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With models and research designs ever increasing in complexity, the foundational question of model identification is more important than ever. The determination of whether or not a model can be fit at all or fit to some particular data set is the essence of model identification. In this article, we pull from previously published work on data-independent model identification applicable to a broad set of structural equation models, and extend it further to include extremely flexible exogenous covariate effects and also to include data-dependent empirical model identification. For illustrative purposes, we apply this model identification solution to several small examples for which the answer is already known, including a real data example from the National Longitudinal Survey of Youth; however, the method applies similarly to models that are far from simple to comprehend. The solution is implemented in the open-source OpenMx package in R.
The new software package OpenMx 2.0 for structural equation and other statistical modeling is introduced and its features are described. OpenMx is evolving in a modular direction and now allows a mix-and-match computational approach that separates model expectations from fit functions and optimizers. Major backend architectural improvements include a move to swappable open-source optimizers such as the newly written CSOLNP. Entire new methodologies such as item factor analysis and state space modeling have been implemented. New model expectation functions including support for the expression of models in LISREL syntax and a simplified multigroup expectation function are available. Ease-of-use improvements include helper functions to standardize model parameters and compute their Jacobian-based standard errors, access to model components through standard R $ mechanisms, and improved tab completion from within the R Graphical User Interface.
Past studies indicate daily increases in estrogen across the menstrual cycle protect against binge-eating (BE) phenotypes (e.g. emotional eating), whereas increases in progesterone enhance risk. Two previous studies from our laboratory suggest these associations could be due to differential genomic effects of estrogen and progesterone. However, these prior studies were unable to directly model effects of daily changes in hormones on etiologic risk, instead relying on menstrual cycle phase or mean hormone levels. The current study used newly modified twin models to examine, for the first time, the effects of daily changes in estradiol and progesterone on genetic/environmental influences on emotional eating in our archival twin sample assessed across 45 consecutive days.
Methods
Participants included 468 female twins from the Michigan State University Twin Registry. Daily emotional eating was assessed with the Dutch Eating Behavior Questionnaire, and daily saliva samples were assayed for ovarian hormone levels. Modified genotype × environment interaction models examined daily changes in genetic/environmental effects across hormone levels.
Results
Findings revealed differential effects of daily changes in hormones on etiologic risk, with increasing genetic influences across progesterone levels, and increasing shared environmental influences at the highest estradiol levels. Results were consistent across primary analyses examining all study days and sensitivity analyses within menstrual cycle phases.
Conclusions
Findings are significant in being the first to identify changes in etiologic risk for BE symptoms across daily hormone levels and highlighting novel mechanisms (e.g. hormone threshold effects, regulation of conserved genes) that may contribute to the etiology of BE.
A model based on Gouy-Chapman theory, describing the ion exchange behavior of clays in mixed electrolyte solutions is presented. Computed ionic distributions, taking into account variations in relative permittivity, ion activity, and closeness of approach of ions to clay surfaces, are compared with experimental data for smectite and kaolinite in contact with river and saline waters. To obtain reasonable agreement between theoretical prediction and observation the most important extension of Gouy-Chapman theory involves the introduction of a closeness of approach term. Furthermore, the aggregated nature of smectites plays an important part in controlling its exchange properties, whereas a fixed-charge model provides a poor description for the ion exchange properties of kaolinite.
Observational studies suggest that 25-hydroxy vitamin D (25(OH)D) concentration is inversely associated with pain. However, findings from intervention trials are inconsistent. We assessed the effect of vitamin D supplementation on pain using data from a large, double-blind, population-based, placebo-controlled trial (the D-Health Trial). 21 315 participants (aged 60–84 years) were randomly assigned to a monthly dose of 60 000 IU vitamin D3 or matching placebo. Pain was measured using the six-item Pain Impact Questionnaire (PIQ-6), administered 1, 2 and 5 years after enrolment. We used regression models (linear for continuous PIQ-6 score and log-binomial for binary categorisations of the score, namely ‘some or more pain impact’ and ‘presence of any bodily pain’) to estimate the effect of vitamin D on pain. We included 20 423 participants who completed ≥1 PIQ-6. In blood samples collected from 3943 randomly selected participants (∼800 per year), the mean (sd) 25(OH)D concentrations were 77 (sd 25) and 115 (sd 30) nmol/l in the placebo and vitamin D groups, respectively. Most (76 %) participants were predicted to have 25(OH)D concentration >50 nmol/l at baseline. The mean PIQ-6 was similar in all surveys (∼50·4). The adjusted mean difference in PIQ-6 score (vitamin D cf placebo) was 0·02 (95 % CI (−0·20, 0·25)). The proportion of participants with some or more pain impact and with the presence of bodily pain was also similar between groups (both prevalence ratios 1·01, 95 % CI (0·99, 1·03)). In conclusion, supplementation with 60 000 IU of vitamin D3/month had negligible effect on bodily pain.
The COVID-19 pandemic resulted in millions of deaths worldwide and is considered a significant mass-casualty disaster (MCD). The surge of patients and scarcity of resources negatively impacted hospitals, patients and medical practice. We hypothesized ICUs during this MCD had a higher acuity of illness, and subsequently had increased lengths of stay (LOS), complication rates, death rates and costs of care. The purpose of this study was to investigate those outcomes.
Methods:
This was a multicenter, retrospective study that compared intensive care admissions in 2020 to those in 2019 to evaluate patient outcomes and cost of care. Data were obtained from the Vizient Clinical Data Base/Resource Manager (Vizient Inc., Irvine, Texas, USA).
Results:
Data included the number of ICU admissions, patient outcomes, case mix index and summary of cost reports. Quality outcomes were also collected, and a total of 1304981 patients from 333 hospitals were included. For all medical centers, there was a significant increase in LOS index, ICU LOS, complication rate, case mix index, total cost, and direct cost index.
Conclusion:
The MCD caused by COVID-19 was associated with increased adverse outcomes and cost-of-care for ICU patients.
To determine associations of alcohol use with cognitive aging among middle-aged men.
Method:
1,608 male twins (mean 57 years at baseline) participated in up to three visits over 12 years, from 2003–2007 to 2016–2019. Participants were classified into six groups based on current and past self-reported alcohol use: lifetime abstainers, former drinkers, very light (1–4 drinks in past 14 days), light (5–14 drinks), moderate (15–28 drinks), and at-risk drinkers (>28 drinks in past 14 days). Linear mixed-effects regressions modeled cognitive trajectories by alcohol group, with time-based models evaluating rate of decline as a function of baseline alcohol use, and age-based models evaluating age-related differences in performance by current alcohol use. Analyses used standardized cognitive domain factor scores and adjusted for sociodemographic and health-related factors.
Results:
Performance decreased over time in all domains. Relative to very light drinkers, former drinkers showed worse verbal fluency performance, by –0.21 SD (95% CI –0.35, –0.07), and at-risk drinkers showed faster working memory decline, by 0.14 SD (95% CI 0.02, –0.20) per decade. There was no evidence of protective associations of light/moderate drinking on rate of decline. In age-based models, light drinkers displayed better memory performance at advanced ages than very light drinkers (+0.14 SD; 95% CI 0.02, 0.20 per 10-years older age); likely attributable to residual confounding or reverse association.
Conclusions:
Alcohol consumption showed minimal associations with cognitive aging among middle-aged men. Stronger associations of alcohol with cognitive aging may become apparent at older ages, when cognitive abilities decline more rapidly.
The first demonstration of laser action in ruby was made in 1960 by T. H. Maiman of Hughes Research Laboratories, USA. Many laboratories worldwide began the search for lasers using different materials, operating at different wavelengths. In the UK, academia, industry and the central laboratories took up the challenge from the earliest days to develop these systems for a broad range of applications. This historical review looks at the contribution the UK has made to the advancement of the technology, the development of systems and components and their exploitation over the last 60 years.
Clarifying the relationship between depression symptoms and cardiometabolic and related health could clarify risk factors and treatment targets. The objective of this study was to assess whether depression symptoms in midlife are associated with the subsequent onset of cardiometabolic health problems.
Methods
The study sample comprised 787 male twin veterans with polygenic risk score data who participated in the Harvard Twin Study of Substance Abuse (‘baseline’) and the longitudinal Vietnam Era Twin Study of Aging (‘follow-up’). Depression symptoms were assessed at baseline [mean age 41.42 years (s.d. = 2.34)] using the Diagnostic Interview Schedule, Version III, Revised. The onset of eight cardiometabolic conditions (atrial fibrillation, diabetes, erectile dysfunction, hypercholesterolemia, hypertension, myocardial infarction, sleep apnea, and stroke) was assessed via self-reported doctor diagnosis at follow-up [mean age 67.59 years (s.d. = 2.41)].
Results
Total depression symptoms were longitudinally associated with incident diabetes (OR 1.29, 95% CI 1.07–1.57), erectile dysfunction (OR 1.32, 95% CI 1.10–1.59), hypercholesterolemia (OR 1.26, 95% CI 1.04–1.53), and sleep apnea (OR 1.40, 95% CI 1.13–1.74) over 27 years after controlling for age, alcohol consumption, smoking, body mass index, C-reactive protein, and polygenic risk for specific health conditions. In sensitivity analyses that excluded somatic depression symptoms, only the association with sleep apnea remained significant (OR 1.32, 95% CI 1.09–1.60).
Conclusions
A history of depression symptoms by early midlife is associated with an elevated risk for subsequent development of several self-reported health conditions. When isolated, non-somatic depression symptoms are associated with incident self-reported sleep apnea. Depression symptom history may be a predictor or marker of cardiometabolic risk over decades.
Conventional longitudinal behavioral genetic models estimate the relative contribution of genetic and environmental factors to stability and change of traits and behaviors. Longitudinal models rarely explain the processes that generate observed differences between genetically and socially related individuals. We propose that exchanges between individuals and their environments (i.e., phenotype–environment effects) can explain the emergence of observed differences over time. Phenotype–environment models, however, would require violation of the independence assumption of standard behavioral genetic models; that is, uncorrelated genetic and environmental factors. We review how specification of phenotype–environment effects contributes to understanding observed changes in genetic variability over time and longitudinal correlations among nonshared environmental factors. We then provide an example using 30 days of positive and negative affect scores from an all-female sample of twins. Results demonstrate that the phenotype–environment effects explain how heritability estimates fluctuate as well as how nonshared environmental factors persist over time. We discuss possible mechanisms underlying change in gene–environment correlation over time, the advantages and challenges of including gene–environment correlation in longitudinal twin models, and recommendations for future research.
Despite being identified as a pervasive emotion in the modern workplace (Pfeffer & Sutton, 2000), fear oddly has not received a corresponding amount of attention among management researchers. In fact, Kish-Gephart, Detert, Treviño, and Edmondson (2009, p. 163) observe that we still have much to learn about the nature of fear in workplace settings, including “what it is, how and why it is experienced, and to what effects.” Bennis (1966) notes further that fear has always been a part of the work environment (see also Connelly & Turner, 2018), but it remains an especially important issue in today’s workplaces because of the effects of rapid and ongoing organizational change, which are often linked to uncertain outcomes (Bordia, Hobman, Jones, Gallois, & Callan, 2004; Tiedens & Linton, 2001). Our aim in this chapter is to provide an overview of fear (arising from uncertainty) as a discrete emotion, to identify stimuli that may trigger fear at work, and to identify the potential positive and negative outcomes that can be linked to employees’ fear. We also outline potential pathways for future research on fear of uncertainty in the workplace.
Dr Nick Martin has made enormous contributions to the field of behavior genetics over the past 50 years. Of his many seminal papers that have had a profound impact, we focus on his early work on the power of twin studies. He was among the first to recognize the importance of sample size calculation before conducting a study to ensure sufficient power to detect the effects of interest. The elegant approach he developed, based on the noncentral chi-squared distribution, has been adopted by subsequent researchers for other genetic study designs, and today remains a standard tool for power calculations in structural equation modeling and other areas of statistical analysis. The present brief article discusses the main aspects of his seminal paper, and how it led to subsequent developments, by him and others, as the field of behavior genetics evolved into the present era.
An improved understanding of diagnostic and treatment practices for patients with rare primary mitochondrial disorders can support benchmarking against guidelines and establish priorities for evaluative research. We aimed to describe physician care for patients with mitochondrial diseases in Canada, including variation in care.
Methods:
We conducted a cross-sectional survey of Canadian physicians involved in the diagnosis and/or ongoing care of patients with mitochondrial diseases. We used snowball sampling to identify potentially eligible participants, who were contacted by mail up to five times and invited to complete a questionnaire by mail or internet. The questionnaire addressed: personal experience in providing care for mitochondrial disorders; diagnostic and treatment practices; challenges in accessing tests or treatments; and views regarding research priorities.
Results:
We received 58 survey responses (52% response rate). Most respondents (83%) reported spending 20% or less of their clinical practice time caring for patients with mitochondrial disorders. We identified important variation in diagnostic care, although assessments frequently reported as diagnostically helpful (e.g., brain magnetic resonance imaging, MRI/MR spectroscopy) were also recommended in published guidelines. Approximately half (49%) of participants would recommend “mitochondrial cocktails” for all or most patients, but we identified variation in responses regarding specific vitamins and cofactors. A majority of physicians recommended studies on the development of effective therapies as the top research priority.
Conclusions:
While Canadian physicians’ views about diagnostic care and disease management are aligned with published recommendations, important variations in care reflect persistent areas of uncertainty and a need for empirical evidence to support and update standard protocols.
Vulnerability to depression can be measured in different ways. We here examine how genetic risk factors are inter-related for lifetime major depression (MD), self-report current depressive symptoms and the personality trait Neuroticism.
Method
We obtained data from three population-based adult twin samples (Virginia n = 4672, Australia #1 n = 3598 and Australia #2 n = 1878) to which we fitted a common factor model where risk for ‘broadly defined depression’ was indexed by (i) lifetime MD assessed at personal interview, (ii) depressive symptoms, and (iii) neuroticism. We examined the proportion of genetic risk for MD deriving from the common factor v. specific to MD in each sample and then analyzed them jointly. Structural equation modeling was conducted in Mx.
Results
The best fit models in all samples included additive genetic and unique environmental effects. The proportion of genetic effects unique to lifetime MD and not shared with the broad depression common factor in the three samples were estimated as 77, 61, and 65%, respectively. A cross-sample mega-analysis model fit well and estimated that 65% of the genetic risk for MD was unique.
Conclusion
A large proportion of genetic risk factors for lifetime MD was not, in the samples studied, captured by a common factor for broadly defined depression utilizing MD and self-report measures of current depressive symptoms and Neuroticism. The genetic substrate for MD may reflect neurobiological processes underlying the episodic nature of its cognitive, motor and neurovegetative manifestations, which are not well indexed by current depressive symptom and neuroticism.
Most studies underline the contribution of heritable factors for psychiatric disorders. However, heritability estimates depend on the population under study, diagnostic instruments, and study designs that each has its inherent assumptions, strengths, and biases. We aim to test the homogeneity in heritability estimates between two powerful, and state of the art study designs for eight psychiatric disorders.
Methods
We assessed heritability based on data of Swedish siblings (N = 4 408 646 full and maternal half-siblings), and based on summary data of eight samples with measured genotypes (N = 125 533 cases and 208 215 controls). All data were based on standard diagnostic criteria. Eight psychiatric disorders were studied: (1) alcohol dependence (AD), (2) anorexia nervosa, (3) attention deficit/hyperactivity disorder (ADHD), (4) autism spectrum disorder, (5) bipolar disorder, (6) major depressive disorder, (7) obsessive-compulsive disorder (OCD), and (8) schizophrenia.
Results
Heritability estimates from sibling data varied from 0.30 for Major Depression to 0.80 for ADHD. The estimates based on the measured genotypes were lower, ranging from 0.10 for AD to 0.28 for OCD, but were significant, and correlated positively (0.19) with national sibling-based estimates. When removing OCD from the data the correlation increased to 0.50.
Conclusions
Given the unique character of each study design, the convergent findings for these eight psychiatric conditions suggest that heritability estimates are robust across different methods. The findings also highlight large differences in genetic and environmental influences between psychiatric disorders, providing future directions for etiological psychiatric research.
The mode of action of quinclorac was investigated in broadleaf and grass species. Quinclorac induced characteristic auxinlike symptoms in broadleaf species but not in susceptible grasses. In susceptible grasses, quinclorac caused necrotic bands near the zones of elongation in shoots and roots. Electrolyte leakage was induced by quinclorac in smooth crabgrass and other susceptible grasses but not in tolerant grass or susceptible broadleaf species. In smooth crabgrass, increased electrolyte leakage and reduced fresh weight were rate dependent, and initially specific to young tissues. An inhibitory effect on elongation in the youngest leaf of smooth crabgrass and in primary roots of corn was detected 6 and 3 h after quinclorac treatment, respectively. Electrolyte leakage required more than 12 and 6 h in the leaf and root, respectively. Depolarization of corn root cell membrane potential was not observed in a 6-h treatment period. Results presented here provide additional evidence that quinclorac activity differs between susceptible broadleaf and grass species. In addition, the action of quinclorac appears to be similar in both shoot and root tissues of susceptible grasses. It is proposed that quinclorac-induced electrolyte leakage in susceptible grasses is a secondary response and that the primary mechanism of action involves inhibition of an as yet unknown metabolic process associated with cell expansion.
Investigations of smooth crabgrass growth and fenoxaprop-ethyl retention, foliar penetration, translocation, and metabolism were conducted at various soil moisture levels using a polyethylene glycol (PEG) semipermeable membrane system. The activity of fenoxapropethyl was significantly reduced at higher levels of moisture stress and this antagonistic effect was greater with increased duration of water deficit following herbicide application. Fenoxaprop-ethyl spray retention decreased linearly (23% total reduction) as soil matric potential (Ψm) decreased from −0.01 to −0.1 MPa. Foliar penetration and translocation of 14C-fenoxaprop-ethyl applied on the third true leaf were not affected by level or duration of moisture stress. Only 2% of the absorbed radioactivity was translocated out of the treated leaf for each moisture stress level and duration. As the soil Ψm decreased (−0.01 to −1.0 MPa) the relative levels of fenoxaprop-ethyl increased by 76 and 65% after a 48- and 96-h postapplication moisture stress period, respectively. In contrast, fenoxaprop acid decreased by 59 and 44% after 48 and 96 h of moisture stress, respectively. The relative level of fenoxaprop acid was linearly correlated to the antagonistic effect on shoot dry weight. These results suggest that decreased spray retention and, particularly, alterations in fenoxaprop-ethyl metabolism contribute to reduced fenoxaprop-ethyl activity observed in moisture-stressed smooth crabgrass.
DSM-5 includes two conceptualizations of personality disorders (PDs). The classification in Section II is identical to the one found in DSM-IV, and includes 10 categorical PDs. The Alternative Model (Section III) includes criteria for dimensional measures of maladaptive personality traits organized into five domains. The degree to which the two conceptualizations reflect the same etiological factors is not known.
Methods
We use data from a large population-based sample of adult twins from the Norwegian Institute of Public Health Twin Panel on interview-based DSM-IV PDs and a short self-report inventory that indexes the five domains of the DSM-5 Alternative Model plus a domain explicitly targeting compulsivity. Schizotypal, Paranoid, Antisocial, Borderline, Avoidant, and Obsessive-compulsive PDs were assessed at the same time as the maladaptive personality traits and 10 years previously. Schizoid, Histrionic, Narcissistic, and Dependent PDs were only assessed at the first interview. Biometric models were used to estimate overlap in genetic and environmental risk factors.
Results
When measured concurrently, there was 100% genetic overlap between the maladaptive trait domains and Paranoid, Schizotypal, Antisocial, Borderline, and Avoidant PDs. For OCPD, 43% of the genetic variance was shared with the domains. Genetic correlations between the individual domains and PDs ranged from +0.21 to +0.91.
Conclusion
The pathological personality trait domains, which are part of the Alternative Model for classification of PDs in DSM-5 Section III, appears to tap, at an aggregate level, the same genetic risk factors as the DSM-5 Section II classification for most of the PDs.