92 research outputs found

    Constitutive Parameter Measurement Using Double Ridge Waveguide

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    Electromagnetic materials characterization is important in the design of systems that interact with electromagnetic waves. Determining the constitutive parameters of a material is a vast area of research and practice. For this paper, discussion will focus on a destructive method using waveguides in the frequency range of 6-18 GHz. Traditional methods to perform similar measurements include using coaxial cable, stripline, focus beam and rectangular waveguides. This work will use Double Ridged Waveguide (DRWG) to compare to these other methods and will discuss the attributes and drawbacks of this new approach. The most similar method utilizes rectangular waveguide, so the primary focus will be on comparisons this method with DRWG. The significant advantage to using DRWG is the increase in available measurement bandwidth. The challenges include sample fabrication and increased mathematical difficulty in finding the cutoff frequency for DRWG. These challenges are addressed and measurement results are examined

    Freehand Juxtapedicular Screws Placed in the Apical Concavity of Adult Idiopathic Scoliosis Patients: Technique, Computed Tomography Confirmation, and Radiographic Results

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    Objective The purpose of this study is to highlight our technique for freehand placement of juxtapedicular screws along with intraoperative computed tomography (CT) and radiographic results. Methods Consecutive patients with adult idiopathic scoliosis undergoing primary surgery by the senior author were identified. All type D (absent/slit like channel) pedicles were identified on preoperative CT. Three-dimensional visualization software was used to measure screw angulation and purchase. Radiographs were measured by a fellowship trained spine surgeon. The freehand technique was used to place all screws in a juxtapedicular fashion without any fluoroscopic, radiographic, navigational or robotic assistance. Results Seventy-three juxtapedicular screws were analyzed. The most common level was T7 (9 screws) on the left and T5 (12 screws) on the right. The average medial angulation was 20.7° (range, 7.1°–36.3°), lateral vertebral body purchase was 13.4 mm (range, 0–28.9 mm), and medial vertebral body purchase was 21.1 mm (range, 8.9–31.8 mm). More than half (53.4%) of the screws had bicortical purchase. Two screws were lateral on CT scan, defined by the screw axis lateral to the lateral vertebral body cortex. No screws were medial. There was a difference in medial angulation between screws with (n = 58) and without (n = 15) lateral body purchase (22.0±4.9 vs. 15.5±4.5, p < 0.001). Three of 73 screws were repositioned after intraoperative CT. There were no neurovascular complications. The mean coronal cobb corrections for main thoracic and lumbar curves were 83.0% and 80.5%, respectively, at an average of 17.5 months postoperative. Conclusion Freehand juxtapedicular screw placement is a safe technique for type D pedicles in adult idiopathic scoliosis patients

    Freeze-Dried Somatic Cells Direct Embryonic Development after Nuclear Transfer

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    The natural capacity of simple organisms to survive in a dehydrated state has long been exploited by man, with lyophylization the method of choice for the long term storage of bacterial and yeast cells. More recently, attempts have been made to apply this procedure to the long term storage of blood cells. However, despite significant progress, practical application in a clinical setting is still some way off. Conversely, to date there are no reports of attempts to lyophilize nucleated somatic cells for possible downstream applications. Here we demonstrate that lyophilised somatic cells stored for 3 years at room temperature are able to direct embryonic development following injection into enucleated oocytes. These remarkable results demonstrate that alternative systems for the long-term storage of cell lines are now possible, and open unprecedented opportunities in the fields of biomedicine and for conservation strategies

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

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    Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

    Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

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    Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

    Neutrophils: the forgotten cell in JIA disease pathogenesis

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    Juvenile idiopathic arthritis (JIA) has long been assumed to be an autoimmune disease, triggered by aberrant recognition of "self" antigens by T-cells. However, systems biology approaches to this family of diseases have suggested complex interactions between innate and adaptive immunity that underlie JIA. In particular, new data suggest an important role for neutrophils in JIA pathogenesis. In this short review, we will discuss the new data that support a role for neutrophils in JIA, discuss regulatory functions that link neutrophils to adaptive immune responses, and discuss future areas of investigation. Above all else, we invite the reader to re-consider the use of the term "autoimmunity" as applied to the family of illnesses we collectively call JIA

    Interactions between growth-dependent changes in cell size, nutrient supply and cellular elemental stoichiometry of marine Synechococcus

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    The factors that control elemental ratios within phytoplankton, like carbon:nitrogen:phosphorus (C:N:P), are key to biogeochemical cycles. Previous studies have identified relationships between nutrient-limited growth and elemental ratios in large eukaryotes, but little is known about these interactions in small marine phytoplankton like the globally important Cyanobacteria. To improve our understanding of these interactions in picophytoplankton, we asked how cellular elemental stoichiometry varies as a function of steady-state, N- and P-limited growth in laboratory chemostat cultures of Synechococcus WH8102. By combining empirical data and theoretical modeling, we identified a previously unrecognized factor (growth-dependent variability in cell size) that controls the relationship between nutrient-limited growth and cellular elemental stoichiometry. To predict the cellular elemental stoichiometry of phytoplankton, previous theoretical models rely on the traditional Droop model, which purports that the acquisition of a single limiting nutrient suffices to explain the relationship between a cellular nutrient quota and growth rate. Our study, however, indicates that growth-dependent changes in cell size have an important role in regulating cell nutrient quotas. This key ingredient, along with nutrient-uptake protein regulation, enables our model to predict the cellular elemental stoichiometry of Synechococcus across a range of nutrient-limited conditions. Our analysis also adds to the growth rate hypothesis, suggesting that P-rich biomolecules other than nucleic acids are important drivers of stoichiometric variability in Synechococcus. Lastly, by comparing our data with field observations, our study has important ecological relevance as it provides a framework for understanding and predicting elemental ratios in ocean regions where small phytoplankton like Synechococcus dominates

    A comprehensive analysis of autocorrelation and bias in home range estimation

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    Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated-Gaussian reference function [AKDE], SilvermanÂŽs rule of thumb, and least squares cross-validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half-sample cross-validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ((Formula presented.)) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID-based estimates by a mean factor of 2. The median number of cross-validated locations included in the hold-out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing (Formula presented.). To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animalÂŽs movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small (Formula presented.). While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an (Formula presented.) >1,000, where 30% had an (Formula presented.) <30. In this frequently encountered scenario of small (Formula presented.), AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.Fil: Noonan, Michael J.. National Zoological Park; Estados Unidos. University of Maryland; Estados UnidosFil: Tucker, Marlee A.. Senckenberg Gesellschaft FĂŒr Naturforschung; . Goethe Universitat Frankfurt; AlemaniaFil: Fleming, Christen H.. University of Maryland; Estados Unidos. National Zoological Park; Estados UnidosFil: Akre, Thomas S.. National Zoological Park; Estados UnidosFil: Alberts, Susan C.. University of Duke; Estados UnidosFil: Ali, Abdullahi H.. Hirola Conservation Programme. Garissa; KeniaFil: Altmann, Jeanne. University of Princeton; Estados UnidosFil: Antunes, Pamela Castro. Universidade Federal do Mato Grosso do Sul; BrasilFil: Belant, Jerrold L.. State University of New York; Estados UnidosFil: Beyer, Dean. Universitat Phillips; AlemaniaFil: Blaum, Niels. Universitat Potsdam; AlemaniaFil: Böhning Gaese, Katrin. Senckenberg Gesellschaft FĂŒr Naturforschung; Alemania. Goethe Universitat Frankfurt; AlemaniaFil: Cullen Jr., Laury. Instituto de Pesquisas EcolĂłgicas; BrasilFil: de Paula, Rogerio Cunha. National Research Center For Carnivores Conservation; BrasilFil: Dekker, Jasja. Jasja Dekker Dierecologie; PaĂ­ses BajosFil: Drescher Lehman, Jonathan. George Mason University; Estados Unidos. National Zoological Park; Estados UnidosFil: Farwig, Nina. Michigan State University; Estados UnidosFil: Fichtel, Claudia. German Primate Center; AlemaniaFil: Fischer, Christina. Universitat Technical Zu Munich; AlemaniaFil: Ford, Adam T.. University of British Columbia; CanadĂĄFil: Goheen, Jacob R.. University of Wyoming; Estados UnidosFil: Janssen, RenĂ©. Bionet Natuuronderzoek; PaĂ­ses BajosFil: Jeltsch, Florian. Universitat Potsdam; AlemaniaFil: Kauffman, Matthew. University Of Wyoming; Estados UnidosFil: Kappeler, Peter M.. German Primate Center; AlemaniaFil: Koch, FlĂĄvia. German Primate Center; AlemaniaFil: LaPoint, Scott. Max Planck Institute fĂŒr Ornithologie; Alemania. Columbia University; Estados UnidosFil: Markham, A. Catherine. Stony Brook University; Estados UnidosFil: Medici, Emilia Patricia. Instituto de Pesquisas EcolĂłgicas (IPE) ; BrasilFil: Morato, Ronaldo G.. Institute For Conservation of The Neotropical Carnivores; Brasil. National Research Center For Carnivores Conservation; BrasilFil: Nathan, Ran. The Hebrew University of Jerusalem; IsraelFil: Oliveira Santos, Luiz Gustavo R.. Universidade Federal do Mato Grosso do Sul; BrasilFil: Olson, Kirk A.. Wildlife Conservation Society; Estados Unidos. National Zoological Park; Estados UnidosFil: Patterson, Bruce. Field Museum of National History; Estados UnidosFil: Paviolo, Agustin Javier. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Nordeste. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș | Universidad Nacional de Misiones. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș; Argentina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Nordeste; ArgentinaFil: Ramalho, Emiliano Esterci. Institute For Conservation of The Neotropical Carnivores; Brasil. Instituto de Desenvolvimento Sustentavel MamirauĂĄ; BrasilFil: Rösner, Sascha. Michigan State University; Estados UnidosFil: Schabo, Dana G.. Michigan State University; Estados UnidosFil: Selva, Nuria. Institute of Nature Conservation of The Polish Academy of Sciences; PoloniaFil: Sergiel, Agnieszka. Institute of Nature Conservation of The Polish Academy of Sciences; PoloniaFil: Xavier da Silva, Marina. Parque Nacional do Iguaçu; BrasilFil: Spiegel, Orr. Universitat Tel Aviv; IsraelFil: Thompson, Peter. University of Maryland; Estados UnidosFil: Ullmann, Wiebke. Universitat Potsdam; AlemaniaFil: Ziឝba, Filip. Tatra National Park; PoloniaFil: Zwijacz Kozica, Tomasz. Tatra National Park; PoloniaFil: Fagan, William F.. University of Maryland; Estados UnidosFil: Mueller, Thomas. Senckenberg Gesellschaft FĂŒr Naturforschung; . Goethe Universitat Frankfurt; AlemaniaFil: Calabrese, Justin M.. National Zoological Park; Estados Unidos. University of Maryland; Estados Unido
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