Evidence map›Paper›PMID 42362501›Full record

ArticleCell death discovery2026

Nitric oxide refines retinal circuit architecture independently of retinal wave dynamics.

Lais Takata Walter, Marília Inês Móvio, Guilherme Shigueto Vilar Higa, Cayo Antônio Soares de Almeida, Reza Raeisossadati, Fernando da Silva Borges, Mariana Sacrini Ayres Ferraz, Giselle Cerchiaro, Christian Schmeltzer, Sten Rüdiger and 1 more

Abstract read
In one paragraph

Article in Cell death discovery, 2026. 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

11 authors.

Lais Takata Walter *Centro de Matemática, Computação e Cognição, Universidade Federal do ABC, São Bernardo do Campo, SP, Brazil.
Marília Inês Móvio *Centro de Matemática, Computação e Cognição, Universidade Federal do ABC, São Bernardo do Campo, SP, Brazil.
Guilherme Shigueto Vilar HigaCentro de Matemática, Computação e Cognição, Universidade Federal do ABC, São Bernardo do Campo, SP, Brazil.
Cayo Antônio Soares de AlmeidaCentro de Matemática, Computação e Cognição, Universidade Federal do ABC, São Bernardo do Campo, SP, Brazil.
Reza RaeisossadatiCentro de Matemática, Computação e Cognição, Universidade Federal do ABC, São Bernardo do Campo, SP, Brazil.
Fernando da Silva BorgesCentro de Matemática, Computação e Cognição, Universidade Federal do ABC, São Bernardo do Campo, SP, Brazil.
Mariana Sacrini Ayres FerrazCentro de Matemática, Computação e Cognição, Universidade Federal do ABC, São Bernardo do Campo, SP, Brazil.
Giselle CerchiaroCentro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, SP, Brazil.
Christian SchmeltzerInstitute of Physics, Humboldt University at Berlin, Berlin, Germany.
Sten RüdigerInstitute of Physics, Humboldt University at Berlin, Berlin, Germany.
Alexandre Hiroaki KiharaCentro de Matemática, Computação e Cognição, Universidade Federal do ABC, São Bernardo do Campo, SP, Brazil. alexandrekihara@gmail.com.ORCID http://orcid.org/0000-0002-4027-7261

Funding

Deutsche Forschungsgemeinschaft (German Research Foundation) 1740/2Fundação de Amparo à Pesquisa do Estado de São Paulo (São Paulo Research Foundation) 2015/50122-0Fundação de Amparo à Pesquisa do Estado de São Paulo (São Paulo Research Foundation) 2019/17892-8Fundação de Amparo à Pesquisa do Estado de São Paulo (São Paulo Research Foundation) 2020/11667-0Ministry of Science, Technology and Innovation | Conselho Nacional de Desenvolvimento Científico e Tecnológico (National Council for Scientific and Technological Development) 315372/2021-4Ministry of Science, Technology and Innovation | Conselho Nacional de Desenvolvimento Científico e Tecnológico (National Council for Scientific and Technological Development) 402616/2025-1
6 · The paper itself

Abstract

How diffusible neuromodulators control neural circuit assembly remains a key open question in neuroscience. While nitric oxide (NO) is known to regulate mature synaptic plasticity, its role during development, specifically whether it shapes circuits through activity-dependent or activity-independent pathways, has not been fully understood. Here, we combine ultrasensitive electron paramagnetic resonance (EPR) spectroscopy, 4096-channel high-density multielectrode array (HD-MEA) recordings, and advanced graph-theoretical analysis to study how NO contributes to retinal network formation during a critical period of synaptogenesis. In the rat retina, nNOS expression begins at postnatal day 10 in two distinct amacrine cell subtypes, coinciding with the first detectable NO production. Acute or selective nNOS inhibition preserved the spatiotemporal features of Stage III retinal waves but significantly changed network topology, increasing network degree and density. Molecular profiling showed that nNOS blockade lowered the expression of chemical (SYN, SYP) and electrical (Cx36, Cx45) synaptic genes, disrupted their laminar distribution in vivo, and increased neurite length in primary retinal cultures without altering branching complexity. By combining ultrasensitive NO detection, large-scale electrophysiology, and mathematical network analysis, our results identify NO as a key regulator of circuit refinement that operates largely independently of the spatiotemporal dynamics of retinal waves during development. These findings reveal a molecular mechanism by which diffusible modulators shape neural networks independently of patterned activity and offer a framework for understanding how altered NO signaling might contribute to neurodevelopmental disorders characterized by impaired synaptic organization.

Identifiers

PMID42362501
PMCPMC13572502

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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.