Automatic detection of Crohn's disease using quantified motility in magnetic resonance enterography : initial experiences

Publisher Copyright: © 2021 The AuthorsAIM: To report initial experiences of automatic detection of Crohn's disease (CD) using quantified motility in magnetic resonance enterography (MRE). MATERIALS AND METHODS: From 302 patients, three datasets with roughly equal proportions of CD and non-CD cases with various illnesses were drawn for testing and neural network training and validation. All datasets had unique MRE parameter configurations and were performed in free breathing. Nine neural networks were devised for automatic generation of three different regions of interests (ROI): small bowel, all bowel, and non-bowel. Additionally, a full-image ROI was tested. The motility in an MRE series was quantified via a registration procedure, which, accompanied with given ROIs, resulted in three motility indices (MI). A subset of the indices was used as an input for a binary logistic regression classifier, which predicted whether the MRE series represented CD. RESULTS: The highest mean area under the curve (AUC) score, 0.78, was reached using the full-image ROI and with the dataset with the highest cine series length. The best AUC scores for the other two datasets were only 0.54 and 0.49. CONCLUSION: The automatic system was able to detect CD in the group of MRE studies with lower temporal resolution and longer cine series showing potential in primary bowel disorder diagnostics. Larger ROI selections and utilising all available cine series for motility registration yielded slight performance improvements. (c) 2021 The Authors. Published by Elsevier Ltd on behalf of The Royal College of Radiologists. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/ 4.0/).Peer reviewe

Porosities and dimensions of measures

We introduce a concept of porosity for measures and study relations between dimensions and porosities for two classes of measures: measures on $R^n$ which satisfy the doubling condition and strongly porous measures on $R$.Comment: Jarvenpaa = J\"arvenp\"a\"

Modelo de regresión logística para la comparación de series climatológicas registradas en la cuenca del río Torbes, Venezuela

El objetivo de esta investigación fue evaluar series de precipitación mensual mediante regresión logística multinominal para comparar la tendencia, estacionalidad y presencia de observaciones atípicas en series de precipitación mensual. Para ello se utilizaron datos de la estación meteorológica San Cristóbal del estado Táchira y series simuladas mediante modelos de eventos extremos: Pearson tipo III, Gumbel tipo I, Log-Normal y Log-Pearson tipo III. En el análisis de la tendencia y estacionalidad se utilizaron gráficos de saturación de la varianza, para ver observaciones atípicas se utilizó la distancia de Mahalanobis (D2). Para el ajuste de modelos de eventos extremos se utilizó la estimación de máxima verosimilitud y el ajuste de densidades. Se evidenció una distribución asimétrica de las precipitaciones con una discontinuidad en el periodo 1973-1983, asociada a una alta variabilidad (75,75%) como consecuencia de la presencia de observaciones atípicas causadas por errores en los registros. También, se detectaron observaciones atípicas distribuidas en la época lluviosa, asociadas al mes de agosto de 1960, junio de 1984, julio de 1985 y de 1989. Por otro lado, la precipitación mensual se ajustó a una distribución Pearson tipo III. La regresión logística sugirió que la única variable relacionada con la distribución teórica de la serie fue la precipitación. La simulación de MonteCarlo evidenció consistencia en los estimadores de máxima verosimilitud del modelo logístico en el análisis de la precipitación mensual. Finalmente, los resultados mostraron que las metodologías consideradas son una poderosa herramienta para el estudio de la tendencia y homogeneidad de la precipitación mensual, detección de outliers multivariados y la comparación de series de precipitación mensual, respectivamente.</p

Influence of 2 '-fucosyllactose and galacto-oligosaccharides on the growth and adhesion of Streptococcus mutans

Human milk oligosaccharides, such as 2 '-fucosyllactose (2 '-FL), and galacto-oligosaccharides (GOS), a prebiotic carbohydrate mixture, are being increasingly added to infant formulas, necessitating the understanding of their impact on the oral microbiota. Here, for the first time, the effects of 2 '-FL and GOS on the planktonic growth and adhesion characteristics of the caries-associated oral pathogenStreptococcus mutanswere assessed, and the results were compared against the effects of xylitol, lactose and glucose. There were differences inS. mutansgrowth between 2 '-FL and GOS. None of the threeS. mutansstrains grew with 2 '-FL, while they all grew with GOS as well as lactose and glucose. Xylitol inhibitedS. mutansgrowth. The adhesion ofS. mutansCI 2366 to saliva-coated hydroxyapatite was reduced by 2 '-FL and GOS. Exopolysaccharide-mediated adhesion ofS. mutansDSM 20523 to a glass surface was decreased with 2 '-FL, GOS and lactose, and the adhesion of strain CI 2366 strain was reduced only by GOS. Unlike GOS, 2 '-FL did not support the growth of anyS. mutansstrain. Neither 2 '-FL nor GOS enhanced the adhesive properties of theS. mutansstrains, but they inhibited some of the tested strains. Thus, the cariogenic tendency may vary between infant formulas containing different types of oligosaccharides

Comparison of Manual Cross-Sectional Measurements and Automatic Volumetry of the Corpus Callosum, and Their Clinical Impact: A Study on Type 1 Diabetes and Healthy Controls

Manually measured callosal area and automatically segmented are interchangeable. The association seen between callosal size with cerebral microbleeds and insulin resistance is indicative of small vessel disease pathology in diabetes type 1

Cerebral small vessel disease genomics and its implications across the lifespan

White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.Peer reviewe

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Meta-analysis of 375,000 individuals identifies 38 susceptibility loci for migraine

Migraine is a debilitating neurological disorder affecting around one in seven people worldwide, but its molecular mechanisms remain poorly understood. There is some debate about whether migraine is a disease of vascular dysfunction or a result of neuronal dysfunction with secondary vascular changes. Genome-wide association (GWA) studies have thus far identified 13 independent loci associated with migraine. To identify new susceptibility loci, we carried out a genetic study of migraine on 59,674 affected subjects and 316,078 controls from 22 GWA studies. We identified 44 independent single-nucleotide polymorphisms (SNPs) significantly associated with migraine risk (P < 5 × 10−8) that mapped to 38 distinct genomic loci, including 28 loci not previously reported and a locus that to our knowledge is the first to be identified on chromosome X. In subsequent computational analyses, the identified loci showed enrichment for genes expressed in vascular and smooth muscle tissues, consistent with a predominant theory of migraine that highlights vascular etiologies