMID27048814
PMCPMC4889460
OpenAlexW2323272925

What OpenQuestion holds

Textmetadata
LicenceTDM
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.