The SMFA program for quantum chemistry calculations on large molecules

SMFA is a general program package for performing quantum chemistry calculations on large molecules, using an energy-based fragmentation approach. The program can calculate electronic energies, energy gradients and second derivatives; perform geometry optimization; find first order saddle points (transition states); perform energy optimized scans along a user-defined path; and evaluate various molecular properties. The program can use any of the following quantum chemistry packages: GAMESS(US), GAUSSIAN, NWChem and Q-Chem. In addition, SMFA provides a number of utility programs that, inter alia, calculate vibrational frequencies and infrared spectra with isotopic substitutions, the electrostatic potential on the solvent-accessible-surface, and isodesmic and higher order near-iso-energetic reaction schemes. Calculations of the electronic energy and related properties can be carried out using a scheme that provides a computation time that is linearly dependent on the size of the molecule or, if the user has enough processing units available, in a walltime that is independent of the size of the molecule

A Unified Framework Integrating Parent-of-Origin Effects for Association Study

Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting is related to several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we generalize the natural and orthogonal interactions (NOIA) framework to allow for estimation of both main allelic effects and POEs. We develop a statistical (Stat-POE) model that has the orthogonal estimates of parameters including the POEs. We conducted simulation studies for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat- POE and Func-POE models under HWE for quantitative traits

A preliminary study of genetic factors that influence susceptibility to bovine tuberculosis in the British cattle herd

Associations between specific host genes and susceptibility to Mycobacterial infections such as tuberculosis have been reported in several species. Bovine tuberculosis (bTB) impacts greatly the UK cattle industry, yet genetic predispositions have yet to be identified. We therefore used a candidate gene approach to study 384 cattle of which 160 had reacted positively to an antigenic skin test (‘reactors’). Our approach was unusual in that it used microsatellite markers, embraced high breed diversity and focused particularly on detecting genes showing heterozygote advantage, a mode of action often overlooked in SNP-based studies. A panel of neutral markers was used to control for population substructure and using a general linear model-based approach we were also able to control for age. We found that substructure was surprisingly weak and identified two genomic regions that were strongly associated with reactor status, identified by markers INRA111 and BMS2753. In general the strength of association detected tended to vary depending on whether age was included in the model. At INRA111 a single genotype appears strongly protective with an overall odds ratio of 2.2, the effect being consistent across nine diverse breeds. Our results suggest that breeding strategies could be devised that would appreciably increase genetic resistance of cattle to bTB (strictly, reduce the frequency of incidence of reactors) with implications for the current debate concerning badger-culling

Real Space Renormalization Group for Langevin Dynamics in Absence of Translational Invariance

A novel exact dynamical real space renormalization group for a Langevin equation derivable from a Euclidean Gaussian action is presented. It is demonstrated rigorously that an algebraic temporal law holds for the Green function on arbitrary structures of infinite extent. In the case of fractals it is shown on specific examples that two different fixed points are found at variance with periodic structures. Connection with growth dynamics of interfaces is also discussed.Comment: 22 pages, RevTex 3.0, 5 figures available upon request from [email protected], to be published in J.Stat.Phy

Parental Adverse Childhood Experiences and Perpetration of Child Physical Punishment in Wales

Child physical punishment is harmful to children and, as such, is being prohibited by a growing number of countries, including Wales. Parents’ own childhood histories may affect their risks of using child physical punishment. We conducted a national cross-sectional survey of Welsh adults and measured relationships between the number of adverse childhood experiences (ACEs) parents (n = 720 with children aged < 18) had suffered during childhood and their use of physical punishment towards children. Overall, 28.2% of parents reported having ever physically punished a child, and 5.8% reported having done so recently (in the last year). Child physical punishment use increased with the number of ACEs parents reported. Parents with 4+ ACEs were almost three times more likely to have ever physically punished a child and eleven times more likely to have done so recently (vs. those with 0 ACEs). The majority (88.1%) of parents that reported recent child physical punishment had a personal history of ACEs, while over half reported recently having been hit themselves by a child. Child physical punishment is strongly associated with parents’ own ACE exposure and can occur within the context of broader conflict. Prohibiting physical punishment can protect children and, with appropriate family support, may help break intergenerational cycles of violence

ACEtimation—The Combined Effect of Adverse Childhood Experiences on Violence, Health-Harming Behaviors, and Mental Ill-Health: Findings across England and Wales

Adverse childhood experiences (ACEs) encompass various adversities, e.g., physical and/or emotional abuse. Understanding the effects of different ACE types on various health outcomes can guide targeted prevention and intervention. We estimated the association between three categories of ACEs in isolation and when they co-occurred. Specifically, the relationship between child maltreatment, witnessing violence, and household dysfunction and the risk of being involved in violence, engaging in health-harming behaviors, and experiencing mental ill-health. Data were from eight cross-sectional surveys conducted in England and Wales between 2012 and 2022. The sample included 21,716 adults aged 18–69 years; 56.6% were female. Exposure to child maltreatment and household dysfunction in isolation were strong predictors of variant outcomes, whereas witnessing violence was not. However, additive models showed that witnessing violence amplified the measured risk beyond expected levels for being a victim or perpetrator of violence. The multiplicative effect of all three ACE categories demonstrated the highest level of risk (RRs from 1.7 to 7.4). Given the increased risk associated with co-occurring ACEs, it is crucial to target individuals exposed to any ACE category to prevent their exposure to additional harm. Implementing universal interventions that safeguard children from physical, emotional, and sexual violence is likely to mitigate a range of subsequent issues, including future involvement in violence

Emergence of structural and dynamical properties of ecological mutualistic networks

Mutualistic networks are formed when the interactions between two classes of species are mutually beneficial. They are important examples of cooperation shaped by evolution. Mutualism between animals and plants plays a key role in the organization of ecological communities. Such networks in ecology have generically evolved a nested architecture independent of species composition and latitude - specialists interact with proper subsets of the nodes with whom generalists interact. Despite sustained efforts to explain observed network structure on the basis of community-level stability or persistence, such correlative studies have reached minimal consensus. Here we demonstrate that nested interaction networks could emerge as a consequence of an optimization principle aimed at maximizing the species abundance in mutualistic communities. Using analytical and numerical approaches, we show that because of the mutualistic interactions, an increase in abundance of a given species results in a corresponding increase in the total number of individuals in the community, as also the nestedness of the interaction matrix. Indeed, the species abundances and the nestedness of the interaction matrix are correlated by an amount that depends on the strength of the mutualistic interactions. Nestedness and the observed spontaneous emergence of generalist and specialist species occur for several dynamical implementations of the variational principle under stationary conditions. Optimized networks, while remaining stable, tend to be less resilient than their counterparts with randomly assigned interactions. In particular, we analytically show that the abundance of the rarest species is directly linked to the resilience of the community. Our work provides a unifying framework for studying the emergent structural and dynamical properties of ecological mutualistic networks.Comment: 10 pages, 4 figure

Is parental unemployment associated with increased risk of adverse childhood experiences? A systematic review and meta-analysis

Background Unemployment has adverse consequences for families and can put children at risk of harm. This study presents a systematic review and meta-analysis of global evidence on associations between parental unemployment and adverse childhood experiences (ACEs).Methods Systematic literature searches across four databases identified cross-sectional, cohort or case-control studies measuring associations between parental employment and individual or cumulative ACEs in children. Available risk estimates were extracted and pooled odds ratios calculated using random-effects models.Results Of 60 included studies, 37 provided risk estimates suitable for pooling across seven ACE types. Paternal/any parental unemployment was associated with a 29% increased risk of sexual abuse, 54% increased risk of neglect, 60% increased risk of physical abuse and around 90% increased risk of child maltreatment and parental mental illness. No associations were found between maternal unemployment and ACEs. Pooling estimates from representative general population studies also identified increased risk of child maltreatment with paternal/any parental unemployment (82%) but not maternal unemployment. Conclusions Children who grow up with parental unemployment can be at increased risk of ACEs. A combination of socioeconomic measures to increase employment opportunities and parental support targeting fathers and mothers may help break multigenerational cycles of abuse and deprivation

Linkage analysis of longitudinal data and design consideration

BACKGROUND: Statistical methods have been proposed recently to analyze longitudinal data in genetic studies. So far, little attention has been paid to examine the relationship among key factors in genetic longitudinal studies including power, the number of families or sibships, and the number of repeated measures per individual subjects. RESULTS: We proposed a variance component model that extends classic variance component models for a single quantitative trait to mapping longitudinal traits. Our model includes covariate effects and allows genetic effects to vary over time. Using our proposed model, we examined the power, pedigree structures, and sample size through simulation experiments. CONCLUSION: Our simulation results provide useful insights into the study design for genetic, longitudinal studies. For example, collecting a small number of large sibships is much more powerful than collecting a large number of small sibships or increasing the number of repeated measures, when the total number of measurements is comparable