Hybrid Pathwise Sensitivity Methods for Discrete Stochastic Models of Chemical Reaction Systems

Stochastic models are often used to help understand the behavior of intracellular biochemical processes. The most common such models are continuous time Markov chains (CTMCs). Parametric sensitivities, which are derivatives of expectations of model output quantities with respect to model parameters, are useful in this setting for a variety of applications. In this paper, we introduce a class of hybrid pathwise differentiation methods for the numerical estimation of parametric sensitivities. The new hybrid methods combine elements from the three main classes of procedures for sensitivity estimation, and have a number of desirable qualities. First, the new methods are unbiased for a broad class of problems. Second, the methods are applicable to nearly any physically relevant biochemical CTMC model. Third, and as we demonstrate on several numerical examples, the new methods are quite efficient, particularly if one wishes to estimate the full gradient of parametric sensitivities. The methods are rather intuitive and utilize the multilevel Monte Carlo philosophy of splitting an expectation into separate parts and handling each in an efficient manner.Comment: 30 pages. The numerical example section has been extensively rewritte

Intimate Partner Violence and the Victim-Offender Overlap

Objectives: Examine the prevalence and correlates of intimate partner violence (IPV) victimization and offending, as well as the overlap of these experiences. Method: Data from wave 4 of the National Longitudinal Study of Adolescent Health were analyzed to examine IPV among adults ages 24 to 33. A multinomial logistic regression model was estimated to determine whether the correlates of IPV vary across victims, perpetrators, and victim-perpetrators. Results: Approximately 20% of respondents reported some IPV involvement in the past year, one-third of whom reported victimization and perpetration. The victim-offender overlap was observed for males and females across various measures of IPV. Bivariate correlations suggest victimization and perpetration have common correlates. Multivariate analysis, however, reveals considerable differences once we distinguish between victims, offenders, and victim-offenders and control for other variables. Perpetrators and victim-perpetrators were more likely to live with a nonspouse partner; feel isolated; display negative temperaments; and report substance use problems. “Victims only” were more likely to live with children and have lower household incomes. Conclusions: The victim-offender overlap exists for IPV across a variety of measures. Though perpetrators and victim-perpetrators have similar characteristics, those who are victims only appear distinctly different. We discuss the implications for theory, policy, and research

Neighborhoods and Intimate Partner Violence Against Women: The Direct and Interactive Effects of Social Ties and Collective Efficacy

This study examines the impact of several indicators of neighborhood social ties (e.g., residents’ interactions with each other; residents’ ability to recognize outsiders) on intimate partner violence (IPV) against women as well as whether neighborhood collective efficacy’s impact on IPV is contingent upon such ties. This study used data from 4,151 women (46% Latina, 33% African American, 17% Caucasian, on average 32 years old) in 80 neighborhoods from the Project on Human Development in Chicago Neighborhoods. We estimated a series of random effects hierarchical Bernoulli models to assess the main and interactive effects of neighborhood social ties and collective efficacy on minor and severe forms of IPV against women. Results indicate that certain neighborhood social ties are associated with higher rates of minor forms of IPV against women (but not severe forms of IPV), and collective efficacy does not appear to influence IPV against women, regardless of the level of individual or neighborhood social ties. Unlike street crime, collective efficacy does not significantly reduce IPV against women, even in neighborhoods with strong social ties that may facilitate awareness of the violence. In fact, perpetrators of minor IPV may enjoy some protective benefit in communities with social ties that make neighbors hesitant to intervene in what some might perceive as “private matters.

Intimate partner violence and the overlap of perpetration and victimization: Considering the influence of physical, sexual, and emotional abuse in childhood

Using data from Wave 4 of the National Longitudinal Study of Adolescent to Adult Health, this study examined the independent relationship of childhood maltreatment type (emotional, sexual, physical) on IPV victimization and perpetration; then mutually exclusive categories of IPV involvement (victimization, perpetration, and victimization/perpetration) were investigated. IPV victimization and perpetration were assessed using items from the revised Conflict Tactics Scales. A series of binary regression models and multinomial regression models were estimated. Models were stratified across gender. Results uncovered significant relationships between child physical abuse and IPV victimization as well as IPV perpetration for males and females, but this effect was reduced when emotional maltreatment was added to the model. When IPV victimization/perpetration was considered, maltreatment effects changed. For males, physical maltreatment remained significantly related to victimization only and physical, sexual, and emotional maltreatment were related to victimization/perpetration. For females, physical maltreatment remained significantly related to IPV victimization only and emotional maltreatment was related to perpetration only and to victimization/perpetration. Screening and intervention for maltreatment, including emotional maltreatment, among children as well as adults with IPV histories may be important to preventing first IPV experiences and stemming current involvement

Automatic protein structure solution from weak X-ray data

Biophysical Structural Chemistr

When Victims Refuse and Prosecutors Decline: Examining Exceptional Clearance in Sexual Assault Cases

This study examines the predictors of sexual assault case clearance, with a focus on arrest and two types of exceptional clearance: victim refusal to cooperate and prosecutorial declination to prosecute. Using National Incident Based Reporting System (NIBRS) data on crime incidents that contain a sexual offense (N = 21,977), we estimated a multinomial regression model to examine the predictors of different clearance types for cases of sexual assault. Results indicated that the likelihood of victim refusal decreases in cases perpetrated by strangers, involving victim injury, occurring in public, and involving multiple offenses. A similar pattern of findings was observed for the decision to decline to prosecute a case. In addition, prosecutors are more likely to decline to prosecute cases with male victims and older victims. We discuss the implications of our findings and directions for future research

A new MR-SAD algorithm for the automatic building of protein models from low-resolution X-ray data and a poor starting model

Determining macromolecular structures from X-ray data with resolution worse than 3 Å remains a challenge. Even if a related starting model is available, its incompleteness or its bias together with a low observation-to-parameter ratio can render the process unsuccessful or very time-consuming. Yet, many biologically important macromolecules, especially large macromolecular assemblies, membrane proteins and receptors, tend to provide crystals that diffract to low resolution. A new algorithm to tackle this problem is presented that uses a multivariate function to simultaneously exploit information from both an initial partial model and low-resolution single-wavelength anomalous diffraction data. The new approach has been used for six challenging structure determinations, including the crystal structures of membrane proteins and macromolecular complexes that have evaded experts using other methods, and large structures from a 3.0 Å resolution F1-ATPase data set and a 4.5 Å resolution SecYEG–SecA complex data set. All of the models were automatically built by the method to Rfree values of between 28.9 and 39.9% and were free from the initial model bias

Automating tasks in protein structure determination with the Clipper Python module

Scripting programming languages provide the fastest means of prototyping complex functionality. Those with a syntax and grammar resembling human language also greatly enhance the maintainability of the produced source code. Furthermore, the combination of a powerful, machine-independent scripting language with binary libraries tailored for each computer architecture allows programs to break free from the tight boundaries of efficiency traditionally associated with scripts. In the present work, we describe how an efficient C++ crystallographic library such as Clipper can be wrapped, adapted and generalised for use in both crystallographic and electron cryo-microscopy applications, scripted with the Python language. We shall also place an emphasis on best practices in automation, illustrating how this can be achieved with this new Python module. This article is protected by copyright. All rights reserved

Legionella DotM structure reveals a role in effector recruiting to the Type 4B secretion system

Legionella pneumophila, a causative agent of pneumonia, utilizes the Type 4B secretion (T4BS) system to translocate over 300 effectors into the host cell during infection. T4BS systems are encoded by a large gene cluster termed dot/icm, three components of which, DotL, DotM, and DotN, form the “coupling complex”, which serves as a platform for recruitment of effector proteins. One class of effectors includes proteins containing Glu-rich/E-block sequences at their C terminus. However, the protein or region of the coupling complex mediating recruitment of such effectors is unknown. Here we present the crystal structure of DotM. This all alpha-helical structure exhibits patches of positively charged residues. We show that these regions form binding sites for acidic Glu-rich peptides and that mutants targeting these patches are defective in vivo in the translocation of acidic Glu-rich motif-containing effectors. We conclude that DotM forms the interacting surface for recruitment of acidic Glu-rich motif-containing Legionella effectors

Structure-function analysis of the <em>Fusarium oxysporum</em> Avr2 effector allows uncoupling of its immune-suppressing activity from recognition

Plant pathogens employ effector proteins to manipulate their hosts. Fusarium oxysporum f. sp. lycopersici (Fol), the causal agent of tomato wilt disease, produces effector protein Avr2. Besides being a virulence factor, Avr2 triggers immunity in I-2 carrying tomato (Solanum lycopersicum). Fol strains that evade I-2 recognition carry point mutations in Avr2 (e.g. Avr2R45H), but retain full virulence. Here we investigate the virulence function of Avr2 and determine its crystal structure. Transgenic tomato and Arabidopsis expressing either wild-type ΔspAvr2 (deleted signal-peptide) or the ΔspAvr2R45H variant become hypersusceptible to fungal, and even bacterial infections, suggesting that Avr2 targets a conserved defense mechanism. Indeed, Avr2 transgenic plants are attenuated in immunity-related readouts, including flg22-induced growth inhibition, ROS production and callose deposition. The crystal structure of Avr2 reveals that the protein shares intriguing structural similarity to ToxA from the wheat pathogen Pyrenophora tritici-repentis and to TRAF proteins. The I-2 resistance-breaking Avr2V41M, Avr2R45H and Avr2R46P variants cluster on a surface-presented loop. Structure-guided mutagenesis enabled uncoupling of virulence from I-2-mediated recognition. We conclude that I-2-mediated recognition is not based on monitoring Avr2 virulence activity, which includes suppression of immune responses via an evolutionarily conserved effector target, but by recognition of a distinct epitope