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5. Differentiation of Avian Orthoavulavirus-1, Genotype VII, and it's Sub-Genotypes by High Resolution Melting (HRM) assay.

Author

Alghizzawi, Daoud, Ababneh, Mustafa M., and Al-Zghoul, Mohammad Borhan

Subjects
*NEWCASTLE disease virus, *GENOTYPES, *MELTING, *GENITALIA
Abstract

The avian orthoavulavirus type 1, previously recognized as avian paramyxovirus 1, is responsible for the widely recognized Newcastle disease virus (NDV) within the poultry field. This disease has substantial and adverse effects on crucial avian systems, including the respiratory, gastrointestinal, and reproductive systems. The aim of our study was to develop a high-resolution melting (HRM) assay targeting the fusion (F) gene, aimed at discriminating between NDV genotype VII and its associated subgenotypes. Then HRM results were compared with those obtained through sequencing of the F gene. The primers were specifically designed to suit NDV genotype VII and its corresponding subgenotypes (1.1, 1.2, 2, and 1.1L). Subsequently, these primers, underwent thorough assessment using 14 out of 24 clinical samples and positive controls. Notably, all assessed clinical samples exhibited a genotype VII profile in the HRM assay, characterized by a melting temperature of 77.95 ± 0.04°C. Subgenotype 1.1 manifested a distinctive melting temperature of 82.41± 0.02°C, while subgenotype 1.2 displayed 81.8 ± 0.02°C, subgenotype 2 exhibited 80.28 ± 0.02°C, and subgenotype 1.1l indicated 79.39 ± 0.06°C. Remarkably, the sequencing results from all 14 samples were in concordance with the HRM outcomes. These developed HRM assays were able to differentiate the NDV genotype VII and its subgenotypes thus providing alternative for genotyping of NDV sequencing of F gene. [ABSTRACT FROM AUTHOR]

Published
2024
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14. Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

Author

Saylors, Karen, Wolking, David J., Hagan, Emily, Martinez, Stephanie, Francisco, Leilani, Euren, Jason, Olson, Sarah H., Miller, Maureen, Fine, Amanda E., Thanh, Nga Nguyen Thi, Tran Minh, Phuc, Kalengkongan, Jusuf D., Kusumaningrum, Tina, Latinne, Alice, Pamungkas, Joko, Safari, Dodi, Saputro, Suryo, Bamba, Djeneba, Coulibaly, Kalpy Julien, Dosso, Mireille, Laudisoit, Anne, N'guettia Jean, Kouassi Manzan, Dutta, Shusmita, Islam, Ariful, Shano, Shahanaj, Mwanzalila, Mwokozi I., Trupin, Ian P., Gbakima, Aiah, Bangura, James, Yondah, Sylvester T., Karmacharya, Dibesh, Shrestha, Rima D., Kamta, Marcelle Annie Matsida, Mouiche, Mohamed Moctar Mouliom, Ndolo, Hilarion Moukala, Niama, Fabien Roch, Onikrotin, Dionne, Daszak, Peter, Johnson, Christine K., Mazet, Jonna A. K., Abaneh, Ola, Ababneh, Mustafa, Rafia, Jum, Sukor, Abd, Abdullah, Mohd Lufti, Abedin, Josefina, Abu-Basha, Ehab, Ali, Mohamed, Beal Akoundze, Junior, Akpaki, Joel, Al Hanandeh, Sief Addeen, Al Omari, Bilal, Al Shakil, Abdullah, Al-Zghoul, Mohammed, Albart, Stephenie Ann, Alshammari, Abdullah, Amarneh, Basil H., Ampofo, William, Andrew, Victoria, Ahn, Dao Le, Ankhanbaatar, Ulaankhuu, Anthony, Simon, Antonjaya, Ungke, Araya, Kidan, Arku, Jallah, Arshat, Norsharina, Asigbee, Theodore, Aung, Ohnmar, Awuni, Joseph, Ayukebong, James, Azian, Mohammed, Aziz, Nor Adilah, Ba, Aminata, Bassan, Ganzorig, Bagato, Ola, Bamba, Aboubacar, Bamba, Djenba, Barkhasbaatar, Ariunbaatar, Barrera, June, Basaraba, Cale, Bel-nono, Samuel, Belaganahalli, Manjunatha, Belay, Desalgen, Belkharia, Jaber, Binol, Ridzki M. F., Bird, Brian, Bista, Manisha, Biswas, Pitu, Blake, Matthew, Boatemaa, Linda, Bonason, Margret, Brandful, James, Brown, Joseph, Brownstein, John, Camara, Mamadi, Camara, Salif, Chai, Daniel, Chakraborty, Debapriyo, Chale, Hannah, Chaudhary, Ashok, Chea, Sokha, Chmura, Aleksei, Goossens, Benoit, Chow, Andrew, Churchill, Carolina, Commey, Abraham, Couacy-Hymann, Emmanuel, Coulibaly, Julien Kalpy, Cranfield, Michael, Damanik, Wirda, Damdinjav, Batchullum, Danial, Norhidayah, Dasak, Peter, David, Runie, Dawson, Patrick, Dembele, Arjouma, Deme, Awa, Desmond, James, Dewantari, Arghianditya Kresno, Dhanota, Jaseet, Dhole, Tapan, Diep, Nguyen Thi, Dionkounda, Artistide, Diop, Gaye Laye, Dodd, Kimberly, Dogby, Otilia, Dorjnyam, Tumendemberel, Dosso, Mireielle, Doumbouya, Kalil, Doumbouya, Mohamed Idriss, Doyle, Megan, Dramou, Simone, Drazenovich, Tracy, Duc Ahn, Dang, Duc Luu, Bach, Duendkae, Prateep, Duoc, Vu Trong, Duong, Tran Nhu, Duong, Veasna, Dursman, Huda, Dussart, Phillipe, Ee, Tan Jun, Ekiri, Abel, El Rifay, Amira S., El Shesheny, Rabel, El Taween, Ahmed N., Emmanuel, Zena Babu, Epstein, Jonathan H., Evans, Tierra Smiley, Fahmawi, Alaa, Fahn, Simeon, Feferholtz, Yasha, Ferdous, Jinnat, Fine, Amanda, Flora, Meerjady, Fransisco, Leilani, Fui Fui, Lem, Gabourie, Taylor, Gani, Millawati, Garbo, Michael, Gardner, Nicole, Gbamele, Marie, Ge, Xingyi, Gee, Lee Heng, Genovese, Brooke, Gibson, Alexandra, Gilardi, Kirsten, Gilbert, Martin, Gillis, Amethyst, Ginsos, Andrew, Godji Gnabro, Privat, Goldstein, Tracey, Gomaa, Moktar, Gomis, Jules, Gonzalez, Kevin, Grange, Zoe, Greig, Denise, Grodus, Michael, Gueu, Kpon Kakeuma Romeo, Gutierrez, Leticia, Haba, Dan Marcelin, Hamid, Suraya, Harris, Daniel K., Hashim, Abdul Kadir Abu, Hassan, Moushumi, Hassan, Quazar Nizamuddin, He, Qun, Hemachudha, Thiravat, Henry, Helen, Herbert, Ronald, Hijazeen, Zaidoun, Hilarion, Moukala Ndolo, Hill, Rebecca, Hoa, Nguyen Thi, Horwood, Paul, Hossain, Md. Enayet, Hossain, Saddam, Htun, Moh Moh, Hu, Ben, Hughes, Tom, Hul, Vibol, Van, Vo, Hussein, Fatima, Indola, Ghislain Dzeret, Iskandriati, Diah, Islam, Md. Tarikul, Islam, Shariful, Isnaim Ismail, Mohd, Ismail, Zuhair Bani, Iyanya, Jacques, Jaimin, Joel Judson, Jambai, Amara, Japning, Jeffrine Rovie Ryan, Japrin, Alexter, Jean Louis, Frantz, Joe, Titus, Johnson, Erica, Joly, Damien, Joshi, Jyotsna, Kalengkongan, Jusuf, Kalivogui, Douokoro, Kamara-Chieyoe, Nenneh, Kamau, Joseph, Kambale Syaluha, Eddy, Kandeil, Ahmed, Kane, Yogouba, Karesh, William, Kargo, Kandeh, Kasenda, Novie, Kayali, Ghazi, Kayed, Ahmed S., Kazwala, Rudovick, Ke, Changwen, Keates, Lucy, Kebede, Nigatu, Khamphaphongphane, Bouaphanh, Kheong, Chong Chee, Kilonzo, Christopher, Koffa, Ma-Sue, Kollie, Amos G., Kondiano, Marcel Sidik, Koropo, Michel, Kouamé Kouakou, Valere, Kouassi Koffi, Eugene, Kourouma, Mariam, Koutate, Abdoulaye Ousmane, Kowel, Citra Liv, Krou, Hermann Assemien, Kumakamba, Charles, Kutkat, Omnia, Lamah, François, Lan, Nguyen Thi, Lane, Jennifer, Lange, Christian, Larmouth, Emmanuel, Le Doux, Joseph Diffo, Leasure, Elizabeth, Leasure, Katherine, LeBreton, Mat, Lee, Jimmy, Lee, Helen, Lee, Mei Ho, Leno, Amara, Li, Hongying, Liang, Eliza, Liang, Neal, Lim, Dorothy, Lipkin, W. Ian, Liu, Jun, Lo, Modou Moustafa, Lojivis, Leonoris, Long, Nguyen Van, Lucas, Ashley, Lukusa, Jean Paul, Lungay, Victor, Lushima, Shongo, Lutwama, Julius, Ma, Wenjun, Machalaba, Catherine, Maganga, Grace, Magesa, Walter Simon, Mahmoud, Sara H., Makuwa, Maria, Makweta, Asha, Mamun, Abdullah Al, Manandhar, Prajwol, Maneeorn, Patarapol, Mann, Harjeet, Maomy, Bhele, Maptue, Victorine, Mathew, Alice, Mavoungou, Yanne Vanessa, Maw, Min Thein, Mazet, Jonna, Mbala, Placide, Mbuba, Emmanuel, Mbunwe, Eric, McIver, David, Mendelsohn, Emma, Miegakanda, Valchy Bel-Bebi, Minh, Phan Quang, Mkali, Happy, Moatasim, Yassmin, Mombouli, Jean Vivien, Monagin, Corina, Montecino-Latorre, Diego, Mossoun Mossoun, Arsene, Mostafa, Ahmed, Mouiche, Moctar, Mpassi, Romain Bagamboula, Msigwa, Alphonce, Mudakikwa, Antoine, Mugok, Laura Benedict, Mulembakani, Prime, Murray, Suzan, Musa, Fakhrul Hatta, Musabimana, Pacifique, Mutura, Samson, Mwamlima, Tunu, Mwanzanilla, Mwokozi, Myaing, Tin Tin, Myat, Theingi Win, Myo Chit, Aung, N’faly, Magassouba, N’Guettia, Manzan Jean, N’télo, Anatole, Nakimera, Sylivia, Nam, Vu Sinh, Napit, Rajindra, Nathan, Senthilvel K. S. S., Navarrete-Macias, Isamara, Ndebe, Kortu M., Ndiaye, Amadou, Ndiaye, Daouda, Negash, Yohannes, Nga, Nguyen Thi Thanh, Ngay, Ipos, Ngoc, Pham Thi Bich, Niama, Fabien, Nina, Rock Aimé, Niyonzima, Schadrack, Nkom, Felix, Nkoua, Cynthia, Noordin, Noorliza, Noviana, Rachmitasari, Nwobegahay, Julius, Nziza, Julius, O’Rourke, Daniel, O’Rourke, Tammie, Obodai, Evangeline, Okello Okwir, Ricky, Olival, Kevin, Olson, Sarah, Olva, Onkirotin Dionne, Ontiveros, Victoria, Opook, Fernandes, Panchadcharam, Chandrawathani, Pandit, Pranav, Parra, Henri-Joseph, Phuc, Tran Minh, Phuong, Nguyen Thanh, Poultolnor, Jackson Y., Pradhan, Saman, Preston, Eunah Cho, Pruvot, Mathieu, Purevtseren, Dulam, Puri, Dhiraj, Quang, Le Tin Vinh, Rachmitasari, Novie, Rahman, Kaisar, Rahman, Mizanur, Rahman, Mohammed Ziaur, Rahman, Mustafizur, Ramirez, Diana, Randhawa, Nistara, Raut, Samita, Rosario, Joseph, Ross, Albert, Ross, Noam, Rostal, Melinda, Roualdes, Pamela, Rubin, Eddy, Rumi, Aftab Uddin, Rundi, Christina, Sackie, Melkor, Sajali, Zikankuba, Samuels, Sandra G, Sango, Mathias, Saptu, Ammar Rafidah, Saraka, Daniel N’guessan, Sartee, Alvis A., Sayandouno, Sia Alida, Seck, Mame Cheikh, Sedor, Victoria, Sharma, Ajay Narayan, Sharminie, Velsri, Shehata, Mahmoud M., Sheikh, Gafur, Shi, Zhengli, Shiilegdamba, Enkhtuvshin, Shrestha, Bishwo, Shrestha, Rima, Sidibey, Mohammed, Silithammavong, Soubanh, Simon, Daniel, Sion, Emilly, Sipangkui, Symphorosa, Sitam, Frankie Thomas, Smith, Brett, Smith, Bridgette, Smith, Woutrina, Sodnom, Batsikhan, Ssebide, Benard, Suleiman, Maria, Sullivan, Ava, Sungif, Nur Amirah, Suu-Ire, Richard, Sy, Mouhamed, Takuo, Jean Michel, Talafha, Hani, Tamoufe, Ubald, Tetteh, Emmanuel, Than Toe, Aung, Thanda, Lanash, Thanh Long, Ngo, Thein, Wai Zin, Theppangna, Watthana, Thinh, Nguyen Duc, Thuy, Hoang Bich, Thuy, Nguyen Thu, Togami, Eri, Tolno, Moise Bendoua, Tolovou, Kevin, Topani, Rahmat, Tremeau-Bravard, Alexandre, Trupin, Ian, Tumushime, Jean Claude, Tun, Kyaw Yan Naing, Turay, Joseph, Uddin, Helal, Uhart, Marcela, Ureda, Nicole, Valitutto, Marc, Verasahib, Khebir, Vodzak, Megan, Wacharapluesadee, Supaporn, Wahad, Mohammad Yuery Wazlan Abdul, Watson, Brooke, Wells, Heather, White, Allison, Willoughby, Anna, Wiyatno, Ageng, Wolking, David, Yang, Xinglou, Yao, Lim Ming, Yombouno, Sayon, Young, Cristin, Zambrana-Torrelio, Carlos, Zeid, Zahidah Izzati, Zghoul, Ghadeer, Zhang, Libiao, Zhang, Yunzhi, Zhu, Guangjian, Zimmerman, Dawn, Zoumarou, Daba, Aguirre, Alonso, Aguirre, Luis, Akongo, Mark-Joel, Alandia Robles, Erika, Ambu, Laurentius, Ayala Aguilar, Glenda, Barcena, Luis, Barradas, Rosario, Basir, Misliah Mohamad, Bogich, Tiffany, Bounga, Gerard, Buchy, Philippe, Bunn, David, Byaruba, Denis, Cameron, Ken, Carroll, Dennis, Cavero, Nancy, Cespedes, Manuel, Che, Xiaoyu, Chiu, Charles, Chor, Kimashalen, Clements, Andrew, Dary Acevedo, Luz, de Almeida Campos, Angelica, De La Puente, Micaela, de Lamballerie, Xavier, de Paula, Catia, Delwart, Eric, Diffo Le Doux, Joseph, Doyle-Capitman, Catherine, Durigon, Edison, Fair, Joseph, Ferrer-Paris, José R., Formenty, Pierre, Galarza, Isabel, Garcia, Joel, Grard, Gilda, Greatorex, Zoe, Harris, Laurie, Hitchens, Peta, Ho, Mei, Hosseini, Parviez, In, Samath, Iñíguez, Volga, Jain, Komal, Jamaluddin, Abd. Aziz, Johnson, Christine, Jones, Kate, Joyner, Priscilla, Kaba, Serge, Kambale, Eddy, Kataregga, Abdulhameed, Kelly, Terra, Khammavong, Kongsy, Kilpatrick, A. Marm, Laimun, Samsir, Lee, Mei-Ho, LeRoy, Eric, Levinson, Jordan, Levy, Marc, Limachi, Rolando, Loh, Elizabeth, Lowenstine, Linda J., Luis Mollericona, José, Maganga, Ruth, Malakalinga, Joseph, Manhas, Melissa, Marra, Pete, Mbabazi, Rachael, Medellín, Rodrigo, Mendoza, Patricia, Miller, Sireeda, Miranda, Flavia, Mitchell, Megan, Mohamed, Ramlan, Mollard, Debbie, Morse, Stephen, Mouellet, Wivine, Moya, Isabel, Murillo, Yovanna, Murray, Kris, Muyembe Tamfum, Jean-Jacques, Nassar, Fernando, Nathan, Sen, Nsengimana, Olivier, Ogg Keatts, Lucy, Ojeda-Flore, Rafael, Okwir Okello, Ricky, Ondzie, Alain, Paweska, Janusz, Pereira, Alisa, Pereira, Victoria, Perez, Alberto, Perez, Jocelyn, Phon, Simorn, Reed, Patricia, Rejmanek, Dan, Rico, Oscar, Rivera, Rosario, Romero, Monica, Roy, Celina, Saepuloh, Uus, Schneider, Brad, Schwind, Jessica, Singhalath, Sinpakhome, Smith, Kristine, Suárez, Fabiola, Suzan, Gerardo, Thanh Nga, Nguyen Thi, Thomas, Kate, Ticona, Herminio, VanWormer, Elizabeth, Villar, Sandra, Weisman, Wendy, Westfall, Michael, Whittier, Chris, Wicker, Leanne, Wolfe, Nathan, Yang, Angela, Zariquiey, Carlos, Zhang, Shu-Yi, Zorine Nkouants, Baudelaire, Zainuddin, Zainal, Chrisman, Cara, Pabst, August, Shek, Amalhin, and Trostle, Murray

Subjects
0301 basic medicine, Behavioral risk, medicine.medical_specialty, Behavioural sciences, Disease, Community integration, Basic Behavioral and Social Science, 03 medical and health sciences, 0302 clinical medicine, Clinical Research, 2.3 Psychological, Behavioral and Social Science, Agency (sociology), medicine, 2.2 Factors relating to the physical environment, GE1-350, Aetiology, One health, Social science research, business.industry, Prevention, Research, Public health, PREDICT Consortium, Public relations, Focus group, Environmental sciences, Good Health and Well Being, 030104 developmental biology, One Health, Multi-disciplinary surveillance, social and economic factors, Public aspects of medicine, RA1-1270, Infection, Psychology, International development, business, 030217 neurology & neurosurgery
Abstract

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security. Supplementary Information The online version contains supplementary material available at 10.1186/s42522-021-00036-9.

Published
2021

17. New SARS-CoV-2 Variant from Jordan

Author

Alanagreh, Lo’ai, primary, Ababneh, Mustafa, additional, Al-Shudifat, Abdel-Ellah, additional, Ajlouny, Mai, additional, Abu-Shaikh, Hanan, additional, Alzoughool, Foad, additional, Al-zghoul, Mohammad-Borhan, additional, Atoum, Manar, additional, and Mahafzeh, Azmi, additional

Published
2021
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33. PCR Amplification and Sequencing Analysis of Full-Length Turkey Coronavirus Spike Gene

Author

Chen, Yi-Ning, Akin, Aydemir, Loa, Chien Chang, Ababneh, Mustafa, Cao, Jianzhong, Chen, Wan-Jung, Wu, Ching Ching, and Lin, Tsang Long

Subjects
Genotype, Spike gene, Sequencing, Turkey coronavirus, Article
Abstract

Turkey coronaviral enteritis caused by turkey coronavirus (TCoV) continues to infect turkey flocks, resulting in significant economic loss. Determining and understanding genetic relationships among different TCoV isolates or strains is important for controlling the disease. Using two-step RT-PCR assays that amplify the full length of TCoV spike (S) gene, TCoV isolates can be sequenced, analyzed, and genotyped. Described in this chapter is the protocol on PCR amplification and sequencing analysis of full-length TCoV S gene. Such protocol is useful in molecular epidemiology for establishing an effective strategy to control the transmission of TCoV among turkey flocks.

Published
2015

35. The Role of Big Data and Machine Learning in COVID-19.

Author

ABABNEH, Mustafa, ALJARRAH, Aayat, and KARAGOZLU, Damla

Subjects
*COVID-19, *BIG data, *MACHINE learning, *GLOBAL Positioning System, *SMART cities, *TECHNICAL reports
Abstract

The big rise in the existence of digital data contributed to creating many good chances, especially related to corporations, institutions and firms. Also, it gives the capability to scrimp data regarding its major or area, where the countries have benefited from the analysis of big data (BD) greatly in the face of epidemics and diseases, especially COVID-19 since BD is now available everywhere around us, from official reports and scientific studies related to virology and epidemiology. The general aim of this study is to clarify how the conjunction among both BD and machine learning (ML) created huge differences in data science and a big influence on the applications related to a lot of fields chiefly in COVID-19. The method which is used in this study 'relevance tree' by identifying papers related to ML and BD, especially in COVID-19. The results have been shown that the use of reinforcement learning in analyzing BD provides effective and tremendous results, although it faces many challenges and restrictions that have been explained in detail in this study. In addition, the results showed that most of the countries in the time of Corona turned into smart cities, totally dependent on smart applications based on the analysis of BD using ML, and one of the most important applications that were circulated around the world global positioning system. In addition to the results that have been found, data privacy is one of the most important challenges facing data analysis. Consequently, it recommended future researchers to focus on studying the challenges faced by ML in analyzing medical data in the COVID-19 era. [ABSTRACT FROM AUTHOR]

Published
2020
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36. First detection of foot‐and‐mouth disease virus O/ME‐SA/ Ind2001e sublineage in Jordan.

Author

Ababneh, Mustafa M., Hananeh, Wael, Bani Ismail, Zuhair, Hawawsheh, Majid, Al‐Zghoul, Mohammad, Knowles, Nick J., and Maanen, Kees

Subjects
*FOOT & mouth disease, *VIRUS diseases, *ANIMAL mechanics, *DOMESTIC animals, *LIVESTOCK productivity, *GOAT diseases, *SHEEP diseases, *CLASSICAL swine fever
Abstract

Foot‐and‐mouth disease (FMD) is a highly contagious vesicular disease that is caused by the FMD virus (FMDV). This disease affects both wild and domestic cloven‐hoofed animals, and the latter of which includes cattle, swine, sheep and goats. FMD is endemic to Jordan and has a severe impact on the productivity of domestic livestock. In January 2017, FMD outbreaks were detected in different animal species across Jordan, resulting in high mortality rates among young lamb and goat populations as well as causing classic FMD symptoms in cattle. In this study, clinical specimens were collected from animals affected by FMD. The results obtained from sequencing the VP1 gene place the studied FMDV isolate within the FMDV O/ME‐SA/ Ind2001e sublineage. Phylogenetic analysis of VP1 suggests that the O/JOR/1/2017 isolate is very similar to that of viruses isolated from Saudi Arabia in 2016. The possible introduction of this strain to Jordan might occur through transboundary animal movement or other transmission routes from Saudi Arabia, a neighbouring country. [ABSTRACT FROM AUTHOR]

Published
2020
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43. Female reproductive tract anatomy of the endangered Arabian oryx (Oryx leucoryx) in Jordan

Author

Eljarah, Abdulhakeem H., Al-Zghoul, Mohd B., Jawasreh, Khaleel, Bani Ismail, Zuhair A., Ababneh, Mustafa M., Elhalah, Ashraf N., and Alsumadi, Maen M.

Subjects
female reproductive system, ovary, vagina, morphometry, cycling animals, not-cycling animals
Abstract

Female reproductive anatomy of the Arabian oryx is unknown. In this study, reproductive tracts of seven female Arabian oryx (aged 2 to 7 years) were examined to characterize their reproductive anatomy. Observations and measurements were obtained in situ from dead animals during necropsy. Animals were allocated into two groups: cycling (n=3; follicles or corpora lutea present) and not-cycling (n=4; follicles or corpora lutea absent). Different reproductive tract segments for each animal in both groups were measured using a digital caliper. The mean, SD and range for each reproductive tract segment were generated and compared between groups. Female oryx reproductive anatomy share some anatomical characteristics with that of domestic ruminants except that the oryx uterus has no distinct uterine body and the cervix has two internal openings for each respective uterine horn. In addition, there were more than 8 rows of caruncles within each uterine horn. There were significant differences in the length and width (P0.05). Posterior and anterior vaginal lengths varied between cycling and not-cycling groups (P0.05). Defining this unique morphology of female Arabian oryx reproductive anatomy will help in the development of appropriate reproductive techniques in order to propagate this endangered species and control its reproduction., Italian Journal of Anatomy and Embryology, Vol 117, No 3 (2012)

Published
2012
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46. Detection, Identification, and Prevalence of Pathogenic Vibrio parahaemolyticus in Fish and Coastal Environment in Jordan.

Author

Alaboudi, Akram R., Ababneh, Mustafa, Osaili, Tareq M., and Shloul, Khalaf Al

Subjects
*VIBRIO parahaemolyticus, *BACTERIAL diseases in fishes, *DISEASE prevalence, *COASTAL ecology, MICROORGANISM identification
Abstract

Vibrio parahaemolyticus is widely distributed in the marine environments and considered the leading cause of human gastroenteritis in Asian countries. A total of 150 marketed fish and 50 water and sediment samples from the Gulf of Aqaba were examined for the prevalence of pathogenic strains of V. parahaemolyticus. A total of 132 typical isolates obtained from the primary selective medium (thiosulfate-citrate bile salt sucrose agar) and showed positive biochemical properties were subjected to confirmation by polymerase chain reaction targeting the gyrB and toxR genes. These genes were confirmed at rates of 82% (108 isolates) and 72% (95 isolates), respectively. The toxR positive isolates were tested for the presence of thermolabile hemolysin ( tlh), thermostable direct hemolysin ( tdh), and tdh-related hemolysin ( trh) virulence genes. Accordingly, the prevalence rates of pathogenic V. parahaemolyticus were 4%, 8%, and 12% in sediment, water, and fish samples, respectively. The 16S rRNA amplification and sequences were conducted for confirmation of the isolates and showing the relatedness among these isolates. The results showed that both 16S rRNA and toxR assays had same sensitivity and tested isolates had high nucleotide similarity irrespective of their sources. [ABSTRACT FROM AUTHOR]

Published
2016
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