Masks, miners, and machines

Newsletter 1 | Bye Bye 2020

Don’t throw that mask away

A pilot study in India found the potential use of masks in detecting the presence of tuberculosis in children. If proven in further large-scale, multisite studies, researchers are hoping this could contribute to better childhood TB diagnosis, which remains a huge challenge globally.

The masks were fitted with a gelatin-like membrane that captures respiratory particles expelled by the child through talking, coughing, or taking deep breaths. The membranes were then taken to check the presence of TB bacteria, which, if found, usually indicate an active TB infection.

Through the mask sample, researchers were able to detect TB in 9 out of the 10 children involved in the pilot.

Full Story: Can repurposing masks to detect child TB work?


Save those miners

A pilot study in India found the potential use of masks in detecting the presence of tuberculosis in children. If proven in further large-scale, multisite studies, researchers are hoping this could contribute to better childhood TB diagnosis, which remains a huge challenge globally.

The masks were fitted with a gelatin-like membrane that captures respiratory particles expelled by the child through talking, coughing, or taking deep breaths. The membranes were then taken to check the presence of TB bacteria, which, if found, usually indicate an active TB infection.

Through the mask sample, researchers were able to detect TB in 9 out of the 10 children involved in the pilot.

Full Story: Can repurposing masks to detect child TB work?


Ask the Machine

Machine learning is a computational tool used by many biologists to analyze huge amounts of data, helping them to identify potential new drugs. MIT researchers have now incorporated a new feature into these types of machine-learning algorithms, improving their prediction-making ability.

Using this new approach, which allows computer models to account for uncertainty in the data they’re analyzing, the MIT team identified several promising compounds that target a protein required by the bacteria that cause tuberculosis.

Full Story: Machine learning uncovers potential new TB drugs


The Biggest Shift

A new four-month treatment course for drug-sensitive tuberculosis (the most common form of TB) is as safe and effective as the current six-month treatment course that has been in use since the 1980s, according to findings from an extensive study.

The development is expected to translate to cost-savings for funders and better experiences for patients, who often struggle to take medication for half a year.

According to a CDC press release, shortened treatment “can benefit patients, families, healthcare providers and health systems” and “can help patients more easily complete treatment for TB disease than they would on the existing standard regimen”.

Full story: ‘The biggest shift in TB care in decades’: Tuberculosis treatment time reduced by a third


Tell me your story, I’ll tell your TB

A new tool can predict the chances of a person developing tuberculosis: this can limit the spread of the disease and improve the life chances of millions of people.

Researchers at University College London (UCL) said they believe they have produced an algorithm that could help eliminate the disease in some countries based on tens of thousands of people, including information on age, exposure to TB, whether an individual’s immune system is compromised, and whether they are a migrant.

This is the first time that patient histories have been used to predict the risk of developing active TB.

Full story: Tuberculosis breakthrough as scientists develop risk prediction tool