The lateral border of the neural plate is a major source of signals that induce primary neurons, neural crest cells and cranial placodes as well as provide patterning cues to mesodermal structures such as somites and heart. Whereas secreted BMP, FGF and Wnt proteins influence the differentiation of neural and non-neural ectoderm, we show here that members of the Dlx family of transcription factors position the border between neural and non-neural ectoderm and are required for the specification of adjacent cell fates. Inhibition of endogenous Dlx activity in Xenopus embryos with an EnR-Dlx homeodomain fusion protein expands the neural plate into non-neural ectoderm tissue whereas ectopic activation of Dlx target genes inhibits neural plate differentiation. Importantly, the stereotypic pattern of border cell fates in the adjacent ectoderm is re-established only under conditions where the expanded neural plate abuts Dlx-positive non-neural ectoderm. Experiments in which presumptive neural plate was grafted to ventral ectoderm reiterate induction of neural crest and placodal lineages and also demonstrate that Dlx activity is required in non-neural ectoderm for the production of signals needed for induction of these cells. We propose that Dlx proteins regulate intercellular signaling across the interface between neural and non-neural ectoderm that is critical for inducing and patterning adjacent cell fates.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4018238PMC
http://dx.doi.org/10.1242/dev.00212DOI Listing

Publication Analysis

Top Keywords

neural plate
24
non-neural ectoderm
24
cell fates
16
adjacent cell
12
neural non-neural
12
neural
11
dlx proteins
8
border neural
8
neural crest
8
ectoderm
8

Similar Publications

In robotic-assisted laminectomy decompression, stable and precise vertebral plate cutting remains challenging due to manual dependency and the absence of adaptive skill-learning mechanisms. This paper presents an advanced robotic vertebral plate-cutting system that leverages patient-specific anatomical variations and replicates the surgeon's cutting technique through a trajectory parameter prediction model. A spatial mapping relationship between artificial and patient vertebrae is first established, enabling the robot to mimic surgeon-defined trajectories with high accuracy.

View Article and Find Full Text PDF

Objective: The Polycomb Repressive Complex 2 (PRC2) regulates neural stem cell behaviour during development of the cerebral cortex, yet how the loss of PRC2 developmentally influences cell identity in the mature brain is poorly defined. Using a mouse model in which the PRC2 gene Embryonic ectoderm development (Eed) was conditionally deleted from the developing mouse dorsal telencephalon, we performed single nuclei RNA sequencing (snRNA-seq) on the cortical plate of an adult heterozygote Eed knockout mouse and an adult homozygote Eed knockout mouse compared to a littermate control. This work was part of a larger effort to understand consequences of mutations to PRC2 within the mature brain.

View Article and Find Full Text PDF

Auditory rhythm encoding during the last trimester of human gestation: From tracking the basic beat to tracking hierarchical nested temporal structures.

J Neurosci

December 2024

Inserm UMR1105, Groupe de Recherches sur l'Analyse Multimodale de la Fonction Cérébrale, CURS, Avenue Laennec, 80036 Amiens Cedex, France

Rhythm perception and synchronization to periodicity hold fundamental neurodevelopmental importance for language acquisition, musical behavior, and social communication. Rhythm is omnipresent in the fetal auditory world and newborns demonstrate sensitivity to auditory rhythmic cues. During the last trimester of gestation, the brain begins to respond to auditory stimulation and to code the auditory environment.

View Article and Find Full Text PDF

A new single-cell atlas of gene expression provides insights into the patterning of the neural plate of mice.

View Article and Find Full Text PDF

Automatic License Plate Recognition (ALPR) systems are essential for Intelligent Transport Systems (ITS), effective transportation management, security, law enforcement, etc. However, the performance of ALPR systems can be significantly affected by environmental conditions such as heavy rain, fog, and pollution. This paper introduces a weather-adaptive Convolutional Neural Network (CNN) framework that leverages the YOLOv10 model that is designed to enhance license plate detection in adverse weather conditions.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!