Quantification of white matter cellularity and damage in preclinical and early symptomatic Alzheimer\u27s disease

Interest in understanding the roles of white matter (WM) inflammation and damage in the pathophysiology of Alzheimer disease (AD) has been growing significantly in recent years. However, in vivo magnetic resonance imaging (MRI) techniques for imaging inflammation are still lacking. An advanced diffusion-based MRI method, neuro-inflammation imaging (NII), has been developed to clinically image and quantify WM inflammation and damage in AD. Here, we employed NII measures in conjunction with cerebrospinal fluid (CSF) biomarker classification (for β-amyloid (Aβ) and neurodegeneration) to evaluate 200 participants in an ongoing study of memory and aging. Elevated NII-derived cellular diffusivity was observed in both preclinical and early symptomatic phases of AD, while disruption of WM integrity, as detected by decreased fractional anisotropy (FA) and increased radial diffusivity (RD), was only observed in the symptomatic phase of AD. This may suggest that WM inflammation occurs earlier than WM damage following abnormal Aβ accumulation in AD. The negative correlation between NII-derived cellular diffusivity and CSF Aβ42 level (a marker of amyloidosis) may indicate that WM inflammation is associated with increasing Aβ burden. NII-derived FA also negatively correlated with CSF t-tau level (a marker of neurodegeneration), suggesting that disruption of WM integrity is associated with increasing neurodegeneration. Our findings demonstrated the capability of NII to simultaneously image and quantify WM cellularity changes and damage in preclinical and early symptomatic AD. NII may serve as a clinically feasible imaging tool to study the individual and composite roles of WM inflammation and damage in AD. Keywords: Inflammation, White matter damage, Diffusion basis spectrum imaging, Neuro-inflammation imaging, Cerebrospinal fluid, Preclinical Alzheimer disease, Early symptomatic Alzheimer disease, Magnetic resonance imagin

Hyperspectral remote sensing of cyanobacterial pigments as indicators for cell populations and toxins in eutrophic lakes

The growth of mass populations of toxin-producing cyanobacteria is a serious concern for the ecological status of inland waterbodies and for human and animal health. In this study we examined the performance of four semi-analytical algorithms for the retrieval of chlorophyll a (Chl a) and phycocyanin (C-PC) from data acquired by the Compact Airborne Spectrographic Imager-2 (CASI-2) and the Airborne Imaging Spectrometer for Applications (AISA) Eagle sensor. The retrieval accuracies of the semi-analytical models were compared to those returned by optimally calibrated empirical band-ratio algorithms. The best-performing algorithm for the retrieval of Chl a was an empirical band-ratio model based on a quadratic function of the ratio of re!ectance at 710 and 670 nm (R2=0.832; RMSE=29.8%). However, this model only provided a marginally better retrieval than the best semi-analytical algorithm. The best-performing model for the retrieval of C-PC was a semi-analytical nested band-ratio model (R2=0.984; RMSE=3.98 mg m−3). The concentrations of C-PC retrieved using the semi-analytical model were correlated with cyanobacterial cell numbers (R2=0.380) and the particulate and total (particulate plus dissolved) pools of microcystins (R2=0.858 and 0.896 respectively). Importantly, both the empirical and semi-analytical algorithms were able to retrieve the concentration of C-PC at cyanobacterial cell concentrations below current warning thresholds for cyanobacteria in waterbodies. This demonstrates the potential of remote sensing to contribute to early-warning detection and monitoring of cyanobacterial blooms for human health protection at regional and global scales

Tisa: A Language Design and Modular Verification Technique for Temporal Policies in Web Services

Web services are distributed software components, that are decoupled from each other using interfaces with specified functional behaviors. However, such behavioral specifications are insufficient to demonstrate compliance with certain temporal non-functional policies. An example is demonstrating that a patient’s health-related query sent to a health care service is answered only by a doctor (and not by a secretary). Demonstrating compliance with such policies is important for satisfying governmental privacy regulations. It is often necessary to expose the internals of the web service implementation for demonstrating such compliance, which may compromise modularity. In this work, we provide a language design that enables such demonstrations, while hiding majority of the service’s source code. The key idea is to use greybox specifications to allow service providers to selectively hide and expose parts of their implementation. The overall problem of showing compliance is then reduced to two subproblems: whether the desired properties are satisfied by the service’s greybox specification, and whether this greybox specification is satisfied by the service’s implementation. We specify policies using LTL and solve the first problem by model checking. We solve the second problem by refinement techniques

Student Satisfaction and Performance in an Online Teacher Certification Program

The article presents a study which demonstrates the effectiveness of an online post baccalaureate teacher certification program developed by a Wisconsin university. The case method approach employing multiple methods and multiple data sources were used to investigate the degree to which pre-service teachers were prepared to teach. It was concluded that the study supports online delivery as an effective means of teacher preparation, but it was limited in the number of students followed into their first year of teaching

Intragroup and Galaxy-linked Diffuse X-ray Emission In Hickson Compact Groups

Isolated compact groups (CGs) of galaxies present a range of dynamical states, group velocity dispersions, and galaxy morphologies with which to study galaxy evolution, particularly the properties of gas both within the galaxies and in the intragroup medium. As part of a large, multiwavelength examination of CGs, we present an archival study of diffuse X-ray emission in a subset of nine Hickson compact groups (HCGs) observed with the Chandra X-Ray Observatory. We find that seven of the groups in our sample exhibit detectable diffuse emission. However, unlike large-scale emission in galaxy clusters, the diffuse features in the majority of the detected groups are linked to the individual galaxies, in the form of both plumes and halos likely as a result of vigourous star formation or activity in the galaxy nucleus, as well as in emission from tidal features. Unlike previous studies from earlier X-ray missions, HCGs 31, 42, 59, and 92 are found to be consistent with the L(sub X-Tau) relationship from clusters within the errors, while HCGs 16 and 31 are consistent with the cluster L(sub X-sigma) relation, though this is likely coincidental given that the hot gas in these two systems is largely due to star formation. We find that L(sub X) increases with decreasing group Hi to dynamical-mass ratio with tentative evidence for a dependence in X-ray luminosity on Hi morphology whereby systems with intragroup Hi indicative of strong interactions are considerably more X-ray luminous than passively evolving groups. We also find a gap in the L(sub X) of groups as a function of the total group specific star formation rate. Our findings suggest that the hot gas in these groups is not in hydrostatic equilibrium and these systems are not low-mass analogs of rich groups or clusters, with the possible exception of HCG 62

Ic‐P‐204: The Relationship Between Tau Pet And Other Ad Biomarkers In Autosomal Dominant Alzheimer Disease

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152660/1/alzjjalz2018062271.pd