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2. Polygenic score distribution differences across European ancestry populations: implications for breast cancer risk prediction.

Author

Yiangou, Kristia, Mavaddat, Nasim, Dennis, Joe, Zanti, Maria, Wang, Qin, Bolla, Manjeet, Abubakar, Mustapha, Ahearn, Thomas, Andrulis, Irene, Anton-Culver, Hoda, Antonenkova, Natalia, Arndt, Volker, Aronson, Kristan, Augustinsson, Annelie, Baten, Adinda, Behrens, Sabine, Bermisheva, Marina, de Gonzalez, Amy, Białkowska, Katarzyna, Boddicker, Nicholas, Bodelon, Clara, Bogdanova, Natalia, Bojesen, Stig, Brantley, Kristen, Brauch, Hiltrud, Brenner, Hermann, Camp, Nicola, Canzian, Federico, Castelao, Jose, Cessna, Melissa, Chang-Claude, Jenny, Chenevix-Trench, Georgia, Chung, Wendy, Colonna, Sarah, Couch, Fergus, Cox, Angela, Cross, Simon, Czene, Kamila, Daly, Mary, Devilee, Peter, Dörk, Thilo, Dunning, Alison, Eccles, Diana, Eliassen, A, Engel, Christoph, Eriksson, Mikael, Evans, D, Fasching, Peter, Fletcher, Olivia, Flyger, Henrik, Fritschi, Lin, Gago-Dominguez, Manuela, Gentry-Maharaj, Aleksandra, González-Neira, Anna, Guénel, Pascal, Hahnen, Eric, Haiman, Christopher, Hamann, Ute, Hartikainen, Jaana, Ho, Vikki, Hodge, James, Hollestelle, Antoinette, Honisch, Ellen, Hooning, Maartje, Hoppe, Reiner, Hopper, John, Howell, Sacha, Howell, Anthony, Jakovchevska, Simona, Jakubowska, Anna, Jernström, Helena, Johnson, Nichola, Kaaks, Rudolf, Khusnutdinova, Elza, Kitahara, Cari, Koutros, Stella, Kristensen, Vessela, Lacey, James, Lambrechts, Diether, Lejbkowicz, Flavio, Lindblom, Annika, Lush, Michael, Mannermaa, Arto, Mavroudis, Dimitrios, Menon, Usha, Murphy, Rachel, Nevanlinna, Heli, Obi, Nadia, Offit, Kenneth, Park-Simon, Tjoung-Won, Patel, Alpa, Peng, Cheng, Peterlongo, Paolo, Pita, Guillermo, Plaseska-Karanfilska, Dijana, Pylkäs, Katri, Radice, Paolo, Rashid, Muhammad, Rennert, Gad, and Roberts, Eleanor

Subjects
Breast cancer, Polygenic risk scores, Risk calibration, Risk prediction, Humans, Female, Breast Neoplasms, Genetic Predisposition to Disease, Multifactorial Inheritance, White People, Risk Assessment, Risk Factors, Europe, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Middle Aged, Genotype
Abstract

BACKGROUND: The 313-variant polygenic risk score (PRS313) provides a promising tool for clinical breast cancer risk prediction. However, evaluation of the PRS313 across different European populations which could influence risk estimation has not been performed. METHODS: We explored the distribution of PRS313 across European populations using genotype data from 94,072 females without breast cancer diagnosis, of European-ancestry from 21 countries participating in the Breast Cancer Association Consortium (BCAC) and 223,316 females without breast cancer diagnosis from the UK Biobank. The mean PRS was calculated by country in the BCAC dataset and by country of birth in the UK Biobank. We explored different approaches to reduce the observed heterogeneity in the mean PRS across the countries, and investigated the implications of the distribution variability in risk prediction. RESULTS: The mean PRS313 differed markedly across European countries, being highest in individuals from Greece and Italy and lowest in individuals from Ireland. Using the overall European PRS313 distribution to define risk categories, leads to overestimation and underestimation of risk in some individuals from these countries. Adjustment for principal components explained most of the observed heterogeneity in the mean PRS. The mean estimates derived when using an empirical Bayes approach were similar to the predicted means after principal component adjustment. CONCLUSIONS: Our results demonstrate that PRS distribution differs even within European ancestry populations leading to underestimation or overestimation of risk in specific European countries, which could potentially influence clinical management of some individuals if is not appropriately accounted for. Population-specific PRS distributions may be used in breast cancer risk estimation to ensure predicted risks are correctly calibrated across risk categories.

Published
2024

3. Crown-Like Structures in Breast Adipose Tissue: Finding a 'Needle-in-a-Haystack' using Artificial Intelligence and Collaborative Active Learning on the Web

Author

Bhawsar, Praphulla MS, Ramin, Cody, Lenz, Petra, Duggan, Máire A, Harris, Alexandra R, Jenkins, Brittany, Cora, Renata, Abubakar, Mustapha, Gierach, Gretchen, Saltz, Joel, and Almeida, Jonas S

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Crown-like structures (CLS) in breast adipose tissue are formed as a result of macrophages clustering around necrotic adipocytes in specific patterns. As a histologic marker of local inflammation, CLS could have potential diagnostic utility as a biomarker for breast cancer risk. However, given the scale of whole slide images and the rarity of CLS (a few cells in an entire tissue sample), microscope-based manual identification is a challenge for the pathologist. In this report, we describe an artificial intelligence pipeline to solve this needle-in-a-haystack problem. We developed a zero-cost, zero-footprint web platform to enable remote operation on digital whole slide imaging data directly in the web browser, supporting collaborative annotation of the data by multiple experts. The annotated images then allow for incremental training and fine tuning of deep neural networks via active learning. The platform is reusable and requires no backend or installations, thus ensuring the data remains secure and private under the governance of the end user. Using this platform, we iteratively trained a CLS identification model, evaluating the performance after each round and adding examples to the training data to overcome failure cases. The resulting model, with an AUC of 0.90, shows promise as a first-pass screening tool to detect CLS in breast adipose tissue, considerably reducing the workload of the pathologist. Platform available at: https://episphere.github.io/path

Published
2024

4. TMA-Grid: An open-source, zero-footprint web application for FAIR Tissue MicroArray De-arraying

Author

Ge, Aaron, Saha, Monjoy, Duggan, Maire A., Lenz, Petra, Abubakar, Mustapha, García-Closas, Montserrat, Balasubramanian, Jeya, Almeida, Jonas S., and Bhawsar, Praphulla MS

Subjects
Quantitative Biology - Tissues and Organs, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Abstract

Background: Tissue Microarrays (TMAs) significantly increase analytical efficiency in histopathology and large-scale epidemiologic studies by allowing multiple tissue cores to be scanned on a single slide. The individual cores can be digitally extracted and then linked to metadata for analysis in a process known as de-arraying. However, TMAs often contain core misalignments and artifacts due to assembly errors, which can adversely affect the reliability of the extracted cores during the de-arraying process. Moreover, conventional approaches for TMA de-arraying rely on desktop solutions.Therefore, a robust yet flexible de-arraying method is crucial to account for these inaccuracies and ensure effective downstream analyses. Results: We developed TMA-Grid, an in-browser, zero-footprint, interactive web application for TMA de-arraying. This web application integrates a convolutional neural network for precise tissue segmentation and a grid estimation algorithm to match each identified core to its expected location. The application emphasizes interactivity, allowing users to easily adjust segmentation and gridding results. Operating entirely in the web-browser, TMA-Grid eliminates the need for downloads or installations and ensures data privacy. Adhering to FAIR principles (Findable, Accessible, Interoperable, and Reusable), the application and its components are designed for seamless integration into TMA research workflows. Conclusions: TMA-Grid provides a robust, user-friendly solution for TMA dearraying on the web. As an open, freely accessible platform, it lays the foundation for collaborative analyses of TMAs and similar histopathology imaging data. Availability: Web application: https://episphere.github.io/tma-grid Code: https://github.com/episphere/tma-grid Tutorial: https://youtu.be/miajqyw4BVk, Comment: NA

Published
2024

8. Moving towards FAIR practices in epidemiological research

Author

Garcia-Closas, Montserrat, Ahearn, Thomas U., Gaudet, Mia M., Hurson, Amber N., Balasubramanian, Jeya Balaji, Choudhury, Parichoy Pal, Gerlanc, Nicole M., Patel, Bhaumik, Russ, Daniel, Abubakar, Mustapha, Freedman, Neal D., Wong, Wendy S. W., Chanock, Stephen J., de Gonzalez, Amy Berrington, and Almeida, Jonas S

Subjects
Quantitative Biology - Populations and Evolution
Abstract

Reproducibility and replicability of research findings are central to the scientific integrity of epidemiology. In addition, many research questions require combiningdata from multiple sources to achieve adequate statistical power. However, barriers related to confidentiality, costs, and incentives often limit the extent and speed of sharing resources, both data and code. Epidemiological practices that follow FAIR principles can address these barriers by making resources (F)indable with the necessary metadata , (A)ccessible to authorized users and (I)nteroperable with other data, to optimize the (R)e-use of resources with appropriate credit to its creators. We provide an overview of these principles and describe approaches for implementation in epidemiology. Increasing degrees of FAIRness can be achieved by moving data and code from on-site locations to the Cloud, using machine-readable and non-proprietary files, and developing open-source code. Adoption of these practices will improve daily work and collaborative analyses, and facilitate compliance with data sharing policies from funders and scientific journals. Achieving a high degree of FAIRness will require funding, training, organizational support, recognition, and incentives for sharing resources. But these costs are amply outweighed by the benefits of making research more reproducible, impactful, and equitable by facilitating the re-use of precious research resources by the scientific community.

Published
2022

11. Incorporating progesterone receptor expression into the PREDICT breast prognostic model

Author

Grootes, Isabelle, Keeman, Renske, Blows, Fiona M, Milne, Roger L, Giles, Graham G, Swerdlow, Anthony J, Fasching, Peter A, Abubakar, Mustapha, Andrulis, Irene L, Anton-Culver, Hoda, Beckmann, Matthias W, Blomqvist, Carl, Bojesen, Stig E, Bolla, Manjeet K, Bonanni, Bernardo, Briceno, Ignacio, Burwinkel, Barbara, Camp, Nicola J, Castelao, Jose E, Choi, Ji-Yeob, Clarke, Christine L, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Devilee, Peter, Dörk, Thilo, Dunning, Alison M, Dwek, Miriam, Easton, Douglas F, Eccles, Diana M, Eriksson, Mikael, Ernst, Kristina, Evans, D Gareth, Figueroa, Jonine D, Fink, Visnja, Floris, Giuseppe, Fox, Stephen, Gabrielson, Marike, Gago-Dominguez, Manuela, García-Sáenz, José A, González-Neira, Anna, Haeberle, Lothar, Haiman, Christopher A, Hall, Per, Hamann, Ute, Harkness, Elaine F, Hartman, Mikael, Hein, Alexander, Hooning, Maartje J, Hou, Ming-Feng, Howell, Sacha J, Investigators, ABCTB, Investigators, kConFab, Ito, Hidemi, Jakubowska, Anna, Janni, Wolfgang, John, Esther M, Jung, Audrey, Kang, Daehee, Kristensen, Vessela N, Kwong, Ava, Lambrechts, Diether, Li, Jingmei, Lubiński, Jan, Manoochehri, Mehdi, Margolin, Sara, Matsuo, Keitaro, Taib, Nur Aishah Mohd, Mulligan, Anna Marie, Nevanlinna, Heli, Newman, William G, Offit, Kenneth, Osorio, Ana, Park, Sue K, Park-Simon, Tjoung-Won, Patel, Alpa V, Presneau, Nadege, Pylkäs, Katri, Rack, Brigitte, Radice, Paolo, Rennert, Gad, Romero, Atocha, Saloustros, Emmanouil, Sawyer, Elinor J, Schneeweiss, Andreas, Schochter, Fabienne, Schoemaker, Minouk J, Shen, Chen-Yang, Shibli, Rana, Sinn, Peter, Tapper, William J, Tawfiq, Essa, Teo, Soo Hwang, Teras, Lauren R, Torres, Diana, Vachon, Celine M, van Deurzen, Carolien HM, Wendt, Camilla, and Williams, Justin A

Subjects
Cancer, Breast Cancer, Breast Neoplasms, Female, Humans, Progesterone, Prognosis, Receptor, ErbB-2, Receptors, Progesterone, PREDICT Breast, breast cancer, Progesterone receptor, ABCTB Investigators, kConFab Investigators, Receptor, erbB-2, Oncology and Carcinogenesis, Public Health and Health Services, Oncology & Carcinogenesis
Abstract

BackgroundPredict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2).MethodThe prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance.ResultsHaving a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0.902 for patients with ER-positive tumours (p = 2.3 × 10-6) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted.ConclusionThe inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predictions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration.

Published
2022

14. Tumour Infiltrating Lymphocytes (TILs) and immune composition in breast cancer patients from Kenya: Spatial distributions and associations with risk factors and tumour characteristics

Author

Sayed, Shahin, Koka, Hela, Abubakar, Mustapha, Gardner, Kevin, Salgado, Roberto, Moloo, Zahir, Caban-Ureña, Ambar Beatriz, Rosen, Daniel, Castro, Patricia, Saleh, Mansoor, Shaikh, Asim Jamal, Shah, Jasmit, Figueroa, Jonine, Makokha, Francis, Ha, Hien Khanh, Wang, Zhong, Magangane, Pumza, Naidoo, Richard, Ngundo, Veronica, Yang, Xiaohong Rose, and Govender, Dhirendra

Published
2023
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15. Mosquito control exposures and breast cancer risk: analysis of 1071 cases and 2096 controls from the Ghana Breast Health Study

Author

Olivos, Naomie, Banta, Jim E., Spencer-Hwang, Rhonda, Ansong, Daniel, Beane Freeman, Laura E., Clegg-Lamptey, Joe-Nat, Wiafe-Addai, Beatrice, Edusei, Lawrence, Adjei, Ernest, Titiloye, Nicholas, Dedey, Florence, Aitpillah, Francis, Oppong, Joseph, Vanderpuye, Verna, Osei-Bonsu, Ernest, Ahearn, Thomas U., Biritwum, Richard, Yarney, Joel, Awuah, Baffour, Nyarko, Kofi, Garcia-Closas, Montserrat, Abubakar, Mustapha, Brinton, Louise A., Figueroa, Jonine D., and Wiafe, Seth

Published
2023
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17. GWAS Explorer: an open-source tool to explore, visualize, and access GWAS summary statistics in the PLCO Atlas

Author

Machiela, Mitchell J., Huang, Wen-Yi, Wong, Wendy, Berndt, Sonja I., Sampson, Joshua, De Almeida, Jonas, Abubakar, Mustapha, Hislop, Jada, Chen, Kai-Ling, Dagnall, Casey, Diaz-Mayoral, Norma, Ferrell, Mary, Furr, Michael, Gonzalez, Alex, Hicks, Belynda, Hubbard, Aubrey K., Hutchinson, Amy, Jiang, Kevin, Jones, Kristine, Liu, Jia, Loftfield, Erikka, Loukissas, Jennifer, Mabie, Jerome, Merkle, Shannon, Miller, Eric, Minasian, Lori M., Nordgren, Ellen, Park, Brian, Pinsky, Paul, Riley, Thomas, Sandoval, Lorena, Saxena, Neeraj, Vogt, Aurelie, Wang, Jiahui, Williams, Craig, Wright, Patrick, Yeager, Meredith, Zhu, Bin, Zhu, Claire, Chanock, Stephen J., Garcia-Closas, Montserrat, and Freedman, Neal D.

Published
2023
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18. Data Encryption in Fog Computing Using Hybrid Cryptography with Integrity Check

Author

Ejim, Samson, Gital, Abdulsalam Ya’u, Chiroma, Haruna, Lawal, Mustapha Abdulrahman, Abubakar, Mustapha Yusuf, Kubi, Ganaka Musa, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Thakur, Manoj, editor, Agnihotri, Samar, editor, Rajpurohit, Bharat Singh, editor, Pant, Millie, editor, Deep, Kusum, editor, and Nagar, Atulya K., editor

Published
2023
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21. A novel array of real-time RT-PCR assays for the rapid pathotyping of type I avian paramyxovirus (APMV-1)

Author

Fortin, Andrea, Laconi, Andrea, Monne, Isabella, Zohari, Siamak, Andersson, Kristofer, Grund, Christian, Cecchinato, Mattia, Crimaudo, Marika, Valastro, Viviana, D’Amico, Valeria, Bortolami, Alessio, Gastaldelli, Michele, Varotto, Maria, Abdelrahman, Amgad, Amarin, Nadim, Abubakar, Mustapha Bala, Belayneh, Redeat, Cyprien, Yapi Bokpè, Christodoulou, Vasiliki, Chvala, Ilya, Dodovski, Aleksandar, Ghafouri, Seyed Ali, Giasuddin, Mohammed, Hassan, Magdy, Kammon, Abdulwahab, Shittu, Ismaila, Snoeck, Chantal J., Steensel, Mieke, Suarez, David, Torchetti, Mia Kim, Tshipambe, Serge Mpiana, Ouermi Zerbo, Lamouni Habibata, Terregino, Calogero, and Panzarin, Valentina

Published
2023
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26. Proceedings of the fifth international Molecular Pathological Epidemiology (MPE) meeting

Author

Yao, Song, Campbell, Peter T., Ugai, Tomotaka, Gierach, Gretchen, Abubakar, Mustapha, Adalsteinsson, Viktor, Almeida, Jonas, Brennan, Paul, Chanock, Stephen, Golub, Todd, Hanash, Samir, Harris, Curtis, Hathaway, Cassandra A., Kelsey, Karl, Landi, Maria Teresa, Mahmood, Faisal, Newton, Christina, Quackenbush, John, Rodig, Scott, Schultz, Nikolaus, Tearney, Guillermo, Tworoger, Shelley S., Wang, Molin, Zhang, Xuehong, Garcia-Closas, Montserrat, Rebbeck, Timothy R., Ambrosone, Christine B., and Ogino, Shuji

Published
2022
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28. The impact of an educational intervention on undergraduate students’ knowledge, acceptability, and willingness to pay for dapivirine vaginal ring in Nigeria's first indigenous university: a single-arm, non-randomized study.

Author

Isah, Abdulmuminu, Ezenri, Gabriel, Obi, Ogechi, Okibe, Nnamdi A., Ma’aji, Hadiza Usman, Ugochukwu, Ezinwanne J., Eze, Cynthia C., Amoke, Chisom M., Ezeodimegwu, Augustus, Idabor, Charles C., Abubakar, Mustapha Muhammed, Iloabuchi, Francis, Ugwu, Ikenna John, Asogwa, Chukwuebuka M., Ukwe, Chinwe V., and Ukoha-kalu, Blessing Onyinye

Abstract

Background: This study aimed to assess the impact of an educational intervention on knowledge, acceptability, and willingness to pay (WTP) for dapivirine vaginal ring (DPV-VR) by undergraduate female students at the University of Nigeria (UNN). Methods: A cross-sectional design was adopted to obtain responses from the respondents using a validated 23-item questionnaire. A sample size of 1500 was estimated from five systematically sampled faculties. Their acceptability was accessed before and after educating them on the dapivirine vaginal ring (DPV-VR). WTP was determined in Naira (N490/$1) using contingent valuation. Descriptive statistics were used to summarize the findings, with inter-faculty comparison done with the Chi-squared test. Results: 1017 students responded to the questionnaire. The modal age was 18–24 years (754 [74.1%]), and most of them (886 [87.1%]) were unmarried. More than half of the respondents had tested for HIV (531 [52.2%])), with 3 (1.5%), 3 (1.7%), 2 (0.6%), 2 (1.8%) and 1 (0.5%) student from Arts, Biological Sciences, Pharmaceutical Sciences, Social Sciences, and Veterinary Medicine, respectively, having positive results. Only 304 (29.9%) of the students had prior knowledge of DPV-VR. There was about a two-fold increase in the acceptability of the dapivirine vaginal ring (DPV-VR) (294 to 596) after the intervention (p ≤ 0.001). Most of the students (466 [45.8%]) indicated that they would be willing to pay < N410.00 for a single dapivirine vaginal ring (DPV-VR). Conclusions: Many of the female students at UNN were willing to use the dapivirine vaginal ring (DPV-VR); even more after they were informed of its importance. Most of the students were willing to pay less than one dollar out-of-pocket for the ring. [ABSTRACT FROM AUTHOR]

Published
2025
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29. Risk factors for breast cancer subtypes by race and ethnicity: a scoping review.

Author

Hurson, Amber N, Ahearn, Thomas U, Koka, Hela, Jenkins, Brittany D, Harris, Alexandra R, Roberts, Sylvia, Fan, Sharon, Franklin, Jamirra, Butera, Gisela, Keeman, Renske, Jung, Audrey Y, Middha, Pooja, Gierach, Gretchen L, Yang, Xiaohong R, Chang-Claude, Jenny, Tamimi, Rulla M, Troester, Melissa A, Bandera, Elisa V, Abubakar, Mustapha, and Schmidt, Marjanka K

Subjects
ESTROGEN replacement therapy, HISPANIC American women, ESTROGEN receptors, BODY mass index, AFRICAN Americans, HISPANIC Americans
Abstract

Background Breast cancer consists of distinct molecular subtypes. Studies have reported differences in risk factor associations with breast cancer subtypes, especially by tumor estrogen receptor (ER) status, but their consistency across racial and ethnic populations has not been comprehensively evaluated. Methods We conducted a qualitative, scoping literature review using the Preferred Reporting Items for Systematic Reviews and Meta-analysis, extension for Scoping Reviews to investigate consistencies in associations between 18 breast cancer risk factors (reproductive, anthropometric, lifestyle, and medical history) and risk of ER-defined subtypes in women who self-identify as Asian, Black or African American, Hispanic or Latina, or White. We reviewed publications between January 1, 1990 and July 1, 2022. Etiologic heterogeneity evidence (convincing, suggestive, none, or inconclusive) was determined by expert consensus. Results Publications per risk factor ranged from 14 (benign breast disease history) to 66 (parity). Publications were most abundant for White women, followed by Asian, Black or African American, and Hispanic or Latina women. Etiologic heterogeneity evidence was strongest for parity, followed by age at first birth, postmenopausal body mass index, oral contraceptive use, and estrogen-only and combined menopausal hormone therapy. Evidence was limited for other risk factors. Findings were consistent across racial and ethnic groups, although the strength of evidence varied. Conclusion The literature supports etiologic heterogeneity by ER for some established risk factors that are consistent across race and ethnicity groups. However, in non-White populations evidence is limited. Larger, more comparable data in diverse populations are needed to better characterize breast cancer etiologic heterogeneity. [ABSTRACT FROM AUTHOR]

Published
2024
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36. Man with acute abdomen

Author

Kyaw, Naychi Kyaw, Abubakar, Mustapha, Shekhda, Kalyan Mansukhbhai, Tageldeen, Ramy, Afifi, Waleed, Halliru, Fatima Muhammad, and Ibrahim, Yakub Wahab

Published
2023

41. ASSESSMENT OF HAEMATOLOGICAL PROFILE AND OTHER PATHOLOGICAL CHANGES IN FARM CHICKENS NATURALLY INFECTED WITH CHICKEN ANAEMIA VIRUS IN MAIDUGURI.

Author

Shettima, Yasheruram Muhammed, Gambo, Halima Idris, Hamisu, Tasiu Mallam, Sajo, Mohammed Usman, Abubakar, Mustapha Bala, Majama, Yagama Bukar, and Wulgo, Ali Musa

Abstract

Copyright of Veterinaria is the property of University of Sarajevo, Veterinary Faculty 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
2024
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45. Risk factors for breast cancer subtypes by race and ethnicity: A scoping review of the literature

Author

Hurson, Amber, primary, Ahearn, Thomas, additional, Koka, Hela, additional, Jenkins, Brittany, additional, Harris, Alexandra, additional, Roberts, Sylvia, additional, Fan, Sharon, additional, Franklin, Jamirra, additional, Butera, Gisela, additional, Keeman, Renske, additional, Jung, Audrey, additional, Middha, Pooja, additional, Gierach, Gretchen, additional, Yang, Xiaohong, additional, Chang-Claude, Jenny, additional, Tamimi, Rulla, additional, Troester, Melissa A., additional, Bandera, Elisa V., additional, Abubakar, Mustapha, additional, Schmidt, Marjanka, additional, and Garcia-Closas, Montserrat, additional

Published
2024
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46. Ionised serum calcium reference interval among rural women of reproductive age in Abuja, Nigeria

Author

Angus Chukwuemeka Onyekwelu, Habiba Ibrahim Abdullahi, Aliyu Yabagi Isah, Abubakar Mustapha Jamda, and Maxwell Maduekwe Nwegbu

Subjects
federal capital territory, reproductive age, serum calcium, women, Medicine
Abstract

Background: Various medical conditions in pregnancy may be traced to suboptimal levels of serum calcium during pregnancy. Communities' derivation of normal serum calcium reference interval is imperative. Objective: The objective was to determine the normal free (ionised) serum calcium reference interval among women of reproductive age in the federal capital territory (FCT) of Nigeria. Materials and Methods: This was a cross-sectional study of 240 women from six primary health-care facilities in Abuja, Nigeria. Their blood samples were collected in serum separator bottles. The outcome measure was the determination of the reference interval of free (ionised) serum calcium among the participants. Results: The obtained normal reference interval of ionised serum calcium (iCa) was 0.88–1.4 mmol/L. The accompanying reference intervals for total protein and albumin were 5.7–9.4 mg/dl and 3.3–5.2 mg/dl, respectively. Conclusion: The derived reference interval of iCa in this study was 0.88–1.4 mmol/L, while the total calcium range was 2.18–2.82 mmol/L. These intervals are recommended for use in the Nigerian FCT and its environs as it provides lower intervals compared to the operational values. There is a need for a national derived value as this may change the practice.

Published
2021
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49. Mammary collagen architecture and its association with mammographic density and lesion severity among women undergoing image-guided breast biopsy

Author

Bodelon, Clara, Mullooly, Maeve, Pfeiffer, Ruth M., Fan, Shaoqi, Abubakar, Mustapha, Lenz, Petra, Vacek, Pamela M., Weaver, Donald L., Herschorn, Sally D., Johnson, Jason M., Sprague, Brian L., Hewitt, Stephen, Shepherd, John, Malkov, Serghei, Keely, Patricia J., Eliceiri, Kevin W., Sherman, Mark E., Conklin, Matthew W., and Gierach, Gretchen L.

Published
2021
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