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3. Therapeutic efficacy of amygdaline and amygdaline-loaded niosomes in a rat model of Alzheimer’s disease via oxidative stress, brain neurotransmitters, and apoptotic pathway

Author

Ahmed H. El-Banna, Fatma I. Abo El-Ela, Ahmed Abdel-Wahab, Amr Gamal, Abdel-Razik H. Abdel-Razik, Hossny A. El-Banna, Salma.I. Elsamannoudy, Marwa A. Ibrahim, and Asmaa K. Abdelghany

Subjects
Alzheimer’s disease, Amygdaline, Brain neurotransmitters, Cognitive impairment, Molecular measures, Niosomes, Medicine (General), R5-920, Science
Abstract

Abstract Background Alzheimer’s disease (AD) is a specific form of neurodegeneration that is marked by impairments in memory and cognition. Exposure to some metal toxins, such as aluminum (AL), was directly linked to the onset of AD as it was hosted in the body via several exposure routes and can change the permeability and cross the blood–brain barrier. Due to amygdaline’s existence, apricot kernel therapy for AD is believed to have been established to be successful in numerous investigations. Amygdaline has been shown to have antioxidant effects that mitigate oxidative damage, and free radicals scavenger activity, as well as amygdaline niosomes as a nanoparticle has been found to improve the drug’s efficiency and selectivity. The objectives of this investigation are to study the neuroprotective role of amygdaline, and amygdaline-loaded niosomes formulation in the diminishment of the incidence of AD in neurotoxin (aluminum chloride; AlCl3) AD animal model. Results Data revealed that AlCl3 caused cognitive decline that was confirmed by cognitive behavioral tests (novel object and Y-maze); biochemical disturbances that include marked oxidative stress (elevated malondialdehyde and reduced total antioxidant capacity), reduced acetylcholinesterase, and brain monoamines levels (nor adrenalin; 4-dihydroxyphenylacetic acid; 5-hydroxytryptamine /serotonin; dopamine), and gene regulation upset (down-regulated transcript levels of acetylcholinesterase; monoamine oxidase; BCL-2 and up-regulated transcript levels of BAX), as well as neurodegenerative changes were observed in the hippocampus of AlCl3-treated rats. Treatment with amygdaline and amygdaline-loaded niosomes formulation improved working memory and recognition, alleviated oxidative stress, and restored the levels of brain monoamines and neurotransmitters. Moreover, gene expression data showed a significant down-regulation of BAX, while BCL-2, acetylcholinesterase, and monoamine oxidase were significantly up-regulated. Additionally, the histopathological examination showed reduced neurodegeneration. Conclusion Conclusively, it was evident that amygdaline and amygdaline-loaded niosomes formulation possess a neuroprotective and cognitive enhancement role in AD via their potent antioxidant potential, neurotransmitters, and gene expression regulations, as well as neural damage reduction capability. Graphical abstract

Published
2024
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4. Relationship between dominant decision-making style and creativity of nursing managers: A cross-sectional study

Author

Eman Kamel Hossny and Hammad S. Alotaibi

Subjects
Decision- making styles, Managerial creativity, Nursing managers, Rational style, Nursing, RT1-120
Abstract

Abstract Objective This study aims to investigate the connection between dominant decision-making style and creativity among nursing managers. Background The dominant style of decision-making nursing managers use definitely affects the quality of decisions. Also, in another way, it can develop a skill of creative thinking that may influence the entire health care system. Methods Data from 229 nursing managers in four university hospitals were gathered using a cross-sectional study methodology and questionnaires about general decision-making styles and managerial creativity. Results nursing managers are highly creative. In general, the dominant decision-making style is rational and is correlated positively with creativity. Dependent style is the second one, while it is correlated negatively and significantly with creativity. Intuitive style is the third one and correlated negatively but is insignificant with creativity. Regression analysis revealed that only three styles have an effect on creativity: rational (positive), dependent (negative), and avoidant (negative), respectively. Conclusion The most dominant style is rational, which has the highest effect, which is positive on creativity. The dependent is the second dominant style and has a negative effect. Whereas intuitive is the third dominant style and did not have any effect on creativity.

Published
2024
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7. Epidemiology of Diabetes Mellitus in School-Aged Children in Qena Governorate

Author

Khaled Abdullah, Ali Helmy, and Maha Hossny Abu Elhassan

Subjects
type 1 diabetes school-aged children epidemiology, Medicine
Abstract

Background: Previously called juvenile diabetes, this autoimmune illness causes the pancreas' islets of Langerhans to generate little or no insulin. Frequent urination, thirst, hunger, and weight loss are symptoms. DM has many causes. Objectives: To assesses demographic characteristics of type 1 diabetes mellitus in children aged 6-12 years in Qena governorate. Patients and methods: This is an analytical observation cross-sectional study conducted at the Outpatient Pediatric Clinic, Pediatric Department of Qena University Hospital, and General Hospital in Qena on 100 children. Assessment of these children was done using a written questionnaire based on WHO criteria for the diagnosis of DM. Results: The mean age of studied patients was 8.72± 1.67 years, there were 63 males (63%) and 37 females (37%), there were 19 patients (19%) of white race and 81 patients (81%) of black race. there were 54 patients (54%) from rural areas and 46 patients (46%) from urban areas. As regard SES, there were 77 patients (77%) of low SES and 23 patients (23%) of moderate SES in the studied patients. There were 17 patients (17%) of positive consanguinity and 6 patients (60%) of positive family history in the studied patients. The mean BMI of studied patients was 17.1 ± 2.2 (median = 16.5).. As regard comorbidities, there were 3 patients (3%) had bronchial asthma, 2 patients (2%) had Celiac disease and 1 patient (1%) had epilepsy in the studied patients. There were 3 patients (3%) on steroid inhaler in the studied patients. There was history of acute complications in 59 patients (59%), history of repeated infection in 65 patients (65%) and hospital admission in 59 patients (59%). 17 patients (28.8%) were admitted once, 22 patients (37.3%) were admitted twice and 20 patients (33.9%) were admitted 3 times. There were 26 patients (44.1%) admitted due to DKA, 23 patients (39 %) admitted due to hyperglycemia and 10 patients (16.9%) admitted due to hypoglycemia. Conclusion: The mean age of studied patients was 8.72± 1.67 years, with predominance of males (63%). 54% from rural areas. Acute complications were occurred in 59% of patients.

Published
2024
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8. Perceptions of the impact of individual allergic rhinitis symptoms: A survey of ARIA clinical experts

Author

Sara Gil-Mata, MD, Tatiana Teixeira, MD, Anna Bedbrook, BSc, Jean Bousquet, PhD, Bernardo Sousa-Pinto, PhD, Rafael José Vieira, MD, Julijana Asllani, Habib Douagui, Estrella Asayag, Castro Maria Elizabeth, Carlos D. Crisci, René Maximiliano Gomez, Juan Carlos Ivancevich, Edgardo Jares, Jorge Fernando Máspero, Pablo Moreno, Hugo Eduardo Neffen, Mario Emilio Zernotti, Sinthia Bosnic-Anticevich, Kristin Chahhoud Carson, Biljana Cvetkovski, Janet M. Davies, Vicky Kritikos, Robyn O'Hehir, Brian Oliver, House Rachel Tan, Jessica Tattersall, Celia Zubrinich, Werner Aberer, Verena Niederberger-Leppin, Isabella Pali-Schöll, Virginie Doyen, Didier Ebo, Renaud Louis, Philippe Rombaux, Sophie Scheire, Kazi Bennoor, Bruno A. Barreto, Paulo Camargos, Herberto Jose Chong-Neto, Alvaro A. Cruz, Jane da Silva, Guidacci Marta, José Angelo Rizzo, Nelson Rosario Filho, Sarquis Serpa Faradiba, Dirceu Solé, Marilyn Urrutia-Pereira, George Christoff, Mandazhieva-Pepelanova Mariana, Odjakova Cvetanka, Todor A. Popov, Dilyana Vicheva, do Ceu Teixeira Maria, Jacques Bouchard, Jan Brozek, Derek K. Chu, Judah Denburg, Thomas Eiwegger, Paul K. Keith, Teresa To, Susan Waserman, Nancy Abusada, Emilio Alvarez Cuesta, Mario A. Calvo-Gil, Maria Antonieta Guzmán, Tamara Pérez Gomez, Wing Kin Wong Gary, Luo Zhang, Luis Caraballo, Alfonso Cepeda Sarabia, Dieudonné Nyembue, Manuel Soto-Martinez, Neven Miculinic, Davor Plavec, Constantinos Pitsios, Panayiotis Yiallouros, Petr Panzner, Milan Sova, Martina Vachova, Carsten Bindslev-Jensen, Ronald Dahl, Hans-Jorgen Malling, Lars Münter, Lars K. Poulsen, Suppli Ulrik Charlotte, Line Kring Tannert, Bassam Mahboub, Laila Salameh, Ivan Cherrez-Ojeda, de Guevara Karla Robles, Rasha Hassan El-Owaidy, Zeinab A. El-Sayed, Shereen Saad El-Sayed, Elham Hossny, Badr Eldin Mostafa, Kaja Julge, Nils Eric Billo, Patrik Eklund, Marina Erhola, Tari Haahtela, Jussi Karjalainen, Mika Makela, Sanna Toppila-Salmi, Erkka Valovirta, Tuula Vasankari, Isabella Annesi-Maesano, Isabelle Bossé, Melisande Bourgoin-Heck, Denis Charpin, André Coste, Frédéric de Blay, Philippe Devillier, Alain Didier, Anh Tuan Dinh-Xuan, Jean-François Fontaine, Jocelyne Just, Rachel Nadif, Nhân Pham-Thi, Bernard Pigearias, Nicolas Roche, Van Ganse Eric, Ekaterine Chkhartishvili, Amiran Gamkrelidze, Maia Gotua, Sven Becker, Karl-Christian Bergmann, Thomas Bieber, Randolf Brehler, Roland Buhl, Adam M. Chaker, Ulf Darsow, Eckard Hamelmann, Joachim Heinrich, Thomas Keil, Ludger Klimek, Pavel Kolkhir, Susanne Lau, Marcus Maurer, Ralph Mösges, Angelos Neou, Oliver Pfaar, Johannes Ring, Martin Wagenmann, Torsten Zuberbier, Aiste Ramanauskaite, Anja Lingnau, Demetrios Christou, Sophia Neisinger, Xenophon Aggelidis, Jannis Constantinidis, Maria Dimou, Christos Grigoreas, Trisevgeni Kapsali, Michael Katotomichelakis, Stelios Loukides, Michael Makris, Emmanouil Manousakis, Nikolaos Mikos, Aris Pagkalos, Nikolaos G. Papadopoulos, Vasileios Papanikolaou, Giannis Paraskevopoulos, Konstantina Piskou, Emmanuel Prokopakis, Fotios Psarros, Konstantinos Samitas, Sofia Stamataki, Evangelia Stefanaki Lina, Ekaterini Syrigou, Ioanna Tsiligianni, Mina Vallianatou, Dimitrios Vourdas, Paraskevi Xepapadaki, Aspasia Karavelia, Fanny Wai San Ko, Gary Wong, Andor Hirschberg, Helga Kraxner, Kristof Nekam, Stephen Lane, Menachem Rottem, Cristina Artesani Maria, Simona Barbaglia, Bianca Beghé, Beatrice Bilo Maria, Attilio Boner, Matteo Bonini, Sergio Bonini, Fulvio Braido, Luisa Brussino, G Walter Canonica, Lorenzo Cecchi, Giorgio Ciprandi, Enrico Compalati, Gennaro D'Amato, Giulia De Feo, Stefano Del Giacco, Alessandro Fiocchi, Enrico Heffler, Carlo Lombardi, Riccardo Monti, Antonella Muraro, Eustachio Nettis, Stefania Nicola, Giovanni Passalacqua, Vincenzo Patella, Francesca Puggioni, Giovanni Rolla, Antonino Romano, Nicola Scichilone, Massimo Triggiani, Teresa Ventura Maria, Giovanni Viegi, Cristina Boccabella, Mattia Giovannini, Anand Mahesh Padukudru, Tomohisa Iinuma, Ken Ohta, Yoshitaka Okamoto, Kimihiro Okubo, Ruby Pawankar, Daiju Sakurai, Maho Suzukawa, Masao Yamaguchi, Zhanat Ispayeva, Yoon-Seok Chang, Hae-Sim Park, Mona Al-Ahmad, Ieva Cirule, Ineta Grisle, Carla Irani, Philip Rouadi, Fares Zaitoun, Ruta Dubakiene, Regina Emuzyte, Violeta Kvedariene, Brigita Gradauskiene, Arunas Valiulis, Markus Ollert, Farah Hannachi, Dejan Dokic, Amir Hamzah Abdul Latiff, Baharudin Abdullah, S.P. Palaniappan, Kent Woo, Stephen Montefort, Martín Bedolla Barajas, María del Carmen Costa Domínguez, Jesús Guillermo Espinoza Contreras, Jose Miguel Fuentes Pèrez, José Luis Gálvez Romero, María de la Luz Hortensia García Cruz, Sandra González Diaz, Yunuen Rocío Huerta Villalobos, Désiree E. Larenas-Linnemann, Jorge Agustin Luna-Pech, Juan José Matta Campos, Daniela Rivero Yeverino, Mónica Rodríguez González, Eréndira Rodríguez Zagal, Battur Lkhagvaa, Sandra Mavale-Manuel, Abrantes Nunes Elizabete, Niels Chavannes, Wytske J. Fokkens, Gerard Koppelman, Anke-Hilse Maitland-van der Zee, Sietze Reitsma, Ramanathan Chandrasekharan, Osman Yusuf, Maria Susana Repka-Ramirez, Juan Carlos Sisul, José E. Gereda, Marysia T. Recto, Slawomir Bialek, Artur Bialoszewski, Marta Chelminska, Radoslaw Gawlik, Ewa Jassem, Marek Jutel, Piotr Kuna, Maciej Kupczyk, Marcin Moniuszko, Marek Niedoszytko, Filip Raciborski, Jan Romantowski, Boleslaw Samolinski, Krzysztof Specjalski, Pedro Carreiro Martins, Jaime Correia de Sousa, Elisio Costa, Joao A. Fonseca, Olga Lourenço, Mario Morais-Almeida, Margarida Pereira Ana, Frederico Regateiro, Carlos Robalo Cordeiro, Jose Rosado Pinto, Bernardo Sousa-Pinto, Luis Taborda Barata, Ana Maria Todo-Bom, José Vieira Rafael, Daniela Carvalho, Maryam Ali Al-Nesf, Ioana Agache, Camelia Berghea Elena, Roxana Bumbacea, Diana Deleanu, Florin Mihaltan, Carmen Panaitescu Bunu, Musa Khaitov, Leyla Namazova-Baranova, Elena Vishneva, Ali Alshaikh Nada, Sanja Dimic-Janjic, Branislava Milenkovic, De Yun Wang, Martin Hrubiško, Natalija Edelbaher, Maja Jošt, Peter Kopac, Mitja Košnik, Nika Lalek, Antonija Poplas Susic, Irma Rozman Sinur, Tanja Soklic Košak, Nadja Triller, Katja Triller, Jure Urbancic, Mihaela Zidarn, Michael Levin, Paul Potter, Heather Zar, Isam Alobid, Aram Anto, Joan Bartra, Irina Bobolea, Paloma Campo, Vicky Cardona, Maria Carriazo Ana, José Antonio Castillo Vizuete, Tomas Chivato, Ignacio Jesus Davila Gonzalez, Joaquim Mullol, Antonio Nieto Garcia, César Picado, Santiago Quirce, Joaquin Sastre, Leticia de las Vecillas, Mikael Benson, Inger Kull, Marianne van Hage, Magnus Wickman, Nikolai Khaltaev, Yousser Mohammad, Pongsakorn Tantilipikorn, Pakit Vichyanond, Cemal Cingi, Bilun Gemicioglu, Ozlem Goksel, Omer Kalayci, Ali Fuat Kalyoncu, Cem Meço, Koyuncu Ilgim Vardaloglu, Arzu Yorgancioglu, Deniz Eyice Karabacak, Bruce Kirenga, Ian Michael Adcock, Hasan S. Arshad, Mike Bewick, Christine Bond, Christopher Brightling, Andrew Bush, Moïses Calderon, Kian Fan Chung, Adnan Custovic, Ratko Djukanovic, Stephen Durham, John Farrell, David Halpin, Michael Hyland, Sebastian Johnston, Brian Lipworth, Alla Nakonechna, David Price, Graham Roberts, Dermot Ryan, Jürgen Schwarze, Aziz Sheikh, Mike Shields, Samantha Walker, Sian Williams, Igor Kaidashev, Andrii Igorevich Kurchenko, Vladyslav Tsaryk, David Bernstein, Jonathan A. Bernstein, Thomas B. Casale, Sharon Chinthrajah, Mark Dykewicz, Gailen D. Marshall, Eli O. Meltzer, Robert M. Naclerio, Alkis Togias, Elina Toskala, Dana Wallace, Dennis M. Williams, Barbara Yawn, Fernan Caballero-Fonseca, Lan Le Thi Tuyet, and Tran Thien Quan Vu

Subjects
Allergic rhinitis, Survey, Professional-patient relation, Immunologic diseases. Allergy, RC581-607
Abstract

Background: Allergic rhinitis (AR) is a highly prevalent disease. We aimed to assess the symptoms that physicians who see patients with AR perceive as the most bothersome in their patients. Methods: We performed a cross-sectional study based on an online questionnaire sent to all members of the Allergic Rhinitis and its Impact on Asthma (ARIA) initiative. The survey included questions on the physicians' perceptions of patients’ AR symptoms as well as of their own AR symptoms. Results: Among 401 respondents, 155 (38.7%) reported having AR. ARIA members reported nasal symptoms to be the most frequent (89.7%) and bothersome (80.0%) symptoms experienced by themselves. Likewise, nasal symptoms were reported by ARIA members as the most frequent (94.8% in members with AR vs 96.0% in members without AR) and bothersome (57.0% in members with AR vs 67.9% in members without AR) in their patients. We found a significant association (p = 0.001) between physicians’ own symptoms and those perceived as the most bothersome in their patients. Conclusion: Physicians perceive nasal symptoms to be the most frequent and the most bothersome symptoms in AR patients. The physicians' personal experiences with AR may influence their perception of patients’ symptoms.

Published
2024
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9. Time to ACT-UP: Update on precautionary allergen labelling (PAL)

Author

Paul J. Turner, Antonio Bognanni, Stefania Arasi, Ignacio J. Ansotegui, Sabine Schnadt, Sébastien La Vieille, Jonathan O’B. Hourihane, Torsten Zuberbier, Philippe Eigenmann, Motohiro Ebisawa, Mario Morais-Almeida, Julie Barnett, Bryan Martin, Linda Monaci, Graham Roberts, Gary Wong, Ruchi Gupta, Sophia Tsabouri, Clare Mills, Simon Brooke-Taylor, Joan Bartra, Michael Levin, Marion Groetch, Luciana Tanno, Elham Hossny, Barbara Ballmer Weber, Vincenzo Fierro, Ben Remington, Jennifer Gerdts, M. Hazel Gowland, Derek Chu, Marjan Van Ravenhorst, Jennifer Koplin, and Alessandro Fiocchi

Subjects
Food hypersensitivity, Food labelling, Food labelling legislation and jurisprudence, Precautionary allergen labelling, Codex, Risk management, Immunologic diseases. Allergy, RC581-607
Abstract

Background: Precautionary Allergen (“may contain”) Labelling (PAL) is used by industry to communicate potential risk to food-allergic individuals posed by unintended allergen presence (UAP). In 2014, the World Allergy Organization (WAO) highlighted that PAL use was increasing, but often applied inconsistently and without regulation — which reduces its usefulness to consumers with food allergy and those purchasing food for them. WAO proposed the need for a regulated, international framework to underpin application of PAL. In 2019, the World Health Organization (WHO) and the Food and Agriculture Organization (FAO) of the United Nations convened an expert consultation to address the issue of PAL, the outputs of which are now being considered by the Codex Committee on Food Labelling (CCFL). Objectives: To summarise the latest data to inform the application of PAL in a more systematic way, for implementation into global food standards. Methods: A non-systematic review of issues surrounding precautionary labelling and food allergens in pre-packaged products. Results: Approximately, 100 countries around the world have legislation on the declaration of allergenic ingredients. Just a few have legislation on UAP. Given the risks that UAP entails, non-regulated PAL creates inconvenience in real life due to its unequal, difficult interpretation by patients. The attempts made so far to rationalize PAL present lights and shadows. Conclusions: At a time when CCFL is considering the results of the FAO/WHO Expert Consultation 2020–2023, we summarise the prospects to develop an effective and homogeneous legislation at a global level, and the areas of uncertainty that might hinder international agreement on a regulated framework for PAL of food allergens.

Published
2024
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10. LiDAR Inpainting of UAV Based 3D Point Cloud Using Supervised Learning

Author

Talha, Muhammad, Hussein, Aya, Hossny, Mohammed, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Liu, Tongliang, editor, Webb, Geoff, editor, Yue, Lin, editor, and Wang, Dadong, editor

Published
2024
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11. MIRST-DM: Multi-Instance RST with Drop-Max Layer for Robust Classification of Breast Cancer

Author

Sun, Shoukun, Xian, Min, Vakanski, Aleksandar, and Ghanem, Hossny

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

Robust self-training (RST) can augment the adversarial robustness of image classification models without significantly sacrificing models' generalizability. However, RST and other state-of-the-art defense approaches failed to preserve the generalizability and reproduce their good adversarial robustness on small medical image sets. In this work, we propose the Multi-instance RST with a drop-max layer, namely MIRST-DM, which involves a sequence of iteratively generated adversarial instances during training to learn smoother decision boundaries on small datasets. The proposed drop-max layer eliminates unstable features and helps learn representations that are robust to image perturbations. The proposed approach was validated using a small breast ultrasound dataset with 1,190 images. The results demonstrate that the proposed approach achieves state-of-the-art adversarial robustness against three prevalent attacks., Comment: 10 pages

Published
2022

12. Perceptions of the impact of individual allergic rhinitis symptoms: A survey of ARIA clinical experts

Author

Asllani, Julijana, Douagui, Habib, Asayag, Estrella, Elizabeth, Castro Maria, Crisci, Carlos D., Gomez, René Maximiliano, Ivancevich, Juan Carlos, Jares, Edgardo, Máspero, Jorge Fernando, Moreno, Pablo, Neffen, Hugo Eduardo, Zernotti, Mario Emilio, Bosnic-Anticevich, Sinthia, Chahhoud Carson, Kristin, Cvetkovski, Biljana, Davies, Janet M., Kritikos, Vicky, O'Hehir, Robyn, Oliver, Brian, Tan, House Rachel, Tattersall, Jessica, Zubrinich, Celia, Aberer, Werner, Niederberger-Leppin, Verena, Pali-Schöll, Isabella, Doyen, Virginie, Ebo, Didier, Louis, Renaud, Rombaux, Philippe, Scheire, Sophie, Bennoor, Kazi, Barreto, Bruno A., Camargos, Paulo, Chong-Neto, Herberto Jose, Cruz, Alvaro A., da Silva, Jane, Marta, Guidacci, Rizzo, José Angelo, Rosario Filho, Nelson, Faradiba, Sarquis Serpa, Solé, Dirceu, Urrutia-Pereira, Marilyn, Christoff, George, Mariana, Mandazhieva-Pepelanova, Cvetanka, Odjakova, Popov, Todor A., Vicheva, Dilyana, Teixeira Maria, do Ceu, Bouchard, Jacques, Brozek, Jan, Chu, Derek K., Denburg, Judah, Eiwegger, Thomas, Keith, Paul K., To, Teresa, Waserman, Susan, Abusada, Nancy, Alvarez Cuesta, Emilio, Calvo-Gil, Mario A., Guzmán, Maria Antonieta, Pérez Gomez, Tamara, Wong Gary, Wing Kin, Zhang, Luo, Caraballo, Luis, Cepeda Sarabia, Alfonso, Nyembue, Dieudonné, Soto-Martinez, Manuel, Miculinic, Neven, Plavec, Davor, Pitsios, Constantinos, Yiallouros, Panayiotis, Panzner, Petr, Sova, Milan, Vachova, Martina, Bindslev-Jensen, Carsten, Dahl, Ronald, Malling, Hans-Jorgen, Münter, Lars, Poulsen, Lars K., Charlotte, Suppli Ulrik, Tannert, Line Kring, Mahboub, Bassam, Salameh, Laila, Cherrez-Ojeda, Ivan, Robles, de Guevara Karla, El-Owaidy, Rasha Hassan, El-Sayed, Zeinab A., El-Sayed, Shereen Saad, Hossny, Elham, Mostafa, Badr Eldin, Julge, Kaja, Billo, Nils Eric, Eklund, Patrik, Erhola, Marina, Haahtela, Tari, Karjalainen, Jussi, Makela, Mika, Toppila-Salmi, Sanna, Valovirta, Erkka, Vasankari, Tuula, Annesi-Maesano, Isabella, Bossé, Isabelle, Bourgoin-Heck, Melisande, Charpin, Denis, Coste, André, de Blay, Frédéric, Devillier, Philippe, Didier, Alain, Dinh-Xuan, Anh Tuan, Fontaine, Jean-François, Just, Jocelyne, Nadif, Rachel, Pham-Thi, Nhân, Pigearias, Bernard, Roche, Nicolas, Ganse Eric, Van, Chkhartishvili, Ekaterine, Gamkrelidze, Amiran, Gotua, Maia, Becker, Sven, Bergmann, Karl-Christian, Bieber, Thomas, Brehler, Randolf, Buhl, Roland, Chaker, Adam M., Darsow, Ulf, Hamelmann, Eckard, Heinrich, Joachim, Keil, Thomas, Klimek, Ludger, Kolkhir, Pavel, Lau, Susanne, Maurer, Marcus, Mösges, Ralph, Neou, Angelos, Pfaar, Oliver, Ring, Johannes, Wagenmann, Martin, Zuberbier, Torsten, Ramanauskaite, Aiste, Lingnau, Anja, Christou, Demetrios, Neisinger, Sophia, Aggelidis, Xenophon, Constantinidis, Jannis, Dimou, Maria, Grigoreas, Christos, Kapsali, Trisevgeni, Katotomichelakis, Michael, Loukides, Stelios, Makris, Michael, Manousakis, Emmanouil, Mikos, Nikolaos, Pagkalos, Aris, Papadopoulos, Nikolaos G., Papanikolaou, Vasileios, Paraskevopoulos, Giannis, Piskou, Konstantina, Prokopakis, Emmanuel, Psarros, Fotios, Samitas, Konstantinos, Stamataki, Sofia, Stefanaki Lina, Evangelia, Syrigou, Ekaterini, Tsiligianni, Ioanna, Vallianatou, Mina, Vourdas, Dimitrios, Xepapadaki, Paraskevi, Karavelia, Aspasia, Wai San Ko, Fanny, Wong, Gary, Hirschberg, Andor, Kraxner, Helga, Nekam, Kristof, Lane, Stephen, Rottem, Menachem, Artesani Maria, Cristina, Barbaglia, Simona, Beghé, Bianca, Bilo Maria, Beatrice, Boner, Attilio, Bonini, Matteo, Bonini, Sergio, Braido, Fulvio, Brussino, Luisa, Canonica, G Walter, Cecchi, Lorenzo, Ciprandi, Giorgio, Compalati, Enrico, D'Amato, Gennaro, De Feo, Giulia, Del Giacco, Stefano, Fiocchi, Alessandro, Heffler, Enrico, Lombardi, Carlo, Monti, Riccardo, Muraro, Antonella, Nettis, Eustachio, Nicola, Stefania, Passalacqua, Giovanni, Patella, Vincenzo, Puggioni, Francesca, Rolla, Giovanni, Romano, Antonino, Scichilone, Nicola, Triggiani, Massimo, Ventura Maria, Teresa, Viegi, Giovanni, Boccabella, Cristina, Giovannini, Mattia, Mahesh Padukudru, Anand, Iinuma, Tomohisa, Ohta, Ken, Okamoto, Yoshitaka, Okubo, Kimihiro, Pawankar, Ruby, Sakurai, Daiju, Suzukawa, Maho, Yamaguchi, Masao, Ispayeva, Zhanat, Chang, Yoon-Seok, Park, Hae-Sim, Al-Ahmad, Mona, Cirule, Ieva, Grisle, Ineta, Irani, Carla, Rouadi, Philip, Zaitoun, Fares, Dubakiene, Ruta, Emuzyte, Regina, Kvedariene, Violeta, Gradauskiene, Brigita, Valiulis, Arunas, Ollert, Markus, Hannachi, Farah, Dokic, Dejan, Abdul Latiff, Amir Hamzah, Abdullah, Baharudin, Palaniappan, S.P., Woo, Kent, Montefort, Stephen, Bedolla Barajas, Martín, Costa Domínguez, María del Carmen, Espinoza Contreras, Jesús Guillermo, Fuentes Pèrez, Jose Miguel, Gálvez Romero, José Luis, García Cruz, María de la Luz Hortensia, González Diaz, Sandra, Huerta Villalobos, Yunuen Rocío, Larenas-Linnemann, Désiree E., Luna-Pech, Jorge Agustin, Matta Campos, Juan José, Rivero Yeverino, Daniela, Rodríguez González, Mónica, Rodríguez Zagal, Eréndira, Lkhagvaa, Battur, Mavale-Manuel, Sandra, Nunes Elizabete, Abrantes, Chavannes, Niels, Fokkens, Wytske J., Koppelman, Gerard, Maitland-van der Zee, Anke-Hilse, Reitsma, Sietze, Chandrasekharan, Ramanathan, Yusuf, Osman, Repka-Ramirez, Maria Susana, Sisul, Juan Carlos, Gereda, José E., Recto, Marysia T., Bialek, Slawomir, Bialoszewski, Artur, Chelminska, Marta, Gawlik, Radoslaw, Jassem, Ewa, Jutel, Marek, Kuna, Piotr, Kupczyk, Maciej, Moniuszko, Marcin, Niedoszytko, Marek, Raciborski, Filip, Romantowski, Jan, Samolinski, Boleslaw, Specjalski, Krzysztof, Carreiro Martins, Pedro, Correia de Sousa, Jaime, Costa, Elisio, Fonseca, Joao A., Lourenço, Olga, Morais-Almeida, Mario, Pereira Ana, Margarida, Regateiro, Frederico, Robalo Cordeiro, Carlos, Rosado Pinto, Jose, Sousa-Pinto, Bernardo, Taborda Barata, Luis, Todo-Bom, Ana Maria, Vieira Rafael, José, Carvalho, Daniela, Al-Nesf, Maryam Ali, Agache, Ioana, Berghea Elena, Camelia, Bumbacea, Roxana, Deleanu, Diana, Mihaltan, Florin, Panaitescu Bunu, Carmen, Khaitov, Musa, Namazova-Baranova, Leyla, Vishneva, Elena, Alshaikh Nada, Ali, Dimic-Janjic, Sanja, Milenkovic, Branislava, Wang, De Yun, Hrubiško, Martin, Edelbaher, Natalija, Jošt, Maja, Kopac, Peter, Košnik, Mitja, Lalek, Nika, Poplas Susic, Antonija, Rozman Sinur, Irma, Soklic Košak, Tanja, Triller, Nadja, Triller, Katja, Urbancic, Jure, Zidarn, Mihaela, Levin, Michael, Potter, Paul, Zar, Heather, Alobid, Isam, Anto, Aram, Bartra, Joan, Bobolea, Irina, Campo, Paloma, Cardona, Vicky, Carriazo Ana, Maria, Castillo Vizuete, José Antonio, Chivato, Tomas, Davila Gonzalez, Ignacio Jesus, Mullol, Joaquim, Nieto Garcia, Antonio, Picado, César, Quirce, Santiago, Sastre, Joaquin, de las Vecillas, Leticia, Benson, Mikael, Kull, Inger, van Hage, Marianne, Wickman, Magnus, Khaltaev, Nikolai, Mohammad, Yousser, Tantilipikorn, Pongsakorn, Vichyanond, Pakit, Cingi, Cemal, Gemicioglu, Bilun, Goksel, Ozlem, Kalayci, Omer, Kalyoncu, Ali Fuat, Meço, Cem, Vardaloglu, Koyuncu Ilgim, Yorgancioglu, Arzu, Karabacak, Deniz Eyice, Kirenga, Bruce, Adcock, Ian Michael, Arshad, Hasan S., Bewick, Mike, Bond, Christine, Brightling, Christopher, Bush, Andrew, Calderon, Moïses, Chung, Kian Fan, Custovic, Adnan, Djukanovic, Ratko, Durham, Stephen, Farrell, John, Halpin, David, Hyland, Michael, Johnston, Sebastian, Lipworth, Brian, Nakonechna, Alla, Price, David, Roberts, Graham, Ryan, Dermot, Schwarze, Jürgen, Sheikh, Aziz, Shields, Mike, Walker, Samantha, Williams, Sian, Kaidashev, Igor, Kurchenko, Andrii Igorevich, Tsaryk, Vladyslav, Bernstein, David, Bernstein, Jonathan A., Casale, Thomas B., Chinthrajah, Sharon, Dykewicz, Mark, Marshall, Gailen D., Meltzer, Eli O., Naclerio, Robert M., Togias, Alkis, Toskala, Elina, Wallace, Dana, Williams, Dennis M., Yawn, Barbara, Caballero-Fonseca, Fernan, Le Thi Tuyet, Lan, Vu, Tran Thien Quan, Gil-Mata, Sara, Teixeira, Tatiana, Bedbrook, Anna, Bousquet, Jean, and Vieira, Rafael José

Published
2024
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14. Global change, climate change, and asthma in children: Direct and indirect effects - A WAO Pediatric Asthma Committee Report

Author

Le Souëf, Peter N., Adachi, Yuichi, Anastasiou, Eleni, Ansotegui, Ignacio J., Badellino, Héctor A., Banzon, Tina, Beltrán, Cesar Pozo, D'Amato, Gennaro, El-Sayed, Zeinab A., Gómez, Rene Maximiliano, Hossny, Elham, Kalayci, Ömer, Morais-Almeida, Mário, Nieto-Garcia, Antonio, Peden, David B., Phipatanakul, Wanda, Wang, Jiu-Yao, Wan, I-Jen, Wong, Gary, Xepapadaki, Paraskevi, and Papadopoulos, Nikolaos G.

Published
2024
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15. Concepts for the Development of Person-Centered, Digitally Enabled, Artificial Intelligence–Assisted ARIA Care Pathways (ARIA 2024)

Author

Bousquet, Jean, Schünemann, Holger J., Sousa-Pinto, Bernardo, Zuberbier, Torsten, Togias, Alkis, Samolinski, Boleslaw, Bedbrook, Anna, Czarlewski, Wienczyslawa, Hofmann-Apitius, Martin, Litynska, Justyna, Vieira, Rafael José, Anto, Josep M., Fonseca, Joao A., Brozek, Jan, Bognanni, Antonio, Brussino, Luisa, Canonica, G. Walter, Cherrez-Ojeda, Ivan, Cruz, Alvaro A., Vecillas, Leticia de las, Dykewicz, Mark, Gemicioglu, Bilun, Giovannini, Mattia, Haahtela, Tari, Jacobs, Marc, Jacomelli, Cristina, Klimek, Ludger, Kvedariene, Violeta, Larenas-Linnemann, Desiree E., Louis, Gilles, Lourenço, Olga, Leemann, Lucas, Morais-Almeida, Mario, Neves, Ana Luisa, Nadeau, Kari C., Nowak, Artur, Palamarchuk, Yuliia, Palkonen, Susanna, Papadopoulos, Nikolaos G., Parmelli, Elena, Pereira, Ana Margarida, Pfaar, Oliver, Regateiro, Frederico S., Savouré, Marine, Taborda-Barata, Luis, Toppila-Salmi, Sanna K., Torres, Maria J., Valiulis, Arunas, Ventura, Maria Teresa, Williams, Sian, Yepes-Nuñez, Juan J., Yorgancioglu, Arzu, Zhang, Luo, Zuberbier, Jaron, Abdul Latiff, Amir Hamzah, Abdullah, Baharudin, Agache, Ioana, Al-Ahmad, Mona, Al-Nesf, Maryam Ali, Al Shaikh, Nada A., Amaral, Rita, Ansotegui, Ignacio J., Asllani, Julijana, Balotro-Torres, Maria Cristina, Bergmann, Karl-Christian, Bernstein, Jonathan A., Bindslev-Jensen, Carsten, Blaiss, Michael S., Bonaglia, Cristina, Bonini, Matteo, Bossé, Isabelle, Braido, Fulvio, Caballero-Fonseca, Fernan, Camargos, Paulo, Carreiro-Martins, Pedro, Casale, Thomas, Castillo-Vizuete, José-Antonio, Cecchi, Lorenzo, Teixeira, Maria do Ceu, Chang, Yoon-Seok, Loureiro, Claudia Chaves, Christoff, George, Ciprandi, Giorgio, Cirule, Ieva, Correia-de-Sousa, Jaime, Costa, Elisio M., Cvetkovski, Biljana, de Vries, Govert, Del Giacco, Stefano, Devillier, Philippe, Dokic, Dejan, Douagui, Habib, Durham, Stephen R., Enecilla, Maria Lourdes, Fiocchi, Alessandro, Fokkens, Wytske J., Fontaine, Jean-François, Gawlik, Radoslaw, Gereda, Jose E., Gil-Mata, Sara, Giuliano, Antonio F.M., Gotua, Maia, Gradauskiene, Brigita, Guzman, Maria Antonieta, Hossny, Elham, Hrubiško, Martin, Iinuma, Tomohisa, Irani, Carla, Ispayeva, Zhanat, Ivancevich, Juan Carlos, Jartti, Tuomas, Jeseňák, Miloš, Julge, Kaja, Jutel, Marek, Kaidashev, Igor, Bennoor, Kazi S., Khaltaev, Nicolai, Kirenga, Bruce, Kraxner, Helga, Kull, Inger, Kulus, Marek, Kuna, Piotr, Kupczyk, Maciej, Kurchenko, Andriy, La Grutta, Stefania, Lane, Stephen, Miculinic, Neven, Lee, Sang Min, Le Thi Tuyet, Lan, Lkhagvaa, Battur, Louis, Renaud, Mahboub, Bassam, Makela, Mika, Makris, Michael, Maurer, Marcus, Melén, Eric, Milenkovic, Branislava, Mohammad, Yousser, Moniuszko, Marcin, Montefort, Stephen, Moreira, Andre, Moreno, Pablo, Mullol, Joaquim, Nadif, Rachel, Nakonechna, Alla, Navarro-Locsin, Cecilia Gretchen, Neffen, Hugo E., Nekam, Kristof, Niedoszytko, Marek, Nunes, Elizabete, Nyembue, Dieudonné, O’Hehir, Robyn, Ollert, Markus, Ohta, Ken, Okamoto, Yoshitaka, Okubo, Kimihiro, Olze, Heidi, Padukudru, Mahesh Anand, Palomares, Oscar, Pali-Schöll, Isabella, Panzner, Petr, Palosuo, Kati, Park, Hae S., Passalacqua, Giovanni, Patella, Vincenzo, Pawankar, Ruby, Pétré, Benoît, Pitsios, Constantinos, Plavec, Davor, Popov, Todor A., Puggioni, Francesca, Quirce, Santiago, Raciborski, Filip, Ramonaité, Agné, Recto, Marysia, Repka-Ramirez, Susana, Roberts, Graham, Robles-Velasco, Karla, Roche, Nicolas, Rodriguez-Gonzalez, Monica, Romualdez, Joel A., Rottem, Menachem, Rouadi, Philip W., Salapatas, Marianella, Sastre, Joaquin, Serpa, Faradiba S., Sayah, Zineb, Scichilone, Nicola, Senna, Gianenrico, Sisul, Juan Carlos, Solé, Dirceu, Soto-Martinez, Manuel E., Sova, Milan, Sozinova, Olga, Stevanovic, Katarina, Ulrik, Charlotte Suppli, Szylling, Anna, Tan, Frances M., Tantilipikorn, Pongsakorn, Todo-Bom, Ana, Tomic-Spiric, Vesna, Tsaryk, Vladyslav, Tsiligianni, Ioanna, Urrutia-Pereira, Marilyn, Rostan, Marylin Valentin, Sofiev, Mikhail, Valovirta, Erkka, Van Eerd, Michiel, Van Ganse, Eric, Vasankari, Tuula, Vichyanond, Pakit, Viegi, Giovanni, Wallace, Dana, Wang, De Yun, Waserman, Susan, Wong, Gary, Worm, Margitta, Yusuf, Osman M., Zaitoun, Fares, and Zidarn, Mihaela

Published
2024
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16. Time to ACT-UP: Update on precautionary allergen labelling (PAL)

Author

Turner, Paul J., Bognanni, Antonio, Arasi, Stefania, Ansotegui, Ignacio J., Schnadt, Sabine, Vieille, Sébastien La, Hourihane, Jonathan O’B., Zuberbier, Torsten, Eigenmann, Philippe, Ebisawa, Motohiro, Morais-Almeida, Mario, Barnett, Julie, Martin, Bryan, Monaci, Linda, Roberts, Graham, Wong, Gary, Gupta, Ruchi, Tsabouri, Sophia, Mills, Clare, Brooke-Taylor, Simon, Bartra, Joan, Levin, Michael, Groetch, Marion, Tanno, Luciana, Hossny, Elham, Weber, Barbara Ballmer, Fierro, Vincenzo, Remington, Ben, Gerdts, Jennifer, Gowland, M. Hazel, Chu, Derek, Van Ravenhorst, Marjan, Koplin, Jennifer, and Fiocchi, Alessandro

Published
2024
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19. Pediatric asthma comorbidities: Global impact and unmet needs

Author

Elham Hossny, MD, PhD, Yuichi Adachi, MD, PhD, Eleni Anastasiou, MD, Héctor Badellino, MD, PhD, Adnan Custovic, PhD, Rasha El-Owaidy, MD, PhD, Zeinab A. El-Sayed, MD, PhD, Ivana Filipovic, MD, PhD, R. Maximiliano Gomez, MD, PhD, Ömer Kalayci, MD, Peter Le Souëf, FRACP, MD, Michael Miligkos, MD, PhD, Mário Morais-Almeida, MD, PhD, Antonio Nieto, MD, PhD, Wanda Phipatanakul, MD, Ghada Shousha, MD, PhD, Alvaro Teijeiro, MD, PhD, Jiu-Yao Wang, MD, DPhil, Gary W.K. Wong, MD, FRCPC, FHKAM, Paraskevi Xepapadaki, MD, PhD, Su Boon Yong, MD, PhD, and Nikolaos G. Papadopoulos, MD, PhD

Subjects
Asthma, Children, Comorbid conditions, Asthma control, Obesity, Upper airway, Immunologic diseases. Allergy, RC581-607
Abstract

Real-world data on the range and impact of comorbid health conditions that affect pediatric asthma are scant, especially from developing countries. Lack of data hinders effective diagnosis, treatment, and overall management of these complex cases. We, hereby, describe the common pediatric asthma comorbid conditions in terms of evidence for association, potential mechanisms of impact on asthma control, and treatment benefit. Obesity, upper airway allergies, dysfunctional breathing, multiple sensitizations, depressive disorders, food allergy, and gastro-esophageal reflux are common associations with difficult-to-treat asthma. On the other hand, asthma symptoms and/or management may negatively impact the well-being of children through drug adverse effects, worsening of anaphylaxis symptoms, and disturbing mental health.Awareness of these ailments may be crucial for designing the optimum care for each asthmatic child individually and may ultimately improve the quality of life of patients and their families. A multidisciplinary team of physicians is required to identify and manage such comorbidities aiming to mitigate the over-use of asthma pharmacotherapy. Asthma research should target relevant real-world difficulties encountered at clinical practice and focus on interventions that would mitigate the impact of such comorbidities. Finally, policymakers and global healthcare organizations are urged to recognize pediatric asthma control as a healthcare priority and allocate resources for research and clinical interventions. In other words, global asthma control needs support by compassionate scientific partnership.

Published
2024
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22. Pediatric asthma comorbidities: Global impact and unmet needs

Author

Hossny, Elham, Adachi, Yuichi, Anastasiou, Eleni, Badellino, Héctor, Custovic, Adnan, El-Owaidy, Rasha, El-Sayed, Zeinab A., Filipovic, Ivana, Gomez, R. Maximiliano, Kalayci, Ömer, Le Souëf, Peter, Miligkos, Michael, Morais-Almeida, Mário, Nieto, Antonio, Phipatanakul, Wanda, Shousha, Ghada, Teijeiro, Alvaro, Wang, Jiu-Yao, Wong, Gary W.K., Xepapadaki, Paraskevi, Yong, Su Boon, and Papadopoulos, Nikolaos G.

Published
2024
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25. Updated grading system for systemic allergic reactions: Joint Statement of the World Allergy Organization Anaphylaxis Committee and Allergen Immunotherapy Committee

Author

Turner, Paul J., Ansotegui, Ignacio J., Campbell, Dianne E., Cardona, Victoria, Carr, Stuart, Custovic, Adnan, Durham, Stephen, Ebisawa, Motohiro, Geller, Mario, Gonzalez-Estrada, Alexei, Greenberger, Paul A., Hossny, Elham, Irani, Carla, Leung, Agnes S.Y., Levin, Michael E., Muraro, Antonella, Oppenheimer, John J., Ortega Martell, José Antonio, Pouessel, Guillaume, Rial, Manuel J., Senna, Gianenrico, Tanno, Luciana K., Wallace, Dana V., Worm, Margitta, and Morais-Almeida, Mário

Published
2024
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26. Updated grading system for systemic allergic reactions: Joint Statement of the World Allergy Organization Anaphylaxis Committee and Allergen Immunotherapy Committee

Author

Paul J. Turner, MD, PhD, Ignacio J. Ansotegui, MD, PhD, Dianne E. Campbell, MD, PhD, Victoria Cardona, MD, PhD, Stuart Carr, MD, Adnan Custovic, MD, PhD, Stephen Durham, MD, Motohiro Ebisawa, MD, PhD, Mario Geller, MD, Alexei Gonzalez-Estrada, MD, Paul A. Greenberger, MD, Elham Hossny, MD, PhD, Carla Irani, MD, Agnes S.Y. Leung, MD, Michael E. Levin, MD, PhD, Antonella Muraro, MD, John J. Oppenheimer, MD, José Antonio Ortega Martell, MD, Guillaume Pouessel, MD, Manuel J. Rial, MD, PhD, Gianenrico Senna, MD, PhD, Luciana K. Tanno, MD, PhD, Dana V. Wallace, MD, Margitta Worm, MD, PhD, and Mário Morais-Almeida, MD, PhD

Subjects
Adverse events, Allergen immunotherapy, Anaphylaxis, Clinical trials, Safety reporting, Immunologic diseases. Allergy, RC581-607
Abstract

There is a lack of consensus over the description and severity assignment of allergic adverse reactions to immunotherapy, although there seems to be a consensus at least in terms of using the World Allergy Organization (WAO) grading systems to describe local adverse events for Sublingual Immunotherapy (SLIT) and Systemic Allergic Reactions (SARs) to Subcutaneous Immunotherapy (SCIT) amongst the major national/regional allergy societies. In this manuscript, we propose a modification of the previous WAO Grading system for SARs, which aligns with the newly-proposed Consortium for Food Allergy Research (CoFAR) Grading Scale for Systemic Allergic Reactions in Food Allergy (version 3.0). We hope this can facilitate a unified grading system appropriate to SARs due to allergen immunotherapy, independent of allergen and route of administration, and across clinical and research practice.

Published
2024
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27. Biomechanic Posture Stabilisation via Iterative Training of Multi-policy Deep Reinforcement Learning Agents

Author

Hossny, Mohammed and Iskander, Julie

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence, I.2.9
Abstract

It is not until we become senior citizens do we recognise how much we took maintaining a simple standing posture for granted. It is truly fascinating to observe the magnitude of control the human brain exercises, in real time, to activate and deactivate the lower body muscles and solve a multi-link 3D inverted pendulum problem in order to maintain a stable standing posture. This realisation is even more apparent when training an artificial intelligence (AI) agent to maintain a standing posture of a digital musculoskeletal avatar due to the error propagation problem. In this work we address the error propagation problem by introducing an iterative training procedure for deep reinforcement learning which allows the agent to learn a finite set of actions and how to coordinate between them in order to achieve a stable standing posture. The proposed training approach allowed the agent to increase standing duration from 4 seconds using the traditional training method to 348 seconds using the proposed method. The proposed training method allowed the agent to generalise and accommodate perception and actuation noise for almost 108 seconds., Comment: Content: 12 pages, 6 figures. \c{opyright} 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by- nc-nd/4.0/

Published
2020

28. An ocular biomechanics environment for reinforcement learning

Author

Iskander, Julie and Hossny, Mohammed

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, I.6.5
Abstract

Reinforcement learning has been applied to human movement through physiologically-based biomechanical models to add insights into the neural control of these movements; it is also useful in the design of prosthetics and robotics. In this paper, we extend the use of reinforcement learning into controlling an ocular biomechanical system to perform saccades, which is one of the fastest eye movement systems. We describe an ocular environment and an agent trained using Deep Deterministic Policy Gradients method to perform saccades. The agent was able to match the desired eye position with a mean deviation angle of 3:5+/-1:25 degrees. The proposed framework is a first step towards using the capabilities of deep reinforcement learning to enhance our understanding of ocular biomechanics., Comment: 5 figures, 2 tables

Published
2020

29. Fast Synthetic LiDAR Rendering via Spherical UV Unwrapping of Equirectangular Z-Buffer Images

Author

Hossny, Mohammed, Saleh, Khaled, Attia, Mohammed, Abobakr, Ahmed, and Iskander, Julie

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

LiDAR data is becoming increasingly essential with the rise of autonomous vehicles. Its ability to provide 360deg horizontal field of view of point cloud, equips self-driving vehicles with enhanced situational awareness capabilities. While synthetic LiDAR data generation pipelines provide a good solution to advance the machine learning research on LiDAR, they do suffer from a major shortcoming, which is rendering time. Physically accurate LiDAR simulators (e.g. Blensor) are computationally expensive with an average rendering time of 14-60 seconds per frame for urban scenes. This is often compensated for via using 3D models with simplified polygon topology (low poly assets) as is the case of CARLA (Dosovitskiy et al., 2017). However, this comes at the price of having coarse grained unrealistic LiDAR point clouds. In this paper, we present a novel method to simulate LiDAR point cloud with faster rendering time of 1 sec per frame. The proposed method relies on spherical UV unwrapping of Equirectangular Z-Buffer images. We chose Blensor (Gschwandtner et al., 2011) as the baseline method to compare the point clouds generated using the proposed method. The reported error for complex urban landscapes is 4.28cm for a scanning range between 2-120 meters with Velodyne HDL64-E2 parameters. The proposed method reported a total time per frame to 3.2 +/- 0.31 seconds per frame. In contrast, the BlenSor baseline method reported 16.2 +/- 1.82 seconds., Comment: This version has been removed by arXiv administrators as the submitter did not have the right to agree to the license at the time of submission

Published
2020

30. Refined Continuous Control of DDPG Actors via Parametrised Activation

Author

Hossny, Mohammed, Iskander, Julie, Attia, Mohammed, and Saleh, Khaled

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

In this paper, we propose enhancing actor-critic reinforcement learning agents by parameterising the final actor layer which produces the actions in order to accommodate the behaviour discrepancy of different actuators, under different load conditions during interaction with the environment. We propose branching the action producing layer in the actor to learn the tuning parameter controlling the activation layer (e.g. Tanh and Sigmoid). The learned parameters are then used to create tailored activation functions for each actuator. We ran experiments on three OpenAI Gym environments, i.e. Pendulum-v0, LunarLanderContinuous-v2 and BipedalWalker-v2. Results have shown an average of 23.15% and 33.80% increase in total episode reward of the LunarLanderContinuous-v2 and BipedalWalker-v2 environments, respectively. There was no significant improvement in Pendulum-v0 environment but the proposed method produces a more stable actuation signal compared to the state-of-the-art method. The proposed method allows the reinforcement learning actor to produce more robust actions that accommodate the discrepancy in the actuators' response functions. This is particularly useful for real life scenarios where actuators exhibit different response functions depending on the load and the interaction with the environment. This also simplifies the transfer learning problem by fine tuning the parameterised activation layers instead of retraining the entire policy every time an actuator is replaced. Finally, the proposed method would allow better accommodation to biological actuators (e.g. muscles) in biomechanical systems., Comment: 9 pages, 7 figures, 2 tables, submitted to Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by- nc-nd/4.0/

Published
2020

34. The Aesthetics of String Theory Design Structure as a Source for Innovating Creative Metal Pendants

Author

naglaa hossny elashraf ebrahim elmogazy

Subjects
string theory, relativity theory, quantum theory, metal pendants, Fine Arts, Architecture, NA1-9428
Abstract

Nature, with its laws and systems latent within the smallest cells and particles of matter, is full of wonderful structural and aesthetic syntheses, which are utilized by the artist to build many linear, colorful or tactile rhythms. Technological development and recent discoveries of science have affected many areas that led to the expansion of vision and the emergence of new and advanced concepts that have affected art and its philosophy, which in turn has led to changing the aesthetic standards of artistic work based on experimentation, discovery, analysis, interpretation and other tools of scientific research in order to link art technological development and recent discoveries. So, it is necessary for the arts in all its fields, and metalworking in particular, to find new approaches that combine modern discoveries with the field of metalworking.String theory is one of the cosmic theories that explains all natural phenomena. It unifies laws related to phenomena on the cosmic level, whether related to bodies or objects. It is an emerging theory that combines the geometry of time and space based on the theory of relativity as well as quantum theory and dimensional multiplicity theoryThe current research tackles enriching the educational field for students of the Art Education Department at the Faculty of Specific Education, Kafr El-Sheikh University, through the metalworking course, to create modern Art metal pendants that bear in their nature the idea of string theory, including various intellectual premises that enrich artistic taste and stimulate imagination and mental activity among students.

Published
2023
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39. The first articulated skeletons of enigmatic Late Cretaceous billfish-like actinopterygians

Author

Tamara El Hossny, Lionel Cavin, Ulrich Kaplan, Achim H. Schwermann, Elias Samankassou, and Matt Friedman

Subjects
ecological analogue, Cenomanian, billfishes, Protosphyraena, Plethodidae, Rhamphoichthys taxidiotis, Science
Abstract

Only few candidates of Mesozoic fishes with a similar body plan and ecological niche to the modern billfishes are suggested as their analogues. Several specimens were recovered from Cenomanian deposits in Germany and Lebanon and display a billfish-like fusiform body with elongated premaxillae. They are found close to the plethodids and show a unique combination of characters (rostrum pointed and extremely elongated, double articular head of the quadrate, anteroposteriorly elongated abdominal centra indicating a slender body and different types of scales on the body) allowing their inclusion in a new genus. Two ‘Protosphyraena’ species are also assigned to this new genus. This fish can be considered as an ecological analogue to the extant xiphioids sharing their feeding habits. This fish was abundant and roamed, as an apex predator, the Central Tethys and the Boreal realms during the Cenomanian.

Published
2023
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40. Influence of nurses’ perception of organizational climate and toxic leadership behaviors on intent to stay: A descriptive comparative study

Author

Eman Kamel Hossny, Hammad S. Alotaibi, Aml Moubark Mahmoud, Nermine Mohamed Elcokany, Mohamed Mahmoud Seweid, Nouf Afit Aldhafeeri, Abeer Mohamed Abdelkader, and Seham Mohamed Abd Elhamed

Subjects
Organizational climate, Toxic leadership, Intention to stay, Nurses, Nursing, RT1-120
Abstract

Background: Nursing managers and leaders must fight to retain nurses in hospitals by constructing an inviting organizational climate that is attractive to work in, not toxic. The organizational climate is primarily affected by employees’ internal work environment and behavior. Hence, nursing managers and leaders must implement effective strategies to increase nurses intention to stay by address the organizational climate. Aim: This study was designed to assess nurses’ perception of the effects of organizational climate and toxic leadership behaviors on their intention to stay and the differences in these domains between the two hospitals studied. Methods: A descriptive comparative design was used. Data were collected in 2022 from 250 nurses working in the two largest hospitals in Assiut, an Egyptian city south of Cairo, using three self-administered questionnaires: the organizational climate questionnaire (42 items categorized into nine domains), the toxic leadership scale (30 items categorized into five domains), and the Chinese version of the intent-to-stay scale. Results: Most nurses reported their intention to stay as “normal.” The nurse participants perceived that a positive organizational climate was not present, but toxic leadership was at a low level (13.6% and 25.6%, respectively). The model of regression analysis was significant, showing that the organizational climate represented by supportive systems impacted nurses’ intention to stay in the hospitals under study. Meanwhile, toxic leadership behaviors, represented by authoritarian leadership, unpredictability in the university hospital, and self-promotion in the insurance hospital, affected nurses’ intention to stay. Conclusion: Positive organizational climate played a significant role in retaining nurses through investing in incentives and providing supportive systems. Authoritarian leadership, unpredictability, and the self-promotion of leaders' behaviors impacted the nurses and the climate negatively. Hence, we recommend investing in potential strategies to improve the nurses’ intention to stay through performance standards, increased pay and benefits, clear reward mechanisms, participation in decision making, and assessments of leaders’ behaviors. Furthermore, decision and policy makers need to establish effective, supportive systems in hospitals to retain nurses. Hence, nursing managers and leaders must rethink how they can use their leadership skills and behavior in a positive manner to promote nurse retention. Study registration: Not registered

Published
2023
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41. Unanswered questions on the use of biologics in pediatric asthma

Author

Antonio Nieto, MD, PhD, Zeinab A. El-Sayed, MD, PhD, René Maximiliano Gómez, PhD, Elham Hossny, MD, PhD, Wang Jiu-Yao, MD, DPhil, Ömer Kalayci, MD, Mário Morais-Almeida, Wanda Phipatanakul, MD, Paulo Marcio Pitrez, MD, César Fireth Pozo Beltrán, MD, Paraskevi Xepapadaki, MD, and Nikolaos G. Papadopoulos, MD, PhD

Subjects
Severe childhood asthma, Biologics, Omalizumab, Mepolizumab, Benralizumab, Dupilumab, Immunologic diseases. Allergy, RC581-607
Abstract

The emergence of biologic therapies for the management of asthma has been a revolutionary change in our capacity to manage this disease.Since the launch of omalizumab, several other biologics have been marketed or are close to being marketed, suggesting that a plethora of monoclonal antibodies can be expected in the coming years. This will facilitate the transition to the paradigm of personalized medicine, but on the other hand will decisively further complicate the choice of the most appropriate treatment, in the absence of reliable enough biological markers.For these reasons, along with the relatively short time of use with these treatments, there are recurrently arising questions for which there are not even moderately documented answers, and for which the only solution must be based, with all reservations, on the combination of indirect evidence and expertise. In this paper, we attempt to address such questions, providing relevant commentaries and considering the whole width of the evidence base.

Published
2023
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42. Domain Adaptation for Vehicle Detection from Bird's Eye View LiDAR Point Cloud Data

Author

Saleh, Khaled, Abobakr, Ahmed, Attia, Mohammed, Iskander, Julie, Nahavandi, Darius, and Hossny, Mohammed

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

Point cloud data from 3D LiDAR sensors are one of the most crucial sensor modalities for versatile safety-critical applications such as self-driving vehicles. Since the annotations of point cloud data is an expensive and time-consuming process, therefore recently the utilisation of simulated environments and 3D LiDAR sensors for this task started to get some popularity. With simulated sensors and environments, the process for obtaining an annotated synthetic point cloud data became much easier. However, the generated synthetic point cloud data are still missing the artefacts usually exist in point cloud data from real 3D LiDAR sensors. As a result, the performance of the trained models on this data for perception tasks when tested on real point cloud data is degraded due to the domain shift between simulated and real environments. Thus, in this work, we are proposing a domain adaptation framework for bridging this gap between synthetic and real point cloud data. Our proposed framework is based on the deep cycle-consistent generative adversarial networks (CycleGAN) architecture. We have evaluated the performance of our proposed framework on the task of vehicle detection from a bird's eye view (BEV) point cloud images coming from real 3D LiDAR sensors. The framework has shown competitive results with an improvement of more than 7% in average precision score over other baseline approaches when tested on real BEV point cloud images., Comment: Under review for IEEE SMC 2019

Published
2019

43. Real-time Intent Prediction of Pedestrians for Autonomous Ground Vehicles via Spatio-Temporal DenseNet

Author

Saleh, Khaled, Hossny, Mohammed, and Nahavandi, Saeid

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

Understanding the behaviors and intentions of humans are one of the main challenges autonomous ground vehicles still faced with. More specifically, when it comes to complex environments such as urban traffic scenes, inferring the intentions and actions of vulnerable road users such as pedestrians become even harder. In this paper, we address the problem of intent action prediction of pedestrians in urban traffic environments using only image sequences from a monocular RGB camera. We propose a real-time framework that can accurately detect, track and predict the intended actions of pedestrians based on a tracking-by-detection technique in conjunction with a novel spatio-temporal DenseNet model. We trained and evaluated our framework based on real data collected from urban traffic environments. Our framework has shown resilient and competitive results in comparison to other baseline approaches. Overall, we achieved an average precision score of 84.76% with a real-time performance at 20 FPS., Comment: Accepted to ICRA 2019

Published
2019

44. Realistic Hair Simulation Using Image Blending

Author

Attia, Mohamed, Hossny, Mohammed, Nahavandi, Saeid, Yazdabadi, Anousha, and Asadi, Hamed

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In this presented work, we propose a realistic hair simulator using image blending for dermoscopic images. This hair simulator can be used for benchmarking and validation of the hair removal methods and in data augmentation for improving computer aided diagnostic tools. We adopted one of the popular implementation of image blending to superimpose realistic hair masks to hair lesion. This method was able to produce realistic hair masks according to a predefined mask for hair. Thus, the produced hair images and masks can be used as ground truth for hair segmentation and removal methods by inpainting hair according to a pre-defined hair masks on hairfree areas. Also, we achieved a realism score equals to 1.65 in comparison to 1.59 for the state-of-the-art hair simulator.

Published
2019

45. Event detection in Twitter: A keyword volume approach

Author

Hossny, Ahmad Hany and Mitchell, Lewis

Subjects
Computer Science - Social and Information Networks, Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

Event detection using social media streams needs a set of informative features with strong signals that need minimal preprocessing and are highly associated with events of interest. Identifying these informative features as keywords from Twitter is challenging, as people use informal language to express their thoughts and feelings. This informality includes acronyms, misspelled words, synonyms, transliteration and ambiguous terms. In this paper, we propose an efficient method to select the keywords frequently used in Twitter that are mostly associated with events of interest such as protests. The volume of these keywords is tracked in real time to identify the events of interest in a binary classification scheme. We use keywords within word-pairs to capture the context. The proposed method is to binarize vectors of daily counts for each word-pair by applying a spike detection temporal filter, then use the Jaccard metric to measure the similarity of the binary vector for each word-pair with the binary vector describing event occurrence. The top n word-pairs are used as features to classify any day to be an event or non-event day. The selected features are tested using multiple classifiers such as Naive Bayes, SVM, Logistic Regression, KNN and decision trees. They all produced AUC ROC scores up to 0.91 and F1 scores up to 0.79. The experiment is performed using the English language in multiple cities such as Melbourne, Sydney and Brisbane as well as the Indonesian language in Jakarta. The two experiments, comprising different languages and locations, yielded similar results., Comment: In: Proceedings of the 2nd International Workshop on Social Computing (IWSC '18): Spatial Social Behavior Analytics in Urban Society

Published
2019

46. Federated blockchain system (FBS) for the healthcare industry

Author

Ashraf Mohey Eldin, Eman Hossny, Khaled Wassif, and Fatma A. Omara

Subjects
Medicine, Science
Abstract

Abstract Blockchain is a distributed technology that introduced the well known Bitcoin cryptocurrency into action. Blockchain has been considered for research by many countries and industries. It is being applied in many fields such as the healthcare domain. Many companies started using Blockchain to increase the security and privacy of the Electronic Healthcare Records for their patients. The work in this paper discusses some existing healthcare problems and challenges. In addition, the paper reviews some related work models and provides a comparison that shows their objectives and limitations. Also, a proposed Federated Blockchain System (FBS) is introduced to provide solutions for these healthcare problems and elaborates the technical details of the system architecture. Moreover, the effectiveness of the system has been validated which showed an average of 68–100 ms for performing query operations and average of 0.944–19.041 s for performing writing operations on the system. Finally, a discussion of the system validation and future work are presented.

Published
2023
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47. Distinctive physical insights driven from machine learning modelling of nuclear power plant severe accident scenario propagation

Author

K. Hossny, W. Villanueva, and H. D. Wang

Subjects
Medicine, Science
Abstract

Abstract The severe accident scenario propagation studies of nuclear power plants (NPPs) have been one of the most critical factors in deploying nuclear power for decades. During an NPP accident, the accident scenario can change during its propagation from the initiating event to a series of accident sub-scenarios. Hence, having time-wise updated information about the current type of accident sub-scenario can help plant operators mitigate the accident propagation and underlying consequences. In this work, we demonstrate the capability of machine learning (Decision Tree) to help researchers and design engineers in finding distinctive physical insights between four different types of accident scenarios based on the pressure vessel's maximum external surface temperature at a particular time. Although the four accidents we included in this study are considered some of the most extensively studied NPPs accident scenarios for decades, our findings shows that decision tree classification could define remarkable distinct differences between them with reliable statistical confidence.

Published
2023
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