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Precipitating energetic particles can penetrate into the low-altitude ionosphere and alter the ionization rate. Enhanced ionization in the D-region caused by energetic particle precipitation (EPP) affects cosmic radio signal absorption in the ionosphere. This impact is monitored by a Canadian network of wide-beam passive radio receivers, or riometers, to study precipitation-induced variations in the D-region ionosphere remotely. In this study, we examine the relationship between the background ionospheric profiles and absorption during a precipitation event observed by one of the POES satellites in conjunction with the Gillam riometer station (56N, 95W). We use different chemistry models to model the D-region ionosphere and investigate the effect of changing the chemistry model in an absorption event. We compare modelled absorption with ground-based measurements to discuss possible reasons for any discrepancy.

Tumors are characterized by somatic mutations that drive biological processes ultimately reflected in tumor phenotype. With regard to radiographic phenotypes, generally unconnected through present understanding to the presence of specific mutations, artificial intelligence methods can automatically quantify phenotypic characters by using predefined, engineered algorithms or automatic deep-learning methods, a process also known as radiomics. Here we demonstrate how imaging phenotypes can be connected to somatic mutations through an integrated analysis of independent datasets of 763 lung adenocarcinoma patients with somatic mutation testing and engineered CT image analytics. We developed radiomic signatures capable of distinguishing between tumor genotypes in a discovery cohort (n = 353) and verified them in an independent validation cohort (n = 352). All radiomic signatures significantly outperformed conventional radiographic predictors (tumor volume and maximum diameter). We found a radiomic signature related to radiographic heterogeneity that successfully discriminated between EGFR+ and EGFR− cases (AUC = 0.69). Combining this signature with a clinical model of EGFR status (AUC = 0.70) significantly improved prediction accuracy (AUC = 0.75). The highest performing signature was capable of distinguishing between EGFR+ and KRAS+ tumors (AUC = 0.80) and, when combined with a clinical model (AUC = 0.81), substantially improved its performance (AUC = 0.86). A KRAS+/KRAS− radiomic signature also showed significant albeit lower performance (AUC = 0.63) and did not improve the accuracy of a clinical predictor of KRAS status. Our results argue that somatic mutations drive distinct radiographic phenotypes that can be predicted by radiomics. This work has implications for the use of imaging-based biomarkers in the clinic, as applied noninvasively, repeatedly, and at low cost. Cancer Res; 77(14); 3922–30. ©2017 AACR.

Supplemental Figures and Tables to augment (1) the mathematical modeling (providing details on specific therapeutics); (2) patient characteristics (treatment history, clinical and predicted response), (3) synergistic activities identified by EMMA; and (4) data processing guides

Multiple myeloma remains treatable but incurable. Despite a growing armamentarium of effective agents, choice of therapy, especially in relapse, still relies almost exclusively on clinical acumen. We have developed a system, Ex vivo Mathematical Myeloma Advisor (EMMA), consisting of patient-specific mathematical models parameterized by an ex vivo assay that reverse engineers the intensity and heterogeneity of chemosensitivity of primary cells from multiple myeloma patients, allowing us to predict clinical response to up to 31 drugs within 5 days after bone marrow biopsy. From a cohort of 52 multiple myeloma patients, EMMA correctly classified 96% as responders/nonresponders and correctly classified 79% according to International Myeloma Working Group stratification of level of response. We also observed a significant correlation between predicted and actual tumor burden measurements (Pearson r = 0.5658, P < 0.0001). Preliminary estimates indicate that, among the patients enrolled in this study, 60% were treated with at least one ineffective agent from their therapy combination regimen, whereas 30% would have responded better if treated with another available drug or combination. Two in silico clinical trials with experimental agents ricolinostat and venetoclax, in a cohort of 19 multiple myeloma patient samples, yielded consistent results with recent phase I/II trials, suggesting that EMMA is a feasible platform for estimating clinical efficacy of drugs and inclusion criteria screening. This unique platform, specifically designed to predict therapeutic response in multiple myeloma patients within a clinically actionable time frame, has shown high predictive accuracy in patients treated with combinations of different classes of drugs. The accuracy, reproducibility, short turnaround time, and high-throughput potential of this platform demonstrate EMMA's promise as a decision support system for therapeutic management of multiple myeloma. Cancer Res; 77(12); 3336–51. ©2017 AACR.

Supplements with additional descriptions of datasets, feature selection, and results.

Individual patient EMMA predicitons of actual responses to therapy (companion to Figure 3i).

PDF file - 69K, Table S1. Tumor grade and histology of samples used for global metabolomic profiling. Table S2. Metabolites making up the identified metabolomic profiles that demonstrated statistical significance in malignant glioma

PDF file - 224K, Transcriptional pathways associated with metabolic pathways

PDF file - 609K, Kruskal-Wallis test for transciptional differences in metabolic subtypes

PDF file - 237K, Figure S1. RF analysis was performed to determine the accuracy of metabolomic profiles in predicting glioma grade. Figure S2. Intra-sample concordance of glycolytic intermediates PEP and 3-PG in glioma. Figure S3. Glioma subtype classification based on transcriptional profiles was performed using unsupervised hierarchical clustering from a total of 35 probe sets, as described as Phillips et al. (15). Figure S4. PCA of each metabolic profile by plotting the first two components, indicating no discernable separation between transcriptional subtypes or grade.

We present a unique database of tumor samples from 399 multiple myeloma (MM) patients, whose functional genomic landscape was assessed by integrating ex vivo drug sensitivity to 138 drugs, clinical variables, cytogenetics, mutational profiles and transcriptomes. These analyses revealed a novel MM transcriptomic topology that, when associated with ex vivo drug sensitivity, generates “footprints” having both mechanistic and predictive applications. We validated the transcriptomic footprint for the nuclear export inhibitor selinexor in two clinical trials, BOSTON and MCC17814, and showed such a gene signature can accurately classify clinical response and suggest mechanism of resistance. Finally, we propose a novel evolutionary-based therapeutic strategy involving sequential therapy of monoclonal antibody daratumumab and selinexor, based on anti-correlative transcriptomic footprints, which was validated in two clinical trials (STOMP and XPORT-MM-028). Collectively, this database and computational framework can be leveraged to inform underlying biology, and to identify novel therapeutic strategies to improve treatment of MM.

The use of social media, such as Twitter, has changed the information landscape for citizens participation in crisis response and recovery activities. Given that drought progression is slow and also spatially extensive, an interesting set of questions arise: How the usage of Twitter by a large population may change during the development of a major drought alongside how changing usage promotes drought detection? For this reason, by investigating contemporary procedures, this paper scrutinizes the potential to advance drought depiction. Hence, an analysis of how social media data, in conjunction with meteorological records, was conducted towards improvement in the detection of drought and furthermore, its progression. The research utilized machine learning techniques applied over satellite-derived drought conditions in Colorado. Specifically, 3 different machine learning techniques were examined: the generalized linear model, support vector machines and deep learning, each applied to test the integration of Twitter data with meteorological records as a predictor of drought development. It is maintained that the data integration of resources is viable given that the Twitter-based model outperformed the control run which did not include social media input. Furthermore the Twitter-based model was superior in predicting drought severity.

Lung cancer is the most common fatal malignancy in adults worldwide, and non-small cell lung cancer (NSCLC) accounts for 85% of lung cancer diagnoses. Computed tomography (CT) is routinely used in clinical practice to determine lung cancer treatment and assess prognosis. Here, we developed LungNet, a shallow convolutional neural network for predicting outcomes of NSCLC patients. We trained and evaluated LungNet on four independent cohorts of NSCLC patients from four medical centers: Stanford Hospital (n = 129), H. Lee Moffitt Cancer Center and Research Institute (n = 185), MAASTRO Clinic (n = 311) and Charité – Universitätsmedizin (n=84). We show that outcomes from LungNet are predictive of overall survival in all four independent survival cohorts as measured by concordance indices of 0.62, 0.62, 0.62 and 0.58 on cohorts 1, 2, 3, and 4, respectively. Further, the survival model can be used, via transfer learning, for classifying benign vs malignant nodules on the Lung Image Database Consortium (n = 1010), with improved performance (AUC=0.85) versus training from scratch (AUC=0.82). LungNet can be used as a noninvasive predictor for prognosis in NSCLC patients and can facilitate interpretation of CT images for lung cancer stratification and prognostication.

Background: Multiparametric magnetic resonance imaging (mpMRI) has emerged as a non-invasive modality to diagnose and monitor prostate cancer. Quantitative metrics on the regions of abnormality have shown to be useful descriptors to discriminate clinically significant cancers. In this study, we evaluate the reproducibility of quantitative imaging features using repeated mpMRI on the same patients. Methods: We retrospectively obtained the deidentified records of patients, who underwent two mpMRI scans within 2 weeks of the first baseline scan. The patient records were obtained as deidentified data (including imaging), obtained through the TCIA (The Cancer Imaging Archive) repository and analyzed in our institution with an institutional review board-approved Health Insurance Portability and Accountability Act-compliant retrospective study protocol. Indicated biopsied regions were used as a marker for our study radiologists to delineate the regions of interest. We extracted 307 quantitative features in each mpMRI modality [T2-weighted MR sequence image (T2w) and apparent diffusion coefficient (ADC) with b values of 0 and 1,400 mm/s2] across the two sequential scans. Concordance correlation coefficients (CCCs) were computed on the features extracted from sequential scans. Redundant features were removed by computing the coefficient of determination (R 2) among them and replaced with a feature that had the highest dynamic range within intercorrelated groups. Results: We have assessed the reproducibility of quantitative imaging features among sequential scans and found that habitat region characterization improves repeatability in ADC maps. There were 19 T2w features and two ADC features in radiologist drawn regions (native raw image), compared to 18 T2w and 15 ADC features in habitat regions (sphere), which were reproducible (CCC ≥0.65) and non-redundant (R 2 ≥ 0.99). We also found that z-transformation of the images prior to feature extraction reduced the number of reproducible features with no detrimental effect. Conclusion: We have shown that there are quantitative imaging features that are reproducible across sequential prostate mpMRI acquisition at a preset level of filters. We also found that a habitat approach improves feature repeatability in ADC. A validated set of reproducible image features in mpMRI will allow us to develop clinically useful disease risk stratification, enabling the possibility of using imaging as a surrogate to invasive biopsies.

18th EISCAT symposiumSession E4: Aurora and airglowMay 30 (Tue), National Institute for Japanese Language

Characterization of lung nodules as benign or malignant is one of the most important tasks in lung cancer diagnosis, staging and treatment planning. While the variation in the appearance of the nodules remains large, there is a need for a fast and robust computer aided system. In this work, we propose an end-to-end trainable multi-view deep Convolutional Neural Network (CNN) for nodule characterization. First, we use median intensity projection to obtain a 2D patch corresponding to each dimension. The three images are then concatenated to form a tensor, where the images serve as different channels of the input image. In order to increase the number of training samples, we perform data augmentation by scaling, rotating and adding noise to the input image. The trained network is used to extract features from the input image followed by a Gaussian Process (GP) regression to obtain the malignancy score. We also empirically establish the significance of different high level nodule attributes such as calcification, sphericity and others for malignancy determination. These attributes are found to be complementary to the deep multi-view CNN features and a significant improvement over other methods is obtained., Comment: Accepted for publication in IEEE International Symposium on Biomedical Imaging (ISBI) 2017

Multiple myeloma (MM) remains treatable but incurable. Despite a growing armamentarium of effective agents, choice of therapy, especially in relapse, still relies almost exclusively on clinical acumen. We have developed a system, EMMA (Ex vivo Mathematical Myeloma Advisor), consisting of patient-specific mathematical models parameterized by an ex vivo assay that reverse engineers the intensity and heterogeneity of chemosensitivity of primary cells from MM patients, allowing us to predict clinical response to up to 31 drugs within 5 days post-bone marrow biopsy. From a cohort of 52 MM patients, EMMA correctly classified 96% as responders/non-responders and correctly classified 79% according to IMWG stratification of level of response. We also observed a significant correlation between predicted and actual tumor burden measurements (Pearson r=0.5658, P

Malignant tumors exhibit altered metabolism and consume higher levels of glucose compared to surrounding normal tissue, resulting in acidic extracellular microenvironment. Acidity in the microenvironment is a critical stress factor and selection force for the evolution of aggressive tumor types. There are several acid sensing cell surface receptors and ion channels (ASICs) that can sense acidity in the microenvironment; among them proton sensing G protein-coupled receptors (GPCRs) such as OGR1 (GPR68), TDAG8 (GPR65), GPR4 and GPR132 form a major class of acid receptors. Our previous studies demonstrated that acid adaptation is associated with survival mechanisms like chronic activation of autophagy and redistribution of the lysosomal proteins to the plasma membrane. When grown under acidic pH, breast cancer cells accumulate lipids as revealed by staining with Nile Red and perilipin 2, a protein that coats adiposomes or lipid droplets. These are dynamic organelles that store neutral lipids surrounded by a shell of proteins and a phospholipid monolayer. The lipids stored in adiposomes are produced de novo, as acid-induced lipogenic phenotype is maintained, even if cells are grown with de-lipidated serum. Inhibition of fatty acid synthesis was selectively toxic under acidic conditions and attenuated adiposome accumulation. Among the acid sensing receptors, TDAG8 and OGR1 are highly expressed in a panel of breast cancer cell lines compared to non-malignant breast epithelial cells. Highly invasive and acid tolerant MDA-MB-231 cells express significantly higher levels of TDAG8 while MCF7 and T47D cells have high levels of OGR1. We investigated the role of these receptors in transducing the acid signal that results in the accumulation of lipid droplets. CRISPR/Cas9 mediated depletion of the major acid sensors in breast cancer cell lines MCF7 and T47D showed that depletion of OGR1, not TDAG8, specifically inhibited acid induced adiposome accumulation. Additionally, inducing the cells with ogerin, an allosteric activator of OGR1 resulted in adiposomogenesis. Further, OGR1 knock out cells showed inhibition in cell growth under acidic growth conditions compared to OGR1 expressing cells. OGR1 knockout cells were defective in acid induced autophagy. OGR1 is coupled with Gq/11 and, upon ligand (H+) binding, triggers activation of phospholipase C stimulating the formation of the second messenger IP3. Adiposome formation was inhibited in presence of PLC inhibitors, Edelfosine or U73122. These results indicate that OGR1 is the major acid sensing GPCR in these cells that mediate adiposomogenesis. Accumulation of adiposomes is a highly regulated process related to storing autophagic products, and appears to be important in cell survival in acid stress. Taken together, increased dependence on lipid metabolism by cancer cells under acidic conditions reveals novel therapeutic vulnerabilities. Citation Format: Smitha Pillai, Michael Langsen, Jonathan Nguyen, Jonathan Wojtkowiak, Marilyn Bui, Robert Gatenby, Robert Gillies. Acid sensing G protein-coupled receptor OGR1 is required for acid induced adiposomogenesis in breast cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1846.

This article argues that because the whole of Jesus’ ministry should be seen as a totality, what he taught in Galilee is as valid as what happened in Gethsemane. His teaching on healing, kingdom proclamation, concern for others is thus on a level with his teaching on and practice of prayer. He enjoined his disciples to follow his way in all respects both then and still does so now. A direct link between the evangelistic and the contemplative imperatives of Jesus is the substantive thesis of this paper. A narrative reading of the Gethsemane story is the biblical setting in which this thesis is proposed.

Limited depth of penetration significantly limits photodynamic therapy of nodular basal cell carcinoma (BCC) using topical delta (5)-aminolevulinic acid (ALA). To demonstrate safety and efficacy of orally administered ALA in inducing endogenous protoporphyrin IX (PpIX) production in BCC, 13 patients with BCC ingested ALA in a dose-escalation protocol. All dose ranges (10, 20 or 40 mg/kg single doses) resulted in formation of PpIX in human skin and BCC, measurable by in vivo fluorescence spectrophotometry. The PpIX fluorescence peaked in tumors before normal adjacent skin from 1 to 3 h after ALA ingestion. Gross fluorescence imaging of ex vivo specimens revealed greater PpIX fluorescence in tumor than normal skin only at the 40 mg/kg dose. Fluorescence microscopy confirmed this finding by showing distinct, full-thickness PpIX fluorescence in all subtypes of BCC only after ALA given at 40 mg/kg. Side effects were dose dependent and self limited. Photosensitivity lasting less than 24 h and nausea coinciding with peak skin PpIX fluorescence occurred at 20 and 40 mg/kg doses. After 40 mg/kg ALA, serum hepatic enzyme levels rose to a maximum within 24 h, then resolved over 1-3 weeks. Transient bilirubinuria occurred in two patients.

Sheets of polysulphone film have been extensively used as detectors to monitor solar UVB radiation. The advantages of polysulphone detectors are that they are small in size, they have good thermal stability and they are sensitive to UVB radiation. The principal disadvantage of polysulphone detectors is that their spectral sensitivity includes part of the short-wavelength UVA. In this study, we investigate the spectral sensitivity of the polysulphone detector with a series of monochromatic (±2 nm) excitations. We then compare the polysulphone-effective solar radiation with the erythemally effective solar radiation by comparing solar UVB data obtained with polysulphone films with those obtained with a spectroradiometer. From polysulphone data on the seasonal variation of solar UVB radiation, we estimate the corresponding fluctuations of the absorption of the ozone layer. We show that the spectral sensitivity of the polysulphone film is closer to the erythema action spectrum than that indicated by earlier data and that polysulphone detectors can be used to predict the erythema risk of solar UVB. Measurements on solar UVB with polysulphone films and with a spectroradiometer were found to be strongly correlated (R2 > 0.95). Finally, polysulphone-based measurements provide a good measure of the fluctuations of the stratospheric ozone layer.

These prayers are taken, with a few changes, from my book Sounds before the Cross (Handsel Press, 2007). The first seven prayers are for use at any point in Lent, the final two are principally for use in Holy Week and are especially prepared for devotional use on Good Friday. The structure of the prayers is best described as skeletal. Intrusions of grammar and the conventions of syntax and form are kept to a minimum. The purpose behind setting these prayers in a varied and irregular style is to create as much interpretative space as possible for the person who might wish to pray through them. They can be read, and therefore prayed, with a wide range of varying meanings and emphases by deploying variations in punctuation, voice tone, speed and meditative silence. In these prayers I am not so much offering comprehensive theology as open theology and I invite those committed to prayer and leading prayers to experiment with their scope to the fullest extent. This will require some perseverance for on first reading the prayers may seem confusing. However my hopes will have borne fruit if the prayers that follow come to be understood, are then phrased in a way that is appropriate to the local context and, most importantly, lead people closer to God. The World Cries to the Father

Objective evaluation of comedone lesions, especially in vivo, remains a challenge. We have used the rhino mouse model in combination with topical application of all-trans retinoic acid as a comedolytic agent, to investigate the potential of fluorescence spectroscopy as a noninvasive technique in the assessment of noninflammatory acne. The results indicate that there is a strong correlation between the fluorescence excitation spectral features assessed in vivo, and the histologic changes identified, particularly the size of the utriculi as well as the dermal and epidermal thickness. We conclude that fluorescence excitation spectroscopy represents a promising novel and useful tool in the quantitative evaluation of the pseudocomedones and could also be used for the rapid and noninvasive assessment of comedolysis induced by the application of pharmacologic agents such as retinoids.

Background. Microfine zinc oxide and microfine titanium dioxide are particulate sunscreen ingredients that absorb broad-spectrum ultraviolet (UV) irradiation. Objective. We compare microfine zinc oxide and microfine titanium dioxide for their abilities to attenuate UVA radiation and their relative whiteness in cosmetic formulations. Methods. UVA attenuation was measured by diffuse reflectance spectroscopy on normal human skin in vivo. Whiteness was determined by reflectance density of dried coatings on a black background of the two particulates at varying concentrations. Results. Microfine zinc oxide demonstrates superior protection compared to microfine titanium dioxide in the UV spectrum between 340 and 380 nm. Microfine zinc oxide is less white than titanium dioxide at all concentrations. Conclusion. Microfine zinc oxide is superior to microfine titanium dioxide as a sunscreen ingredient. It is more protective against long-wave UVA and is less white at a given concentration.

Background: Doxepin applied topically by itself or in combination with triamcinolone acetonide is a safe and effective treatment for atopic dermatitis. Objective: We evaluated the pharmacokinetic profile of doxepin and desmethyldoxepin after topical application of doxepin hydrochloride 5% cream alone or in combination with 0.025% triamcinolone acetonide (doxepin/TAC). Methods: Twenty-four subjects with atopic dermatitis received either doxepin or doxepin/TAC cream 4 times daily for 7 days in a randomized, double-blind, controlled trial. Serum samples were obtained and pharmacokinetic parameters estimated from the dose-normalized serum concentrations of doxepin and desmethyldoxepin. Efficacy and adverse experiences were determined by physician and subject evaluations. Results: Pharmacokinetic parameters (K e , t 1/2 and AUC) calculated in 9 subjects (doxepin/TAC = 4 subjects, doxepin=5 subjects) with detectable serum concentrations were similar for both groups. Pruritus relief and lessening of pruritus severity were significantly greater with doxepin/TAC than doxepin alone. Conclusion: Topically applied doxepin is safe and effective therapy for pruritus. (J Am Acad Dermatol 1999;41:209-14.)

Aging and photoaging cause distinct changes in skin cells and extracellular matrix. Changes in hairless mouse skin as a function of age and chronic UVB exposure were investigated by fluorescence excitation spectroscopy. Fluorescence excitation spectra were measured in vivo, on heat-separated epidermis and dermis, and on extracts of mouse skin to characterize the absorption spectra of the emitting chromophores. Fluorescence excitation spectra obtained in vivo on 6 wk old mouse skin had maxima at 295, 340, and 360 nm; the 295 nm band was the dominant band. Using heat separated tissue, the 295 nm band predominantly originated in the epidermis and the bands at 340 and 360 nm originated in the dermis. The 295 nm band was assigned to tryptophan fluorescence, the 340 nm band to pepsin digestable collagen cross-links fluorescence and the 360 nm band to collagenase digestable collagen cross-links fluorescence. Fluorescence excitation maxima remained unchanged in chronologically aged mice (34–38 wk old), whereas the 295 nm band decreased in intensity with age and the 340 nm band increased in intensity with age. In contrast, fluorescence excitation spectra of chronically UVB exposed mice showed a large increase in the 295 nm band compared with age-matched controls and the bands at 340 and 350 nm were no longer distinct. Two new bands appeared in the chronically exposed mice at 270 nm and at 305 nm. These reproducible changes in skin autofluorescence suggest that aging causes predictable alterations in both epidermal and dermal fluorescence, whereas chronic UV exposure induces the appearance of new fluorphores.