Biology subjects

Evans, A. C.

Publications and source records attributed to Evans, A. C..

53 records · Page 3Linked to original sources

bioRxiv2020

Student-focused development of a next-generation centrifuge force microscope

Advanced biological molecule force probing methods such as atomic force microscopy and optical tweezers used to quantify forces at the single-molecule level are expensive and require extensive training and technical knowledge. However, the technologies underlying a centrifuge force microscope (CFM) are relatively straight forward, allowing for construction by labs with relatively low budgets and minimal training. Design ideas from previously constructed CFMs served as a guide in the development of this CFM. There were two primary goals: first, to develop an inexpensive, functional CFM using off-the-shelf and 3D printed parts; and second, to do so in the context of providing an educational experience for a broad range of students. The team included high school students and undergraduates from local high schools, the University of Minnesota, and other local higher education institutions. This project created an environment for student-focused development of the CFM that fostered active learning, individual ownership, as well as excellence in research. The instrument discussed herein represents a fully functional CFM designed and built by a postdoctoral researcher and a graduate student who together mentored several high school and undergraduate students. STATEMENT OF SIGNIFICANCEThe presented centrifuge force microscope (CFM) builds on features of existing designs specifically engineered for probing macromolecular force interactions at the single-molecule level. In the coming years, more versatile and modular CFM designs will be utilized in the force spectroscopy field, and the presented design is a step in that direction. In addition to constructing a functional instrument, true student ownership of the project design was equally an end goal. Students from high school through graduate school were included, and the project was structured so that everyone was seen as peers. This active learning project allowed students to acquire scientific concepts and techniques and apply them to real-life situations.

biophysics↗

bioRxiv2020

Nanolipoprotein mediated Her2 protein transfection induces malignant transformation in human breast acinar cultures

Her2 overexpression is associated with an aggressive form of breast cancer and malignant transformation. We sought to determine if a nano-carrier system could introduce Her2 protein to non-malignant cells and determine the effects on cell phenotype and transcriptome. With stimulation with Her2-NLPs, we observed uptake of Her2 protein and a decreased probability of individual non-malignant cells forming polar growth arrested acinar-like structures. The NLP delivery system alone or Her2-NLPs plus trastuzumab showed no effect on acinar organization rate. Transcriptomics revealed essentially no effect of empty NLPs versus untreated cells whereas Her2-NLPs versus either untreated or empty NLP treated cells revealed upregulation of several factors associated with breast cancer. Pathway analysis also suggested that known nodes downstream of Her2 were activated in response to Her2-NLP treatment. This suggests that Her2-NLPs are sufficient for malignant transformation of non-malignant cells and that this system offers a new model for studying cell surface receptor signaling without genomic modification or transformation techniques.

cancer biology↗

bioRxiv2020

CIVET-Macaque: an automated pipeline for MRI-based cortical surface generation and cortical thickness in macaques

The MNI CIVET pipeline for automated extraction of cortical surfaces and evaluation of cortical thickness from in-vivo human MRI has been extended for processing macaque brains. Processing is performed based on the NIMH Macaque Template (NMT), as the reference template, with the anatomical parcellation of the surface following the D99 and CHARM atlases. The modifications needed to adapt CIVET to the macaque brain are detailed. Results have been obtained using CIVET-macaque to process the anatomical scans of the 31 macaques used to generate the NMT and another 95 macaques from the PRIME-DE initiative. It is anticipated that the open usage of CIVET-macaque will promote collaborative efforts in data collection and processing, sharing, and automated analyses from which the non-human primate brain imaging field will advance.

neuroscience↗

bioRxiv2020

Convergence of cortical types and functional motifs in the mesiotemporal lobe

AO_SCPLOWBSTRACTC_SCPLOWThe parahippocampus-hippocampus complex in the mesiotemporal lobe (MTL) is implicated in many different cognitive processes, is compromised in numerous disorders, and exhibits a unique cytoarchitectural transition from six-layered isocortex to three-layered allocortex. Our study leveraged an ultra-high-resolution histological reconstruction of a human brain to (i) develop a continuous surface model of the MTL iso-to-allocortex transition and (ii) quantitatively characterise the regions cytoarchitecture. We projected the model into the native space of in vivo functional magnetic resonance imaging of healthy adults to (iii) construct a generative model of its intrinsic circuitry and (iv) determine its relationship with distributed functional dynamics of macroscale isocortical fluctuations. We provide evidence that the most prominent axis of cytoarchitectural differentiation of the MTL follows infolding from iso-to-allocortex and is defined by depth-specific variations in neuron density. Intrinsic effective connectivity exhibited a more complex relationship to MTL geometry, varying across both iso-to-allocortical and anterior-posterior axes. Variation along the long axis of the MTL was associated with differentiation between transmodal and unimodal systems, with anterior regions linked to transmodal cortex. In contrast, the iso-to-allocortical gradient was associated with the multiple demand system, with isocortex linked to regions activated when task demands prohibit the use of prior knowledge. Our findings establish a novel model of the MTL, in which its broad influence on neural function emerges through the combination micro- and macro-scale structural features. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/148643v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@48dbc7org.highwire.dtl.DTLVardef@15500a2org.highwire.dtl.DTLVardef@19c99b2org.highwire.dtl.DTLVardef@2eab49_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2020

Reproducible functional connectivity endophenotype confers high risk of ASD diagnosis in a subset of individuals

Functional connectivity (FC) analyses of individuals with autism spectrum disorder (ASD) have established robust alterations of brain connectivity at the group level. Yet, the translation of these imaging findings into robust markers of individual risk is hampered by the extensive heterogeneity among ASD individuals. Here, we report an FC endophenotype that confers a greater than 7-fold risk increase of ASD diagnosis, yet is still identified in an estimated 1 in 200 individuals in the general population. By focusing on a subset of individuals with ASD and highly predictive FC alterations, we achieved a greater than 3-fold increase in risk over previous predictive models. The identified FC risk endophenotype was characterized by underconnectivity of transmodal brain networks and generalized to independent data. Our results demonstrate the ability of a highly targeted prediction model to meaningfully decompose part of the heterogeneity of the autism spectrum. The identified FC signature may help better delineate the multitude of etiological pathways and behavioural symptoms that challenge our understanding of the autism spectrum.

neuroscience↗

bioRxiv2020

Subtypes of functional connectivity associate robustly with ASD diagnosis

Our understanding of the changes in functional brain organization in autism is hampered by the extensive heterogeneity that characterizes this neurodevelopmental disorder. Data driven clustering offers a straightforward way to decompose this heterogeneity into subtypes of distinguishable connectivity types and promises an unbiased framework to investigate behavioural symptoms and causative genetic factors. Yet the robustness and generalizability of these imaging subtypes is unknown. Here, we show that unsupervised functional connectivity subtypes are moderately associated with the clinical diagnosis of autism, and that these associations generalize to independent replication data. We found that subtypes identified robust patterns of functional connectivity, but that a discrete assignment of individuals to these subtypes was not supported by the data. Our results support the use of data driven subtyping as a data dimensionality reduction technique, rather than to establish clinical categories.

neuroscience↗

bioRxiv2020

Creation of an Open Science Dataset from PREVENT-AD, a Longitudinal Cohort Study of Pre-symptomatic Alzheimer's Disease.

To move Alzheimer Disease (AD) research forward it is essential to collect data from large cohorts, but also make such data available to the global research community. We describe the creation of an open science dataset from the PREVENT-AD (PResymptomatic EValuation of Experimental or Novel Treatments for AD) cohort, composed of cognitively unimpaired older individuals with a parental or multiple-sibling history of AD. From 2011 to 2017, 386 participants were enrolled (mean age 63 years old {+/-} 5) for sustained investigation among whom 349 have retrospectively agreed to share their data openly. Repositories are findable through the unified interface of the Canadian Open Neuroscience Platform (https://portal.conp.ca/) and contain up to five years of longitudinal imaging data, cerebral fluid biochemistry, neurosensory capacities, cognitive, genetic, and medical information. Imaging data can be accessed openly at https://openpreventad.loris.ca while most of the other information, sensitive by nature, is accessible by qualified researchers at https://registeredpreventad.loris.ca. In addition to being a living resource for continued data acquisition, PREVENT-AD offers opportunities to facilitate understanding of AD pathogenesis.

neuroscience↗

bioRxiv2019

A sub+ cortical fMRI-based surface parcellation

Both the cortex and the subcortical structures are organized into a large number of distinct areas reflecting functional and cytoarchitectonic differences. Mapping these areas is of fundamental importance to neuroscience. A central obstacle to this task is the inaccuracy associated with mapping results from individuals into a common space. The vast individual differences in morphology pose a serious problem for volumetric registration. Surface-based approaches fare substantially better, but have thus far been used only for cortical parcellation. We extend this surface-based approach to include also the subcortical deep gray-matter structures. Using the life-span data from the Enhanced Nathan Klein Institute - Rockland Sample, comprised of data from 590 individuals from 6 to 85 years of age, we generate a functional parcellation of both the cortical and subcortical surfaces. To assess this extended parcellation, we show that our extended functional parcellation provides greater homogeneity of functional connectivity patterns than do arbitrary parcellations matching in the number and size of parcels. We also show that our subcortical parcels align with known subnuclei. Further, we show that this parcellation is appropriate for use with data from other modalities; we generate cortical and subcortical white/gray contrast measures for this same dataset, and draw on the fact that areal differences are evident in the relation of white/gray contrast to age, to sex, to brain volume, and to interactions of these terms; we show that our extended functional parcellation provides an improved fit to the complexity of the life-span changes in the white/gray contrast data compared to arbitrary parcellations matching in the number and size of parcels. We provide our extended functional parcellation for the use of the neuroimaging community.

neuroscience↗

bioRxiv2019

Neuropsychiatric mutations delineate functional brain connectivity dimensions contributing to autism and schizophrenia

16p11.2 and 22q11.2 Copy Number Variants (CNVs) confer high risk for Autism Spectrum Disorder (ASD), schizophrenia (SZ), and Attention-Deficit-Hyperactivity-Disorder (ADHD), but their impact on functional connectivity (FC) remains unclear. We analyzed resting-state functional magnetic resonance imaging data from 101 CNV carriers, 755 individuals with idiopathic ASD, SZ, or ADHD and 1,072 controls. We used CNV FC-signatures to identify dimensions contributing to complex idiopathic conditions. CNVs had large mirror effects on FC at the global and regional level. Thalamus, somatomotor, and posterior insula regions played a critical role in dysconnectivity shared across deletions, duplications, idiopathic ASD, SZ but not ADHD. Individuals with higher similarity to deletion FC-signatures exhibited worse cognitive and behavioral symptoms. Deletion similarities identified at the connectivity level could be related to the redundant associations observed genome-wide between gene expression spatial patterns and FC-signatures. Results may explain why many CNVs affect a similar range of neuropsychiatric symptoms.

neuroscience↗

bioRxiv2019

Amplifying the Neural Power Spectrum

We introduce a novel method that employs a parametric model of human electroen-cephalographic (EEG) brain signal power spectra to evaluate cognitive science experiments and test scientific hypotheses. We develop the Neural Power Amplifier (NPA), a data-driven approach to EEG pre-processing that can replace current filtering strategies with a principled method based on combining filters with log-arithmic and Gaussian magnitude responses. Presenting the first time domain evidence to validate an increasingly popular model for neural power spectra [1], we show that filtering out the 1/f background signal and selecting peaks improves a time-domain decoding experiment for visual stimulus of human faces versus random noise.

neuroscience↗

bioRxiv2019

A molecular gradient along the longitudinal axis of the human hippocampus informs large-scale behavioral systems

The functional organization of the hippocampus is distributed as a gradient along its longitudinal axis that explains its differential interaction with diverse brain systems. We show that the location of human tissue samples extracted along the longitudinal axis of the hippocampus can be predicted within 2mm using the expression pattern of less than 100 genes. When variation in this specific gene expression pattern was observed across the whole brain, a distinct anterioventral-posteriodorsal gradient was observed. Frontal, anterior temporal and brainstem regions involved in social and motivational behaviors, selectively vulnerable to frontotemporal dementia and more functionally connected to the anterior hippocampus could be clearly differentiated from posterior parieto-occipital and cerebellar regions involved in spatial cognition, selectively vulnerable to Alzheimers disease, and more functionally connected to the posterior hippocampus. These findings place the human hippocampus at the interface of two major brain systems defined by a single distinct molecular gradient. (148/150)

neuroscience↗

bioRxiv2019

Automated segmentation of cortical layers in BigBrain reveals divergent cortical and laminar thickness gradients in sensory and motor cortices.

Histological atlases of the cerebral cortex, such as those made famous by Brodmann and von Economo, are invaluable for understanding human brain microstructure and its relationship with functional organization in the brain. However, these existing atlases are limited to small numbers of manually annotated samples from a single cerebral hemisphere, measured from 2D histological sections. We present the first whole-brain quantitative 3D laminar atlas of the human cerebral cortex. This atlas was derived from a 3D histological model of the human brain at 20 micron isotropic resolution (BigBrain), using a convolutional neural network to segment, automatically, the cortical layers in both hemispheres. Our approach overcomes many of the historical challenges with measurement of histological thickness in 2D and the resultant laminar atlas provides an unprecedented level of precision and detail. We utilized this BigBrain cortical atlas to test whether previously reported thickness gradients, as measured by MRI in sensory and motor processing cortices, were present in a histological atlas of cortical thickness, and which cortical layers were contributing to these gradients. Cortical thickness increased across sensory processing hierarchies, primarily driven by layers III, V and VI. In contrast, fronto-motor cortices showed the opposite pattern, with decreases in total and pyramidal layer thickness. These findings illustrate how this laminar atlas will provide a link between single-neuron morphology, mesoscale cortical layering, macroscopic cortical thickness and, ultimately, functional neuroanatomy.

neuroscience↗

bioRxiv2019

Pathological tau spreads through communicating brain regions in human Alzheimer's disease

Tau is one of the two pathological hallmarks of Alzheimers disease, and bears a much closer relationship to local neurodegeneration and cognitive impairment than the other hallmark, {beta}-amyloid. Cell and rodent models have shown evidence that tau spreads from cell to cell through anatomical neuronal connections, and that this process is facilitated by the presence of {beta}-amyloid. We test this hypothesis in humans by using an epidemic spreading model (ESM) to simulate the spread of tau over human neuronal connections, and we compare the simulated pattern of progression to the observed pattern measured in the brains of 312 individuals on the Alzheimers disease spectrum, using PET. Fitting our model, we found that the majority of variance in the overall pattern of tau progression could be explained by diffusion of an agent through the human connectome, measured using either functional connectivity or diffusion tractography. These models far exceeded chance, and outperformed models testing the extracellular spread of tau over Euclidian space. Surprisingly, the ESM predicted the spatial patterns of tau irrespective of whether subjects demonstrated evidence for brain {beta}-amyloid. In addition, in {beta}-amyloid-positive subjects only, regions with greater amyloid burden showed greater tau than predicted by connectivity patterns, suggesting a role of amyloid in accelerating the spread of tau in certain isocortical regions. Altogether, our results provide strong evidence that tau spreads through neuronal communication pathways even in normal aging, and that this process is accelerated by the presence of brain {beta}-amyloid.

neuroscience↗

bioRxiv2019

Cortical and subcortical T1 white/gray contrast, chronological age, and cognitive performance

The maturational schedule of typical brain development is tightly constrained; deviations from it are associated with cognitive atypicalities, and are potentially predictive of developmental disorders. Previously, we have shown that the white/gray contrast at the inner border of the cortex is a good predictor of chronological age, and is sensitive to aspects of brain development that reflect cognitive performance. Here we extend that work to include the contrast at the white/gray border of subcortical structures. We show that cortical and subcortical contrast together yield better age-predictions than any non-kernel-based method based on a single image-type, and that the residuals of the improved predictions provide new insight into unevenness in cognitive performance. We demonstrate the improvement in age predictions in two large datasets: the NIH Pediatric Data, with 831 scans of typically developing individuals between 4 and 22 years of age; and the Pediatric Imaging, Neurocognition, and Genetics data, with 909 scans of individuals in a similar age-range. Assessment of the relation of the residuals of these age predictions to verbal and performance IQ revealed correlations in opposing directions, and a principal component analysis of the residuals of the model that best fit the contrast data produced components related to either performance IQ or verbal IQ. Performance IQ was associated with the first principle component, reflecting increased cortical contrast, broadly, with almost no subcortical presence; verbal IQ was associated with the second principle component, reflecting reduced contrast in the basal ganglia and increased contrast in the bilateral arcuate fasciculi.

neuroscience↗

bioRxiv2018

NeuroMTL iSEG challenge methods

We propose a tissue classification method for MRI scans of 6-month old infants, and used it to process the iSeg-2017 challenge data. The method relies on a deep-learning 3D U-Net network, trained with MRI scans of 216 infants, aged 6-24 months, from the ACE-IBIS longitudinal database.

neuroscience↗

bioRxiv2018

Data-driven approaches improve Tau-PET biomarkers in Alzheimer’s disease

Previous positron emission tomography (PET) studies have quantified filamentous tau pathology using regions-of-interest (ROIs) based on observations of the topographical distribution of neurofibrillary tangles in post-mortem tissue. However, such approaches may not take full advantage of information contained in neuroimaging data. The present study employs an unsupervised data-driven method to identify spatial patterns of tau-PET distribution, and to compare these patterns to previously published \"pathology-driven\" ROIs. Tau-PET patterns were identified from a discovery sample comprised of 123 normal controls and patients with mild cognitive impairment or Alzheimers disease (AD) dementia from the Swedish BioFINDER cohort, who underwent [18F]AV1451 PET scanning. Associations with cognition were tested in a separate sample of 90 individuals from ADNI. BioFINDER [18F]AV1451 images were entered into a robust voxelwise stable clustering algorithm, which resulted in five clusters. Mean [18F]AV1451 uptake in the data-driven clusters, and in 35 previously published pathology-driven ROIs, was extracted from ADNI [18F]AV1451 scans. We performed linear models comparing [18F]AV1451 signal across all 40 ROIs to several tests of global cognition, adjusting for age, sex and education. Two data-driven ROIs consistently demonstrated the strongest or near-strongest effect sizes across all cognitive tests. Inputting all regions plus demographics into a feature selection routine resulted in selection of two ROIs (one data-driven, one pathology-driven) and education, which together explained 28% of the variance of a global cognitive composite score. Our findings suggest that [18F]AV1451-PET data naturally clusters into spatial patterns that are biologically meaningful and that may offer advantages as clinical tools.

neuroscience↗

bioRxiv2017

T1 white/gray contrast as a predictor of chronological age, and an index of cognitive performance

The maturational schedule of human brain development appears to be narrowly confined. The chronological age of an individual can be predicted from brain images with considerable accuracy, and deviation from the typical pattern of brain maturation has been related to cognitive performance. Methods using multi-modal data, or complex measures derived from voxels throughout the brain have shown the greatest accuracy, but are difficult to interpret in terms of the biology. Measures based on the cortical surface(s) have yielded less accurate predictions, suggesting that perhaps developmental changes related to cortical gray matter are not strongly related to chronological age, and that perhaps development is more strongly related to changes in subcortical regions or in deep white matter. We show that a simple metric based on the white/gray contrast at the inner border of the cortical gray-matter is a comparably good predictor of chronological age, and our usage of an elastic net penalized linear regression model reveals the brain regions which contribute most to age-prediction. We demonstrate this in two large datasets: the NIH Pediatric Data, with 832 scans of typically developing children, adolescents, and young adults; and the Pediatric Imaging, Neurocognition, and Genetics data, with 760 scans of individuals in a similar age-range. Moreover, we show that the residuals of age-prediction based on this white/gray contrast metric are more strongly related to IQ than are those from cortical thickness, suggesting that this metric is more sensitive to aspects of brain development that reflect cognitive performance.

neuroscience↗