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BEIR VII develops the most up-to-date and comprehensive risk estimates for cancer and other health effects from exposure to low-level ionizing radiation. It is among the first reports of its kind to include detailed estimates for cancer incidence in addition to cancer mortality. In general, BEIR VII supports previously reported risk estimates for cancer and leukemia, but the availability of new and more extensive data have strengthened confidence in these estimates. A comprehensive review of available biological and biophysical data supports a \"linear-no-threshold\" (LNT) risk model-that the risk of cancer proceeds in a linear fashion at lower doses without a threshold and that the smallest dose has the potential to cause a small increase in risk to humans. The report is from the Board on Radiation Research Effects that is now part of the newly formed Nuclear and Radiation Studies Board.

This volume is part of the ongoing review of the underlying scientific bases for decision-making in chemical risk assessment by International Programme on Chemical Safety. It involves specific consideration of the area of dose-response assessment in the evaluation of information from toxicological studies in animals and from human clinical and epidemiological studies. It covers toxicants with threshold effects and those for which there may be no practical threshold, such as substances that are genotoxic and carcinogenic. The discussions are concerned with that subset of cause-effect relationships commonly referred to as dose-response models, which are typically used to characterize the biological effects of intentional (e.g. drugs and nutrients) and unintentional (e.g. contaminants) exposure to chemicals.This report is intended primarily to provide descriptive guidance for risk assessors in using dose-response modelling in hazard characterization. It will also provide mathematical modellers with an appreciation of issues to be considered when modelling in the context of the risk assessment process. Risk managers will be able to obtain a general understanding of the applications and limitations of dose-response modelling. For both risk assessors and risk managers, some considerations for communicating the results of risk assessments that use dose-response modelling are presented.

Risk assessment has become a dominant public policy tool for making choices, based on limited resources, to protect public health and the environment. It has been instrumental to the mission of the U.S. Environmental Protection Agency (EPA) as well as other federal agencies in evaluating public health concerns, informing regulatory and technological decisions, prioritizing research needs and funding, and in developing approaches for cost-benefit analysis. However, risk assessment is at a crossroads. Despite advances in the field, risk assessment faces a number of significant challenges including lengthy delays in making complex decisions; lack of data leading to significant uncertainty in risk assessments; and many chemicals in the marketplace that have not been evaluated and emerging agents requiring assessment. Science and Decisions makes practical scientific and technical recommendations to address these challenges. This book is a complement to the widely used 1983 National Academies book, Risk Assessment in the Federal Government (also known as the Red Book). The earlier book established a framework for the concepts and conduct of risk assessment that has been adopted by numerous expert committees, regulatory agencies, and public health institutions. The new book embeds these concepts within a broader framework for risk-based decision-making. Together, these are essential references for those working in the regulatory and public health fields.

By means of meta-analyses we determined how 70 traits related to plant anatomy, morphology, chemistry, physiology, growth and reproduction are affected by daily light integral (DLI; mol photons m−2 d−1). A large database including 500 experiments with 760 plant species enabled us to determine generalized dose–response curves. Many traits increase with DLI in a saturating fashion. Some showed a more than 10-fold increase over the DLI range of 1–50 mol m−2 d−1, such as the number of seeds produced per plant and the actual rate of photosynthesis. Strong decreases with DLI (up to three-fold) were observed for leaf area ratio and leaf payback time. Plasticity differences among species groups were generally small compared with the overall responses to DLI. However, for a number of traits, including photosynthetic capacity and realized growth, we found woody and shade-tolerant species to have lower plasticity. We further conclude that the direction and degree of trait changes adheres with responses to plant density and to vertical light gradients within plant canopies. This synthesis provides a strong quantitative basis for understanding plant acclimation to light, from molecular to whole plant responses, but also identifies the variables that currently form weak spots in our knowledge, such as respiration and reproductive characteristics.

1. Marine mammals may be negatively affected by anthropogenic noise. Behavioural response studies (BRS) aim to establish a relationship between noise exposure conditions (dose) from a potential Stressor and associated behavioural responses of animals. A recent series of BRS have focused on the effects of naval sonar sounds on cetaceans. Here, we review the current state of understanding of naval sonar impact on marine mammals and highlight knowledge gaps and future research priorities. 2. Many marine mammal species exhibit responses to naval sonar sounds. However, responses vary between and within individuals and populations, highlighting the importance of exposure context in modulating dose-response relationships. 3. There is increasing support from both terrestrial and marine systems for the risk-disturbance hypothesis as an explanation for underlying response processes. This proposes that sonar sounds may be perceived by animals as a threat, evoking a response shaped by the underlying species-specific risk of predation and antipredator strategy. An understanding of responses within both the dose-response and risk-disturbance frameworks may enhance our ability to predict responsiveness for unstudied species and populations. 4. Many observed behavioural responses are energetically costly, but the way that these responses may lead to long-term individual and population-level impacts is poorly understood. 5. Synthesis and applications. Behavioural response studies have greatly improved our understanding of the potential effects of naval sonar on marine mammals. Despite data gaps, we believe a dose-response approach within a risk-disturbance framework will enhance our ability to predict responsiveness for unstudied species and populations. W e advocate for (1) regulatory frameworks to utilize peer-reviewed research findings when making predictions of impact, (2) regulatory frameworks to account for the inherent uncertainty in predictions of impact and (3) investment in monitoring programmes that are both directed by recent research and offer opportunities for validation of predictions at the individual and population level.

The anti–interleukin-1 antibody canakinumab was effective at controlling and preventing recurrence of flares in autoimmune inflammatory diseases: familial Mediterranean fever, mevalonate kinase deficiency, and the TNF receptor–associated periodic syndrome.

Dose–response relationships reflect the effects of a substance on organisms, and are widely used in broad research areas, from medicine and physiology, to vector control and pest management in agronomy. Furthermore, reporting on the response of organisms to stressors is an essential component of many public policies (e.g. public health, environment), and assessment of xenobiotic responses is an integral part of World Health Organization recommendations. Building upon an R script that we previously made available, and considering its popularity, we have now developed a software package in the R environment, BioRssay , to efficiently analyze dose–response relationships. It has more user-friendly functions and more flexibility, and proposes an easy interpretation of the results. The functions in the BioRssay package are built on robust statistical analyses to compare the dose/exposure–response of various bioassays and effectively visualize them in probit-graphs. Graphical Abstract

Patients with moderate-to-severe ulcerative colitis were randomly assigned to receive placebo or induction doses of ustekinumab. Patients who had a response to induction therapy underwent a second randomization to maintenance therapy with ustekinumab or placebo. Ustekinumab was more effective than placebo for inducing and maintaining remission.

Dose-response analysis can be carried out using multi-purpose commercial statistical software, but except for a few special cases the analysis easily becomes cumbersome as relevant, non-standard output requires manual programming. The extension package drc for the statistical environment R provides a flexible and versatile infrastructure for dose-response analyses in general. The present version of the package, reflecting extensions and modifications over the last decade, provides a user-friendly interface to specify the model assumptions about the dose-response relationship and comes with a number of extractors for summarizing fitted models and carrying out inference on derived parameters. The aim of the present paper is to provide an overview of state-of-the-art dose-response analysis, both in terms of general concepts that have evolved and matured over the years and by means of concrete examples.