Sunday September 22, 2019

New Vaccine for Tuberculosis Shows Promise

Two peptides (small proteins), which are normally found in tuberculosis bacteria, were synthesised and then bound extremely tightly to an adjuvant (a stimulant) that was able to kick-start the immune response in the lungs

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The study, published in European Respiratory Journal, shows that one in four people in the world carries tuberculosis bacterium in the body. Pixabay

Researchers have successfully developed and tested a new type of vaccine targeting tuberculosis (TB).

Published in the Journal of Medicinal Chemistry, the early-stage vaccine was shown to provide substantial protection against TB in a pre-clinical laboratory setting.

“Tuberculosis is a huge world-wide health problem. It’s caused by a bacteria that infects the lungs after it’s inhaled, is contagious and results in approximately 1.6 million deaths per year globally,” said study co-author Anneliese Ashhurst, who is affiliated with both the Centenary Institute and the University of Sydney.

The research programme targeting the deadly disease took over five years of effort to be implemented.

FILE – A tuberculosis patient receives treatment at a clinic in Jakarta, Indonesia. VOA

A team of scientists created the advanced synthetic TB vaccine and have now demonstrated its effectiveness using mouse models.

Two peptides (small proteins), which are normally found in tuberculosis bacteria, were synthesised and then bound extremely tightly to an adjuvant (a stimulant) that was able to kick-start the immune response in the lungs.

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“We were then able to show that when this vaccine was inhaled into the lungs, it stimulated the type of T cells known to protect against TB. Importantly, we then demonstrated that this type of vaccine could successfully protect against experimental airborne TB infection,” Ashhurst said.

“The important thing is that the vaccine actually gets to the lungs because that’s where you first see TB. Ultimately, we would love to see a form of this vaccine available for use in an easily inhaled nasal spray which would provide life-long TB protections,” said researcher Warwick Britton. (IANS)

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Researchers Develop New Algorithm to Identify Cyber-bullies on Twitter

“In a nutshell, the algorithms ‘learn’ how to tell the difference between bullies and typical users by weighing certain features as they are shown more examples,” said Blackburn

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FILE - A man reads tweets on his phone in front of a displayed Twitter logo. VOA

Researchers have developed machine learning algorithms which can identify bullies and aggressors on Twitter with 90 per cent accuracy.

For the study published in the journal Transactions on the Web, the research team analysed the behavioural patterns exhibited by abusive Twitter users and their differences from other users.

“We built crawlers — programs that collect data from Twitter via variety of mechanisms,” said study researcher Jeremy Blackburn from Binghamton University in the US.

“We gathered tweets of Twitter users, their profiles, as well as (social) network-related things, like who they follow and who follows them,” Blackburn said.

The researchers then performed natural language processing and sentiment analysis on the tweets themselves, as well as a variety of social network analyses on the connections between users.

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Twitter is a social media app that encourages short tweets and brief conversations. Pixabay

They developed algorithms to automatically classify two specific types of offensive online behaviour, i.e. cyber-bullying and cyber-aggression.

The algorithms were able to identify abusive users — who engage in harassing behaviour like those who send death threats or make racist remarks — on Twitter with 90 per cent accuracy.

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“In a nutshell, the algorithms ‘learn’ how to tell the difference between bullies and typical users by weighing certain features as they are shown more examples,” said Blackburn.

“Our research indicates that machine learning can be used to automatically detect users that are cyber-bullies, and thus could help Twitter and other social media platforms remove problematic users,” Blackburn added. (IANS)