Atmospheric electricity/meteorology analysis

This activity focuses on Lightning Imaging Sensor (LIS)/Lightning Mapper Sensor (LMS) algorithm development and applied research. Specifically we are exploring the relationships between (1) global and regional lightning activity and rainfall, and (2) storm electrical development, physics, and the role of the environment. U.S. composite radar-rainfall maps and ground strike lightning maps are used to understand lightning-rainfall relationships at the regional scale. These observations are then compared to SSM/I brightness temperatures to simulate LIS/TRMM multi-sensor algorithm data sets. These data sets are supplied to the WETNET project archive. WSR88-D (NEXRAD) data are also used as it becomes available. The results of this study allow us to examine the information content from lightning imaging sensors in low-earth and geostationary orbits. Analysis of tropical and U.S. data sets continues. A neural network/sensor fusion algorithm is being refined for objectively associating lightning and rainfall with their parent storm systems. Total lightning data from interferometers are being used in conjunction with data from the national lightning network. A 6-year lightning/rainfall climatology has been assembled for LIS sampling studies

EarlyR: A Robust Gene Expression Signature for Predicting Outcomes of Estrogen Receptor–Positive Breast Cancer

Introduction Early stage estrogen receptor (ER)-positive breast cancer may be treated with chemotherapy in addition to hormone therapy. Currently available molecular signatures assess the risk of recurrence and the benefit of chemotherapy; however, these tests may have large intermediate risk groups, limiting their usefulness. Methods The EarlyR prognostic score was developed using integrative analysis of microarray data sets and formalin-fixed, paraffin-embedded–based quantitative real-time PCR assay and validated in Affymetrix data sets and METABRIC cohort using Cox proportional hazards models and Kaplan-Meier survival analysis. Concordance index was used to measure the probability of prognostic score agreement with outcome. Results The EarlyR score and categorical risk strata (EarlyR-Low, EarlyR-Int, EarlyR-High) derived from expression of ESPL1, MKI67, SPAG5, PLK1 and PGR was prognostic of 8-year distant recurrence-free interval in Affymetrix (categorical P = 3.5 × 10−14; continuous P = 8.8 × 10−15) and METABRIC (categorical P < 2.2 × 10−16; continuous P < 10−16) data sets of ER+ breast cancer. Similar results were observed for the breast cancer–free interval end point. At most 13% of patients were intermediate risk and at least 66% patients were low risk in both ER+ cohorts. The EarlyR score was significantly prognostic (distant recurrence-free interval; P < .001) in both lymph node–negative and lymph node–positive patients and was independent from clinical factors. EarlyR and surrogates of current molecular signatures were comparable in prognostic significance by concordance index. Conclusion The 5-gene EarlyR score is a robust prognostic assay that identified significantly fewer patients as intermediate risk and more as low risk than currently available assays. Further validation of the assay in clinical trial–derived cohorts is ongoing

Cyclosporine shows benefit as compared to methotrexate for treatment of pediatric atopic dermatitis refractory to topical medications when rapidity of clinical response is of key importance to the patient

A clinical decision report appraising El-Khalawany MA, Hassan H, Shaaban D, Ghonaim N, Eassa B. Methotrexate versus cyclosporine in the treatment of severe atopic dermatitis in children: a multicenter experience from Egypt. European Journal of Pediatrics. 2012;172(3):351-356. https://doi.org10.1007/s00431-012-1893-3 for a pediatric patient with severe atopic dermatitis

Investigating the Use of Deep Convective Clouds (DCCT) to Monitor On-orbit Performance of the Geostationary Lightning Mapper (GLM) using Lightning Imaging Sensor (LIS) Measurements

There is a need to monitor the on-orbit performance of the Geostationary Lightning Mapper (GLM) on the Geostationary Operational Environmental Satellite R (GOES-R) for changes in instrument calibration that will affect GLM's lightning detection efficiency. GLM has no onboard calibration so GLM background radiance observations (available every 2.5 min) of Deep Convective Clouds (DCCs) are investigated as invariant targets to monitor GLM performance. Observations from the Lightning Imaging Sensor (LIS) and the Visible and Infrared Scanner (VIRS) onboard the Tropical Rainfall Measuring Mission (TRMM) satellite are used as proxy datasets for GLM and ABI 11 m measurements

Near Real-Time Lightning Data for Operations and Science Applications from the Lightning Imaging Sensor (LIS) on the International Space Station (ISS)

No abstract availabl

The ENSO Effect on the Temporal and Spatial Distribution of Global Lightning Activity

The recently reprocessed (1997-2006) OTD/LIS database is used to investigate the global lightning climatology in response to the ENSO cycle. A linear correlation map between lightning anomalies and ENSO (NINO3.4) identifies areas that generally follow patterns similar to precipitation anomalies. We also observed areas where significant lightning/ENSO correlations are found and are not accompanied of significant precipitation/ENSO correlations. An extreme case of the strong decoupling between lightning and precipitation is observed over the Indonesian peninsula (Sumatra) where positive lightning/NINO3.4 correlations are collocated with negative precipitation/NINO3.4 correlations. Evidence of linear relationships between the spatial extent of thunderstorm distribution and the respective NINO3.4 magnitude are presented for different regions on the Earth. Strong coupling is found over areas remote to the main ENSO axis of influence and both during warm and cold ENSO phases. Most of the resulted relationships agree with the tendencies of precipitation related to ENSO empirical maps or documented teleconnection patterns. Over the Australian continent, opposite behavior in terms of thunderstorm activity is noted for warm ENSO phases with NINO3.4 magnitudes with NINO3.4>+l.08 and 0<NqNO3.4<I.08. Finally, we investigate the spatial distribution of areas that consistently portrayed enhanced lightning activity during the main warm/cold (El Nino/La Nina) ENSO episodes of the past decade. The observed patterns show no spatial overlapping and identify areas that in their majority are in agreement with empirical precipitation/ENSO maps. The areas that appear during the warm ENSO phase are found over regions that have been identified as anomalous Hadley circulation ENSO-related patterns. The areas that appear during the cold ENSO phase are found predominantly around the west hemisphere equatorial belt and are in their majority identified by anomalous Walker circulation

Fluidized Bed Polymer Particle ALD Process for Producing HDPE/Alumina Nanocomposites

Micron-sized High Density Polyethylene (HDPE) particles were coated with ultrathin alumina (Al2O3) films in a Fluidized Bed Reactor (FBR) by Atomic Layer Deposition (ALD) at 77 ºC. Al2O3 films on the HDPE particles were confirmed by different methods. These particles were extruded conventionally with the ceramic shells mixing intimately in the polymer matrix. The successful dispersion of the Al2O3 shells in the polymer matrix following extrusion was confirmed using cross sectional Transmission Electron Microscopy (TEM)

Characterizing the GOES-R (GOES-16) Geostationary Lightning Mapper (GLM) On-Orbit Performance

Two overlapping efforts help to characterize the GLM performance, the Post Launch Test (PLT) phase to validate the predicted pre-launch instrument performance and the Post Launch Product Test (PLPT) phase to validate the lightning detection product used in forecast and warning decision-making. This paper documents the calibration and validation plans and activities for the first 6 months of GLM on-orbit testing and validation commencing with first light on 4 January 2017. The PLT phase addresses image quality, on-orbit calibration, RTEP threshold tuning, image navigation, noise filtering, and solar intrusion assessment, resulting in a GLM calibration parameter file. The PLPT includes four main activities, the Reference Data Comparisons (RDC), Algorithm Testing (AT), Instrument Navigation and Registration Testing (INRT), and Long Term Baseline Testing (LTBT). Field campaigns are also designed to contribute valuable insights into the GLM performance capabilities. The PLPT tests each contribute to the beta, provisional, and fully validated GLM data

Independent Validation of EarlyR Gene Signature in BIG 1-98: A Randomized, Double-Blind, Phase III Trial Comparing Letrozole and Tamoxifen as Adjuvant Endocrine Therapy for Postmenopausal Women with Hormone Receptor-Positive, Early Breast Cancer

Background EarlyR gene signature in estrogen receptor–positive (ER+) breast cancer is computed from the expression values of ESPL1, SPAG5, MKI67, PLK1, and PGR. EarlyR has been validated in multiple cohorts profiled using microarrays. This study sought to verify the prognostic features of EarlyR in a case-cohort sample from BIG 1–98, a randomized clinical trial of ER+ postmenopausal breast cancer patients treated with adjuvant endocrine therapy (letrozole or tamoxifen). Methods Expression of EarlyR gene signature was estimated by Illumina cDNA-mediated Annealing, Selection, and Ligation assay of RNA from formalin-fixed, paraffin-embedded primary breast cancer tissues in a case-cohort subset of ER+ women (N = 1174; 216 cases of recurrence within 8 years) from BIG 1–98. EarlyR score and prespecified risk strata (≤25 = low, 26–75 = intermediate, >75 = high) were “blindly” computed. Analysis endpoints included distant recurrence–free interval and breast cancer–free interval at 8 years after randomization. Hazard ratios (HRs) and test statistics were estimated with weighted analysis methods. Results The distribution of the EarlyR risk groups was 67% low, 19% intermediate, and 14% high risk in this ER+ cohort. EarlyR was prognostic for distant recurrence–free interval; EarlyR high-risk patients had statistically increased risk of distant recurrence within 8 years (HR = 1.73, 95% confidence interval = 1.14 to 2.64) compared with EarlyR low-risk patients. EarlyR was also prognostic of breast cancer–free interval (HR = 1.74, 95% confidence interval = 1.21 to 2.62). Conclusions This study confirmed the prognostic significance of EarlyR using RNA from formalin-fixed, paraffin-embedded tissues from a case-cohort sample of BIG 1–98. EarlyR identifies a set of high-risk patients with relatively poor prognosis who may be considered for additional treatment. Further studies will focus on analyzing the predictive value of EarlyR signature

Satellite Proving Ground for the GOES-R Geostationary Lightning Mapper (GLM)

The key mission of the Satellite Proving Ground is to demonstrate new satellite observing data, products and capabilities in the operational environment to be ready on Day 1 to use the GOES-R suite of measurements. Algorithms, tools, and techniques must be tested, validated, and assessed by end users for their utility before they are finalized and incorporated into forecast operations. The GOES-R Proving Ground for the Geostationary Lightning Mapper (GLM) focuses on evaluating how the infusion of the new technology, algorithms, decision aids, or tailored products integrate with other available tools (weather radar and ground strike networks; nowcasting systems, mesoscale analysis, and numerical weather prediction models) in the hands of the forecaster responsible for issuing forecasts and warning products. Additionally, the testing concept fosters operation and development staff interactions which will improve training materials and support documentation development. Real-time proxy total lightning data from regional VHF lightning mapping arrays (LMA) in Northern Alabama, Central Oklahoma, Cape Canaveral Florida, and the Washington, DC Greater Metropolitan Area are the cornerstone for the GLM Proving Ground. The proxy data will simulate the 8 km Event, Group and Flash data that will be generated by GLM. Tailored products such as total flash density at 1-2 minute intervals will be provided for display in AWIPS-2 to select NWS forecast offices and national centers such as the Storm Prediction Center. Additional temporal / spatial combinations are being investigated in coordination with operational needs and case-study proxy data and prototype visualizations may also be generated from the NASA heritage Lightning Imaging Sensor and Optical Transient Detector data. End users will provide feedback on the utility of products in their operational environment, identify use cases and spatial/temporal scales of interest, and provide feedback to the developers for adjusted or new products