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1,107 results on '"Makowski, M. A."'

552. Divertor detachment studies in DIII-D

Author

Hill, D. N., Mclean, A. G., Leonard, A. W., Allen, S. L., Briesemeister, A. R., Covele, B. M., Mathias Groth, Makowski, M. A., Petrie, T. W., Soukhanovskii, V. A., and Guo, H. Y.

554. Control of DIII-D advanced tokamak discharges

Author

Fdron, J. R., Casper, T. A., Doyle, E. J., Garofalo, A. M., Gohil, P., Greenfield, C. M., Hyatt, A. W., Jayakumar, R. J., Kessel, C., Kim, J. Y., La Haye, R. J., Loin, J., Luce, T. C., Makowski, M. A., Mazon, D., Menard, J. E., Murakami, M., Petty, C. C., Politzer, P. A., Rater, R., Taylor, T. S., and Mickey Wade

559. IMP, a free electron laser amplifier for plasma heating in the Microwave Tokamak Experiment

Author

Jong, R.A., primary, Atkinson, D.P., additional, Byers, J.A., additional, Coffield, F.E., additional, Deis, G.A., additional, Felker, B., additional, Ferguson, S.W., additional, Fontaine, R.A., additional, Hopkins, D.B., additional, Makowski, M., additional, Orzechowski, T.J., additional, Paul, A.C., additional, Scharlemann, E.T., additional, Schlueter, R.D., additional, Stallard, B.W., additional, Stever, R.D., additional, and Throop, A.L., additional

Published
1989
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574. Characterization of Magnetosomes After Exposure to the Effect of the Sonication and Ultracentrifugation.

Author

MOLČAN, M., HASHIM, A., KOVÁČ, J., RAJŇÁK, M., KOPČANSKÝ, P., MAKOWSKI, M., GOJZEWSKI, H., MOLOKÁČ, M., HVIZDÁK, L., and TIMKO, M.

Subjects
MAGNETOSOMES, SONICATION, ULTRACENTRIFUGATION, MARINE microorganisms, BIOMINERALIZATION, MAGNETOSPIRILLUM, SCANNING electron microscopy
Abstract

Magnetosomes are intracellular organelles of widespread aquatic microorganisms called Magnetotactic bacteria. At present they are under investigation especially in biomedical applications. This ability depends on the presence of intracellular magnetosomes which are composed of two parts: first, nanometer-sized magnetite (Fe3O4) or greigite (Fe3S4) crystals (magnetosome crystal), depending on the bacterial species; and second, the bilayer membrane surrounding the crystal (magnetosome membrane). The magnetosomes were prepared by biomineralization process of magnetotactic bacteria Magnetospirillum Magnetotacticum sp. AMB-1. The isolated magnetosome chains (sample M) were centrifugated at speed of 100000 rpm for 4 hours (sample UM) and sonicated at power of 120 W for 3 hours (sample SM), respectively. The prepared suspensions were investigated with respect to morphological, structural and magnetic properties. The results from scanning electron microscopy showed that isolated chains of magnetosomes were partially broken to smaller ones after ultracentrifugation. On the other hand the application of the sonication process caused the formation of individual magnetosomes (unordered in chain). These results were confirmed by coercivity and magnetization saturation measurements. [ABSTRACT FROM AUTHOR]

Published
2014
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575. Orthopaedic manifestations of pseudoachondroplasia.

Author

Weiner, D. S., Guirguis, J., Makowski, M., Testa, S., Shauver, L., and Morgan, D.

Subjects
*SKELETAL dysplasia, *THORACIC vertebrae, *EXTRACELLULAR matrix proteins, *GROWTH plate, *LUMBAR vertebrae
Abstract

Purpose In 1959, Maroteaux and Lamy initially designated pseudoachondroplasia as a distinct dysplasia different from achondroplasia the most common form of skeletal dysplasia. Pseudoachondroplasia is caused by a mutation in the collagen oligomeric matrix protein gene (COMP) gene on chromosome 19p13.1-p12 encoding the COMP. The COMP gene mutations result in rendering the articular and growth plate cartilages incapable of withstanding routine biomechanical loads with resultant deformity of the joints. The purpose of the study was to characterize the typical orthopaedic findings in pseudoachondroplasia. Methods The charts and radiographs of 141 patients with pseudoachondroplasia were analyzed. This cohort, to our knowledge, represents the largest group of patients describing the typical orthopaedic manifestations of pseudoachondroplasia. Results Patients with pseudoachondroplasia have normal craniofacial appearance with normal intelligence. Short stature is not present at birth and generally appears by two to four years of age. The condition is a form of spondyloepiphyseal dysplasia and the long bones are characterized by dysplastic changes in the epiphysis, metaphysis and vertebral bodies. Radiographically the long bones have altered the appearance and structure of the epiphyses with small irregularly formed or fragmented epiphyses or flattening. The metaphyseal regions of the long bones show flaring, widening or 'trumpeting'. The cervical (89%) and thoracic and lumbar vertebrae show either platyspondyly, ovoid, 'cod-fish' deformity or anterior 'beaking'. Kyphosis (28%), scoliosis (58%) and lumbar lordosis (100%) are commonly seen. The femoral head and acetabulum are severely dysplastic (100%). The knees show either genu valgum (22%), genu varum (56%) or 'windswept' deformity (22%). Conclusion Most commonly these distortions of the appendicular and the axial skeleton lead to premature arthritis particularly of the hips and often the knees not uncommonly in the 20- to 30-year-old age group. [ABSTRACT FROM AUTHOR]

Published
2019
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577. Evaluation of bone viability in patients after girdlestone arthroplasty: comparison of bone SPECT/CT and MRI.

Author

Diederichs, G., Hoppe, P., Collettini, F., Wassilew, G., Hamm, B., Brenner, W., Makowski, M., and Makowski, M R

Subjects
*ARTHROPLASTY, *SINGLE-photon emission computed tomography, *HISTOPATHOLOGY, *OSTEONECROSIS, BONE biopsy
Abstract

Purpose: To test the diagnostic performance of bone SPECT/CT and MRI for the evaluation of bone viability in patients after girdlestone-arthroplasty with histopathology used as gold standard.Materials and Methods: In this cross-sectional study, patients after girdlestone-arthroplasty were imaged with single-photon-emission-computed-tomography/computed-tomography (SPECT/CT) bone-scans using 99mTc-DPD. Additionally, 1.5 T MRI was performed with turbo-inversion-recovery-magnitude (TIRM), contrast-enhanced T1-fat sat (FS) and T1-mapping. All imaging was performed within 24 h prior to revision total-hip-arthroplasty in patients with a girdlestone-arthroplasty. In each patient, four standardized bone-tissue-biopsies (14 patients) were taken intraoperatively at the remaining acetabulum superior/inferior and trochanter major/minor. Histopathological evaluation of bone samples regarding bone viability was used as gold standard.Results: A total of 56 bone-segments were analysed and classified as vital (n = 39) or nonvital (n = 17) by histopathology. Mineral/late-phase SPECT/CT showed a high sensitivity (90%) and specificity (94%) to distinguish viable and nonviable bone tissue. TIRM (sensitivity 87%, specificity 88%) and contrast-enhanced T1-FS (sensitivity 90%, specificity 88%) also achieved a high sensitivity and specificity. T1-mapping achieved the lowest values (sensitivity 82%, specificity 82%). False positive results in SPECT/CT and MRI resulted from small bone fragments close to metal artefacts.Conclusions: Both bone SPECT/CT and MRI allow a reliable differentiation between viable and nonviable bone tissue in patients after girdlestone arthroplasty. The findings of this study could also be relevant for the evaluation of bone viability in the context of avascular bone necrosis. [ABSTRACT FROM AUTHOR]

Published
2017
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578. Physisorption of functionalized gold nanoparticles on AlGaN/GaN high electron mobility transistors for sensing applications.

Author

Makowski, M. S., Kim, S., Gaillard, M., Janes, D., Manfra, M. J., Bryan, I., Sitar, Z., Arellano, C., Xie, J., Collazo, R., and Ivanisevic, A.

Subjects
*MODULATION-doped field-effect transistors, *GOLD nanoparticles, *PHYSISORPTION, *ALKANETHIOLS, *BIOSENSORS, *AMINES
Abstract

AlGaN/GaN high electron mobility transistors (HEMTs) were used to measure electrical characteristics of physisorbed gold nanoparticles (Au NPs) functionalized with alkanethiols with a terminal methyl, amine, or carboxyl functional group. Additional alkanethiol was physisorbed onto the NP treated devices to distinguish between the effects of the Au NPs and alkanethiols on HEMT operation. Scanning Kelvin probe microscopy and electrical measurements were used to characterize the treatment effects. The HEMTs were operated near threshold voltage due to the greatest sensitivity in this region. The Au NP/HEMT system electrically detected functional group differences on adsorbed NPs which is pertinent to biosensor applications. [ABSTRACT FROM AUTHOR]

Published
2013
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583. Statins impair antitumor effects of rituximab by inducing conformational changes of CD20.

Author

Winiarska M, Bil J, Wilczek E, Wilczynski GM, Lekka M, Engelberts PJ, Mackus WJ, Gorska E, Bojarski L, Stoklosa T, Nowis D, Kurzaj Z, Makowski M, Glodkowska E, Issat T, Mrowka P, Lasek W, Dabrowska-Iwanicka A, Basak GW, and Wasik M

Abstract

Background: Rituximab is used in the treatment of CD20+ B cell lymphomas and other B cell lymphoproliferative disorders. Its clinical efficacy might be further improved by combinations with other drugs such as statins that inhibit cholesterol synthesis and show promising antilymphoma effects. The objective of this study was to evaluate the influence of statins on rituximab-induced killing of B cell lymphomas.Methods and Findings: Complement-dependent cytotoxicity (CDC) was assessed by MTT and Alamar blue assays as well as trypan blue staining, and antibody-dependent cellular cytotoxicity (ADCC) was assessed by a 51Cr release assay. Statins were found to significantly decrease rituximab-mediated CDC and ADCC of B cell lymphoma cells. Incubation of B cell lymphoma cells with statins decreased CD20 immunostaining in flow cytometry studies but did not affect total cellular levels of CD20 as measured with RT-PCR and Western blotting. Similar effects are exerted by other cholesterol-depleting agents (methyl-beta-cyclodextrin and berberine), but not filipin III, indicating that the presence of plasma membrane cholesterol and not lipid rafts is required for rituximab-mediated CDC. Immunofluorescence microscopy using double staining with monoclonal antibodies (mAbs) directed against a conformational epitope and a linear cytoplasmic epitope revealed that CD20 is present in the plasma membrane in comparable amounts in control and statin-treated cells. Atomic force microscopy and limited proteolysis indicated that statins, through cholesterol depletion, induce conformational changes in CD20 that result in impaired binding of anti-CD20 mAb. An in vivo reduction of cholesterol induced by short-term treatment of five patients with hypercholesterolemia with atorvastatin resulted in reduced anti-CD20 binding to freshly isolated B cells.Conclusions: Statins were shown to interfere with both detection of CD20 and antilymphoma activity of rituximab. These studies have significant clinical implications, as impaired binding of mAbs to conformational epitopes of CD20 elicited by statins could delay diagnosis, postpone effective treatment, or impair anti-lymphoma activity of rituximab. [ABSTRACT FROM AUTHOR]

Published
2008
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584. DIII-D research advancing the physics basis for optimizing the tokamak approach to fusion energy

Author

M. E. Fenstermacher, J. Abbate, S. Abe, T. Abrams, M. Adams, B. Adamson, N. Aiba, T. Akiyama, P. Aleynikov, E. Allen, S. Allen, H. Anand, J. Anderson, Y. Andrew, T. Andrews, D. Appelt, R. Arbon, N. Ashikawa, A. Ashourvan, M. Aslin, Y. Asnis, M. Austin, D. Ayala, J. Bak, I. Bandyopadhyay, S. Banerjee, K. Barada, L. Bardoczi, J. Barr, E. Bass, D. Battaglia, A. Battey, W. Baumgartner, L. Baylor, J. Beckers, M. Beidler, E. Belli, J. Berkery, T. Bernard, N. Bertelli, M. Beurskens, R. Bielajew, S. Bilgili, B. Biswas, S. Blondel, J. Boedo, I. Bogatu, R. Boivin, T. Bolzonella, M. Bongard, X. Bonnin, P. Bonoli, M. Bonotto, A. Bortolon, S. Bose, N. Bosviel, S. Bouwmans, M. Boyer, W. Boyes, L. Bradley, R. Brambila, D. Brennan, S. Bringuier, L. Brodsky, M. Brookman, J. Brooks, D. Brower, G. Brown, W. Brown, M. Burke, K. Burrell, K. Butler, R. Buttery, I. Bykov, P. Byrne, A. Cacheris, K. Callahan, J. Callen, G. Campbell, J. Candy, J. Canik, P. Cano-Megias, N. Cao, L. Carayannopoulos, T. Carlstrom, W. Carrig, T. Carter, W. Cary, L. Casali, M. Cengher, G. Cespedes Paz, R. Chaban, V. Chan, B. Chapman, I. Char, A. Chattopadhyay, R. Chen, J. Chen, X. Chen, M. Chen, Z. Chen, M. Choi, W. Choi, G. Choi, L. Chousal, C. Chrobak, C. Chrystal, Y. Chung, R. Churchill, M. Cianciosa, J. Clark, M. Clement, S. Coda, A. Cole, C. Collins, W. Conlin, A. Cooper, J. Cordell, B. Coriton, T. Cote, J. Cothran, A. Creely, N. Crocker, C. Crowe, B. Crowley, T. Crowley, D. Cruz-Zabala, D. Cummings, M. Curie, D. Curreli, A. Dal Molin, B. Dannels, A. Dautt-Silva, K. Davda, G. De Tommasi, P. De Vries, G. Degrandchamp, J. Degrassie, D. Demers, S. Denk, S. Depasquale, E. Deshazer, A. Diallo, S. Diem, A. Dimits, R. Ding, S. Ding, W. Ding, T. Do, J. Doane, G. Dong, D. Donovan, J. Drake, W. Drews, J. Drobny, X. Du, H. Du, V. Duarte, D. Dudt, C. Dunn, J. Duran, A. Dvorak, F. Effenberg, N. Eidietis, D. Elder, D. Eldon, R. Ellis, W. Elwasif, D. Ennis, K. Erickson, D. Ernst, M. Fasciana, D. Fedorov, E. Feibush, N. Ferraro, J. Ferreira, J. Ferron, P. Fimognari, D. Finkenthal, R. Fitzpatrick, P. Fox, W. Fox, L. Frassinetti, H. Frerichs, H. Frye, Y. Fu, K. Gage, J. Galdon Quiroga, A. Gallo, Q. Gao, A. Garcia, M. Garcia Munoz, D. Garnier, A. Garofalo, A. Gattuso, D. Geng, K. Gentle, D. Ghosh, L. Giacomelli, S. Gibson, E. Gilson, C. Giroud, F. Glass, A. Glasser, D. Glibert, P. Gohil, R. Gomez, S. Gomez, X. Gong, E. Gonzales, A. Goodman, Y. Gorelov, V. Graber, R. Granetz, T. Gray, D. Green, C. Greenfield, M. Greenwald, B. Grierson, R. Groebner, W. Grosnickle, M. Groth, H. Grunloh, S. Gu, W. Guo, H. Guo, P. Gupta, J. Guterl, W. Guttenfelder, T. Guzman, S. Haar, R. Hager, S. Hahn, M. Halfmoon, T. Hall, K. Hallatschek, F. Halpern, G. Hammett, H. Han, E. Hansen, C. Hansen, M. Hansink, J. Hanson, M. Hanson, G. Hao, A. Harris, R. Harvey, S. Haskey, E. Hassan, A. Hassanein, D. Hatch, R. Hawryluk, W. Hayashi, W. Heidbrink, J. Herfindal, J. Hicok, D. Hill, E. Hinson, C. Holcomb, L. Holland, C. Holland, E. Hollmann, J. Hollocombe, A. Holm, I. Holmes, K. Holtrop, M. Honda, R. Hong, R. Hood, A. Horton, L. Horvath, M. Hosokawa, S. Houshmandyar, N. Howard, E. Howell, D. Hoyt, W. Hu, Y. Hu, Q. Hu, J. Huang, Y. Huang, J. Hughes, T. Human, D. Humphreys, P. Huynh, A. Hyatt, C. Ibanez, L. Ibarra, R. Icasas, K. Ida, V. Igochine, Y. In, S. Inoue, A. Isayama, O. Izacard, V. Izzo, A. Jackson, G. Jacobsen, A. Jaervinen, A. Jalalvand, J. Janhunen, S. Jardin, H. Jarleblad, Y. Jeon, H. Ji, X. Jian, E. Joffrin, A. Johansen, C. Johnson, T. Johnson, C. Jones, I. Joseph, D. Jubas, B. Junge, W. Kalb, R. Kalling, C. Kamath, J. Kang, D. Kaplan, A. Kaptanoglu, S. Kasdorf, J. Kates-Harbeck, P. Kazantzidis, A. Kellman, D. Kellman, C. Kessel, K. Khumthong, E. Kim, H. Kim, J. Kim, S. Kim, K. Kim, C. Kim, W. Kimura, M. King, J. King, J. Kinsey, A. Kirk, B. Kiyan, A. Kleiner, V. Klevarova, R. Knapp, M. Knolker, W. Ko, T. Kobayashi, E. Koch, M. Kochan, B. Koel, M. Koepke, A. Kohn, R. Kolasinski, E. Kolemen, E. Kostadinova, M. Kostuk, G. Kramer, D. Kriete, L. Kripner, S. Kubota, J. Kulchar, K. Kwon, R. La Haye, F. Laggner, H. Lan, R. Lantsov, L. Lao, A. Lasa Esquisabel, C. Lasnier, C. Lau, B. Leard, J. Lee, R. Lee, M. Lee, Y. Lee, C. Lee, S. Lee, M. Lehnen, A. Leonard, E. Leppink, M. Lesher, J. Lestz, J. Leuer, N. Leuthold, X. Li, K. Li, E. Li, G. Li, L. Li, Z. Li, J. Li, Y. Li, Z. Lin, D. Lin, X. Liu, J. Liu, Y. Liu, T. Liu, C. Liu, Z. Liu, D. Liu, A. Liu, A. Loarte-Prieto, L. Lodestro, N. Logan, J. Lohr, B. Lombardo, J. Lore, Q. Luan, T. Luce, T. Luda Di Cortemiglia, N. Luhmann, R. Lunsford, Z. Luo, A. Lvovskiy, B. Lyons, X. Ma, M. Madruga, B. Madsen, C. Maggi, K. Maheshwari, A. Mail, J. Mailloux, R. Maingi, M. Major, M. Makowski, R. Manchanda, C. Marini, A. Marinoni, A. Maris, T. Markovic, L. Marrelli, E. Martin, J. Mateja, G. Matsunaga, R. Maurizio, P. Mauzey, D. Mauzey, G. Mcardle, J. Mcclenaghan, K. Mccollam, C. Mcdevitt, K. Mckay, G. Mckee, A. Mclean, V. Mehta, E. Meier, J. Menard, O. Meneghini, G. Merlo, S. Messer, W. Meyer, C. Michael, C. Michoski, P. Milne, G. Minet, A. Misleh, Y. Mitrishkin, C. Moeller, K. Montes, M. Morales, S. Mordijck, D. Moreau, S. Morosohk, P. Morris, L. Morton, A. Moser, R. Moyer, C. Moynihan, T. Mrazkova, D. Mueller, S. Munaretto, J. Munoz Burgos, C. Murphy, K. Murphy, C. Muscatello, C. Myers, A. Nagy, G. Nandipati, M. Navarro, F. Nave, G. Navratil, R. Nazikian, A. Neff, G. Neilson, T. Neiser, W. Neiswanger, D. Nelson, A. Nelson, F. Nespoli, R. Nguyen, L. Nguyen, X. Nguyen, J. Nichols, M. Nocente, S. Nogami, S. Noraky, N. Norausky, M. Nornberg, R. Nygren, T. Odstrcil, D. Ogas, T. Ogorman, S. Ohdachi, Y. Ohtani, M. Okabayashi, M. Okamoto, L. Olavson, E. Olofsson, M. Omullane, R. Oneill, D. Orlov, W. Orvis, T. Osborne, D. Pace, G. Paganini Canal, A. Pajares Martinez, L. Palacios, C. Pan, Q. Pan, R. Pandit, M. Pandya, A. Pankin, Y. Park, J. Park, S. Parker, P. Parks, M. Parsons, B. Patel, C. Pawley, C. Paz-Soldan, W. Peebles, S. Pelton, R. Perillo, C. Petty, Y. Peysson, D. Pierce, A. Pigarov, L. Pigatto, D. Piglowski, S. Pinches, R. Pinsker, P. Piovesan, N. Piper, A. Pironti, R. Pitts, J. Pizzo, U. Plank, M. Podesta, E. Poli, F. Poli, D. Ponce, Z. Popovic, M. Porkolab, G. Porter, C. Powers, S. Powers, R. Prater, Q. Pratt, I. Pusztai, J. Qian, X. Qin, O. Ra, T. Rafiq, T. Raines, R. Raman, J. Rauch, A. Raymond, C. Rea, M. Reich, A. Reiman, S. Reinhold, M. Reinke, R. Reksoatmodjo, Q. Ren, Y. Ren, J. Ren, M. Rensink, J. Renteria, T. Rhodes, J. Rice, R. Roberts, J. Robinson, P. Rodriguez Fernandez, T. Rognlien, A. Rosenthal, S. Rosiello, J. Rost, J. Roveto, W. Rowan, R. Rozenblat, J. Ruane, D. Rudakov, J. Ruiz Ruiz, R. Rupani, S. Saarelma, S. Sabbagh, J. Sachdev, J. Saenz, S. Saib, M. Salewski, A. Salmi, B. Sammuli, C. Samuell, A. Sandorfi, C. Sang, J. Sarff, O. Sauter, K. Schaubel, L. Schmitz, O. Schmitz, J. Schneider, P. Schroeder, K. Schultz, E. Schuster, J. Schwartz, F. Sciortino, F. Scotti, J. Scoville, A. Seltzman, S. Seol, I. Sfiligoi, M. Shafer, S. Sharapov, H. Shen, Z. Sheng, T. Shepard, S. Shi, Y. Shibata, G. Shin, D. Shiraki, R. Shousha, H. Si, P. Simmerling, G. Sinclair, J. Sinha, P. Sinha, G. Sips, T. Sizyuk, C. Skinner, A. Sladkomedova, T. Slendebroek, J. Slief, R. Smirnov, J. Smith, S. Smith, D. Smith, J. Snipes, G. Snoep, A. Snyder, P. Snyder, E. Solano, W. Solomon, J. Song, A. Sontag, V. Soukhanovskii, J. Spendlove, D. Spong, J. Squire, C. Srinivasan, W. Stacey, G. Staebler, L. Stagner, T. Stange, P. Stangeby, R. Stefan, R. Stemprok, D. Stephan, J. Stillerman, T. Stoltzfus-Dueck, W. Stonecipher, S. Storment, E. Strait, D. Su, L. Sugiyama, Y. Sun, P. Sun, Z. Sun, A. Sun, D. Sundstrom, C. Sung, J. Sungcoco, W. Suttrop, Y. Suzuki, T. Suzuki, A. Svyatkovskiy, C. Swee, R. Sweeney, C. Sweetnam, G. Szepesi, M. Takechi, T. Tala, K. Tanaka, X. Tang, S. Tang, Y. Tao, R. Tao, D. Taussig, T. Taylor, K. Teixeira, K. Teo, A. Theodorsen, D. Thomas, K. Thome, A. Thorman, A. Thornton, A. Ti, M. Tillack, N. Timchenko, R. Tinguely, R. Tompkins, J. Tooker, A. Torrezan De Sousa, G. Trevisan, S. Tripathi, A. Trujillo Ochoa, D. Truong, C. Tsui, F. Turco, A. Turnbull, M. Umansky, E. Unterberg, P. Vaezi, P. Vail, J. Valdez, W. Valkis, B. Van Compernolle, J. Van Galen, R. Van Kampen, M. Van Zeeland, G. Verdoolaege, N. Vianello, B. Victor, E. Viezzer, S. Vincena, M. Wade, F. Waelbroeck, J. Wai, T. Wakatsuki, M. Walker, G. Wallace, R. Waltz, W. Wampler, L. Wang, H. Wang, Y. Wang, Z. Wang, G. Wang, S. Ward, M. Watkins, J. Watkins, W. Wehner, Y. Wei, M. Weiland, D. Weisberg, A. Welander, A. White, R. White, S. Wiesen, R. Wilcox, T. Wilks, M. Willensdorfer, H. Wilson, A. Wingen, M. Wolde, M. Wolff, K. Woller, A. Wolz, H. Wong, S. Woodruff, M. Wu, Y. Wu, S. Wukitch, G. Wurden, W. Xiao, R. Xie, Z. Xing, X. Xu, C. Xu, G. Xu, Z. Yan, X. Yang, S. Yang, T. Yokoyama, R. Yoneda, M. Yoshida, K. You, T. Younkin, J. Yu, M. Yu, G. Yu, Q. Yuan, L. Zaidenberg, L. Zakharov, A. Zamengo, S. Zamperini, M. Zarnstorff, E. Zeger, K. Zeller, L. Zeng, M. Zerbini, L. Zhang, X. Zhang, R. Zhang, B. Zhang, J. Zhang, L. Zhao, B. Zhao, Y. Zheng, L. Zheng, B. Zhu, J. Zhu, Y. Zhu, M. Zsutty, M. Zuin, Fenstermacher, M. E., Abbate, J., Abe, S., Abrams, T., Adams, M., Adamson, B., Aiba, N., Akiyama, T., Aleynikov, P., Allen, E., Allen, S., Anand, H., Anderson, J., Andrew, Y., Andrews, T., Appelt, D., Arbon, R., Ashikawa, N., Ashourvan, A., Aslin, M., Asnis, Y., Austin, M., Ayala, D., Bak, J., Bandyopadhyay, I., Banerjee, S., Barada, K., Bardoczi, L., Barr, J., Bass, E., Battaglia, D., Battey, A., Baumgartner, W., Baylor, L., Beckers, J., Beidler, M., Belli, E., Berkery, J., Bernard, T., Bertelli, N., Beurskens, M., Bielajew, R., Bilgili, S., Biswas, B., Blondel, S., Boedo, J., Bogatu, I., Boivin, R., Bolzonella, T., Bongard, M., Bonnin, X., Bonoli, P., Bonotto, M., Bortolon, A., Bose, S., Bosviel, N., Bouwmans, S., Boyer, M., Boyes, W., Bradley, L., Brambila, R., Brennan, D., Bringuier, S., Brodsky, L., Brookman, M., Brooks, J., Brower, D., Brown, G., Brown, W., Burke, M., Burrell, K., Butler, K., Buttery, R., Bykov, I., Byrne, P., Cacheris, A., Callahan, K., Callen, J., Campbell, G., Candy, J., Canik, J., Cano-Megias, P., Cao, N., Carayannopoulos, L., Carlstrom, T., Carrig, W., Carter, T., Cary, W., Casali, L., Cengher, M., Cespedes Paz, G., Chaban, R., Chan, V., Chapman, B., Char, I., Chattopadhyay, A., Chen, R., Chen, J., Chen, X., Chen, M., Chen, Z., Choi, M., Choi, W., Choi, G., Chousal, L., Chrobak, C., Chrystal, C., Chung, Y., Churchill, R., Cianciosa, M., Clark, J., Clement, M., Coda, S., Cole, A., Collins, C., Conlin, W., Cooper, A., Cordell, J., Coriton, B., Cote, T., Cothran, J., Creely, A., Crocker, N., Crowe, C., Crowley, B., Crowley, T., Cruz-Zabala, D., Cummings, D., Curie, M., Curreli, D., Dal Molin, A., Dannels, B., Dautt-Silva, A., Davda, K., De Tommasi, G., De Vries, P., Degrandchamp, G., Degrassie, J., Demers, D., Denk, S., Depasquale, S., Deshazer, E., Diallo, A., Diem, S., Dimits, A., Ding, R., Ding, S., Ding, W., Do, T., Doane, J., Dong, G., Donovan, D., Drake, J., Drews, W., Drobny, J., Du, X., Du, H., Duarte, V., Dudt, D., Dunn, C., Duran, J., Dvorak, A., 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R, Piovesan, P, Piper, N, Pironti, A, Pitts, R, Pizzo, J, Plank, U, Podesta, M, Poli, E, Poli, F, Ponce, D, Popovic, Z, Porkolab, M, Porter, G, Powers, C, Powers, S, Prater, R, Pratt, Q, Pusztai, I, Qian, J, Qin, X, Ra, O, Rafiq, T, Raines, T, Raman, R, Rauch, J, Raymond, A, Rea, C, Reich, M, Reiman, A, Reinhold, S, Reinke, M, Reksoatmodjo, R, Ren, Q, Ren, Y, Ren, J, Rensink, M, Renteria, J, Rhodes, T, Rice, J, Roberts, R, Robinson, J, Fernandez, P, Rognlien, T, Rosenthal, A, Rosiello, S, Rost, J, Roveto, J, Rowan, W, Rozenblat, R, Ruane, J, Rudakov, D, Ruiz, J, Rupani, R, Saarelma, S, Sabbagh, S, Sachdev, J, Saenz, J, Saib, S, Salewski, M, Salmi, A, Sammuli, B, Samuell, C, Sandorfi, A, Sang, C, Sarff, J, Sauter, O, Schaubel, K, Schmitz, L, Schmitz, O, Schneider, J, Schroeder, P, Schultz, K, Schuster, E, Schwartz, J, Sciortino, F, Scotti, F, Scoville, J, Seltzman, A, Seol, S, Sfiligoi, I, Shafer, M, Sharapov, S, Shen, H, Sheng, Z, Shepard, T, Shi, S, Shibata, Y, Shin, G, Shiraki, D, Shousha, R, Si, H, Simmerling, P, Sinclair, G, Sinha, J, Sinha, P, Sips, G, Sizyuk, T, Skinner, C, Sladkomedova, A, Slendebroek, T, Slief, J, Smirnov, R, Smith, J, Smith, S, Smith, D, Snipes, J, Snoep, G, Snyder, A, Snyder, P, Solano, E, Solomon, W, Song, J, Sontag, A, Soukhanovskii, V, Spendlove, J, Spong, D, Squire, J, Srinivasan, C, Stacey, W, Staebler, G, Stagner, L, Stange, T, Stangeby, P, Stefan, R, Stemprok, R, Stephan, D, Stillerman, J, Stoltzfus-Dueck, T, Stonecipher, W, Storment, S, Strait, E, Su, D, Sugiyama, L, Sun, Y, Sun, P, Sun, Z, Sun, A, Sundstrom, D, Sung, C, Sungcoco, J, Suttrop, W, Suzuki, Y, Suzuki, T, Svyatkovskiy, A, Swee, C, Sweeney, R, Sweetnam, C, Szepesi, G, Takechi, M, Tala, T, Tanaka, K, Tang, X, Tang, S, Tao, Y, Tao, R, Taussig, D, Taylor, T, Teixeira, K, Teo, K, Theodorsen, A, Thomas, D, Thome, K, Thorman, A, Thornton, A, Ti, A, Tillack, M, Timchenko, N, Tinguely, R, Tompkins, R, Tooker, J, De Sousa, A, Trevisan, G, Tripathi, S, Ochoa, A, Truong, D, Tsui, C, Turco, F, Turnbull, A, Umansky, M, Unterberg, E, Vaezi, P, Vail, P, Valdez, J, Valkis, W, Van Compernolle, B, Van Galen, J, Van Kampen, R, Van Zeeland, M, Verdoolaege, G, Vianello, N, Victor, B, Viezzer, E, Vincena, S, Wade, M, Waelbroeck, F, Wai, J, Wakatsuki, T, Walker, M, Wallace, G, Waltz, R, Wampler, W, Wang, L, Wang, H, Wang, Y, Wang, Z, Wang, G, Ward, S, Watkins, M, Watkins, J, Wehner, W, Wei, Y, Weiland, M, Weisberg, D, Welander, A, White, A, White, R, Wiesen, S, Wilcox, R, Wilks, T, Willensdorfer, M, Wilson, H, Wingen, A, Wolde, M, Wolff, M, Woller, K, Wolz, A, Wong, H, Woodruff, S, Wu, M, Wu, Y, Wukitch, S, Wurden, G, Xiao, W, Xie, R, Xing, Z, Xu, X, Xu, C, Xu, G, Yan, Z, Yang, X, Yang, S, Yokoyama, T, Yoneda, R, Yoshida, M, You, K, Younkin, T, Yu, J, Yu, M, Yu, G, Yuan, Q, Zaidenberg, L, Zakharov, L, Zamengo, A, Zamperini, S, Zarnstorff, M, Zeger, E, Zeller, K, Zeng, L, Zerbini, M, Zhang, L, Zhang, X, Zhang, R, Zhang, B, Zhang, J, Zhao, L, Zhao, B, Zheng, Y, Zheng, L, Zhu, B, Zhu, J, Zhu, Y, Zsutty, M, Zuin, M, Lawrence Livermore National Laboratory, Princeton Plasma Physics Laboratory, Princeton University, General Atomics, Max-Planck-Institut für Plasmaphysik, Imperial College London, National Institute for Fusion Science, Universidade de São Paulo, University of Texas at Austin, ITER, College of William and Mary, University of California Los Angeles, University of California San Diego, Columbia University, Massachusetts Institute of Technology, Oak Ridge National Laboratory, Eindhoven University of Technology, Oak Ridge Associated Universities, West Virginia University, University of Tennessee, Knoxville, National Research Council of Italy, Stony Brook University, Purdue University, University of Seville, University of Science and Technology of China, Carnegie Mellon University, Institute for Plasma Research, Peking University, University of California Davis, University of California Irvine, Commonwealth Fusion Systems, University of Liverpool, University of Illinois at Urbana-Champaign, University of Milan - Bicocca, Georgia Institute of Technology, Southwestern Institute of Physics, University of Toronto, Auburn University, Polytechnic University of Turin, Universidade Lisboa, Association CCFE, KTH Royal Institute of Technology, San Diego State University, Durham University, Lehigh University, Fusion and Plasma Physics, University of Washington, Department of Applied Physics, Sandia National Laboratories, Ghent University, Technical University of Denmark, CEA, University of Colorado Boulder, Harvard University, National Technical University of Athens, Coventry University, University of Stuttgart, Czech Academy of Sciences, Harvey Mudd College, Seoul National University, Donghua University, University of York, Dalian University of Technology, University of California Berkeley, Los Alamos National Laboratory, United States Department of Energy, University of British Columbia, Pacific Northwest National Laboratory, University of Wisconsin, Michigan State University, University of Strathclyde, Pennsylvania State University, Rensselaer Polytechnic Institute, University of Southern California, Chalmers University of Technology, University of Virginia, University of Naples Federico II, University of Oxford, VTT Technical Research Centre of Finland, National Institute of Technology, University of Connecticut, DIFFER, CIEMAT, Hanyang University, Brigham Young University, UiT The Arctic University of Norway, Australian National University, Russian Research Centre Kurchatov Institute, Forschungszentrum Jülich, Zhejiang University, The University of Tokyo, University of Michigan, Agenzia nazionale per le nuove tecnologie, l'energia e lo sviluppo economico sostenibile, Aalto-yliopisto, Aalto University, DIII-D Team, Complex Ionized Media, Elementary Processes in Gas Discharges, Applied Physics and Science Education, Science and Technology of Nuclear Fusion, and Control Systems Technology

Subjects
Nuclear and High Energy Physics, Tokamak, Technology and Engineering, DIII-D, Nuclear engineering, TOKAMAKS, MITIGATION, law.invention, Plasma physics, mitigation, law, plasma physic, tokamak, Physics, Core-edge integration, Basis (linear algebra), plasma physics, core-edge integration, scenarios, Fusion power, Condensed Matter Physics, SCENARIOS, fusion energy, Fusion energy
Abstract

Funding Information: This material is based upon work supported by the US Department of Energy, Office of Science, Office of Fusion Energy Sciences, using the DIII-D National Fusion Facility, a DOE Office of Science user facility, under Awards DE-FC02-04ER54698 and DE-AC52-07NA27344. Publisher Copyright: © 2022 IAEA, Vienna. DIII-D physics research addresses critical challenges for the operation of ITER and the next generation of fusion energy devices. This is done through a focus on innovations to provide solutions for high performance long pulse operation, coupled with fundamental plasma physics understanding and model validation, to drive scenario development by integrating high performance core and boundary plasmas. Substantial increases in off-axis current drive efficiency from an innovative top launch system for EC power, and in pressure broadening for Alfven eigenmode control from a co-/counter-I p steerable off-axis neutral beam, all improve the prospects for optimization of future long pulse/steady state high performance tokamak operation. Fundamental studies into the modes that drive the evolution of the pedestal pressure profile and electron vs ion heat flux validate predictive models of pedestal recovery after ELMs. Understanding the physics mechanisms of ELM control and density pumpout by 3D magnetic perturbation fields leads to confident predictions for ITER and future devices. Validated modeling of high-Z shattered pellet injection for disruption mitigation, runaway electron dissipation, and techniques for disruption prediction and avoidance including machine learning, give confidence in handling disruptivity for future devices. For the non-nuclear phase of ITER, two actuators are identified to lower the L-H threshold power in hydrogen plasmas. With this physics understanding and suite of capabilities, a high poloidal beta optimized-core scenario with an internal transport barrier that projects nearly to Q = 10 in ITER at ∼8 MA was coupled to a detached divertor, and a near super H-mode optimized-pedestal scenario with co-I p beam injection was coupled to a radiative divertor. The hybrid core scenario was achieved directly, without the need for anomalous current diffusion, using off-axis current drive actuators. Also, a controller to assess proximity to stability limits and regulate β N in the ITER baseline scenario, based on plasma response to probing 3D fields, was demonstrated. Finally, innovative tokamak operation using a negative triangularity shape showed many attractive features for future pilot plant operation.

Published
2022
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589. Erratum: "Understanding and control of transport in advanced tokamak regimes in DIII-D" [Phys. Plasmas 7, 1959 (2000)].

Author

Greenfield, C. M., DeBoo, J. C., Luce, T. C., Stallard, B. W., Synakowski, E. J., Baylor, L. R., Burrell, K. H., Casper, T. A., Doyle, E. J., Ernst, D. R., Ferron, J. R., Gohil, P., Groebner, R. J., Lao, L. L., Makowski, M., McKee, G. R., Murakami, M., Petty, C. C., Pinsker, R. I., and Politzer, P.A.

Subjects
TOKAMAKS, ELECTRON transport, ION channels
Abstract

Presents an erratum on an article on understanding and control of transport in advanced tokamak regimes in DIII-D. Revision of the diagram depicting transport barrier in ion thermal channel; Correct equations used in the calculations; Misprint of diagrams.

Published
2000

590. Complex light modulation for lensless image projection

Author

Makowski, M., Siemion, A., Ducin, I., Kakarenko, K., Sypek, M., Siemion, A. M., Suszek, J., Wojnowski, D., Jaroszewicz, Z., and Kolodziejczyk, A.

Abstract

We present a lensless projection of color images based on computer-generated Fourier holograms. Amplitude and phase modulation of three primary-colored laser beams is performed by a matched pair of spatial light modulators. The main advantage of the complex light modulation is the lack of iterative phase retrieval techniques. The advantage is the lack of speckles in the projected images. Experimental results are given and compared with the outcome of classical phase-only modulation.

Published
2011

594. Epidemiology and reporting of osteoporotic vertebral fractures in patients with long-term hospital records based on routine clinical CT imaging.

Author

Löffler, M. T., Kallweit, M., Niederreiter, E., Baum, T., Makowski, M. R., Zimmer, C., and Kirschke, J. S.

Subjects
*SPINE radiography, *OSTEOPOROSIS diagnosis, *BLOOD vessels, *OSTEOPOROSIS, *TUMOR classification, *SEX distribution, *CANCER patients, *RISK assessment, *MEDICAL records, *DISEASE prevalence, *DESCRIPTIVE statistics, *COMPUTED tomography, *ROUTINE diagnostic tests, *LOGISTIC regression analysis, *VERTEBRAL fractures, *BONE fractures, *DISEASE risk factors
Abstract

Summary: Osteoporotic vertebral fractures signify an increased risk of future fractures and mortality and can manifest the diagnosis of osteoporosis. We investigated the prevalence of vertebral fractures in routine CT of patients with long-term hospital records. Three out of ten patients showed osteoporotic vertebral fractures (VFs) corresponding to the highest rates reported in European population-based studies. Introduction: VFs are a common manifestation of osteoporosis, which influences future fracture risk. Their epidemiology has been investigated in population-based studies. However, few studies report the prevalence of osteoporotic VF in patients seen in clinical routine and include all common fracture levels of the thoracolumbar spine. The purpose of this study was to investigate the prevalence of osteoporotic VF in patients with CT scans and long-term hospital records and identify clinical factors associated with prevalent VFs. Methods: All patients aged 45 years and older with a CT scan and prior hospital record of at least 5 years that were seen in the study period between September 2008 and May 2017 were reviewed. Imaging requirements were a CT scan with sagittal reformations including at least T6-L4. Patients with multiple myeloma were excluded. Fracture reading was performed using the Genant semi-quantitative method. Medical notes were reviewed for established diagnoses of osteoporosis and clinical information. Clinical factors (e.g. drug intake, chemotherapy, and mobility level) associated with prevalent VF were identified in logistic regression. Results: The study population consisted of 718 patients (228 women and 490 men; mean age 69.3 ± 10.1 years) with mainly cancer staging and angiography CT imaging. The overall prevalence of VFs was 30.5%, with non-significantly more men showing a fracture (32.5%) compared to women (26.3%; p > 0.05). Intake of metamizole for ≥ 3 months was significantly associated with a prevalent VF. Medical records did not include information about bone health in 90% of all patients. CT reports did mention a VF in only 24.7% of patients with a prevalent VF on CT review. Conclusion: Approximately 30% of elderly patients with CT imaging and long-term hospital records showed VFs. Only one-quarter of these patients had VFs mentioned in CT reports. Osteoporosis management could be improved by consequent reporting of VFs in CT, opportunistic bone density measurements, and early involvement of fracture liaison services. [ABSTRACT FROM AUTHOR]

Published
2022
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595. MR-based proton density fat fraction (PDFF) of the vertebral bone marrow differentiates between patients with and without osteoporotic vertebral fractures.

Author

Gassert, F. T., Kufner, A., Gassert, F. G., Leonhardt, Y., Kronthaler, S., Schwaiger, B. J., Boehm, C., Makowski, M. R., Kirschke, J. S., Baum, T., Karampinos, D. C., and Gersing, A. S.

Subjects
*BIOMARKERS, *STATURE, *BODY weight, *CONFIDENCE intervals, *AGE distribution, *MULTIVARIATE analysis, *MAGNETIC resonance imaging, *REGRESSION analysis, *HEALTH outcome assessment, *OSTEOPOROSIS, *SEX distribution, *PEARSON correlation (Statistics), *T-test (Statistics), *CHI-squared test, *DESCRIPTIVE statistics, *BONE marrow, *BONE density, *COMPUTED tomography, *RECEIVER operating characteristic curves, *DATA analysis software, *VERTEBRAL fractures, *BONE fractures
Abstract

Summary: The bone marrow proton density fat fraction (PDFF) assessed with MRI enables the differentiation between osteoporotic/osteopenic patients with and without vertebral fractures. Therefore, PDFF may be a potentially useful biomarker for bone fragility assessment. Introduction: To evaluate whether magnetic resonance imaging (MRI)-based proton density fat fraction (PDFF) of vertebral bone marrow can differentiate between osteoporotic/osteopenic patients with and without vertebral fractures. Methods: Of the 52 study patients, 32 presented with vertebral fractures of the lumbar spine (66.4 ± 14.4 years, 62.5% women; acute low-energy osteoporotic/osteopenic vertebral fractures, N = 25; acute high-energy traumatic vertebral fractures, N = 7). These patients were frequency matched for age and sex to patients without vertebral fractures (N = 20, 69.3 ± 10.1 years, 70.0% women). Trabecular bone mineral density (BMD) values were derived from quantitative computed tomography. Chemical shift encoding-based water-fat MRI of the lumbar spine was performed, and PDFF maps were calculated. Associations between fracture status and PDFF were assessed using multivariable linear regression models. Results: Over all patients, mean PDFF and trabecular BMD correlated significantly (r = − 0.51, P < 0.001). In the osteoporotic/osteopenic group, those patients with osteoporotic/osteopenic fractures had a significantly higher PDFF than those without osteoporotic fractures after adjusting for age, sex, weight, height, and trabecular BMD (adjusted mean difference [95% confidence interval], 20.8% [10.4%, 30.7%]; P < 0.001), although trabecular BMD values showed no significant difference between the subgroups (P = 0.63). For the differentiation of patients with and without vertebral fractures in the osteoporotic/osteopenic subgroup using mean PDFF, an area under the receiver operating characteristic (ROC) curve (AUC) of 0.88 (P = 0.006) was assessed. When evaluating all patients with vertebral fractures, those with high-energy traumatic fractures had a significantly lower PDFF than those with low-energy osteoporotic/osteopenic vertebral fractures (P < 0.001). Conclusion: MR-based PDFF enables the differentiation between osteoporotic/osteopenic patients with and without vertebral fractures, suggesting the use of PDFF as a potential biomarker for bone fragility. [ABSTRACT FROM AUTHOR]

Published
2022
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600. Prostate Cancer Nodal Staging: Using Deep Learning to Predict 68Ga-PSMA-Positivity from CT Imaging Alone.

Author

Hartenstein, A., Lübbe, F., Baur, A. D. J., Rudolph, M. M., Furth, C., Brenner, W., Amthauer, H., Hamm, B., Makowski, M., and Penzkofer, T.

Subjects
*PROSTATE cancer, *DEEP learning, *COMPUTED tomography, *SEEPAGE, *POLYETHYLENE terephthalate
Abstract

Lymphatic spread determines treatment decisions in prostate cancer (PCa) patients. 68Ga-PSMA-PET/CT can be performed, although cost remains high and availability is limited. Therefore, computed tomography (CT) continues to be the most used modality for PCa staging. We assessed if convolutional neural networks (CNNs) can be trained to determine 68Ga-PSMA-PET/CT-lymph node status from CT alone. In 549 patients with 68Ga-PSMA PET/CT imaging, 2616 lymph nodes were segmented. Using PET as a reference standard, three CNNs were trained. Training sets balanced for infiltration status, lymph node location and additionally, masked images, were used for training. CNNs were evaluated using a separate test set and performance was compared to radiologists' assessments and random forest classifiers. Heatmaps maps were used to identify the performance determining image regions. The CNNs performed with an Area-Under-the-Curve of 0.95 (status balanced) and 0.86 (location balanced, masked), compared to an AUC of 0.81 of experienced radiologists. Interestingly, CNNs used anatomical surroundings to increase their performance, "learning" the infiltration probabilities of anatomical locations. In conclusion, CNNs have the potential to build a well performing CT-based biomarker for lymph node metastases in PCa, with different types of class balancing strongly affecting CNN performance. [ABSTRACT FROM AUTHOR]

Published
2020
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