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02 August 2022 | Story Leonie Bolleurs | Photo Leonie Bolleurs
Alistair Naidoo, second-year master’s student in Conservation Genetics and full-time technician in the Department of Genetics; Prof Paul Grobler, Head of the Department of Genetics; Prof Gordon Luikart; and Hannah Janse van Vuuren, third-year master’s student in Conservation Genetics.

It is an important and exciting time to be doing research in conservation genetics. This is according to Prof Gordon Luikart, Professor of Conservation Ecology and Genetics at the Flathead Lake Bio Station at the University of Montana in the United States. 

Prof Luikart, whose primary research focus is the application of genetics to the conservation of natural and managed populations, recently delivered a lecture, The Expanding Role of Genetics/omics in Wildlife Research and Conservation, on the Bloemfontein Campus of the University of the Free State (UFS). The lecture, hosted by the Department of Genetics, was attended by a group of students and lecturers in conservation and a number of related fields. 

He is one of the leading scientists in the field of conservation genetics, including integration of genomics in conservation projects. He is also co-author of the textbook Conservation and the Genomics of populations – the current prescribed textbook for GENE3744.

Species threatened with extinction

In 2008, the International Union for Conservation of Nature (IUCN) stated that approximately 10-20% of all vertebrate and plant species are threatened with extinction over the next few decades. In 1984, American biologist Edward O Wilson also said that it will take millions of years to correct the ongoing loss of genetics and species diversity caused by the destruction of natural habitats. “This is the folly our descendants are least likely to forgive us.”

Prof Luikart is of the opinion that genetics has enormous potential to help manage wildlife and prevent extirpation. “My research works to realise this potential and help wildlife managers conserve populations and ecosystems,” he says. 

Conservation managers and biologists have understood the risks of inbreeding for more than 100 years. In his lecture, one of the aspects of genetic conservation he focused on, was the negative effects of inbreeding and how this can be reversed using genetic rescue. 

With the genetic rescue study, they found that the gene flow into recently isolated populations can increase individual fitness and population growth. He proposed that conservation managers should consider genetic principles and rescue as practical and important tools. 

Prof Luikart also provided a list of information that can be retrieved from molecular genetic data to help conservation managers. This includes intel on census and effective population size, gene flow and dispersal, local adaptation and selection, forensics, genetic identification and law enforcement, and disease ecology and transmission. 

Non-invasive genetic monitoring

In terms of detecting gene flow, he focused on a study about non-invasive genetic monitoring that was conducted in the Yellowstone Park. Prof Luikart and a group of students collected the shed hair and faeces of the grizzly bear, obtained from trees and hair traps, which were used as a source of DNA. 

They established, for instance, that inbreeding depression is more common and stronger than previously thought in natural populations. Genetic monitoring, using non-invasive methods as described, has been found to be an effective tool that conservation managers should consider for detecting inbreeding and loss of genome-wide variation.

His research on the bighorn sheep, the alpine ibex, and the black bear informed most of the findings he discussed during his lecture.

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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