Reactions to uncertainty and the accuracy of diagnostic mammography.

BackgroundReactions to uncertainty in clinical medicine can affect decision making.ObjectiveTo assess the extent to which radiologists' reactions to uncertainty influence diagnostic mammography interpretation.DesignCross-sectional responses to a mailed survey assessed reactions to uncertainty using a well-validated instrument. Responses were linked to radiologists' diagnostic mammography interpretive performance obtained from three regional mammography registries.ParticipantsOne hundred thirty-two radiologists from New Hampshire, Colorado, and Washington.MeasurementMean scores and either standard errors or confidence intervals were used to assess physicians' reactions to uncertainty. Multivariable logistic regression models were fit via generalized estimating equations to assess the impact of uncertainty on diagnostic mammography interpretive performance while adjusting for potential confounders.ResultsWhen examining radiologists' interpretation of additional diagnostic mammograms (those after screening mammograms that detected abnormalities), a 5-point increase in the reactions to uncertainty score was associated with a 17% higher odds of having a positive mammogram given cancer was diagnosed during follow-up (sensitivity), a 6% lower odds of a negative mammogram given no cancer (specificity), a 4% lower odds (not significant) of a cancer diagnosis given a positive mammogram (positive predictive value [PPV]), and a 5% higher odds of having a positive mammogram (abnormal interpretation).ConclusionMammograms interpreted by radiologists who have more discomfort with uncertainty have higher likelihood of being recalled

Complexity, transparency and time pressure: practical insights into science communication in times of crisis

A global crisis such as the COVID-19 pandemic that started in early 2020 poses significant challenges for how research is conducted and communicated. We present four case studies from the perspective of an interdisciplinary research institution that switched to “corona-mode” during the first two months of the crisis, focussing all its capacities on COVID-19-related issues, communicating to the public directly and via media, as well as actively advising the national government. The case studies highlight the challenges posed by the increased time pressure, high demand for transparency, and communication of complexity and uncertainty. The article gives insights into how these challenges were addressed in our research institution and how science communication in general can be managed during a crisis

Functional consequences of seven novel mutations in the CYP11B1 Gene: four mutations associated with nonclassic and three mutations causing classic 11 -Hydroxylase Deficiency

Context: Steroid 11β-hydroxylase (CYP11B1) deficiency (11OHD) is the second most common form of congenital adrenal hyperplasia (CAH). Cases of nonclassic 11OHD are rare compared with the incidence of nonclassic 21-hydroxylase deficiency. Objective: The aim of the study was to analyze the functional consequences of seven novel CYP11B1 mutations (p.M88I, p.W116G, p.P159L, p.A165D, p.K254_A259del, p.R366C, p.T401A) found in three patients with classic 11OHD, two patients with nonclassic 11OHD, and three heterozygous carriers for CYP11B1 mutations. Methods: We conducted functional studies employing a COS7 cell in vitro expression system comparing wild-type (WT) and mutant CYP11B1 activity. Mutants were examined in a computational three-dimensional model of the CYP11B1 protein. Results: All mutations (p.W116G, p.A165D, p.K254_A259del) found in patients with classic 11OHD have absent or very little 11β-hydroxylase activity relative to WT. The mutations detected in patients with nonclassic 11OHD showed partial functional impairment, with one patient being homozygous (p.P159L; 25% of WT) and the other patient compound heterozygous for a novel mild p.M88I (40% of WT) and the known severe p.R383Q mutation. The two mutations detected in heterozygous carriers (p.R366C, p.T401A) also reduced CYP11B1 activity by 23 to 37%, respectively. Conclusion: Functional analysis results allow for the classification of novel CYP11B1 mutations as causative for classic and nonclassic 11OHD, respectively. Four partially inactivating mutations are predicted to result in nonclassic 11OHD. These findings double the number of mild CYP11B1 mutations previously described as associated with mild 11OHD. Our data are important to predict phenotypic expression and provide important information for clinical and genetic counseling i

Haplotyping the Vitis collinear core genome with rhAmpSeq improves marker transferability in a diverse genus

Transferable DNA markers are essential for breeding and genetics. Grapevine (Vitis) breeders utilize disease resistance alleles from congeneric species ~20 million years divergent, but existing Vitis marker platforms have cross-species transfer rates as low as 2%. Here, we apply a marker strategy targeting the inferred Vitis core genome. Incorporating seven linked-read de novo assemblies and three existing assemblies, the Vitis collinear core genome is estimated to converge at 39.8 Mb (8.67% of the genome). Adding shotgun genome sequences from 40 accessions enables identification of conserved core PCR primer binding sites flanking polymorphic haplotypes with high information content. From these target regions, we develop 2,000 rhAmpSeq markers as a PCR multiplex and validate the panel in four biparental populations spanning the diversity of the Vitis genus, showing transferability increases to 91.9%. This marker development strategy should be widely applicable for genetic studies in many taxa, particularly those ~20 million years divergent

Digitalization and sustainability: a call for a digital green deal

The relation between digitalization and environmental sustainability is ambiguous. There is potential of various digital technologies to slow down the transgression of planetary boundaries. Yet resource and energy demand for digital hardware production and use of data-intensive applications is of substantial size. The world over, there is no comprehensive regulation that addresses opportunities and risks of digital technology for sustainability. In this perspective article, we call for a Digital Green Deal that includes strong, cross-sectoral green digitalization policies on all levels of governance. We argue that a Digital Green Deal should first and foremost aim at greater policy coherence: Current digital policy initiatives should include measures that service environmental goals, and environmental policies must address risks and advance opportunities of digital technologies to spur sustainability transformations

Associations of Sleep Duration and Screen Time with Incidence of Overweight in European Children: The IDEFICS/I.Family Cohort

Introduction: Over the past decades, children have been increasingly using screen devices, while at the same time their sleep duration has decreased. Both behaviors have been associated with excess weight, and it is possible they act as mutually reinforcing behaviors for weight gain. The aim of the study was to explore independent, prospective associations of screen time and sleep duration with incident overweight in a sample of European children. Methods: Data from 4, 285 children of the IDEFICS/I.Family cohort who were followed up from 2009/2010 to 2013/2014 were analyzed. Hours per day of screen time and of sleep duration were reported by parents at baseline. Logistic regression analyses were carried out in separate and mutually adjusted models controlled for sex, age, European country region, parental level of education, and baseline BMI z-scores. Results: Among normal weight children at baseline (N = 3, 734), separate models suggest that every hour increase in screen time and every hour decrease in sleep duration were associated with higher odds of the child becoming overweight or obese at follow-up (OR = 1.16, 95% CI: 1.02-1.32 and OR = 1.23, 95% CI: 1.05-1.43, respectively). In the mutually adjusted model, both associations were attenuated slightly (screen time OR = 1.13, 95% CI: 0.99-1.28; sleep duration OR = 1.20, 95% CI: 1.03-1.40), being consistently somewhat stronger for sleep duration. Discussion/Conclusion: Both screen time and sleep duration increased the incidence of overweight or obesity by 13-20%. Interventions that include an emphasis on adequate sleep and minimal screen time are needed to establish their causal role in the prevention of overweight and obesity among European children. © 2021 The Author(s). Published by S. Karger AG, Basel

Genotype-Phenotype Correlation in 153 Adult Patients With Congenital Adrenal Hyperplasia due to 21-Hydroxylase Deficiency: Analysis of the United Kingdom Congenital Adrenal Hyperplasia Adult Study Executive (CaHASE) Cohort

CONTEXT: In congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency, a strong genotype-phenotype correlation exists in childhood. However, similar data in adults are lacking. OBJECTIVE: The objective of the study was to test whether the severity of disease-causing CYP21A2 mutations influences the treatment and health status in adults with CAH. RESEARCH DESIGN AND METHODS: We analyzed the genotype in correlation with treatment and health status in 153 adults with CAH from the United Kingdom Congenital adrenal Hyperplasia Adult Study Executive cohort. RESULTS: CYP21A2 mutations were distributed similarly to previously reported case series. In 7 patients a mutation was identified on only 1 allele. Novel mutations were detected on 1.7% of alleles (5 of 306). Rare mutations were found on 2.3% of alleles (7 of 306). For further analysis, patients were categorized into CYP21A2 mutation groups according to predicted residual enzyme function: null (n = 34), A (n = 42), B (n = 36), C (n = 34), and D (n = 7). Daily glucocorticoid dose was highest in group null and lowest in group C. Fludrocortisone was used more frequently in patients with more severe genotypes. Except for lower female height in group B, no statistically significant associations between genotype and clinical parameters were found. Androgens, blood pressure, lipids, blood glucose, and homeostasis model assessment of insulin resistance were not different between groups. Subjective health status was similarly impaired across groups. CONCLUSIONS: In adults with classic CAH and women with nonclassic CAH, there was a weak association between genotype and treatment, but health outcomes were not associated with genotype. The underrepresentation of males with nonclassic CAH may reflect that milder genotypes result in a milder condition that is neither diagnosed nor followed up in adulthood. Overall, our results suggest that the impaired health status of adults with CAH coming to medical attention is acquired rather than genetically determined and therefore could potentially be improved through modification of treatment

Towards environmentally sustainable human behaviour: targeting non-conscious and conscious processes for effective and acceptable policies.

Meeting climate change targets to limit global warming to 2°C requires rapid and large reductions in demand for products that most contribute to greenhouse gas (GHG) emissions. These include production of bulk materials (e.g. steel and cement), energy supply (e.g. fossil fuels) and animal source foods (particularly ruminants and their products). Effective strategies to meet these targets require transformative changes in supply as well as demand, involving changes in economic, political and legal systems at local, national and international levels, building on evidence from many disciplines. This paper outlines contributions from behavioural science in reducing demand. Grounded in dual-process models of human behaviour (involving non-conscious and conscious processes) this paper considers first why interventions aimed at changing population values towards the environment are usually insufficient or unnecessary for reducing demand although they may be important in increasing public acceptability of policies that could reduce demand. It then outlines two sets of evidence from behavioural science towards effective systems-based strategies, to identify interventions likely to be effective at: (i) reducing demand for products that contribute most to GHG emissions, mainly targeting non-conscious processes and (ii) increasing public acceptability for policy changes to enable these interventions, targeting conscious processes.This article is part of the themed issue 'Material demand reduction'

Warm-Start AlphaZero Self-Play Search Enhancements

Recently, AlphaZero has achieved landmark results in deep reinforcement learning, by providing a single self-play architecture that learned three different games at super human level. AlphaZero is a large and complicated system with many parameters, and success requires much compute power and fine-tuning. Reproducing results in other games is a challenge, and many researchers are looking for ways to improve results while reducing computational demands. AlphaZero's design is purely based on self-play and makes no use of labeled expert data ordomain specific enhancements; it is designed to learn from scratch. We propose a novel approach to deal with this cold-start problem by employing simple search enhancements at the beginning phase of self-play training, namely Rollout, Rapid Action Value Estimate (RAVE) and dynamically weighted combinations of these with the neural network, and Rolling Horizon Evolutionary Algorithms (RHEA). Our experiments indicate that most of these enhancements improve the performance of their baseline player in three different (small) board games, with especially RAVE based variants playing strongly