The biobehavioral family model and the family relational assessment protocol: Map and GPS for family systems training

The Biobehavioral Family Model (BBFM) was developed and evolved as a heuristic research model to support the investigation of pathways by which family relational function impacts individual family member wellbeing and disorder. Recently, the BBFM and its related assessment approach, the Family Relational Process Assessment Protocol (FRAP), have emerged as tools for clinical practice and training. The BBFM model will be presented, along with definitions of the dimensions constructed in the model, and research evidence in support of the model. To illustrate how the BBFM and FRAP are used in training, instructions for conducting the FRAP will be presented. Then, transcripts from two contrasting families participating in one of the interaction tasks will illustrate how, in training, the FRAP is interpreted through the BBFM lens to illuminate how these patterns of family relationship impact the identified patient. Finally, three applications of this training approach will exemplify the use of the BBFM and FRAP in the context of a Child and Adolescent Psychiatry Fellowship, a Family Medicine Fellowship, and a Family Therapy Training Program in Istanbul, Turkey. Limitations and future directions for the application of the BBFM in the exploration of multicultural aspects of family function for clinical and training purposes will be discussed.

Mechanisms of improved body composition among perimenopausal women practicing Meditative Movement: a proposed biobehavioral model

OBJECTIVES

Weight gain and unfavorable body composition are prevalent among midlife/older women throughout menopause. These shifts may negatively impact health, well-being, and longevity. Efforts to attenuate weight and body composition changes are traditionally driven by manipulation of diet and/or exercise; however, sustained results are limited, possibly because the full spectrum of biobehavioral systems is not addressed by diet and exercise alone. We propose a biobehavioral model detailing mechanisms of body composition decline among perimenopausal women and the associated components of Meditative Movement (ie, tai chi, qigong, yoga) that address each of these factors.

METHODS

Based on our previous work and extensive review of the literature, we developed a multifactorial and multidimensional biobehavioral model including factors that most directly relate to body composition among perimenopausal women: 1) psychological (ie, stress and mood, mindfulness and self-compassion, body awareness), 2) behavioral (ie, sleep, physical activity, eating behaviors), and 3) physiological (ie, cortisol, estrogen). Relationships between each factor, Meditative Movement practice components, and predicted effects on body composition were explored in detail.

RESULTS

Our model describes select psychological, behavioral, and physiological factors, and potential mechanistic pathways of Meditative Movement practice driving improved changes in body composition and weight outcomes for perimenopausal women.

CONCLUSIONS

The proposed model details a novel, evidence-supported means to reduce the risk of deleterious shifts in body composition throughout perimenopause and menopause thereafter. We suggest that these changes may occur directly and/or indirectly through psychological, behavioral, and physiological mechanisms that facilitate the desired changes in body composition.

Testing a Biobehavioral Model of Food Insecurity and Chronic Disease in Hispanic Older Adolescents

The biobehavioral model of food insecurity and chronic disease posits that stress perpetuates the cycle of food insecurity and chronic disease, in part, through changes in eating behaviors and weight gain. The current study conducted a preliminary test of the biobehavioral model in a sample of Hispanic older adolescents. It was hypothesized that older adolescents experiencing food insecurity would report greater depressive symptoms, which would be associated with more disordered eating, which would be associated with worse cardiometabolic indicators. Hispanic older adolescents (N = 113; 60% female; 15-21 years with mean age of 19.1; BMImean = 24.4) completed self-report baseline measures of food insecurity, depression, and disordered eating behaviors as part of a larger experimental study. Anthropometrics and body composition, blood pressure, heart rate, and resting metabolic rate were objectively measured. Hypotheses were tested using structural equation modeling. Experiencing food insecurity was associated with more disordered eating (b = 2.20, p = 0.032). Greater depressive symptoms were associated with more disordered eating (b = 0.28, p = 0.025) and worse cardiometabolic indicators (b = 0.15, p = 0.017). The full biobehavioral model, however, was not supported. Findings underscore the complex interaction of social and psychological functioning and physical health.

An application of the Biobehavioral Family Model: Examining the impact of maternal depression on child asthma mediated by insecure attachment and child depression

OBJECTIVE

Child asthma disparities are prevalent in socio-economically stressed single-parent families. Stress impacts childhood asthma mediated by immune and autonomic pathways, but specific family stress pathways are not well established. This study tests the hypothesis, derived from a version of the Biobehavioral Family Model, that single parent maternal depression impacts child asthma mediated by insecure attachment and child depression.

METHODS

In a cross-sectional study, children with asthma (age 7-17 years old) from a socio-economically disadvantaged population and their single parent mothers (N = 202) were assessed for depression and attachment security. Child asthma disease activity was assessed by symptom report and lung function tests. Structural equation modeling (SEM) was used to test a model in which caregiver depression impacts child asthma disease activity mediated by insecure attachment and child depression.

RESULTS

SEM results indicated that maternal depression statistically predicted child depression (β = 0.21, p < 0.01) and insecure mother-child attachment (β = 0.17, p < 0.05). In addition, insecure attachment statistically predicted child depression (β = 0.50, p < 0.001). Child depression mediated the adverse effects of maternal depression and insecure attachment on child asthma disease activity (β = 0.43, p < 0.01). There was no direct effect of insecure attachment on child asthma.

CONCLUSION

In single-parent families, maternal depression may impact child asthma disease activity, mediated serially by insecure attachment and child depression. Longitudinal and/or intervention studies are needed to establish a causal effect. These findings suggest that caregiver depression and parent-child relationships may be important targets for family intervention. These interventions may help improve child asthma outcomes and reduce health disparities.

A jury of scientists: Formal education in biobehavioral sciences reduces the odds of punitive criminal sentencing

This study examines how formal education in biological and behavioral sciences may impact punishment intuitions (views on criminal sentencing, free will, responsibility, and dangerousness) in cases involving neurobiological evidence. In a survey experiment, we compared intuitions between biobehavioral science and non-science university graduates by presenting them with a baseline case without a neurobiological explanation for offending followed by one of two cases with a neurobiological explanation (described as either innate or acquired biological influences to offending). An ordinal logistic regression indicated that both science and non-science graduates selected significantly more severe punishments for the baseline case as compared to when an innate neurobiological explanation for offending was provided. However, across all cases, science graduates selected significantly less severe sentences than non-science graduates, and only science graduates' decisions were mediated by free will and responsibility attributions. Findings are discussed in relation to scientific understandings of behavior, the impact of science education on attitudes towards punishment, and potential criminal-legal implications.

Childhood maltreatment and its role in the development of pain and psychopathology

Childhood maltreatment represents a form of trauma capable of altering fundamental neurobiological properties and negatively impacting neurodevelopmental processes. An outcome of childhood maltreatment is the emergence of psychopathology, which might become evident during childhood or adolescence, but might also project into adulthood. In this Review, we propose a biobehavioural framework in which childhood maltreatment and the associated aberrant neurobiological mechanisms and behavioural processes additionally lead to the onset of altered pain processing and, ultimately, the existence of pain syndromes. Considering that subpopulations of maltreated children show preserved function and minimal psychiatric or pain symptoms, compensatory mechanisms-perhaps instilled by robust psychosocial support systems-are also discussed. We present validated tools and experimental methods that could facilitate better comprehension of the interactions between childhood maltreatment, psychopathology, and pain. Such tools and approaches can in parallel be implemented to monitor abnormal pain-related processes and potentially guide early intervention strategies in cases of childhood maltreatment.

Bisdemethoxycurcumin Induces Cell Apoptosis and Inhibits Human Brain Glioblastoma GBM 8401/Luc2 Cell Xenograft Tumor in Subcutaneous Nude Mice In Vivo

Bisdemethoxycurcumin (BDMC) has biological activities, including anticancer effects in vitro; however, its anticancer effects in human glioblastoma (GBM) cells have not been examined yet. This study aimed to evaluate the tumor inhibitory effect and molecular mechanism of BDMC on human GBM 8401/luc2 cells in vitro and in vivo. In vitro studies have shown that BDMC significantly reduced cell viability and induced cell apoptosis in GBM 8401/luc2 cells. Furthermore, BDMC induced apoptosis via inhibited Bcl-2 (anti-apoptotic protein) and increased Bax (pro-apoptotic proteins) and cytochrome c release in GBM 8401/luc2 cells in vitro. Then, twelve BALB/c-nude mice were xenografted with human glioblastoma GBM 8401/luc2 cancer cells subcutaneously, and the xenograft nude mice were treated without and with BDMC (30 and 60 mg/kg of BDMC treatment) every 3 days. GBM 8401/luc2 cell xenografts experiment showed that the growth of the tumors was significantly suppressed by BDMC administration at both doses based on the reduction of tumor size and weights. BDMC did not change the body weight and the H&E histopathology analysis of liver samples, indicating that BDMC did not induce systemic toxicity. Meanwhile, treatment with BDMC up-regulated the expressions of BAX and cleaved caspase-3, while it down-regulated the protein expressions of Bcl-2 and XIAP in the tumor tissues compared with the control group. This study has demonstrated that BDMC presents potent anticancer activity on the human glioblastoma GBM 8401/luc2 cell xenograft model by inducing apoptosis and inhibiting tumor cell proliferation and shows the potential for further development to the anti-GBM cancer drug.

Non-invasive quantification of the mitochondrial redox state in livers during machine perfusion

Ischemia reperfusion injury (IRI) is a critical problem in liver transplantation that can lead to life-threatening complications and substantially limit the utilization of livers for transplantation. However, because there are no early diagnostics available, fulminant injury may only become evident post-transplant. Mitochondria play a central role in IRI and are an ideal diagnostic target. During ischemia, changes in the mitochondrial redox state form the first link in the chain of events that lead to IRI. In this study we used resonance Raman spectroscopy to provide a rapid, non-invasive, and label-free diagnostic for quantification of the hepatic mitochondrial redox status. We show this diagnostic can be used to significantly distinguish transplantable versus non-transplantable ischemically injured rat livers during oxygenated machine perfusion and demonstrate spatial differences in the response of mitochondrial redox to ischemia reperfusion. This novel diagnostic may be used in the future to predict the viability of human livers for transplantation and as a tool to better understand the mechanisms of hepatic IRI.

Correlates of attendance at community engagement meetings held in advance of bio-behavioral research studies: A longitudinal, sociocentric social network study in rural Uganda

BACKGROUND

Community engagement is central to the conduct of health-related research studies as a way to determine priorities, inform study design and implementation, increase recruitment and retention, build relationships, and ensure that research meets the goals of the community. Community sensitization meetings, a form of community engagement, are often held prior to the initiation of research studies to provide information about upcoming study activities and resolve concerns in consultation with potential participants. This study estimated demographic, health, economic, and social network correlates of attendance at community sensitization meetings held in advance of a whole-population, combined behavioral, and biomedical research study in rural Uganda.

METHODS AND FINDINGS

Research assistants collected survey data from 1,630 adults participating in an ongoing sociocentric social network cohort study conducted in a rural region of southwestern Uganda. These community survey data, collected between 2016 and 2018, were linked to attendance logs from community sensitization meetings held in 2018 and 2019 before the subsequent community survey and community health fair. Of all participants, 264 (16%) attended a community sensitization meeting before the community survey, 464 (28%) attended a meeting before the community health fair, 558 (34%) attended a meeting before either study activity (survey or health fair), and 170 (10%) attended a meeting before both study activities (survey and health fair). Using multivariable Poisson regression models, we estimated correlates of attendance at community sensitization meetings. Attendance was more likely among study participants who were women (adjusted relative risk [ARR]health fair = 1.71, 95% confidence interval [CI], 1.32 to 2.21, p < 0.001), older age (ARRsurvey = 1.02 per year, 95% CI, 1.01 to 1.02, p < 0.001; ARRhealth fair = 1.02 per year, 95% CI, 1.01 to 1.02, p < 0.001), married (ARRsurvey = 1.74, 95% CI, 1.29 to 2.35, p < 0.001; ARRhealth fair = 1.41, 95% CI, 1.13 to 1.76, p = 0.002), and members of more community groups (ARRsurvey = 1.26 per group, 95% CI, 1.10 to 1.44, p = 0.001; ARRhealth fair = 1.26 per group, 95% CI, 1.12 to 1.43, p < 0.001). Attendance was less likely among study participants who lived farther from meeting locations (ARRsurvey = 0.54 per kilometer, 95% CI, 0.30 to 0.97, p = 0.041; ARRhealth fair = 0.57 per kilometer, 95% CI, 0.38 to 0.86, p = 0.007). Leveraging the cohort's sociocentric design, social network analyses suggested that information conveyed during community sensitization meetings could reach a broader group of potential study participants through attendees' social network and household connections. Study limitations include lack of detailed data on reasons for attendance/nonattendance at community sensitization meetings; achieving a representative sample of community members was not an explicit aim of the study; and generalizability may not extend beyond this study setting.

CONCLUSIONS

In this longitudinal, sociocentric social network study conducted in rural Uganda, we observed that older age, female sex, being married, membership in more community groups, and geographical proximity to meeting locations were correlated with attendance at community sensitization meetings held in advance of bio-behavioral research activities. Information conveyed during meetings could have reached a broader portion of the population through attendees' social network and household connections. To ensure broader input and potentially increase participation in health-related research studies, the dissemination of research-related information through community sensitization meetings may need to target members of underrepresented groups.

Deviations in criminal filings of child abuse and neglect during COVID-19 from forecasted models: An analysis of the state of Oklahoma, USA

BACKGROUND

The COVID-19 pandemic has contributed to risk factors for child abuse and neglect and disrupted conventional abuse surveillance.

OBJECTIVE

The goal of this study was to assess how counts of criminal charges have been affected by COVID-19 social distancing measures and related policy changes.

PARTICIPANTS AND SETTING

This study used publicly available court filings pertaining to child abuse and neglect from Jan 1, 2010 to June 30, 2020.

METHODS

Autoregressive integrated moving average (ARIMA) algorithms were constructed with case data from January 2010 to January 2020 to forecast trends in criminal charges for February to June 2020. These forecasted values were then compared to actual charges filed for this time period.

RESULTS

Criminal cases filed between February and June 2020, had an overall 25.7 percent lower average than forecasted. All individual months had progressively lower cases than forecasted with the exception of March. June had the largest deviation from forecasted with 60.1 percent fewer cases than predicted.

CONCLUSIONS

Although risk factors for child abuse have increased due to COVID-19, these findings demonstrate a declining trend in child abuse charges. Rather than a decreasing incidence of child abuse and neglect, it is more likely that less cases are being reported. The results warrant immediate action and further investigation in order to address the dangers this pandemic poses for children in abusive situations.

Cognitive bias analysis of young novice drivers' observation abilities-A questionnaire-based study

Observation ability, which is the basis of following decision-making and vehicle manipulation behaviour, is of great importance while driving. However, the subject self-cognition and objective assessment of driving ability are usually different, especially for the young novice drivers. In this paper, drivers' observation abilities for both static traffic signs and markings and dynamic surrounding vehicles were investigated based on questionnaire data. Effects of gender and driving characteristics (driving year, driving frequency, driving time) on drivers' observation abilities were verified by ANOVA analysis and structural equation model (SEM) from two aspects: drivers' self-assessment scores (self-assessment) and mutual assessment scores (evaluated by others). Significant difference could be found between all the factors and drivers' self-assessment scores, while only driving year had a significant effect on drivers' mutual assessment scores. Besides, cognitive bias was found between all the driving year groups. It seemed that drivers with driving experience less than one year were always overconfident with their driving abilities. And drivers with driving experience more than three years usually gave the most conservative assessment scores for themselves and others. With more exposures to various traffic conditions, experienced drivers are more aware of their limitations on observing surrounding information, while young novice drivers still not realized their limitations on observing traffic signs and other vehicles in a right way.

The model crisis, or how to have critical promiscuity in the time of Covid-19

During the past forty years, statistical modelling and simulation have come to frame perceptions of epidemic disease and to determine public health interventions that might limit or suppress the transmission of the causative agent. The influence of such formulaic disease modelling has pervaded public health policy and practice during the Covid-19 pandemic. The critical vocabulary of epidemiology, and now popular debate, thus includes R₀, the basic reproduction number of the virus, 'flattening the curve', and epidemic 'waves'. How did this happen? What are the consequences of framing and foreseeing the pandemic in these modes? Focusing on historical and contemporary disease responses, primarily in Britain, I explore the emergence of statistical modelling as a 'crisis technology', a reductive mechanism for making rapid decisions or judgments under uncertain biological constraint. I consider how Covid-19 might be configured or assembled otherwise, constituted as a more heterogeneous object of knowledge, a different and more encompassing moment of truth - not simply as a measured telos directing us to a new normal. Drawing on earlier critical engagements with the AIDS pandemic, inquiries into how to have 'theory' and 'promiscuity' in a crisis, I seek to open up a space for greater ecological, sociological, and cultural complexity in the biopolitics of modelling, thereby attempting to validate a role for critique in the Covid-19 crisis.

The biopsychosocial-digital continuum of foot orthosis practice and research: the VALUATOR model

Foot orthoses have been used for decades despite uncertainty surrunding their therapeutic efficacy. Orthoses have been used exclusively to affect neuro-biomechanical input and outcome variables, however, there is emerging evidence that therapeutic efficacy may be affected by a psychological stimulus. Critical appraisal of the literature highlights that there is no holistic model upon which foot orthosis practice is taught, practised nor investigated. This paper introduces a conceptual model of foot orthosis practice (Value Based Foot Orthosis Practice (VALUATOR) model) that embraces a broader range of factors that are pertinent to orthosis practice, incorporating contemporary health service behaviours and values into orthosis practice for the first time.Within the VALUATOR model, foot orthosis design and clinical value is considered along a bio-psycho-social-digital continuum that reflects the reality of foot orthosis practice. The model contextualises the variable outcomes that are observed in research and practice within 6 key areas: 1) value, 2) person-centered approach, 3) zone of optimal bio-psycho-social stress, 4) bio-psycho-social assessment, 5) monitoring, 6) primary and secondary clinical strategies.The VALUATOR model is targeted at students, lecturers, scientists and practitioners and includes carefully chosen terminology to support a robust basis for educational and scientific discussion. It is believed that it provides a contemporary viewpoint and a structured conceptual metaphor that builds on existing evidence from a wide range of sources, invites constructive intellectual debate, and is anchored in the experiences of practitioners too. Stress testing the VALUATOR model will help determine its model and support further developments and evolution of orthotic practice in a evidence based way.

A review of current strategies to improve HIV prevention and treatment in sexual and gender minority Latinx (SGML) communities

INTRODUCTION

The HIV epidemic continues to disproportionately impact sexual and gender minority Latinxs (SGML). Several syndemic conditions have been linked with HIV acquisition and transmission among SGML including immigration, discrimination, environmental racism, substance use, and mental health.

AREAS COVERED

We provide a summary of biomedical, behavioral, and social/structural interventions to reduce risks for acquiring HIV and improve outcomes along the HIV care continuum among SGML. We also discuss intervention approaches and opportunities that respond at the intersection of HIV and COVID-19 prevention and treatment.

EXPERT OPINION

There is a dire need for the combination of biomedical, behavioral, and social/structural interventions to reduce risks for acquiring HIV and improve outcomes along the HIV care continuum. Interventions and combination approaches should be driven by community-based participatory action research. The inclusion of community members in all stages of the research process can assure successful implementation of program activities and deliverables, including the provision of culturally and linguistically appropriate services. Given the current COVID-19 pandemic, which is disproportionately impacting individuals living with HIV and other comorbidities, the elderly, and under-resourced communities with a ferocity not seen in other communities, intervention approaches that respond at the intersection of HIV and COVID-19 prevention and treatment are also urgently needed.

Etiological Overlap Between Sex Under the Influence and Number of Lifetime Sexual Partners

Drug and alcohol use is associated with risky sexual behavior (RSB). It is unclear whether this association is due to correlated liabilities (e.g., third variables influencing both traits), or whether use of drugs and alcohol during sexual decision making increases RSB. This study addresses this question by fitting a series of biometrical models using over 800 twin pairs assessed in early adulthood (m = 25.21 years). Measures included an index of sex under the influence (e.g., frequency that drugs or alcohol affect sexual decision making), number of lifetime sexual partners, and a general measure of substance use. Analyses suggest the covariance among these measures is explained by both genetic and environmental correlated liabilities. The overlap was not specific to sex under the influence, but was shared with a measure of general substance use. Models testing necessary but not sufficient parameters for direction of causation suggest that sex under the influence is unlikely to cause an increase in RSB; more evidence for reverse causation was found.

Development of a Testing Funnel for Identification of Small-Molecule Modulators Targeting Secretin Receptors

The secretin receptor (SCTR), a prototypical class B G protein-coupled receptor (GPCR), exerts its effects mainly by activating Gαs proteins upon binding of its endogenous peptide ligand secretin. SCTRs can be found in a variety of tissues and organs across species, including the pancreas, stomach, liver, heart, lung, colon, kidney, and brain. Beyond that, modulation of SCTR-mediated signaling has therapeutic potential for the treatment of multiple diseases, such as heart failure, obesity, and diabetes. However, no ligands other than secretin and its peptide analogs have been described to regulate SCTRs, probably due to inherent challenges in family B GPCR drug discovery. Here we report creation of a testing funnel that allowed targeted detection of SCTR small-molecule activators. Pursuing the strategy to identify positive allosteric modulators (PAMs), we established a unique primary screening assay employing a mixture of three orthosteric stimulators that was compared in a screening campaign testing 12,000 small-molecule compounds. Beyond that, we developed a comprehensive set of secondary assays, such as a radiolabel-free target engagement assay and a NanoBiT (NanoLuc Binary Technology)-based approach to detect β-arrestin-2 recruitment, all feasible in a high-throughput environment as well as capable of profiling ligands and hits regarding their effect on binding and receptor function. This combination of methods enabled the discovery of five promising scaffolds, four of which have been validated and further characterized with respect to their allosteric activities. We propose that our results may serve as starting points for developing the first in vivo active small molecules targeting SCTRs.

Values encoded in orbitofrontal cortex are causally related to economic choices

In the eighteenth century, Daniel Bernoulli, Adam Smith and Jeremy Bentham proposed that economic choices rely on the computation and comparison of subjective values1. This hypothesis continues to inform modern economic theory2 and research in behavioural economics3, but behavioural measures are ultimately not sufficient to verify the proposal4. Consistent with the hypothesis, when agents make choices, neurons in the orbitofrontal cortex (OFC) encode the subjective value of offered and chosen goods5. Value-encoding cells integrate multiple dimensions6-9, variability in the activity of each cell group correlates with variability in choices10,11 and the population dynamics suggests the formation of a decision12. However, it is unclear whether these neural processes are causally related to choices. More generally, the evidence linking economic choices to value signals in the brain13-15 remains correlational16. Here we show that neuronal activity in the OFC is causal to economic choices. We conducted two experiments using electrical stimulation in rhesus monkeys (Macaca mulatta). Low-current stimulation increased the subjective value of individual offers and thus predictably biased choices. Conversely, high-current stimulation disrupted both the computation and the comparison of subjective values, and thus increased choice variability. These results demonstrate a causal chain linking subjective values encoded in OFC to valuation and choice.

3D printing of bioreactors in tissue engineering: A generalised approach

3D printing is a rapidly evolving field for biological (bioprinting) and non-biological applications. Due to a high degree of freedom for geometrical parameters in 3D printing, prototype printing of bioreactors is a promising approach in the field of Tissue Engineering. The variety of printers, materials, printing parameters and device settings is difficult to overview both for beginners as well as for most professionals. In order to address this problem, we designed a guidance including test bodies to elucidate the real printing performance for a given printer system. Therefore, performance parameters such as accuracy or mechanical stability of the test bodies are systematically analysed. Moreover, post processing steps such as sterilisation or cleaning are considered in the test procedure. The guidance presented here is also applicable to optimise the printer settings for a given printer device. As proof of concept, we compared fused filament fabrication, stereolithography and selective laser sintering as the three most used printing methods. We determined fused filament fabrication printing as the most economical solution, while stereolithography is most accurate and features the highest surface quality. Finally, we tested the applicability of our guidance by identifying a printer solution to manufacture a complex bioreactor for a perfused tissue construct. Due to its design, the manufacture via subtractive mechanical methods would be 21-fold more expensive than additive manufacturing and therefore, would result in three times the number of parts to be assembled subsequently. Using this bioreactor we showed a successful 14-day-culture of a biofabricated collagen-based tissue construct containing human dermal fibroblasts as the stromal part and a perfusable central channel with human microvascular endothelial cells. Our study indicates how the full potential of biofabrication can be exploited, as most printed tissues exhibit individual shapes and require storage under physiological conditions, after the bioprinting process.

SE-stacking: Improving user purchase behavior prediction by information fusion and ensemble learning

Online shopping behavior has the characteristics of rich granularity dimension and data sparsity and presents a challenging task in e-commerce. Previous studies on user behavior prediction did not seriously discuss feature selection and ensemble design, which are important to improving the performance of machine learning algorithms. In this paper, we proposed an SE-stacking model based on information fusion and ensemble learning for user purchase behavior prediction. After successfully using the ensemble feature selection method to screen purchase-related factors, we used the stacking algorithm for user purchase behavior prediction. In our efforts to avoid the deviation of the prediction results, we optimized the model by selecting ten different types of models as base learners and modifying the relevant parameters specifically for them. Experiments conducted on a publicly available dataset show that the SE-stacking model can achieve a 98.40% F1 score, approximately 0.09% higher than the optimal base models. The SE-stacking model not only has a good application in the prediction of user purchase behavior but also has practical value when combined with the actual e-commerce scene. At the same time, this model has important significance in academic research and the development of this field.

Network structure reveals clusters of associations between childhood adversities and development outcomes

Exposure to childhood adversity is common and associated with a host of negative developmental outcomes. The most common approach used to examine the consequences of adversity exposure is a cumulative risk model. Recently, we have proposed a novel approach, the dimensional model of adversity and psychopathology (DMAP), where different dimensions of adversity are hypothesized to impact health and well-being through different pathways. We expect deprivation to primarily disrupt cognitive processing, whereas we expect threat to primarily alter emotional reactivity and automatic regulation. Recent hypothesis-driven approaches provide support for these differential associations of deprivation and threat on developmental outcomes. However, it is not clear whether these patterns would emerge using data-driven approaches. Here we use a network analytic approach to identify clusters of related adversity exposures and outcomes in an initial study (Study 1: N = 277 adolescents aged 16-17 years; 55.1% female) and a replication (Study 2: N = 262 children aged 8-16 years; 45.4% female). We statistically compare our observed clusters with our hypothesized DMAP model and a clustering we hypothesize would be the result of a cumulative stress model. In both samples we observed a network structure consistent with the DMAP model and statistically different than the hypothesized cumulative stress model. Future work seeking to identify in the pathways through which adversity impacts development should consider multiple dimensions of adversity.

Neural Correlates of the Dual-Pathway Model for ADHD in Adolescents

OBJECTIVE

The dual-pathway model has been proposed to explain the heterogeneity in symptoms of attention deficit hyperactivity disorder (ADHD) by two independent psychological pathways based on distinct brain circuits. The authors sought to test whether the hypothesized cognitive and motivational pathways have separable neural correlates.

METHODS

In a longitudinal community-based cohort of 1,963 adolescents, the neuroanatomical correlates of ADHD were identified by a voxel-wise association analysis and then validated using an independent clinical sample (99 never-medicated patients with ADHD, 56 medicated patients with ADHD, and 267 healthy control subjects). The cognitive and motivational pathways were assessed by neuropsychological tests of working memory, intrasubject variability, stop-signal reaction time, and delay discounting. The associations were tested between the identified neuroanatomical correlates and both ADHD symptoms 2 years later and the polygenic risk score for ADHD.

RESULTS

Gray matter volumes of both a prefrontal cluster and a posterior occipital cluster were negatively associated with inattention. Compared with healthy control subjects, never-medicated patients, but not medicated patients, had significantly lower gray matter volumes in these two clusters. Working memory and intrasubject variability were associated with the posterior occipital cluster, and delay discounting was independently associated with both clusters. The baseline gray matter volume of the posterior occipital cluster predicted the inattention symptoms in a 2-year follow-up and was associated with the genetic risk for ADHD.

CONCLUSIONS

The dual-pathway model has both shared and separable neuroanatomical correlates, and the shared correlate in the occipital cortex has the potential to serve as an imaging trait marker of ADHD, especially the inattention symptom domain.

Developing a Stopover-CORT hypothesis: Corticosterone predicts body composition and refueling rate in Gray Catbirds during migratory stopover

Migratory flight is energetically challenging, requiring alternating phases of fuel catabolism and fuel accumulation, accompanied by dramatic changes in body composition and behavior. Baseline corticosterone (CORT; the primary glucocorticoid in birds) is thought to underlie transitions between fuel catabolism during flight, fuel deposition during stopover, and the initiation of migratory flight. However, studies of CORT on stopover physiology and behavior remain disparate efforts, lacking the cohesion of a general hypothesis. Here we develop a Stopover-CORT hypothesis formalizing the relationships among CORT, body condition, and refueling rate in migratory birds. First we expect body mass to increase with triglycerides (TRIG) as birds refuel. Second, based on a synthesis of previous literature, we predict a U-shaped CORT curve over the course of stopover, postulating that elevated CORT at arrival is reactive, responding to poor body condition, while CORT elevation before departure is preparative, driving changes in behavior and body condition. We tested these predictions in Gray Catbirds (Dumetella carolinensis) following a trans-Gulf flight during spring migration. We found baseline CORT was negatively correlated with body condition and TRIG, corresponding with our predictions for arriving and refueling-but not departing-birds. It is possible catbirds undergo regional habitat translocations rather than complete the entire stopover phase at our study site. We propose the Stopover-CORT hypothesis as a useful predictive framework for future studies of the mechanistic basis of stopover physiology. By studying the regulation of stopover refueling and departure, we may better understand physiological limitations to overall migration rate and improve assessments of habitat quality for refueling birds.

Exploring stress, cognitive, and affective mechanisms of the relationship between interpersonal trauma and opioid misuse

BACKGROUND

People with a history of interpersonal trauma, including intimate partner violence, sexual assault, and adverse childhood experiences, are disproportionately affected by the current opioid epidemic. Interpersonal trauma has been shown to increase risk for chronic pain conditions, prescription opioid use, and opioid misuse. Stress, cognition, and affective function have been examined as potential mechanisms that may influence opioid misuse among individuals with a history of interpersonal trauma. However, no studies have examined these factors simultaneously, despite their interrelatedness.

OBJECTIVE

The purpose of this study was to 1) examine perceived stress, perceived cognitive function, depressive symptoms, and PTSD symptoms as potential mechanisms of opioid misuse among individuals with a history of interpersonal trauma, 2) examine the types of interpersonal trauma that are associated with opioid misuse, and 3) assess the mediating role of pain and opioid prescription.

METHODS

A cross-sectional, observational study design was conducted. Data were collected through a confidential self-report online survey using validated instruments (n = 230). A series of regression analyses were conducted to identify mechanistic factors and interpersonal trauma types associated with opioid misuse, opioid prescription, and pain intensity. Structural equation modeling was used to examine mediating effects of pain intensity and opioid prescription.

RESULTS

Opioid prescription, depressive symptoms, and intimate partner violence increased the odds of reporting opioid misuse. Pain intensity and adverse childhood experiences increased the odds of opioid prescription. Higher levels of perceived stress and depressive symptoms were associated with increased pain intensity. Pain intensity emerged as a mediator of the relationship between depressive symptoms and opioid misuse.

CONCLUSIONS

Our work shows that there are likely several pathways through which interpersonal trauma can lead to opioid misuse. Interventions aimed at improving depressive symptoms and coping with traumatizing events should be included as part of comprehensive trauma-informed pain management practices.

Opposing patterns of abnormal D1 and D2 receptor dependent cortico-striatal plasticity explain increased risk taking in patients with DYT1 dystonia

Patients with DYT1 dystonia caused by the mutated TOR1A gene exhibit risk neutral behaviour compared to controls who are risk averse in the same reinforcement learning task. It is unclear whether this behaviour can be linked to changes in cortico-striatal plasticity demonstrated in animal models which share the same TOR1A mutation. We hypothesised that we could reproduce the experimental risk taking behaviour using a model of the basal ganglia under conditions where cortico-striatal plasticity was abnormal. As dopamine exerts opposing effects on cortico-striatal plasticity via different receptors expressed on medium spiny neurons (MSN) of the direct (D1R dominant, dMSNs) and indirect (D2R dominant, iMSNs) pathways, we tested whether abnormalities in cortico-striatal plasticity in one or both of these pathways could explain the patient's behaviour. Our model could generate simulated behaviour indistinguishable from patients when cortico-striatal plasticity was abnormal in both dMSNs and iMSNs in opposite directions. The risk neutral behaviour of the patients was replicated when increased cortico-striatal long term potentiation in dMSN's was in combination with increased long term depression in iMSN's. This result is consistent with previous observations in rodent models of increased cortico-striatal plasticity at in dMSNs, but contrasts with the pattern reported in vitro of dopamine D2 receptor dependant increases in cortico-striatal LTP and loss of LTD at iMSNs. These results suggest that additional factors in patients who manifest motor symptoms may lead to divergent effects on D2 receptor dependant cortico-striatal plasticity that are not apparent in rodent models of this disease.

Mentoring Programs by and for a New Generation of Latino Investigators in Behavioral-Social Science HIV Research

Latinos represent a critical resource of talent that could be cultivated to expand the HIV research workforce. However, their rapid growth, as the largest and fastest growing ethnic minority group in the US population, has yet to translate into a significant increase in Latino health academic researchers. Historically, strategies to build a diverse research workforce have grouped together individuals from underrepresented minority populations obscuring significance between and within group differences. This limits approaches that are responsive to the diversity of needs and experiences of emerging investigators from underrepresented groups. In this article, we discuss challenges associated with heterogeneity of Latinos and barriers that impede research independence/career success in the context of a review of Latino-investigator targeted mentorship approaches on the behavioral-social science of HIV infection. Mentorship workforce strategies could benefit from a personalized framework emphasizing individualized and tailored approaches to address the limitations and gaps in knowledge regarding Latino research development. This perspective encourages increased emphasis on organizational and structural processes to aid in overcoming institutional-level barriers that impede research and career development. Recommendations are proposed for features and components of effective mentorship programs that will lead to robust outcomes for strengthening the Latino research workforce in the HIV research field and elsewhere.

Noradrenergic-dependent functions are associated with age-related locus coeruleus signal intensity differences

The locus coeruleus (LC), the origin of noradrenergic modulation of cognitive and behavioral function, may play an important role healthy ageing and in neurodegenerative conditions. We investigated the functional significance of age-related differences in mean normalized LC signal intensity values (LC-CR) in magnetization-transfer (MT) images from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) cohort - an open-access, population-based dataset. Using structural equation modelling, we tested the pre-registered hypothesis that putatively noradrenergic (NA)-dependent functions would be more strongly associated with LC-CR in older versus younger adults. A unidimensional model (within which LC-CR related to a single factor representing all cognitive and behavioral measures) was a better fit with the data than the a priori two-factor model (within which LC-CR related to separate NA-dependent and NA-independent factors). Our findings support the concept that age-related reduction of LC structural integrity is associated with impaired cognitive and behavioral function.

A synthetic dataset primer for the biobehavioural sciences to promote reproducibility and hypothesis generation

Open research data provide considerable scientific, societal, and economic benefits. However, disclosure risks can sometimes limit the sharing of open data, especially in datasets that include sensitive details or information from individuals with rare disorders. This article introduces the concept of synthetic datasets, which is an emerging method originally developed to permit the sharing of confidential census data. Synthetic datasets mimic real datasets by preserving their statistical properties and the relationships between variables. Importantly, this method also reduces disclosure risk to essentially nil as no record in the synthetic dataset represents a real individual. This practical guide with accompanying R script enables biobehavioural researchers to create synthetic datasets and assess their utility via the synthpop R package. By sharing synthetic datasets that mimic original datasets that could not otherwise be made open, researchers can ensure the reproducibility of their results and facilitate data exploration while maintaining participant privacy.

Stress hypothesis overload: 131 hypotheses exploring the role of stress in tradeoffs, transitions, and health

Stress is ubiquitous and thus, not surprisingly, many hypotheses and models have been created to better study the role stress plays in life. Stress spans fields and is found in the literature of biology, psychology, psychophysiology, sociology, economics, and medicine, just to name a few. Stress, and the hypothalamic-pituitaryadrenal/interrenal (HPA/I) axis and sympathetic nervous system (SNS), are involved in a multitude of behaviors and physiological processes, including life-history and ecological tradeoffs, developmental transitions, health, and survival. The goal of this review is to highlight and summarize the large number of available hypotheses and models, to aid in comparative and interdisciplinary thinking, and to increase reproducibility by a) discouraging hypothesizing after results are known (HARKing) and b) encouraging a priori hypothesis testing. For this review I collected 214 published hypotheses or models dealing broadly with stress. In the main paper, I summarized and categorized 131 of those hypotheses and models which made direct connections among stress and/or HPA/I and SNS, tradeoffs, transitions, and health. Of those 131, the majority made predictions about reproduction (n = 43), the transition from health to disease (n = 38), development (n = 23), and stress coping (n = 18). Additional hypotheses were classified as stage-spanning or models (n = 37). The additional 83 hypotheses found during searches were tangentially related, or pertained to immune function or oxidative stress, and these are listed separately. Many of the hypotheses share underlying rationale and suggest similar, if not identical, predictions, and are thus not mutually exclusive; some hypotheses spanned classification categories. Some of the hypotheses have been tested multiple times, whereas others have only been examined a few times. It is the hope that multi-disciplinary stress researchers will begin to harmonize their naming of hypotheses in the literature so as to build a clearer picture of how stress impacts various outcomes across fields. The paper concludes with some considerations and recommendations for robust testing of stress hypotheses.

A re-evaluation of silk measurement by the cecropia caterpillar (Hyalophora cecropia) during cocoon construction reveals use of a silk odometer that is temporally regulated

The late 5th instar caterpillar of the cecropia silk moth (Hyalophora cecropia) spins a silken cocoon with a distinct, multilayered architecture. The cocoon construction program, first described by the seminal work of Van der Kloot and Williams, consists of a highly ordered sequence of events. We perform behavioral experiments to re-evaluate the original cecropia work, which hypothesized that the length of silk that passes through the spinneret controls the orderly execution of each of the discrete events of cocoon spinning. We confirm and extend by three-dimensional scanning and quantitative measurements of silk weights that if cocoon construction is interrupted, upon re-spinning, the caterpillar continues the cocoon program from where it left off. We also confirm and extend by quantitative measurements of silk weights that cecropia caterpillars will not bypass any of the sections of the cocoon during the construction process, even if presented with a pre-spun section of a cocoon spun by another caterpillar. Blocking silk output inhibits caterpillars from performing normal spinning behaviors used for cocoon construction. Surprisingly, unblocking silk output 24-hr later did not restart the cocoon construction program, suggesting the involvement of a temporally-defined interval timer. We confirm with surgical reductions of the silk glands that it is the length of silk itself that matters, rather than the total amount of silk extracted by individuals. We used scanning electron microscopy to directly show that either mono- or dual-filament silk (i.e., equal silk lengths but which vary in their total amount of silk extracted) can be used to construct equivalent cocoons of normal size and that contain the relevant layers. We propose that our findings, taken together with the results of prior studies, strongly support the hypothesis that the caterpillar uses a silk "odometer" to measure the length of silk extracted during cocoon construction but does so in a temporally regulated manner. We further postulate that our examination of the anatomy of the silk spinning apparatus and ablating spinneret sensory output provides evidence that silk length measurement occurs upstream of output from the spinneret.

Multi-domain cognitive assessment of male mice shows space radiation is not harmful to high-level cognition and actually improves pattern separation

Astronauts on interplanetary missions - such as to Mars - will be exposed to space radiation, a spectrum of highly-charged, fast-moving particles that includes 56Fe and 28Si. Earth-based preclinical studies show space radiation decreases rodent performance in low- and some high-level cognitive tasks. Given astronaut use of touchscreen platforms during training and space flight and given the ability of rodent touchscreen tasks to assess functional integrity of brain circuits and multiple cognitive domains in a non-aversive way, here we exposed 6-month-old C57BL/6J male mice to whole-body space radiation and subsequently assessed them on a touchscreen battery. Relative to Sham treatment, 56Fe irradiation did not overtly change performance on tasks of visual discrimination, reversal learning, rule-based, or object-spatial paired associates learning, suggesting preserved functional integrity of supporting brain circuits. Surprisingly, 56Fe irradiation improved performance on a dentate gyrus-reliant pattern separation task; irradiated mice learned faster and were more accurate than controls. Improved pattern separation performance did not appear to be touchscreen-, radiation particle-, or neurogenesis-dependent, as 56Fe and 28Si irradiation led to faster context discrimination in a non-touchscreen task and 56Fe decreased new dentate gyrus neurons relative to Sham. These data urge revisitation of the broadly-held view that space radiation is detrimental to cognition.

Using Behavioral Analytics to Predict Customer Invoice Payment

Experiences from various industries show that companies may have problems collecting customer invoice payments. Studies report that almost half of the small- and medium-sized enterprise and business-to-business invoices in the United States and United Kingdom are paid late. In this study, our aim is to understand customer behavior regarding invoice payments, and propose an analytical approach to learning and predicting payment behavior. Our logic can then be embedded into a decision support system where decision makers can make predictions regarding future payments, and take actions as necessary toward the collection of potentially unpaid debt, or adjust their financial plans based on the expected invoice-to-cash amount. In our analysis, we utilize a large data set with more than 1.6 million customers and their invoice and payment history, as well as various actions (e.g., e-mail, short message service, phone call) performed by the invoice-issuing company toward customers to encourage payment. We use supervised and unsupervised learning techniques to help predict whether a customer will pay the invoice or outstanding balance by the next due date based on the actions generated by the company and the customer's response. We propose a novel behavioral scoring model used as an input variable to our predictive models. Among the three machine learning approaches tested, we report the results of logistic regression that provides up to 97% accuracy with or without preclustering of customers. Such a model has a high potential to help decision makers in generating actions that contribute to the financial stability of the company in terms of cash flow management and avoiding unnecessary corporate lines of credit.

Emergence of social inequality in the spatial harvesting of renewable public goods

Spatially extended ecological public goods, such as forests, grasslands, and fish stocks, are at risk of being overexploited by selfish consumers–a phenomenon widely recognized as the ‘tragedy of the commons.’ The interplay of spatial and ecological dimensions introduces new features absent in non-spatial ecological contexts, such as consumer mobility, local information availability, and strategy evolution through social learning in neighborhoods. It is unclear how these features interact to influence the harvesting and dispersal strategies of consumers. To answer these questions, we develop and analyze an individual-based, spatially structured, eco-evolutionary model with explicit resource dynamics. We report the following findings. (1) When harvesting efficiency is low, consumers evolve a sedentary consumption strategy, through which the resource is harvested sustainably, but with harvesting rates far below their maximum sustainable value. (2) As harvesting efficiency increases, consumers adopt a mobile ‘consume-and-disperse’ strategy, which is sustainable, equitable, and gives maximum sustainable yield. (3) A further increase in harvesting efficiency leads to large-scale overexploitation. (4) If costs of dispersal are significant, increased harvesting efficiency also leads to social inequality between frugal sedentary consumers and overexploitative mobile consumers. Whereas overexploitation can occur without social inequality, social inequality always leads to overexploitation. Thus, we identify four conditions that–while being characteristic of technological progress in modern societies–risk social inequality and overexploitation: high harvesting efficiency, moderately low costs of dispersal, high consumer density, and the tendency of consumers to adopt new strategies rapidly. We also show how access to global information–another feature widespread in modern societies–helps mitigate these risks.

Throughout history, humans have shaped ecological landscapes, which in turn have influenced human behavior. This mutual dependence is epitomized when human consumers harvest a spatially extended renewable resource. Simple models predict that, when multiple consumers harvest a shared resource, each is tempted to harvest faster than his/her peers, putting the resource at risk of overexploitation. It is unclear, however, how the interplay among resource productivity, consumer mobility, and social learning in spatial ecological public goods games influences evolved consumer behavior. Here, using an individual-based, spatially structured, eco-evolutionary model of consumers and a resource, we find that increasing resource productivity initially promotes efficient resource use by enabling mobile consumption strategies, but eventually leads to inequality and overexploitation, as overexploitative mobile consumers coexist with frugal sedentary consumers. When consumers are impatient (i.e., eager to imitate successful strategies) or myopic (i.e., unaware of conditions outside of their neighborhoods), inequality and overexploitation tend to aggravate.

Delayed feedback embedded in perception-action coordination cycles results in anticipation behavior during synchronized rhythmic action: A dynamical systems approach

Dancing and playing music require people to coordinate actions with auditory rhythms. In laboratory perception-action coordination tasks, people are asked to synchronize taps with a metronome. When synchronizing with a metronome, people tend to anticipate stimulus onsets, tapping slightly before the stimulus. The anticipation tendency increases with longer stimulus periods of up to 3500ms, but is less pronounced in trained individuals like musicians compared to non-musicians. Furthermore, external factors influence the timing of tapping. These factors include the presence of auditory feedback from one’s own taps, the presence of a partner performing coordinated joint tapping, and transmission latencies (TLs) between coordinating partners. Phenomena like the anticipation tendency can be explained by delay-coupled systems, which may be inherent to the sensorimotor system during perception-action coordination. Here we tested whether a dynamical systems model based on this hypothesis reproduces observed patterns of human synchronization. We simulated behavior with a model consisting of an oscillator receiving its own delayed activity as input. Three simulation experiments were conducted using previously-published behavioral data from 1) simple tapping, 2) two-person alternating beat-tapping, and 3) two-person alternating rhythm-clapping in the presence of a range of constant auditory TLs. In Experiment 1, our model replicated the larger anticipation observed for longer stimulus intervals and adjusting the amplitude of the delayed feedback reproduced the difference between musicians and non-musicians. In Experiment 2, by connecting two models we replicated the smaller anticipation observed in human joint tapping with bi-directional auditory feedback compared to joint tapping without feedback. In Experiment 3, we varied TLs between two models alternately receiving signals from one another. Results showed reciprocal lags at points of alternation, consistent with behavioral patterns. Overall, our model explains various anticipatory behaviors, and has potential to inform theories of adaptive human synchronization.

When navigating a busy sidewalk, people coordinate their behavior in an orderly manner. Other activities require people to carefully synchronize periodic actions, as in a group rowing or marching. When individuals tap in synchrony with a metronome, their taps tend to anticipate the metronome. Experiments have revealed that factors like musical expertise, the presence of a synchronizing partner, auditory feedback, and the sound travel time, all systematically affect the tendency to anticipate. While researchers have hypothesized a number of potential mechanisms for such anticipatory behavior, none have successfully accounted for all of the effects. Previous research on coupled physical systems has shown that when one system receives input from a second system, plus its own delayed signal as input, this causes system 1 to anticipate system 2. We hypothesize that the tendency to anticipate is the result of delayed communication between neurons. Our work demonstrates the ability of delay-coupled physical systems to capture human anticipation and the effect of external factors in the anticipation tendency. Our model supports the theory that delayed communication within the nervous system is crucial to understanding anticipatory coordinative behavior.

Dynamic Empirically Based Model for Understanding Future Trends in US Obesity Prevalence in the Context of Social Influences

OBJECTIVE

This study aimed to (1) identify mechanistic model structures that produced quality fit to historic obesity prevalence trends and (2) evaluate the sensitivity of future obesity prevalence to social transmission and nonsocial parameters.

METHODS

An age- and gender-structured compartmental model was used to describe transitions between weight status groups. Four model structures with different combinations of social transmission and nonsocial mechanisms were calibrated to match historic time series and assessed for quality of fit. Projections of overall obesity prevalence to 2052 were simulated, and sensitivity analyses were conducted.

RESULTS

The model structure that included only nonsocial mechanisms indicated that the overall obesity prevalence in the United States has already stabilized and will increase little more; however, it underestimated observed obesity prevalence since 2013. If social transmission mechanisms influence obesity, the model estimated continued increases in obesity prevalence, reaching 48.0% to 55.1% by 2050. Obesity prevalence was most sensitive to changes in the adult social transmission parameters, especially among women.

CONCLUSIONS

The model projected that US obesity prevalence in the overall population will likely continue to increase for decades. The findings that obesity prevalence was most sensitive to adult parameters can be used to inform conversations about priorities for public health and health care programs and policies.

Using a theory-driven creative process to design a peri-urban on-site sanitation quality improvement intervention

BACKGROUND

Behavior change interventions have been developed by drawing from many different theories using design processes of varying specificity. We describe the development of a behavior change intervention to improve on-site peri-urban sanitation quality in Lusaka, Zambia using the Behavior Centered Design (BCD) framework to explain the results of the process applied to improving the quality of shared peri-urban sanitation and compare them to similar interventions.

METHODS

We used the BCD behavioral determinants model to synthesize the data from our literature review and formative research. Then, we partnered with creative professionals using a design process to develop a theory-driven on-site peri-urban sanitation intervention. Particular attention was paid to the implications of using BCD for intervention development on improving its effectiveness, increasing the contributions to knowledge for other behaviors and settings, and advancing the discipline of applied behavioral science.

RESULTS

Based on findings from a literature review and formative research, we designed an intervention to encourage landlords to improve their toilets by making them more accessible, desirable, hygienic, and sustainable. The intervention involved landlords meeting in facilitated groups every 2 weeks with individual follow-up after each meeting. The meetings presented surprising "hidden camera"-style videos to reveal tenants' perspectives, used participatory activities to help landlords reevaluate the benefits they would derive from improving sanitation on their plots, and provided practical guidance and mechanisms to facilitate the performance of construction and cleaning behaviors.

CONCLUSIONS

Using the BCD framework provided an easy-to-follow intervention design process. The resulting intervention is highly creative and multi-faceted, with each element having a theoretical role in an explicit theory of change. The development of this theory-driven intervention advances applied behavioral science by facilitating evaluation of each of the behavior change techniques and the overall delivery mechanism hypothesized to change the target behaviors. This informs the adaptation of these findings to improving on-site sanitation in other settings and the iterative development of the BCD model, which can be used to more effectively change other behaviors.

In Our Lives and Under Our Skin: An Investigation of Specific Psychobiological Mediators Linking Family Relationships and Health Using the Biobehavioral Family Model

The objective of this study was to use the Biobehavioral Family Model (BBFM) to delineate which psychophysiological variables link romantic and family relationship satisfaction variables to health outcomes. Data from individuals who reported being partnered from the second wave of the National Survey of Midlife Development in the United States (MIDUS II), Project 4 (n = 812) were used to test a structural equation model which explored which psychophysiological variables potentially mediated associations between positive and negative family emotional climate variables and disease activity. This model found that current and past family variables had larger associations with the psychophysiological variables than romantic partner variables; depressive symptoms, anxiety, and inflammation partially mediated associations between family relationships and health; and, contrary to the hypotheses, romantic partner and family support were linked to worse health outcomes. However, the findings should be viewed with regard to the cross-sectional design of the study. Overall, the findings support the use of the BBFM as a model that can guide clinical interventions.

The New Biobehavioral Developmental Science of Puberty

This special section is the product of a small-group meeting of those who study puberty and its relevance. Our aim was to gather information and write manuscripts to inform scientists of advances and continuing obstacles, as well as to stimulate interdisciplinary research on puberty relevant across the lifespan. The themes of the nine position or review papers (and commentary), range from cell to society. We hope this introduction will entice you to read all the papers and consider how they apply or expand your next steps in research or help you synthesize the literature on puberty. We anticipate the papers can embellish your adolescent courses, and, for junior scientists, we hope the many intriguing possibilities for future research on puberty will be apparent.

Going with the flow: hydrodynamic cues trigger directed escapes from a stalking predator

In the coevolution of predator and prey, different and less well-understood rules for threat assessment apply to freely suspended organisms than to substrate-dwelling ones. Particularly vulnerable are small prey carried with the bulk movement of a surrounding fluid and thus deprived of sensory information within the bow waves of approaching predators. Some planktonic prey have solved this apparent problem, however. We quantified cues generated by the slow approach of larval clownfish ( Amphiprion ocellaris) that triggered a calanoid copepod ( Bestiolina similis) to escape before the fish could strike. To estimate water deformation around the copepod immediately preceding its jump, we represented the body of the fish as a rigid sphere in a hydrodynamic model that we parametrized with measurements of fish size, approach speed and distance to the copepod. Copepods of various developmental stages (CII-CVI) were sensitive to the water flow caused by the live predator, at deformation rates as low as 0.04 s-1. This rate is far lower than that predicted from experiments that used artificial predator-mimics. Additionally, copepods localized the source, with 87% of escapes directed away (greater than or equal to 90°) from the predator. Thus, copepods' survival in life-threatening situations relied on their detection of small nonlinear signals within an environment of locally linear deformation.

The self-organization of ball bouncing

The hybrid rhythmic ball-bouncing task considered in this study requires a participant to hit a ball in a virtual environment by moving a paddle in the real environment. It allows for investigation of the online visual control of action in humans. Changes in gravity acceleration in the virtual environment affect the ball dynamics and modify the ball-paddle system limit cycle. These changes are shown to be accurately reproduced through simulation by a model integrating continuous information-movement couplings between the ball trajectory and the paddle trajectory, giving rise to a resonance-tuning phenomenon. On the contrary, the tested models integrating only intermittent sensorimotor couplings were unable to replicate the observed human behavior. Results suggest that the visual control of action is achieved online, in a prospective way. Human rhythmic motor control would benefit from the timing and phase control emerging from the low-level continuous coupling between the central pattern generator and the visual perception of the ball trajectory. This control strategy, which precludes the need for internal clock and explicit environmental representation, is also able to explain the empirical result that the bounces tend to converge toward a passive stability regime during human ball bouncing.

Capturing sexual contact patterns in modelling the spread of sexually transmitted infections: Evidence using Natsal-3

BACKGROUND

Understanding the spread of sexually transmitted infections (STIs) in a population is of great importance to the planning and delivery of health services globally. The worldwide rise of HIV since the 1980's, and the recent increase in common STIs (including HPV and Chlamydia) in many countries, means that there is an urgent need to understand transmission dynamics in order to better predict the spread of such infections in the population. Unlike many other infections which can be captured by assumptions of random mixing, STI transmission is intimately linked to the number and pattern of sexual contacts. In fact, it is the huge variation in the number of new sexual partners that gives rise to the extremes of risk within populations which need to be captured in predictive models of STI transmission. Such models are vital in providing the necessary scientific evidence to determine whether a range of controls (from education to screening to vaccination) are cost-effective.

METHOD AND RESULTS

We use probability sample survey data from Britain's third National Survey of Sexual Attitudes and Lifestyles (Natsal-3) to determine robust distributions for the rate of new partnerships that involve condomless sex and can therefore facilitate the spread of STIs. Different distributions are defined depending on four individual-level characteristics: age, sex, sexual orientation, and previous sexual experience. As individual behaviour patterns can change (e.g. by remaining in a monogamous relationship for a long period) we allow risk-percentiles to be randomly redrawn, to capture longer term behaviour as measured by Natsal-3. We demonstrate how this model formulation interacts with the transmission of infection by constructing an individual-based SIS-P (Susceptible-Infected-Susceptible-Protected) transmission model for the spread of a generic STI, and observing overall population demographics when varying the transmission probability within a partnership, recovery rate and the level of population protection (e.g. from vaccination where applicable).

Administration of chitosan-tripolyphosphate-DNA nanoparticles to knockdown glutamate dehydrogenase expression impairs transdeamination and gluconeogenesis in the liver

Glutamate dehydrogenase (GDH) plays a major role in amino acid catabolism. To increase the current knowledge of GDH function, we analysed the effect of GDH silencing on liver intermediary metabolism from gilthead sea bream (Sparus aurata). Sequencing of GDH cDNA from S. aurata revealed high homology with its vertebrate orthologues and allowed us to design short hairpin RNAs (shRNAs) to knockdown GDH expression. Following validation of shRNA-dependent downregulation of S. aurata GDH in vitro, chitosan-tripolyphosphate (TPP) nanoparticles complexed with a plasmid encoding a selected shRNA (pCpG-sh2GDH) were produced to address the effect of GDH silencing on S. aurata liver metabolism. Seventy-two hours following intraperitoneal administration of chitosan-TPP-pCpG-sh2GDH, GDH mRNA levels and immunodetectable protein decreased in the liver, leading to reduced GDH activity in both oxidative and reductive reactions to about 53-55 % of control values. GDH silencing decreased glutamate, glutamine and aspartate aminotransferase activity, while increased 2-oxoglutarate content, 2-oxoglutarate dehydrogenase activity and 6-phosphofructo-1-kinase/fructose-1,6-bisphosphatase activity ratio. Our findings show for the first time that GDH silencing reduces transdeamination and gluconeogenesis in the liver, hindering the use of amino acids as gluconeogenic substrates and enabling protein sparing and metabolisation of dietary carbohydrates, which would reduce environmental impact and production costs of aquaculture.

White Female Bystanders' Responses to a Black Woman at Risk for Sexual Assault: Positive Effects of Intergroup Contact

Although much research suggests that intergroup contact reduces prejudice, less research has examined the effects of contact on prosocial intergroup bystander behaviors. The current study examined mediators between White undergraduate women's (N = 139) contact with racial/ethnic minority group members and their intent to help a Black woman at risk for sexual assault. As expected, White women who had more frequent and higher quality contact reported greater intent to intervene. Results showed that the effect of quality intergroup contact was mediated by diversity beliefs, or the attitude that cultural heterogeneity leads to favorable outcomes. These results suggest that promoting high-quality opportunities for intergroup contact and education regarding cultural diversity could promote the safety of racially and ethnically diverse students on predominantly White campuses.

Drawing power of virtual crowds

In 1969, social psychologist Milgram and his colleagues conducted an experiment on a busy city street where passers-by witnessed a set of actors spontaneously looking up towards a building. The experiment showed that the crowd's propensity to mimic the actor's gaze increased with the number of actors that looked up. This form of behavioural contagion is found in many social organisms and is central to how information travels through large groups. With the advancement of virtual reality and its continued application towards understanding human response to crowd behaviour, it remains to be verified if behavioural contagion occurs in walkable virtual environments, and how it compares with results from real-world experiments. In this study, we adapt Milgram's experiment for virtual environments and use it to reproduce behavioural contagion. Specifically, we construct a replica of an indoor location and combine two established pedestrian motion models to create an interactive crowd of 60 virtual characters that walk through the indoor location. The stimulus group comprised a subset of the characters who look up at a random time as the participants explore the virtual environment. Our results show that the probability of looking up by a participant is dependent on the size of the stimulus group saturating to near certainty when three or more characters look up. The role of stimulus size was also evident when participant actions were compared with survey responses which showed that more participants selected to not look up even though they saw characters redirect their gaze upwards when the size of the stimulus group was small. Participants also spent more time looking up and exhibited frequent head turns with a larger stimulus group. Results from this study provide evidence that behavioural contagion can be triggered in the virtual environment, and can be used to build and test complex hypotheses for understanding human behaviour in a variety of crowd scenarios.

Examining the Triple Code Model in numerical cognition: An fMRI study

The Triple Code Model (TCM) of numerical cognition argues for the existence of three representational codes for number: Arabic digits, verbal number words, and analog nonsymbolic magnitude representations, each subserved by functionally dissociated neural substrates. Despite the popularity of the TCM, no study to date has explored all three numerical codes within one fMRI paradigm. We administered three tasks, associated with each of the aforementioned numerical codes, in order to explore the neural correlates of numerosity processing in a sample of adults (N = 46). Independent task-control contrast analyses revealed task-dependent activity in partial support of the model, but also highlight the inherent complexity of a distributed and overlapping fronto-parietal network involved in all numerical codes. The results indicate that the TCM correctly predicts the existence of some functionally dissociated neural substrates, but requires an update that accounts for interactions with attentional processes. Parametric contrasts corresponding to differences in task difficulty revealed specific neural correlates of the distance effect, where closely spaced numbers become more difficult to discriminate than numbers spaced further apart. A conjunction analysis illustrated overlapping neural correlates across all tasks, in line with recent proposals for a fronto-parietal network of number processing. We additionally provide tentative results suggesting the involvement of format-independent numerosity-sensitive retinotopic maps in the early visual stream, extending previous findings of nonsymbolic stimulus selectivity. We discuss the functional roles of the components associated with the model, as well as the purported fronto-parietal network, and offer arguments in favor of revising the TCM.

Functional connectivity in ruminants: A generalized state-dependent modelling approach

Animal behaviour is increasingly seen as an important component in maintaining functional connectivity between patches in fragmented landscapes. However, models that explicitly incorporate behavioural trade-offs are rarely applied to landscape planning problems like connectivity. The aim of this study was to explore how state-dependent behaviour influenced functional connectivity between patches from a theoretical perspective. We investigated how inter-patch distances influenced functional connectivity using a dynamic state variable model framework. The decision making process of an individual ruminant facing fitness trade-offs in staying in its patch of origin or moving to another patch at various distances were explicitly modelled. We incorporated energetic costs and predation costs of feeding, ruminating, and resting while in the patch and for transit between patches based on inter-patch distance. Functional connectivity was maintained with isolated patches when they offered high intake and the inactivity of rumination associated with rapid gut fill resulted in reduced predation risk. Nevertheless, individuals in high energetic state often would forgo moving to another patch, whereas individuals in poor energetic states were forced to accept the cost of movement to best meet their requirements in the distant patch. The inclusion of state-dependent behavioural models provides important insights into functional connectivity in fragmented landscapes and helps integrate animal behaviour into landscape planning. We discuss the consequences of our findings for landscape planning to show how the approach provides a heuristic tool to assess alternative scenarios for restoring landscape functional connectivity.

Parameter sensitivity analysis for a stochastic model of mitochondrial apoptosis pathway

Understanding how gene alterations induce oncogenesis plays an important role in cancer research and may be instructive for cancer prevention and treatment. We conducted a parameter sensitivity analysis to the mitochondrial apoptosis model. Both a nonlinear bifurcation analysis of the deterministic dynamics and energy barrier analysis of the corresponding stochastic models were performed. We found that the parameter sensitivity ranking according to the change of the bifurcation-point locations in deterministic models and the change of the barrier heights from a living to death state of the cell in stochastic models are highly correlated. For the model we considered, in combination with previous knowledge that the parameters significantly affecting the system’s bifurcation point are strongly associated with frequently mutated oncogenic genes, we conclude that the energy barrier height can be used as indicator of oncogenesis as well as bifurcation point. We provide a possible mechanism that may help elucidate the logic of cancer initiation from the view of stochastic dynamics and energy landscape. And we show the equivalence of energy barrier height and bifurcation-point location in determining the parameter sensitivity spectrum for the first time.

Unified biophysical mechanism for cell-shape oscillations and cell ingression

We describe a mechanochemical and percolation cascade that augments myosin's regulatory network to tune cytoskeletal forces. Actomyosin forces collectively generate cytoskeletal forces during cell oscillations and ingression, which we quantify by elastic percolation of the internally driven, cross-linked actin network. Contractile units can produce relatively large, oscillatory forces that disrupt crosslinks to reduce cytoskeletal forces. A (reverse) Hopf bifurcation switches contractile units to produce smaller, steady forces that enhance crosslinking and consequently boost cytoskeletal forces to promote ingression. We describe cell-shape changes and cell ingression in terms of intercellular force imbalances along common cell junctions.

Missing the mark for patient engagement: mHealth literacy strategies and behavior change processes in smoking cessation apps

OBJECTIVE

To examine how Transtheoretical Model (TTM)'s processes of change and mHealth literacy strategies are employed in mobile smoking cessation apps.

METHODS

A purposive sample of 100 iTunes apps were coded to assess descriptive (price, type, developer, user-rating) and engagement metrics, including processes of change and mHealth literacy strategies (plain language, usability, interactivity). One-way ANOVAs and independent samples t-tests examined associations between descriptive and engagement metrics.

RESULTS

Over half of the apps included 7 (78%) processes of change. Fewer included self-liberation (36%) and reinforcement management (34%). Most apps incorporated plain language, but few integrated usability and interactivity strategies. Hypnotherapy and informational apps included more behavioral processes of change than apps incorporating a combination of features, including gaming, cigarette trackers, and motivational coaching (p<0.01).

CONCLUSION

Apps included behavior change processes but rarely incorporated usability and interactivity features to promote patient engagement. Engagement metrics did not vary by app user-ratings, price-to-download, or developer, including for-profit organizations or government and educational institutions.

PRACTICE IMPLICATIONS

Providers should acknowledge the popularity of smoking cessation apps as potential cessation aids and communicate their benefits and drawbacks to patients. Future efforts to improve smoking cessation apps should focus on enhancing the quality of tailored and interactive content.

Indirect reciprocity with negative assortment and limited information can promote cooperation

Cooperation is ubiquitous in biological and social systems, even though cooperative behavior is often costly and at risk of exploitation by non-cooperators. Several studies have demonstrated that indirect reciprocity, whereby some members of a group observe the behaviors of their peers and use this information to discriminate against previously uncooperative agents in the future, can promote prosocial behavior. Some studies have shown that differential propensities of interacting among and between different types of agents (interaction assortment) can increase the effectiveness of indirect reciprocity. No previous studies have, however, considered differential propensities of observing the behaviors of different types of agents (information assortment). Furthermore, most previous studies have assumed that discriminators possess perfect information about others and incur no costs for gathering and storing this information. Here, we (1) consider both interaction assortment and information assortment, (2) assume discriminators have limited information about others, and (3) introduce a cost for information gathering and storage, in order to understand how the ability of discriminators to stabilize cooperation is affected by these steps toward increased realism. We report the following findings. First, cooperation can persist when agents preferentially interact with agents of other types or when discriminators preferentially observe other discriminators, even when they have limited information. Second, contrary to intuition, increasing the amount of information available to discriminators can exacerbate defection. Third, introducing costs of gathering and storing information makes it more difficult for discriminators to stabilize cooperation. Our study is one of only a few studies to date that show how negative interaction assortment can promote cooperation and broadens the set of circumstances in which it is know that cooperation can be maintained.

A state-trait model of cortisol in early childhood: Contextual and parental predictors of stable and time-varying effects

This study examined state-trait models of diurnal cortisol (morning level and diurnal slope), and whether income, cumulative risk and parenting behaviors predicted variance in trait and state levels of cortisol. The sample of 306 mothers and their preschool children included 29% families at or near poverty, 27% families below the median income, and the remaining families at middle and upper income. Diurnal cortisol, income, cumulative risk, and parenting were measured at 4 time points, once every 9months, starting when children were 36-40months. State-trait models fit the data, suggesting significant state but not trait variance in cortisol. Low income and cumulative risk were related to trait levels of diurnal cortisol with little evidence of time-varying or state effects. Stable levels of parenting predicted trait levels of diurnal cortisol and time-varying levels of parenting predicted time-varying state levels of diurnal cortisol. Findings highlight the allostatic process of adaptation to risk as well as time-specific reactivity to variability in experience.