Evidence map›Paper›PMID 31161783›Full record

ArticleCell transplantation

Analysis of Synapses in Cerebral Organoids.

Abraam M Yakoub, Mark Sadek

Open access · goldAbstract read
In one paragraph

Article in Cell transplantation. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 11% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

  1. Pooled it
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  5. Brain organoids: A new tool for modelling of neurodevelopmental disorders.Journal of cellular and molecular medicine · 2024
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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 2 institutions in 1 country.

Abraam M YakoubDepartment of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA.
Mark SadekDepartment of Pharmaceutical Biotechnology, University of Illinois College of Pharmacy, Chicago, IL, USA.
Illinois College · USStanford University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cerebral organoids are an emerging cutting-edge technology to model human brain development and neurodevelopmental disorders, for which mouse models exhibit significant limitations. In the human brain, synaptic connections define neural circuits, and synaptic deficits account for various neurodevelopmental disorders. Thus, harnessing the full power of cerebral organoids for human brain modeling requires the ability to visualize and analyze synapses in cerebral organoids. Previously, we devised an optimized method to generate human cerebral organoids, and showed that optimal organoids express mature-neuron markers, including synaptic proteins and neurotransmitter receptors and transporters. Here, we give evidence for synaptogenesis in cerebral organoids, via microscopical visualization of synapses. We also describe multiple approaches to quantitatively analyze synapses in cerebral organoids. Collectively, our work provides sufficient evidence for the possibility of modeling synaptogenesis and synaptic disorders in cerebral organoids, and may help advance the use of cerebral organoids in molecular neuroscience and studies of neurodevelopmental disorders such as autism.

Indexed as

Models, NeurologicalCerebellumHumansNerve Tissue ProteinsNeurodevelopmental DisordersOrganoidsSynapsesNerve Tissue Proteinsautismcerebral organoidshuman brainneurodevelopmental disordersstem cellssynapsessynaptic deficits

Identifiers

PMID31161783
PMCPMC6767899
OpenAlexW2948588843

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.