Pediatric Emergency Medicine Physicians’ Use of Point‐of‐care Ultrasound and Barriers to Implementation: A Regional Pilot Study

ObjectivesPoint‐of‐care ultrasound (POCUS) has been identified as a critical skill for pediatric emergency medicine (PEM) physicians. The purpose of this study was to profile the current status of PEM POCUS in pediatric emergency departments (EDs).MethodsAn electronic survey was distributed to PEM fellows and attending physicians at four major pediatric academic health centers. The 24‐item questionnaire covered professional demographics, POCUS experience and proficiency, and barriers to the use of POCUS in pediatric EDs. We used descriptive and inferential statistics to profile respondent’s PEM POCUS experience and proficiency and Rasch analysis to evaluate barriers to implementation.ResultsOur return rate was 92.8% (128/138). Respondents were attending physicians (68%) and fellows (28%). Most completed pediatric residencies prior to PEM fellowship (83.6%). Almost all had some form of ultrasound education (113/128, 88.3%). Approximately half (46.9%) completed a formal ultrasound curriculum. More than half (53.2%) said their ultrasound education was pediatric‐specific. Most participants (67%) rated their POCUS proficiency low (Levels 1–2), while rating proficiency in other professional competencies (procedures 52%, emergency stabilization 70%) high (Levels 4–5). There were statistically significant differences in POCUS proficiency between those with formal versus informal ultrasound education (p < 0.001) and those from pediatric versus emergency medicine residencies (p < 0.05). Participants identified both personal barriers discomfort with POCUS skills (76.7%), insufficient educational time to learn POCUS (65%), and negative impact of POCUS on efficiency (58.5%)—and institutional barriers to the use of ultrasound‐consultants will not use ultrasound findings from the ED (60%); insufficient mentoring (64.7%), and POCUS not being a departmental priority (57%).ConclusionsWhile POCUS utilization continues to grow in PEM, significant barriers to full implementation still persist. One significant barrier relates to the need for dedicated time to learn and practice POCUS to achieve sufficient levels of proficiency for use in practice.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138938/1/aet210049_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138938/2/aet210049-sup-0001-SupInfo.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138938/3/aet210049.pd

Publisher Correction: Copper adparticle enabled selective electrosynthesis of n-propanol.

An amendment to this paper has been published and can be accessed via a link at the top of the paper

Impact of Redshift Information on Cosmological Applications with Next-Generation Radio Surveys

In this paper, we explore how the forthcoming generation of large-scale radio continuum surveys, with the inclusion of some degree of redshift information, can constrain cosmological parameters. By cross-matching these radio surveys with shallow optical to near-infrared surveys, we can essentially separate the source distribution into a low- and a high-redshift sample, thus providing a constraint on the evolution of cosmological parameters such as those related to dark energy. We examine two radio surveys, the Evolutionary Map of the Universe (EMU) and the Westerbork Observations of the Deep APERTIF Northern sky (WODAN). A crucial advantage is their combined potential to provide a deep, full-sky survey. The surveys used for the cross-identifications are SkyMapper and SDSS, for the southern and northern skies, respectively. We concentrate on the galaxy clustering angular power spectrum as our benchmark observable, and find that the possibility of including such low redshift information yields major improvements in the determination of cosmological parameters. With this approach, and provided a good knowledge of the galaxy bias evolution, we are able to put strict constraints on the dark energy parameters, i.e. w_0=-0.9+/-0.041 and w_a=-0.24+/-0.13, with type Ia supernovae and CMB priors (with a one-parameter bias in this case); this corresponds to a Figure of Merit (FoM) > 600, which is twice better than what is obtained by using only the cross-identified sources and greater than four time better than the case without any redshift information at all.Comment: 12 pages, 6 figures, 6 tables; accepted for publication in MNRA

Future changes and uncertainty in decision-relevant measures of East African climate

The need for the development of adaptation strategies for climate change in Africa is becoming critical. For example, infrastructure with a long lifespan now needs to be designed or adapted to account for a future climate that will be different from the past or present. There is a growing necessity for the climate information used in decision making to change from traditional science-driven metrics to decision-driven metrics. This is particularly relevant in East Africa, where limited adaptation and socio-economic capacity make this region acutely vulnerable to climate change. Here, we employ an interdisciplinary consultation process to define and analyse a number of such decision-oriented metrics. These metrics take a holistic approach, addressing the key East African sectors of agriculture, water supply, fisheries, flood management, urban infrastructure and urban health. A multifaceted analysis of multimodel climate projections then provides a repository of user-focused information on climate change and its uncertainties, for all metrics and seasons and two future time horizons. The spatial character and large intermodel uncertainty of changes in temperature and rainfall metrics are described, as well as those of other relevant metrics such as evaporation and solar radiation. Intermodel relationships amongst metrics are also explored, with two clear clusters forming around rainfall and temperature metrics. This latter analysis determines the extent to which model weights could, or could not, be applied across multiple climate metrics. Further work must now focus on maximising the utility of model projections, and developing tailored risk-based communication strategies

A public void catalog from the SDSS DR7 Galaxy Redshift Surveys based on the watershed transform

We produce the most comprehensive public void catalog to date using the Sloan Digital Sky Survey Data Release 7 main sample out to redshift z=0.2 and the luminous red galaxy sample out to z=0.44. Using a modified version of the parameter-free void finder ZOBOV, we fully take into account the presence of the survey boundary and masks. Our strategy for finding voids is thus appropriate for any survey configuration. We produce two distinct catalogs: a complete catalog including voids near any masks, which would be appropriate for void galaxy surveys, and a bias-free catalog of voids away from any masks, which is necessary for analyses that require a fair sampling of void shapes and alignments. Our discovered voids have effective radii from 5 to 135 h^-1 Mpc. We discuss basic catalog statistics such as number counts and redshift distributions and describe some additional data products derived from our catalog, such as radial density profiles and projected density maps. We find that radial profiles of stacked voids show a qualitatively similar behavior across nearly two decades of void radii and throughout the full redshift range.Comment: 13 pages, 10 figures, minor revisions and comparisons added, ApJ accepted, public catalog available at http://www.cosmicvoids.ne

Genomic Profiling of Childhood Tumor Patient-Derived Xenograft Models to Enable Rational Clinical Trial Design.

Accelerating cures for children with cancer remains an immediate challenge as a result of extensive oncogenic heterogeneity between and within histologies, distinct molecular mechanisms evolving between diagnosis and relapsed disease, and limited therapeutic options. To systematically prioritize and rationally test novel agents in preclinical murine models, researchers within the Pediatric Preclinical Testing Consortium are continuously developing patient-derived xenografts (PDXs)-many of which are refractory to current standard-of-care treatments-from high-risk childhood cancers. Here, we genomically characterize 261 PDX models from 37 unique pediatric cancers; demonstrate faithful recapitulation of histologies and subtypes; and refine our understanding of relapsed disease. In addition, we use expression signatures to classify tumors for TP53 and NF1 pathway inactivation. We anticipate that these data will serve as a resource for pediatric oncology drug development and will guide rational clinical trial design for children with cancer

A grammar-based distance metric enables fast and accurate clustering of large sets of 16S sequences

Background: We propose a sequence clustering algorithm and compare the partition quality and execution time of the proposed algorithm with those of a popular existing algorithm. The proposed clustering algorithm uses a grammar-based distance metric to determine partitioning for a set of biological sequences. The algorithm performs clustering in which new sequences are compared with cluster-representative sequences to determine membership. If comparison fails to identify a suitable cluster, a new cluster is created. Results: The performance of the proposed algorithm is validated via comparison to the popular DNA/RNA sequence clustering approach, CD-HIT-EST, and to the recently developed algorithm, UCLUST, using two different sets of 16S rDNA sequences from 2,255 genera. The proposed algorithm maintains a comparable CPU execution time with that of CD-HIT-EST which is much slower than UCLUST, and has successfully generated clusters with higher statistical accuracy than both CD-HIT-EST and UCLUST. The validation results are especially striking for large datasets. Conclusions: We introduce a fast and accurate clustering algorithm that relies on a grammar-based sequence distance. Its statistical clustering quality is validated by clustering large datasets containing 16S rDNA sequences