ArticleThe Journal of biological chemistry2020
The protein tyrosine phosphatase RPTPζ/phosphacan is critical for perineuronal net structure.
Article in The Journal of biological chemistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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.
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.
Who cites it
28 citing papers in PubMed, 33 citations in OpenAlex.
- Keratan Sulfate: An Electroconductive Glycosaminoglycan at the Interface of Sensory Perception and Neural Signaling.Journal of neuroscience research · 2026Review
- The Role of Meprins on the Brain Extracellular Matrix and Perineuronal Nets.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Depletion of Neurocan in the Prefrontal Cortex Impairs Temporal Order Recognition, Cognitive Flexibility and Perisomatic GABAergic Innervation.Cellular and molecular neurobiology · 2026Article
- Article
- Chondroitin Sulfate Proteoglycans in CNS Development and Pathophysiology.Journal of neuroscience research · 2026Review
- Sustained diabetes remission induced by FGF1 involves a shift in transcriptionally distinct AgRP neuron subpopulations.Molecular metabolism · 2026Article
- Glucocorticoids Modulate Expression of Perineuronal Net Component Genes and Parvalbumin During Development of Mouse Cortical Neurons.Molecular neurobiology · 2025Article
- Targeting CA2 Perineuronal Nets Restores Recognition Memory and Theta Oscillations in Aged Mice.Aging cell · 2025Article
- Keratan Sulfate Is a Multifunctional Brain Glycosaminoglycan With Instructive Capabilities.Journal of neurochemistry · 2025Review
- Contactin-1 is a critical neuronal cell surface receptor for perineuronal net structure.The Journal of biological chemistry · 2025Article
- Enhanced fear extinction through infralimbic perineuronal net digestion: The modulatory role of adolescent alcohol exposure.Alcohol (Fayetteville, N.Y.) · 2025Article
- Review
- Vaccine-induced T cell receptor T cell therapy targeting a glioblastoma stemness antigen.Nature communications · 2025Article
- Perineuronal Nets: From Structure to Neurological Disorders.Current medicinal chemistry · 2025Review
- Pleiotrophin Overexpression Reduces Adolescent Ethanol Consumption and Modulates Ethanol-Induced Glial Responses and Changes in the Perineuronal Nets in the Mouse Hippocampus.CNS neuroscience & therapeutics · 2024Article
- Enhanced Fear Extinction Through Infralimbic Perineuronal Net Digestion: The Modulatory Role of Adolescent Alcohol Exposure.bioRxiv : the preprint server for biology · 2024Article
- From molecules to behavior: Implications for perineuronal net remodeling in learning and memory.Journal of neurochemistry · 2024Review
- The Role of Tenascin-C on the Structural Plasticity of Perineuronal Nets and Synaptic Expression in the Hippocampus of Male Mice.Biomolecules · 2024Article
- Perineuronal Net Microscopy: From Brain Pathology to Artificial Intelligence.International journal of molecular sciences · 2024Review
- Keratan sulfate, an electrosensory neurosentient bioresponsive cell instructive glycosaminoglycan.Glycobiology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
Perineuronal nets (PNNs) are conspicuous neuron-specific substructures within the extracellular matrix of the central nervous system that have generated an explosion of interest over the last decade. These reticulated structures appear to surround synapses on the cell bodies of a subset of the neurons in the central nervous system and play key roles in both developmental and adult-brain plasticity. Despite the interest in these structures and compelling demonstrations of their importance in regulating plasticity, their precise functional mechanisms remain elusive. The limited mechanistic understanding of PNNs is primarily because of an incomplete knowledge of their molecular composition and structure and a failure to identify PNN-specific targets. Thus, it has been challenging to precisely manipulate PNNs to rigorously investigate their function. Here, using mouse models and neuronal cultures, we demonstrate a role of receptor protein tyrosine phosphatase zeta (RPTPζ) in PNN structure. We found that in the absence of RPTPζ, the reticular structure of PNNs is lost and phenocopies the PNN structural abnormalities observed in tenascin-R knockout brains. Furthermore, we biochemically analyzed the contribution of RPTPζ to PNN formation and structure, which enabled us to generate a more detailed model for PNNs. We provide evidence for two distinct kinds of interactions of PNN components with the neuronal surface, one dependent on RPTPζ and the other requiring the glycosaminoglycan hyaluronan. We propose that these findings offer important insight into PNN structure and lay important groundwork for future strategies to specifically disrupt PNNs to precisely dissect their function.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.