Evidence map›Paper›PMID 23396805›Full record

ArticleImmune network2012

Signaling for synergistic activation of natural killer cells.

Hyung-Joon Kwon, Hun Sik Kim

Open access · hybridAbstract read
In one paragraph

Article in Immune network, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.3field-weighted citation impact, top 41% 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

10 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Enhancing network activation in natural killer cells: predictions from in silico modeling.Integrative biology : quantitative biosciences from nano to macro · 2020
    Article
  8. Article
  9. Article
  10. Beware of NK cells in pre-clinical metastasis models.Clinical & experimental metastasis · 2013
    Article
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.

Hyung-Joon KwonDepartment of Medicine, Graduate School, University of Ulsan College of Medicine, Seoul 138-736, Korea.
Hun Sik Kim
University of Ulsan · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Natural killer (NK) cells play a pivotal role in early surveillance against virus infection and cellular transformation, and are also implicated in the control of inflammatory response through their effector functions of direct lysis of target cells and cytokine secretion. NK cell activation toward target cell is determined by the net balance of signals transmitted from diverse activating and inhibitory receptors. A distinct feature of NK cell activation is that stimulation of resting NK cells with single activating receptor on its own cannot mount natural cytotoxicity. Instead, specific pairs of co-activation receptors are required to unleash NK cell activation via synergy-dependent mechanism. Because each co-activation receptor uses distinct signaling modules, NK cell synergy relies on the integration of such disparate signals. This explains why the study of the mechanism underlying NK cell synergy is important and necessary. Recent studies revealed that NK cell synergy depends on the integration of complementary signals converged at a critical checkpoint element but not on simple amplification of the individual signaling to overcome intrinsic activation threshold. This review focuses on the signaling events during NK cells activation and recent advances in the study of NK cell synergy.

Indexed as

Activating receptorNatural killer cellSignalingSynergy

Identifiers

PMID23396805
PMCPMC3566418
OpenAlexW2148801836

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.