Subtyping cognitive profiles in Autism Spectrum Disorder using a Functional Random Forest algorithm.

DSM-5 Autism Spectrum Disorder (ASD) comprises a set of neurodevelopmental disorders characterized by deficits in social communication and interaction and repetitive behaviors or restricted interests, and may both affect and be affected by multiple cognitive mechanisms. This study attempts to identify and characterize cognitive subtypes within the ASD population using our Functional Random Forest (FRF) machine learning classification model. This model trained a traditional random forest model on measures from seven tasks that reflect multiple levels of information processing. 47 ASD diagnosed and 58 typically developing (TD) children between the ages of 9 and 13 participated in this study. Our RF model was 72.7% accurate, with 80.7% specificity and 63.1% sensitivity. Using the random forest model, the FRF then measures the proximity of each subject to every other subject, generating a distance matrix between participants. This matrix is then used in a community detection algorithm to identify subgroups within the ASD and TD groups, and revealed 3 ASD and 4 TD putative subgroups with unique behavioral profiles. We then examined differences in functional brain systems between diagnostic groups and putative subgroups using resting-state functional connectivity magnetic resonance imaging (rsfcMRI). Chi-square tests revealed a significantly greater number of between group differences (p < .05) within the cingulo-opercular, visual, and default systems as well as differences in inter-system connections in the somato-motor, dorsal attention, and subcortical systems. Many of these differences were primarily driven by specific subgroups suggesting that our method could potentially parse the variation in brain mechanisms affected by ASD.

Rheo-optical studies of carbon nanotube suspensions.

We use a polarization-modulation technique to investigate the optical anisotropy of multi- and single-wall carbon nanotubes suspended in a variety of solvents under simple shear flow. Measurements of birefringence and dichroism are performed as a function of shear rate, tube concentration, and solvent viscosity. At fixed volume fraction, the anisotropy increases with increasing shear stress due to enhanced flow alignment. At fixed shear stress, the anisotropy increases with volume fraction due to rotational excluded-volume interactions. By considering the rotational diffusivity as a function of nanotube length, diameter, concentration, and solvent viscosity, we demonstrate a leading-order scaling relation for the optical anisotropy in terms of rotary Peclet number Pe. At low Pe, our results are in qualitative agreement with the theoretical predictions of Doi and Edwards. At high Pe, our data suggest that the degree of nanotube alignment scales as Pe16.

Anisotropy of sheared carbon-nanotube suspensions.

We measure the anisotropy of sheared carbon-nanotube suspensions for a broad range of concentration, aspect ratio, and strain rate using a variety of methods. Our measurements highlight the importance of excluded-volume interactions in the semidilute regime, with scaling in terms of a dimensionless shear rate. Our results also suggest that such interactions might be exploited to fractionate carbon nanotubes by length in simple shear flow.

SBE-TAGS: an array-based method for efficient single-nucleotide polymorphism genotyping.

Generating human single-nucleotide polymorphisms (SNPs) is no longer a rate-limiting step for genetic studies of disease. The number of SNPs in public databases already exceeds 200,000, and the total is expected to exceed 1,000,000 within a year. Rather, progress is limited by the inability to genotype large numbers of SNPs. Current genotyping methods are suitable for studying individual loci or at most a handful at a time. Here, we describe a method for parallel genotyping of SNPs, called single base extension-tag array on glass slides, SBE-TAGS. The principle is as follows. SNPs are genotyped by single base extension (SBE), using bifunctional primers carrying a unique sequence tag in addition to a locus-specific sequence. Because each locus has a distinct tag, the genotyping reactions can be performed in a highly multiplexed fashion, and the resulting product can then be "demultiplexed" by hybridization to the reverse complements of the sequence tags arrayed on a glass slide. SBE-TAGS is simple and inexpensive because of the high degree of multiplexing and the use of an easily generated, generic tag array. The method is also highly accurate: we genotyped over 100 SNPs, obtaining over 5, 000 genotypes, with approximately 99% accuracy.