Search

Your search keyword '"Novak Jan"' showing total 1,741 results
Start Over Author "Novak Jan"
1,741 results on '"Novak Jan"'

1. Segmentation of Pediatric Brain Tumors using a Radiologically informed, Deep Learning Cascade

Author

Mulvany, Timothy, Griffiths-King, Daniel, Novak, Jan, and Rose, Heather

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Monitoring of Diffuse Intrinsic Pontine Glioma (DIPG) and Diffuse Midline Glioma (DMG) brain tumors in pediatric patients is key for assessment of treatment response. Response Assessment in Pediatric Neuro-Oncology (RAPNO) guidelines recommend the volumetric measurement of these tumors using MRI. Segmentation challenges, such as the Brain Tumor Segmentation (BraTS) Challenge, promote development of automated approaches which are replicable, generalizable and accurate, to aid in these tasks. The current study presents a novel adaptation of existing nnU-Net approaches for pediatric brain tumor segmentation, submitted to the BraTS-PEDs 2024 challenge. We apply an adapted nnU-Net with hierarchical cascades to the segmentation task of the BraTS-PEDs 2024 challenge. The residual encoder variant of nnU-Net, used as our baseline model, already provides high quality segmentations. We incorporate multiple changes to the implementation of nnU-Net and devise a novel two-stage cascaded nnU-Net to segment the substructures of brain tumors from coarse to fine. Using outputs from the nnU-Net Residual Encoder (trained to segment CC, ED, ET and NET tumor labels from T1w, T1w-CE, T2w and T2-FLAIR MRI), these are passed to two additional models one classifying ET versus NET and a second classifying CC vs ED using cascade learning. We use radiological guidelines to steer which multi parametric MRI (mpMRI) to use in these cascading models. Compared to a default nnU-Net and an ensembled nnU-net as baseline approaches, our novel method provides robust segmentations for the BraTS-PEDs 2024 challenge, achieving mean Dice scores of 0.657, 0.904, 0.703, and 0.967, and HD95 of 76.2, 10.1, 111.0, and 12.3 for the ET, NET, CC and ED, respectively.

Published
2024

2. High Priority Request List cross-section measurements: 7Li(d,x)7Be/3H and 39K(n,p)39Ar

Author

Koliadko Daniil, Majerle Mitja, Klix Axel, Šimečková Eva, Novak Jan, Mrázek Jaromír, Ansorge Martin, Angelone Maurizio, and Štefánik Milan

Subjects
Physics, QC1-999
Abstract

The Nuclear Energy Agency’s High Priority Nuclear Data Request List is a compilation of the highest priority nuclear data requirements. The U-120M cyclotron of the Nuclear Physics Institute of the Czech Academy of Sciences is a suitable tool for studies of several reactions from this list. In this paper, we present the measurements of the 7Be and 3H production in the lithium-7 after the irradiation with deuterons and the validation measurement for the 39Ar production in 39K after irradiation with neutrons .

Published
2023
Full Text
View/download PDF

3. An Open-Label Pilot Study of Adrenocorticotrophic Hormone in the Treatment of IgA Nephropathy at High Risk of Progression

Author

Ladan Zand, Pietro Canetta, Richard Lafayette, Nabeel Aslam, Novak Jan, Sanjeev Sethi, and Fernando C. Fervenza

Subjects
Diseases of the genitourinary system. Urology, RC870-923
Abstract

Introduction: IgA nephropathy (IgAN) is the most common glomerulonephritis with high risk of progression to end-stage renal disease in patients with proteinuria >1 g/24 hours. There are no known effective treatments in patients with IgAN. Methods: We conducted a prospective open-label pilot study in patients with IgAN using adrenocorticotrophic hormone (ACTH) (Acthar Gel, Mallinckrodt Pharmaceuticals, Bedminster, NJ) at a dosage of 80 units subcutaneously twice weekly for a total of 6 months and followed patients for a total of 12 months. Patients had to have urinary protein >1 g/24 hours despite adequate renin-angiotensin-aldosterone system (RAAS) blockade and estimated glomerular filtration rate (eGFR) >30 ml/min at enrollment. Results: A total of 19 patients were recruited and followed for 1 year. At baseline, the mean age was 34.9 ± 10.5 years with 11 men and 8 women, and 14 Caucasian and 5 Asian individuals. At 12 months, there was a statistically significant decline in 24-hour urinary protein from 2.6 to 1.3 g (P = 0.007) and significant increase in serum albumin (3.79 to 3.93, P = 0.02). There was no significant change in eGFR (65.5 to 61.1 ml/min, P = 0.1). There were 0 complete remissions and 8 partial remissions (42%). There were a total of 6 infections: 2 were viral and 4 required antibiotic therapy (2 sinusitis, 1 pneumonia, 1 otitis media). The most common adverse events included acne, hot flashes, soreness, and anxiety. Conclusion: In summary, patients with IgAN with >1 g/24-hour urinary protein and eGFR >30 ml/min had a significant reduction in 24-hour urinary protein with stable eGFR at 12-month follow-up after being treated with 6 months of ACTH. Keywords: ACTH, IgA nephropathy, proteinuria

Published
2020
Full Text
View/download PDF

6. Waveform Modelling for the Laser Interferometer Space Antenna

Author

LISA Consortium Waveform Working Group, Afshordi, Niayesh, Akçay, Sarp, Seoane, Pau Amaro, Antonelli, Andrea, Aurrekoetxea, Josu C., Barack, Leor, Barausse, Enrico, Benkel, Robert, Bernard, Laura, Bernuzzi, Sebastiano, Berti, Emanuele, Bonetti, Matteo, Bonga, Béatrice, Bozzola, Gabriele, Brito, Richard, Buonanno, Alessandra, Cárdenas-Avendaño, Alejandro, Casals, Marc, Chernoff, David F., Chua, Alvin J. K., Clough, Katy, Colleoni, Marta, Dhesi, Mekhi, Druart, Adrien, Durkan, Leanne, Faye, Guillaume, Ferguson, Deborah, Field, Scott E., Gabella, William E., García-Bellido, Juan, Gracia-Linares, Miguel, Gerosa, Davide, Green, Stephen R., Haney, Maria, Hannam, Mark, Heffernan, Anna, Hinderer, Tanja, Helfer, Thomas, Hughes, Scott A., Husa, Sascha, Isoyama, Soichiro, Katz, Michael L., Kavanagh, Chris, Khanna, Gaurav, Kidder, Larry E., Korol, Valeriya, Küchler, Lorenzo, Laguna, Pablo, Larrouturou, François, Tiec, Alexandre Le, Leather, Benjamin, Lim, Eugene A., Lim, Hyun, Littenberg, Tyson B., Long, Oliver, Lousto, Carlos O., Lovelace, Geoffrey, Lukes-Gerakopoulos, Georgios, Lynch, Philip, Macedo, Rodrigo P., Markakis, Charalampos, Maggio, Elisa, Mandel, Ilya, Maselli, Andrea, Mathews, Josh, Mourier, Pierre, Neilsen, David, Nagar, Alessandro, Nichols, David A., Novák, Jan, Okounkova, Maria, O'Shaughnessy, Richard, Oshita, Naritaka, O'Toole, Conor, Pan, Zhen, Pani, Paolo, Pappas, George, Paschalidis, Vasileios, Pfeiffer, Harald P., Pompili, Lorenzo, Pound, Adam, Pratten, Geraint, Rüter, Hannes R., Ruiz, Milton, Sam, Zeyd, Sberna, Laura, Shapiro, Stuart L., Shoemaker, Deirdre M., Sopuerta, Carlos F., Spiers, Andrew, Sundar, Hari, Tamanini, Nicola, Thompson, Jonathan E., Toubiana, Alexandre, Tsokaros, Antonios, Upton, Samuel D., van de Meent, Maarten, Vernieri, Daniele, Wachter, Jeremy M., Warburton, Niels, Wardell, Barry, Witek, Helvi, Witzany, Vojtěch, Yang, Huan, Zilhão, Miguel, Albertini, Angelica, Arun, K. G., Bezares, Miguel, Bonilla, Alexander, Chapman-Bird, Christian, Cownden, Bradley, Cunningham, Kevin, Devitt, Chris, Dolan, Sam, Duque, Francisco, Dyson, Conor, Fryer, Chris L., Gair, Jonathan R., Giacomazzo, Bruno, Gupta, Priti, Han, Wen-Biao, Haas, Roland, Hirschmann, Eric W., Huerta, E. A., Jetzer, Philippe, Kelly, Bernard, Khalil, Mohammed, Lewis, Jack, Lloyd-Ronning, Nicole, Marsat, Sylvain, Nardini, Germano, Neef, Jakob, Ottewill, Adrian, Pantelidou, Christiana, Piovano, Gabriel Andres, Redondo-Yuste, Jaime, Sagunski, Laura, Stein, Leo C., Skoupý, Viktor, Sperhake, Ulrich, Speri, Lorenzo, Spieksma, Thomas F. M., Stevens, Chris, Trestini, David, and Vañó-Viñuales, Alex

Subjects
General Relativity and Quantum Cosmology, Astrophysics - High Energy Astrophysical Phenomena
Abstract

LISA, the Laser Interferometer Space Antenna, will usher in a new era in gravitational-wave astronomy. As the first anticipated space-based gravitational-wave detector, it will expand our view to the millihertz gravitational-wave sky, where a spectacular variety of interesting new sources abound: from millions of ultra-compact binaries in our Galaxy, to mergers of massive black holes at cosmological distances; from the beginnings of inspirals that will venture into the ground-based detectors' view to the death spiral of compact objects into massive black holes, and many sources in between. Central to realising LISA's discovery potential are waveform models, the theoretical and phenomenological predictions of the pattern of gravitational waves that these sources emit. This white paper is presented on behalf of the Waveform Working Group for the LISA Consortium. It provides a review of the current state of waveform models for LISA sources, and describes the significant challenges that must yet be overcome., Comment: 239 pages, 11 figures, white paper from the LISA Consortium Waveform Working Group, invited for submission to Living Reviews in Relativity, updated with comments from community

Published
2023

7. Participatory development of an mHealth intervention delivered in general practice to increase physical activity and reduce sedentary behaviour of patients with prediabetes and type 2 diabetes (ENERGISED)

Author

Novak, Jan, Jurkova, Katerina, Lojkaskova, Anna, Jaklova, Andrea, Kuhnova, Jitka, Pfeiferova, Marketa, Kral, Norbert, Janek, Michael, Omcirk, Dan, Malisova, Katerina, Maes, Iris, Dyck, Delfien Van, Wahlich, Charlotte, Ussher, Michael, Elavsky, Steriani, Cimler, Richard, Pelclova, Jana, Tufano, James J., Steffl, Michal, Seifert, Bohumil, Yates, Tom, Harris, Tess, and Vetrovsky, Tomas

Published
2024
Full Text
View/download PDF

8. The methodology for validation of cross sections in quasi monoenergetic neutron field

Author

Matěj, Zdeněk, Košťál, Michal, Majerle, Mitja, Ansorge, Martin, Losa, Evžen, Zmeškal, Marek, Schulc, Martin, Šimon, Jan, Štefánik, Milan, Novák, Jan, Koliadko, Daniil, Cvachovec, František, Mravec, Filip, Přenosil, Václav, Zach, Václav, Czakoj, Tomáš, Rypar, Vojtěch, and Capote, Roberto

Subjects
Physics - Instrumentation and Detectors, Nuclear Experiment, Physics - Accelerator Physics
Abstract

Dosimetry cross sections are fundamental quantities essential in determination of neutron fluences in points of interest in technologies under heavy radiation load. The most common is their application to Reactor Pressure Vessel aging management, relating to correct estimation of its residual lifetime. The neutron spectrum in various reactor positions has a similar character as the fission spectrum. Due to this fact, the validation of the neutron dosimetry cross sections in reactor fields, or in a very well-known neutron field of 252Cf(s.f.) is sufficient for ensuring their validity in estimations of neutron fluxes in reactor physics. With an increasing field of applications, as in neutron dosimetry in accelerator-based fields or space applications, requests occurred on detailed validation in spectra different from fission ones. This paper presents the testing of a new methodology for the use of quasi monoenergetic neutron fields, where different sensitivity allows validations of the cross-section in different energy regions than in the fission spectrum. The exact shape of the neutron spectrum in the tested fields is determined by stilbene spectrometry and corrected to scattering by calculation, where applicable. The total flux is determined from Ni and Al flux monitors. The evaluated neutron flux in the target set of activation foils is used for calculation of theoretical reaction rate, which is compared with the experimental value determined from gamma activity. This kind of comparison can be understood as validation. It is worth noting, this methodology applied to the IRDFF-II library shows satisfactory agreement for selected reactions.

Published
2023

9. Wang tiles enable combinatorial design and robot-assisted manufacturing of modular mechanical metamaterials

Author

Doškář, Martin, Somr, Michael, Hlůžek, Radim, Havelka, Jan, Novák, Jan, and Zeman, Jan

Subjects
Condensed Matter - Materials Science, Condensed Matter - Soft Condensed Matter
Abstract

In this paper, we introduce a novel design paradigm for modular architectured materials that allows for spatially nonuniform designs from a handful of building blocks, which can be robotically assembled for efficient and scalable production. The traditional, design-limiting periodicity in material design is overcome by utilizing Wang tiles to achieve compatibility among building blocks. We illustrate our approach with the design and manufacturing of an L-shaped domain inspired by a scissor-like soft gripper, whose internal module distribution was optimized to achieve an extreme tilt of a tip of the gripper's jaw when the handle part was uniformly compressed. The geometry of individual modules was built on a 3$\times$3 grid of elliptical holes with varying semi-axes ratios and alternating orientations. We optimized the distribution of the modules within the L-shaped domain using an enumeration approach combined with a factorial search strategy. To address the challenge of seamless interface connections in modular manufacturing, we produced the final designs by casting silicone rubber into modular molds automatically assembled by a robotic arm. The predicted performance was validated experimentally using a custom-built, open-hardware test rig, Thymos, supplemented with digital image correlation measurements. Our study demonstrates the potential for enhancing the mechanical performance of architectured materials by incorporating nonuniform modular designs and efficient robot-assisted manufacturing., Comment: manuscript: 9 pages, 5 figures; supplementary: 10 pages, 10 figures

Published
2023
Full Text
View/download PDF

10. Real-Time Neural Appearance Models

Author

Zeltner, Tizian, Rousselle, Fabrice, Weidlich, Andrea, Clarberg, Petrik, Novák, Jan, Bitterli, Benedikt, Evans, Alex, Davidovič, Tomáš, Kallweit, Simon, and Lefohn, Aaron

Subjects
Computer Science - Graphics
Abstract

We present a complete system for real-time rendering of scenes with complex appearance previously reserved for offline use. This is achieved with a combination of algorithmic and system level innovations. Our appearance model utilizes learned hierarchical textures that are interpreted using neural decoders, which produce reflectance values and importance-sampled directions. To best utilize the modeling capacity of the decoders, we equip the decoders with two graphics priors. The first prior -- transformation of directions into learned shading frames -- facilitates accurate reconstruction of mesoscale effects. The second prior -- a microfacet sampling distribution -- allows the neural decoder to perform importance sampling efficiently. The resulting appearance model supports anisotropic sampling and level-of-detail rendering, and allows baking deeply layered material graphs into a compact unified neural representation. By exposing hardware accelerated tensor operations to ray tracing shaders, we show that it is possible to inline and execute the neural decoders efficiently inside a real-time path tracer. We analyze scalability with increasing number of neural materials and propose to improve performance using code optimized for coherent and divergent execution. Our neural material shaders can be over an order of magnitude faster than non-neural layered materials. This opens up the door for using film-quality visuals in real-time applications such as games and live previews., Comment: Equal contribution by the first six authors. Order determined by a rock-paper-scissors tournament. Project page: https://research.nvidia.com/labs/rtr/neural_appearance_models/

Published
2023
Full Text
View/download PDF

11. Inverse Global Illumination using a Neural Radiometric Prior

Author

Hadadan, Saeed, Lin, Geng, Novák, Jan, Rousselle, Fabrice, and Zwicker, Matthias

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Graphics
Abstract

Inverse rendering methods that account for global illumination are becoming more popular, but current methods require evaluating and automatically differentiating millions of path integrals by tracing multiple light bounces, which remains expensive and prone to noise. Instead, this paper proposes a radiometric prior as a simple alternative to building complete path integrals in a traditional differentiable path tracer, while still correctly accounting for global illumination. Inspired by the Neural Radiosity technique, we use a neural network as a radiance function, and we introduce a prior consisting of the norm of the residual of the rendering equation in the inverse rendering loss. We train our radiance network and optimize scene parameters simultaneously using a loss consisting of both a photometric term between renderings and the multi-view input images, and our radiometric prior (the residual term). This residual term enforces a physical constraint on the optimization that ensures that the radiance field accounts for global illumination. We compare our method to a vanilla differentiable path tracer, and more advanced techniques such as Path Replay Backpropagation. Despite the simplicity of our approach, we can recover scene parameters with comparable and in some cases better quality, at considerably lower computation times., Comment: Homepage: https://inverse-neural-radiosity.github.io

Published
2023
Full Text
View/download PDF

12. Neutron spectrum determination of p+Be reaction for 30 MeV protons using the multi-foil activation technique

Author

Stefanik Milan, Simeckova Eva, Bem Pavel, Majerle Mitja, Novak Jan, Ansorge Martin, Mrazek Jaromir, and Stursa Jan

Subjects
Physics, QC1-999
Abstract

At the NPI in Rez, the p + Be source reaction was investigated for 30 MeV proton beam and thick beryllium target. For neutron field determination of the p(30)+Be source reaction in close source-to-sample distance, the multi-foil activation technique with a set of 10 activation materials (Au, Co, Lu, Ti, In, Al, Y, Fe, Ni, Nb) was utilized. From resulting reaction rates, the neutron spectrum was reconstructed using the SAND-II unfolding code. New neutron field of white spectrum up to 28 MeV has an intensity of 8.6 × 1010 cm−2s−1 close to target. The obtained neutron field extends the utilization of cyclotron-based fast neutron sources at the NPI and provides new experimental opportunities for future irradiation experiments such as fast neutron activation analysis, nuclear data validation, and radiation damage study of electronics and materials for nuclear energetics.

Published
2020
Full Text
View/download PDF

13. Charged particle activation facility in NPI CAS and in future GANIL/SPIRAL2-NFS

Author

Mrazek Jaromir, Simeckova Eva, Behal Radomir, Glagolev Vadim, Vesely František, Stefanik Milan, Majerle Mitja, Novak Jan, Ansorge Martin, Sivacek Ivan, Vrzalova Jitka, Ledoux Xavier, de Oliveira Santos Francois, Fischer Ulrich, Klix Axel, Avrigeanu Marilena, and Avrigeanu Vlad

Subjects
Physics, QC1-999
Abstract

The proton, deuteron and alpha induced reactions are of a great interest for the assessment of induced radioactivity of accelerator components, targets and beam stoppers as well as isotope production for medicine and also to nuclear astrophysics. We present a new irradiation chamber for activation measurements, that forms a prolongation of long-term experimental activities using stacked-foil activation technique in NPI CAS, Řež. The chamber is based on an airlock system and is coupled to a pneumatic transfer system delivered by KIT Karlsruhe. This system is installed in GANIL/SPIRAL2-NFS and will be used for proton, deuteron and alpha particle activation measurements with long- and short-lived isotopes.

Published
2020
Full Text
View/download PDF

14. Glasdegib plus intensive or non-intensive chemotherapy for untreated acute myeloid leukemia: results from the randomized, phase 3 BRIGHT AML 1019 trial.

Author

Tomlinson, Benjamin, Mayer, Jiri, Jou, Erin, Robak, Tadeusz, Taussig, David, Dombret, Hervé, Merchant, Akil, Shaik, Naveed, OBrien, Thomas, Roh, Whijae, Liu, Xueli, Ma, Wendy, DiRienzo, Christine, Chan, Geoffrey, Cortes, Jorge, Sekeres, Mikkael, Montesinos, Pau, Novak, Jan, Wang, Jianxiang, and Jeyakumar, Deepa

Abstract

This is the primary report of the randomized, placebo-controlled phase 3 BRIGHT AML 1019 clinical trial of glasdegib in combination with intensive chemotherapy (cytarabine and daunorubicin) or non-intensive chemotherapy (azacitidine) in patients with untreated acute myeloid leukemia. Overall survival (primary endpoint) was similar between the glasdegib and placebo arms in the intensive (n = 404; hazard ratio [HR] 1.05; 95% confidence interval [CI]: 0.782-1.408; two-sided p = 0.749) and non-intensive (n = 325; HR 0.99; 95% CI: 0.768-1.289; two-sided p = 0.969) studies. The proportion of patients who experienced treatment-emergent adverse events was similar for glasdegib versus placebo (intensive: 99.0% vs. 98.5%; non-intensive: 99.4% vs. 98.8%). The most common treatment-emergent adverse events were nausea, febrile neutropenia, and anemia in the intensive study and anemia, constipation, and nausea in the non-intensive study. The addition of glasdegib to either cytarabine and daunorubicin or azacitidine did not significantly improve overall survival and the primary efficacy endpoint for the BRIGHT AML 1019 phase 3 trial was not met. Clinical trial registration: ClinicalTrials.gov: NCT03416179.

Published
2023

19. Neutron field of accelerator-driven p(35 MeV)+Be fast neutron source at NPI Rez

Author

Stefanik Milan, Bem Pavel, Majerle Mitja, Novak Jan, and Simeckova Eva

Subjects
Physics, QC1-999
Abstract

The accelerator driven fast neutron sources of the white- and quasi-monoenergetic spectra are operated at the NPI Rez Fast Neutron Facility utilizing the Be(thick), D2O(thick), and 7Li(C) target stations and the variable energy proton beam (up to 37 MeV) from the U-120M isochronous cyclotron. Recently, the design of beryllium target station was upgraded in order to provide the higher neutron flux at the modified positions of irradiated samples. Afterwards, the thick target neutron field of the p+Be source reaction was investigated for proton energy of 35 MeV. The spectral neutron flux for several target-to-sample distances was determined using the multi-foil activation technique. From measured reaction rates, new neutron spectra were reconstructed employing the SAND-II unfolding code and validated against the MCNPX predictions. The IFMIF-like (International Fusion Material Irradiation Facility) neutron field obtained from the p(35)+Be source is suitable for the neutron cross-sections validation within the IFMIF research program, radiation hardness tests of electronics, and neutron activation analysis experiments.

Published
2017
Full Text
View/download PDF

20. Heart rate variability and stroke or systemic embolism in patients with atrial fibrillation

Author

Aeschbacher, Stefanie, Bhend, Katalin, Blum, Steffen, Bonati, Leo H., Carmine, Désirée, Conen, David, Eken, Ceylan, Fischer, Urs, Girroy, Corinne, Hennings, Elisa, Krisai, Philipp, Kühne, Michael, Mäder, Nina, Meyer-Zürn, Christine, Meyre, Pascal B., Monsch, Andreas U., Mosher, Luke, Müller, Christian, Osswald, Stefan, Paladini, Rebecca E., Peter, Raffaele, Schweigler, Adrian, Sticherling, Christian, Szucs, Thomas, Völlmin, Gian, Aujesky, Drahomir, Fuhrer, Juerg, Roten, Laurent, Jung, Simon, Mattle, Heinrich, Netzer, Seraina, Adam, Luise, Aubert, Carole Elodie, Feller, Martin, Loewe, Axel, Moutzouri, Elisavet, Schneider, Claudio, Flückiger, Tanja, Groen, Cindy, Ehrsam, Lukas, Hellrigl, Sven, Nuoffer, Alexandra, Rakovic, Damiana, Schwab, Nathalie, Wenger, Rylana, Zarrabi Saffari, Tu Hanh, Rodondi, Nicolas, Reichlin, Tobias, Beynon, Christopher, Dillier, Roger, Deubelbeiss, Michèle, Eberli, Franz, Franzini, Christine, Juchli, Isabel, Liedtke, Claudia, Murugiah, Samira, Nadler, Jacqueline, Obst, Thayze, Roth, Jasmin, Schlomowitsch, Fiona, Schneider, Xiaoye, Studerus, Katrin, Tynan, Noreen, Weishaupt, Dominik, Müller, Andreas, Friedli, Corinne, Kuest, Silke, Scheuch, Karin, Hischier, Denise, Bonetti, Nicole, Grau, Alexandra, Villinger, Jonas, Laube, Eva, Baumgartner, Philipp, Filipovic, Mark, Frick, Marcel, Montrasio, Giulia, Leuenberger, Stefanie, Rutz, Franziska, Beer, Jürg-Hans, Auricchio, Angelo, Anesini, Adriana, Camporini, Cristina, Caputo, Maria Luce, Peronaci, Rebecca, Regoli, Francois, Ronchi, Martina, Conte, Giulio, Brenner, Roman, Altmann, David, Fink, Karin, Gemperle, Michaela, Ammann, Peter, Firmann, Mathieu, Foucras, Sandrine, Rime, Martine, Hayoz, Daniel, Berte, Benjamin, Bühler, Kathrin, Justi, Virgina, Kellner-Weldon, Frauke, Koch, Melanie, Mehmann, Brigitta, Meier, Sonja, Roth, Myriam, Ruckli-Kaeppeli, Andrea, Russi, Ian, Schmidt, Kai, Young, Mabelle, Kobza, Richard, Rigamonti, Elia, Cereda, Carlo, Cianfoni, Alessandro, De Perna, Maria Luisa, Frangi-Kultalahti, Jane, Mayer Melchiorre, Patrizia Assunta, Pin, Anica, Terrot, Tatiana, Vicari, Luisa, Moschovitis, Giorgio, Ehret, Georg, Gallet, Hervé, Guillermet, Elise, Lazeyras, Francois, Lovblad, Karl-Olof, Perret, Patrick, Tavel, Philippe, Teres, Cheryl, Shah, Dipen, Lauriers, Nathalie, Méan, Marie, Salzmann, Sandrine, Schläpfer, Jürg, Porretta, Alessandra Pia, Grêt, Andrea, Novak, Jan, Vitelli, Sandra, Stephan, Frank-Peter, Gallino, Augusto, Di Valentino, Marcello, Aebersold, Helena, Foster, Fabienne, Schwenkglenks, Matthias, Düring, Marco, Sinnecker, Tim, Altermatt, Anna, Amann, Michael, Huber, Petra, Hürbin, Manuel, Ruberte, Esther, Thöni, Alain, Würfel, Jens, Zuber, Vanessa, Coslovsky (Head), Michael, Neuschwander, Pia, Simon, Patrick, Wunderlin, Olivia, Schmid, Ramun, Baumann, Christian, Hämmerle, Peter, Schlageter, Vincent, Coslovsky, Michael, Coduri, Federica, Blum, Manuel R., Stauber, Annina, Beer, Jürg, and Zuern, Christine S.

Published
2024
Full Text
View/download PDF

21. Advancements in risk stratification and management strategies in primary cardiovascular prevention

Author

Barkas, Fotios, Sener, Yusuf Ziya, Golforoush, Pelin Arabacilar, Kheirkhah, Azin, Rodriguez-Sanchez, Elena, Novak, Jan, Apellaniz-Ruiz, Maria, Akyea, Ralph Kwame, Bianconi, Vanessa, Ceasovschih, Alexandr, Chee, Ying Jie, Cherska, Mariia, Chora, Joana Rita, D'Oria, Mario, Demikhova, Nadiia, Kocyigit Burunkaya, Duygu, Rimbert, Antoine, Macchi, Chiara, Rathod, Krishnaraj, Roth, Lynn, Sukhorukov, Vasily, Stoica, Svetlana, Scicali, Roberto, Storozhenko, Tatyana, Uzokov, Jamol, Lupo, Maria Giovanna, van der Vorst, Emiel P.C., and Porsch, Florentina

Published
2024
Full Text
View/download PDF

22. Scalar perturbations of Galileon cosmologies in the mechanical approach within the late Universe

Author

Novák, Jan

Subjects
General Relativity and Quantum Cosmology
Abstract

We investigate the Universe at the late stage of its evolution and inside the cell of uniformity 150-370 Mpc. We consider the Universe to be filled at these scales with dust like matter, a minimally coupled Galileon field and radiation. We use the mechanical approach. Therefore, the peculiar velocities of the inhomogeneities as well as the fluctuations of the other perfect fluids can be considered nonrelativistic. Such fluids are said to be coupled because they are concentrated around the inhomogeneities. We investigate the conditions under which the physical Galileon field, i.e. compatible with results of the latest gravitational wave experiments GW150914, GW151226, GW170104, GW170814, GW170817 and GW170608, can become coupled. We know that at the background level coupled scalar fields behave as a two-component perfect fluids: one which mimics a network of frustrated cosmic string and an another one which corresponds to an effective cosmological constant. We found a correction for the Galileon field, which behaves like a matter component., Comment: 8 pages

Published
2021
Full Text
View/download PDF

23. Glasdegib plus intensive or non-intensive chemotherapy for untreated acute myeloid leukemia: results from the randomized, phase 3 BRIGHT AML 1019 trial

Author

Sekeres, Mikkael A., Montesinos, Pau, Novak, Jan, Wang, Jianxiang, Jeyakumar, Deepa, Tomlinson, Benjamin, Mayer, Jiri, Jou, Erin, Robak, Tadeusz, Taussig, David C., Dombret, Hervé, Merchant, Akil, Shaik, Naveed, O’Brien, Thomas, Roh, Whijae, Liu, Xueli, Ma, Wendy, DiRienzo, Christine G., Chan, Geoffrey, and Cortes, Jorge E.

Published
2023
Full Text
View/download PDF

24. Hormonal responses of rice to organ-targeted cold stress

Author

Jarošová, Jana, Prerostova, Sylva, Černý, Martin, Dobrev, Petre, Gaudinova, Alena, Knirsch, Vojtech, Kobzová, Eva, Müller, Karel, Fiala, Roman, Benczúr, Kinga, Szalai, Gabriella, Novák, Jan, Brzobohatý, Břetislav, Novak, Ondrej, and Vankova, Radomira

Published
2024
Full Text
View/download PDF

25. Decoding the historical tale: COVID-19 impact on haematological malignancy patients—EPICOVIDEHA insights from 2020 to 2022

Author

Martín-Vallejo, Francisco Javier, Zdziarski, Przemyslaw, Zarrinfer, Hossein, Wittig, Jana, Win, Sein, Wai-Man, Vivien, Víšek, Benjamín, Vinh, Donald C., Vehreschild, Maria, Varricchio, Gina, Tsirigotis, Panagiotis, Torres-Tienza, Ana, Tanase, Alina Daniela, Tafuri, Agostino, Stamouli, Maria, Sramek, Jiří, Soussain, Carole, Shirinova, Ayten, Schubert, Jörg, Schalk, Enrico, Salehi, Mohammad Reza, Saleh, Modar, Rosati, Giorgio, Roldán, Elisa, Reizine, Florian, Rêgo, Mayara, Regalado-Artamendi, Isabel, Popova, Marina, Pinto, Fernando, Philippe, Laure, Orth, Hans Martin, Ommen, Hans-Beier, Obr, Aleš, Núñez-Martín-Buitrago, Lucía, Noël, Nicolas, Neuhann, Julia, Nadali, Gianpaolo, Nacov, Julia A., Munhoz Alburquerque, Ana M., Mitra, Maria Enza, Mikulska, Malgorzata, Mellinghoff, Sibylle, Mechtel, Ben, Martín-González, Juan-Alberto, Malak, Sandra, Loureiro-Amigo, Jorge, Lorenzo De La Peña, Lisset, Liberti, Giulia, Landau, Marianne, Lacej, Ira, Kolditz, Martin, Kho, Chi Shan, Khedr, Reham Abdelaziz, Karthaus, Meinolf, Karlsson, Linda Katharina, Jiménez-Lorenzo, María-Josefa, Izuzquiza, Macarena, Hoell-Neugebauer, Baerbel, Herbrecht, Raoul, Heath, Christopher H., Guolo, Fabio, Grothe, Jan, Giordano, Antonio, Gerasymchuk, Sergey, García-Sanz, Ramón, García-Poutón, Nicole, Funke, Vaneuza Araújo Moreira, Fung, Monica, Flasshove, Charlotte, Fianchi, Luana, Essame, Jenna, Egger, Matthias, Drenou, Bernard, Dragonetti, Giulia, Desole, Maximilian, Della Pepa, Roberta, Deau Fischer, Bénédicte, De Kort, Elizabeth, De Cabo, Erik, Danion, François, Daguindau, Etienne, Cushion, Tania, Cremer, Louise, Criscuolo, Marianna, Cordini, Gregorio, Cingolani, Antonella, Ciceri, Fabio, Chowdhury, Fazle Rabbi, Chelysheva, Ekaterina, Chauchet, Adrien, Chai, Louis Yi Ann, Ceesay, M. Mansour, Busch, Elena, Brehon, Mathias, Borducchi, Davimar M.M., Booth, Stephen, Bologna, Serge, Berg Venemyr, Caroline, Bailén-Almorox, Rebeca, Antoniadou, Anastasia, Anastasopoulou, Amalia N., Altuntaş, Fevzi, Salmanton-García, Jon, Marchesi, Francesco, Farina, Francesca, Weinbergerová, Barbora, Itri, Federico, Dávila-Valls, Julio, Martín-Pérez, Sonia, Glenthøj, Andreas, Hersby, Ditte Stampe, Gomes Da Silva, Maria, Nunes Rodrigues, Raquel, López-García, Alberto, Córdoba, Raúl, Bilgin, Yavuz M., Falces-Romero, Iker, El-Ashwah, Shaimaa, Emarah, Ziad, Besson, Caroline, Kohn, Milena, Van Doesum, Jaap, Ammatuna, Emanuele, Marchetti, Monia, Labrador, Jorge, Zambrotta, Giovanni Paolo Maria, Verga, Luisa, Jaksic, Ozren, Nucci, Marcio, Piukovics, Klára, Cabirta-Touzón, Alba, Jiménez, Moraima, Arellano, Elena, Espigado, Ildefonso, Blennow, Ola, Nordlander, Anna, Meers, Stef, Vian Praet, Jens, Aiello, Tommaso Francesco, Garcia-Vidal, Carolina, Fracchiolla, Nicola S., Sciumè, Mariarita, Seval, Guldane Cengiz, Žák, Pavel, Buquicchio, Caterina, Tascini, Carlo, Gräfe, Stefanie K., Schönlein, Martin, Adžić-VUKIČEVIĆ, Tatjana, Bonuomo, Valentina, Cattaneo, Chiara, Nizamuddin, Summiya, Čerňan, Martin, Plantefeve, Gaëtan, Prin, Romane, Szotkovski, Tomas, Collins, Graham P., Dargenio, Michelina, Petzer, Verena, Wolf, Dominik, Čolović, Natasha, Prezioso, Lucia, Valković, Toni, Passamonti, Francesco, Méndez, Gustavo-Adolfo, Sili, Uluhan, Vena, Antonio, Bavastro, Martina, Limongelli, Alessandro, Duarte, Rafael F., Ledoux, Marie-Pierre, Cvetanoski, Milche, Stojanoski, Zlate, Machado, Marina, Batinić, Josip, Magliano, Gabriele, Biernat, Monika M., Pantić, Nikola, Poulsen, Christian Bjørn, Cuccaro, Annarosa, Del Principe, Maria Ilaria, Kulasekararaj, Austin, Ormazabal-Vélez, Irati, Busca, Alessandro, Demirkan, Fatih, Ijaz, Marriyam, Klimko, Nikolai, Stoma, Igor, Khostelidi, Sofya, Fernández, Noemí, Omrani, Ali S., Bergantim, Rui, De Jonge, Nick, Fouquet, Guillemette, Navrátil, Milan, Abu-Zeinah, Ghaith, Samarkos, Michail, Maertens, Johan, De Ramón, Cristina, Guidetti, Anna, Magyari, Ferenc, González-López, Tomás José, Lahmer, Tobias, Finizio, Olimpia, Ali, Natasha, Pinczés, László Imre, Lavilla-Rubira, Esperanza, Romano, Alessandra, Merelli, Maria, Delia, Mario, Calbacho, Maria, Meletiadis, Joseph, Antić, Darko, Hernández-Rivas, José-Ángel, Marques De Almeida, Joyce, Al-Khabori, Murtadha, Hoenigl, Martin, Tisi, Maria Chiara, Khanna, Nina, Barać, Aleksandra, Eisa, Noha, Di Blasi, Roberta, Liévin, Raphaël, Miranda-Castillo, Carolina, Bahr, Nathan C., Lamure, Sylvain, Papa, Mario Virgilio, Yahya, Ayel, Aujayeb, Avinash, Novák, Jan, Erben, Nurettin, Fernández-Galán, María, Ribera-Santa Susana, José-María, Rinaldi, Ikhwan, Fazzi, Rita, Piedimonte, Monica, Duléry, Rémy, Gonzaga, Yung, Soto-Silva, Andrés, Sapienza, Giuseppe, Serris, Alexandra, Drgoňa, Ľuboš, Groh, Ana, Serrano, Laura, Gavriilaki, Eleni, Tragiannidis, Athanasios, Prattes, Juergen, Coppola, Nicola, Otašević, Vladimir, Mladenović, Miloš, Mitrović, Mirjana, Mišković, Bojana, Jindra, Pavel, Zompi, Sofia, Sacchi, Maria Vittoria, Krekeler, Carolin, Shumilov, Evgenii, Infante, Maria Stefania, García-Bordallo, Daniel, Çolak, Gökçe Melis, Mayer, Jiří, Nygaard, Marietta, Hanáková, Michaela, Ráčil, Zdeněk, Quattrone, Martina, Bonanni, Matteo, Koehler, Philipp, Rahimli, Laman, Cornely, Oliver A., and Pagano, Livio

Published
2024
Full Text
View/download PDF

26. Real-time Neural Radiance Caching for Path Tracing

Author

Müller, Thomas, Rousselle, Fabrice, Novák, Jan, and Keller, Alexander

Subjects
Computer Science - Graphics, Computer Science - Machine Learning
Abstract

We present a real-time neural radiance caching method for path-traced global illumination. Our system is designed to handle fully dynamic scenes, and makes no assumptions about the lighting, geometry, and materials. The data-driven nature of our approach sidesteps many difficulties of caching algorithms, such as locating, interpolating, and updating cache points. Since pretraining neural networks to handle novel, dynamic scenes is a formidable generalization challenge, we do away with pretraining and instead achieve generalization via adaptation, i.e. we opt for training the radiance cache while rendering. We employ self-training to provide low-noise training targets and simulate infinite-bounce transport by merely iterating few-bounce training updates. The updates and cache queries incur a mild overhead -- about 2.6ms on full HD resolution -- thanks to a streaming implementation of the neural network that fully exploits modern hardware. We demonstrate significant noise reduction at the cost of little induced bias, and report state-of-the-art, real-time performance on a number of challenging scenarios., Comment: To appear at SIGGRAPH 2021. 16 pages, 16 figures

Published
2021
Full Text
View/download PDF

27. An unbiased ray-marching transmittance estimator

Author

Kettunen, Markus, d'Eon, Eugene, Pantaleoni, Jacopo, and Novak, Jan

Subjects
Computer Science - Graphics
Abstract

We present an in-depth analysis of the sources of variance in state-of-the-art unbiased volumetric transmittance estimators, and propose several new methods for improving their efficiency. These combine to produce a single estimator that is universally optimal relative to prior work, with up to several orders of magnitude lower variance at the same cost, and has zero variance for any ray with non-varying extinction. We first reduce the variance of truncated power-series estimators using a novel efficient application of U-statistics. We then greatly reduce the average expansion order of the power series and redistribute density evaluations to filter the optical depth estimates with an equidistant sampling comb. Combined with the use of an online control variate built from a sampled mean density estimate, the resulting estimator effectively performs ray marching most of the time while using rarely-sampled higher order terms to correct the bias., Comment: 20 pages

Published
2021
Full Text
View/download PDF

28. Venetoclax combinations delay the time to deterioration of HRQoL in unfit patients with acute myeloid leukemia

Author

Pratz, Keith W, Panayiotidis, Panayiotis, Recher, Christian, Wei, Xudong, Jonas, Brian A, Montesinos, Pau, Ivanov, Vladimir, Schuh, Andre C, DiNardo, Courtney D, Novak, Jan, Pejsa, Vlatko, Stevens, Don, Yeh, Su-Peng, Kim, Inho, Turgut, Mehmet, Fracchiolla, Nicola, Yamamoto, Kazuhito, Ofran, Yishai, Wei, Andrew H, Bui, Cat N, Benjamin, Katy, Kamalakar, Rajesh, Potluri, Jalaja, Mendes, Wellington, Devine, Jacob, and Fiedler, Walter

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Oncology and Carcinogenesis, Clinical Research, Rare Diseases, Cancer, Antineoplastic Combined Chemotherapy Protocols, Bridged Bicyclo Compounds, Heterocyclic, Cytarabine, Fatigue, Humans, Leukemia, Myeloid, Acute, Quality of Life, Sulfonamides, Cardiorespiratory Medicine and Haematology, Cardiovascular medicine and haematology, Oncology and carcinogenesis
Abstract

Phase 3 trials Viale-A and Viale-C evaluated health-related quality of life (HRQoL) in patients with AML unfit for intensive chemotherapy who received venetoclax (VEN) + (AZA) (Viale-A) or low-dose cytarabine (LDAC) (Viale-C) or placebo (PBO) + AZA or LDAC. Patient-reported outcomes included: EORTC QLQ-C30 global health status (GHS/QoL) and physical functioning (PF), PROMIS Cancer Fatigue Short Form 7a (Fatigue), and EQ-5D-5L health status visual analog scale (HS-VAS). Time to deterioration (TTD), defined as worsening from baseline in meaningful change thresholds (MCT) of ≥10, 5, or 7 points for GHS/QoL or PF, fatigue, and HS-VAS, respectively, was assessed; differences between groups were analyzed using Kaplan-Meier and unadjusted log-rank analyses. VEN + AZA vs PBO + AZA patients had longer TTD in GHS/QoL (P = 0.066) and fatigue (P = 0.189), and significantly longer TTD in PF (P = 0.028) and HS-VAS (P MCT in GHS/QoL. Overall, VEN may positively impact HRQoL in patients with AML ineligible for intensive chemotherapy, leading to longer preservation of functioning and overall health status.

Published
2022

30. Genome-wide association analyses define pathogenic signaling pathways and prioritize drug targets for IgA nephropathy

Author

Kiryluk, Krzysztof, Sanchez-Rodriguez, Elena, Zhou, Xu-Jie, Zanoni, Francesca, Liu, Lili, Mladkova, Nikol, Khan, Atlas, Marasa, Maddalena, Zhang, Jun Y., Balderes, Olivia, Sanna-Cherchi, Simone, Bomback, Andrew S., Canetta, Pietro A., Appel, Gerald B., Radhakrishnan, Jai, Trimarchi, Hernan, Sprangers, Ben, Cattran, Daniel C., Reich, Heather, Pei, York, Ravani, Pietro, Galesic, Kresimir, Maixnerova, Dita, Tesar, Vladimir, Stengel, Benedicte, Metzger, Marie, Canaud, Guillaume, Maillard, Nicolas, Berthoux, Francois, Berthelot, Laureline, Pillebout, Evangeline, Monteiro, Renato, Nelson, Raoul, Wyatt, Robert J., Smoyer, William, Mahan, John, Samhar, Al-Akash, Hidalgo, Guillermo, Quiroga, Alejandro, Weng, Patricia, Sreedharan, Raji, Selewski, David, Davis, Keefe, Kallash, Mahmoud, Vasylyeva, Tetyana L., Rheault, Michelle, Chishti, Aftab, Ranch, Daniel, Wenderfer, Scott E., Samsonov, Dmitry, Claes, Donna J., Akchurin, Oleh, Goumenos, Dimitrios, Stangou, Maria, Nagy, Judit, Kovacs, Tibor, Fiaccadori, Enrico, Amoroso, Antonio, Barlassina, Cristina, Cusi, Daniele, Del Vecchio, Lucia, Battaglia, Giovanni Giorgio, Bodria, Monica, Boer, Emanuela, Bono, Luisa, Boscutti, Giuliano, Caridi, Gianluca, Lugani, Francesca, Ghiggeri, GianMarco, Coppo, Rosanna, Peruzzi, Licia, Esposito, Vittoria, Esposito, Ciro, Feriozzi, Sandro, Polci, Rosaria, Frasca, Giovanni, Galliani, Marco, Garozzo, Maurizio, Mitrotti, Adele, Gesualdo, Loreto, Granata, Simona, Zaza, Gianluigi, Londrino, Francesco, Magistroni, Riccardo, Pisani, Isabella, Magnano, Andrea, Marcantoni, Carmelita, Messa, Piergiorgio, Mignani, Renzo, Pani, Antonello, Ponticelli, Claudio, Roccatello, Dario, Salvadori, Maurizio, Salvi, Erica, Santoro, Domenico, Gembillo, Guido, Savoldi, Silvana, Spotti, Donatella, Zamboli, Pasquale, Izzi, Claudia, Alberici, Federico, Delbarba, Elisa, Florczak, Michał, Krata, Natalia, Mucha, Krzysztof, Pączek, Leszek, Niemczyk, Stanisław, Moszczuk, Barbara, Pańczyk-Tomaszewska, Malgorzata, Mizerska-Wasiak, Malgorzata, Perkowska-Ptasińska, Agnieszka, Bączkowska, Teresa, Durlik, Magdalena, Pawlaczyk, Krzysztof, Sikora, Przemyslaw, Zaniew, Marcin, Kaminska, Dorota, Krajewska, Magdalena, Kuzmiuk-Glembin, Izabella, Heleniak, Zbigniew, Bullo-Piontecka, Barbara, Liberek, Tomasz, Dębska-Slizien, Alicja, Hryszko, Tomasz, Materna-Kiryluk, Anna, Miklaszewska, Monika, Szczepańska, Maria, Dyga, Katarzyna, Machura, Edyta, Siniewicz-Luzeńczyk, Katarzyna, Pawlak-Bratkowska, Monika, Tkaczyk, Marcin, Runowski, Dariusz, Kwella, Norbert, Drożdż, Dorota, Habura, Ireneusz, Kronenberg, Florian, Prikhodina, Larisa, van Heel, David, Fontaine, Bertrand, Cotsapas, Chris, Wijmenga, Cisca, Franke, Andre, Annese, Vito, Gregersen, Peter K., Parameswaran, Sreeja, Weirauch, Matthew, Kottyan, Leah, Harley, John B., Suzuki, Hitoshi, Narita, Ichiei, Goto, Shin, Lee, Hajeong, Kim, Dong Ki, Kim, Yon Su, Park, Jin-Ho, Cho, BeLong, Choi, Murim, Van Wijk, Ans, Huerta, Ana, Ars, Elisabet, Ballarin, Jose, Lundberg, Sigrid, Vogt, Bruno, Mani, Laila-Yasmin, Caliskan, Yasar, Barratt, Jonathan, Abeygunaratne, Thilini, Kalra, Philip A., Gale, Daniel P., Panzer, Ulf, Rauen, Thomas, Floege, Jürgen, Schlosser, Pascal, Ekici, Arif B., Eckardt, Kai-Uwe, Chen, Nan, Xie, Jingyuan, Lifton, Richard P., Loos, Ruth J. F., Kenny, Eimear E., Ionita-Laza, Iuliana, Köttgen, Anna, Julian, Bruce A., Novak, Jan, Scolari, Francesco, Zhang, Hong, and Gharavi, Ali G.

Published
2023
Full Text
View/download PDF

32. Neural Control Variates

Author

Müller, Thomas, Rousselle, Fabrice, Novák, Jan, and Keller, Alexander

Subjects
Computer Science - Machine Learning, Computer Science - Graphics, Statistics - Machine Learning
Abstract

We propose neural control variates (NCV) for unbiased variance reduction in parametric Monte Carlo integration. So far, the core challenge of applying the method of control variates has been finding a good approximation of the integrand that is cheap to integrate. We show that a set of neural networks can face that challenge: a normalizing flow that approximates the shape of the integrand and another neural network that infers the solution of the integral equation. We also propose to leverage a neural importance sampler to estimate the difference between the original integrand and the learned control variate. To optimize the resulting parametric estimator, we derive a theoretically optimal, variance-minimizing loss function, and propose an alternative, composite loss for stable online training in practice. When applied to light transport simulation, neural control variates are capable of matching the state-of-the-art performance of other unbiased approaches, while providing means to develop more performant, practical solutions. Specifically, we show that the learned light-field approximation is of sufficient quality for high-order bounces, allowing us to omit the error correction and thereby dramatically reduce the noise at the cost of negligible visible bias., Comment: To appear at SIGGRAPH Asia 2020. Updated with better loss function, leading to better results. 19 pages, 14 figures

Published
2020

33. Combining multi-site Magnetic Resonance Imaging with machine learning predicts survival in paediatric brain tumours

Author

Grist, James T., Withey, Stephanie, Bennett, Christopher, Rose, Heather E. L., MacPherson, Lesley, Oates, Adam, Powell, Stephen, Novak, Jan, Abernethy, Laurence, Pizer, Barry, Bailey, Simon, Clifford, Steven C., Mitra, Dipayan, Arvanitis, Theodoros N., Auer, Dorothee P., Avula, Shivaram, Grundy, Richard, and Peet, Andrew C

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Background Brain tumours represent the highest cause of mortality in the paediatric oncological population. Diagnosis is commonly performed with magnetic resonance imaging and spectroscopy. Survival biomarkers are challenging to identify due to the relatively low numbers of individual tumour types, especially for rare tumour types such as atypical rhabdoid tumours. Methods 69 children with biopsy-confirmed brain tumours were recruited into this study. All participants had both perfusion and diffusion weighted imaging performed at diagnosis. Data were processed using conventional methods, and a Bayesian survival analysis performed. Unsupervised and supervised machine learning were performed with the survival features, to determine novel sub-groups related to survival. Sub-group analysis was undertaken to understand differences in imaging features, which pertain to survival. Findings Survival analysis showed that a combination of diffusion and perfusion imaging were able to determine two novel sub-groups of brain tumours with different survival characteristics (p <0.01), which were subsequently classified with high accuracy (98%) by a neural network. Further analysis of high-grade tumours showed a marked difference in survival (p=0.029) between the two clusters with high risk and low risk imaging features. Interpretation This study has developed a novel model of survival for paediatric brain tumours, with an implementation ready for integration into clinical practice. Results show that tumour perfusion plays a key role in determining survival in brain tumours and should be considered as a high priority for future imaging protocols.

Published
2020

35. Author Correction: Genetic regulation of serum IgA levels and susceptibility to common immune, infectious, kidney, and cardio-metabolic traits

Author

Liu, Lili, Khan, Atlas, Sanchez-Rodriguez, Elena, Zanoni, Francesca, Li, Yifu, Steers, Nicholas, Balderes, Olivia, Zhang, Junying, Krithivasan, Priya, LeDesma, Robert A., Fischman, Clara, Hebbring, Scott J., Harley, John B., Moncrieffe, Halima, Kottyan, Leah C., Namjou-Khales, Bahram, Walunas, Theresa L., Knevel, Rachel, Raychaudhuri, Soumya, Karlson, Elizabeth W., Denny, Joshua C., Stanaway, Ian B., Crosslin, David, Rauen, Thomas, Floege, Jürgen, Eitner, Frank, Moldoveanu, Zina, Reily, Colin, Knoppova, Barbora, Hall, Stacy, Sheff, Justin T., Julian, Bruce A., Wyatt, Robert J., Suzuki, Hitoshi, Xie, Jingyuan, Chen, Nan, Zhou, Xujie, Zhang, Hong, Hammarström, Lennart, Viktorin, Alexander, Magnusson, Patrik K. E., Shang, Ning, Hripcsak, George, Weng, Chunhua, Rundek, Tatjana, Elkind, Mitchell S. V., Oelsner, Elizabeth C., Barr, R. Graham, Ionita-Laza, Iuliana, Novak, Jan, Gharavi, Ali G., and Kiryluk, Krzysztof

Published
2023
Full Text
View/download PDF

36. mHealth intervention delivered in general practice to increase physical activity and reduce sedentary behaviour of patients with prediabetes and type 2 diabetes (ENERGISED): rationale and study protocol for a pragmatic randomised controlled trial

Author

Vetrovsky, Tomas, Kral, Norbert, Pfeiferova, Marketa, Kuhnova, Jitka, Novak, Jan, Wahlich, Charlotte, Jaklova, Andrea, Jurkova, Katerina, Janek, Michael, Omcirk, Dan, Capek, Vaclav, Maes, Iris, Steffl, Michal, Ussher, Michael, Tufano, James J., Elavsky, Steriani, Van Dyck, Delfien, Cimler, Richard, Yates, Tom, Harris, Tess, and Seifert, Bohumil

Published
2023
Full Text
View/download PDF

37. Association of COVID-19 Versus COVID-19 Vaccination With Kidney Function and Disease Activity in Primary Glomerular Disease: A Report of the Cure Glomerulonephropathy Study

Author

Ahn, Wooin, Appel, Gerald, Appelbaum, Paul, Babayev, Revekka, Chan, Brenda, D’Agati, Vivette Denise, Dogra, Samitri, Fernandez, Hilda, Gharavi, Ali, Hines, William, Husain, Syed Ali, Jain, Namrata, Kiryluk, Krzysztof, Lin, Fangming, Marasa, Maddalena, Markowitz, Glen, Rasouly, Hila Milo, Mohan, Sumit, Mongera, Nicola, Nestor, Jordan, Nickolas, Thomas, Radhakrishnan, Jai, Rao, Maya, Sanna-Cherchi, Simone, Shirazian, Shayan, Stokes, Michael Barry, Uy, Natalie, Valeri, Anthony, Vena, Natalie, Foroncewicz, Bartosz, Moszczuk, Barbara, Mucha, Krzysztof, Perkowska-Ptasińska, Agnieszka, Ghiggeri, Gian Marco, Lugani, Francesca, Ambruzs, Josephine, Liapis, Helen, Baracco, Rossana, Jain, Amrish, Isa Ashoor, Aviles, Diego, Srivastava, Tarak, Ahn, Sun-Young, Devarajan, Prasad, Erkan, Elif, Claes, Donna, Stone, Hillarey, Mason, Sherene, Gbadegesin, Rasheed, Gomez-Mendez, Liliana, Yin, Hong (Julie), Cai, Yi, Jens, Goebel, Steinke, Julia, Weaver, Donald, Lane, Jerome, Cramer, Carl, Pan, Cindy, Paloian, Neil, Sreedharan, Rajasree, Selewski, David, Twombley, Katherine, Bowers, Corinna, Dreher, Mary, Kallash, Mahmoud, Mahan, John, Sharpe, Samantha, Al-Uzri, Amira, Iragorri, Sandra, Belsha, Craig, Alge, Joseph, Braun, Michael, Gomez, A.C., Wenderfer, Scott, Vasylyeva, Tetyana, Feig, Daniel, Fuentes, Gabriel Cara, Hannah, Melisha, Nester, Carla, Chishti, Aftab, Klein, Jon, Katsoufis, Chryso, Seeherunvong, Wacharee, Wong, Craig, Mathews, Nisha, Barcia, John, Swiatecka-Urban, Agnes, Bartosh, Sharon, Hunley, Tracy, Dharnidharka, Vikas, Gaut, Joseph, Laurin, Louis-Philippe, Royal, Virginie, Achanti, Anand, Budisavljevic, Milos, Self, Sally, Ghossein, Cybele, Peleg, Yonatan, Wadhwani, Shikha, Almaani, Salem, Ayoub, Isabelle, Nadasdy, Tibor, Parikh, Samir, Rovin, Brad, Chang, Anthony, Fatima, Huma, Julian, Bruce, Novak, Jan, Renfrow, Matthew, Rizk, Dana, Chen, Dhruti, Derebail, Vimal, Falk, Ronald, Gibson, Keisha, Hogan, Susan, Jain, Koyal, Jennette, J. Charles, Mottl, Amy, Poulton, Caroline, Saha, Manish Kanti, Fogo, Agnes, Sanghani, Neil, Kidd, Jason, Muthusamy, Selvaraj, Hou, Jean, Lemley, Kevin, Mika, Warren, Russo, Pierre, Denburg, Michelle, Kogon, Amy, Meyers, Kevin, Pradhan, Madhura, O’Toole, John, Sedor, John, Sethna, Christine, Vento, Suzanne, Atta, Mohamed, Bagnasco, Serena, Neu, Alicia, Sperati, John, Adler, Sharon, Dai, Tiane, Dukkipati, Ram, Fervenza, Fernando, Sethi, Sanjeev, Kaskel, Frederick, Brathwaite, Kaye, Reidy, Kimberly, Weisstuch, Joseph, Wu, Ming, Zhdanova, Olga, Heymann, Jurgen, Kopp, Jeffrey, Waldman, Meryl, Winkler, Cheryl, Krissberg, Jill, Lafayette, Richard, Fahmeedah, Kamal, Talley, Elizabeth, Hladunewich, Michelle, Parekh, Rulan, Avila-Casado, Carmen, Cattran, Daniel, Heather, Reich, Boll, Philip, Drexler, Yelena, Fornoni, Alessia, Blazius, Brooke, Hodgin, Jeffrey, Oliverio, Andrea, Hogan, Jon, Palmer, Matthew, Abromovitz, Blaise, Mortiz, Michael, Alpers, Charles, Jefferson, J. Ashley, Brown, Elizabeth, Sambandam, Kamal, Roehm, Bethany, Graff, John, Gillespie, Brenda, Kretzler, Matthias, Nast, Cynthia, Barisoni, Laura, Guay-Woodford, Lisa M., Wang, Chia-shi, Glenn, Dorey A., Helmuth, Margaret, Smith, Abigail R., Bomback, Andrew S., Canetta, Pietro A., Coppock, Gaia M., Khalid, Myda, Tuttle, Katherine R., Bou-Matar, Raed, Greenbaum, Larry A., Robinson, Bruce M., Holzman, Lawrence B., Smoyer, William E., Rheault, Michelle N., Gipson, Debbie, and Mariani, Laura H.

Published
2024
Full Text
View/download PDF

38. Age, successive waves, immunization, and mortality in elderly COVID-19 hematological patients: EPICOVIDEHA findings

Author

MARQUES DE ALMEIDA, Joyce, HERNÁNDEZ-RIVAS, José-Ángel, GUIDETTI, Anna, FINIZIO, Olimpia, STOJANOSKI, Zlate, CVETANOSKI, Milche, MELETIADIS, Joseph, DE JONGE, Nick, ANTIĆ, Darko, ALI, Natasha, TISI, Maria Chiara, SERRANO, Laura, PLANTEFEVE, Gaëtan, KHANNA, Nina, HOENIGL, Martin, ČERŇAN, Martin, MIRANDA-CASTILLO, Carolina, FERNÁNDEZ-GALÁN, María, SERRIS, Alexandra, ERBEN, Nurettin, DULÉRY, Rémy, AUJAYEB, Avinash, PAPA, Mario Virgilio, NOVÁK, Jan, DELIA, Mario, SAPIENZA, Giuseppe, REIZINE, Florian, OMRANI, Ali S., DI BLASI, Roberta, LAMURE, Sylvain, DRGOŇA, Ľuboš, COPPOLA, Nicola, BATINIĆ, Josip, AL-KHABORI, Murtadha, RIBERA-SANTA SUSANA, José-María, PIEDIMONTE, Monica, LOUREIRO-AMIGO, Jorge, FOUQUET, Guillemette, FAZZI, Rita, DANION, François, SCHUBERT, Jörg, HOELL-NEUGEBAUER, Baerbel, BAHR, Nathan C., YAHIA, Ayel Omar, TORRES-ATIENZA, Ana, RINALDI, Ikhwan, POPOVA, Marina, OMMEN, Hans-Beier, MITRA, Maria Enza, MIKULSKA, Malgorzata, LACEJ, Ira, KHOSTELIDI, Sofya, WIN, Sein, VINH, Donald, SALEH, Modar, PRATTES, Juergen, JINDRA, Pavel, GUOLO, Fabio, DELLA PEPA, Roberta, CHELYSHEVA, Ekaterina, ZDZIARSKI, Przemyslaw, WAI-MAN, Vivien, SOTO-SILVA, Andrés, ORTH, Hans Martin, MALAK, Sandra, LORENZO DE LA PEÑA, Lisset, KOLDITZ, Martin, Shan KHO, Chi, HEATH, Christopher H., GROH, Ana, GAVRIILAKI, Eleni, FUNG, Monica, EGGER, Matthias, DE KORT, Elizabeth, DE CABO, Erik, CUSHION, Tania, CHOWDHURY, Fazle Rabbi, CEESAY, M. Mansour, BREHON, Mathias, VARRICCHIO, Gina, TAFURI, Agostino, JIMÉNEZ-LORENZO, María-Josefa, KLIMKO, Nikolai, TSIRIGOTIS, Panagiotis, ANTONIADOU, Anastasia, VEHRESCHILD, Maria, Rossi, Giuseppe, Salmanton-García, Jon, Cattaneo, Chiara, Marchesi, Francesco, Dávila-Valls, Julio, Martín-Pérez, Sonia, Itri, Federico, López-García, Alberto, Glenthøj, Andreas, Gomes da Silva, Maria, Besson, Caroline, Marchetti, Monia, Weinbergerová, Barbora, Jaksic, Ozren, Jiménez, Moraima, Bilgin, Yavuz M., Van Doesum, Jaap, Farina, Francesca, Žák, Pavel, Verga, Luisa, Collins, Graham P., Bonuomo, Valentina, Van Praet, Jens, Nucci, Marcio, Meers, Stef, Espigado, Ildefonso, Fracchiolla, Nicola S., Valković, Toni, Poulsen, Christian Bjørn, Čolović, Natasha, Dragonetti, Giulia, Ledoux, Marie-Pierre, Tascini, Carlo, Buquicchio, Caterina, Blennow, Ola, Passamonti, Francesco, Machado, Marina, Labrador, Jorge, Duarte, Rafael F., Schönlein, Martin, Prezioso, Lucia, Falces-Romero, Iker, Kulasekararaj, Austin, Garcia-Vidal, Carolina, Fernández, Noemí, Abu-Zeinah, Ghaith, Ormazabal-Vélez, Irati, Adžić-Vukičević, Tatjana, Piukovics, Klára, Stoma, Igor, Cuccaro, Annarosa, Magliano, Gabriele, Szotkowski, Tomáš, González-López, Tomás-José, El-Ashwah, Shaimaa, Bergantim, Rui, Sili, Uluhan, Maertens, Johan, Demirkan, Fatih, De Ramón, Cristina, Petzer, Verena, Del Principe, Maria Ilaria, Navrátil, Milan, Dargenio, Michelina, Seval, Guldane Cengiz, Samarkos, Michail, Ráčil, Zdeněk, Pinczés, László Imre, Lahmer, Tobias, Busca, Alessandro, Méndez, Gustavo-Adolfo, Vena, Antonio, Biernat, Monika M., Merelli, Maria, Calbacho, Maria, Barać, Aleksandra, Bavastro, Martina, Limongelli, Alessandro, Ilhan, Osman, Wolf, Dominik, Çolak, Gökçe Melis, García-Sanz, Ramón, Emarah, Ziad, Mišković, Bojana, Gräfe, Stefanie K., Mladenović, Miloš, Aiello, Tommaso Francesco, Núñez-Martín-Buitrago, Lucía, Nordlander, Anna, Arellano, Elena, Zambrotta, Giovanni Paolo Maria, Ammatuna, Emanuele, Cabirta, Alba, Sacchi, Maria Vittoria, Nunes Rodrigues, Raquel, Hersby, Ditte Stampe, Hanakova, Michaela, Rahimli, Laman, Cordoba, Raul, Cornely, Oliver A., and Pagano, Livio

Published
2023
Full Text
View/download PDF

39. Biological factors and self-perception of stress in relation to freeze-like response in humans

Author

Vít, Michal, Kučera, Jan, Lenárt, Peter, Novák, Jan, Zlámal, Filip, Reguli, Zdenko, Bugala, Martin, Čihounková, Jitka, Přecechtěl, Pavel, Malčík, Vojtěch, Vojtíšek, Tomáš, Kučerová, Jana Fialová, Eclerová, Veronika, Tomandlová, Marie, Šíp, Radek, Ráčková, Lucie, Grulichová, Markéta, Tomandl, Josef, and Bienertová-Vašků, Julie

Published
2023
Full Text
View/download PDF

41. Guadecitabine vs treatment choice in newly diagnosed acute myeloid leukemia: a global phase 3 randomized study

Author

Fenaux, Pierre, Gobbi, Marco, Kropf, Patricia L., Issa, Jean-Pierre J., Roboz, Gail J., Mayer, Jiri, Krauter, Jürgen, Robak, Tadeusz, Kantarjian, Hagop, Novak, Jan, Jedrzejczak, Wieslaw. W., Thomas, Xavier, Ojeda-Uribe, Mario, Miyazaki, Yasushi, Min, Yoo Hong, Yeh, Su-Peng, Brandwein, Joseph, Gercheva-Kyuchukova, Liana, Demeter, Judit, Griffiths, Elizabeth, Yee, Karen, Döhner, Konstanze, Hao, Yong, Keer, Harold, Azab, Mohammad, and Döhner, Hartmut

Published
2023
Full Text
View/download PDF

42. Distinguishing between paediatric brain tumour types using multi-parametric magnetic resonance imaging and machine learning: a multi-site study

Author

Grist, James T., Withey, Stephanie, MacPherson, Lesley, Oates, Adam, Powell, Stephen, Novak, Jan, Abernethy, Laurence, Pizer, Barry, Grundy, Richard, Bailey, Simon, Mitra, Dipayan, Arvanitis, Theodoros N., Auer, Dorothee P., Avula, Shivaram, and Peet, Andrew C

Subjects
Physics - Medical Physics, Electrical Engineering and Systems Science - Image and Video Processing, Quantitative Biology - Quantitative Methods
Abstract

The imaging and subsequent accurate diagnosis of paediatric brain tumours presents a radiological challenge, with magnetic resonance imaging playing a key role in providing tumour specific imaging information. Diffusion weighted and perfusion imaging are commonly used to aid the non invasive diagnosis of paediatric brain tumours, but are usually evaluated by expert qualitative review. Quantitative studies are mainly single centre and single modality. The aim of this work was to combine multi centre diffusion and perfusion imaging, with machine learning, to develop machine learning based classifiers to discriminate between three common paediatric tumour types. The results show that diffusion and perfusion weighted imaging of both the tumour and whole brain provide significant features which differ between tumour types, and that combining these features gives the optimal machine learning classifier with greater than 80 percent predictive precision. This work represents a step forward to aid in the non invasive diagnosis of paediatric brain tumours, using advanced clinical imaging., Comment: 22 pages, 7 figures and tables

Published
2019

43. Soluble prefusion-closed HIV-envelope trimers with glycan-covered bases

Author

Olia, Adam S., Cheng, Cheng, Zhou, Tongqing, Biju, Andrea, Harris, Darcy R., Changela, Anita, Duan, Hongying, Ivleva, Vera B., Kong, Wing-Pui, Ou, Li, Rawi, Reda, Tsybovsky, Yaroslav, Van Wazer, David J., Corrigan, Angela R., Gonelli, Christopher A., Lee, Myungjin, McKee, Krisha, Narpala, Sandeep, O’Dell, Sijy, Parchment, Danealle K., Stancofski, Erik-Stephane D., Stephens, Tyler, Tan, Ivy, Teng, I-Ting, Wang, Shuishu, Wei, Qing, Yang, Yongping, Yang, Zhengrong, Zhang, Baoshan, Novak, Jan, Renfrow, Matthew B., Doria-Rose, Nicole A., Koup, Richard A., McDermott, Adrian B., Gall, Jason G., Lei, Q. Paula, Mascola, John R., and Kwong, Peter D.

Published
2023
Full Text
View/download PDF

45. Designing modular 3D printed reinforcement of wound composite hollow beams with semidefinite programming

Author

Tyburec, Marek, Zeman, Jan, Novák, Jan, Lepš, Matěj, Plachý, Tomáš, and Poul, Robin

Subjects
Physics - Applied Physics
Abstract

Fueled by their excellent stiffness-to-weight ratio and the availability of mature manufacturing technologies, filament wound carbon fiber reinforced polymers represent ideal materials for thin-walled laminate structures. However, their strong anisotropy reduces structural resistance to wall instabilities under shear and buckling. Increasing laminate thickness degrades weight and structural efficiencies and the application of a dense internal core is often uneconomical and labor-intensive. In this contribution, we introduce a convex linear semidefinite programming formulation for truss topology optimization to design an efficient non-uniform lattice-like internal structure. The internal structure not only reduces the effect of wall instabilities, mirrored in the increase of the fundamental free-vibration eigenfrequency, but also keeps weight low, secures manufacturability using conventional three-dimensional printers, and withstands the loads induced during the production process. We showcase a fully-automatic procedure in detail for the design, prototype manufacturing, and verification of a simply-supported composite machine tool component, including validation with roving hammer tests. The results confirm that the 3D-printed optimized internal structure almost doubles the fundamental free-vibration eigenfrequency, allowing to increase working frequency of the machine tool, even though the ratio between elastic properties of the carbon composite and the ABS polymer used for 3D printing exceeds two orders of magnitude., Comment: 13 pages, 13 figures

Published
2019
Full Text
View/download PDF

46. Level-set based design of Wang tiles for modelling complex microstructures

Author

Doškář, Martin, Zeman, Jan, Rypl, Daniel, and Novák, Jan

Subjects
Computer Science - Computational Geometry, Condensed Matter - Materials Science
Abstract

Microstructural geometry plays a critical role in the response of heterogeneous materials. Consequently, methods for generating microstructural samples are increasingly crucial to advanced numerical analyses. We extend Sonon et al.'s unified framework, developed originally for generating particulate and foam-like microstructural geometries of Periodic Unit Cells, to non-periodic microstructural representations based on the formalism of Wang tiles. This formalism has been recently proposed in order to generalize the Periodic Unit Cell approach, enabling a fast synthesis of arbitrarily large, stochastic microstructural samples from a handful of domains with predefined compatibility constraints. However, a robust procedure capable of designing complex, three-dimensional, foam-like and cellular morphologies of Wang tiles has not yet been proposed. This contribution fills the gap by significantly broadening the applicability of the tiling concept. Since the original Sonon et al.'s framework builds on a random sequential addition of particles enhanced with an implicit representation of particle boundaries by the level-set field, we first devise an analysis based on a connectivity graph of a tile set, resolving the question where a particle should be copied when it intersects a tile boundary. Next, we introduce several modifications to the original algorithm that are necessary to ensure microstructural compatibility in the generalized periodicity setting of Wang tiles. Having established a universal procedure for generating tile morphologies, we compare strictly aperiodic and stochastic sets with the same cardinality in terms of reducing the artificial periodicity in reconstructed microstructural samples. We demonstrate the superiority of the vertex-defined tile sets for two-dimensional problems and illustrate the capabilities of the algorithm with two- and three-dimensional examples., Comment: 16 pages, 16 figures. Abstract has been shortened to match the arXiv.org's limit of 1920 characters

Published
2019
Full Text
View/download PDF

47. Age of Onset and Disease Course in Biopsy-Proven Minimal Change Disease: An Analysis From the Cure Glomerulonephropathy Network

Author

Ahn, Wooin, Appel, Gerald, Appelbaum, Paul, Babayev, Revekka, Bomback, Andrew, Chan, Brenda, D’Agati, Vivette Denise, Dogra, Samitri, Fernandez, Hilda, Gharavi, Ali, Hines, William, Husain, Syed Ali, Jain, Namrata, Kiryluk, Krzysztof, Lin, Fangming, Marasa, Maddalena, Markowitz, Glen, Rasouly, Hila Milo, Mohan, Sumit, Mongera, Nicola, Nestor, Jordan, Nickolas, Thomas, Radhakrishnan, Jai, Rao, Maya, Sanna-Cherchi, Simone, Shirazian, Shayan, Stokes, Michael Barry, Uy, Natalie, Valeri, Anthony, Vena, Natalie, Foroncewicz, Bartosz, Moszczuk, Barbara, Perkowska-Ptasińska, Agnieszka, Ghiggeri, Gian Marco, Lugani, Francesca, Ambruzs, Josephine, Liapis, Helen, Baracco, Rossana, Jain, Amrish, Ashoor, Isa, Aviles, Diego, Ahn, Sun-Young, Devarajan, Prasad, Erkan, Elif, Claes, Donna, Stone, Hillarey, Mason, Sherene, Gomez-Mendez, Liliana, Wang, Chia-shi, Yin, Hong, Cai, Yi, Jens, Goebel, Steinke, Julia, Weaver, Donald, Lane, Jerome, Cramer, Carl, Pan, Cindy, Paloian, Neil, Sreedharan, Rajasree, Bowers, Corinna, Dreher, Mary, Mahan, John, Sharpe, Samantha, Smoyer, William, Al-Uzri, Amira, Iragorri, Sandra, Khalid, Myda, Belsha, Craig, Alge, Joseph, Braun, Michael, Gomez, A.C., Wenderfer, Scott, Vasylyeva, Tetyana, Feig, Daniel, Fuentes, Gabriel Cara, Hannah, Melisha, Nester, Carla, Klein, Jon, Katsoufis, Chryso, Seeherunvong, Wacharee, Rheault, Michelle, Wong, Craig, Mathews, Nisha, Barcia, John, Swiatecka-Urban, Agnes, Bartosh, Sharon, Dharnidharka, Vikas, Gaut, Joseph, Laurin, Louis-Philippe, Royal, Virginie, Achanti, Anand, Budisavljevic, Milos, Self, Sally, Ghossein, Cybele, Peleg, Yonatan, Wadhwani, Shikha, Almaani, Salem, Nadasdy, Tibor, Samir, Parikh, Rovin, Brad, Chang, Anthony, Fatima, Huma, Julian, Bruce, Novak, Jan, Renfrow, Matthew, Rizk, Dana, Derebail, Vimal, Falk, Ronald, Gibson, Keisha, Glenn, Dorey, Hogan, Susan, Jain, Koyal, Jennette, J. Charles, Poulton, Caroline, Saha, Manish Kanti, Fogo, Agnes, Sanghani, Neil, Muthusamy, Selvaraj, Schelling, Jeffrey, Hou, Jean, Lemley, Kevin, Mika, Warren, Russo, Pierre, Denburg, Michelle, Kogon, Amy, Meyers, Kevin, Pradhan, Madhura, Matar, Raed Bou, O’Toole, John, Sedor, John, Sethna, Christine, Vento, Suzanne, Atta, Mohamed, Bagnasco, Serena, Neu, Alicia, Adler, Sharon, Dai, Tiane, Dukkipati, Ram, Fervenza, Fernando, Sethi, Sanjeev, Kaskel, Frederick, Brathwaite, Kaye, Weisstuch, Joseph, Wu, Ming, Zhdanova, Olga, Heymann, Jurgen, Waldman, Meryl, Winkler, Cheryl, Tuttle, Katherine, Krissberg, Jill, Lafayette, Richard, Fahmeedah, Kamal, Talley, Elizabeth, Hladunewich, Michelle, Avila-Casado, Carmen, Cattran, Daniel, Heather, Reich, Boll, Philip, Drexler, Yelena, Fornoni, Alessia, Gipson, Patrick, Hodgin, Jeffrey, Oliverio, Andrea, Hogan, Jon, Holzman, Lawrence, Palmer, Matthew, Coppock, Gaia, Abromovitz, Blaise, Mortiz, Michael, Alpers, Charles, Jefferson, J. Ashley, Brown, Elizabeth, Sambandam, Kamal, Roehm, Bethany, Robinson, Bruce, Nast, Cynthia, Barisoni, Laura, Kretzler, Matthias, Mariani, Laura, Guay-Woodford, Lisa M., Chen, Dhruti P., Helmuth, Margaret E., Smith, Abigail R., Canetta, Pietro A., Ayoub, Isabelle, Mucha, Krzysztof, Kallash, Mahmoud, Kopp, Jeffrey B., Gbadegesin, Rasheed, Gillespie, Brenda W., Greenbaum, Larry A., Parekh, Rulan S., Hunley, Tracy E., Sperati, C. John, Selewski, David T., Kidd, Jason, Chishti, Aftab, Reidy, Kimberly, Mottl, Amy K., Gipson, Debbie S., Srivastava, Tarak, and Twombley, Katherine E.

Published
2023
Full Text
View/download PDF

49. Mapping European Association of Urology Guideline Practice Across Europe: An Audit of Androgen Deprivation Therapy Use Before Prostate Cancer Surgery in 6598 Cases in 187 Hospitals Across 31 European Countries

Author

Heidegger, Isabel, Resch, Johannes Mischinger Irene, Turba, Simon, Zeder, Robin, Lodeta, Braninimir, Van Praet, Charles, Ghysel, Christophe, Arentsen, Harm C., Beysens, Matthias, Vinckier, Marie-Hélène, Mottrie, Alexandre, de Groote, Ruben, Timev, Aleksandar Ivanov, Georgiev, Marincho Ivanov, Yanev, Krassimir Prodanov, Mladenov, Boris, Ivanov, Atanas Slavchev, Antonov, Petar, Valkanov, Stanislav, Tomašković, Igor, Kulis, Tomislav, Bokarica, Pero, Pavlović, Oliver, Krajina, Vinko, Situm, Marijan, Boban, Toni, Soric, Tomislav, Vidic, Ivan, Benko, Goran, Peršec, Zoran, Sović, Tomislav, Zachoval, Roman, Stejskal, Jiri, Capoun, Otakar, Pitra, Tomáš, Gojdič, Marek, Babjuk, Marek, Novák, Vojtěch, Grepl, Michal, Broul, Marek, Novák, Jan, Lund, Lars, Nordström Joensen, Ulla, Borre, Michael, Veskimäe, Priit, Baum, Peep, Tamm, Toomas, Okas, Rauno, Jämsä, Pyry, Lahdensuo, Kanerva, Siltari, Sirkku, Seikkula, Heikki, Palmberg, Christian, Isotalo, Taina, Fiard, Gaelle, Verrier, Cecile, Wiedemann, Laura, Lecornet, Emilie, Leon, Priscilla, Millet, Clementine, Ponzio, Charles, Ploussard, Guillaume, Xylinas, Evanguelos, Ingels, Alexandre, Bigot, Pierre, Le Corre, Vincent, Audenet, François, Berg, Sebastian, Palisaar, Rein-Jueri, Heidenreich, Axel, Seelemeyer, Felix, Krege, Susanne, Leyh-Bannurah, Sami-Ramzi, Witt, Jörn H., Abdirahman, Ayanle, Truß, Michael C., Kranz, Jennifer, Andreas, Karagiannis, Vassileios, Tzortzis, Andreas, Andreou, Paparidis, Spyridon, Davis, Nikolaos Ferakis Niall F., Keane, Kevin G., Fuentes, Adrian, Scuderi, Simone, Barletta, Francesco, Manfredi, Matteo, Porpiglia, Francesco, Cerruto, Maria Angela, Antonelli, Alessandro, Esperto, Francesco, Rossanese, Marta, Veneziano, Domenico, Castelli, Tommaso, La Rocca, Roberto, Scarcia, Marcello, Mantica, Guglielmo, Rebuffo, Silvia, Pomara, Giorgio, Pavan, Nicola, Silvestri, Tommaso, Reale, Giulio Francesco, Polara, Andrea, Falagario, Ugo Giovanni, Carrieri, Giuseppe, Ferrari, Giovanni, Brausi, Maurizio, Orecchia, Luca, Annino, Filippo, Kazlauskas, Gražvydas, Stavridis, Sotir, Radovic, Nenad, Vukovic, Marko, van der Slot, Margaretha Adriana, Bruins, Harman Maxim, van Oort, Inge, Witjes, Fred, van der Poel, Henk, Beisland, Christian, Lilleåsenm, Gunder, Müller, Stig, Haug, Erik S., Dimmen, Magne, Czech, Anna K., Nyk, Lukasz, Jaskulski, Jaroslaw, Ratajczyk, Krzysztof, Azevedo, Nuno, Braga, Isaac, Pereira, João, Lúcio, Rui, Pina, João, da Silva, Edgar Miguel Calvo Loureiro Tavares, Furriel, Frederico, Mota, Paulo, Rodrigues, Miguel, Radavoi, George Daniel, Crisan, Nicolae, Andras, Iulia, Robert, Stoica, Bratu, Ovidiu, Surcel, Cristian, Kotov, Sergei, Malkhasyan, Vigen, Petrov, Sergei, Reva, Sergei, Bumbasirevic, Uros, Kováčik, Viktor, Perečinský, Ivan, Rybár, Ľuboš, Šulgan, Ján, Briš, Lukáš, Jursová, Katarína, Chovan, Miroslav, Kička, Tomáš, Taskovska, Milena, Kovačič, Rok, Miklavžina, Andraž, Alvarez-Maestro, Mario, De Castro, Javier Mayor, Aragón-Chamizo, Juan, Sutil, Raquel Sopeña, Perrello, Carmen Garau, Vilaseca, Antoni, Perez, Jorge Huguet, Ovide, Julia Aumatell, Planas, Jacques, Borque-Fernando, Angel, Sánchez-Izquierdo, Elena, Jimenez, Jose Luis Marenco, Lendínez-Cano, Guillermo, Puche-Sanz, Ignacio, Garcia-Baquero, Rodrigo, Esteban, Mario Domínguez, Pérez-Fentes, Daniel, Serván, Patricia Parra, Koskela, Lotta Renström, Stranne, Johan, Scholtz, Bianca, Torbrand, Christian, Wagenius, Magnus, Ugge, Henrik, Örtegren, Joakim, Langenauer, Janine, Zumstein, Valentin, Schmid, Hans Peter, Rieken, Malte, Saba, Karim, Strebel, Raeto T., Mortezavi, Ashkan, Rentsch, Cyrill, Roth, Beat, Eberli, Daniel, Pascal, Oechslin, Auer, Rebecca, John, Hubert, Thalmann, George N., Baltacı, Sümer, Mungan, Aydın, Sözen, Sinan, Cetin, Serhat, Aslan, Guven, Türkeri, Levent, İzol, Volkan, Demirdağ, Çetin, Ozden, Sami Berk, Toktaş, Gökhan, Sarikaya, Şaban, Tinay, İlker, Müezzinoğlu, Talha, Erbatu, Oguzcan, Sagnak, Levent, Akdoğan, Bülent, Can, Cavit, Şahin, Hayrettin, Yazıcı, Cenk Murat, Volkov, Serhii, Shulyak, Olexandr, Douglas, David, Hemmant, Joshua, El-Taji, Omar, Ahmad, Imran, Nalagatla, Sarika, Janebdar, Husay, Veeratterapillay, Rajan, Rai, Bhavan, Conroy, Samantha, Cumberbatch, Marcus, Malde, Sachin, MacLennan, Steven, Duncan, Eilidh, Dunsmore, Jennifer, Fullwood, Louise, Lumen, Nicolaas, Plass, Karin, Ribal, Maria J., Roobol, Monique J., Nieboer, Daan, Schouten, Natasha, Skolarus, Ted A., Smith, Emma Jane, N'Dow, James, Mottet, Nicolas, and Briganti, Alberto

Published
2023
Full Text
View/download PDF

50. The Significance of Hematuria in Podocytopathies

Author

Marchel, Dorota, Trachtman, Howard, Larkina, Maria, Helmuth, Margaret, Lai Yee, Jennifer Y., Fermin, Damian, Bomback, Andrew S., Canetta, Pietro A., Gipson, Debbie S., Mottl, Amy K., Parekh, Rulan S., Saha, Manish K., Sampson, Matthew G., Lafayette, Richard A., Mariani, Laura H., Massengill, S., Lo, L., Dell, K., Sedor, J., Martin, B., Lemley, K., Fajardo, C., Sharma, S., Srivastava, T., Markus, K., Sethna, C., Vento, S., Canetta, P., Pradhan, A., Gbadegesin, R., Olabisi, O., Smith, M., Greenbaum, L., Wang, C.S., Yun, E., Adler, S., LaPage, J., Amarah, A., Itteera, M., Atkinson, M., Williams, M., Fervenza, F., Hogan, M., Lieske, J., Selewski, D., Alston, C., Kaskel, F., Ross, M., Flynn, P., Kopp, J., Malaga-Dieguez, L., Zhdanova, O., Pehrson, L.J., Almaani, S., Roberts, L., Lafayette, R., Dave, S., Lee, I., Pfeffer, Z., Shah, S., Deslandes, A., Reich, H., Hladunewich, M., Ling, P., Romano, M., Brakeman, P, Podoll, A., Rogers, N., McCarthy, E., Landry, E., Fornoni, A., Bidot, C., Kretzler, M., Gipson, D., Williams, A., Stelzer, M., Nachman, P., Rheault, M., Rao, V., Derebail, V., Gibson, K., Froment, A., Ochoa-Toro, F., Holzman, L., Meyers, K., Kallem, K., Swenson, A., Sharma, K., Sambandam, K., Robles, E., Turk, M., Jefferson, A., Hingorani, S., Tuttle, K., Manahan, L., Pao, E., Kuykendall K, K., Lin, J.J., Cody, E., Kretzler, M., Barisoni, L., Gadegbeku, C., Gillespie, B., Gipson, D., Holzman, L., Mariani, L., Sampson, M.G., Sedor, J., Smith, A., Zee, J., Alter, G., Desmond, H., Eddy, S., Fermin, D., Ju, W., Larkina, M., Li, S., Lienczewski, C.C., Mainieri, T., Scherr, R., Troost, J., Williams, A., Wang, Y., Avila-Casado, Carmen, Bagnasco, Serena, Cassol, Clarissa, Bu, Lihong, Caltharp, Shelley, Demeke, Dawit, Gillespie, Brenda, Hassler, Jared, Herlitz, Leal, Hewitt, Stephen, Hodgin, Jeff, Holanda, Danni, Kambham, Neeraja, Lemley, Kevin, Mariani, Laura, Messias, Nidia, Mikhailov, Alexei, Najafian, Behzad, Palmer, Matthew, Rosenberg, Avi, Royal, Virginie, Stokes, Barry, Thomas, David, Yamashita, Michifumi, Yin, Hong, Zee, Jarcy, Zuo, Yiqin, Barisoni, Laura, Nast, Cynthia, Ahn, Wooin, Appel, Gerald, Appelbaum, Paul, Babayev, Revekka, Bomback, Andrew, Canetta, Pietro, Chan, Brenda, DʼAgati, Vivette Denise, Dogra, Samitri, Fernandez, Hilda, Gharavi, Ali, Hines, William, Husain, Syed Ali, Jain, Namrata, Kiryluk, Krzysztof, Lin, Fangming, Marasa, Maddalena, Markowitz, Glen, Rasouly, Hila Milo, Mohan, Sumit, Mongera, Nicola, Nestor, Jordan, Nickolas, Thomas, Radhakrishnan, Jai, Rao, Maya, Sanna-Cherchi, Simone, Shirazian, Shayan, Stokes, Michael Barry, Uy, Natalie, Valeri, Anthony, Vena, Natalie, Foroncewicz, Bartosz, Moszczuk, Barbara, Mucha, Krzysztof, Perkowska-Ptasińska, Agnieszka, Ghiggeri, Gian Marco, Lugani, Francesca, Ambruzs, Josephine, Liapis, Helen, Baracco, Rossana, Jain, Amrish, Ashoor, Isa, Aviles, Diego, Srivastava, Tarak, Ahn, Sun-Young, Devarajan, Prasad, Erkan, Elif, Claes, Donna, Stone, Hillarey, Mason, Sherene, Gbadegesin, Rasheed, Gomez-Mendez, Liliana, Greenbaum, Larry, Wang, Chia-shi, Yin, Hong (Julie), Cai, Yi, Jens, Goebel, Steinke, Julia, Weaver, Donald, Lane, Jerome, Cramer, Carl, Pan, Cindy, Paloian, Neil, Sreedharan, Rajasree, Selewski, David, Twombley, Katherine, Bowers, Corinna, Dreher, Mary, Kallash, Mahmoud, Mahan, John, Sharpe, Samantha, Smoyer, William, Al-Uzri, Amira, Iragorri, Sandra, Khalid, Myda, Belsha, Craig, Alge, Joseph, Braun, Michael, Gomez, AC, Wenderfer, Scott, Vasylyeva, Tetyana, Feig, Daniel, Fuentes, Gabriel Cara, Hannah, Melisha, Nester, Carla, Chishti, Aftab, Klein, Jon, Katsoufis, Chryso, Seeherunvong, Wacharee, Rheault, Michelle, Wong, Craig, Mathews, Nisha, Barcia, John, Swiatecka-Urban, Agnes, Bartosh, Sharon, Hunley, Tracy, Dharnidharka, Vikas, Gaut, Joseph, Laurin, Louis-Philippe, Royal, Virginie, Achanti, Anand, Budisavljevic, Milos, Self, Sally, Ghossein, Cybele, Peleg, Yonatan, Wadhwani, Shikha, Almaani, Salem, Ayoub, Isabelle, Nadasdy, Tibor, Samir, Parikh, Rovin, Brad, Chang, Anthony, Fatima, Huma, Julian, Bruce, Novak, Jan, Renfrow, Matthew, Rizk, Dana, Chen, Dhruti, Derebail, Vimal, Falk, Ronald, Gibson, Keisha, Glenn, Dorey, Hogan, Susan, Jain, Koyal, Jennette, J. Charles, Mottl, Amy, Poulton, Caroline, Saha, Manish Kanti, Fogo, Agnes, Sanghani, Neil, Kidd, Jason, Muthusamy, Selvaraj, Schelling, Jeffrey, Hou, Jean, Lemley, Kevin, Mika, Warren, Russo, Pierre, Denburg, Michelle, Kogon, Amy, Meyers, Kevin, Pradhan, Madhura, Matar, Raed Bou, OʼToole, John, Sedor, John, Sethna, Christine, Vento, Suzanne, Atta, Mohamed, Bagnasco, Serena, Neu, Alicia, Sperati, John, Adler, Sharon, Dai, Tiane, Dukkipati, Ram, Fervenza, Fernando, Sethi, Sanjeev, Kaskel, Frederick, Brathwaite, Kaye, Reidy, Kimberly, Weisstuch, Joseph, Wu, Ming, Zhdanova, Olga, Heymann, Jurgen, Kopp, Jeffrey, Waldman, Meryl, Winkler, Cheryl, Tuttle, Katherine, Krissberg, Jill, Lafayette, Richard, Fahmeedah, Kamal, Talley, Elizabeth, Hladunewich, Michelle, Parekh, Rulan, Avila-Casado, Carmen, Cattran, Daniel, Heather, Reich, Boll, Philip, Drexler, Yelena, Fornoni, Alessia, Gipson, Patrick, Hodgin, Jeffrey, Oliverio, Andrea, Hogan, Jon, Holzman, Lawrence, Palmer, Matthew, Coppock, Gaia, Abromovitz, Blaise, Mortiz, Michael, Alpers, Charles, Jefferson, J. Ashley, Brown, Elizabeth, Sambandam, Kamal, Roehm, Bethany, Smith, Abigail, Nast, Cynthia, Barisoni, Laura, Gillespie, Brenda, Robinson, Bruce, Kretzler, Matthias, Mariani, Laura, and Guay-Woodford, Lisa M.

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results