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4. Lindsay Lohan 229 Success Facts : Everything You Need to Know About Lindsay Lohan

Author

Estrada, Alan and Estrada, Alan

Subjects
Actors--United States--Biography, Actors--United States--Miscellanea
Abstract

Lindsay Morgan Lohan'(born'Lindsay Dee Lohan'; July 2, 1986) is an American female actor, model and transcriptioning creator. She started her vocation as a kid style type once she was 3, and was afterward highlighted onto the soap production Another World (TV series)|Another World for a annum once she was 10. At age 11, Lohan produced her motion depiction first public appearance within Walt Disney Pictures|Disney's recreate of The Parent Trap (1998 film)|The Parent Trap (1998), a serious and profit-oriented hit. Her following motion depiction, Disney's recreate of Freaky Friday (2003 film)|Freaky Friday (2003), was as well a triumph at the Box Office and with reviewers. With the discharge of Mean Girls (2004), one other serious and profit-oriented triumph, Lohan grew to be a family designation and a recurrent center of paparazzi and tabloids. The 2 features received her some MTV Movie Awards and Teen Choice Awards.This book is your ultimate resource for Lindsay Lohan. Here you will find the most up-to-date 229 Success Facts, Information, and much more.In easy to read chapters, with extensive references and links to get you to know all there is to know about Lindsay Lohan's Early life, Career and Personal life right away. A quick look inside: Cold Spring Harbor High School - Notable alumni, YoungStar Award - Best Young Actress in a Comedy Film, 1998 in film - L-Q, Merrick, New York - Notable people, 25th Young Artist Awards - Best Performance in a Feature Film - Leading Young Actress, Eating disorder - Cultural pressure, Herbie: Fully Loaded - Soundtrack, Oh No They Didn't - Community culture, The Parent Trap (1961 film) - Subsequent developments, I Know Who Killed Me - Critical reception, Michael Lohan - Personal life, Halle Berry - Career, Tommy Mottola - After Sony, Herbie: Fully Loaded - Awards, Tyra Banks - Move into television and film, King of the Hill - Characters, Abercrombie kids - History, and much more…

Published
2014

5. A Crowdsourcing Approach to Developing and Assessing Prediction Algorithms for AML Prognosis

Author

Noren, David P., Long, Byron L., Norel, Raquel, Rrhissorrakrai, Kahn, Hess, Kenneth, Chenyue Wendy, Hu, Bisberg, Alex J., Schultz, Andre, Engquist, Erik, Liu, Li, Lin, Xihui, Chen, Gregory M., Xie, Honglei, Hunter, Geoffrey A. M., Boutros, Paul C., Stepanov, Oleg, Abrams, Zachary, Ambrosini, Giovanna, Anastassiou, Dimitris, Baladandayuthapani, Veerabhadran, Batten, Kimberly, Bucher, Philipp, Buturovic, Ljubomir, Campion, Loic, Creighton, Chad J., Chen, Greg, Cheong, Jae Ho, DI CAMILLO, Barbara, Dreos, René, Estrada, Alan, Fatemi, Seyyed A., Fitzgerald, Andrew, Flynn, Jennifer, Fronczuk, Maciej, Weiyi, Gu, Guha, Subharup, Hosseini, Maryam, Hung, Ling Hong, Hunter, Geoffrey, Hwang, Tae Hyun, Kim, Daniel, Kim, Minsoo, Korra, Jyothi, Krstajic, Damjan, Kumar, Sunil, Kuh, Anthony, Jinpu, Li, Liu, Yashu, Mcmurray, James, Morgan, Daniel, Motiwala, Tasneem, Naegle, Kristen, Niemiec, Rafał, Oehler, Vivian G., Park, Sunho, Pattin, Alejandrina, Peabody, Andrea, Piraino, Scott W., Regan, Kelly, Ronan, Tom, Rościszewski, Antoni, Rudnicki, Witold, Sanavia, Tiziana, Santhanam, Narayana, Shay, Jerry, Tang, Hao, Vilar, Jose M. G., Wang, Tao, Wright, Woodring, Wrzesień, Mariusz, Xiao, Guanghua, Xie, Yang, Yang, Sen, Yang, Tai Hsien Ou, Yang, Tao, Jieping, Ye, Yeung, Ka Yee, Zang, Xiao, Zolfaghar, Kiyana, Żuk, Paweł, Norman, Thea, Friend, Stephen H., Stolovitzky, Gustavo, Kornblau, Steven, Qutub, Amina A., and Tan, Kai

Subjects
Proteomics, 0301 basic medicine, Myeloid, Proteome, Cancer Treatment, Bioinformatics, Patient response, Biochemistry, Systems Science, Mathematical Sciences, Hematologic Cancers and Related Disorders, Machine Learning, Database and Informatics Methods, 0302 clinical medicine, Medicine and Health Sciences, lcsh:QH301-705.5, Cancer, Pediatric, screening and diagnosis, Ecology, Proteomic Databases, Systems Biology, Myeloid leukemia, Hematology, Biological Sciences, Myeloid Leukemia, Prognosis, 3. Good health, Detection, Prediction algorithms, Outcome and Process Assessment, Health Care, Treatment Outcome, medicine.anatomical_structure, Oncology, Computational Theory and Mathematics, 030220 oncology & carcinogenesis, Modeling and Simulation, Physical Sciences, Crowdsourcing, Risk assessment, Algorithms, Research Article, Acute Myeloid Leukemia, DREAM 9 AML-OPC Consortium, Computer and Information Sciences, Childhood Leukemia, Pediatric Cancer, Research and Analysis Methods, Outcome and Process Assessment, Risk Assessment, Sensitivity and Specificity, 03 medical and health sciences, Cellular and Molecular Neuroscience, Rare Diseases, Diagnostic Medicine, Artificial Intelligence, Information and Computing Sciences, Leukemias, Genetics, medicine, Humans, Acute Myeloid Leukemia, Prediction algorithms, Machine Learning, Bioinformatics, Molecular Biology, Ecology, Evolution, Behavior and Systematics, business.industry, Amyotrophic Lateral Sclerosis, Cancers and Neoplasms, Biology and Life Sciences, Reproducibility of Results, Human Genetics, Outcome and Process Assessment (Health Care), medicine.disease, Human genetics, 4.1 Discovery and preclinical testing of markers and technologies, Health Care, Biological Databases, 030104 developmental biology, lcsh:Biology (General), 13. Climate action, Cognitive Science, business, Mathematics, Biomarkers, Neuroscience
Abstract

Acute Myeloid Leukemia (AML) is a fatal hematological cancer. The genetic abnormalities underlying AML are extremely heterogeneous among patients, making prognosis and treatment selection very difficult. While clinical proteomics data has the potential to improve prognosis accuracy, thus far, the quantitative means to do so have yet to be developed. Here we report the results and insights gained from the DREAM 9 Acute Myeloid Prediction Outcome Prediction Challenge (AML-OPC), a crowdsourcing effort designed to promote the development of quantitative methods for AML prognosis prediction. We identify the most accurate and robust models in predicting patient response to therapy, remission duration, and overall survival. We further investigate patient response to therapy, a clinically actionable prediction, and find that patients that are classified as resistant to therapy are harder to predict than responsive patients across the 31 models submitted to the challenge. The top two performing models, which held a high sensitivity to these patients, substantially utilized the proteomics data to make predictions. Using these models, we also identify which signaling proteins were useful in predicting patient therapeutic response., Author Summary Acute Myeloid Leukemia (AML) is a hematological cancer with a very low 5-year survival rate. It is a very heterogeneous disease, meaning that the molecular underpinnings that cause AML vary greatly among patients, necessitating the use of precision medicine for treatment. While this personalized approach could be greatly improved by the incorporation of high-throughput proteomics data into AML patient prognosis, the quantitative methods to do so are lacking. We held the DREAM 9 AML Outcome Prediction Challenge to foster support, collaboration, and participation from multiple scientific communities in order to solve this problem. The outcome of the challenge yielded several accurate methods (AUROC >0.78, BAC > 0.69) capable of predicting whether a patient would respond to therapy. Moreover, this study also determined aspects of the methods which enabled accurate predictions, as well as key signaling proteins that were informative to the most accurate models.

Published
2016

7. Guía Mexicana de Práctica Clínica de Inmunoterapia 2011.

Author

Larenas-Linnemann, Désirée, Ortega-Martell, José Antonio, del Río-Navarro, Blanca, Rodríguez-Pérez, Noel, Arias-Cruz, Alfredo, Estrada, Alan, Becerril-Ángeles, Martín, Pietropaolo-Cienfuegos, Dino R., de Jesús Ambriz-Moreno, Maria, Báez-Loyola, Carlos, Cossío-Ochoa, Enna, González-Díaz, Sandra Nora, Hidalgo-Castro, Emilia María, Huerta-Hernández, Rosa Elena, Macías-Weinmann, Alejandra, Oyoqui-Flores, Joel, Stone-Aguilar, Héctor, Belinda Treviño-Salinas, Marisol, and del Carmen Zárate-Hernández, María

Subjects
PHYSICIAN practice patterns, IMMUNOTHERAPY, ALLERGIES, SKIN tests, ALLERGENS, RHINITIS, ATOPIC dermatitis, PATIENTS, THERAPEUTICS
Abstract

Copyright of Revista Alergia de Mexico is the property of Coleg. Mexicano de Inmunologia Clinica y Alergia A.C.; Soc. Lat. de Alergia, Asma e Inmunologia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2011

8. [Mexican clinical practice guidelines of immunotherapy 2011].

Author

Larenas-Linnemann D, Ortega-Martell JA, Del Río-Navarro B, Rodríguez-Pérez N, Arias-Cruz A, Estrada A, Becerril-Ángeles M, Pietropaolo-Cienfuegos DR, Ambriz-Moreno Mde J, Báez-Loyola C, Cossío-Ochoa E, González-Díaz SN, Hidalgo-Castro EM, Huerta-Hernández RE, Macías-Weinmann A, Oyoqui-Flores J, Stone-Aguilar H, Treviño-Salinas MB, and Zárate-Hernández Mdel C

Subjects
Allergens therapeutic use, Animals, Asthma therapy, Humans, Pyroglyphidae immunology, Skin Tests, Sublingual Immunotherapy, Desensitization, Immunologic, Hypersensitivity
Abstract

Background: Several international guidelines on immunotherapy exist, but they only apply partially in Mexico. The Mexican guideline of immunotherapy dates from 1998., Objectives: To establish clinical recommendations and suggestions for Allergy residents and specialists for skin testing and allergen immunotherapy based on evidence and Mexican expert opinion, according to the GRADE system., Methods: The guidelines were developed following the methodology of a guideline for clinical practice starting with the formulation of clinical questions, in the context of Mexican environmental conditions and morbidity, with the participation of allergists from all regions of the country. External validation was obtained. Its development followed three steps: 1. formulation of 24 clinical questions. 2. Search for consensus on the answers among members of the Regional chapters of both Mexican Colleges of Allergists (CMICA and COMPEDIA) during regional meetings. 3. Literature search for articles related to the questions and grading of its quality according to GRADE., Results: Based on the regional consensus, 116 articles and the safety, patient acceptance/ comfort and cost clinical recommendations and suggestions were developed on basic aspects of skin testing, subcutaneous and sublingual immunotherapy (patient preparation, vial preparation and application schedules) and the treatment of eventual adverse reactions., Conclusions: A clinical guideline was developed respecting particular methodology, validated by CMICA and COMPEDIA for its implementation among Mexican allergists. Several aspects deserve further study to improve scientific evidence., Keywords: Allergen immunotherapy, subcutaneous immunotherapy, sublingual immunotherapy, skin testing, allergy diagnosis, rhinitis, asthma, atopic dermatitis, house dust mite, pollens, anaphylaxis, adrenaline, Mexico.

Published
2011

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