Evidence map›Paper›PMID 41619856›Full record

ReviewMolecules and cells2026

A decade of progress in understanding LRRTM and Slitrk synaptic cell-adhesion molecules.

Dongwook Kim, Byeongchan Kim, Ji Won Um, Jaewon Ko

Abstract readReview
In one paragraph

Review in Molecules and cells, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Dongwook KimDepartment of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Korea; Center for Synapse Diversity and Specificity, DGIST, Daegu 42988, Korea.
Byeongchan KimDepartment of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Korea.
Ji Won UmDepartment of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Korea; Center for Synapse Diversity and Specificity, DGIST, Daegu 42988, Korea.
Jaewon KoDepartment of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Korea; Center for Synapse Diversity and Specificity, DGIST, Daegu 42988, Korea. Electronic address: jaewonko@dgist.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For over a decade, synaptic cell-adhesion molecules (CAMs) have been recognized as fundamental determinants of neural circuit specificity and diversity. Among the CAMs, leucine-rich repeat-containing transmembrane proteins have been established as crucial regulators of synaptic properties across diverse cell types and brain regions. This minireview focuses on two families of leucine-rich repeat-containing CAMs: leucine-rich repeat transmembrane proteins and the Slit and Trk-like family. We provide a comprehensive synthesis of significant findings on leucine-rich repeat transmembrane proteins and Slit and Trk-like family since their initial characterization more than 15 years ago. Furthermore, we outline key unresolved questions to stimulate future studies on their functional mechanisms in neural circuit assembly and their pathophysiological roles in various neurological disorders.

Indexed as

Cell Adhesion MoleculesCell Adhesion Molecules, NeuronalMembrane ProteinsNerve Tissue ProteinsSynapsesAnimalsHumansLeucine-Rich Repeat ProteinsCell Adhesion MoleculesCell Adhesion Molecules, NeuronalLeucine-Rich Repeat ProteinsMembrane ProteinsNerve Tissue ProteinsBrain disordersLeucine-rich repeatLeucine-rich repeat transmembrane proteinsSlit and Trk-like familySynaptic cell-adhesion molecule

Identifiers

PMID41619856
PMCPMC13100631

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.