Identifying Boys With Autism Spectrum Disorder Based on Whole-Brain Resting-State Interregional Functional Connections Using a Boruta-Based Support Vector Machine Approach.

An increasing number of resting-state functional magnetic resonance neuroimaging (R-fMRI) studies have used functional connections as discriminative features for machine learning to identify patients with brain diseases. However, it remains unclear which functional connections could serve as highly discriminative features to realize the classification of autism spectrum disorder (ASD). The aim of this study was to find ASD-related functional connectivity patterns and examine whether these patterns had the potential to provide neuroimaging-based information to clinically assist with the diagnosis of ASD by means of machine learning. We investigated the whole-brain interregional functional connections derived from R-fMRI. Data were acquired from 48 boys with ASD and 50 typically developing age-matched controls at NYU Langone Medical Center from the publicly available Autism Brain Imaging Data Exchange I (ABIDE I) dataset; the ASD-related functional connections identified by the Boruta algorithm were used as the features of support vector machine (SVM) to distinguish patients with ASD from typically developing controls (TDC); a permutation test was performed to assess the classification performance. Approximately, 92.9% of participants were correctly classified by a combined SVM and leave-one-out cross-validation (LOOCV) approach, wherein 95.8% of patients with ASD were correctly identified. The default mode network (DMN) exhibited a relatively high network degree and discriminative power. Eight important brain regions showed a high discriminative power, including the posterior cingulate cortex (PCC) and the ventrolateral prefrontal cortex (vlPFC). Significant correlations were found between the classification scores of several functional connections and ASD symptoms (p < 0.05). This study highlights the important role of DMN in ASD identification. Interregional functional connections might provide useful information for the clinical diagnosis of ASD.

Altered dynamic functional connectivity of insular subregions could predict symptom severity of male patients with autism spectrum disorder.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by difficulties with social communication and restricted or repetitive patterns of behavior. This disorder was characterized by widespread abnormalities involving distributed brain networks. As one such key network node, the insular cortex has been regarded as a research focus of ASD neuropathology. The insula is a functionally complex brain structure. However, it is not fully clear if dynamic characteristics of resting-state functional magnetic resonance imaging (R-fMRI) signals in insular heterogeneous could be used to depict abnormalities in ASD. To address this question, we investigated dynamic functional connectivity (dFC) of 12 insular subregions. Data were obtained from 44 individuals with ASD and 65 typically developing age-matched controls (TDC). We assessed dFC by sliding-window method and quantified its temporal variability. Multivariable linear regression models were constructed to determine whether dFC support complementary information about symptom severity of individuals with ASD rather than static functional connectivity (sFC). The results showed that individuals with ASD exhibited dFC and sFC alterations in distinct insular subregions. Some brain regions showed only abnormal dFC but not sFC with insular subregions. These abnormal dFC could significantly predict the symptom severity of individuals with ASD. Our findings might advance our knowledge about the potential of insular heterogeneity and dynamic characteristics in understanding the neuropathology mechanism of ASD and in developing neuroimaging biomarkers for clinical applications.

The acts of opening and closing the eyes are of importance for congenital blindness: Evidence from resting-state fMRI.

Volitional eye closure is observed only in conscious and awake humans, and is rare in animals. It is believed that eye closure can focus one's attention inward and facilitate activities such as meditation and mental imagery. Congenital blind individuals are also required to close their eyes for these activities. Resting-state functional magnetic resonance imaging (RS-fMRI) studies have found robust differences between the eyes-closed (EC) and eyes-open (EO) conditions in some brain regions in the sighted. This study analyzed data from 21 congenital blind individuals and 21 sighted controls by using amplitude of low-frequency fluctuation (ALFF) of RS-fMRI. The blind group and the sighted group shared similar pattern of differences between the EC and EO condition: ALFF was higher in the EC condition than the EO condition in the bilateral primary sensorimotor cortex, bilateral supplementary motor area, and inferior occipital cortex, while ALFF was lower in the EC condition than the EO condition in the medial prefrontal cortex, highlighting the "nature" effect on the difference between the EC and EO conditions. The results of other matrices such as fractional ALFF (fALFF) and regional homogeneity (ReHo) showed similar patterns to that of ALFF. Moreover, no significant difference was observed between the EC-EO pattern of the two subgroups of congenital blind (i.e., with and without light perception), suggesting that the EC-EO difference is irrespective of residual light perception which reinforced the "nature" effect. We also found between-group differences, i.e., more probably "nurture effect", in the posterior insula and fusiform. Our results suggest that the acts of closing and opening the eyes are of importance for the congenital blind, and that these actions and their differences might be inherent in the nature of humans.

Low SO2 emission from CFB co-firing MSW and bituminous.

Influence of co-firing rate on SO2 emission from co-firing municipal solid waste (MSW) and bituminous containing high amount of sulfur (1.79%) was studied in a 0.15 MWt circulating fluidized bed (CFB). The temperature selected is 1123 K, typical for MSW incineration using CFB. The particle concentration in the dilution zone of the furnace, the alkali metal concentration and sulfate concentration in the recirculating ash and fly ash, and flue gas composition were determined. The results showed that the addition of MSW leads to a significant decrease in SO2 emission. Concentration of SO2 in flue gas decreased to 0 with the co-firing rate greater than 51%. This reduction in SO2 emission is attributed both to the high particle concentration in the dilution zone of the furnace, the high content of alkali metals in the bed material, and to the comparatively high concentration of HCI in flue gas during co-firing of MSW and bituminous.