Evidence map›Paper›PMID 41135097›Full record

ReviewAging and disease2025

Cellular Characterization and Neural Electrophysiology in Cerebral Organoid Models of Neurological Disorders.

Quankun Zhou, Ling Ma, Bangming Guo, Peng Li, Ye Song

Abstract readReview
In one paragraph

Review in Aging and disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Quankun ZhouDepartment of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Ling MaDepartment of Neurosurgery, Guangzhou Women and Children's Medical Center, Guangzhou, China.
Bangming GuoDepartment of Neurosurgery, The First Affiliated Hospital of Gannan Medical University, Ganzhou, China.
Peng LiDepartment of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Ye SongDepartment of Neurosurgery, Guangzhou Women and Children's Medical Center, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human cerebral organoids (hCOs), generated in vitro from induced pluripotent stem cells (iPSCs) or human embryonic stem cells (hESCs), exhibit cellular compositions similar to those of specific human brain regions. These organoids simulate early stages of brain development and can serve as in vitro disease models, providing a unique platform for studying neurodevelopmental processes and investigating underlying disease mechanisms. This review systematically summarizes research progress on cellular characteristics and neural electrophysiology in hCO-based models of neurodevelopmental disorders, neurodegenerative diseases, psychiatric disorders, epilepsy, viral infections, and traumatic brain injuries. These studies have elucidated the mechanisms underlying neuroelectrophysiological dysfunction in related diseases and facilitated innovative therapeutic explorations. Current limitations include prolonged culture durations and high costs, insufficient standardization that compromises reproducibility, the absence of neurovascular units that restrict pathological fidelity, immature laminar architectures that hinder complex circuit modeling, and electrophysiological bottlenecks in network-level analysis. Future efforts should focus on optimizing hCO culture protocols, innovating electrophysiological detection technologies, and promoting their clinical translation.

Indexed as

BrainNervous System DiseasesOrganoidsAnimalsElectrophysiological PhenomenaHumansInduced Pluripotent Stem Cells

Identifiers

PMID41135097
PMCPMC13653708

What OpenQuestion holds

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Registered trials

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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.