scholarly journals OC-0161 Validation of clinical/dosimetric/genetic risk factor models for late RT-induced rectal bleeding

2019 ◽  
Vol 133 ◽  
pp. S78
Author(s):  
T. Rancati ◽  
P. Seibold ◽  
A. Webb ◽  
J. Chang-Claude ◽  
A. Cicchetti ◽  
...  
Keyword(s):  
Risk Factor ◽  
Rectal Bleeding ◽  
Genetic Risk ◽  
Factor Models ◽  
Genetic Risk Factor ◽  
Risk Factor Models

A Mutation in Plasma Platelet-activating Factor Acetylhydrolase (Val279Phe) Is a Genetic Risk Factor for Cerebral Hemorrhage but not for Hypertension

1998 ◽  
Vol 80 (09) ◽  
pp. 372-375 ◽  
Author(s):  
Hidemi Yoshida ◽  
Tadaatsu Imaizumi ◽  
Koji Fujimoto ◽  
Hiroyuki Itaya ◽  
Makoto Hiramoto ◽  
...  
Keyword(s):  
Risk Factor ◽  
Genetic Risk ◽  
Platelet Activating Factor ◽  
Vascular Diseases ◽  
Genetic Risk Factor ◽  
Brain Hemorrhage ◽  
Platelet Activating Factor Acetylhydrolase ◽  
Paf Acetylhydrolase ◽  
Polymerase Chain ◽  
The Difference

SummaryPlatelet-activating factor (PAF) acetylhydrolase is an enzyme that inactivates PAF. Deficiency of this enzyme is caused by a missense mutation in the gene. We previously found a higher prevalence of this mutation in patients with ischemic stroke. This fact suggests that the mutation might enhance the risk for stroke through its association with hypertension. We have addressed this hypothesis by analyzing the prevalence of the mutation in hypertension. We studied 138 patients with essential hypertension, 99 patients with brain hemorrhage, and 270 healthy controls. Genomic DNA was analyzed for the mutant allele by the polymerase-chain reaction. The prevalence of the mutation was 29.3% (27.4% heterozygotes and 1.9% homozygotes) in controls and 36.2% in hypertensives and the difference was not significant. The prevalence in patients with brain hemorrhage was significantly higher than the control: 32.6% heterozygotes and 6.1% homozygotes (p <0.05). PAF acetylhydrolase deficiency may be a genetic risk factor for vascular diseases.

scholarly journals 170 Psoriasis and coronary artery disease share a genetic risk factor through IFIH1

2021 ◽  
Vol 141 (5) ◽  
pp. S30
Author(s):  
M.T. Patrick ◽  
S. Sreeskandarajan ◽  
Q. Li ◽  
N. Mehta ◽  
J.E. Gudjonsson ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Risk Factor ◽  
Coronary Artery ◽  
Genetic Risk ◽  
Genetic Risk Factor ◽  
Artery Disease

The Contributions of Propensity, Delinquent Peers, Low Parental Supervision, and Empathy to the Emergence of Antisocial Behavior in Childhood and Adolescence: Testing Developmental Path Models Combining Psychological- and Sociological-Criminological Approaches

2020 ◽  
pp. 1-14
Author(s):  
Susanne Wallner ◽  
Stemmler Mark ◽  
Jost Reinecke
Keyword(s):  
Risk Factor ◽  
Antisocial Behavior ◽  
Action Theory ◽  
Cumulative Risk ◽  
Factor Models ◽  
Individual Risk ◽  
Parental Supervision ◽  
Childhood And Adolescence ◽  
Path Models ◽  
Risk Factor Models

Psychological- and sociological-criminological research refers to, for example, cumulative risk factor models (e.g., Lösel & Bender, 2003) and Situational Action Theory (SAT; e.g., Wikström, 2006). The German longitudinal study “Chances and Risks in the Life Course“ (research project A2, Collaborative Research Center 882; e.g., Reinecke, Stemmler, & Wittenberg, 2016) focuses upon the development of antisocial behavior from a psychological and sociological point of view. Two-wave panel data of two cohorts (children and adolescents) were utilized to test the power of developmental path models investigating the development of antisocial behavior. Individual risk seems to have both direct and indirect influences on antisocial behavior, supporting the ideas of risk factor models; antisocial behavior might be the outcome of the interaction between propensity and criminogenic exposure, so there is evidence for SAT. Additionally, empathy seems to be related to both propensity and low parental supervision. Implications for the study of antisocial behavior in childhood and adolescence are discussed in line with developmental criminology.

scholarly journals Ordering risk bounds in factor models

2018 ◽  
Vol 6 (1) ◽  
pp. 259-287 ◽  
Author(s):  
Jonathan Ansari ◽  
Ludger Rüschendorf
Keyword(s):  
Risk Factor ◽  
Systemic Risk ◽  
Factor Models ◽  
Worst Case ◽  
Sign Changes ◽  
Risk Factor Models ◽  
Risk Bounds ◽  
Derivatives Of ◽  
Dependence Structures

AbstractConditionally comonotonic risk vectors have been proved in [4] to yield worst case dependence structures maximizing the risk of the portfolio sum in partially specified risk factor models. In this paper we investigate the question how risk bounds depend on the specification of the pairwise copulas of the risk components Xiwith the systemic risk factor. As basic toolwe introduce a new ordering based on sign changes of the derivatives of copulas. This together with discretization by n-grids and the theory of supermodular transfers allows us to derive concrete ordering criteria for the maximal risks.

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