Computational framework for the generation of one-dimensional vascular models accounting for uncertainty in networks extracted from medical images.

One-dimensional (1D) cardiovascular models offer a non-invasive method to answer medical questions, including predictions of wave-reflection, shear stress, functional flow reserve, vascular resistance and compliance. This model type can predict patient-specific outcomes by solving 1D fluid dynamics equations in geometric networks extracted from medical images. However, the inherent uncertainty in in vivo imaging introduces variability in network size and vessel dimensions, affecting haemodynamic predictions. Understanding the influence of variation in image-derived properties is essential to assess the fidelity of model predictions. Numerous programs exist to render three-dimensional surfaces and construct vessel centrelines. Still, there is no exact way to generate vascular trees from the centrelines while accounting for uncertainty in data. This study introduces an innovative framework employing statistical change point analysis to generate labelled trees that encode vessel dimensions and their associated uncertainty from medical images. To test this framework, we explore the impact of uncertainty in 1D haemodynamic predictions in a systemic and pulmonary arterial network. Simulations explore haemodynamic variations resulting from changes in vessel dimensions and segmentation; the latter is achieved by analysing multiple segmentations of the same images. Results demonstrate the importance of accurately defining vessel radii and lengths when generating high-fidelity patient-specific haemodynamics models. KEY POINTS: This study introduces novel algorithms for generating labelled directed trees from medical images, focusing on accurate junction node placement and radius extraction using change points to provide haemodynamic predictions with uncertainty within expected measurement error. Geometric features, such as vessel dimension (length and radius) and network size, significantly impact pressure and flow predictions in both pulmonary and aortic arterial networks. Standardizing networks to a consistent number of vessels is crucial for meaningful comparisons and decreases haemodynamic uncertainty. Change points are valuable to understanding structural transitions in vascular data, providing an automated and efficient way to detect shifts in vessel characteristics and ensure reliable extraction of representative vessel radii.

Computational framework for the generation of one-dimensional vascular models accounting for uncertainty in networks extracted from medical images.

One-dimensional (1D) cardiovascular models offer a non-invasive method to answer medical questions, including predictions of wave-reflection, shear stress, functional flow reserve, vascular resistance, and compliance. This model type can predict patient-specific outcomes by solving 1D fluid dynamics equations in geometric networks extracted from medical images. However, the inherent uncertainty in in-vivo imaging introduces variability in network size and vessel dimensions, affecting hemodynamic predictions. Understanding the influence of variation in image-derived properties is essential to assess the fidelity of model predictions. Numerous programs exist to render three-dimensional surfaces and construct vessel centerlines. Still, there is no exact way to generate vascular trees from the centerlines while accounting for uncertainty in data. This study introduces an innovative framework employing statistical change point analysis to generate labeled trees that encode vessel dimensions and their associated uncertainty from medical images. To test this framework, we explore the impact of uncertainty in 1D hemodynamic predictions in a systemic and pulmonary arterial network. Simulations explore hemodynamic variations resulting from changes in vessel dimensions and segmentation; the latter is achieved by analyzing multiple segmentations of the same images. Results demonstrate the importance of accurately defining vessel radii and lengths when generating high-fidelity patient-specific hemodynamics models.

Evaluation of the moderated-expression and differential configuration hypotheses in the context of "successful" or "noncriminal" psychopathy.

The concept of "successful" psychopathy has intrigued the field, yet relatively little actual science exists to understand what makes those high in psychopathic traits more or less successful, or even what constitutes "success." In the current study, we examined the validity of the moderated expression hypothesis, including an elaborated version that considers differential configuration of psychopathy traits, as accounting for differences in criminal and noncriminal (the most common operationalization of "success") expressions of psychopathy. The latter was conceptualized from the perspective of the triarchic psychopathy model. We recruited a community sample (n = 212) that had been overweighted toward psychopathic personality traits. The triarchic psychopathy domains of boldness, meanness, and disinhibition were modeled as latent constructs based on scores from multiple psychopathy measures. We examined affective processing dysfunction, various executive cognitive deficits, substance misuse, and socioeconomic indicators (income, education) as potential moderators of associations between psychopathy and criminality. We estimated a series of latent regression models in which we tested interaction effects between hypothesized moderators and a latent criminality variable. We found that affective processing dysfunction, substance misuse, and the triarchic psychopathy domain of disinhibition all moderated the association between meanness and criminality, in that the latter association was stronger as these moderators increased in severity. Disinhibition was also moderated by substance misuse and boldness by both personal income and commission errors from a go/no-go task, though in the case of the latter domain, these moderators served as protective factors against criminality. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Development and Validation of MMPI-2-RF Scales for Indexing Triarchic Psychopathy Constructs.

The triarchic model characterizes psychopathy in terms of three distinct dispositional constructs of boldness, meanness, and disinhibition. The model can be operationalized through scales designed specifically to index these domains or by using items from other inventories that provide coverage of related constructs. The present study sought to develop and validate scales for assessing the triarchic model domains using items from the Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF). A consensus rating approach was used to identify items relevant to each triarchic domain, and following psychometric refinement, the resulting MMPI-2-RF-based triarchic scales were evaluated for convergent and discriminant validity in relation to multiple psychopathy-relevant criterion variables in offender and nonoffender samples. Expected convergent and discriminant associations were evident very clearly for the Boldness and Disinhibition scales and somewhat less clearly for the Meanness scale. Moreover, hierarchical regression analyses indicated that all MMPI-2-RF triarchic scales incremented standard MMPI-2-RF scale scores in predicting extant triarchic model scale scores. The widespread use of MMPI-2-RF in clinical and forensic settings provides avenues for both clinical and research applications in contexts where traditional psychopathy measures are less likely to be administered.

Personality domains and traits that predict self-reported aberrant driving behaviours in a southeastern US university sample.

Personality traits are meaningful predictors of many significant life outcomes, including mortality. Several studies have investigated the relationship between specific personality traits and driving behaviours, e.g., aggression and speeding, in an attempt to identify traits associated with elevated crash risk. These studies, while valuable, are limited in that they examine only a narrow range of personality constructs and thus do not necessarily reveal which traits in constellation best predict aberrant driving behaviours. The primary aim of this study was to use a comprehensive measure of personality to investigate which personality traits are most predictive of four types of aberrant driving behaviour (Aggressive Violations, Ordinary Violations, Errors, Lapses) as indicated by the Manchester Driver Behaviour Questionnaire (DBQ). We recruited 285 young adults (67% female) from a university in the southeastern US. They completed self-report questionnaires including the DBQ and the Personality Inventory for DSM-5, which indexes 5 broad personality domains (Antagonism, Detachment, Disinhibition, Negative Affectivity, Psychoticism) and 25 specific trait facets. Confirmatory factor analysis showed adequate evidence for the DBQ internal structure. Structural regression analyses revealed that the personality domains of Antagonism and Negative Affectivity best predicted both Aggressive Violations and Ordinary Violations, whereas the best predictors of both Errors and Lapses were Negative Affectivity, Disinhibition and to a lesser extent Antagonism. A more nuanced analysis of trait facets revealed that Hostility was the best predictor of Aggressive Violations; Risk-taking and Hostility of Ordinary Violations; Irresponsibility, Separation Insecurity and Attention Seeking of Errors; and Perseveration and Irresponsibility of Lapses.

Gender differences in the effects of deployment-related stressors and pre-deployment risk factors on the development of PTSD symptoms in National Guard Soldiers deployed to Iraq and Afghanistan.

OBJECTIVE: Although women in the military are exposed to combat and its aftermath, little is known about whether combat as well as pre-deployment risk/protective factors differentially predict post-deployment PTSD symptoms among women compared to men. The current study assesses the influence of combat-related stressors and pre-deployment risk/protective factors on women's risk of developing PTSD symptoms following deployment relative to men's risk. METHOD: Participants were 801 US National Guard Soldiers (712 men, 89 women) deployed to Iraq or Afghanistan who completed measures of potential risk/protective factors and PTSD symptoms one month before deployment (Time 1) and measures of deployment-related stressors and PTSD symptoms about 2-3 months after returning from deployment (Time 2). RESULTS: Men reported greater exposure to combat situations than women, while women reported greater sexual stressors during deployment than men. Exposure to the aftermath of combat (e.g., witnessing injured/dying people) did not differ by gender. At Time 2, women reported more severe PTSD symptoms and higher rates of probable PTSD than did men. Gender remained a predictor of higher PTSD symptoms after accounting for pre-deployment symptoms, prior interpersonal victimization, and combat related stressors. Gender moderated the association between several risk factors (combat-related stressors, prior interpersonal victimization, lack of unit support and pre-deployment concerns about life/family disruptions) and post-deployment PTSD symptoms. CONCLUSIONS: Elevated PTSD symptoms among female service members were not explained simply by gender differences in pre-deployment or deployment-related risk factors. Combat related stressors, prior interpersonal victimization, and pre-deployment concerns about life and family disruptions during deployment were differentially associated with greater post-deployment PTSD symptoms for women than men.

Antisocial personality disorder: a current review.

The Diagnostic and Statistical Manual of Mental Disorders (DSM 5) classification of antisocial personality disorder (ASPD) describes individuals who engage in repetitive irresponsible, delinquent, and criminal behavior. The diagnosis is highly controversial, with many researchers and clinicians arguing that the category is too heterogeneous, overinclusive, and demonstrates considerable overlap with other disorders. This review focuses on recent studies that have improved our understanding of the characteristics of individuals who fit the ASPD definition by exploring how subtypes differ and how comorbid conditions influence the presentation of ASPD. In addition, we discuss research on the etiology of ASPD that has identified genetic and environmental factors that may contribute to the development and persistence of antisocial behavior, and brain imaging research that has improved our understanding of the relationships between ASPD and other psychopathology. Finally, we discuss promising preliminary research on treatment for this disorder.

Heat of freezing for supercooled water: measurements at atmospheric pressure.

Unlike reversible phase transitions, the amount of heat released upon freezing of a metastable supercooled liquid depends on the degree of supercooling. Although terrestrial supercooled water is ubiquitous and has implications for cloud dynamics and nucleation, measurements of its heat of freezing are scarce. We have performed calorimetric measurements of the heat released by freezing water at atmospheric pressure as a function of supercooling. Our measurements show that the heat of freezing can be considerably below one predicted from a reversible hydrostatic process. Our measurements also indicate that the state of the resulting ice is not fully specified by the final pressure and temperature; the ice is likely to be strained on a variety of scales, implying a higher vapor pressure. This would reduce the vapor gradient between supercooled water and ice in mixed phase atmospheric clouds.

Sex reversal in zebrafish fancl mutants is caused by Tp53-mediated germ cell apoptosis.

The molecular genetic mechanisms of sex determination are not known for most vertebrates, including zebrafish. We identified a mutation in the zebrafish fancl gene that causes homozygous mutants to develop as fertile males due to female-to-male sex reversal. Fancl is a member of the Fanconi Anemia/BRCA DNA repair pathway. Experiments showed that zebrafish fancl was expressed in developing germ cells in bipotential gonads at the critical time of sexual fate determination. Caspase-3 immunoassays revealed increased germ cell apoptosis in fancl mutants that compromised oocyte survival. In the absence of oocytes surviving through meiosis, somatic cells of mutant gonads did not maintain expression of the ovary gene cyp19a1a and did not down-regulate expression of the early testis gene amh; consequently, gonads masculinized and became testes. Remarkably, results showed that the introduction of a tp53 (p53) mutation into fancl mutants rescued the sex-reversal phenotype by reducing germ cell apoptosis and, thus, allowed fancl mutants to become fertile females. Our results show that Fancl function is not essential for spermatogonia and oogonia to become sperm or mature oocytes, but instead suggest that Fancl function is involved in the survival of developing oocytes through meiosis. This work reveals that Tp53-mediated germ cell apoptosis induces sex reversal after the mutation of a DNA-repair pathway gene by compromising the survival of oocytes and suggests the existence of an oocyte-derived signal that biases gonad fate towards the female developmental pathway and thereby controls zebrafish sex determination.