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Background Adaptations of evidence-based interventions (EBIs) often occur. However, little is known about the reasons for adaptation, the adaptation process, and outcomes of adapted EBIs. To address this gap, we conducted a systematic review to answer the following questions: (1) What are the reasons for and common types of adaptations being made to EBIs in community settings as reported in the published literature? (2) What steps are described in making adaptations to EBIs? and (3) What outcomes are assessed in evaluations of adapted EBIs? Methods We conducted a systematic review of English language publications that described adaptations of public health EBIs. We searched Ovid PubMed, PsycINFO, PsycNET, and CINAHL and citations of included studies for adapted public health EBIs. We abstracted characteristics of the original and adapted populations and settings, reasons for adaptation, types of modifications, use of an adaptation framework, adaptation steps, and evaluation outcomes. Results Forty-two distinct EBIs were found focusing on HIV/AIDS, mental health, substance abuse, and chronic illnesses. More than half (62%) reported on adaptations in the USA. Frequent reasons for adaptation included the need for cultural appropriateness (64.3%), focusing on a new target population (59.5%), and implementing in a new setting (57.1%). Common adaptations were content (100%), context (95.2%), cultural modifications (73.8%), and delivery (61.9%). Most study authors conducted a community assessment, prepared new materials, implemented the adapted intervention, evaluated or planned to evaluate the intervention, determined needed changes, trained staff members, and consulted experts/stakeholders. Most studies that reported an evaluation ( k  = 36) included behavioral outcomes (71.4%), acceptability (66.7%), fidelity (52.4%), and feasibility (52.4%). Fewer measured adoption (47.6%) and changes in practice (21.4%). Conclusions These findings advance our understanding of the patterns and effects of modifications of EBIs that are reported in published studies and suggest areas of further research to understand and guide the adaptation process. Furthermore, findings can inform better reporting of adapted EBIs and inform capacity building efforts to assist health professionals in adapting EBIs.

Maps showing the thickness of sediments above the bedrock (depth to bedrock, or DTB) are important for many geoscience studies and are necessary for many hydrogeological, engineering, mining, and forestry applications. However, it can be difficult to accurately estimate DTB in areas with varied topography, like lowland and mountainous terrain, because traditional methods of predicting bedrock elevation often underestimate or overestimate the elevation in rugged or incised terrain. Here, we describe a machine learning spatial prediction approach that uses information from traditional digital elevation model derived estimates of terrain morphometry and satellite imagery, augmented with spatial feature engineering techniques to predict DTB across Alberta, Canada. First, compiled measurements of DTB from borehole lithologs were used to train a natural language model to predict bedrock depth across all available lithologs, significantly increasing the dataset size. The combined data were then used for DTB modelling employing several algorithms (XGBoost, Random forests, and Cubist) and spatial feature engineering techniques, using a combination of geographic coordinates, proximity measures, neighbouring points, and spatially lagged DTB estimates. Finally, the results were contrasted with DTB predictions based on modelled relationships with the auxiliary variables, as well as conventional spatial interpolations using inverse-distance weighting and ordinary kriging methods. The results show that the use of spatially lagged variables to incorporate information from the spatial structure of the training data significantly improves predictive performance compared to using auxiliary predictors and/or geographic coordinates alone. Furthermore, unlike some of the other tested methods such as using neighbouring point locations directly as features, spatially lagged variables did not generate spurious spatial artifacts in the predicted raster maps. The proposed method is demonstrated to produce reliable results in several distinct physiographic sub-regions with contrasting terrain types, as well as at the provincial scale, indicating its broad suitability for DTB mapping in general.

Wall shear stress (WSS), the frictional force of the blood on the vessel wall, plays a crucial role in atherosclerotic plaque development. Low WSS has been associated with plaque growth, however previous research used different approaches to define low WSS to investigate its effect on plaque progression. In this study, we used four methodologies to allocate low, mid and high WSS in one dataset of human coronary arteries and investigated the predictive power of low WSS for plaque progression. Coronary reconstructions were based on multimodality imaging, using intravascular ultrasound and CT-imaging. Vessel-specific flow was measured using Doppler wire and computational fluid dynamics was performed to calculate WSS. The absolute WSS range varied greatly between the coronary arteries. On the population level, the established pattern of most plaque progression at low WSS was apparent in all methodologies defining the WSS categories. However, for the individual patient, when using measured flow to determine WSS, the absolute WSS values range so widely, that the use of absolute thresholds to determine low WSS was not appropriate to identify regions at high risk for plaque progression.

Purpose Breast cancer incidence and survival is high, which results in high prevalence of breast cancer survivors. The risk of (death from) cardiovascular disease (CVD) is higher in patients exposed to cardiotoxic treatments, in particular if they have pre-existing CVD risk factors. This study systematically summarized the risk of death from CVD following breast cancer. Methods Databases of Medline, Embase, and the Cochrane Library were systematically searched using the following terms and synonyms: breast cancer, cardiovascular disease, and cause of death. Articles reporting on both risk and risk factors of CVD mortality following breast cancer were eligible for inclusion. The methodological quality of each article was assessed using the Newcastle Ottawa quality assessment scale for cohort studies. Results Fourteen articles were included assessing the risk of CVD mortality among 1,217,910 women with breast cancer. The methodological quality was high for the majority of the studies. Studies were heterogeneous in design, study population, length of follow-up, CVD outcomes, and risk factors. 1.6–10.4% of all women with breast cancer died of CVD. Women with breast cancer had a higher risk of CVD mortality than women from the general population. The risk of CVD mortality was higher among women with breast cancer with older age at diagnosis, left-sided tumor, diagnosis in an earlier calendar period, and black ethnic origin. Conclusions CVD is an important cause of death following breast cancer. Identification of patients at high risk of CVD is important to optimize CVD prevention and tailor breast cancer treatment.

There have been many studies examining the differences between infant-directed speech (IDS) and adult-directed speech (ADS). However, investigations asking whether mothers clarify vowel articulation in IDS have reached equivocal findings. Moreover, it is unclear whether maternal speech clarification has any effect on a child's developing language skills. This study examined vowel clarification in mothers’ IDS at 0;10–11, 1;6, and 2;0, as compared to their vowel production in ADS. Relationships between vowel space, vowel duration, and vowel variability and child language outcomes at two years were also explored. Results show that vowel space and vowel duration tended to be greater in IDS than in ADS, and that one measure of vowel clarity, a mother's vowel space at 1;6, was significantly related to receptive as well as expressive child language outcomes at two years of age.

Plants have amazing regenerative properties with single somatic cells, or groups of cells able to give rise to fully formed plants. One means of regeneration is somatic embryogenesis, by which an embryonic structure is formed that “converts” into a plantlet. Somatic embryogenesis has been used as a model for zygotic processes that are buried within layers of maternal tissues. Understanding mechanisms of somatic embryo induction and development are important as a more accessible model for seed development. We rely on seed development not only for most of our caloric intake, but also as a delivery system for engineered crops to meet agricultural challenges. Regeneration of transformed cells is needed for this applied work as well as basic research to understand gene function. Here we focus on a MADS-domain transcription factor, AGAMOUS-Like15 (AGL15) that shows a positive correlation between accumulation levels and capacity for somatic embryogenesis. We relate AGL15 function to other transcription factors, hormones, and epigenetic modifiers involved in somatic embryo development.

BACKGROUNDMyotonic dystrophy type 1 (DM1) is a multisystemic, CTG repeat expansion disorder characterized by a slow, progressive decline in skeletal muscle function. A biomarker correlating RNA mis-splicing, the core pathogenic disease mechanism, and muscle performance is crucial for assessing response to disease-modifying interventions. We evaluated the Myotonic Dystrophy Splice Index (SI), a composite RNA splicing biomarker incorporating 22 disease-specific events, as a potential biomarker of DM1 muscle weakness.METHODSTotal RNA sequencing of tibialis anterior biopsies from 58 DM1 participants and 33 unaffected/disease controls was used to evaluate RNA splicing events across the disease spectrum. Targeted RNA sequencing was used to derive the SI from biopsies collected at baseline (n = 52) or a 3-month (n = 37) follow-up visit along with clinical measures of muscle performance.RESULTSThe SI demonstrated significant associations with measures of muscle strength and ambulation, including ankle dorsiflexion (ADF) strength and 10-meter run/fast walk (Pearson's r = -0.719 and -0.680, respectively). The SI was relatively stable over 3 months (intraclass correlation coefficient [ICC] = 0.863). Latent-class analysis identified 3 DM1 subgroups stratified by baseline SI (SIMild, SIModerate, and SISevere); SIModerate individuals had a significant increase in the SI over 3 months. Multiple linear regression modeling revealed that baseline ADF and SI were predictive of strength at 3 months (adjusted R² = 0.830).CONCLUSIONThe SI is a reliable biomarker that captures associations of RNA mis-splicing with physical strength and mobility and has prognostic utility to predict future function, establishing it as a potential biomarker for assessment of therapeutic target engagement.TRIAL REGISTRATIONClinicalTrials.gov NCT03981575.FUNDINGFDA (7R01FD006071), Myotonic Dystrophy Foundation, Wyck Foundation, Muscular Dystrophy Association, Novartis, Dyne, Avidity, PepGen, Takeda, Sanofi Genzyme, Pfizer, Arthex, and Vertex Pharmaceuticals.

Formulations of macrocyclic lactone anthelmintics such as moxidectin are regularly administered to sheep to combat parasites. A disadvantage of these pharmaceuticals are their side effects on non-target organisms when entering the environment. Little is known about anthelmintic effects on plant reproduction and whether the effects depend on environmental factors. For ecological and methodological reasons, we aimed at testing whether temperature affects the efficacy of a common moxidectin-based formulation on seed germination. We carried out a germination experiment including three typical species of temperate European grasslands ( Centaurea jacea , Galium mollugo , Plantago lanceolata ). We applied three temperature regimes (15/5, 20/10, 30/20°C), and a four-level dilution series (1:100–1:800) of formulated moxidectin (i.e., Cydectin oral drench). These solutions represent seed-anthelmintic contacts in the digestive tract of sheep shortly after deworming. In addition, a control was carried out with purified water only. We regularly counted emerging seedlings and calculated final germination percentage, mean germination time and synchrony of germination. Formulated moxidectin significantly reduced percentage, speed and synchrony of germination. A 1:100 dilution of the formulation reduced germination percentage by a quarter and increased mean germination time by six days compared to the control. Temperature moderated effects of the anthelmintic drug on germination in all response variables and all species, but in different patterns and magnitudes (significant anthelmintic x temperature x species interactions). In all response variables, the two more extreme temperature regimes (15/5, 30/20°C) led to the strongest effects of formulated moxidectin. With respect to germination percentage, G . mollugo was more sensitive to formulated moxidectin at the warmest temperature regime, whereas P . lanceolata showed the highest sensitivity at the coldest regime. This study shows that it is important to consider temperature dependencies of the effects of pharmaceuticals on seed germination when conducting standardised germination experiments.

The first observational run of the Advanced LIGO detectors, from September 12, 2015 to January 19, 2016, saw the first detections of gravitational waves from binary black hole mergers. In this paper we present full results from a search for binary black hole merger signals with total masses up to 100M solar mass and detailed implications from our observations of these systems. Our search, based on general-relativistic models of gravitational wave signals from binary black hole systems, unambiguously identified two signals, GW150914 and GW151226, with a significance of greater than 5 alpha over the observing period. It also identified a third possible signal, LVT151012, with substantially lower significance, which has a 87 probability of being of astrophysical origin. We provide detailed estimates of the parameters of the observed systems. Both GW150914 and GW151226 provide an unprecedented opportunity to study the two-body motion of a compact-object binary in the large velocity, highly nonlinear regime. We do not observe any deviations from general relativity, and place improved empirical bounds on several high-order post-Newtonian coefficients. From our observations we infer stellar-mass binary black hole merger rates lying in the range 9-240 Gpc-3 yr-1. These observations are beginning to inform astrophysical predictions of binary black hole formation rates, and indicate that future observing runs of the Advanced detector network will yield many more gravitational wave detections.