Predicting conversion to dementia in a memory clinic: A standard clinical approach compared with an empirically defined clustering method (latent profile analysis) for mild cognitive impairment subtyping

AbstractIntroductionMild cognitive impairment (MCI) has clinical value in its ability to predict later dementia. A better understanding of cognitive profiles can further help delineate who is most at risk of conversion to dementia. We aimed to (1) examine to what extent the usual MCI subtyping using core criteria corresponds to empirically defined clusters of patients (latent profile analysis [LPA] of continuous neuropsychological data) and (2) compare the two methods of subtyping memory clinic participants in their prediction of conversion to dementia.MethodsMemory clinic participants (MCI, n = 139) and age-matched controls (n = 98) were recruited. Participants had a full cognitive assessment, and results were grouped (1) according to traditional MCI subtypes and (2) using LPA. MCI participants were followed over approximately 2 years after their initial assessment to monitor for conversion to dementia.ResultsGroups were well matched for age and education. Controls performed significantly better than MCI participants on all cognitive measures. With the traditional analysis, most MCI participants were in the amnestic multidomain subgroup (46.8%) and this group was most at risk of conversion to dementia (63%). From the LPA, a three-profile solution fit the data best. Profile 3 was the largest group (40.3%), the most cognitively impaired, and most at risk of conversion to dementia (68% of the group).DiscussionLPA provides a useful adjunct in delineating MCI participants most at risk of conversion to dementia and adds confidence to standard categories of clinical inference

PREDICTING CONVERSION TO DEMENTIA IN A MEMORY CLINIC A STANDARD CLINICAL APPROACH COMPARED WITH AN EMPIRICALLY DEFINED CLUSTERING METHOD LATENT PROFILE ANALYSIS FOR MILD COGNITIVE IMPAIRMENT SUBTYPING

Introduction: Mild cognitive impairment (MCI) has clinical value in its ability to predict later dementia. A better understanding of cognitive profiles can further help delineate who is most at risk of conversion to dementia. We aimed to (1) examine to what extent the usual MCI subtyping using core criteria corresponds to empirically defined clusters of patients (latent profile analysis [LPA] of continuous neuropsychological data) and (2) compare the two methods of subtyping memory clinic participants in their prediction of conversion to dementia. Methods: Memory clinic participants (MCI, n = 139) and age-matched controls (n = 98) were recruited. Participants had a full cognitive assessment, and results were grouped (1) according to traditional MCI subtypes and (2) using LPA. MCI participants were followed over approximately 2 years after their initial assessment to monitor for conversion to dementia. Results: Groups were well matched for age and education. Controls performed significantly better than MCI participants on all cognitive measures. With the traditional analysis, most MCI participants were in the amnestic multidomain subgroup (46.8%) and this group was most at risk of conversion to dementia (63%). From the LPA, a three-profile solution fit the data best. Profile 3 was the largest group (40.3%), the most cognitively impaired, and most at risk of conversion to dementia (68% of the group). Discussion: LPA provides a useful adjunct in delineating MCI participants most at risk of conversion to dementia and adds confidence to standard categories of clinical inference

Climatology of size, shape and intensity of precipitation features over Great Britain and Ireland

A climatology of precipitation features (or objects) from the Great Britain and Ireland radar-derived precipitation mosaic from 2006–2015 is constructed, with features defined as contiguous areas of nonzero precipitation rates. Over the ten years, there are 54,811,747 non-unique precipitating features over 100 km2 in area, with a median precipitation-feature area of 249 km2, median major axis length of 29.2 km, median aspect ratio of 2.0, median feature mean precipitation rate of 0.49 mm h-1, and median feature maximum precipitation rate of 2.4 mm h-1. Small-scale precipitating systems are most common, but larger systems exceeding 10,000 km2 contribute close to 70% of the annual precipitation across the study region. Precipitation feature characteristics are sensitive to changes in annual and diurnal environment, with feature intensities peaking during the afternoon in summer and the largest precipitation features occurring during winter. Precipitation intensities less than 5 mm h-1 comprise 97.3% of all precipitation occurrence and contribute 83.6% of the total precipitation over land. Banded-precipitation features (defined as precipitation features with aspect ratio at least 3:1 and major axis length at least 100 km) comprise 3% of all precipitation features by occurrence, but contribute 23.7% of the total precipitation. Mesoscale banded features (defined as banded-precipitation features with major axis length at least 100 km and total area not exceeding 10,000 km2) and mesoscale convective banded features (defined as banded-precipitation features with at least 100 km2 of precipitation rates exceeding 10 mm h-1) are most prevalent in southwestern England with mesoscale convective banded features contributing up to 2% of precipitation

Microstructural abnormalities in white and gray matter in obese adolescents with and without type 2 diabetes

Aims/hypotheses. In adults, type 2 diabetes and obesity have been associated with structural brain changes, even in the absence of dementia. Some evidence suggested similar changes in adolescents with type 2 diabetes but comparisons with a non-obese control group have been lacking. The aim of the current study was to examine differences in microstructure of gray and white matter between adolescents with type 2 diabetes, obese adolescents and healthy weight adolescents.Methods. Magnetic resonance imaging data were collected from 15 adolescents with type 2 diabetes, 21 obese adolescents and 22 healthy weight controls. Volumetric differences in the gray matter between the three groups were examined using voxel based morphology, while tract based spatial statistics was used to examine differences in the microstructure of the white matter. Results. Adolescents with type 2 diabetes and obese adolescents had reduced gray matter volume in the right hippocampus, left putamen and caudate, bilateral amygdala and left thalamus compared to healthy weight controls. Type 2 diabetes was also associated with significant regional changes in fractional anisotropy within the corpus callosum, fornix, left inferior fronto-occipital fasciculus, left uncinate, left internal and external capsule. Fractional anisotropy reductions within these tracts were explained by increased radial diffusivity, which may suggest demyelination of white matter tracts. Mean diffusivity and axial diffusivity did not differ between the groups

Climatology of banded precipitation over the contiguous United States

A climatology of banded-precipitation features over the contiguous United States from 2003–2014 is constructed. A band is defined as a precipitation feature with a major axis of 100 km or greater and a ratio of major axis length to minor axis length (hereafter, aspect ratio) of 3:1 or greater. By applying an automated feature-based detection algorithm to composite radar imagery, a database of 48,916,844 precipitation features is created, of which 7,213,505 (14.8%) are bands. This algorithm produces the first climatology of precipitation bands over the contiguous United States. Banded precipitation occurrence is broadly similar to total precipitation occurrence, with a maximum of 175 hours of banded precipitation annually over the Ohio River Valley. In the warm season, there is a strong diurnal signature associated with convective storm development for both precipitation feature area and total area covered by precipitation, but little diurnal signature in aspect ratio. A strong west-east gradient in both precipitation occurrence and banded precipitation occurrence exist, as areas west of the Rockies receive less frequent precipitation, which is much less likely to be banded. East of the Rockies, precipitation features are banded 30% of the time, versus 10–15% west of the Rockies. Areas downwind of the Great Lakes show prominent late autumn and winter maxima in banded precipitation associated with lake-effect snowbands. Local maxima of banded precipitation percentage occur in the Dakotas and east of the Colorado Rockies during winter. Although banded-precipitation features comprise only 14.8% of all precipitation features, they contribute 21.9% of the annual precipitation occurrence over the contiguous United States

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Preparative isolation, fractionation and chemical characterization of dissolved organics from natural and industrially derived bitumen-influenced groundwaters from the Athabasca River watershed

Recent analytical advances have provided evidence that groundwater affected by oil sands process-affected water (OSPW) is reaching the Athabasca River at one location. To understand and discriminate the toxicological risks posed by OSPW-influenced groundwater relative to groundwaters associated with natural oil sands deposits, these highly complex mixtures of soluble organics were subjected to toxicological characterization through effects directed analysis. A recently-developed preparative fractionation methodology was applied to bitumen-influenced groundwaters and successfully isolated dissolved organics from both industrial and natural sources into three chemically distinct fractions (F1, F2, F3), enabling multiple toxicological assessments. Analytical techniques included electrospray ionization high resolution mass spectrometry (ESI-HRMS), liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QToF/MS), gas chromatography mass spectrometry (GC–MS), and synchronous fluorescence spectroscopy (SFS) methods, which did not reveal obvious differences between sources. Comparisons between fractions within each source consistently demonstrated that F3 contained compounds with greater polarity than F2, which in turn was more polar than F1. The abundance of O2 species was confined to F1, including naphthenic acids often cited for being the primary toxicants within bitumen-influenced waters. This result is consistent with earlier work on aged OSPW, as well as with other extraction methods, suggesting that additional factors other than molecular weight and the presence of acid functionalities play a prominent role in defining compound polarities and toxicities within complex bitumen-derived organic mixtures. The similarities in organic abundances, chemical speciation, aromaticity, and double bond equivalents, concomitant with inorganic mixture similarities, demonstrate the resemblances of bitumen-influenced groundwaters regardless of the source, and reinforce the need for more advanced targeted analyses for source differentiation.This work was funded under the Oil Sands Monitoring Program, and is a contribution to the Program, but does not necessarily reflect the position of the Program. Internal resources from Environment and Climate Change Canada were also used to fund this research

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin