We conducted meta-analyses to assess risk for anxiety disorders among offspring of parents with anxiety disorders, and to establish whether there is evidence of specificity of risk for anxiety ...disorders as opposed to depression in offspring, and whether particular parent anxiety disorders confer risks for particular child anxiety disorders. We also examined whether risk was moderated by offspring age, gender, temperament, and the presence of depressive disorders in parents.
We searched PsycINFO, PubMed, and Web of Science in June, 2016, and July, 2017 (PROSPERO CRD42016048814). Study inclusion criteria were as follows: published in peer-reviewed journals; contained at least one group of parents with anxiety disorders and at least one comparison group of parents who did not have anxiety disorders; reported rates of anxiety disorders in offspring; and used validated diagnostic tools to ascertain diagnoses. We used random and mixed-effects models and evaluated study quality.
We included 25 studies (7,285 offspring). Where parents had an anxiety disorder, offspring were significantly more likely to have anxiety (risk ratio RR = 1.76, 95% CI = 1.58−1.96) and depressive disorders (RR = 1.31, 95% CI = 1.13−1.52) than offspring of parents without anxiety disorders. Parent panic disorder and generalized anxiety disorder appeared to confer particular risk. Risk was greater for offspring anxiety than for depressive disorders (RR = 2.50, 95% CI = 1.50−4.16), and specifically for offspring generalized anxiety disorder, separation anxiety disorder and specific phobia, but there was no evidence that children of parents with particular anxiety disorders were at increased risk for the same particular anxiety disorders. Moderation analyses were possible only for offspring age, sex, and parental depressive disorder; none were significant.
Parent anxiety disorders pose specific risks of anxiety disorders to offspring. However, there is limited support for transmission of the same particular anxiety disorder. These results support the potential for targeted prevention of anxiety disorders.
There is growing interest in estimating and analyzing heterogeneous treatment effects in experimental and observational studies. We describe a number of metaalgorithms that can take advantage of any ...supervised learning or regression method in machine learning and statistics to estimate the conditional average treatment effect (CATE) function. Metaalgorithms build on base algorithms—such as random forests (RFs), Bayesian additive regression trees (BARTs), or neural networks—to estimate the CATE, a function that the base algorithms are not designed to estimate directly. We introduce a metaalgorithm, the X-learner, that is provably efficient when the number of units in one treatment group is much larger than in the other and can exploit structural properties of the CATE function. For example, if the CATE function is linear and the response functions in treatment and control are Lipschitz-continuous, the X-learner can still achieve the parametric rate under regularity conditions. We then introduce versions of the X-learner that use RF and BART as base learners. In extensive simulation studies, the X-learner performs favorably, although none of the metalearners is uniformly the best. In two persuasion field experiments from political science, we demonstrate how our X-learner can be used to target treatment regimes and to shed light on underlying mechanisms. A software package is provided that implements our methods.
The Community Land Model is the land component of the Community Climate System Model. Here, we describe a broad set of model improvements and additions that have been provided through the CLM ...development community to create CLM4. The model is extended with a carbon-nitrogen (CN) biogeochemical model that is prognostic with respect to vegetation, litter, and soil carbon and nitrogen states and vegetation phenology. An urban canyon model is added and a transient land cover and land use change (LCLUC) capability, including wood harvest, is introduced, enabling study of historic and future LCLUC on energy, water, momentum, carbon, and nitrogen fluxes. The hydrology scheme is modified with a revised numerical solution of the Richards equation and a revised ground evaporation parameterization that accounts for litter and within-canopy stability. The new snow model incorporates the SNow and Ice Aerosol Radiation model (SNICAR) - which includes aerosol deposition, grain-size dependent snow aging, and vertically-resolved snowpack heating – as well as new snow cover and snow burial fraction parameterizations. The thermal and hydrologic properties of organic soil are accounted for and the ground column is extended to ~50-m depth. Several other minor modifications to the land surface types dataset, grass and crop optical properties, atmospheric forcing height, roughness length and displacement height, and the disposition of snow-capped runoff are also incorporated.Taken together, these augmentations to CLM result in improved soil moisture dynamics, drier soils, and stronger soil moisture variability. The new model also exhibits higher snow cover, cooler soil temperatures in organic-rich soils, greater global river discharge, and lower albedos over forests and grasslands, all of which are improvements compared to CLM3.5. When CLM4 is run with CN, the mean biogeophysical simulation is slightly degraded because the vegetation structure is prognostic rather than prescribed, though running in this mode also allows more complex terrestrial interactions with climate and climate change.
Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further ...to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past–future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-management strategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land–atmosphere coupling strength, and the extent to which impacts of enhanced CO2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.
This phase 3 trial evaluated the safety and efficacy of inclisiran, a small interfering RNA that inhibits hepatic PCSK9 synthesis, in 482 adults with heterozygous familial hypercholesterolemia, who ...received subcutaneous injections of inclisiran or placebo on days 1, 90, 270, and 450. Changes in cholesterol were assessed up to day 540.
Although the objective of any ‘omic science is broad measurement of its constituents, such coverage has been challenging in metabolomics because the metabolome is comprised of a chemically diverse ...set of small molecules with variable physical properties. While extensive studies have been performed to identify metabolite isolation and separation methods, these strategies introduce bias toward lipophilic or water-soluble metabolites depending on whether reversed-phase (RP) or hydrophilic interaction liquid chromatography (HILIC) is used, respectively. Here we extend our consideration of metabolome isolation and separation procedures to integrate RPLC/MS and HILIC/MS profiling. An aminopropyl-based HILIC/MS method was optimized on the basis of mobile-phase additives and pH, followed by evaluation of reproducibility. When applied to the untargeted study of perturbed bacterial metabolomes, the HILIC method enabled the accurate assessment of key, dysregulated metabolites in central carbon pathways (e.g., amino acids, organic acids, phosphorylated sugars, energy currency metabolites), which could not be retained by RPLC. To demonstrate the value of the integrative approach, bacterial cells, human plasma, and cancer cells were analyzed by combined RPLC/HILIC separation coupled to ESI positive/negative MS detection. The combined approach resulted in the observation of metabolites associated with lipid and central carbon metabolism from a single biological extract, using 80% organic solvent (ACN:MeOH:H2O 2:2:1). It enabled the detection of more than 30,000 features from each sample type, with the highest number of uniquely detected features by RPLC in ESI positive mode and by HILIC in ESI negative mode. Therefore, we conclude that when time and sample are limited, the maximum amount of biological information related to lipid and central carbon metabolism can be acquired by combining RPLC ESI positive and HILIC ESI negative mode analysis.
The imine linkages of two layered, porous covalent organic frameworks (COFs), TPB-TP-COF (C6H3(C6H4N)32C6H4(CH)23, 1) and 4PE-1P-COF (C2(C6H4N)4C6H4(CH)22, 2), have been transformed into amide ...linkages to make the respective isostructural amide COFs 1′ and 2′ by direct oxidation with retention of crystallinity and permanent porosity. Remarkably, the oxidation of both imine COFs is complete, as assessed by FT-IR and 13C CP-MAS NMR spectroscopy and demonstrates (a) the first chemical conversion of a COF linkage and (b) how the usual “crystallization problem” encountered in COF chemistry can be bypassed to access COFs, such as these amides, that are typically thought to be difficult to obtain by the usual de novo methods. The amide COFs show improved chemical stability relative to their imine progenitors.
Mental health disorders in children and adolescents are highly prevalent yet undertreated. A detailed understanding of the reasons for not seeking or accessing help as perceived by young people is ...crucial to address this gap. We conducted a systematic review (PROSPERO 42018088591) of quantitative and qualitative studies reporting barriers and facilitators to children and adolescents seeking and accessing professional help for mental health problems. We identified 53 eligible studies; 22 provided quantitative data, 30 provided qualitative data, and one provided both. Four main barrier/facilitator themes were identified. Almost all studies (96%) reported barriers related to young people’s individual factors, such as limited mental health knowledge and broader perceptions of help-seeking. The second most commonly (92%) reported theme related to social factors, for example, perceived social stigma and embarrassment. The third theme captured young people’s perceptions of the therapeutic relationship with professionals (68%) including perceived confidentiality and the ability to trust an unknown person. The fourth theme related to systemic and structural barriers and facilitators (58%), such as financial costs associated with mental health services, logistical barriers, and the availability of professional help. The findings highlight the complex array of internal and external factors that determine whether young people seek and access help for mental health difficulties. In addition to making effective support more available, targeted evidence-based interventions are required to reduce perceived public stigma and improve young people’s knowledge of mental health problems and available support, including what to expect from professionals and services.
Long-term dietary intake influences the structure and activity of the trillions of microorganisms residing in the human gut, but it remains unclear how rapidly and reproducibly the human gut ...microbiome responds to short-term macronutrient change. Here we show that the short-term consumption of diets composed entirely of animal or plant products alters microbial community structure and overwhelms inter-individual differences in microbial gene expression. The animal-based diet increased the abundance of bile-tolerant microorganisms (Alistipes, Bilophila and Bacteroides) and decreased the levels of Firmicutes that metabolize dietary plant polysaccharides (Roseburia, Eubacterium rectale and Ruminococcus bromii). Microbial activity mirrored differences between herbivorous and carnivorous mammals, reflecting trade-offs between carbohydrate and protein fermentation. Foodborne microbes from both diets transiently colonized the gut, including bacteria, fungi and even viruses. Finally, increases in the abundance and activity of Bilophila wadsworthia on the animal-based diet support a link between dietary fat, bile acids and the outgrowth of microorganisms capable of triggering inflammatory bowel disease. In concert, these results demonstrate that the gut microbiome can rapidly respond to altered diet, potentially facilitating the diversity of human dietary lifestyles.
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