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We present this article as a testament to Ed Zigler's commitment to science in the service of humanity and to policy based on conceptually compelling theory and methodologically rigorous science. In doing so, we highlight ways that Ed's universal and inclusive developmental world view, early training as a behaviorist, exacting scientific standards, concern for others, and appreciation of his own roots and upbringing all transformed the way that many different groups of people of all ages and backgrounds are studied, viewed, and intervened with by researchers, policy makers, and society at large. Ed's narrative of development rather than defect, universality rather than difference, and holistic rather than reductionist continues to compel us in the quest for a kinder, more inclusive, and enabling society. Conversely, Ed's behaviorist training as a graduate student also influenced him throughout his career and was essential to his career-long commitment to systemic action in the service of improving the lives of others. We cite the lessons that we, as his descendants, learned from Ed and apply them to our own areas of research with populations that Ed did not study, but had considerable interest in – persons with autism spectrum disorder and Indigenous youth.
Influencer marketing may be amplified on livestreaming platforms (e.g., Twitch) compared with asynchronous social media (e.g., YouTube). However, food and beverage marketing on Twitch has not been evaluated at a user level. The present study aimed to compare users’ self-reported exposure to food marketing and associated attitudes, consumption and purchasing behaviours on Twitch compared with YouTube. A survey administered via social media was completed by 621 Twitch users (90 % male, 64 % white, 69 % under 25 years old). Of respondents, 72 % recalled observing at least one food or beverage advertisement on Twitch. There were significant differences in the recall of specific brands advertised on Twitch (P < 0⋅01). After observing advertised products, 14 % reported craving the product and 8 % reported purchasing one. In chat rooms, 56 % observed conversations related to food and 25 % participated in such conversations. There were significant differences in the number of users who consumed various products while watching Twitch (P < 0⋅01). Of users who frequented YouTube (n 273), 65 % reported negative emotions when encountering advertising on YouTube compared with 40 % on Twitch (P < 0⋅01). A higher proportion felt Twitch's advertising primarily supported content creators (79 v. 54 %, P < 0⋅01), while a higher proportion felt that YouTube's advertising primarily supported the platform (49 v. 66 %, P < 0⋅01). The findings support that food marketing exposures on Twitch are noticeable, less bothersome to users and influence consumption and purchasing behaviours. Future studies are needed to examine how the livestreaming environment may enhance advertising effectiveness relative to asynchronous platforms.
This study compared the level of education and tests from multiple cognitive domains as proxies for cognitive reserve.
The participants were educationally, ethnically, and cognitively diverse older adults enrolled in a longitudinal aging study. We examined independent and interactive effects of education, baseline cognitive scores, and MRI measures of cortical gray matter change on longitudinal cognitive change.
Baseline episodic memory was related to cognitive decline independent of brain and demographic variables and moderated (weakened) the impact of gray matter change. Education moderated (strengthened) the gray matter change effect. Non-memory cognitive measures did not incrementally explain cognitive decline or moderate gray matter change effects.
Episodic memory showed strong construct validity as a measure of cognitive reserve. Education effects on cognitive decline were dependent upon the rate of atrophy, indicating education effectively measures cognitive reserve only when atrophy rate is low. Results indicate that episodic memory has clinical utility as a predictor of future cognitive decline and better represents the neural basis of cognitive reserve than other cognitive abilities or static proxies like education.
While application of clustering algorithms to atom probe tomography data have enabled quantification of solute clusters in terms of number density, size, and subcomposition there exist other properties (e.g., volume, surface area, and composition) that are better determined by defining an interface between the cluster and the surrounding matrix. The limitation in composition results from an ion selection step where the expected matrix ion types are omitted from the cluster search algorithm to enhance the contrast between the matrix and cluster and to reduce the complexity of the search. Previously, composition determination within solute clusters has utilized a secondary envelopment and erosion step on top of conventional methods such as maximum separation. In this work, we present a novel stochastic method that combines the particle identification fidelity of a conventional clustering algorithm with the analytical flexibility of mesh-based approaches through the generation of alpha shapes for each identified cluster. The corresponding mesh accounts for concave components of the clusters and determines the volume and surface area of the clusters; additionally, the mesh boundary is utilized to update the total composition according to the internal ions.
Gravitational waves from coalescing neutron stars encode information about nuclear matter at extreme densities, inaccessible by laboratory experiments. The late inspiral is influenced by the presence of tides, which depend on the neutron star equation of state. Neutron star mergers are expected to often produce rapidly rotating remnant neutron stars that emit gravitational waves. These will provide clues to the extremely hot post-merger environment. This signature of nuclear matter in gravitational waves contains most information in the 2–4 kHz frequency band, which is outside of the most sensitive band of current detectors. We present the design concept and science case for a Neutron Star Extreme Matter Observatory (NEMO): a gravitational-wave interferometer optimised to study nuclear physics with merging neutron stars. The concept uses high-circulating laser power, quantum squeezing, and a detector topology specifically designed to achieve the high-frequency sensitivity necessary to probe nuclear matter using gravitational waves. Above 1 kHz, the proposed strain sensitivity is comparable to full third-generation detectors at a fraction of the cost. Such sensitivity changes expected event rates for detection of post-merger remnants from approximately one per few decades with two A+ detectors to a few per year and potentially allow for the first gravitational-wave observations of supernovae, isolated neutron stars, and other exotica.
Potential effectiveness of harvest weed seed control (HWSC) systems depends upon seed shatter of the target weed species at crop maturity, enabling its collection and processing at crop harvest. However, seed retention likely is influenced by agroecological and environmental factors. In 2016 and 2017, we assessed seed-shatter phenology in 13 economically important broadleaf weed species in soybean [Glycine max (L.) Merr.] from crop physiological maturity to 4 wk after physiological maturity at multiple sites spread across 14 states in the southern, northern, and mid-Atlantic United States. Greater proportions of seeds were retained by weeds in southern latitudes and shatter rate increased at northern latitudes. Amaranthus spp. seed shatter was low (0% to 2%), whereas shatter varied widely in common ragweed (Ambrosia artemisiifolia L.) (2% to 90%) over the weeks following soybean physiological maturity. Overall, the broadleaf species studied shattered less than 10% of their seeds by soybean harvest. Our results suggest that some of the broadleaf species with greater seed retention rates in the weeks following soybean physiological maturity may be good candidates for HWSC.
Seed shatter is an important weediness trait on which the efficacy of harvest weed seed control (HWSC) depends. The level of seed shatter in a species is likely influenced by agroecological and environmental factors. In 2016 and 2017, we assessed seed shatter of eight economically important grass weed species in soybean [Glycine max (L.) Merr.] from crop physiological maturity to 4 wk after maturity at multiple sites spread across 11 states in the southern, northern, and mid-Atlantic United States. From soybean maturity to 4 wk after maturity, cumulative percent seed shatter was lowest in the southern U.S. regions and increased moving north through the states. At soybean maturity, the percent of seed shatter ranged from 1% to 70%. That range had shifted to 5% to 100% (mean: 42%) by 25 d after soybean maturity. There were considerable differences in seed-shatter onset and rate of progression between sites and years in some species that could impact their susceptibility to HWSC. Our results suggest that many summer annual grass species are likely not ideal candidates for HWSC, although HWSC could substantially reduce their seed output during certain years.
The authors aim to demonstrate that the current drive-through testing model at a health district was improved in certain parameters compared with a previous testing protocol, and to provide the methodology of the current model for other coronavirus disease (COVID-19) testing sites to potentially emulate.
Initially, a small drive-through site was constructed at a converted tuberculosis clinic, but due to an increase in testing needs, an expanded point of screening and testing (POST) system was developed in an event center parking lot to administer tests to a higher volume of patients.
An average of 51.1 patients was tested each day (2.0 tests per personnel in personal protective equipment [PPE] per hour) at the initial tuberculosis clinic drive-through site, which increased to 217.8 patients tested each day (5.9 tests per personnel in PPE per hour) with the new drive-through POST system (P < 0.001). Mean testing time was 3.4 minutes and the total time on-site averaged 14.4 minutes.
This POST drive-through system serves as an efficient, safe, and adaptable model for high volume COVID-19 nasopharyngeal swabbing that the authors recommend other COVID-19 testing sites nationwide consider adopting for their own use.
This article considers whether candidates strategically use emotional rhetoric in social media messages similar to the way that fear appeals are used strategically in televised campaign advertisements. We use a dataset of tweets issued by the campaign accounts of candidates for the US House of Representatives during the last two months of the 2018 midterm elections to determine whether candidate vulnerability predicts the presence of certain emotions in social media messages. Contrary to theoretical expectations, we find that vulnerability does not appear to inspire candidates to use more anxious language in their tweets. However, we do find evidence of a surprising relationship between sad rhetoric and vulnerability and that campaign context influences the use of other forms of negative rhetoric in tweets.
Cohorting patients who are colonized or infected with multidrug-resistant organisms (MDROs) protects uncolonized patients from acquiring MDROs in healthcare settings. The potential for cross transmission within the cohort and the possibility of colonized patients acquiring secondary isolates with additional antibiotic resistance traits is often neglected. We searched for evidence of cross transmission of KPC+ Klebsiella pneumoniae (KPC-Kp) colonization among cohorted patients in a long-term acute-care hospital (LTACH), and we evaluated the impact of secondary acquisitions on resistance potential.
Genomic epidemiological investigation.
A high-prevalence LTACH during a bundled intervention that included cohorting KPC-Kp–positive patients.
Whole-genome sequencing (WGS) and location data were analyzed to identify potential cases of cross transmission between cohorted patients.
Secondary KPC-Kp isolates from 19 of 28 admission-positive patients were more closely related to another patient’s isolate than to their own admission isolate. Of these 19 cases, 14 showed strong genomic evidence for cross transmission (<10 single nucleotide variants or SNVs), and most of these patients occupied shared cohort floors (12 patients) or rooms (4 patients) at the same time. Of the 14 patients with strong genomic evidence of acquisition, 12 acquired antibiotic resistance genes not found in their primary isolates.
Acquisition of secondary KPC-Kp isolates carrying distinct antibiotic resistance genes was detected in nearly half of cohorted patients. These results highlight the importance of healthcare provider adherence to infection prevention protocols within cohort locations, and they indicate the need for future studies to assess whether multiple-strain acquisition increases risk of adverse patient outcomes.
Through imagining possible actions and considering their consequences, we are able to reason about the morality of behavior – judging whether an action is morally right or wrong. Neuroscience research indicates that moral reasoning depends on a complex, broadly distributed network of brain regions that interact in a both cooperative and competitive manner. Understanding the underlying neurobiology that governs how these regions dynamically interact to produce patterns of behavior is therefore of interest to the field. Currently, prominent theories suggest that moral judgments (consequentialist or deontological) are the product of two distinct cognitive systems (i.e. a dual-process framework). Network neuroscience, an emerging field that measures and interprets brain activity through the framework of modern network science, is positioned to expand our understanding of this dual-process framework by examining how topological properties of networks influence consequentialist and deontological reasoning, and how these two processing systems interact in order to imagine hypothetical scenarios during complex deontological reasoning tasks. In this chapter, we review evidence from neuroscience that bears on our understanding of the dual-process moral reasoning framework and advance a network neuroscience perspective on the neurobiological substrates that underlie it.
We investigate the turbulence statistics in a multiphase plume made of heavy particles (particle Reynolds number at terminal velocity is 450). Using refractive-index-matched stereoscopic particle image velocimetry, we measure the locations of particles whose buoyancy drives the formation of a multiphase plume, together with the local velocity of the induced flow in the ambient salt–water. Measurements of the mean axial flow in the plume centreplane follow Gaussian profiles and that of the mean radial flow is consistent with integral plume theory. The turbulence characteristics resemble those measured in a bubble plume, including strong anisotropy in the normal Reynolds stresses. However, we observe structural differences between the two multiphase plumes. First, the skewness of the probability density function of the axial velocity fluctuations is not that which would be predicted by simply reversing the direction of a bubble plume. Second, in contrast to a bubble plume, the particle plume has a non-negligible fluid-shear production term in the turbulent kinetic energy (TKE) budget. Third, the radial decay of all measured terms in the TKE budget is slower than those in a bubble plume. Despite these dissimilarities, a bigger picture emerges that applies to both flows. The TKE production by particles (or bubbles) roughly balances the viscous dissipation, except near the plume centreline. The one-dimensional power spectra of the velocity fluctuations show a
power law that puts both the particle and bubble plume in a category different from single-phase shear-flow turbulence.
In addition to the positive and negative symptoms, schizophrenia is associated with a variety of cognitive impairments, and in particular with episodic memory deficits. Functional neuroimaging studies have begun exploring the potential neural correlates of memory deficits but there are few reports of structural brain abnormalities underlying memory impairment in schizophrenia. We investigated the potential association between morphological brain abnormalities as revealed by cortical thickness measures and episodic memory performance on a face recognition task. Differences in regional cortical thickness between 27 patients with a DSM-IV diagnosis of schizophrenia and 28 control matched subjects were investigated using MRI T1 images and computer image analysis (CIVET pipeline; Lerch and Evans, 2005). Cortical thickness was estimated as the shortest distance between the pial surface of the cerebral cortex and the white-matter/gray-matter interface surface at numerous points (40 962 vertices) across the cortical mantle. Consistent with previous studies, a group comparison revealed thinner cortex in the patient group relative to controls in the right prefrontal cortex and parahippocampal gyrus. Interestingly, a significant positive correlation between memory performance and cortical thickness of the anterior cingulate, bilaterally as well as the right parahippocampal gyrus was noted in the schizophrenia group. That is, the thinner the cortex in those regions, the more impaired the patients were in terms of memory performance as compared to healthy participants.
Stigma and social exclusion related to mental health are of substantial public health importance for Europe. As part of ROAMER (ROAdmap for MEntal health Research in Europe), we used systematic mapping techniques to describe the current state of research on stigma and social exclusion across Europe. Findings demonstrate growing interest in this field between 2007 and 2012. Most studies were descriptive (60%), focused on adults of working age (60%) and were performed in Northwest Europe—primarily in the UK (32%), Finland (8%), Sweden (8%) and Germany (7%). In terms of mental health characteristics, the largest proportion of studies investigated general mental health (20%), common mental disorders (16%), schizophrenia (16%) or depression (14%). There is a paucity of research looking at mechanisms to reduce stigma and promote social inclusion, or at factors that might promote resilience or protect against stigma/social exclusion across the life course. Evidence is also limited in relation to evaluations of interventions. Increasing incentives for cross-country research collaborations, especially with new EU Member States and collaboration across European professional organizations and disciplines, could improve understanding of the range of underpinning social and cultural factors which promote inclusion or contribute toward lower levels of stigma, especially during times of hardship.
Social contact is one of the most effective strategies for improving inter-group relations and is supported by decades of positive evidence. Several studies specifically support social contact interventions as a way of reducing stigma against people with mental health problems. Despite the effectiveness of this approach, some social groups have few opportunities for social contact in the real world.
Using the England Time to Change anti-stigma campaign as an example, we investigate the feasibility and effectiveness of delivering social contact interventions at the mass population level to reduce stigma and discrimination against people with mental health problems.
To investigate: (i) the feasibility of scaling up social contact interventions to reduce stigma and discrimination against people with mental health problems and (ii) the effectiveness of mass population social contact interventions to: improve intended stigmatising behaviour, increase willingness to disclose mental health problems and to promote engagement in antistigma activities.
Two types of mass participation social contact programmes within England's Time to Change campaign were evaluated via self-report questionnaire. Participants at social contact events were asked about the occurrence and quality of contact, attitudes, readiness to discuss mental health, and intended behaviour towards people with mental health problems.
Findings on feasibility and effectiveness of social contact programmes will be presented.
This study suggests that social contact interventions can be used by anti-stigma campaigns to reduce stigma and discrimination against people with mental health problems. Further investigation is needed regarding the maintenance of these changes
The unprecedented growth, availability and accessibility of sophisticated image analysis algorithms and powerful computational resources led to the idea of developing web-based computational infrastructures that could meet users’ new requirements. On the other hand the gap between the pace of data generation and the capability to extract clinically or scientifically relevant information is rapidly widening.
Integration of the power of sophisticated mathematical models, efficient computational algorithms and advanced hardware infrastructure provides the necessary sensitivity to detect, extract and analyze subtle, dynamic and distributed patterns distinguishing one brain from another, and a diseased brain from a normal brain.
neuGRID is the leading e-Infrastructure where neuroscientists can find core services and resources for brain image analysis. The neuGRID platform makes use of grid services and computing, and was developed with the final aim of overcoming the hurdles that the average scientist meets when trying to set up advanced experiments in computational neuroimaging, thereby empowering a larger base of scientists. Although originally built for neuroscientists working in the field of AD, the infrastructure is designed to be expandable to services from other medical fields (e.g. multiple sclerosis, psychiatric conditions).
“neuGRID for Users” will provide an e-Science environment by further developing and deploying the neuGRID infrastructure to deliver a Virtual Laboratory offering neuroscientists access to a wide range of datasets and algorithm pipelines, access to computational resources, services, and support. Information from this abstract is intended to make aware researchers working with neuroimaging of all possibilities when it comes to resources.
Poor diet quality (DQ) is associated with poor cognition and increased neurodegeneration, including Alzheimer’s disease (AD). We are interested in the role of DQ on cognitive functioning (by sex and increasing genetic risk for AD), in a sample of African American (AA) middle-aged adults. We analysed a sub-group of participants (about 55 % women; mean follow-up time of about 4·7 years) from the Healthy Aging in Neighborhoods of Diversity across the Life Span study with a genetic risk score for AD (hAlzScore). The Healthy Eating Index-2010, Dietary Approaches to Stop Hypertension and the mean adequacy ratio computed at baseline (2004–2009) and follow-up visits (2009–2013) were used to assess initial DQ and change over time. Linear mixed-effects regression models were utilised, adjusting for select covariates, selection bias and multiple testing. DQ change (ΔDQ) was associated with California Verbal Learning Test-List A – overall (0·15 (se 0·06), P = 0·008) and in women (0·21 (se 0·08), P = 0·006), at highest AD risk, indicating protective effects over time. Greater AD risk was longitudinally associated with poorer Clock Command Test scores in men. Poor DQ was positively and cross-sectionally associated with Trails B scores, but in women only. Better-quality diet was associated with a slower decline in verbal memory among AA women, with greater AD risk. Insufficient clinical evidence and/or mixed findings dictate that more studies are needed to investigate brain morphology and volume changes in relation to DQ in an at-risk population for AD, over time.
Nick Martin is a pioneer in recognizing the need for large sample size to study the complex, heterogeneous and polygenic disorders of common mental disorders. In the predigital era, questionnaires were mailed to thousands of twin pairs around Australia. Always quick to adopt new technology, Nick’s studies progressed to phone interviews and then online. Moreover, Nick was early to recognize the value of collecting DNA samples. As genotyping technologies improved over the years, these twin and family cohorts were used for linkage, candidate gene and genome-wide association studies. These cohorts have underpinned many analyses to disentangle the complex web of genetic and lifestyle factors associated with mental health. With characteristic foresight, Nick is chief investigator of our Australian Genetics of Depression Study, which has recruited 16,000 people with self-reported depression (plus DNA samples) over a time frame of a few months — analyses are currently ongoing. The mantra of sample size, sample size, sample size has guided Nick’s research over the last 30 years and continues to do so.
The author provides a personal perspective on Nick Martin’s contributions to behavioral genetics and his role in the workshops on statistical genetics held annually in Boulder. Highlighted are Prof. Martin’s seminal work on multivariate behavioral genetics, his career-long commitment to the value of the study of twins, and his enthusiastic support of the didactic mission of the ‘Boulder workshops’. These contributions and activities continue unabated as we celebrate Prof. Martin’s 70th birthday.
Despite decades of suicide research, our ability to predict suicide has not changed. Why is this the case? We outline the unique challenges facing suicide research. Borrowing successful strategies from other medical fields, we propose specific research directions that aim to translate scientific findings into meaningful clinical impact.