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During the Millennium Development Goal (MDG) era, many countries in Africa achieved marked reductions in under-5 and neonatal mortality. Yet the pace of progress toward these goals substantially varied at the national level, demonstrating an essential need for tracking even more local trends in child mortality. With the adoption of the Sustainable Development Goals (SDGs) in 2015, which established ambitious targets for improving child survival by 2030, optimal intervention planning and targeting will require understanding of trends and rates of progress at a higher spatial resolution. In this study, we aimed to generate high-resolution estimates of under-5 and neonatal all-cause mortality across 46 countries in Africa. We assembled 235 geographically resolved household survey and census data sources on child deaths to produce estimates of under-5 and neonatal mortality at a resolution of 5 × 5 km grid cells across 46 African countries for 2000, 2005, 2010, and 2015. We used a Bayesian geostatistical analytical framework to generate these estimates, and implemented predictive validity tests. In addition to reporting 5 × 5 km estimates, we also aggregated results obtained from these estimates into three different levels—national, and subnational administrative levels 1 and 2—to provide the full range of geospatial resolution that local, national, and global decision makers might require. Amid improving child survival in Africa, there was substantial heterogeneity in absolute levels of under-5 and neonatal mortality in 2015, as well as the annualised rates of decline achieved from 2000 to 2015. Subnational areas in countries such as Botswana, Rwanda, and Ethiopia recorded some of the largest decreases in child mortality rates since 2000, positioning them well to achieve SDG targets by 2030 or earlier. Yet these places were the exception for Africa, since many areas, particularly in central and western Africa, must reduce under-5 mortality rates by at least 8·8% per year, between 2015 and 2030, to achieve the SDG 3.2 target for under-5 mortality by 2030. In the absence of unprecedented political commitment, financial support, and medical advances, the viability of SDG 3.2 achievement in Africa is precarious at best. By producing under-5 and neonatal mortality rates at multiple levels of geospatial resolution over time, this study provides key information for decision makers to target interventions at populations in the greatest need. In an era when precision public health increasingly has the potential to transform the design, implementation, and impact of health programmes, our 5 × 5 km estimates of child mortality in Africa provide a baseline against which local, national, and global stakeholders can map the pathways for ending preventable child deaths by 2030. Bill & Melinda Gates Foundation.

Insufficient growth during childhood is associated with poor health outcomes and an increased risk of death. Between 2000 and 2015, nearly all African countries demonstrated improvements for children under 5 years old for stunting, wasting, and underweight, the core components of child growth failure. Here we show that striking subnational heterogeneity in levels and trends of child growth remains. If current rates of progress are sustained, many areas of Africa will meet the World Health Organization Global Targets 2025 to improve maternal, infant and young child nutrition, but high levels of growth failure will persist across the Sahel. At these rates, much, if not all of the continent will fail to meet the Sustainable Development Goal target—to end malnutrition by 2030. Geospatial estimates of child growth failure provide a baseline for measuring progress as well as a precision public health platform to target interventions to those populations with the greatest need, in order to reduce health disparities and accelerate progress. Geospatial estimates of child growth failure in Africa provide a baseline for measuring progress and a precision public health platform to target interventions to those populations with the greatest need. Mapping Africa's path to prosperity The UN's Sustainable Development Goals set a range of targets to improve global health and prosperity. Their success will rely on high-quality data to assess current progress and needs on a local scale. Simon Hay and colleagues study data gathered at the finest spatial scale yet of child growth and educational attainment across 51 African countries. The data show the spatiotemporal progression of these measures between 2000 and 2015 and reveal geographical inequalities. The authors use Bayesian-model-based geospatial mapping to estimate the prevalence of multiple outcomes related to child growth failure and educational inequality on a 5 kilometre by 5 kilometre scale, enabling them to estimate where various targets related to nutrition and educational attainment are more or less likely to be met.

Between 2000 and 2005 several studies revealed that morphine is more potent and exhibits fewer side effects in beta-arrestin 2 knockout mice. These findings spurred efforts to develop opioids that signal primarily via G protein activation and do not, or only very weakly, recruit beta-arrestin. Development of such molecules targeting the mu opioid receptor initially outpaced those targeting the kappa, delta and nociceptin opioid receptors, with the G protein-biased mu opioid agonist oliceridine/TRV130 having completed phase III clinical trials with improved therapeutic window to treat moderate-to-severe acute pain. Recently however, there has been a sharp increase in the development of novel G protein-biased kappa agonists. It is hypothesized that G protein-biased kappa agonists can reduce pain and itch, but exhibit fewer side effects, such as anhedonia and psychosis, that have thus far limited the clinical development of unbiased kappa opioid agonists. Here we summarize recently discovered G protein-biased kappa agonists, comparing structures, degree of signal bias and preclinical effects. We specifically reviewed nalfurafine, 22-thiocyanatosalvinorin A (RB-64), mesyl-salvinorin B, 2-(4-(furan-2-ylmethyl)-5-((4-methyl-3-(trifluoromethyl)benzyl)thio)-4H-1,2,4-triazol-3-yl)pyridine (triazole 1.1), 3-(2-((cyclopropylmethyl)(phenethyl)amino)ethyl)phenol (HS666), -butyl- -phenylethyl- -3-hydroxyphenylethyl-amine (compound 5/BPHA), 6-guanidinonaltrindole (6'GNTI), and collybolide. These agonists encompass a variety of chemical scaffolds and range in both their potency and efficacy in terms of G protein signaling and beta-arrestin recruitment. Thus unsurprisingly, the behavioral responses reported for these agonists are not uniform. Yet, it is our conclusion that the kappa opioid field will benefit tremendously from future studies that compare several biased agonists and correlate the degree of signaling bias to a particular pharmacological response.

ADP-ribosyltransferases use NAD + to catalyse substrate ADP-ribosylation 1 , and thereby regulate cellular pathways or contribute to toxin-mediated pathogenicity of bacteria 2 – 4 . Reversible ADP-ribosylation has traditionally been considered a protein-specific modification 5 , but recent in vitro studies have suggested nucleic acids as targets 6 – 9 . Here we present evidence that specific, reversible ADP-ribosylation of DNA on thymidine bases occurs in cellulo through the DarT–DarG toxin–antitoxin system, which is found in a variety of bacteria (including global pathogens such as Mycobacterium tuberculosis , enteropathogenic Escherichia coli and Pseudomonas aeruginosa ) 10 . We report the structure of DarT, which identifies this protein as a diverged member of the PARP family. We provide a set of high-resolution structures of this enzyme in ligand-free and pre- and post-reaction states, which reveals a specialized mechanism of catalysis that includes a key active-site arginine that extends the canonical ADP-ribosyltransferase toolkit. Comparison with PARP–HPF1, a well-established DNA repair protein ADP-ribosylation complex, offers insights into how the DarT class of ADP-ribosyltransferases evolved into specific DNA-modifying enzymes. Together, our structural and mechanistic data provide details of this PARP family member and contribute to a fundamental understanding of the ADP-ribosylation of nucleic acids. We also show that thymine-linked ADP-ribose DNA adducts reversed by DarG antitoxin (functioning as a noncanonical DNA repair factor) are used not only for targeted DNA damage to induce toxicity, but also as a signalling strategy for cellular processes. Using M. tuberculosis as an exemplar, we show that DarT–DarG regulates growth by ADP-ribosylation of DNA at the origin of chromosome replication. Structural and mechanistic data of the ADP-ribosyltransferase DarT demonstrate the role of ADP-ribosylation of DNA by this enzyme in generating toxicity and regulating cellular signalling processes in bacteria.

Many published studies in ecological science are viewed as stand‐alone investigations that purport to provide new insights into how ecological systems behave based on single analyses. But it is rare for results of single studies to provide definitive results, as evidenced in current discussions of the “reproducibility crisis” in science. The key step in science is the comparison of hypothesis‐based predictions with observations, where the predictions are typically generated by hypothesis‐specific models. Repeating this step allows us to gain confidence in the predictive ability of a model, and its corresponding hypothesis, and thus to accumulate evidence and eventually knowledge. This accumulation may occur via an ad hoc approach, via meta‐analyses, or via a more systematic approach based on the anticipated evolution of an information state. We argue the merits of this latter approach, provide an example, and discuss implications for designing sequences of studies focused on a particular question. We conclude by discussing current data collection programs that are preadapted to use this approach and argue that expanded use would increase the rate of learning in ecology, as well as our confidence in what is learned. Most scientific research papers in ecology are considered as stand‐alone constructions, whereas few ecological questions can be definitively answered with single studies. We advocate repeat tests of hypothesis‐based predictions against observations as a means of learning. Specifically, we recommend accumulating evidence using an evolving information state approach based on the predictive abilities of hypotheses.

Although the antibody-based recognition of cell-surface markers has been widely used for the identification of immune cells, overlap in the expression of markers by different cell types and the inconsistent use of antibody panels have resulted in a lack of clearly defined signatures for myeloid cell subsets. We developed a 10-fluorochrome flow cytometry panel for the identification and quantitation of myeloid cells in the lungs, including pulmonary monocytes, myeloid dendritic cells, alveolar and interstitial macrophages, and neutrophils. After the initial sorting of viable CD45(+) leukocytes, we detected three leukocyte subpopulations based on CD68 expression: CD68(-), CD68(low), and CD68(hi). Further characterization of the CD68(hi) population revealed CD45(+)/CD68(hi)/F4/80(+)/CD11b(-)/CD11c(+)/Gr1(-) alveolar macrophages and CD45(+)/CD68(hi)/F4/80(-)/CD11c(+)/Gr1(-)/CD103(+)/major histocompatibility complex (MHC) class II(hi) dendritic cells. The CD68(low) population contained primarily CD45(+)/CD68(low)/F4/80(+)/CD11b(+)/CD11c(+)/Gr1(-)/CD14(low) interstitial macrophages and CD45(+)/CD68(low)/F4/80(+)/CD11b(+)/CD11c(-)/Gr1(low)/CD14(hi) monocytes, whereas the CD68(-) population contained neutrophils (CD45(+)/CD68(-)/F4/80(-)/CD11b(+)/Gr1(hi)). The validity of cellular signatures was confirmed by a morphological analysis of FACS-sorted cells, functional studies, and the depletion of specific macrophage subpopulations using liposomal clodronate. We believe our approach provides an accurate and reproducible method for the isolation, quantification, and characterization of myeloid cell subsets in the lungs, which may be useful for studying the roles of myeloid cells during various pathological processes.

Purpose: Clinical next-generation sequencing (CNGS) is introducing new opportunities and challenges into the practice of medicine. Simultaneously, these technologies are generating uncertainties of an unprecedented scale that laboratories, clinicians, and patients are required to address and manage. We describe in this report the conceptual design of a new taxonomy of uncertainties around the use of CNGS in health care. Methods: Interviews to delineate the dimensions of uncertainty in CNGS were conducted with genomics experts and themes were extracted in order to expand on a previously published three-dimensional taxonomy of medical uncertainty. In parallel, we developed an interactive website to disseminate the CNGS taxonomy to researchers and engage them in its continued refinement. Results: The proposed taxonomy divides uncertainty along three axes—source, issue, and locus—and further discriminates the uncertainties into five layers with multiple domains. Using a hypothetical clinical example, we illustrate how the taxonomy can be applied to findings from CNGS and used to guide stakeholders through interpretation and implementation of variant results. Conclusion: The utility of the proposed taxonomy lies in promoting consistency in describing dimensions of uncertainty in publications and presentations, to facilitate research design and management of the uncertainties inherent in the implementation of CNGS. Genet Med advance online publication 19 January 2017

Summer annuals overwinter as seeds in the soil seed bank. This is facilitated by a cold-induced increase in dormancy during seed maturation followed by a switch to a state during seed imbibition in which cold instead promotes germination. Here, we show that the seed maturation transcriptome in Arabidopsis thaliana is highly temperature sensitive and reveal that low temperature during seed maturation induces several genes associated with dormancy, including DELAY OF GERMINATI0N1 [DOG1), and influences gibberellin and abscisic acid levels in mature seeds. Mutants lacking DOG1, or with altered gibberellin or abscisic acid synthesis or signaling, in turn show reduced ability to enter the deeply dormant states in response to low seed maturation temperatures. In addition, we find that DOG1 promotes gibberellin catabolism during maturation. We show that C-REPEAT BINDING FACTORS (CBFs) are necessary for regulation of dormancy and of GA2OX6 and DOG1 expression caused by low temperatures. However, the temperature sensitivity of CBF transcription is markedly reduced in seeds and is absent in imbibed seeds. Our data demonstrate that inhibition of CBF expression is likely a critical feature allowing cold to promote rather than inhibit germination and support a model in which CBFs act in parallel to a low-temperature signaling pathway in the regulation of dormancy.