Evidence map›Paper›PMID 36860877›Full record

ReviewFrontiers in immunology2023

Phase separation in innate immune response and inflammation-related diseases.

Huihui Ma, Mingxi Liu, Rao Fu, Jia Feng, Haoran Ren, Jingyan Cao, Ming Shi

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Review
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  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. International journal of general medicine · 2024
    Article
  10. Article
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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

7 authors.

Huihui MaSchool of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
Mingxi LiuSchool of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
Rao FuSchool of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
Jia FengSchool of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
Haoran RenSchool of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
Jingyan CaoDepartment of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Ming ShiSchool of Life Science and Technology, Harbin Institute of Technology, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inflammation induced by nonspecific pathogenic or endogenous danger signals is an essential mechanism of innate immune response. The innate immune responses are rapidly triggered by conserved germline-encoded receptors that recognize broad patterns indicative of danger, with subsequent signal amplification by modular effectors, which have been the subject of intense investigation for many years. Until recently, however, the critical role of intrinsic disorder-driven phase separation in facilitating innate immune responses went largely unappreciated. In this review, we discuss emerging evidences that many innate immune receptors, effectors, and/or interactors function as "all-or-nothing" switch-like hubs to stimulate acute and chronic inflammation. By concentrating or relegating modular signaling components to phase-separated compartments, cells construct flexible and spatiotemporal distributions of key signaling events to ensure rapid and effective immune responses to a myriad of potentially harmful stimuli.

Indexed as

Immunity, InnateInflammationGerm CellsHumansSignal Transductioninflammatory responseinnate immune responseintrinsic disorderphase separationspatiotemporal control

Identifiers

PMID36860877
PMCPMC9970293

What OpenQuestion holds

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LicenceCC BY
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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.