A MS-lesion pattern discrimination plot based on geostatistics

Introduction A geostatistical approach to characterize MS-lesion patterns based on their geometrical properties is presented. Methods A dataset of 259 binary MS-lesion masks in MNI space was subjected to directional variography. A model function was fit to express the observed spatial variability in x, y, z directions by the geostatistical parameters Range and Sill. Results Parameters Range and Sill correlate with MS-lesion pattern surface complexity and total lesion volume. A scatter plot of ln(Range) versus ln(Sill), classified by pattern anisotropy, enables a consistent and clearly arranged presentation of MS-lesion patterns based on geometry: the so-called MS-Lesion Pattern Discrimination Plot. Conclusions The geostatistical approach and the graphical representation of results are considered efficient exploratory data analysis tools for cross-sectional, follow-up, and medication impact analysis

A R-Script for Generating Multiple Sclerosis Lesion Pattern Discrimination Plots

Càlcul estadístic R; Geoestadística; Esclerosi múltipleCálculo estadístico R; Geoestadística; Esclerosis múltipleR statistical computing; Geostatistics; Multiple sclerosisOne significant characteristic of Multiple Sclerosis (MS), a chronic inflammatory demyelinating disease of the central nervous system, is the evolution of highly variable patterns of white matter lesions. Based on geostatistical metrics, the MS-Lesion Pattern Discrimination Plot reduces complex three- and four-dimensional configurations of MS-White Matter Lesions to a well-arranged and standardized two-dimensional plot that facilitates follow-up, cross-sectional and medication impact analysis. Here, we present a script that generates the MS-Lesion Pattern Discrimination Plot, using the widespread statistical computing environment R. Input data to the script are Nifti-1 or Analyze-7.5 files with individual MS-White Matter Lesion masks in Montreal Normal Brain geometry. The MS-Lesion Pattern Discrimination Plot, variogram plots and associated fitting statistics are output to the R console and exported to standard graphics and text files. Besides reviewing relevant geostatistical basics and commenting on implementation details for smooth customization and extension, the paper guides through generating MS-Lesion Pattern Discrimination Plots using publicly available synthetic MS-Lesion patterns. The paper is accompanied by the R script LDPgenerator.r, a small sample data set and associated graphics for comparison

Evaluation of Performance Measures for Classifiers Comparison

The selection of the best classification algorithm for a given dataset is a very widespread problem, occuring each time one has to choose a classifier to solve a real-world problem. It is also a complex task with many important methodological decisions to make. Among those, one of the most crucial is the choice of an appropriate measure in order to properly assess the classification performance and rank the algorithms. In this article, we focus on this specific task. We present the most popular measures and compare their behavior through discrimination plots. We then discuss their properties from a more theoretical perspective. It turns out several of them are equivalent for classifiers comparison purposes. Futhermore. they can also lead to interpretation problems. Among the numerous measures proposed over the years, it appears that the classical overall success rate and marginal rates are the more suitable for classifier comparison task

The mtDNA 15497 G/A polymorphism in cytochrome b in severe obese subjects from Southern Italy.

Background and aim: A large number of mitochondrial DNA (mtDNA) mutations have been implicated in degenerative diseases and aging. The aim of this study was to evaluate whether the 15497 G/A mtDNA polymorphism (G251S) in the cytochrome b subunit of respiratory complex III, which has been associated with obesity-related variables and lipid metabolism in a Japanese population, is associated with severe obesity also in adult Caucasians from southern Italy. Methods and results: Unrelated severely obese patients (n Z 317; BMI > 40 kg/m2) and controls (n Z 217; BMI < 25 kg/m2) from Southern Italy were genotyped by allelic discrimination TaqMan assay for the 15497 G/A mtDNA polymorphism. In obese patients fasting serum total cholesterol, triglycerides, HDL-cholesterol and glucose were measured enzymatically and sitting blood pressure and heart rate were also collected. Mean levels of total cholesterol, triglycerides and glucose were below the upper reference limit for healthy subjects. Female obese subjects showed lower levels of blood pressure and heart rate and higher levels of HDL cholesterol than male obese patients (P < 0.001). All the control subjects and 315/317 severely obese patients were homozygous for the G allele (wild type), whereas only 2/317, were females homozygous for the A allele. Conclusions: The mtDNA 15497 G/A polymorphism in cytochrome b was present in 0.6% obese subjects, two females whose lipid parameters and BMI were similar to those of the overall group. Therefore, this mutation may appear to contribute in rare instances to severe obesity but does not explain the majority of cases in our population. A more extensive genetic haplogroup characterization is required to identify associations to obesity in Caucasians

Attention Narrows Position Tuning of Population Responses in V1

SummaryWhen attention is directed to a region of space, visual resolution at that location flexibly adapts, becoming sharper to resolve fine-scale details or coarser to reflect large-scale texture and surface properties [1]. By what mechanism does attention improve spatial resolution? An improved signal-to-noise ratio (SNR) at the attended location contributes [2], because of retinotopically specific signal gain [3–10]. Additionally, attention could sharpen position tuning at the neural population level, so that adjacent objects activate more distinct regions of the visual cortex. A dual mechanism involving both signal gain and sharpened position tuning would be highly efficient at improving visual resolution, but there is no direct evidence that attention can narrow the position tuning of population responses. Here, we compared the spatial spread of the fMRI BOLD response for attended versus ignored stimuli. The activity produced by adjacent stimuli overlapped less when subjects were attending at their locations versus attending elsewhere, despite a stronger peak response with attention. Our results show that even as early as primary visual cortex (V1), spatially directed attention narrows the tuning of population-coded position representations

A novel approach to neutron dosimetry

Purpose: Having been overlooked for many years, research is now starting to take into account the directional distribution of neutron workplace fields. Existing neutron dosimetry instrumentation does not account for this directional distribution, resulting in conservative estimates of dose in neutron workplace fields (by around a factor of 2, although this is heavily dependent on the type of field). This conservatism could influence epidemiological studies on the health effects of radiation exposure. This paper reports on the development of an instrument which can estimate the effective dose of a neutron field, accounting for both the direction and the energy distribution. Methods: A 6Li-loaded scintillator was used to perform neutron assays at a number of locations in a 20 × 20 × 17.5 cm3 water phantom. The variation in thermal and fast neutron response to different energies and field directions was exploited. The modeled response of the instrument to various neutron fields was used to train an artificial neural network (ANN) to learn the effective dose and ambient dose equivalent of these fields. All experimental data published in this work were measured at the National Physical Laboratory (UK). Results: Experimental results were obtained for a number of radionuclide source based neutron fields to test the performance of the system. The results of experimental neutron assays at 25 locations in a water phantom were fed into the trained ANN. A correlation between neutron counting rates in the phantom and neutron fluence rates was experimentally found to provide dose rate estimates. A radionuclide source behind shadow cone was used to create a more complex field in terms of energy and direction. For all fields, the resulting estimates of effective dose rate were within 45% or better of their calculated values, regardless of energy distribution or direction for measurement times greater than 25 min. Conclusions: This work presents a novel, real-time, approach to workplace neutron dosimetry. It is believed that in the research presented in this paper, for the first time, a single instrument has been able to estimate effective dose

Stewarding 2,4-D- and dicamba- based weed control technologies in cotton and soybean production systems

Distinguishing 2,4-D and dicamba herbicide formulations in cotton and soybean tissue is challenging in regulation of crop injury from these herbicides. Additionally, stewardship of 2,4-D and dicamba technologies is important to maximize their longevity and efficacy. Research was conducted to (1) characterize cotton and soybean response to various formulations of 2,4-D or dicamba with or without glyphosate, (2) develop a method for classifying these formulations in crop tissue, and (3) optimize use of chloroacetamide herbicides in dicamba systems for mitigation of selection pressure on dicamba. Formulations evaluated include dicamba diglycolamine (DGA), dimethylamine (DMA), N,N-Bis-(3-aminopropyl) methylamine (BAPMA), and DGA plus potassium acetate (KAc); and 2,4-D DMA, acid, isooctyl ester (ESTER), and choline. Weed management by the chloroacetamides s-metolachlor and acetochlor was evaluated with applications preemergence (PRE), early postemergence (EP), late postemergence (LP), PRE followed by (fb) EP, PRE fb LP, and EP fb LP. Cotton and soybean response differed by 2,4-D and dicamba formulation, and glyphosate presence. Cotton yield was reduced by 200 to 500 kg ha-1 following exposure to 2,4-D choline or DMA relative to acid or ESTER. Glyphosate presence led to a reduction in cotton and soybean yield of 377 and 572 kg ha-1, respectively. Exposure to dicamba DMA resulted in a 263 kg ha-1 reduction in soybean yield relative to dicamba DGA, and glyphosate presence reduced yield by 439 and 246 kg ha-1 in cotton and soybeans, respectively. Chemometric analyses generated models capable of up to 85% accuracy in identifying dicamba formulation in cotton and soybean tissue, and up to 80% accuracy in identifying 2,4-D formulation. Split chloroacetamide applications improved cotton yield up to 60%, reduced weed densities up to 90%, and improved control up to 56% relative to single applications. Cotton height was reduced up to 23% if a single chloroacetamide application was made. Soybean yield was maximized following any chloroacetamide application timing except PRE alone, and weed control was reduced up to 31% following single chloroacetamide application relative to split applications. These results will aid regulatory bodies in managing use of new weed control technologies and will assist producers in stewarding these new technologies

A simple and rapid approach for screening of SARS-coronavirus genotypes: an evaluation study

BACKGROUND: The Severe Acute Respiratory Syndrome (SARS) was a newly emerged infectious disease which caused a global epidemic in 2002–2003. Sequence analysis of SARS-coronavirus isolates revealed that specific genotypes predominated at different periods of the epidemic. This information can be used as a footprint for tracing the epidemiology of infections and monitor viral evolution. However, direct sequencing analysis of a large number of clinical samples is cumbersome and time consuming. We present here a simple and rapid assay for the screening of SARS-coronavirus genotypes based on the use of fluorogenic oligonucleotide probes for allelic discrimination. METHODS: Thirty SARS patients were recruited. Allelic discrimination assays were developed based on the use of fluorogenic oligonucleotide probes (TaqMan). Genotyping of the SARS-coronavirus isolates obtained from these patients were carried out by the allelic discrimination assays and confirmed by direct sequencing. RESULTS: Genotyping based on the allelic discrimination assays were fully concordant with direct sequencing. All of the 30 SARS-coronavirus genotypes studied were characteristic of genotypes previously documented to be associated with the latter part of the epidemic. Seven of the isolates contained a previously reported major deletion but in patients not epidemiologically related to the previously studied cohort. CONCLUSION: We have developed a simple and accurate method for the characterization and screening of SARS-coronavirus genotypes. It is a promising tool for the study of epidemiological relationships between documented cases during an outbreak

Development and Validation of eRADAR: A Tool Using EHR Data to Detect Unrecognized Dementia.

ObjectivesEarly recognition of dementia would allow patients and their families to receive care earlier in the disease process, potentially improving care management and patient outcomes, yet nearly half of patients with dementia are undiagnosed. Our aim was to develop and validate an electronic health record (EHR)-based tool to help detect patients with unrecognized dementia (EHR Risk of Alzheimer's and Dementia Assessment Rule [eRADAR]).DesignRetrospective cohort study.SettingKaiser Permanente Washington (KPWA), an integrated healthcare delivery system.ParticipantsA total of 16 665 visits among 4330 participants in the Adult Changes in Thought (ACT) study, who undergo a comprehensive process to detect and diagnose dementia every 2 years and have linked KPWA EHR data, divided into development (70%) and validation (30%) samples.MeasurementsEHR predictors included demographics, medical diagnoses, vital signs, healthcare utilization, and medications within the previous 2 years. Unrecognized dementia was defined as detection in ACT before documentation in the KPWA EHR (ie, lack of dementia or memory loss diagnosis codes or dementia medication fills).ResultsOverall, 1015 ACT visits resulted in a diagnosis of incident dementia, of which 498 (49%) were unrecognized in the KPWA EHR. The final 31-predictor model included markers of dementia-related symptoms (eg, psychosis diagnoses, antidepressant fills), healthcare utilization pattern (eg, emergency department visits), and dementia risk factors (eg, cerebrovascular disease, diabetes). Discrimination was good in the development (C statistic = .78; 95% confidence interval [CI] = .76-.81) and validation (C statistic = .81; 95% CI = .78-.84) samples, and calibration was good based on plots of predicted vs observed risk. If patients with scores in the top 5% were flagged for additional evaluation, we estimate that 1 in 6 would have dementia.ConclusionThe eRADAR tool uses existing EHR data to detect patients with good accuracy who may have unrecognized dementia. J Am Geriatr Soc 68:103-111, 2019

Across-Line SNP Association Study for Direct and Associative Effects on Feather Damage in Laying Hens

An association study between SNP markers and feather condition score on the back, rump and belly of laying hens was performed. Feather condition score is a measure of feather damage, which has been shown to be closely related to feather pecking behaviour in hens housed in groups. A population of 662 hens was genotyped for 1536 SNPs of which 1022 could be used for the association study. The analysis was conducted across 9 different lines of White Leghorn and Rhode Island Red origin. Across lines linkage disequilibrium is conserved at shorter distances than within lines; therefore, SNPs significantly associated with feather condition score across lines are expected to be closer to the functional mutations. The SNPs that had a significant across-line effect but did not show significant SNP-by-line interaction were identified, to test that the association was consistent across lines. Both the direct effect of the individual’s genotype on its plumage condition, and the associative effect of the genotype of the cage mates on the individual’s plumage condition were analysed. The direct genetic effect can be considered as the susceptibility to be pecked at, whereas the associative genetic effect can be interpreted as the propensity to perform feather pecking. Finally, 11 significant associations between SNPs and behavioural traits were detected in the direct model, and 81 in the associative model. A role of the gene for the serotonin receptor 2C (HTR2C) on chromosome 4 was found. This supports existing evidence of a prominent involvement of the serotonergic system in the modulation of this behavioural disorder in laying hens. The genes for IL9, IL4, CCL4 and NFKB were found to be associated to plumage condition, revealing relationships between the immune system and behaviour