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Deliberation is widely believed to enhance democracy by helping to refine the ‘public will’, moving its participants' policy attitudes closer to their ‘full-consideration’ policy attitudes – those they would hypothetically hold with unlimited information, to which they gave unlimited reflection. Yet there have also been claims that the social dynamics involved generally ‘homogenize’ attitudes (decreasing their variance), ‘polarize’ them (moving their means toward the nearer extreme), or engender ‘domination’ (moving their overall means toward those of the attitudes held by the socially advantaged) – attitude changes that may often be away from the participants' full-consideration attitudes and may thus distort rather than refine the public will. This article uses 2,601 group-issue pairs in twenty-one Deliberative Polls to examine these claims. Reassuringly, the results show no routine or strong homogenization, polarization, or domination. What little pattern there is suggests some faint homogenization, but also some faint moderation (as opposed to polarization) and opposition (as opposed to domination) – all as is to be expected when the outside-world forces shaping pre-deliberation attitudes are slightly more centrifugal than centripetal. The authors lay out a theoretical basis for these expectations and interpretations and probe the study's results, highlighting, among other things, deliberation's role in undoing outside-world effects on pre-deliberation attitudes and the observed homogenization's, polarization's, and domination's dependence on deliberative design.
We honour a great man and a true giant. Lodewyk H.S. van Mierop (March 31, 1927 – October 17, 2021), known as Bob, was not only a Paediatric Cardiologist but also a dedicated Scientist. He made many significant and ground-breaking contributions to the fields of cardiac anatomy and embryology. He was devoted as a teacher, spending many hours with medical students, Residents, and Fellows, all of whom appreciated his regularly scheduled educational sessions. Those of us who were fortunate to know and spend time with him will always remember his great mind, his willingness to share his knowledge, and his ability to encourage spirited and fruitful discussions. His life was most productive, and he will long be remembered by many through his awesome and exemplary scientific contributions.
His legacy continues to influence the current and future generations of surgeons and all providers of paediatric and congenital cardiac care through the invaluable archive he established at University of Florida in Gainesville: The University of Florida van Mierop Heart Archive. Undoubtedly, with these extraordinary contributions to the fields of cardiac anatomy and embryology, which were way ahead of his time, Professor van Mierop was a true giant in Paediatric Cardiology. The invaluable archive he established at University of Florida in Gainesville, The University of Florida van Mierop Heart Archive, has been instrumental in teaching medical students, Residents, Medical Fellows, and Surgical Fellows. Only a handful of similar archives exist across the globe, and these archives are the true legacy of giants such as Dr. van Mierop. We have an important obligation to leave no stone unturned to continue to preserve these archives for the future generations of surgeons, physicians, all providers of paediatric and congenital cardiac care, and, most importantly, our patients.
Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.
To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.
This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.
The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.
Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
In April 2019, the U.S. Fish and Wildlife Service (USFWS) released its recovery plan for the jaguar Panthera onca after several decades of discussion, litigation and controversy about the status of the species in the USA. The USFWS estimated that potential habitat, south of the Interstate-10 highway in Arizona and New Mexico, had a carrying capacity of c. six jaguars, and so focused its recovery programme on areas south of the USA–Mexico border. Here we present a systematic review of the modelling and assessment efforts over the last 25 years, with a focus on areas north of Interstate-10 in Arizona and New Mexico, outside the recovery unit considered by the USFWS. Despite differences in data inputs, methods, and analytical extent, the nine previous studies found support for potential suitable jaguar habitat in the central mountain ranges of Arizona and New Mexico. Applying slightly modified versions of the USFWS model and recalculating an Arizona-focused model over both states provided additional confirmation. Extending the area of consideration also substantially raised the carrying capacity of habitats in Arizona and New Mexico, from six to 90 or 151 adult jaguars, using the modified USFWS models. This review demonstrates the crucial ways in which choosing the extent of analysis influences the conclusions of a conservation plan. More importantly, it opens a new opportunity for jaguar conservation in North America that could help address threats from habitat losses, climate change and border infrastructure.
The ability to effectively lead an interdisciplinary translational team is a crucial component of team science success. Most KL2 Clinical Scholars have been members of scientific teams, but few have been team science leaders. There is a dearth of literature and outcome measures of effective Team Science Leadership in clinical and translational research. We focused our curriculum to emphasize Team Science Leadership, developed a list of Team Science Leadership competencies for translational investigators using a modified Delphi method, and incorporated the competencies into a quantitative evaluation survey. The survey is completed on entry and annually thereafter by the Scholar; the Scholar’s primary mentor and senior staff who educate and interact with the Scholar rate the Scholar at the end of each year. The program leaders and mentor review the results with each Scholar. The survey scales had high internal consistency and good factor structure. Overall ratings by mentors and senior staff were generally high, but ratings by Scholars tended to be lower, offering opportunities for discussion and career planning. Scholars rated the process favorably. A Team Science Leadership curriculum and periodic survey of attained competencies can inform individual career development and guide team science curriculum development.
Research participants want to receive results from studies in which they participate. However, health researchers rarely share the results of their studies beyond scientific publication. Little is known about the barriers researchers face in returning study results to participants.
Using a mixed-methods design, health researchers (N = 414) from more than 40 US universities were asked about barriers to providing results to participants. Respondents were recruited from universities with Clinical and Translational Science Award programs and Prevention Research Centers.
Respondents reported the percent of their research where they experienced each of the four barriers to disseminating results to participants: logistical/methodological, financial, systems, and regulatory. A fifth barrier, investigator capacity, emerged from data analysis. Training for research faculty and staff, promotion and tenure incentives, and funding agencies supporting dissemination of results to participants were solutions offered to overcoming barriers.
Study findings add to literature on research dissemination by documenting health researchers’ perceived barriers to sharing study results with participants. Implications for policy and practice suggest that additional resources and training could help reduce dissemination barriers and increase the return of results to participants.
The Hooks et al. review of microbiota-gut-brain (MGB) literature provides a constructive criticism of the general approaches encompassing MGB research. This commentary extends their review by: (a) highlighting capabilities of advanced systems-biology “-omics” techniques for microbiome research and (b) recommending that combining these high-resolution techniques with intervention-based experimental design may be the path forward for future MGB research.
Prenatal adversity shapes child neurodevelopment and risk for later mental health problems. The quality of the early care environment can buffer some of the negative effects of prenatal adversity on child development. Retrospective studies, in adult samples, highlight epigenetic modifications as sentinel markers of the quality of the early care environment; however, comparable data from pediatric cohorts are lacking. Participants were drawn from the Maternal Adversity Vulnerability and Neurodevelopment (MAVAN) study, a longitudinal cohort with measures of infant attachment, infant development, and child mental health. Children provided buccal epithelial samples (mean age = 6.99, SD = 1.33 years, n = 226), which were used for analyses of genome-wide DNA methylation and genetic variation. We used a series of linear models to describe the association between infant attachment and (a) measures of child outcome and (b) DNA methylation across the genome. Paired genetic data was used to determine the genetic contribution to DNA methylation at attachment-associated sites. Infant attachment style was associated with infant cognitive development (Mental Development Index) and behavior (Behavior Rating Scale) assessed with the Bayley Scales of Infant Development at 36 months. Infant attachment style moderated the effects of prenatal adversity on Behavior Rating Scale scores at 36 months. Infant attachment was also significantly associated with a principal component that accounted for 11.9% of the variation in genome-wide DNA methylation. These effects were most apparent when comparing children with a secure versus a disorganized attachment style and most pronounced in females. The availability of paired genetic data revealed that DNA methylation at approximately half of all infant attachment-associated sites was best explained by considering both infant attachment and child genetic variation. This study provides further evidence that infant attachment can buffer some of the negative effects of early adversity on measures of infant behavior. We also highlight the interplay between infant attachment and child genotype in shaping variation in DNA methylation. Such findings provide preliminary evidence for a molecular signature of infant attachment and may help inform attachment-focused early intervention programs.
The History, Electrocardiogram (ECG), Age, Risk Factors, and Troponin (HEART) score is a decision aid designed to risk stratify emergency department (ED) patients with acute chest pain. It has been validated for ED use, but it has yet to be evaluated in a prehospital setting.
A prehospital modified HEART score can predict major adverse cardiac events (MACE) among undifferentiated chest pain patients transported to the ED.
A retrospective cohort study of patients with chest pain transported by two county-based Emergency Medical Service (EMS) agencies to a tertiary care center was conducted. Adults without ST-elevation myocardial infarction (STEMI) were included. Inter-facility transfers and those without a prehospital 12-lead ECG or an ED troponin measurement were excluded. Modified HEART scores were calculated by study investigators using a standardized data collection tool for each patient. All MACE (death, myocardial infarction [MI], or coronary revascularization) were determined by record review at 30 days. The sensitivity and negative predictive values (NPVs) for MACE at 30 days were calculated.
Over the study period, 794 patients met inclusion criteria. A MACE at 30 days was present in 10.7% (85/794) of patients with 12 deaths (1.5%), 66 MIs (8.3%), and 12 coronary revascularizations without MI (1.5%). The modified HEART score identified 33.2% (264/794) of patients as low risk. Among low-risk patients, 1.9% (5/264) had MACE (two MIs and three revascularizations without MI). The sensitivity and NPV for 30-day MACE was 94.1% (95% CI, 86.8-98.1) and 98.1% (95% CI, 95.6-99.4), respectively.
Prehospital modified HEART scores have a high NPV for MACE at 30 days. A study in which prehospital providers prospectively apply this decision aid is warranted.
Low-density, highly porous graphene/graphene oxide (GO) based-foams have shown high performance in energy absorption applications, even under high compressive deformations. In general, foams are very effective as energy dissipative materials and have been widely used in many areas such as automotive, aerospace and biomedical industries. In the case of graphene-based foams, the good mechanical properties are mainly attributed to the intrinsic graphene and/or GO electronic and mechanical properties. Despite the attractive physical properties of graphene/GO based-foams, their structural and thermal stabilities are still a problem for some applications. For instance, they are easily degraded when placed in flowing solutions, either by the collapsing of their layers or just by structural disintegration into small pieces. Recently, a new and scalable synthetic approach to produce low-density 3D macroscopic GO structure interconnected with polydimethylsiloxane (PDMS) polymeric chains (pGO) was proposed. A controlled amount of PDMS is infused into the freeze-dried foam resulting into a very rigid structure with improved mechanical properties, such as tensile plasticity and toughness. The PDMS wets the graphene oxide sheets and acts like a glue bonding PDMS and GO sheets. In order to obtain further insights on mechanisms behind the enhanced mechanical pGO response we carried out fully atomistic molecular dynamics (MD) simulations. Based on MD results, we build up a structural model that can explain the experimentally observed mechanical behavior.
Given the profound public health and economic ramifications of decisions made by the U.S. Food and Drug Administration, the degree to which FDA activities should reflect an approach founded on complete transparency versus one focused on preserving confidentiality of information deserves public discussion. On one hand, reasonable requirements for transparency are critical to stimulating effective innovation, knowledge dissemination, and good business practice. On the other, ensuring the vitality of the medical products industry requires protecting legitimately proprietary information. With current standards reflecting a lengthy accumulation of legal, regulatory, and practical precedent, recent significant changes in the environment in which the FDA operates should prompt a critical examination of current practices. In this article, I comment on Sharfstein and colleagues’ “Blueprint for Transparency,” which calls for multiple specific actions to increase transparency at the agency across five key areas, including interactions between FDA and industry, public disclosure of internal FDA analyses, deliberations concerning generics and biosimilars, expanded access to raw study data, and approaches to countering misleading information in the public sphere. I evaluate these recommendations in light of my experience as a clinician, researcher, and former FDA Commissioner, and reflect on possible outcomes that could result from enacting these practices.
An internationally approved and globally used classification scheme for the diagnosis of CHD has long been sought. The International Paediatric and Congenital Cardiac Code (IPCCC), which was produced and has been maintained by the International Society for Nomenclature of Paediatric and Congenital Heart Disease (the International Nomenclature Society), is used widely, but has spawned many “short list” versions that differ in content depending on the user. Thus, efforts to have a uniform identification of patients with CHD using a single up-to-date and coordinated nomenclature system continue to be thwarted, even if a common nomenclature has been used as a basis for composing various “short lists”. In an attempt to solve this problem, the International Nomenclature Society has linked its efforts with those of the World Health Organization to obtain a globally accepted nomenclature tree for CHD within the 11th iteration of the International Classification of Diseases (ICD-11). The International Nomenclature Society has submitted a hierarchical nomenclature tree for CHD to the World Health Organization that is expected to serve increasingly as the “short list” for all communities interested in coding for congenital cardiology. This article reviews the history of the International Classification of Diseases and of the IPCCC, and outlines the process used in developing the ICD-11 congenital cardiac disease diagnostic list and the definitions for each term on the list. An overview of the content of the congenital heart anomaly section of the Foundation Component of ICD-11, published herein in its entirety, is also included. Future plans for the International Nomenclature Society include linking again with the World Health Organization to tackle procedural nomenclature as it relates to cardiac malformations. By doing so, the Society will continue its role in standardising nomenclature for CHD across the globe, thereby promoting research and better outcomes for fetuses, children, and adults with congenital heart anomalies.
Although infants less than 18 months old are capable of engaging in self-regulatory behavior (e.g., avoidance, withdrawal, and orienting to other aspects of their environment), the use of self-regulatory strategies at this age (as opposed to relying on caregivers) is associated with elevated behavioral and physiological distress. This study investigated infant dopamine-related genotypes (dopamine receptor D2 [DRD2], dopamine transporter solute carrier family C6, member 4 [SLC6A3], and catechol-O-methyltransferase [COMT]) as they interact with maternal self-reported history of maltreatment to predict observed infant independent emotion regulation behavior. A community sample (N = 193) of mother–infant dyads participated in a toy frustration challenge at infant age 15 months, and infant emotion regulation behavior was coded. Buccal cells were collected for genotyping. Maternal maltreatment history significantly interacted with infant SLC6A3 and COMT genotypes, such that infants with more 10-repeat and valine alleles of SLC6A3 and COMT, respectively, relative to infants with fewer or no 10-repeat and valine alleles, utilized more independent (i.e., maladaptive) regulatory behavior if mother reported a more extensive maltreatment history, as opposed to less. The findings indicate that child genetic factors moderate the intergenerational impact of maternal maltreatment history. The results are discussed in terms of potential mechanism of Gene × Environment interaction.
Policy-makers and practitioners have a need to assess community resilience in disasters. Prior efforts conflated resilience with community functioning, combined resistance and recovery (the components of resilience), and relied on a static model for what is inherently a dynamic process. We sought to develop linked conceptual and computational models of community functioning and resilience after a disaster.
We developed a system dynamics computational model that predicts community functioning after a disaster. The computational model outputted the time course of community functioning before, during, and after a disaster, which was used to calculate resistance, recovery, and resilience for all US counties.
The conceptual model explicitly separated resilience from community functioning and identified all key components for each, which were translated into a system dynamics computational model with connections and feedbacks. The components were represented by publicly available measures at the county level. Baseline community functioning, resistance, recovery, and resilience evidenced a range of values and geographic clustering, consistent with hypotheses based on the disaster literature.
The work is transparent, motivates ongoing refinements, and identifies areas for improved measurements. After validation, such a model can be used to identify effective investments to enhance community resilience. (Disaster Med Public Health Preparedness. 2018;12:127–137)
We sought to conduct a major objective of the CAEP Academic Section, an environmental scan of the academic emergency medicine programs across the 17 Canadian medical schools.
We developed an 84-question questionnaire, which was distributed to academic heads. The responses were validated by phone by the lead author to ensure that the questions were answered completely and consistently. Details of pediatric emergency medicine units were excluded from the scan.
At eight of 17 universities, emergency medicine has full departmental status and at two it has no official academic status. Canadian academic emergency medicine is practiced at 46 major teaching hospitals and 13 specialized pediatric hospitals. Another 69 Canadian hospital EDs regularly take clinical clerks and emergency medicine residents. There are 31 full professors of emergency medicine in Canada. Teaching programs are strong with clerkships offered at 16/17 universities, CCFP(EM) programs at 17/17, and RCPSC residency programs at 14/17. Fourteen sites have at least one physician with a Master’s degree in education. There are 55 clinical researchers with salary support at 13 universities. Sixteen sites have published peer-reviewed papers in the past five years, ranging from four to 235 per site. Annual budgets range from $200,000 to $5,900,000.
This comprehensive review of academic activities in emergency medicine across Canada identifies areas of strengths as well as opportunities for improvement. CAEP and the Academic Section hope we can ultimately improve ED patient care by sharing best academic practices and becoming better teachers, educators, and researchers.
While more and more long-period giant planets are discovered by direct imaging, the distribution of planets at these separations (≳5 AU) has remained largely uncertain, especially compared to planets in the inner regions of solar systems probed by RV and transit techniques. The low frequency, the detection challenges, and heterogeneous samples make determining the mass and orbit distributions of directly imaged planets at the end of a survey difficult. By utilizing Monte Carlo methods that incorporate the age, distance, and spectral type of each target, we can use all stars in the survey, not just those with detected planets, to learn about the underlying population. We have produced upper limits and direct measurements of the frequency of these planets with the most recent generation of direct imaging surveys. The Gemini NICI Planet-Finding Campaign observed 220 young, nearby stars at a median H-band contrast of 14.5 magnitudes at 1”, representing the largest, deepest search for exoplanets by the completion of the survey. The Gemini Planet Imager Exoplanet Survey is in the process of surveying 600 stars, pushing these contrasts to a few tenths of an arcsecond from the star. With the advent of large surveys (many hundreds of stars) using advanced planet-imagers we gain the ability to move beyond measuring the frequency of wide-separation giant planets and to simultaneously determine the distribution as a function of planet mass, semi-major axis, and stellar mass, and so directly test models of planet formation and evolution.