scholarly journals Hyperactive Behavior and Altered Brain Morphology in Adult Complement C3a Receptor Deficient Mice

2021 ◽  
Vol 12 ◽  
Author(s):  
Andrea Pozo-Rodrigálvarez ◽  
Roosa Ollaranta ◽  
Jenny Skoog ◽  
Milos Pekny ◽  
Marcela Pekna
Keyword(s):  
Neural Plasticity ◽  
Cell Activation ◽  
Short Term Memory ◽  
Neural Progenitor Cell ◽  
Autism Spectrum ◽  
Brain Morphology ◽  
Immune Functions ◽  
Hyperactive Behavior ◽  
Progenitor Cell Proliferation ◽  
Neurodevelopmental Abnormalities

The C3a receptor (C3aR) is a seven trans-membrane domain G-protein coupled receptor with a range of immune modulatory functions. C3aR is activated by the third complement component (C3) activation derived peptide C3a and a neuropeptide TLQP-21. In the central nervous system (CNS), C3aR is expressed by neural progenitors, neurons as well as glial cells. The non-immune functions of C3aR in the adult CNS include regulation of basal neurogenesis, injury-induced neural plasticity, and modulation of glial cell activation. In the developing brain, C3aR and C3 have been shown to play a role in neural progenitor cell proliferation and neuronal migration with potential implications for autism spectrum disorder, and adult C3aR deficient (C3aR−/−) mice were reported to exhibit subtle deficit in recall memory. Here, we subjected 3 months old male C3aR−/− mice to a battery of behavioral tests and examined their brain morphology. We found that the C3aR−/− mice exhibit a short-term memory deficit and increased locomotor activity, but do not show any signs of autistic behavior as assessed by self-grooming behavior. We also found regional differences between the C3aR−/− and wild-type (WT) mice in the morphology of motor and somatosensory cortex, as well as amygdala and hippocampus. In summary, constitutive absence of C3aR signaling in mice leads to neurodevelopmental abnormalities that persist into adulthood and are associated with locomotive hyperactivity and altered cognitive functions.

scholarly journals Zbtb16 regulates social cognitive behaviors and neocortical development

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Noriyoshi Usui ◽  
Stefano Berto ◽  
Ami Konishi ◽  
Makoto Kondo ◽  
Genevieve Konopka ◽  
...  
Keyword(s):  
Social Cognitive ◽  
Neural Progenitor Cell ◽  
Autism Spectrum ◽  
Repetitive Behaviors ◽  
Social Impairment ◽  
Developmental Defects ◽  
Cognitive Behaviors ◽  
Btb Domain ◽  
Neocortical Development ◽  
Progenitor Cell Proliferation

AbstractZinc finger and BTB domain containing 16 (ZBTB16) play the roles in the neural progenitor cell proliferation and neuronal differentiation during development, however, how the function of ZBTB16 is involved in brain function and behaviors unknown. Here we show the deletion of Zbtb16 in mice leads to social impairment, repetitive behaviors, risk-taking behaviors, and cognitive impairment. To elucidate the mechanism underlying the behavioral phenotypes, we conducted histological analyses and observed impairments in thinning of neocortical layer 6 (L6) and a reduction of TBR1+ neurons in Zbtb16 KO mice. Furthermore, we found increased dendritic spines and microglia, as well as developmental defects in oligodendrocytes and neocortical myelination in the prefrontal cortex (PFC) of Zbtb16 KO mice. Using genomics approaches, we identified the Zbtb16 transcriptome that includes genes involved in neocortical maturation such as neurogenesis and myelination, and both autism spectrum disorder (ASD) and schizophrenia (SCZ) pathobiology. Co-expression networks further identified Zbtb16-correlated modules that are unique to ASD or SCZ, respectively. Our study provides insight into the novel roles of ZBTB16 in behaviors and neocortical development related to the disorders.

scholarly journals Application of Skeleton Data and Long Short-Term Memory in Action Recognition of Children with Autism Spectrum Disorder

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 411
Author(s):  
Yunkai Zhang ◽  
Yinghong Tian ◽  
Pingyi Wu ◽  
Dongfan Chen
Keyword(s):  
Autism Spectrum Disorder ◽  
Action Recognition ◽  
Short Term Memory ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Short Term ◽  
Term Memory ◽  
Clinical Observations ◽  
The Neural Network ◽  
Long Short Term Memory

The recognition of stereotyped action is one of the core diagnostic criteria of Autism Spectrum Disorder (ASD). However, it mainly relies on parent interviews and clinical observations, which lead to a long diagnosis cycle and prevents the ASD children from timely treatment. To speed up the recognition process of stereotyped actions, a method based on skeleton data and Long Short-Term Memory (LSTM) is proposed in this paper. In the first stage of our method, the OpenPose algorithm is used to obtain the initial skeleton data from the video of ASD children. Furthermore, four denoising methods are proposed to eliminate the noise of the initial skeleton data. In the second stage, we track multiple ASD children in the same scene by matching distance between current skeletons and previous skeletons. In the last stage, the neural network based on LSTM is proposed to classify the ASD children’s actions. The performed experiments show that our proposed method is effective for ASD children’s action recognition. Compared to the previous traditional schemes, our scheme has higher accuracy and is almost non-invasive for ASD children.

scholarly journals Spatio-temporal feature learning with reservoir computing for T-cell segmentation in live-cell $$\hbox {Ca}^{2+}$$ fluorescence microscopy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fatemeh Hadaeghi ◽  
Björn-Philipp Diercks ◽  
Daniel Schetelig ◽  
Fabrizio Damicelli ◽  
Insa M. A. Wolf ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
T Cell Activation ◽  
Cell Activation ◽  
Short Term Memory ◽  
Live Cell ◽  
Cell Segmentation ◽  
Reservoir Computing ◽  
Imaging Data ◽  
Temporal Segmentation

AbstractAdvances in high-resolution live-cell $$\hbox {Ca}^{2+}$$ Ca 2 + imaging enabled subcellular localization of early $$\hbox {Ca}^{2+}$$ Ca 2 + signaling events in T-cells and paved the way to investigate the interplay between receptors and potential target channels in $$\hbox {Ca}^{2+}$$ Ca 2 + release events. The huge amount of acquired data requires efficient, ideally automated image processing pipelines, with cell localization/segmentation as central tasks. Automated segmentation in live-cell cytosolic $$\hbox {Ca}^{2+}$$ Ca 2 + imaging data is, however, challenging due to temporal image intensity fluctuations, low signal-to-noise ratio, and photo-bleaching. Here, we propose a reservoir computing (RC) framework for efficient and temporally consistent segmentation. Experiments were conducted with Jurkat T-cells and anti-CD3 coated beads used for T-cell activation. We compared the RC performance with a standard U-Net and a convolutional long short-term memory (LSTM) model. The RC-based models (1) perform on par in terms of segmentation accuracy with the deep learning models for cell-only segmentation, but show improved temporal segmentation consistency compared to the U-Net; (2) outperform the U-Net for two-emission wavelengths image segmentation and differentiation of T-cells and beads; and (3) perform on par with the convolutional LSTM for single-emission wavelength T-cell/bead segmentation and differentiation. In turn, RC models contain only a fraction of the parameters of the baseline models and reduce the training time considerably.

scholarly journals Histone chaperone HIRA regulates neural progenitor cell proliferation and neurogenesis via β-catenin

2017 ◽  
Vol 216 (7) ◽  
pp. 1975-1992 ◽  
Author(s):  
Yanxin Li ◽  
Jianwei Jiao
Keyword(s):  
Cell Cycle ◽  
Cell Proliferation ◽  
Progenitor Cell ◽  
Neural Progenitor Cells ◽  
Neural Progenitor Cell ◽  
Neural Progenitor ◽  
Histone Chaperone ◽  
Epigenetic Mechanism ◽  
Progenitor Cell Proliferation ◽  
Early Neurogenesis

Histone cell cycle regulator (HIRA) is a histone chaperone and has been identified as an epigenetic regulator. Subsequent studies have provided evidence that HIRA plays key roles in embryonic development, but its function during early neurogenesis remains unknown. Here, we demonstrate that HIRA is enriched in neural progenitor cells, and HIRA knockdown reduces neural progenitor cell proliferation, increases terminal mitosis and cell cycle exit, and ultimately results in premature neuronal differentiation. Additionally, we demonstrate that HIRA enhances β-catenin expression by recruiting H3K4 trimethyltransferase Setd1A, which increases H3K4me3 levels and heightens the promoter activity of β-catenin. Significantly, overexpression of HIRA, HIRA N-terminal domain, or β-catenin can override neurogenesis abnormities caused by HIRA defects. Collectively, these data implicate that HIRA, cooperating with Setd1A, modulates β-catenin expression and then regulates neurogenesis. This finding represents a novel epigenetic mechanism underlying the histone code and has profound and lasting implications for diseases and neurobiology.

Region-Wise Brain Response Classification of ASD Children Using EEG and BiLSTM RNN

2021 ◽  
pp. 155005942110549
Author(s):  
Thanga Aarthy Manoharan ◽  
Menaka Radhakrishnan
Keyword(s):  
Classification Accuracy ◽  
Short Term Memory ◽  
Neurodevelopmental Disorder ◽  
Autism Spectrum ◽  
Neural Dynamics ◽  
Sensory Modulation ◽  
Distance Metric ◽  
Brain Response ◽  
Fixed Amount ◽  
Quantification Analysis

Abstract Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairment in sensory modulation. These sensory modulation deficits would ultimately lead them to difficulties in adaptive behavior and intellectual functioning. The purpose of this study was to observe changes in the nervous system with responses to auditory/visual and only audio stimuli in children with autism and typically developing (TD) through electroencephalography (EEG). In this study, 20 children with ASD and 20 children with TD were considered to investigate the difference in the neural dynamics. The neural dynamics could be understood by non-linear analysis of the EEG signal. In this research to reveal the underlying nonlinear EEG dynamics, recurrence quantification analysis (RQA) is applied. RQA measures were analyzed using various parameter changes in RQA computations. In this research, the cosine distance metric was considered due to its capability of information retrieval and the other distance metrics parameters are compared for identifying the best biomarker. Each computational combination of the RQA measure and the responding channel was analyzed and discussed. To classify ASD and TD, the resulting features from RQA were fed to the designed BiLSTM (bi-long short-term memory) network. The classification accuracy was tested channel-wise for each combination. T3 and T5 channels with neighborhood selection as FAN (fixed amount of nearest neighbors) and distance metric as cosine is considered as the best-suited combination to discriminate between ASD and TD with the classification accuracy of 91.86%, respectively.

scholarly journals ToxCast chemical library screen identifies diethanolamine as an activator of Wnt signaling

2021 ◽  
Author(s):  
Justin M. Wolter ◽  
Jessica A. Jimenez ◽  
Jason L. Stein ◽  
Mark J. Zylka
Keyword(s):  
Wnt Signaling ◽  
Human Exposure ◽  
Neural Progenitor Cell ◽  
Autism Spectrum ◽  
Chemical Library ◽  
Gain Of Function ◽  
Agricultural Pesticides ◽  
Library Screen ◽  
Hormone Analogs ◽  
Mutant Construct

AbstractNumerous autism spectrum disorder (ASD) risk genes are associated with Wnt signaling, suggesting that brain development may be especially sensitive to genetic perturbation of this pathway. Additionally, valproic acid, which modulates Wnt signaling, increases risk for ASD when taken during pregnancy. We previously found that an autism-linked gain-of-function UBE3AT485A mutant construct hyperactivated canonical Wnt signaling, providing a genetic means to elevate Wnt signaling above baseline levels. To identify environmental use chemicals that enhance or suppress Wnt signaling, we screened the ToxCast Phase I and II libraries in cells expressing this autism linked UBE3AT485 gain-of-function mutant construct. Using structural comparisons, we identify classes of chemicals that stimulated Wnt signaling, including ethanolamines, as well as chemicals that inhibited Wnt signaling, such as agricultural pesticides, and synthetic hormone analogs. To prioritize chemicals for follow-up, we leveraged predicted human exposure data, and identified diethanolamine (DEA) as a chemical that both stimulates Wnt signaling in UBE3AT485A–transfected cells and has a high potential for prenatal exposure in humans. DEA also enhanced proliferation in two primary human neural progenitor cell lines. Overall, this study identifies chemicals with the potential for human exposure that influence Wnt signaling in human cells.

scholarly journals Integrative analysis identifies key molecular signatures underlying neurodevelopmental deficits in fragile X syndrome

2019 ◽  
Author(s):  
Kagistia Hana Utami ◽  
Niels H. Skotte ◽  
Ana R. Colaço ◽  
Nur Amirah Binte Mohammad Yusof ◽  
Bernice Sim ◽  
...  
Keyword(s):  
Fragile X Syndrome ◽  
Fragile X ◽  
Neurodevelopmental Disorder ◽  
Embryonic Stem ◽  
Neural Progenitor Cell ◽  
Integrative Analysis ◽  
Network Activity ◽  
Neural Cells ◽  
Molecular Signatures ◽  
Neurodevelopmental Abnormalities

AbstractFragile X syndrome (FXS) is an incurable neurodevelopmental disorder with no effective treatment. FXS is caused by epigenetic silencing ofFMR1and loss of FMRP expression. To investigate the consequences of FMRP deficiency in the context of human physiology, we established isogenicFMR1knockout (FMR1KO) human embryonic stem cells (hESCs). Integrative analysis of the transcriptomic and proteomic profiles of hESC-derived FMRP-deficient neurons revealed several dysregulated pathways important for brain development including processes related to axon development, neurotransmission, and the cell cycle. We functionally validated alterations in a number of these pathways, showing abnormal neural rosette formation and increased neural progenitor cell proliferation inFMR1KO cells. We further demonstrated neurite outgrowth and branching deficits along with impaired electrophysiological network activity in FMRP-deficient neurons. Using isogenicFMR1KO hESC-derived neurons, we reveal key molecular signatures and neurodevelopmental abnormalities arising from loss of FMRP. We anticipate that theFMR1KO hESCs and the neuronal transcriptome and proteome datasets will provide a platform to delineate the pathophysiology of FXS in human neural cells.

scholarly journals Consecrate Recurrent Neural Network Classifier for Autism Classification

2019 ◽  
Vol 9 (1) ◽  
pp. 2033-2041
Keyword(s):  
Neural Network ◽  
Autism Spectrum Disorder ◽  
Recurrent Neural Network ◽  
Short Term Memory ◽  
Sequence Data ◽  
Large Data ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Neural Network Classifier ◽  
Gene Sequences

Most recent discoveries in Autism Spectrum Disorder (ASD) detection and classification studies reveal that there is a substantial relationship between Autism disorders and gene sequences. This work is indented to classify the autism spectrum disorder groups and sub-groups based on the gene sequences. The gene sequences are large data and perplexed for handling with conventional data mining or classification procedures. The Consecrate Recurrent Neural Network Classifier for Autism Classification (CRNNC-AC) work is introduced in this work to classify autism disorders using gene sequence data. A dedicated Elman [1] type Recurrent Neural Network (RNN) is introduced along with a legacy Long Short-Term Memory (LSTM) [2] in this classifier. The LSTM model is contrived to achieve memory optimization to eliminate memory overflows without affecting the classification accuracy. The classification quality metrics [3] such as Accuracy, Sensitivity, Specificity and F1-Score are concerned for optimization. The processing time of the proposed method is also measured to evaluate the pertinency.

scholarly journals A Temporal Activity of CA1 Neurons Underlying Short-Term Memory for Social Recognition Altered in PTEN Mouse Models of Autism Spectrum Disorder

2021 ◽  
Vol 15 ◽  
Author(s):  
An-Ping Chai ◽  
Xue-Feng Chen ◽  
Xiao-Shan Xu ◽  
Na Zhang ◽  
Meng Li ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Short Term Memory ◽  
Autism Spectrum ◽  
Social Recognition ◽  
Neuronal Firing ◽  
Spectrum Disorder ◽  
Long Term Memory ◽  
Short Term ◽  
Term Memory ◽  
Ca1 Neurons

Memory-guided social recognition identifies someone from previous encounters or experiences, but the mechanisms of social memory remain unclear. Here, we find that a short-term memory from experiencing a stranger mouse lasting under 30 min interval is essential for subsequent social recognition in mice, but that interval prolonged to hours by replacing the stranger mouse with a familiar littermate. Optogenetic silencing of dorsal CA1 neuronal activity during trials or inter-trial intervals disrupted short-term memory-guided social recognition, without affecting the ability of being sociable or long-term memory-guided social recognition. Postnatal knockdown or knockout of autism spectrum disorder (ASD)-associated phosphatase and tensin homolog (PTEN) gene in dorsal hippocampal CA1 similarly impaired neuronal firing rate in vitro and altered firing pattern during social recognition. These PTEN mice showed deficits in social recognition with stranger mouse rather than littermate and exhibited impairment in T-maze spontaneous alternation task for testing short-term spatial memory. Thus, we suggest that a temporal activity of dorsal CA1 neurons may underlie formation of short-term memory to be critical for organizing subsequent social recognition but that is possibly disrupted in ASD.

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