Evidence map›Paper›PMID 37227044›Full record

ArticleBiotechnology and bioengineering2023

Reconstructing the cell-cell interaction network among mouse immune cells.

Somayeh Azadian, Alireza Doustmohammadi, Mohadeseh Naseri, Masoud Khodarahmi, Seyed Shahriar Arab, Mahboubeh Yazdanifar, Javad Zahiri, Nathan E Lewis

Open access · bronzeAbstract read
In one paragraph

Article in Biotechnology and bioengineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

13 citing papers in PubMed, 13 citations in OpenAlex.

  1. Integration of Bulk RNA Sequencing and Single-Cell Sequencing to Identify Prognostic Genes Associated With MCDRGs in Neuroblastoma.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
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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

8 authors at 6 institutions in 4 countries.

Somayeh AzadianBioinformatics and Computational Omics Lab (BioCOOL), Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University (TMU), Tehran, Iran.
Alireza DoustmohammadiDepartment of Molecular Virology, Pasteur Institute of Iran, Tehran, Iran.
Mohadeseh NaseriInstitute of Infectious Diseases and Infection Control, Jena University Hospital, Jena, Germany.
Masoud KhodarahmiBahar Medical Centre, Karaj, Iran.
Seyed Shahriar ArabDepartment of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University (TMU), Tehran, Iran.
Mahboubeh YazdanifarDepartment of Pediatrics, Stem Cell Transplantation and Regenerative Medicine, Stanford University School of Medicine, Palo Alto, California, USA.
Javad ZahiriDepartment of Neuroscience, University of California San Diego, San Diego, California, USA.
Nathan E LewisDepartment of Pediatrics, La Jolla, California, USA.
Tarbiat Modares University · IRUniversity of California San Diego · USBahria University · PKCalifornia Institute for Regenerative Medicine · USJena University Hospital · DEPasteur Institute of Iran · IR

Funding

Unraveling the mammalian secretory pathway through systems biology and algorithm developmentR35GM119850 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LEWIS, NATHAN ENOCH · 2016 to 2025
$4.3M
ImmCellFIE: producing high-resolution snapshots of the functions of immune cellsUH2AI153029 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LEWIS, NATHAN ENOCH, ROBASKY, KIMBERLY JOAN · 2020 to 2021
$445k
NIAID NIH HHS UH2 AI153029NIGMS NIH HHS R35 GM119850
6 · The paper itself

Abstract

Intercellular interactions and cell-cell communication are critical to regulating cell functions, especially in normal immune cells and immunotherapies. Ligand-receptor pairs mediating these cell-cell interactions can be identified using diverse experimental and computational approaches. Here, we reconstructed the intercellular interaction network between Mus musculus immune cells using publicly available receptor-ligand interaction databases and gene expression data from the immunological genome project. This reconstructed network accounts for 50,317 unique interactions between 16 cell types between 731 receptor-ligand pairs. Analysis of this network shows that cells of hematopoietic lineages use fewer communication pathways for interacting with each other, while nonhematopoietic stromal cells use the most network communications. We further observe that the WNT, BMP, and LAMININ pathways are the most significant contributors to the overall number of cell-cell interactions among the various pathways in the reconstructed communication network. This resource will enable the systematic analysis of normal and pathologic immune cell interactions, along with the study of emerging immunotherapies.

Indexed as

Immune SystemSignal TransductionBlood CellsImmunotherapyLigandsLymph NodesNeurokinin BReceptors, BombesinStromal CellsLigandsNeurokinin Bneuromedin BReceptors, Bombesincell-cell interactionimmune systemimmunological genome projectintercellular interactionnetwork reconstruction

Identifiers

PMID37227044
PMCPMC10524935
OpenAlexW4378173537

What OpenQuestion holds

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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.