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Predictability of behavior is an important characteristic in many fields including biology, medicine, marketing, and education. When a sequence of actions performed by an individual can be modeled as a stationary time-homogeneous Markov chain the predictability of the individual’s behavior can be quantified by the entropy rate of the process. This article compares three estimators of the entropy rate of finite Markov processes. The first two methods directly estimate the entropy rate through estimates of the transition matrix and stationary distribution of the process. The third method is related to the sliding-window Lempel–Ziv compression algorithm. The methods are compared via a simulation study and in the context of a study of interactions between mothers and their children.

In this paper we provide a method for calculating the implied volatility of the outcome of a sports game. We base our analysis on Stern's stochastic model for the evolution of sports scores (Stern, H. S. 1994. "A Brownian Motion Model for the Progress of Sports Scores." Journal of the American Statistical Association 89:1128-1134.). Using bettors' point spread and moneyline odds, we extend the model to calculate the market-implied volatility of the game's score. The model can also be used to calculate the time-varying implied volatility during the game using inputs from real-time, online betting and to identify betting opportunities. We illustrate our methodology on data from Super Bowl XLVII between the Baltimore Ravens and the San Francisco 49ers and show how the market-implied volatility of the outcome varied as the game progressed.

The Bowl Championship Series is designed to match the two top teams in college football in a title game. To determine the top ranked teams, polls are combined with a number of quantitative ratings of the teams known collectively as the computer ranking. The computer ranking serves primarily to offer a validation of the polls. The individuals whose quantitative ratings are used in the computer ranking have never been given a clear objective to design their ratings for and they are limited in the inputs that they can use (for example, they can not use score or site of game). For all of these reasons, I am advocating a boycott of the Bowl Championship Series by all quantitative analysts.

Background: Unpredictable childhood experiences are an understudied form of early life adversity that impacts neurodevelopment in a sex-specific manner. The neurobiological processes by which exposure to early-life unpredictability impacts development and vulnerability to psychopathology remain poorly understood. The present study investigates the sex-specific consequences of early-life unpredictability on the limbic network, focusing on the hippocampus and the amygdala., Methods: Participants included 150 youth (54% female). Early life unpredictability was assessed using the Questionnaire of Unpredictability in Childhood (QUIC). Participants engaged in a task-fMRI scan between the ages of 8 and 17 (223 total observations) measuring BOLD responses to novel and familiar scenes., Results: Exposure to early-life unpredictability associated with BOLD contrast (novel vs. familiar) in a sex-specific manner. For males, but not females, higher QUIC scores were associated with lower BOLD activation in response to novel vs. familiar stimuli in the hippocampal head and amygdala. Secondary psychophysiological interaction (PPI) analyses revealed complementary sex-specific associations between QUIC and condition-specific functional connectivity between the right and left amygdala, as well as between the right amygdala and hippocampus bilaterally., Conclusion: Exposure to unpredictability in early life has persistent implications for the functional operations of limbic circuits. Importantly, consistent with emerging experimental animal and human studies, the consequences of early life unpredictability differ for males and females. Further, impacts of early-life unpredictability were independent of other risk factors including lower household income and negative life events, indicating distinct consequences of early-life unpredictability over and above more commonly studied types of early life adversity., Competing Interests: Disclosures All authors report no conflicts of interest related to this work.

Adverse early-life experiences (ELA) affect a majority of the world's children. Whereas the enduring impact of ELA on cognitive and emotional health is established, there are no tools to predict vulnerability to ELA consequences in an individual child. Epigenetic markers including peripheral-cell DNA-methylation profiles may encode ELA and provide predictive outcome markers, yet the interindividual variance of the human genome and rapid changes in DNA methylation in childhood pose significant challenges. Hoping to mitigate these challenges we examined the relation of several ELA dimensions to DNA methylation changes and outcome using a within-subject longitudinal design and a high methylation-change threshold. DNA methylation was analyzed in buccal swab/saliva samples collected twice (neonatally and at 12 months) in 110 infants. We identified CpGs differentially methylated across time for each child and determined whether they associated with ELA indicators and executive function at age 5. We assessed sex differences and derived a sex-dependent 'impact score' based on sites that most contributed to methylation changes. Changes in methylation between two samples of an individual child reflected age-related trends and correlated with executive function years later. Among tested ELA dimensions and life factors including income to needs ratios, maternal sensitivity, body mass index and infant sex, unpredictability of parental and household signals was the strongest predictor of executive function. In girls, high early-life unpredictability interacted with methylation changes to presage executive function. Thus, longitudinal, within-subject changes in methylation profiles may provide a signature of ELA and a potential predictive marker of individual outcome., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Objective: To determine epidemiologic features of naturally occurring myxomatosis in domestic rabbits in California and to characterize clinicopathologic and diagnostic findings., Animals: 11 client-owned rabbits, Oryctolagus cuniculus subsp domesticus., Clinical Presentation: A prospective study of pet rabbits with myxomatosis seen at an exotic animal specialty clinic in Santa Cruz county, California, was conducted between January 1, 2022, and December 31, 2023. Rabbits were included in the study if they had bilateral blepharedema and were PCR positive for myxoma virus., Results: All infected rabbits had spent time outdoors. Common clinical signs included bilateral blepharedema (11/11), anogenital edema (10/11), rectal temperature ≥ 39.7 °C (5/9), and sudden death (4/11). Eyelid biopsies from all rabbits (11/11) were positive for myxoma virus by qualitative PCR followed by Sanger sequencing (100% nucleotide identity to strain MSW, also known as California/San Francisco 1950 [Genbank accession KF148065]). Most rabbits had keratinocytes containing eosinophilic intracytoplasmic viral inclusions in biopsies of edematous skin (8/11) and lymphocyte necrosis in the spleen (10/11). Immunohistochemistry identified myxoma virus in samples of skin, heart, lung, ileum, spleen, and lymph node., Clinical Relevance: Clinical signs of myxomatosis caused by the MSW strain of myxoma virus are distinctive but subtle. Cases occur regularly in the Santa Cruz and San Jose regions of California. As infection with this virus is almost 100% fatal and no vaccine is available in the US, owners of domestic rabbits in endemic areas should keep their pets indoors or behind mosquito screens. Myxomatosis is a reportable disease in the US, and the appropriate state or federal agencies should be contacted when outbreaks occur.

Background: Anhedonia, an impairment in the motivation for or experience of pleasure, is a well-established transdiagnostic harbinger and core symptom of mental illness. Given increasing recognition of early life origins of mental illness, we posit that anhedonia should, and could, be recognized earlier if appropriate tools were available. However, reliable diagnostic instruments prior to childhood do not currently exist., Methods: We developed an assessment instrument for anhedonia/reward processing in infancy, the Infant Hedonic/Anhedonic Processing Index (HAPI-Infant). Exploratory factor and psychometric analyses were conducted using data from 6- and 12-month-old infants from two cohorts (N = 188, N = 212). Then, associations were assessed between infant anhedonia and adolescent self-report of depressive symptoms., Results: The HAPI-Infant (47-items), exhibited excellent psychometric properties. Higher anhedonia scores at 6 (r = 0.23, p < .01) and 12 months (r = 0.19, p < .05) predicted elevated adolescent depressive symptoms, and these associations were stronger than for established infant risk indicators such as negative affectivity. Subsequent analyses supported the validity of short (27-item) and very short (12-item) versions of this measure., Limitations: The primary limitations of this study are that the HAPI-Infant awaits additional tests of generalizability and of its ability to predict clinical diagnosis of depression., Conclusions: The HAPI-Infant is a novel, psychometrically strong diagnostic tool suitable for recognizing anhedonia during the first year of life with strong predictive value for later depressive symptoms. In view of the emerging recognition of increasing prevalence of affective disorders in children and adolescents, the importance of the HAPI-Infant in diagnosing anhedonia is encouraging. Early recognition of anhedonia could target high-risk individuals for intervention and perhaps prevention of mental health disorders., Competing Interests: Declaration of competing interest The authors have nothing to disclose., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Patterns of sensory inputs early in life play an integral role in shaping the maturation of neural circuits, including those implicated in emotion and cognition. In both experimental animal models and observational human research, unpredictable sensory signals have been linked to aberrant developmental outcomes, including poor memory and effortful control. These findings suggest that sensitivity to unpredictable sensory signals is conserved across species and sculpts the developing brain. The current study provides a novel investigation of unpredictable maternal sensory signals in early life and child internalizing behaviors. We tested these associations in three independent cohorts to probe the generalizability of associations across continents and cultures., Method: The three prospective longitudinal cohorts were based in Orange, USA (n = 163, 47.2 % female, M age  = 1 year); Turku, Finland (n = 239, 44.8 % female, M age  = 5 years); and Irvine, USA (n = 129, 43.4 % female, M age  = 9.6 years). Unpredictability of maternal sensory signals was quantified during free-play interactions. Child internalizing behaviors were measured via parent report (Orange & Turku) and child self-report (Irvine)., Results: Early life exposure to unpredictable maternal sensory signals was associated with greater child fearfulness/anxiety in all three cohorts, above and beyond maternal sensitivity and sociodemographic factors. The association between unpredictable maternal sensory signals and child sadness/depression was relatively weaker and did not reach traditional thresholds for statistical significance., Limitations: The correlational design limits our ability to make causal inferences., Conclusions: Findings across the three diverse cohorts suggest that unpredictable maternal signals early in life shape the development of internalizing behaviors, particularly fearfulness and anxiety., Competing Interests: Declaration of competing interest No conflicts of interests were reported by the authors., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Forensic science disciplines such as latent print examination, bullet and cartridge case comparisons, and shoeprint analysis, involve subjective decisions by forensic experts throughout the examination process. Most of the decisions involve ordinal categories. Examples include a three-category outcome for latent print comparisons (exclusion, inconclusive, identification) and a seven-category outcome for footwear comparisons (exclusion, indications of non-association, inconclusive, limited association of class characteristics, association of class characteristics, high degree of association, identification). As the results of the forensic examinations of evidence can heavily influence the outcomes of court proceedings, it is important to assess the reliability and accuracy of the underlying decisions. "Black box" studies are the most common approach for assessing the reliability and accuracy of subjective decisions. In these studies, researchers produce evidence samples consisting of a sample of questioned source and a sample of known source where the ground truth (same source or different source) is known. Examiners provide assessments for selected samples using the same approach they would use in actual casework. These studies often have two phases; the first phase comprises of decisions on samples of varying complexities by different examiners, and the second phase involves repeated decisions by the same examiner on a (usually) small subset of samples that were encountered by examiners in the first phase. We provide a statistical method to analyze ordinal decisions from black-box trials with the objective of obtaining inferences for the reliability of these decisions and quantifying the variation in decisions attributable to the examiners, the samples, and statistical interaction effects between examiners and samples. We present simulation studies to judge the performance of the model on data with known parameter values and apply the model to data from a handwritten signature complexity study, a latent fingerprint examination black-box study, and a handwriting comparisons black-box study., Competing Interests: Declaration of Competing Interest The authors do not have any conflicts of interest., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Purpose: In 2020, racially/ethnically minoritized (REMD) youth faced the "dual pandemics" of COVID-19 and racism, both significant stressors with potential for adverse mental health effects. The current study tested whether short- and long-term trajectories of depressive symptoms from before to during the COVID-19 pandemic differed between REMD adolescents who did and did not endorse exposure to COVID-19-era-related racism (i.e., racism stemming from conditions created or exacerbated by the COVID-19 pandemic)., Methods: A community sample of 100 REMD adolescents enrolled in an ongoing longitudinal study of mental health was assessed before and during the COVID-19 pandemic. Participants were 51% girls, mean age = 16, standard deviation = 2.7, and identified as Latinx/Hispanic (48%), Multiethnic (34%), Asian American (12%), and Black (6%)., Results: REMD adolescents' depressive symptoms were elevated during the COVID-19 pandemic compared to pre-pandemic levels, and increases were more pronounced over time for those who endorsed exposure to COVID-19-era-related racism. In general, Asian American participants endorsed racism experiences at the highest rates compared to others, including being called names (42%), people acting suspicious around them (33%), and being verbally threatened (17%). Additionally, more than half of Black and Asian American participants reported worry about experiencing racism related to the COVID-19 pandemic, even if they had not experienced it to date., Discussion: REMD adolescents are at increased risk for depressive symptoms related to converging stressors stemming from the COVID-19 pandemic and pandemic-related racism, which has the potential to widen racial/ethnic mental health disparities faced by the REMD youth., (Copyright © 2023 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.)

In this work, we explore the application of likelihood ratio as a forensic evidence assessment tool to evaluate the causal mechanism of a bloodstain pattern. It is assumed that there are two competing hypotheses regarding the cause of a bloodstain pattern. The bloodstain patterns are represented as a collection of ellipses with each ellipse characterized by its location, size and orientation. Quantitative measures and features are derived to summarize key aspects of the patterns. A bivariate Gaussian model is chosen to estimate the distribution of features under a given hypothesis and thus approximate the likelihood of a pattern. Published data with 59 impact patterns and 55 gunshot patterns is used to train and evaluate the model. Results demonstrate the feasibility of the likelihood ratio approach for bloodstain pattern analysis. The results also hint at some of the challenges that need to be addressed for future use of the likelihood ratio approach for bloodstain pattern analysis., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Unpredictability is increasingly recognized as a primary dimension of early life adversity affecting lifespan mental health trajectories; screening for these experiences is therefore vital. The Questionnaire of Unpredictability in Childhood (QUIC) is a 38-item tool that measures unpredictability in childhood in social, emotional and physical domains. The available evidence indicates that exposure to unpredictable experiences measured with the QUIC predicts internalizing symptoms including depression and anxiety. The purpose of the present study was to validate English and Spanish brief versions (QUIC-5) suitable for administration in time-limited settings (e.g., clinical care settings, large-scale epidemiological studies). Five representative items were identified from the QUIC and their psychometric properties examined. The predictive validity of the QUIC-5 was then compared to the QUIC by examining mental health in four cohorts: (1) English-speaking adult women assessed at 6-months postpartum ( N = 116), (2) English-speaking male veterans ( N = 95), (3) English-speaking male and female adolescents ( N = 155), and (4) Spanish-speaking male and female adults ( N = 285). The QUIC-5 demonstrated substantial variance in distributions in each of the cohorts and is correlated on average 0.84 ( r's = 0.81-0.87) with the full 38-item version. Furthermore, the QUIC-5 predicted internalizing symptoms (anxiety and depression) in all cohorts with similar effect sizes ( r's = 0.16-0.39; all p's < 0.05) to the full versions ( r's = 0.19-0.42; all p's < 0.05). In sum, the QUIC-5 exhibits good psychometric properties and is a valid alternative to the full QUIC. These findings support the future use of the QUIC-5 in clinical and research settings as a concise way to measure unpredictability, identify risk of psychopathology, and intervene accordingly., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Lindert, Maxwell, Liu, Stern, Baram, Poggi Davis, Risbrough, Baker, Nievergelt and Glynn.)

Exposure to early life adversity has long term consequences on cognitive function. Most research has focused on understanding components of early life adversities that contribute to later risk, including poverty, trauma, maltreatment, and neglect. Whereas these factors, in the aggregate, explain a significant proportion of emotional and cognitive problems, there are serious gaps in our ability to identify potential mechanisms by which early life adversities might promote vulnerability or resilience. Here we discuss early life exposure to unpredictable signals from the caretaker as an understudied type of adversity that is amenable to prevention and intervention. We employ a translational approach to discover underlying neurobiological mechanisms by which early life exposure to unpredictable signals sculpts the developing brain. First, we review evidence that exposure to unpredictable signals from the parent during sensitive periods impacts development of neural circuits. Second, we describe a method for characterizing early life patterns of sensory signals across species. Third, we present published and original data illustrating that patterns of maternal care predict memory function in humans, non-human primates, and rodents. Finally, implications are discussed for identifying individuals at risk so that early preventive-intervention can be provided., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Davis, McCormack, Arora, Sharpe, Short, Bachevalier, Glynn, Sandman, Stern, Sanchez and Baram.)

Exposure to early-life adversity (ELA) is associated with several neuropsychiatric conditions, including major depressive disorder, yet causality is difficult to establish in humans. Recent work in rodents has implicated impaired reward circuit signaling in anhedonic-like behavior after ELA exposure. Anhedonia, the lack of reactivity to previously rewarding stimuli, is a transdiagnostic construct common to mental illnesses associated with ELA. Here, we employed an assay of reward responsiveness validated across species, the Probabilistic Reward Task (PRT). In the PRT, healthy participants reliably develop a response bias toward the more richly rewarded stimulus, whereas participants with anhedonia exhibit a blunted response bias that correlates with current and future anhedonia. In a well-established model of ELA that generates a stressful, chaotic, and unpredictable early-life environment, ELA led to blunted response biases in the PRT in two separate cohorts, recapitulating findings in humans with anhedonia. The same ELA rats had blunted sucrose preference, further supporting their anhedonic-like phenotypes. Probing the aspects of ELA that might provoke these deficits, we quantified the unpredictability of dam/pup interactions using entropy measures and found that the unpredictability of maternal care was significantly higher in the ELA groups in which PRT and sucrose preference reward deficits were present later in life. Taken together, these data position the PRT, established in clinical patient populations, as a potent instrument to assess the impact of ELA on the reward circuit across species. These findings also implicate the unpredictability of maternal signals during early life as an important driver of reward sensitivity deficits., (© 2021. The Author(s), under exclusive licence to American College of Neuropsychopharmacology.)

Emerging evidence indicates that the predictability of signals early in life may influence the developing brain. This study examines links between a novel indicator of maternal mood dysregulation, mood entropy, and child neurodevelopmental outcomes. Associations between prenatal maternal mood entropy and child neurodevelopment were assessed in 2 longitudinal cohorts. Maternal mood was measured several times over pregnancy beginning as early as 15 weeks' gestation. Shannon's mood entropy was applied to distributions of mothers' responses on mood questionnaires. Child cognitive and language development were evaluated at 2 and 6-9 years of age. Higher prenatal maternal mood entropy was associated with lower cognitive development scores at 2 years of age and lower expressive language scores at 6-9 years of age. These associations persisted after adjusting for maternal pre and postnatal mood levels and for other relevant sociodemographic factors. Our findings identify maternal mood entropy as a novel predictor of child neurodevelopment. Characterizing components of maternal mood in addition to level of severity or valence may further our understanding of specific processes by which maternal mood shapes child development. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Background: For young children, existing measures of children's health-related quality of life must be parent-reported or interviewer-administered for those who cannot read or complete measures independently. Parents' and childrens' reports about the child's health have been shown to disagree., Aims: (a) To test the reliability and validity of an animated, computer-administered Child Health Rating Inventories (CHRIS2.0) among children aged 4-12 undergoing surgery; and (b) to develop and test two CHRIS measures of preoperative anxiety and postoperative pain management., Methods: We conducted a longitudinal cohort study of a diverse group of 542 children aged 4-12 undergoing surgery. We compared the CHRIS measures to Pediatric Quality of Life Inventory (PedsQL), the Functional Disabilities Inventory (FDI), State-Trait Anxiety Inventory for children (STAI-CH), and the Parent Postoperative Pain Measure (PPPM)., Results: Factor analyses supported the construct validity of the 12-item general physical health and the 8-item mental health CHRIS scales, as well as a composite 20-item scale, and the CHRIS preoperative anxiety and postoperative pain scales. Internal consistency reliability for all CHRIS scales exceeded the standard for group comparisons (Cronbach's α ≥0.70). The CHRIS general health composite was significantly correlated with composite PedsQL and FDI (r = 0.28, P < .001 and r = 0.43, P < .001, respectively). The CHRIS peri-operative anxiety measure was significantly correlated with the STAI-CH (r = 0.44, P < .001), as was the CHRIS postoperative pain scale with the PPPM (r = 0.52, P < .001)., Conclusions: The CHRIS measures were reliable and valid in this diverse sample of young children (4-12). Because CHRIS measures are self-administered, scored in real time, and run on multiple different platforms, this approach provides a feasible method for the collection of health-related quality of life in young children and those with limited literacy. Our data indicate that this approach is psychometrically sound and has the potential for adding the child's voice to pediatric outcomes., (© 2020 John Wiley & Sons Ltd.)

Background: Dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis is associated with poor physical and mental health. Early-life adversity may dysregulate cortisol response to subsequent stress. This study examines the association between patterns of maternal behavior and infant stress response to a challenge. Specifically, we test whether infant exposure to unpredictable maternal sensory signals is related to the cortisol response to a painful stressor., Method: Participants were 102 mothers and their children enrolled in a longitudinal study. Patterns of maternal sensory signals were evaluated at 6 and 12 months during a 10-min mother-infant play episode. Entropy rate was calculated as a quantitative measure of the degree of unpredictability of maternal sensory signals (visual, auditory, and tactile) exhibited during the play episode. Infant saliva samples were collected for cortisol analysis before and after inoculation at 12 months., Results: Unpredictable patterns of maternal sensory signals were associated with a blunted infant cortisol response to a painful stressor. This relation persisted after evaluation of covariates including maternal sensitivity and maternal psychological distress., Conclusions: This study provides evidence that unpredictable patterns of maternal sensory signals are one process through which caregiving affects the function of infant stress response systems., (© 2020 Wiley Periodicals, Inc.)

It is generally accepted that relatively more permanent (i.e., more temporally persistent) traits are more valuable for biometric performance than less permanent traits. Although this finding is intuitive, there is no current work identifying exactly where in the biometric analysis temporal persistence makes a difference. In this paper, we answer this question. In a recent report, we introduced the intraclass correlation coefficient (ICC) as an index of temporal persistence for such features. Here, we present a novel approach using synthetic features to study which aspects of a biometric identification study are influenced by the temporal persistence of features. What we show is that using more temporally persistent features produces effects on the similarity score distributions that explain why this quality is so key to biometric performance. The results identified with the synthetic data are largely reinforced by an analysis of two datasets, one based on eye-movements and one based on gait. There was one difference between the synthetic and real data, related to the intercorrelation of features in real data. Removing these intercorrelations for real datasets with a decorrelation step produced results which were very similar to that obtained with synthetic features.

Propensity scores are commonly employed in observational study settings where the goal is to estimate average treatment effects. This paper introduces a flexible propensity score modeling approach, where the probability of treatment is modeled through a Gaussian process framework. To evaluate the effectiveness of the estimated propensity score, a metric of covariate imbalance is developed that quantifies the discrepancy between the distributions of covariates in the treated and control groups. It is demonstrated that this metric is ultimately a function of the hyperparameters of the covariance matrix of the Gaussian process and therefore it is possible to select the hyperparameters to optimize the metric and minimize overall covariate imbalance. The effectiveness of the GP method is compared in a simulation against other methods of estimating the propensity score and the method is applied to data from Dehejia and Wahba (1999) to demonstrate benchmark performance within a relevant policy application.

Background: Early life experiences have persisting influence on brain function throughout life. Maternal signals constitute a primary source of early life experiences, and their quantity and quality during sensitive developmental periods exert enduring effects on cognitive function and emotional and social behaviors. Here we examined if, in addition to established qualitative dimensions of maternal behavior during her interactions with her infant and child, patterns of maternal signals may contribute to the maturation of children's executive functions. We focused primarily on effortful control, a potent predictor of mental health outcomes later in life., Methods: In two independent prospective cohorts in Turku, Finland (N = 135), and Irvine, CA, USA (N = 192) that differed significantly in race/ethnicity and sociodemographic parameters, we assessed whether infant exposure to unpredictable patterns of maternal-derived sensory signals portended poor effortful control., Outcomes: In both the Irvine and Turku cohorts, unpredictable sequences of maternal behavior during infancy were associated with worse effortful control at one year of age. Longitudinal analyses demonstrated that this association persisted for as long as each cohort was assessed-until two years of age in the Turku cohort and to 9.5 years in the Irvine cohort. The relation of unpredictable maternal signals during infancy and the measures of executive function persisted after adjusting for covariates., Interpretations: The consistency of our findings across two cohorts from different demographic backgrounds substantiated the finding that patterns, and specifically unpredictable sequences, of maternal behaviors may influence the development of executive functions which may be associated with vulnerability to subsequent psychopathology. FUND: This research was supported by the National Institutes of Health (NIH) awards P50MH096889, HD051852, NS041298, HD02413, HD050662, HD065823, and by the FinnBrain funders: Academy of Finland (129839, 134950, 253270, 286829, 287908, 308176, 308252), Jane and Aatos Erkko Foundation, Signe and Ane Gyllenberg Foundation, Yrjö Jahnsson Foundation, and State Research Grants (P3498, P3654)., (Copyright © 2019. Published by Elsevier B.V.)

This article summarizes the recommendations on data and methodology issues for studying commercial motor vehicle driver fatigue of a National Academies of Sciences, Engineering, and Medicine study. A framework is provided that identifies the various factors affecting driver fatigue and relating driver fatigue to crash risk and long-term driver health. The relevant factors include characteristics of the driver, vehicle, carrier and environment. Limitations of existing data are considered and potential sources of additional data described. Statistical methods that can be used to improve understanding of the relevant relationships from observational data are also described. The recommendations for enhanced data collection and the use of modern statistical methods for causal inference have the potential to enhance our understanding of the relationship of fatigue to highway safety and to long-term driver health., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Genetic and environmental factors interact during sensitive periods early in life to influence mental health and disease via epigenetic processes such as DNA methylation. However, it is not known if DNA methylation changes outside the brain provide an "epigenetic signature" of early-life experiences. Here, we used a novel intra-individual approach by testing DNA methylation from buccal cells of individual rats before and immediately after exposure to one week of typical or adverse life experience. We find that whereas inter-individual changes in DNA methylation reflect the effect of age, DNA methylation changes within paired DNA samples from the same individual reflect the impact of diverse neonatal experiences. Genes coding for critical cellular metabolic enzymes, ion channels, and receptors were more methylated in pups exposed to the adverse environment, predictive of their repression. In contrast, the adverse experience was associated with less methylation on genes involved in pathways of death and inflammation as well as cell-fate-related transcription factors, indicating their potential up-regulation. Thus, intra-individual methylome signatures indicate large-scale transcription-driven alterations of cellular fate, growth, and function., (© 2019 Jiang et al.)

Increasing evidence indicates that, in addition to poverty, maternal depression, and other well-established factors, unpredictability of maternal and environmental signals early in life influences trajectories of brain development, determining risk for subsequent mental illness. However, whereas most risk factors for later vulnerability to mental illness are readily measured using existing, clinically available tools, there are no similar measures for assessing early-life unpredictability. Here we validate the Questionnaire of Unpredictability in Childhood (QUIC) and examine its associations with mental health in the context of other indicators of childhood adversity (e.g., traumatic life events, socioeconomic status, and parenting quality). The QUIC was initially validated through administration to a cohort of adult females (N = 116) and then further refined in two additional independent cohorts (male Veterans, N = 95, and male and female adolescents, N = 175). The QUIC demonstrated excellent internal (α = 0.89) and test-retest reliability (r = 92). Scores on the QUIC were positively correlated with other prospective indicators of exposures to unpredictable maternal inputs in infancy and childhood (unpredictable maternal mood and sensory signals), and accuracy of recall also was confirmed with prospective data. Importantly, the QUIC predicted symptoms of anxiety, depression, and anhedonia in the three study cohorts, and these effects persisted after adjusting for other previously established risk factors. The QUIC, a reliable and valid self-report assessment of exposure to unpredictability in the social, emotional, and physical domains during early life, is a brief, comprehensive, and promising instrument for predicting risk for mental illness.

Background: This study quantifies the dynamics of maternal mood focusing on unpredictability, and to assess if greater unpredictability of prenatal maternal mood predicts child temperament and internalizing symptoms through early adolescence., Methods: The association between prenatal mood predictability and child internalizing symptoms were assessed in two longitudinal cohorts (N's = 227 and 180). Maternal mood was assessed repeatedly during pregnancy as early as 15 weeks' gestation. Predictability of maternal mood was calculated by applying Shannon's entropy to the distribution of responses on mood questionnaires. Maternal reports of child negative affectivity (a predictor of later internalizing) were collected at 6, 12, 24 months and 7 years of age. Child self-reports of anxiety symptoms were collected at 10 years and reports of depression symptoms at 13 years., Results: Fetal exposure to more elevated maternal mood entropy predicted higher levels of child negative affectivity at 12 months (r = .36; p < 01), 24 months (r = .31; p < 01) and 7 years (r = .32; p < 01) of age. In addition, children exposed to higher prenatal maternal mood entropy, reported higher levels of anxiety symptoms at 10 years (r = .24; p < 01) and elevated depressive symptoms at 13 years (r = .29; p < .01). These associations persisted after adjusting for maternal pre and postnatal mood valence (e.g. depression levels) and for other relevant demographic characteristics., Conclusions: Our findings provide strong support for the notion that patterns of maternal mood influence the developing brain. More specifically, they suggest that prenatal maternal mood predictability may be a critical predictor of developmental mental health trajectories and should be considered when assessing early life influences on lifespan mental health., (Copyright © 2017. Published by Elsevier B.V.)

Anhedonia, the reduced ability to experience pleasure, is a dimensional entity linked to multiple neuropsychiatric disorders, where it is associated with diminished treatment response, reduced global function, and increased suicidality. It has been suggested that anhedonia and the related disruption in reward processing may be critical precursors to development of psychiatric symptoms later in life. Here, we examine cross-species evidence supporting the hypothesis that early life experiences modulate development of reward processing, which if disrupted, result in anhedonia. Importantly, we find that anhedonia may confer risk for later neuropsychiatric disorders, especially posttraumatic stress disorder (PTSD). Whereas childhood trauma has long been associated with increased anhedonia and increased subsequent risk for trauma-related disorders in adulthood, here we focus on an additional novel, emerging direct contributor to anhedonia in rodents and humans: fragmented, chaotic environmental signals ("FRAG") during critical periods of development. In rodents, recent data suggest that adolescent anhedonia may derive from aberrant pleasure/reward circuit maturation. In humans, recent longitudinal studies support that FRAG is associated with increased anhedonia in adolescence. Both human and rodent FRAG exposure also leads to aberrant hippocampal function. Prospective studies are underway to examine if anhedonia is also a marker of PTSD risk. These preliminary cross-species studies provide a critical construct for future examination of the etiology of trauma-related symptoms in adults and for and development of prophylactic and therapeutic interventions. In addition, longitudinal studies of reward circuit development with and without FRAG will be critical to test the mechanistic hypothesis that early life FRAG modifies reward circuitry with subsequent consequences for adolescent-emergent anhedonia and contributes to risk and resilience to trauma and stress in adulthood.

The Function Biomedical Informatics Research Network (FBIRN) developed methods and tools for conducting multi-scanner functional magnetic resonance imaging (fMRI) studies. Method and tool development were based on two major goals: 1) to assess the major sources of variation in fMRI studies conducted across scanners, including instrumentation, acquisition protocols, challenge tasks, and analysis methods, and 2) to provide a distributed network infrastructure and an associated federated database to host and query large, multi-site, fMRI and clinical data sets. In the process of achieving these goals the FBIRN test bed generated several multi-scanner brain imaging data sets to be shared with the wider scientific community via the BIRN Data Repository (BDR). The FBIRN Phase 1 data set consists of a traveling subject study of 5 healthy subjects, each scanned on 10 different 1.5 to 4 T scanners. The FBIRN Phase 2 and Phase 3 data sets consist of subjects with schizophrenia or schizoaffective disorder along with healthy comparison subjects scanned at multiple sites. In this paper, we provide concise descriptions of FBIRN's multi-scanner brain imaging data sets and details about the BIRN Data Repository instance of the Human Imaging Database (HID) used to publicly share the data., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Procedures used for statistical inference are receiving increased scrutiny as the scientific community studies the factors associated with insuring reproducible research. This note addresses recent negative attention directed at p values, the relationship of confidence intervals and tests, and the role of Bayesian inference and Bayes factors, with an eye toward better understanding these different strategies for statistical inference. We argue that researchers and data analysts too often resort to binary decisions (e.g., whether to reject or accept the null hypothesis) in settings where this may not be required.

In this issue, the lead article proposes that e-health technologies should be used more broadly and that patients should have greater access to their information through such technologies. The Canadian Medical Protective Association (CMPA) agrees with this statement and suggests that to facilitate the timely and appropriate adoption of new technologies among healthcare providers to enhance patient care, barriers in the existing regulatory, legislative and legal frameworks must be addressed. While much of the discussion to date on e-health has focused primarily on high-level issues regarding regulatory compliance, "privacy by design" and the e-health "panacea," CMPA suggests that there needs to be a refocus on achieving more concrete change and gains through consideration of the specific impact on the drivers of healthcare delivery. An integrated or holistic approach is required involving healthcare providers, regulators, legislators, stakeholders, ministries of health, privacy commissioners and the courts. To better leverage potential advantages, efficiencies and enhanced, safer care for our healthcare system, all parties must work together to develop an acceptable and flexible approach to the "appropriate use" of e-health technologies that will facilitate adoption by healthcare professionals in a manner that is consistent with the expectations of the profession and applicable standards of practice.

We propose a hierarchical Bayesian model for analyzing multi-site experimental fMRI studies. Our method takes the hierarchical structure of the data (subjects are nested within sites, and there are multiple observations per subject) into account and allows for modeling between-site variation. Using posterior predictive model checking and model selection based on the deviance information criterion (DIC), we show that our model provides a good fit to the observed data by sharing information across the sites. We also propose a simple approach for evaluating the efficacy of the multi-site experiment by comparing the results to those that would be expected in hypothetical single-site experiments with the same sample size.

This report provides practical recommendations for the design and execution of multicenter functional MRI (MC-fMRI) studies based on the collective experience of the Function Biomedical Informatics Research Network (FBIRN). The study was inspired by many requests from the fMRI community to FBIRN group members for advice on how to conduct MC-fMRI studies. The introduction briefly discusses the advantages and complexities of MC-fMRI studies. Prerequisites for MC-fMRI studies are addressed before delving into the practical aspects of carefully and efficiently setting up a MC-fMRI study. Practical multisite aspects include: (i) establishing and verifying scan parameters including scanner types and magnetic fields, (ii) establishing and monitoring of a scanner quality program, (iii) developing task paradigms and scan session documentation, (iv) establishing clinical and scanner training to ensure consistency over time, (v) developing means for uploading, storing, and monitoring of imaging and other data, (vi) the use of a traveling fMRI expert, and (vii) collectively analyzing imaging data and disseminating results. We conclude that when MC-fMRI studies are organized well with careful attention to unification of hardware, software and procedural aspects, the process can be a highly effective means for accessing a desired participant demographics while accelerating scientific discovery., (Copyright © 2012 Wiley Periodicals, Inc.)

Objective: This study investigated the relation between genetic variations in the dopamine system and facial expression recognition., Methods: A sample of Chinese college students (n = 478) was given a facial expression recognition task. Subjects were genotyped for 98 loci [96 single-nucleotide polymorphisms (SNPs) and 2 variable number tandem repeats] in 16 genes involved in the dopamine neurotransmitter system, including its 4 subsystems: synthesis (TH, DDC, and DBH), degradation/transport (COMT,MAOA,MAOB, and SLC6A3), receptors (DRD1,DRD2,DRD3,DRD4, and DRD5), and modulation (NTS,NTSR1,NTSR2, and NLN). To quantify the total contributions of the dopamine system to emotion recognition, we used a series of multiple regression models. Permutation analyses were performed to assess the posterior probabilities of obtaining such results., Results: Among the 78 loci that were included in the final analyses (after excluding 12 SNPs that were in high linkage disequilibrium and 8 that were not in Hardy-Weinberg equilibrium), 1 (for fear), 3 (for sadness), 5 (for anger), 13 (for surprise), and 15 (for disgust) loci exhibited main effects on the recognition of facial expressions. Genetic variations in the dopamine system accounted for 3% for fear, 6% for sadness, 7% for anger, 10% for surprise, and 18% for disgust, with the latter surviving a stringent permutation test., Conclusions: Genetic variations in the dopamine system (especially the dopamine synthesis and modulation subsystems) made significant contributions to individual differences in the recognition of disgust faces., (Copyright © 2012 S. Karger AG, Basel.)

Conclusion: Despite limitations arising from a questionnaire-performed study, it seems that nonspecific physical activity can protect against benign paroxysmal positional vertigo (BPPV), possibly by relocating loosened otoconia from the semicircular canals., Objectives: Mechanical factors might play a role in the onset of the idiopathic form of BPPV. We performed a structured questionnaire study of physical activity in patients with BPPV and controls., Methods: Sixty-three consecutive patients with idiopathic BPPV participated in the study. Their mean age was 59.2 ± 14.5 years; 14 were men and 49 were women. Sixty-four age- and sex-matched generally healthy individuals served as controls. Levels of physical activity were assessed by the PASE questionnaire, which consists of 12 items quantifying physical activity during leisure, household, and occupational activities over a 7-day period., Results: The total physical score activity was significantly lower in BPPV patients than in controls. Differences were found mainly in household and leisure activity, while occupational activity was similar in both groups, regardless of gender. Patients older than 60 years had significantly lower PASE scores than controls, whereas patients aged 60 years or younger reported similar physical activity to controls. No differences were found between physical activity scores in different types of BPPV or in patients with a first versus recurrent attack of vertigo.

Methylmercury data from walleye fillets collected by multiple agencies from northern Wisconsin lakes from 1982 to 2005 were examined for regional time trends. Hierarchical Bayesian methods were used to model dependencies and provide probability statements for parameters pertaining to individual lakes and the region as a whole. A missing data mechanism allowed the sex of the fish to be included as a predictor since the sexes grow at different rates. A slight regional decrease in methylmercury of 0.60% annually was found, consistent with declining atmospheric mercury deposition. Methylmercury was estimated to have decreased in 77% of the 420 lakes from which walleye were sampled, although uncertainty regarding time trends was greater for most individual lakes than for the region as a whole. Methylmercury in walleye varied widely from lake to lake, but generally accumulated in the fish at similar rates by length after accounting for differences in sex. Slower-growing male walleye had higher methylmercury concentrations than females for a given length, and skin-on fillets were 16% lower in methylmercury than skin-off fillets.

I. Klugkist, O. Laudy, and H. Hoijtink (2005) presented a Bayesian approach to analysis of variance models with inequality constraints. Constraints may play 2 distinct roles in data analysis. They may represent prior information that allows more precise inferences regarding parameter values, or they may describe a theory to be judged against the data. In the latter case, the authors emphasized the use of Bayes factors and posterior model probabilities to select the best theory. One difficulty is that interpretation of the posterior model probabilities depends on which other theories are included in the comparison. The posterior distribution of the parameters under an unconstrained model allows one to quantify the support provided by the data for inequality constraints without requiring the model selection framework., (copyright 2006 APA, all rights reserved.)

Electronic swine feeders are used to automatically measure individual feed intake on group-housed pigs, but the resulting data contain errors caused by feeder malfunctions and animal-feeder interactions. The objectives of this study were to 1) develop criteria to identify errors in data from an electronic feeder that is predominant in the United States; 2) evaluate the frequency of errors in data from three consecutive experiments using the same feeders; and 3) identify factors associated with errors. Across experiments, data included 1,878,321 feed intake records (visits) on 1,721 pigs and 124 pens. Sixteen criteria were developed to detect errors in seven variables related to feed trough weights and times. Logistic regression was used to identify factors associated with the presence or absence of each error type in identified visits (visits where the feeder recognized a transponder) using a model that included the fixed effects of replicate, sex, linear and quadratic effects of day on test, and random effects of feeder within replicate, pig within feeder within replicate, test day within replicate, and week within feeder within replicate. Frequencies of error types in identified visits varied considerably within and between experiments. Errors in feed trough weights were more frequent than errors in time. Percentage of identified visits and of daily feed intake records with at least one error ranged from 4.3 to 18.7% and from 17.2 to 50.0%, respectively, and decreased from the first to the last experiment, reflecting the increasing ability of the managers to operate the feeders. Replicate, sex, test day, feeder within replicate, pig, and day within replicate affected the number of errors that occurred, but their effect varied among error types. Week-to-week variation within a feeder and replicate had the largest effect on number of errors, which was likely associated with feeder management. Results indicate that the frequency of errors in data from electronic swine feeders is substantial, but visits with errors can be identified and their frequency can be decreased by proper feeder management.