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1,877 results on '"Huang, S -C"'

6. PET investigation of post-traumatic cerebral blood volume and blood flow

Author

Hattori, Naoya, Huang, S.-C., Wu, H.-M., Liao, W., Glenn, T. C., Vespa, P. M., Phelps, M. E., Hovda, D. A., Bergsneider, M., Steiger, H.-J., editor, Kuroiwa, T., editor, Baethmann, A., editor, Czernicki, Z., editor, Hoff, J. T., editor, Ito, U., editor, Katayama, Y., editor, Marmarou, A., editor, Mendelow, B. A. D., editor, and Reulen, H.-J., editor

Published
2003
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8. Artificial intelligence extension of the OSCAR-IB criteria

Author

Petzold, A., Albrecht, P., Balcer, L., Bekkers, E., Brandt, A. U., Calabresi, P. A., Deborah, O. G., Graves, J. S., Green, A., Keane, P. A., Nij Bijvank, J. A., Sander, J. W., Paul, F., Saidha, S., Villoslada, P., Wagner, S. K., Yeh, E. A., Aktas, O., Antel, J., Asgari, N., Audo, I., Avasarala, J., Avril, D., Bagnato, F. R., Banwell, B., Bar-Or, A., Behbehani, R., Manterola, A. B., Bennett, J., Benson, L., Bernard, J., Bremond-Gignac, D., Britze, J., Burton, J., Calkwood, J., Carroll, W., Chandratheva, A., Cohen, J., Comi, G., Cordano, C., Costa, S., Costello, F., Courtney, A., Cruz-Herranz, A., Cutter, G., Crabb, D., Delott, L., De Seze, J., Diem, R., Dollfuss, H., El Ayoubi, N. K., Fasser, C., Finke, C., Fischer, D., Fitzgerald, K., Fonseca, P., Frederiksen, J. L., Frohman, E., Frohman, T., Fujihara, K., Cuellar, I. G., Galetta, S., Garcia-Martin, E., Giovannoni, G., Glebauskiene, B., Suarez, I. G., Jensen, G. P., Hamann, S., Hartung, H. -P., Havla, J., Hemmer, B., Huang, S. -C., Imitola, J., Jasinskas, V., Jiang, H., Kafieh, R., Kappos, L., Kardon, R., Keegan, D., Kildebeck, E., Kim, U. S., Klistorner, S., Knier, B., Kolbe, S., Korn, T., Krupp, L., Lagreze, W., Leocani, L., Levin, N., Liskova, P., Preiningerova, J. L., Lorenz, B., May, E., Miller, D., Mikolajczak, J., Said, S. M., Montalban, X., Morrow, M., Mowry, E., Murta, J., Navas, C., Nolan, R., Nowomiejska, K., Oertel, F. C., Oh, J., Oreja-Guevara, C., Orssaud, C., Osborne, B., Outteryck, O., Paiva, C., Palace, J., Papadopoulou, A., Patsopoulos, N., Pontikos, N., Preising, M., Prince, J., Reich, D., Rejdak, R., Ringelstein, M., Rodriguez de Antonio, L., Sahel, J. -A., Sanchez-Dalmau, B., Sastre-Garriga, J., Schippling, S., Schuman, J., Shindler, K., Shin, R., Shuey, N., Soelberg, K., Specovius, S., Suppiej, A., Thompson, A., Toosy, A., Torres, R., Touitou, V., Trauzettel-Klosinski, S., van der Walt, A., Vermersch, P., Vidal-Jordana, A., Waldman, A. T., Waters, C., Wheeler, R., White, O., Wilhelm, H., Winges, K. M., Wiegerinck, N., Wiehe, L., Wisnewski, T., Wong, S., Wurfel, J., Yaghi, S., You, Y., Yu, Z., Yu-Wai-Man, P., Zemaitien≐, R., Zimmermann, H., Albrecht P., Petzold A., Balcer, L., Bekkers, E., Brandt, A. U., Calabresi, P. A., Deborah, O. G., Graves, J. S., Green, A., Keane, P. A., Nij Bijvank, J. A., Sander, J. W., Paul, F., Saidha, S., Villoslada, P., Wagner, S. K., Yeh, E. A., Aktas, O., Antel, J., Asgari, N., Audo, I., Avasarala, J., Avril, D., Bagnato, F. R., Banwell, B., Bar-Or, A., Behbehani, R., Manterola, A. B., Bennett, J., Benson, L., Bernard, J., Bremond-Gignac, D., Britze, J., Burton, J., Calkwood, J., Carroll, W., Chandratheva, A., Cohen, J., Comi, G., Cordano, C., Costa, S., Costello, F., Courtney, A., Cruz-Herranz, A., Cutter, G., Crabb, D., Delott, L., De Seze, J., Diem, R., Dollfuss, H., El Ayoubi, N. K., Fasser, C., Finke, C., Fischer, D., Fitzgerald, K., Fonseca, P., Frederiksen, J. L., Frohman, E., Frohman, T., Fujihara, K., Cuellar, I. G., Galetta, S., Garcia-Martin, E., Giovannoni, G., Glebauskiene, B., Suarez, I. G., P. , Jensen, G., Hamann, S., Hartung, H. -P., Havla, J., Hemmer, B., Huang, S. -C., Imitola, J., Jasinskas, V., Jiang, H., Kafieh, R., Kappos, L., Kardon, R., Keegan, D., Kildebeck, E., Kim, U. S., Klistorner, S., Knier, B., Kolbe, S., Korn, T., Krupp, L., Lagreze, W., Leocani, L., Levin, N., Liskova, P., Preiningerova, J. L., Lorenz, B., May, E., Miller, D., Mikolajczak, J., Said, S. M., Montalban, X., Morrow, M., Mowry, E., Murta, J., Navas, C., Nolan, R., Nowomiejska, K., Oertel, F. C., Oh, J., Oreja-Guevara, C., Orssaud, C., Osborne, B., Outteryck, O., Paiva, C., Palace, J., Papadopoulou, A., Patsopoulos, N., Pontikos, N., Preising, M., Prince, J., Reich, D., Rejdak, R., Ringelstein, M., Rodriguez de Antonio, L., Sahel, J. -A., Sanchez-Dalmau, B., Sastre-Garriga, J., Schippling, S., Schuman, J., Shindler, K., Shin, R., Shuey, N., Soelberg, K., Specovius, S., Suppiej, A., Thompson, A., Toosy, A., Torres, R., Touitou, V., Trauzettel-Klosinski, S., van der Walt, A., Vermersch, P., Vidal-Jordana, A., Waldman, A. T., Waters, C., Wheeler, R., White, O., Wilhelm, H., Winges, K. M., Wiegerinck, N., Wiehe, L., Wisnewski, T., Wong, S., Wurfel, J., Yaghi, S., You, Y., Yu, Z., Yu-Wai-Man, P., Zemaitien≐, R., and Zimmermann, H.

Subjects
0301 basic medicine, Big Data, medicine.medical_specialty, Neurology, media_common.quotation_subject, Big data, MEDLINE, Reviews, Socio-culturale, Neurosciences. Biological psychiatry. Neuropsychiatry, Review, Public domain, Retina, Cohort Studies, 03 medical and health sciences, Annotation, 0302 clinical medicine, Artificial Intelligence, medicine, Humans, Quality (business), RC346-429, Tomography, media_common, Image pattern recognition, business.industry, General Neuroscience, Nervous System Diseases, Tomography, Optical Coherence, Algorithms, 030104 developmental biology, Optical Coherence, Imaging technology, RC0321, Neurology. Diseases of the nervous system, Neurology (clinical), Artificial intelligence, sense organs, business, 030217 neurology & neurosurgery, RC321-571
Abstract

Artificial intelligence (AI)‐based diagnostic algorithms have achieved ambitious aims through automated image pattern recognition. For neurological disorders, this includes neurodegeneration and inflammation. Scalable imaging technology for big data in neurology is optical coherence tomography (OCT). We highlight that OCT changes observed in the retina, as a window to the brain, are small, requiring rigorous quality control pipelines. There are existing tools for this purpose. Firstly, there are human‐led validated consensus quality control criteria (OSCAR‐IB) for OCT. Secondly, these criteria are embedded into OCT reporting guidelines (APOSTEL). The use of the described annotation of failed OCT scans advances machine learning. This is illustrated through the present review of the advantages and disadvantages of AI‐based applications to OCT data. The neurological conditions reviewed here for the use of big data include Alzheimer disease, stroke, multiple sclerosis (MS), Parkinson disease, and epilepsy. It is noted that while big data is relevant for AI, ownership is complex. For this reason, we also reached out to involve representatives from patient organizations and the public domain in addition to clinical and research centers. The evidence reviewed can be grouped in a five‐point expansion of the OSCAR‐IB criteria to embrace AI (OSCAR‐AI). The review concludes by specific recommendations on how this can be achieved practically and in compliance with existing guidelines.

Published
2021

9. Learning Styles and Formative Assessment Strategy: Enhancing Student Achievement in Web-Based Learning

Author

Wang, K. H., Wang, T. H., Wang, W. L., and Huang, S. C.

Abstract

The purpose of this research was to investigate the effects of formative assessment and learning style on student achievement in a Web-based learning environment. A quasi-experimental research design was used. Participants were 455 seventh grade students from 12 classes of six junior high schools. A Web-based course, named BioCAL, combining three different formative assessment strategies was developed. The formative assessment strategies included Formative Assessment Module of the Web-Based Assessment and Test Analysis system (FAM-WATA) (with six Web-based formative assessment strategies), Normal Module of Web-Based Assessment and Test Analysis system (N-WATA) (only with partial Web-based formative assessment strategy) and Paper and Pencil Test (PPT) (without Web-based formative assessment strategy). Subjects were tested using Kolb's Learning Style Inventory, and assigned randomly by class into three groups. Each group took Web-based courses using one of the formative assessment strategies. Pre- and post-achievement testing was carried out. A one-way ANCOVA analysis showed that both learning style and formative assessment strategy are significant factors affecting student achievement in a Web-based learning environment. However, there is no interaction between these two factors. A "post hoc" comparison showed that performances of the FAM-WATA group are higher than the N-WATA and PPT groups. Learners with a "Diverger" learning style performed best followed by, "Assimilator", "Accommodator", and "Converger", respectively. Finally, FAM-WATA group students are satisfied with six strategies of the FAM-WATA.

Published
2006
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10. Reaction hijacking of tyrosine tRNA synthetase as a new whole-of-life-cycle antimalarial strategy

Author

Xie, SC, Metcalfe, RD, Dunn, E, Morton, CJ, Huang, S-C, Puhalovich, T, Du, Y, Wittlin, S, Nie, S, Luth, MR, Ma, L, Kim, M-S, Pasaje, CFA, Kumpornsin, K, Giannangelo, C, Houghton, FJ, Churchyard, A, Famodimu, MT, Barry, DC, Gillett, DL, Dey, S, Kosasih, CC, Newman, W, Niles, JC, Lee, MCS, Baum, J, Ottilie, S, Winzeler, EA, Creek, DJ, Williamson, N, Parker, MW, Brand, S, Langston, SP, Dick, LR, Griffin, MDW, Gould, AE, Tilley, L, Xie, SC, Metcalfe, RD, Dunn, E, Morton, CJ, Huang, S-C, Puhalovich, T, Du, Y, Wittlin, S, Nie, S, Luth, MR, Ma, L, Kim, M-S, Pasaje, CFA, Kumpornsin, K, Giannangelo, C, Houghton, FJ, Churchyard, A, Famodimu, MT, Barry, DC, Gillett, DL, Dey, S, Kosasih, CC, Newman, W, Niles, JC, Lee, MCS, Baum, J, Ottilie, S, Winzeler, EA, Creek, DJ, Williamson, N, Parker, MW, Brand, S, Langston, SP, Dick, LR, Griffin, MDW, Gould, AE, and Tilley, L

Abstract

Aminoacyl transfer RNA (tRNA) synthetases (aaRSs) are attractive drug targets, and we present class I and II aaRSs as previously unrecognized targets for adenosine 5'-monophosphate-mimicking nucleoside sulfamates. The target enzyme catalyzes the formation of an inhibitory amino acid-sulfamate conjugate through a reaction-hijacking mechanism. We identified adenosine 5'-sulfamate as a broad-specificity compound that hijacks a range of aaRSs and ML901 as a specific reagent a specific reagent that hijacks a single aaRS in the malaria parasite Plasmodium falciparum, namely tyrosine RS (PfYRS). ML901 exerts whole-life-cycle-killing activity with low nanomolar potency and single-dose efficacy in a mouse model of malaria. X-ray crystallographic studies of plasmodium and human YRSs reveal differential flexibility of a loop over the catalytic site that underpins differential susceptibility to reaction hijacking by ML901.

Published
2022

17. The Effects of Three Aural Advance Organizers for Video Viewing in a Foreign Language.

Author

Chung, J. M. and Huang, S. C.

Abstract

Investigated the effects of three aural-advance organizers on student comprehension of second-language (L2) videotaped materials. Subjects were 160 low-intermediate Chinese students of English in Taiwan. Suggests that in preparing advance organizers for English-as-a-Foreign-Language students, teachers should focus on new words rather than on video characters. (Author/VWL)

Published
1998

19. List of contributors

Author

Audo, M., primary, Beiswenger, J., additional, Bhasin, A., additional, Branthaver, J.F., additional, Cebon, D., additional, Chailleux, E., additional, Cheung, C.Y., additional, Cookman, A., additional, Darabi, M.K., additional, Di Benedetto, H., additional, Goyer, S., additional, Hernando, D., additional, Huang, S.-C., additional, James, A., additional, Kringos, N., additional, Little, D.N., additional, Luo, R., additional, Luo, X., additional, Lytton, R.L., additional, Marzouk, O., additional, Mohajeri, M., additional, Molenaar, A.A.A., additional, Olard, F., additional, Pauli, A.T., additional, Pouget, S., additional, Queffelec, C., additional, Roque, R., additional, Sauzeat, C., additional, Southern, M., additional, Takamura, K., additional, Underwood, B.S., additional, Van de Ven, M.F.C., additional, Varveri, A., additional, Grimes, R. Will, additional, Zhang, Y., additional, Zhu, J., additional, and Zou, J., additional

Published
2015
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36. Vision, challenges and opportunities for a Plant Cell Atlas

Author

National Science Foundation (US), Plant Cell Atlas, Consortium, Romero, Luis C., Brumós Fuentes, Javier, Corpas, Francisco J., Palma Martínez, José Manuel, Jha, S. G., Borowsky, A. T., Cole, B. J., Fahlgren, N., Farmer, Andrew, Huang, S. C., Karia, P., Libault, M., Provart, N. J., Rice, S. L., Saura-Sanchez, M., Agarwal, P., Ahkami, A. H., Anderton, C. R., Briggs, S. P., Brophy, J. A., Denolf, P., Di Costanzo, L. F., Exposito-Alonso, Moises, Giacomello, S., Gomez-Cano, F., Kaufmann, K., Ko, D. K., Kumar, Sumit, Malkovskiy, A. V., Nakayama, N., Obata, T., Otegui, M. S., Palfalvi, G., Quezada-Rodriguez, E. H., Singh, R., Uhrig, R. G., Waese, J., Van Wijk, K., Wright, R. C., Ehrhardt, D. W., Birnbaum, K. D., Rhee, S. Y., National Science Foundation (US), Plant Cell Atlas, Consortium, Romero, Luis C., Brumós Fuentes, Javier, Corpas, Francisco J., Palma Martínez, José Manuel, Jha, S. G., Borowsky, A. T., Cole, B. J., Fahlgren, N., Farmer, Andrew, Huang, S. C., Karia, P., Libault, M., Provart, N. J., Rice, S. L., Saura-Sanchez, M., Agarwal, P., Ahkami, A. H., Anderton, C. R., Briggs, S. P., Brophy, J. A., Denolf, P., Di Costanzo, L. F., Exposito-Alonso, Moises, Giacomello, S., Gomez-Cano, F., Kaufmann, K., Ko, D. K., Kumar, Sumit, Malkovskiy, A. V., Nakayama, N., Obata, T., Otegui, M. S., Palfalvi, G., Quezada-Rodriguez, E. H., Singh, R., Uhrig, R. G., Waese, J., Van Wijk, K., Wright, R. C., Ehrhardt, D. W., Birnbaum, K. D., and Rhee, S. Y.

Abstract

With growing populations and pressing environmental problems, future economies will be increasingly plant-based. Now is the time to reimagine plant science as a critical component of fundamental science, agriculture, environmental stewardship, energy, technology and healthcare. This effort requires a conceptual and technological framework to identify and map all cell types, and to comprehensively annotate the localization and organization of molecules at cellular and tissue levels. This framework, called the Plant Cell Atlas (PCA), will be critical for understanding and engineering plant development, physiology and environmental responses. A workshop was convened to discuss the purpose and utility of such an initiative, resulting in a roadmap that acknowledges the current knowledge gaps and technical challenges, and underscores how the PCA initiative can help to overcome them.

Published
2021

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