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28 September 2020 | Story Andre Damons | Photo Supplied
Dr Martin Nyaga, Senior Lecturer and Researcher: NGS, will be heading the World Health Organisation Collaborating Centre (WHO CC).

The University of the Free State (UFS) has been designated a World Health Organisation Collaborating Centre (WHO CC), and the university’s Next Generation Sequencing (NGS) Unit, in partnership with the World Health Organisation (WHO), will for the next four years be conducting genome sequencing of pathogenic organisms, including rotavirus strains from the African continent. 

This centre will be part of the Vaccine Preventable Diseases (VPD) Pathogens Genomics Cluster and will run from September 2020 to September 2024. 

Dr Martin Nyaga, Senior Lecturer and Researcher: NGS/Virology, who will be heading the WHO CC, says an institution is designated as a WHO CC by the WHO Director-General and endorsed by the host country’s minister of health to form part of an international collaborative network, carrying out activities in support of the WHO programmess at all levels. A designation as a WHO CC is a time-limited agreement of collaboration between WHO and the designated institution, through which the latter agrees to implement a series of concrete activities, specifically designed for WHO.

A supreme achievement

Says Dr Nyaga: “In my opinion, a WHO CC designation is one of the supreme achievements an institution can be conferred as a recognition for foregoing exceptional collaborative venture with the WHO and showing future potential to assist the WHO with its global programmes and in our case, the WHO Regional Office for Africa region to offer solutions to the WHO VPD Surveillance and pathogens genomics cluster.”

According to Dr Nyaga this designation was awarded to the UFS after the WHO was content with the outcome of a service contract whereby the UFS-NGS unit undertook a pilot rotavirus surveillance project at whole genome level, using two African countries for the pilot, Rwanda and Zambia.

“From the outcomes of the pilot surveillance project between 2017 and 2019, the WHO/AFRO was satisfied with the genomic data that was generated and partially disseminated in scientific databases and journals as a collaborative venture. 

“It was thus proposed to strengthen its existing collaboration with the UFS-NGS Unit, which initiated the application process to designate the UFS-NGS unit as a WHO CC, an initiative that has taken approximately 20 months to finalise through the different phases of the application and approvals for the designation,” explains Dr Nyaga.

The purpose of the WHO CC

The new WHO CC will upon request by the WHO, implement agreed work plans in a timely manner and to the highest possible standards of quality and must comply with the referred terms of reference and conditions. These include: 
• Conducting genome sequencing of pathogenic organisms causing VPD, including rotavirus strains collected as part of the routine VPD surveillance using NGS technology and analysis of the generated datasets using bioinformatics tools.

• Conducting molecular characterisation of specimens collected during outbreaks and public health emergencies as part of the support for monitoring, preparedness and response to VPD disease outbreaks in Africa.

• Provide technical guidance to WHO on strategies to improve laboratory molecular diagnostics, molecular typing and NGS of rotavirus diarrheal strains and other enteropathogens to detect novel and re-emerging strains. 

• Conduct validation of tools and new molecular diagnostics for detection and characterisation of unusual or rare VPD strains to guide studies and development of new vaccines for VPD.

• Organise capacity-building and training workshops on whole genome sequencing of priority VPD pathogenic organisms.

The impact of the WHO CC on the work of the UFS-NGS 

According to Dr Nyaga, the designation brings extra responsibilities to his work and to the activities of the UFS-NGS unit. “Such initiatives are very welcome to enhance the business aspects, research and academic activities of the UFS-NGS unit, as the benefits are quite holistic since the collaboration enhances co-ownership of data and offers opportunities to train postgraduate students and other scientists.

“It also expands the research infrastructure and most importantly contributes to policy for numerous African governments in important decisions such as vaccine implementation activities, from an informed point of view and managing public health needs that require rapid response like outbreaks that may lead to pandemics.” 
• The current WHO CC designations at South African Institutions of higher learning and research can be found at: 

News Archive

Mathematical methods used to detect and classify breast cancer masses
2016-08-10

Description: Breast lesions Tags: Breast lesions

Examples of Acho’s breast mass
segmentation identification

Breast cancer is the leading cause of female mortality in developing countries. According to the World Health Organization (WHO), the low survival rates in developing countries are mainly due to the lack of early detection and adequate diagnosis programs.

Seeing the picture more clearly

Susan Acho from the University of the Free State’s Department of Medical Physics, breast cancer research focuses on using mathematical methods to delineate and classify breast masses. Advancements in medical research have led to remarkable progress in breast cancer detection, however, according to Acho, the methods of diagnosis currently available commercially, lack a detailed finesse in accurately identifying the boundaries of breast mass lesions.

Inspiration drawn from pioneer

Drawing inspiration from the Mammography Computer Aided Diagnosis Development and Implementation (CAADI) project, which was the brainchild Prof William Rae, Head of the department of Medical Physics, Acho’s MMedSc thesis titled ‘Segmentation and Quantitative Characterisation of Breast Masses Imaged using Digital Mammography’ investigates classical segmentation algorithms, texture features and classification of breast masses in mammography. It is a rare research topic in South Africa.

 Characterisation of breast masses, involves delineating and analysing the breast mass region on a mammogram in order to determine its shape, margin and texture composition. Computer-aided diagnosis (CAD) program detects the outline of the mass lesion, and uses this information together with its texture features to determine the clinical traits of the mass. CAD programs mark suspicious areas for second look or areas on a mammogram that the radiologist might have overlooked. It can act as an independent double reader of a mammogram in institutions where there is a shortage of trained mammogram readers. 

Light at the end of the tunnel

Breast cancer is one of the most common malignancies among females in South Africa. “The challenge is being able to apply these mathematical methods in the medical field to help find solutions to specific medical problems, and that’s what I hope my research will do,” she says.

By using mathematics, physics and digital imaging to understand breast masses on mammograms, her research bridges the gap between these fields to provide algorithms which are applicable in medical image interpretation.

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