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UFS students honoured at 2024 Women in Science Awards

23 August 2024 | Story André Damons | Photo Supplied

Thandokuhle Gama, Dr Glen Tylor and Anele Mthembu — Winners: Thandokuhle Gama (left) and Anele Mthembu (right), who were honoured with the DSI-Esther Mahlangu Master's Fellowship at the 2024 SAWiSA, with Dr Glen Taylor, Senior Director: Directorate Research Development (DRD), UFS.

Two postgraduate students from the University of the Free State (UFS) were honoured at this year’s Women in Science Awards (SAWiSA) hosted by the Department of Science and Innovation (DSI).

Thandokuhle Gama, a Master of Medical Science student with specialisation in Pharmacology, and Anele Mthembu, who is working on her master’s degree in Disaster Management in the Disaster Management Training and Education Centre for Africa (DIMTEC), are both recipients of the DSI-Esther Mahlangu Master's Fellowships.

This fellowship is awarded to women scientists and researchers who are pursuing their master’s or doctoral studies and already hold scholarships from the National Research Foundation or other DSI agencies. The fellowships for Gama and Mthembu are worth R75 000 each and can be used towards their tuition fees or to enhance academic programmes by covering the costs of attending conferences or specialised research materials and equipment required to complete their degrees.

Honouring Dr Esther Mahlangu

The prestigious 2024 SAWiSA, which honour the exceptional contributions of women to science, technology, engineering, mathematics and innovation (STEMI) in South Africa, took place on 15 August 2024 in Mbombela. The theme was “Transition towards an Innovation Economy: The Role of Women Leaders in STEM”.

This year, the awards honoured world-renowned artist, Dr Esther Mahlangu, by renaming this year's master's and doctoral fellowships the DSI-Esther Mahlangu Fellowships.

“I feel honoured and grateful for the recognition, although it's been difficult to process what it actually means. It has been an overwhelming experience. It came as a surprise, because when I applied, I was not sure what to expect because these are national awards with many other applicants,” says Gama.

She was nominated by Innocensia Mangoato, lecturer in the UFS Department of Pharmacology and a previous winner at the awards. Gama is doing research on medicinal plants that are used in traditional medicine to treat diabetes.

“Winning this award means that my work thus far is being recognised. It is all through God’s grace. I'm also grateful to everyone who has contributed towards my journey: my family, teachers, mentors and sponsors, and everyone else. It will allow me to continue to advance research in the field of diabetes treatment using traditional medicines or medicinal plants.”

Bettering lives

Mthembu, who was nominated by her mentor, Dr Tlou Daisy Raphela-Masuku, a lecturer at DIMTEC, says it is a fantastic feeling winning this award. “Before the awards, Dr Raphela-Masuku and I dreamt I could win the SAWiSA. But before then, I was surprised and grateful for being acknowledged by DSI as a finalist; I focused on being a DSI finalist, and that winning would be a bonus,” she says.

She continues: “It means a lot to me to win the DSI Master’s Fellowship, as it is a testimony of God’s grace in my life. It is the destiny for helpers God has placed in my life, including my mentor, supervisor, and the DIMTEC postgraduate school. We all won!”

Mthembu is working her master’s thesis on the integration of risk-informed development (RID) and nature-based solutions (NbS) into sustainable human settlements in eThekwini Municipality, KwaZulu-Natal.

“The overarching aim is to evaluate the integration of both these concepts into human settlements’ strategic planning to offer eThekwini Municipality innovative and ecosystem-based approaches to achieving sustainable and resilient human settlements and achieving Sustainable Development Goal (SDG) 11 on building resilient cities.

“I hope to publish my findings and contextualise the enabling environments for RID (EE4RID) Framework in eThekwini Municipality so they can make risk-informed decisions on development and human settlements to achieve SDG 11,” explains Mthembu.

Gama says the aim with her research is to determine if these medicinal plants can treat diabetes by stimulating stem cells to differentiate and become insulin-producing cells. She hopes that through this research diabetes treatment can advance from a level where it is being continuously managed, to a level where we can cure the disease.

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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