Trusting the Health System and COVID 19 Restriction Compliance

We examine the extent to which exposure to higher relative COVID-19 mortality (RM), influences health system trust (HST), and whether changes in HST explain the perceived ease of compliance with pandemic restrictions during the COVID-19 pandemic. Drawing on evidence from two representative surveys covering all regions of 28 European countries before and after the first COVID-19 wave, and using a difference in differences strategy together with Coarsened Exact Matching (CEM), we document that living in a region with higher RM during the first wave of the pandemic increased HST. However, the positive effect of RM on HST is driven by individuals over 45 years of age, and the opposite effect is found among younger cohorts. Furthemore, we find that a higher HST reduces the costs of complying with COVID-19 restrictions, but only so long as excess mortality does not exceed the average by more than 20%, at which point the ease of complying with COVID-19 restrictions significantly declines, offsetting the positive effect of trust in the healthcare system. Our interpretation of these estimates is that a higher RM is interpreted as a risk signal among those over 45, and as a signal of health-care system failure among younger age individuals.     

Cucumber mosaic virus genome is encapsidated in alfalfa mosaic virus coat protein expressed in transgenic tobacco plants

The expression of viral coat protein (CP) in transgenic plants has been shown to be very effective in virus plant protection. However, the introduction of CP genes into plants presents the potential risk of the encapsidation of a superinfecting viral genome in the transgenic protein, an event which could change the epidemiology of the disease. To detect the potential heterologous encapsidation of the cucumber mosaic virus (CMV) genome by alfalfa mosaic virus (AIMV) CP expressed in transgenic tobacco plants, a system of immunocapture (IC) and amplification by polymerase chain reaction (PCR) was optimized. This provided high sensitivity and reliable selection of the heterologously encapsidated CMV genome in the presence of natural CMV particles. As little as 2 pg of virus could be detected by immunocapture/polymerase chain reaction (IC/PCR) technique. Evidence for heterologous encapsidation of the CMV genome was found in 11 of the 33 transgenic plants tested two weeks after CMV inoculation. This demonstrates a significant rate of heterologous encapsidation events between two unrelated viruses in transgenic plants. Since CP is involved in the interactions of the virus particle with its vector, the release in the field of such transgenic plants could alter the transmission properties of some important viruses.     

Dietary exposure and risk assessment to trace elements and iodine in seaweeds

IntroductionSeaweeds are a rich source of elements such as iodine, and are also able to accumulate contaminants such as trace elements.MethodsThe aim of this study was to assess the dietary exposure as well as the risk from iodine and trace elements in edible seaweeds for the French population using current consumption data. The contribution of seaweeds to overall dietary exposure to trace elements and iodine was evaluated, and for those substances with minimal contribution to overall dietary exposure, simulations were performed to propose increased maximal limits in seaweeds.ResultsCadmium, inorganic arsenic and mercury in seaweeds were very low contributors to total dietary exposure to these contaminants (0.7 % 1.1 % and 0.1 % on average, respectively). Dietary exposure to lead via seaweed may contribute up to 3.1 % of total dietary exposure. Dietary consumption of iodine via seaweed may contribute up to 33 % of total exposure to iodine, which makes seaweeds the strongest contributor to iodine in diet.DiscussionNew maximal values in seaweeds are proposed for the very low contributors to total dietary exposure: 1 mg/kg dw for cadmium, 10 mg/kg dw for inorganic arsenic and 0.3 mg/kg dw for mercury.     

Cross-trait prediction accuracy of summary statistics in genome-wide association studies

In the era of big data, univariate models have widely been used as a workhorse tool for quickly producing marginal estimators; and this is true even when in a high-dimensional dense setting, in which many features are “true,” but weak signals. Genome-wide association studies (GWAS) epitomize this type of setting. Although the GWAS marginal estimator is popular, it has long been criticized for ignoring the correlation structure of genetic variants (i.e., the linkage disequilibrium [LD] pattern). In this paper, we study the effects of LD pattern on the GWAS marginal estimator and investigate whether or not additionally accounting for the LD can improve the prediction accuracy of complex traits. We consider a general high-dimensional dense setting for GWAS and study a class of ridge-type estimators, including the popular marginal estimator and the best linear unbiased prediction (BLUP) estimator as two special cases. We show that the performance of GWAS marginal estimator depends on the LD pattern through the first three moments of its eigenvalue distribution. Furthermore, we uncover that the relative performance of GWAS marginal and BLUP estimators highly depends on the ratio of GWAS sample size over the number of genetic variants. Particularly, our finding reveals that the marginal estimator can easily become near-optimal within this class when the sample size is relatively small, even though it ignores the LD pattern. On the other hand, BLUP estimator has substantially better performance than the marginal estimator as the sample size increases toward the number of genetic variants, which is typically in millions. Therefore, adjusting for the LD (such as in the BLUP) is most needed when GWAS sample size is large. We illustrate the importance of our results by using the simulated data and real GWAS.     

The prevalence of root surface caries amongst Irish adults

In a national survey of adult dental health conducted in the Republic of Ireland in 1989/90 a total of 1,527 subjects aged 25 and older were examined for root surface caries. It was found that the prevalence of root surface caries was highest in older age groups and also amongst males, residents of non-fluoridated communities and those earning low incomes. Tooth loss masked the potential prevalence of root surface caries. With more persons retaining their natural teeth into middle and old age the prevalence of root surface caries is likely to increase in the future.     

CryoRes: Local Resolution Estimation of Cryo-EM Density Maps by Deep Learning

Recent progress in cryo-EM research has ignited a revolution in biological macromolecule structure determination. Resolution is an essential parameter for quality assessment of a cryo-EM density map, and it is known that resolution varies in different regions of a map. Currently available methods for local resolution estimation require manual adjustment of parameters and in some cases necessitate acquisition or de novo generation of so-called “half maps”. Here, we developed CryoRes, a deep-learning algorithm to estimate local resolution directly from a single final cryo-EM density map, specifically by learning resolution-aware patterns of density map voxels through supervised training on a large dataset comprising 1,174 experimental cryo-EM density maps. CryoRes significantly outperforms all of the state-of-the-art competing resolution estimation methods, achieving an average RMSE of 2.26 Å for local resolution estimation relative to the currently most reliable FSC-based method blocres, yet requiring only the single final map as input. Further, CryoRes is able to generate a molecular mask for each map, with accuracy 12.12% higher than the masks generated by ResMap. CryoRes is ultra-fast, fully automatic, parameter-free, applicable to cryo-EM subtomogram data, and freely available at https://cryores.zhanglab.net.     

Bias-reduced estimators of conditional odds ratios in matched case-control studies with unmatched confounding

We study bias-reduced estimators of exponentially transformed parameters in general linear models (GLMs) and show how they can be used to obtain bias-reduced conditional (or unconditional) odds ratios in matched case-control studies. Two options are considered and compared: the explicit approach and the implicit approach. The implicit approach is based on the modified score function where bias-reduced estimates are obtained by using iterative procedures to solve the modified score equations. The explicit approach is shown to be a one-step approximation of this iterative procedure. To apply these approaches for the conditional analysis of matched case-control studies, with potentially unmatched confounding and with several exposures, we utilize the relation between the conditional likelihood and the likelihood of the unconditional logit binomial GLM for matched pairs and Cox partial likelihood for matched sets with appropriately setup data. The properties of the estimators are evaluated by using a large Monte Carlo simulation study and an illustration of a real dataset is shown. Researchers reporting the results on the exponentiated scale should use bias-reduced estimators since otherwise the effects can be under or overestimated, where the magnitude of the bias is especially large in studies with smaller sample sizes.     

Substance use disorders: a comprehensive update of classification,epidemiology, neurobiology,clinical aspects,treatment and prevention

Substance use disorders (SUDs) are highly prevalent and exact a large toll on individuals’ health, well-being, and social functioning. Long-lasting changes in brain networks involved in reward, executive function, stress reactivity, mood, and self-awareness underlie the intense drive to consume substances and the inability to control this urge in a person who suffers from addiction (moderate or severe SUD). Biological (including genetics and developmental life stages) and social (including adverse childhood experiences) determinants of health are recognized factors that contribute to vulnerability for or resilience against developing a SUD. Consequently, prevention strategies that target social risk factors can improve outcomes and, when deployed in childhood and adolescence, can decrease the risk for these disorders. SUDs are treatable, and evidence of clinically significant benefit exists for medications (in opioid, nicotine and alcohol use disorders), behavioral therapies (in all SUDs), and neuromodulation (in nicotine use disorder). Treatment of SUDs should be considered within the context of a Chronic Care Model, with the intensity of intervention adjusted to the severity of the disorder and with the concomitant treatment of comorbid psychiatric and physical conditions. Involvement of health care providers in detection and management of SUDs, including referral of severe cases to specialized care, offers sustainable models of care that can be further expanded with the use of telehealth. Despite advances in our understanding and management of SUDs, individuals with these conditions continue to be stigmatized and, in some countries, incarcerated, highlighting the need to dismantle policies that perpetuate their criminalization and instead develop policies to ensure support and access to prevention and treatment.