The Autism Phenome Project: Toward Identifying Clinically Meaningful Subgroups of Autism

One of the most universally accepted facts about autism is that it is heterogenous. Individuals diagnosed with autism spectrum disorder have a wide range of behavioral presentations and a variety of co-occurring medical and mental health conditions. The identification of more homogenous subgroups is likely to lead to a better understanding of etiologies as well as more targeted interventions and treatments. In 2006, we initiated the UC Davis MIND Institute Autism Phenome Project (APP) with the overarching goal of identifying clinically meaningful subtypes of autism. This ongoing longitudinal multidisciplinary study now includes over 400 children and involves comprehensive medical, behavioral, and neuroimaging assessments from early childhood through adolescence (2–19 years of age). We have employed several strategies to identify sub-populations within autistic individuals: subgrouping by neural, biological, behavioral or clinical characteristics as well as by developmental trajectories. In this Mini Review, we summarize findings to date from the APP cohort and describe progress made toward identifying meaningful subgroups of autism.

Factorisation-Based Image Labelling

Segmentation of brain magnetic resonance images (MRI) into anatomical regions is a useful task in neuroimaging. Manual annotation is time consuming and expensive, so having a fully automated and general purpose brain segmentation algorithm is highly desirable. To this end, we propose a patched-based labell propagation approach based on a generative model with latent variables. Once trained, our Factorisation-based Image Labelling (FIL) model is able to label target images with a variety of image contrasts. We compare the effectiveness of our proposed model against the state-of-the-art using data from the MICCAI 2012 Grand Challenge and Workshop on Multi-Atlas Labelling. As our approach is intended to be general purpose, we also assess how well it can handle domain shift by labelling images of the same subjects acquired with different MR contrasts.

Impending Mental Health Issues During Coronavirus Disease 2019 – Time for Personalized Nutrition Based on the Gut Microbiota to Tide Over the Crisis?

Coronavirus disease 2019 (COVID-19) is a major pandemic facing the world today caused by SARS-CoV-2 which has implications on our mental health as well. The uncertain future, fear of job loss, lockdown and negative news all around have taken a heavy toll on the mental health of individuals from across the world. Stress and anxiety can affect the COVID-19 patients even more. Recent study suggests COVID-19 infection may lead to post-traumatic stress disorder (PTSD). Certain prebiotics and probiotics have been shown to have anxiolytic effect through gut microbiota modulation. Incidentally, preliminary report also suggests a differential microbial profile in COVID-19 patients as compared to healthy individuals. Gut microbiota’s role in anxiety and depression is well studied. The importance of the “gut-brain” axis has been implicated in overall mental health. It is known that diet, environmental factors and genetics play an important role in shaping gut microbiota. Trials may be initiated to study if personalized diet and supplementation based on individual’s gut microbiome profile may improve the general mental well-being of people prone to anxiety during this pandemic. Also, COVID-19 patients may be provided personalized nutritional therapy based on their gut microbiota profile to see if PTSD and anxiety symptoms can be alleviated.

Sparse Representation-Based Discriminative Metric Learning for Brain MRI Image Retrieval

Magnetic resonance imaging (MRI) can have a good diagnostic function for important organs and parts of the body. MRI technology has become a common and important disease detection technology. At the same time, medical imaging data is increasing at an explosive rate. Retrieving similar medical images from a huge database is of great significance to doctors’ auxiliary diagnosis and treatment. In this paper, combining the advantages of sparse representation and metric learning, a sparse representation-based discriminative metric learning (SRDML) approach is proposed for medical image retrieval of brain MRI. The SRDML approach uses a sparse representation framework to learn robust feature representation of brain MRI, and uses metric learning to project new features into the metric space with matching discrimination. In such a metric space, the optimal similarity measure is obtained by using the local constraints of atoms and the pairwise constraints of coding coefficients, so that the distance between similar images is less than the given threshold, and the distance between dissimilar images is greater than another given threshold. The experiments are designed and tested on the brain MRI dataset created by Chang. Experimental results show that the SRDML approach can obtain satisfactory retrieval performance and achieve accurate brain MRI image retrieval.

Does Oblique Effect Affect SSVEP-Based Visual Acuity Assessment?

This study aimed to explore whether there was an effect on steady-state visual evoked potential (SSVEP) visual acuity assessment from the oblique effect or the stimulus orientation. SSVEPs were induced by seven visual stimuli, e.g., the reversal sinusoidal gratings with horizontal, two oblique, and vertical orientations, reversal checkerboards with vertical and oblique orientations, and oscillating expansion-contraction concentric-rings, at six spatial frequency steps. Ten subjects participated in the experiment. Subsequently, a threshold estimation criterion was used to determine the objective SSVEP visual acuity corresponding to each visual stimulus. Taking the SSVEP amplitude and signal-to-noise-ratio (SNR) of the fundamental reversal frequency as signal characteristics, both the SSVEP amplitude and SNR induced by the reversal sinusoidal gratings at 3.0 cpd among four stimulus orientations had no significant difference, and the same finding was also shown in the checkerboards between vertical and oblique orientation. In addition, the SSVEP visual acuity obtained by the threshold estimation criterion for all seven visual stimuli showed no significant difference. This study demonstrated that the SSVEPs induced by all these seven visual stimuli had a similarly good performance in evaluating visual acuity, and the oblique effect or the stimulus orientation had little effect on SSVEP response as well as the SSVEP visual acuity.

Altered Functional Network in Infants With Profound Bilateral Congenital Sensorineural Hearing Loss: A Graph Theory Analysis

Functional magnetic resonance imaging (fMRI) studies have suggested that there is a functional reorganization of brain areas in patients with sensorineural hearing loss (SNHL). Recently, graph theory analysis has brought a new understanding of the functional connectome and topological features in central neural system diseases. However, little is known about the functional network topology changes in SNHL patients, especially in infants. In this study, 34 infants with profound bilateral congenital SNHL and 28 infants with normal hearing aged 11–36 months were recruited. No difference was found in small-world parameters and network efficiency parameters. Differences in global and nodal topologic organization, hub distribution, and whole-brain functional connectivity were explored using graph theory analysis. Both normal-hearing infants and SNHL infants exhibited small-world topology. Furthermore, the SNHL group showed a decreased nodal degree in the bilateral thalamus. Six hubs in the SNHL group and seven hubs in the normal-hearing group were identified. The left middle temporal gyrus was a hub only in the SNHL group, while the right parahippocampal gyrus and bilateral temporal pole were hubs only in the normal-hearing group. Functional connectivity between auditory regions and motor regions, between auditory regions and default-mode-network (DMN) regions, and within DMN regions was found to be decreased in the SNHL group. These results indicate a functional reorganization of brain functional networks as a result of hearing loss. This study provides evidence that functional reorganization occurs in the early stage of life in infants with profound bilateral congenital SNHL from the perspective of complex networks.

Mechanism of Mongolian Medicine Eerdun Wurile in Improving Postoperative Cognitive Dysfunction Through Activation of the PI3K Signaling Pathway

ObjectiveTo study the effect of Eerdun Wurile (EW), a traditional Mongolian medicine, on the cognitive function of rats by activating the IRS-PI3K-AKT-GLUT4 pathway in an animal model of postoperative cognitive dysfunction (POCD).MethodsFifty clean-grade adults Sprague Dawley (SD) male rats were assigned to one of five groups: (1) a control group with no anesthesia (Group C), (2) a POCD model group with anesthesia only (Group P), (3) POCD group with low-dose EW treated (Group L), (4) a POCD group with high-dose EW treated (Group H), and (5) a POCD model group with dexmedetomidine treated (Group D) for positive control. The study started 7 days after all rats had acclimated to housing. Rats were trained in the Morris Water Maze navigation 5 days before surgery. All rats underwent the same maze for navigation and spatial exploration experiments on the preoperative day 1 and postoperative days 1, 3, 5, and their learning and memory abilities were assessed. At the end of the water maze experiment, rats were sacrificed to obtain hippocampal tissue. The mRNA levels of IRS-2, PI3K, AKT, and GLUT4 were measured in the hippocampus by real-time PCR, and the expression of IRS-2, PI3K, AKT, and GLUT4 protein in the hippocampus was determined by Western blotting to investigate the potential mechanisms at the molecular level.ResultsCompared to control Group C, Group P, L, H, and D showed prolonged escape latency (P < 0.05) and decreased number of times to cross the platform (P < 0.05) at 1, 3 and 5 days after surgery. Compared to Group P, Group L, H, and D showed a decrease in escape latency with an increased number of crossing the platform at all-time points after surgery (P < 0.05). Within individual P, L, H, and D groups, escape latencies decreased (P < 0.05) and the number of times that the platform was crossed increased (P < 0.05) between postoperative days 3 and 5 compared to postoperative 1 day. Compared to Group C, the mRNA expression of IRS-2, PI3K, AKT and GLUT4 in the hippocampus of P, L, H, and D groups were decreased (P < 0.05). Compared to Group P, IRS-2, PI3K, AKT, and GLUT4 in the hippocampus of L, H, and D groups were increased (P < 0.05). Compared with Group D, the expression levels of IRS-2 and AKT in both L and H groups were higher. The expression level of PI3K in Group L was also higher (P < 0.05) vs Group D. The expression of AKT mRNA in Group H was higher than in Group L (P < 0.05). Compared to Group C, the p-IRS-2/IRS-2 ratio in the hippocampus of Group P was higher than that of Group C (P < 0.05). Compared to Group P, the ratios of p-IRS-2/IRS-2 in Group L, Group H, and Group D were lower, and the ratios of the p-PI3K/PI3K, p-AKT/AKT, and p-GLUT4/GLUT4 were higher (P < 0.05).ConclusionAdministration of EW showed the effect on the signaling pathway in rats with POCD. The therapeutic effect was better in the low-dose group. This could be related to the insulin downstream signal molecule PI3K and the IRS-PI3K-AKT-GLUT4 signaling pathway.