Distributed visualization of gridded geophysical data: the Carbon Data Explorer, version 0.2.3

Due to the proliferation of geophysical models, particularly climate models, the increasing resolution of their spatiotemporal estimates of Earth system processes, and the desire to easily share results with collaborators, there is a genuine need for tools to manage, aggregate, visualize, and share data sets. We present a new, web-based software tool – the Carbon Data Explorer – that provides these capabilities for gridded geophysical data sets. While originally developed for visualizing carbon flux, this tool can accommodate any time-varying, spatially explicit scientific data set, particularly NASA Earth system science level III products. In addition, the tool\u27s open-source licensing and web presence facilitate distributed scientific visualization, comparison with other data sets and uncertainty estimates, and data publishing and distribution

Malignant ovarian germ cell tumors in pediatric patients: The AIEOP (Associazione Italiana Ematologia Oncologia Pediatrica) study

Objective: Malignant ovarian germ cell tumors (MOGCT) carry an excellent prognosis, and the treatment aims to achieve results with the least possible treatment-related morbidity. The aim of this study was to assess the outcomes of pediatric patients with MOGCT. Methods: Patients were treated according to their stage: surgery and surveillance for stage I; a modified bleomycin\u2013etoposide\u2013cisplatin (BEP) regimen for stages II (three cycles), III, and IV (three cycles) with surgery on residual disease. Results: Seventy-seven patients were enrolled (median age 11.8 years), 26 with dysgerminoma (Dysg), 13 with immature teratoma and elevated serum alpha-fetoprotein levels (IT+AFP), and 38 with nondysgeminoma (Non-Dysg) staged as follows: 27 stage I, 13 stage II, 32 stage III, 5 stage IV. Among evaluable patients in stage I (5-year event-free survival [EFS] 72.1% [95% CI: 56.4\u201392.1%]; 5-year overall survival [OS] 100%), seven relapsed (three patients with Dysg and four patients with Non-Dysg) and were rescuedwith chemotherapy (plus surgery in three patients). Among the evaluable patients with stages II\u2013IV, 48 (98%) achieved complete remission after chemotherapy \ub1 surgery, one (IT + AFP, stage IV) had progressive disease. In the whole series (median follow-up 80 months), the 5-year OS and EFS were 98.5% (95% CI: 95.6\u2013100%) and 84.5% (95% CI: 76.5\u2013 93.5%). Conclusions:We confirm the excellent outcome for MOGCT. Robust data are lacking on surgical staging, surveillance for Non-Dysg with stage I, the management of IT + AFP, and the most appropriate BEP regimen. As pediatric oncologists,we support the role of surveillance after proper surgical staging providing cases are managed by experts at specialized pediatric centers

Retrograde gastroesophageal intussusception: Initial presenting feature of achalasia in a teenager

A 16-year-old Caucasian male presented with acute vomiting and dysphagia. Imaging studies revealed retrograde gastroesophageal intussusception (RGEI), which reduced prior to diagnostic laparoscopy. No clear etiology for RGEI was identified at that time, so further surgical intervention was deferred. He returned several months later with persistent dysphagia. Imaging, endoscopy, and endoluminal function imaging probe then diagnosed achalasia. He underwent a second laparoscopy for Heller myotomy and Dor fundoplication. This is the first report of RGEI preceding a diagnosis of achalasia

Rapid response tools and datasets for post-fire modeling: linking Earth Observations and process-based hydrological models to support post-fire remediation

Preparation is key to utilizing Earth Observations and process-based models to support post-wildfire mitigation. Post-fire flooding and erosion can pose a serious threat to life, property and municipal water supplies. Increased runoff and sediment delivery due to the loss of surface cover and fire-induced changes in soil properties are of great concern. Remediation plans and treatments must be developed and implemented before the first major storms in order to be effective. One of the primary sources of information for making remediation decisions is a soil burn severity map derived from Earth Observation data (typically Landsat) that reflects fire induced changes in vegetation and soil properties. Slope, soils, land cover and climate are also important parameters that need to be considered. Spatially-explicit process-based models can account for these parameters, but they are currently under-utilized relative to simpler, lumped models because they are difficult to set up and require spatially-explicit inputs (digital elevation models, soils, and land cover). Our goal is to make process-based models more accessible by preparing spatial inputs before a fire, so that datasets can be rapidly combined with soil burn severity maps and formatted for model use. We are building an online database (http://geodjango.mtri.org/geowepp /) for the continental United States that will allow users to upload soil burn severity maps. The soil burn severity map is combined with land cover and soil datasets to generate the spatial model inputs needed for hydrological modeling of burn scars. Datasets will be created to support hydrological models, post-fire debris flow models and a dry ravel model. Our overall vision for this project is that advanced GIS surface erosion and mass failure prediction tools will be readily available for post-fire analysis using spatial information from a single online site

Successful treatment of a solitary skull metastasis in a child with Wilms' Tumor

This report presents the successful treatment of a child with a solitary metastatic lesion to the calvarium following treatment for Stage III anaplastic Wilms’ Tumor

Distributed visualization of gridded geophysical data: the Carbon Data Explorer, version 0.2.3

Due to the proliferation of geophysical models, particularly climate models, the increasing resolution of their spatiotemporal estimates of Earth system processes, and the desire to easily share results with collaborators, there is a genuine need for tools to manage, aggregate, visualize, and share data sets. We present a new, web-based software tool – the Carbon Data Explorer – that provides these capabilities for gridded geophysical data sets. While originally developed for visualizing carbon flux, this tool can accommodate any time-varying, spatially explicit scientific data set, particularly NASA Earth system science level III products. In addition, the tool's open-source licensing and web presence facilitate distributed scientific visualization, comparison with other data sets and uncertainty estimates, and data publishing and distribution

Fetal MRI in the Identification of a Fetal Ventral Wall Defect Spectrum

Objective  To ascertain if useful criteria for prenatal diagnosis of fetal ventral body wall defects (VBWDs) exists by reviewing published literature on diagnosis of VBWD as compared with our own diagnostic experience. Study Design  A comprehensive literature review of diagnostic criteria of fetal VBWD including pentalogy of Cantrell (POC), omphalocele, exstrophy, imperforate anus, spina bifida (OEIS), cloacal exstrophy, limb-body wall complex (LBWC), and body stalk anomaly was performed followed by a retrospective review of all fetal magnetic resonance imaging (MRI) examinations from our medical center over a 2-year period. Results  Classically, OEIS is omphalocele, bladder exstrophy, imperforate anus, and spina bifida. POC is defects of the supraumbilical abdomen, sternum, diaphragm, pericardium, and heart. LBWC is two of the following: exencephaly or enencephaly with facial clefts, thoracoschisis or abdominoschisis, and limb defects. Twenty-four cases of VBWD on MRI over a 24-month period were identified with seven cases involving defects of additional organ systems. Six of these seven cases demonstrated findings from two or more of the traditional diagnoses POC, OEIS, and LBWC making diagnosis and counseling difficult. Conclusion  There is a lack of consensus on useful diagnostic criteria within the published literature which is reflected in our own diagnostic experience and poses a challenge for accurate prenatal counseling

Assessing Boreal Peat Fire Severity and Vulnerability of Peatlands to Early Season Wildland Fire

Globally peatlands store large amounts of carbon belowground with 80% distributed in boreal regions of the northern hemisphere. Climate warming and drying of the boreal region has been documented as affecting fire regimes, with increased fire frequency, severity and extent. While much research is dedicated to assessing changes in boreal uplands, few research efforts are focused on the vulnerability of boreal peatlands to wildfire. In this case study, an integration of field data collection, land cover mapping of peatland types and Landsat-based fire severity mapping was conducted for four early season (May to mid-June) wildfires where peatlands are abundant in northeastern Alberta Canada. The goal was to better understand if peatlands burn more or less preferentially than uplands in fires and how severely the organic soil layers (peat) of different peatland ecotypes burn. The focus was on early season wildfires because they dominated the research area in the decade of study. To do this, a novel Landsat-5 metric was developed to retrieve fire severity of the organic surface layer. Spatial comparisons and statistical analysis showed that proportionally bogs are more likely to burn in early season Alberta wildfires than other ecosystem types, even fire-prone upland conifer. Although for a small sample, we found that when fire weather conditions for the duff layers are severe, the fens of this study appear to become more susceptible to burning. In addition, overall bogs experienced greater severity of burn to the peat layers than fens. Due to the small sample size of peat loss from fire in uplands and limited geographic area of this case study, we were unable to assess if bogs are burning more severely than uplands. Further analysis and Landsat algorithm development for organic soil fire severity in peatlands and uplands are needed to more fully understand trends in belowground consumption for wildfires of all seasons and boreal ecotypes

Mapping modeled exposure of wildland fire smoke for human health studies in California

Wildland fire smoke exposure affects a broad proportion of the U.S. population and is increasing due to climate change, settlement patterns and fire seclusion. Significant public health questions surrounding its effects remain, including the impact on cardiovascular disease and maternal health. Using atmospheric chemical transport modeling, we examined general air quality with and without wildland fire smoke PM2.5. The 24-h average concentration of PM2.5 from all sources in 12-km gridded output from all sources in California (2007–2013) was 4.91 μg/m3. The average concentration of fire-PM2.5 in California by year was 1.22 μg/m3 (~25% of total PM2.5). The fire-PM2.5 daily mean was estimated at 4.40 μg/m3 in a high fire year (2008). Based on the model-derived fire-PM2.5 data, 97.4% of California’s population lived in a county that experienced at least one episode of high smoke exposure (“smokewave”) from 2007–2013. Photochemical model predictions of wildfire impacts on daily average PM2.5 carbon (organic and elemental) compared to rural monitors in California compared well for most years but tended to over-estimate wildfire impacts for 2008 (2.0 µg/m3 bias) and 2013 (1.6 µg/m3 bias) while underestimating for 2009 (−2.1 µg/m3 bias). The modeling system isolated wildfire and PM2.5 from other sources at monitored and unmonitored locations, which is important for understanding population exposure in health studies. Further work is needed to refine model predictions of wildland fire impacts on air quality in order to increase confidence in the model for future assessments. Atmospheric modeling can be a useful tool to assess broad geographic scale exposure for epidemiologic studies and to examine scenario-based health impacts