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BECA

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About

Breast cancer continues being the most commonly diagnosed cancer and the most leading cause of cancer death among females in over 100 countries. The common diagnosis methods of breast cancer include mammography/digital mammography, magnetic resonance imaging (MRI), molecular breast imaging (MBI) and breast biopsy.

 

Our study uses multivariate analysis and AI-based approaches to facilitate early diagnosis of breast cancer and breast implant complication post surgery focusing on the underlying relationship between the metabolite changes and the clinical characteristics of the breast cancer.

The study therefore, is the first stage in the development of a low-cost and high throughput biomarker assay (or panel of biomarker profiles) which may help to detect changes linked to early stage breast cancer. Ultimately, these biomarkers may represent as an adjunct tool to the current mammogram diagnostic test, which give rapid assessment of breast cancer and implant complication and further may facilitate the personalized treatment plan for the patients. 

Haematology

Research Context

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Created using BioRender.com and clipart-library.com

Objectives

  • To identify the biomarkers for early detection of breast cancer (BC) and breast implant complication using minimally invasive samples through OMICs & Artificial intelligence (AI)-based approaches.

  • To investigate the underlying relationships between the biomarkers and inflammatory response that cause the rejection of breast implants following BC surgery.

  • To develop a low-cost and high throughput biomarker assay (or panel of biomarker profiles), detecting disease status, stage and type in the diagnosis and treatment of BC.

Research Findings Dissemination 

Presenting our interesting research findings at conference and Breast Cancer Clinical meeting.

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Meet Our Clinicians & Research Nurses

Research nurses at Glan Clwyd Hospital, BCUHB. 

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Research nurses at Wrexham Maelor Hospital, BCUHB. 
From left to right: Ms Victoria Whitehead, Ms Heulwen Owens, Ms Lisa Jobes and Ms Louise Ransome

Research nurses at Bronglais General Hospital, Hywel Dda University Health Board. 
Site initiation visit with the clinicians and QA team on August 9th, 2023.

Gallery

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Team engagement meeting for BECA with Prof. Mandana O Pennick (Consultant Oncoplastic Breast Surgeon) cum co-supervisor for the project, radiology consultant, breast implant consultant and research nurses at Betsi Cadwaladr University Health Board (BCUHB), Glan Clwyd Hospital, Rhyl on June 14th, 2022.

Clinical governance meeting at Postgraduate Seminar Room, Glan Clwyd Hospital, Rhyl on June 13th, 2023.

From left: Prof. Luis Mur, Miss Aimi Zainurin, Prof. Mandana Pennick (Consultant Oncoplastic Breast Surgeon), Dr. Mei-Ju Hwang (Consultant Oncoplastic and Reconstructive Breast Surgeon), Mr. Habeeb Yinka, Miss Alekhya Ganti.

Shadowing surgery experiences with Prof. Mandana Pennick and Dr. M Haider, at Glan Clwyd Hospital, Rhyl on April, 18th 2024 and November, 10th, 2022.

Our Breast Cancer Fundraiser Charity Events

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Organising Zumba Fitness Fundraiser event in conjunction with Breast Cancer Awareness Month,
in aid of Breast Cancer Now, Wear It Pink campaign on October 21st, 2023 at Aberystwyth University Student Union.

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The amazing zumba instructor Samantha Ackerman and all participants. 

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Hosting a bake sale for Wear It Pink fundraiser campaign for the research & care charity Breast Cancer Now on October 21st, 2022 at Aberystwyth University Student Union.

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Aberystwyth Sisters Breast Cancer Fundraising for Breast Cancer Now, the Research & Support Charity. 

Scan the QR code for donation.

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Miss Aimi Zainurin

Doctoral Student

Aimi graduated with Biochemical-Biotechnology Engineering (Hons) and Masters of Science in Biotechnology Engineering in 2017 and 2019 respectively from International Islamic University Malaysia (IIUM), studied metabolites and the biological activities of natural products. Currently, she is pursuing her PhD at Aberystwyth University, investigating the novel biomarkers for early detection of breast cancer (BC) & breast implant complication post surgery employing OMICs & artificial intelligence (AI)-based approaches. 

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