Cannabidiol is a behavioral modulator in BTBR mouse model of idiopathic autism.

Introduction: The prevalence of Autism Spectrum Disorder (ASD) has drastically risen over the last two decades and is currently estimated to affect 1 in 36 children in the U.S., according to the center for disease control (CDC). This heterogenous neurodevelopmental disorder is characterized by impaired social interactions, communication deficits, and repetitive behaviors plus restricted interest. Autistic individuals also commonly present with a myriad of comorbidities, such as attention deficit hyperactivity disorder, anxiety, and seizures. To date, a pharmacological intervention for the treatment of core autistic symptoms has not been identified. Cannabidiol (CBD), the major nonpsychoactive constituent of Cannabis sativa, is suggested to have multiple therapeutic applications, but its effect(s) on idiopathic autism is unknown. We hypothesized that CBD will effectively attenuate the autism-like behaviors and autism-associated comorbid behaviors in BTBR T+Itpr3tf/J (BTBR) mice, an established mouse model of idiopathic ASD. Methods: Male BTBR mice were injected intraperitoneally with either vehicle, 20 mg/kg CBD or 50 mg/kg CBD daily for two weeks beginning at postnatal day 21 ± 3. On the final treatment day, a battery of behavioral assays were used to evaluate the effects of CBD on the BTBR mice, as compared to age-matched, vehicle-treated C57BL/6 J mice. Results: High dose (50 mg/kg) CBD treatment attenuated the elevated repetitive self-grooming behavior and hyperlocomotion in BTBR mice. The social deficits exhibited by the control BTBR mice were rescued by the 20 mg/kg CBD treatment. Discussion: Our data indicate that different doses for CBD are needed for treating specific ASD-like behaviors. Together, our results suggest that CBD may be an effective drug to ameliorate repetitive/restricted behaviors, social deficits, and autism-associated hyperactivity.

Potential Cross Talk between Autism Risk Genes and Neurovascular Molecules: A Pilot Study on Impact of Blood Brain Barrier Integrity.

Autism Spectrum Disorder (ASD) is a common pediatric neurobiological disorder with up to 80% of genetic etiologies. Systems biology approaches may make it possible to test novel therapeutic strategies targeting molecular pathways to alleviate ASD symptoms. A clinical database of autism subjects was queried for individuals with a copy number variation (CNV) on microarray, Vineland, and Parent Concern Questionnaire scores. Pathway analyses of genes from pathogenic CNVs yielded 659 genes whose protein-protein interactions and mRNA expression mapped 121 genes with maximal antenatal expression in 12 brain regions. A Research Domain Criteria (RDoC)-derived neural circuits map revealed significant differences in anxiety, motor, and activities of daily living skills scores between altered CNV genes and normal microarrays subjects, involving Positive Valence (reward), Cognition (IQ), and Social Processes. Vascular signaling was identified as a biological process that may influence these neural circuits. Neuroinflammation, microglial activation, iNOS and 3-nitrotyrosine increase in the brain of Semaphorin 3F- Neuropilin 2 (Sema 3F-NRP2) KO, an ASD mouse model, agree with previous reports in the brain of ASD individuals. Signs of platelet deposition, activation, release of serotonin, and albumin leakage in ASD-relevant brain regions suggest possible blood brain barrier (BBB) deficits. Disruption of neurovascular signaling and BBB with neuroinflammation may mediate causative pathophysiology in some ASD subgroups. Although preliminary, these data demonstrate the potential for developing novel therapeutic strategies based on clinically derived data, genomics, cognitive neuroscience, and basic neuroscience methods.

Potential crosstalk between sonic hedgehog-WNT signaling and neurovascular molecules: Implications for blood-brain barrier integrity in autism spectrum disorder.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disease originating from combined genetic and environmental factors. Post-mortem human studies and some animal ASD models have shown brain neuroinflammation, oxidative stress, and changes in blood-brain barrier (BBB) integrity. However, the signaling pathways leading to these inflammatory findings and vascular alterations are currently unclear. The BBB plays a critical role in controlling brain homeostasis and immune response. Its dysfunction can result from developmental genetic abnormalities or neuroinflammatory processes. In this review, we explore the role of the Sonic Hedgehog/Wingless-related integration site (Shh/Wnt) pathways in neurodevelopment, neuroinflammation, and BBB development. The balance between Wnt-ß-catenin and Shh pathways controls angiogenesis, barriergenesis, neurodevelopment, central nervous system (CNS) morphogenesis, and neuronal guidance. These interactions are critical to maintain BBB function in the mature CNS to prevent the influx of pathogens and inflammatory cells. Genetic mutations of key components of these pathways have been identified in ASD patients and animal models, which correlate with the severity of ASD symptoms. Disruption of the Shh/Wnt crosstalk may therefore compromise BBB development and function. In turn, impaired Shh signaling and glial activation may cause neuroinflammation that could disrupt the BBB. Elucidating how ASD-related mutations of Shh/Wnt signaling could cause BBB leaks and neuroinflammation will contribute to our understanding of the role of their interactions in ASD pathophysiology. These observations may provide novel targeted therapeutic strategies to prevent or alleviate ASD symptoms while preserving normal developmental processes. Cover Image for this issue: https://doi.org/10.1111/jnc.15081.

A robust DWT-CNN-based CAD system for early diagnosis of autism using task-based fMRI.

PURPOSE: Task-based fMRI (TfMRI) is a diagnostic imaging modality for observing the effects of a disease or other condition on the functional activity of the brain. Autism spectrum disorder (ASD) is a pervasive developmental disorder associated with impairments in social and linguistic abilities. Machine learning algorithms have been widely utilized for brain imaging aiming for objective ASD diagnostics. Recently, deep learning methods have been gaining more attention for fMRI classification. The goal of this paper is to develop a convolutional neural network (CNN)-based framework to help in global diagnosis of ASD using TfMRI data that are collected from a response to speech experiment. METHODS: To achieve this goal, the proposed framework adopts a novel imaging marker integrating both spatial and temporal information that are related to the functional activity of the brain. The developed pipeline consists of three main components. In the first step, the collected TfMRI data are preprocessed and parcellated using the Harvard-Oxford probabilistic atlas included with the fMRIB Software Library (FSL). Second, a group analysis using FSL is performed between ASD and typically developing (TD) children to identify significantly activated brain areas in response to the speech task. In order to reduce brain spatial dimensionality, a K-means clustering technique is performed on such significant brain areas. Informative blood oxygen level-dependent (BOLD) signals are extracted from each cluster. A compression step for each extracted BOLD signal using discrete wavelet transform (DWT) has been proposed. The adopted wavelets are similar to the expected hemodynamic response which enables DWT to compress the BOLD signal while highlighting its activation information. Finally, a deep learning 2D CNN network is used to classify the patients as ASD or TD based on extracted features from the previous step. RESULTS: Preliminary results on 100 TfMRI dataset (50 ASD, 50 TD) obtain 80% correct global classification using tenfold cross validation (with sensitivity = 84%, specificity = 76%). CONCLUSION: The experimental results show the high accuracy of the proposed framework and hold promise for the presented framework as a helpful adjunct to currently used ASD diagnostic tools.

Dynamic glial response and crosstalk in demyelination-remyelination and neurodegeneration processes.

Multiple sclerosis is an autoimmune disease in which the immune system attacks the myelin sheath in the central nervous system. It is characterized by blood-brain barrier dysfunction throughout the course of multiple sclerosis, followed by the entry of immune cells and activation of local microglia and astrocytes. Glial cells (microglia, astrocytes, and oligodendrocyte lineage cells) are known as the important mediators of neuroinflammation, all of which play major roles in the pathogenesis of multiple sclerosis. Network communications between glial cells affect the activities of oligodendrocyte lineage cells and influence the demyelination-remyelination process. A finely balanced glial response may create a favorable lesion environment for efficient remyelination and neuroregeneration. This review focuses on glial response and neurodegeneration based on the findings from multiple sclerosis and major rodent demyelination models. In particular, glial interaction and molecular crosstalk are discussed to provide insights into the potential cell- and molecule-specific therapeutic targets to improve remyelination and neuroregeneration.

Disruption of essential metal homeostasis in the brain by cadmium and high-fat diet.

Analyses of human cohort data support the roles of cadmium and obesity in the development of several neurocognitive disorders. To explore the effects of cadmium exposure in the brain, mice were subjected to whole life oral cadmium exposure. There were significant increases in cadmium levels with female animals accumulating more metal than males (p < 0.001). Both genders fed a high fat diet showed significant increases in cadmium levels compared to low fat diet fed mice (p < 0.001). Cadmium and high fat diet significantly affected the levels of several essential metals, including magnesium, potassium, chromium, iron, cobalt, copper, zinc and selenium. Additionally, these treatments resulted in increased superoxide levels within the cortex, amygdala and hippocampus. These findings support a model where cadmium and high fat diet affect the levels of redox-active, essential metal homeostasis. This phenomenon may contribute to the underlying mechanism(s) responsible for the development of neurocognitive disorders.

Neuroprotective Effects of Adenosine A1 Receptor Signaling on Cognitive Impairment Induced by Chronic Intermittent Hypoxia in Mice.

Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a breathing disorder associated with cognitive impairment. However, the mechanisms leading to cognitive deficits in OSAHS remain uncertain. In this study, a mouse model of chronic intermittent hypoxia (CIH) exposures were applied for simulating the deoxygenation-reoxygenation events occurring in OSAHS. The conventional adenosine A1 receptor gene (A1R) knockout mice and the A1R agonist CCPA- or antagonist DPCPX-administrated mice were utilized to determine the precise function of A1R signaling in the process of OSAHS-relevant cognitive impairment. We demonstrated that CIH induced morphological changes and apoptosis in hippocampal neurons. Further, CIH blunted hippocampal long-term potentiation (LTP) and resulted in learning/memory impairment. Disruption of adenosine A1R exacerbated morphological, cellular, and functional damage induced by CIH. In contrast, activation of adenosine A1R signaling reduced morphological changes and apoptosis of hippocampal neurons, promoted LTP, and enhanced learning and memory. A1Rs may up-regulate protein kinase C (PKC) and its subtype PKC-ζ through the activation of Gα(i) improve spatial learning and memory disorder induced by CIH in mice. Taken together, A1R signaling plays a neuroprotective role in CIH-induced cognitive dysfunction and pathological changes in the hippocampus.

Platelet-Activating Factor Deteriorates Lysophosphatidylcholine-Induced Demyelination Via Its Receptor-Dependent and -Independent Effects.

Accumulating evidence suggests that platelet-activating factor (PAF) increases the inflammatory response in demyelinating diseases such as multiple sclerosis. However, PAF receptor (PAFR) antagonists do not show therapeutic efficacy for MS, and its underlying mechanisms remain poorly understood. In the present study, we investigated the effects of PAF on an ex vivo demyelination cerebellar model following lysophosphatidylcholine (LPC, 0.5 mg/mL) application using wild-type and PAFR conventional knockout (PAFR-KO) mice. Demyelination was induced in cerebellar slices that were cultured with LPC for 18 h. Exogenous PAF (1 µM) acting on cerebellar slices alone did not cause demyelination but increased the severity of LPC-induced demyelination in both wild-type and PAFR-KO mice. LPC inhibited the expression of PAF-AH, MBP, TNF-α, and TGF-ß1 but facilitated the expression of IL-1ß and IL-6 in wild-type preparations. Of note, exogenous PAF stimulated microglial activation in both wild-type and PAFR-KO mice. The subsequent inflammatory cytokines TNFα, IL-1ß, and IL-6 as well as the anti-inflammatory cytokine TGF-ß1 demonstrated a diverse transcriptional profile with or without LPC treatment. PAF promoted TNF-α expression and suppressed TGF-ß1 expression indiscriminately in wild-type and knockout slices; however, transcription of IL-1ß and IL-6 was not significantly affected in both slices. The syntheses of IL-1ß and IL-6 were significantly increased in LPC-induced demyelination preparations without PAF but showed a redundancy in PAF-treated wild-type and knockout slices. These data suggest that PAF can play a detrimental role in LPC-induced demyelination probably due to a redundant response of PAFR-dependent and PAFR-independent effects on inflammatory cytokines.

Publisher Correction: Cadmium and High-Fat Diet Disrupt Renal, Cardiac and Hepatic Essential Metals.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Dynamic response of microglia/macrophage polarization following demyelination in mice.

BACKGROUND: The glial response in multiple sclerosis (MS), especially for recruitment and differentiation of oligodendrocyte progenitor cells (OPCs), predicts the success of remyelination of MS plaques and return of function. As a central player in neuroinflammation, activation and polarization of microglia/macrophages (M/M) that modulate the inflammatory niche and cytokine components in demyelination lesions may impact the OPC response and progression of demyelination and remyelination. However, the dynamic behaviors of M/M and OPCs during demyelination and spontaneous remyelination are poorly understood, and the complex role of neuroinflammation in the demyelination-remyelination process is not well known. In this study, we utilized two focal demyelination models with different dynamic patterns of M/M to investigate the correlation between M/M polarization and the demyelination-remyelination process. METHODS: The temporal and spatial features of M/M activation/polarization and OPC response in two focal demyelination models induced by lysolecithin (LPC) and lipopolysaccharide (LPS) were examined in mice. Detailed discrimination of morphology, sensorimotor function, diffusion tensor imaging (DTI), inflammation-relevant cytokines, and glial responses between these two models were analyzed at different phases. RESULTS: The results show that LPC and LPS induced distinctive temporal and spatial lesion patterns. LPS produced diffuse demyelination lesions, with a delayed peak of demyelination and functional decline compared to LPC. Oligodendrocytes, astrocytes, and M/M were scattered throughout the LPS-induced demyelination lesions but were distributed in a layer-like pattern throughout the LPC-induced lesion. The specific M/M polarization was tightly correlated to the lesion pattern associated with balance beam function. CONCLUSIONS: This study elaborated on the spatial and temporal features of neuroinflammation mediators and glial response during the demyelination-remyelination processes in two focal demyelination models. Specific M/M polarization is highly correlated to the demyelination-remyelination process probably via modulations of the inflammatory niche, cytokine components, and OPC response. These findings not only provide a basis for understanding the complex and dynamic glial phenotypes and behaviors but also reveal potential targets to promote/inhibit certain M/M phenotypes at the appropriate time for efficient remyelination.

Cadmium and High-Fat Diet Disrupt Renal, Cardiac and Hepatic Essential Metals.

Exposure to the environmental toxicant cadmium (Cd) contributes to the development of obesity-associated diseases. Obesity is a risk factor for a spectrum of unhealthy conditions including systemic metabolic dyshomeostasis. In the present study, the effects of whole-life exposure to environmentally-relevant concentrations of Cd on systemic essential metal distribution in adult mice fed a high-fat diet (HFD) were examined. For these studies, male and female mice were exposed to Cd-containing drinking water for >2 weeks before breeding. Pregnant mice and dams with offspring were exposed to Cd-containing drinking water. After weaning, offspring were continuously exposed to the same Cd concentration as their parents, and divided into HFD and normal (low) fat diet (LFD) groups. At 10 and 24 weeks, mice were sacrificed and blood, liver, kidney and heart harvested for metal analyses. There were significant concentration dependent increases in Cd levels in offspring with kidney > liver > heart. Sex significantly affected Cd levels in kidney and liver, with female animals accumulating more metal than males. Mice fed the HFD showed > 2-fold increase in Cd levels in the three organs compared to similarly treated LFD mice. Cadmium significantly affected essential metals levels in blood, kidney and liver. Additionally, HFD affected essential metal levels in these three organs. These findings suggest that Cd interacts with HFD to affect essential metal homeostasis, a phenomenon that may contribute to the underlying mechanism responsible for the development of obesity-associated pathologies.

A randomized controlled trial of levodopa in patients with Angelman syndrome.

Treatment for Angelman syndrome (AS) is currently limited to symptomatic interventions. A mouse model of AS has reduced calcium/calmodulin-dependent kinase II activity due to excessive phosphorylation of specific threonine residues, leading to diminished long-term potentiation. In a rat model of Parkinson disease, levodopa reduced phosphorylation of various proteins, including calcium/calmodulin-dependent kinase II. Further studies demonstrated that AS mice treated with levodopa performed better on rotarod testing than untreated AS mice. We conducted a multi-center double-blind randomized placebo-controlled 1-year trial of levodopa / carbidopa with either 10 or 15 mg/kg/day of levodopa in children with AS. The outcome of this intervention was assessed using either the Bayley Scales of Infant Development or the Mullen Scales of Early Learning, as well as the Vineland Adaptive Behavior Scales, and the Aberrant Behavior Checklist. Of the 78 participants enrolled, 67 participants received study medication (33 on levodopa, 34 on placebo), and 55 participants (29 on levodopa, 26 on placebo) completed the 1-year study. There were no clinically or statistically significant changes in any of the outcome measures over a 1-year period comparing the levodopa and placebo groups. The number of adverse events reported, including the more serious adverse events, was similar in both groups, but none were related to treatment with levodopa. Our data demonstrate that levodopa is well-tolerated by children with AS. However, in the doses used in this study, it failed to improve their neurodevelopment or behavioral outcome.

Alzheimer's disease diagnostics by a 3D deeply supervised adaptable convolutional network.

Early diagnosis is playing an important role in preventing progress of the Alzheimer's disease (AD). This paper proposes to improve the prediction of AD with a deep 3D Convolutional Neural Network (3D-CNN), which can show generic features capturing AD biomarkers extracted from brain images, adapt to different domain datasets, and accurately classify subjects with improved fine-tuning method. The 3D-CNN is built upon a convolutional autoencoder, which is pre-trained to capture anatomical shape variations in structural brain MRI scans for source domain. Fully connected upper layers of the 3D-CNN are then fine-tuned for each task-specific AD classification in target domain. In this paper, deep supervision algorithm is used to improve the performance of already proposed 3D Adaptive CNN. Experiments on the ADNI MRI dataset without skull-stripping preprocessing have shown that the proposed 3D Deeply Supervised Adaptable CNN outperforms several proposed approaches, including 3D-CNN model, other CNN-based methods and conventional classifiers by accuracy and robustness. Abilities of the proposed network to generalize the features learnt and adapt to other domains have been validated on the CADDementia dataset.

Medical imaging diagnosis of early Alzheimer's disease.

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases that influences the central nervous system, often leading to dire consequences for quality of life. The disease goes through some stages mainly divided into early, moderate, and severe. Among them, the early stage is the most important as medical intervention has the potential to alter the natural progression of the condition. In practice, the early diagnosis is a challenge since the neurodegenerative changes can precede the onset of clinical symptoms by 10-15 years. This factor along with other known and unknown ones, hinder the ability for the early diagnosis and treatment of AD. Numerous research efforts have been proposed to address the complex characteristics of AD exploiting various tests including brain imaging that is massively utilized due to its powerful features. This paper aims to highlight our present knowledge on the clinical and computer-based attempts at early diagnosis of AD. We concluded that the door is still open for further research especially with the rapid advances in scanning and computer-based technologies.

A fast stochastic framework for automatic MR brain images segmentation.

This paper introduces a new framework for the segmentation of different brain structures (white matter, gray matter, and cerebrospinal fluid) from 3D MR brain images at different life stages. The proposed segmentation framework is based on a shape prior built using a subset of co-aligned training images that is adapted during the segmentation process based on first- and second-order visual appearance characteristics of MR images. These characteristics are described using voxel-wise image intensities and their spatial interaction features. To more accurately model the empirical grey level distribution of the brain signals, we use a linear combination of discrete Gaussians (LCDG) model having positive and negative components. To accurately account for the large inhomogeneity in infant MRIs, a higher-order Markov-Gibbs Random Field (MGRF) spatial interaction model that integrates third- and fourth- order families with a traditional second-order model is proposed. The proposed approach was tested and evaluated on 102 3D MR brain scans using three metrics: the Dice coefficient, the 95-percentile modified Hausdorff distance, and the absolute brain volume difference. Experimental results show better segmentation of MR brain images compared to current open source segmentation tools.

A Novel Early Diagnosis System for Mild Cognitive Impairment Based on Local Region Analysis: A Pilot Study.

Alzheimer's disease (AD) is an irreversible neurodegenerative disorder that accounts for 60-70% of cases of dementia in the elderly. An early diagnosis of AD is usually hampered for many reasons including the variable clinical and pathological features exhibited among affected individuals. This paper presents a computer-aided diagnosis (CAD) system with the primary goal of improving the accuracy, specificity, and sensitivity of diagnosis. In this system, PiB-PET scans, which were obtained from the ADNI database, underwent five essential stages. First, the scans were standardized and de-noised. Second, an Automated Anatomical Labeling (AAL) atlas was utilized to partition the brain into 116 regions or labels that served for local (region-based) diagnosis. Third, scale-invariant Laplacian of Gaussian (LoG) was used, per brain label, to detect the discriminant features. Fourth, the regions' features were analyzed using a general linear model in the form of a two-sample t-test. Fifth, the support vector machines (SVM) and their probabilistic variant (pSVM) were constructed to provide local, followed by global diagnosis. The system was evaluated on scans of normal control (NC) vs. mild cognitive impairment (MCI) (19 NC and 65 MCI scans). The proposed system showed superior accuracy, specificity, and sensitivity as compared to other related work.

A novel role for PTEN in the inhibition of neurite outgrowth by myelin-associated glycoprotein in cortical neurons.

Axonal regeneration in the central nervous system is prevented, in part, by inhibitory proteins expressed by myelin, including myelin-associated glycoprotein (MAG). Although injury to the corticospinal tract can result in permanent disability, little is known regarding the mechanisms by which MAG affects cortical neurons. Here, we demonstrate that cortical neurons plated on MAG expressing CHO cells, exhibit a striking reduction in process outgrowth. Interestingly, none of the receptors previously implicated in MAG signaling, including the p75 neurotrophin receptor or gangliosides, contributed significantly to MAG-mediated inhibition. However, blocking the small GTPase Rho or its downstream effector kinase, ROCK, partially reversed the effects of MAG on the neurons. In addition, we identified the lipid phosphatase PTEN as a mediator of MAG's inhibitory effects on neurite outgrowth. Knockdown or gene deletion of PTEN or overexpression of activated AKT in cortical neurons resulted in significant, although partial, rescue of neurite outgrowth on MAG-CHO cells. Moreover, MAG decreased the levels of phospho-Akt, suggesting that it activates PTEN in the neurons. Taken together, these results suggest a novel pathway activated by MAG in cortical neurons involving the PTEN/PI3K/AKT axis.

Decreased number of interneurons and increased seizures in neuropilin 2 deficient mice: implications for autism and epilepsy.

PURPOSE: Clinically, perturbations in the semaphorin signaling system have been associated with autism and epilepsy. The semaphorins have been implicated in guidance, migration, differentiation, and synaptic plasticity of neurons. The semaphorin 3F (Sema3F) ligand and its receptor, neuropilin 2 (NPN2) are highly expressed within limbic areas. NPN2 signaling may intimately direct the apposition of presynaptic and postsynaptic locations, facilitating the development and maturity of hippocampal synaptic function. To further understand the role of NPN2 signaling in central nevous system (CNS) plasticity, structural and functional alterations were assessed in NPN2 deficient mice. METHODS: In NPN2 deficient mice, we measured seizure susceptibility after kainic acid or pentylenetetrazol, neuronal excitability and synaptic throughput in slice preparations, principal and interneuron cell counts with immunocytochemical protocols, synaptosomal protein levels with immunoblots, and dendritic morphology with Golgi-staining. RESULTS: NPN2 deficient mice had shorter seizure latencies, increased vulnerability to seizure-related death, were more likely to develop spontaneous recurrent seizure activity after chemical challenge, and had an increased slope on input/output curves. Principal cell counts were unchanged, but GABA, parvalbumin, and neuropeptide Y interneuron cell counts were significantly reduced. Synaptosomal NPN2 protein levels and total number of GABAergic synapses were decreased in a gene dose-dependent fashion. CA1 pyramidal cells showed reduced dendritic length and complexity, as well as an increased number of dendritic spines. DISCUSSION: These data suggest the novel hypothesis that the Sema 3F signaling system's role in appropriate placement of subsets of hippocampal interneurons has critical downstream consequences for hippocampal function, resulting in a more seizure susceptible phenotype.