Tuesday June 18, 2019

Researchers Discover Treatment for Obesity, Fatty Liver Disease

Goldblum predicts that in a few years we will hopefully be seeing several of these molecules in the pipeline for clinical studies on humans

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Obesity
An overweight woman sits on a chair in Times Square in New York, May 8, 2012. VOA

Israeli researchers have discovered 27 new molecules, which may lead to a potential treatment for fatty liver disease, obesity and to heal wounds.

The findings, led by Professor Amiram Goldblum at the Hebrew University of Jerusalem, were made possible by a new algorithm, which chose the 27 molecules with the strongest therapeutic potential from a database of 1.56 million molecules.

These molecules, which are undergoing pharmaceutical evaluations to treat obesity and the incurable fatty liver disease, all activate a special protein called PPAR-delta (peroxisome proliferator-activated receptor delta).

PPAR-delta activation has the potential to increase physical endurance and trim waistlines by getting muscle cells to burn more fat, according to the study published in the Scientific Reports journal.

“With such a large group of highly active molecules, there is a high probability to find treatments for several common diseases. However, we should wait till all the experiments are done before we get our hopes up too high,” said Goldblum.

Adults
Soon treatment for obesity, fatty liver disease . Pixabay

Future evaluations will hopefully include testing treatments for improved wound healing, and to prevent kidney toxicity in diabetics, the researchers said.

There is much pharmaceutical interest in Goldblum’s new molecules.

Integra Holdings, Hebrew University’s biotech company, determined that 21 of the 27 have the potential to reach pharmaceutical success, especially as a possible cure for fatty liver disease.

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In addition, Israel’s Heller Institute of Medical Research is currently testin g PPAR-delta’s physical endurance properties on mice.

Goldblum predicts that in a few years we will hopefully be seeing several of these molecules in the pipeline for clinical studies on humans. (IANS)

Next Story

Researchers Teaching Artificial Intelligence to Connect Senses Like Vision and Touch

The new AI-based system can create realistic tactile signals from visual inputs

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Tool, Humans, Robots
Members of that same MIT team applied the new algorithm to the BMW factory floor experiments and found that instead of freezing in place, the robot simply rolled on . Pixabay

A team of researchers at the Massachusetts Institute of Technology (MIT) have come up with a predictive Artificial Intelligence (AI) that can learn to see by touching and to feel by seeing.

While our sense of touch gives us capabilities to feel the physical world, our eyes help us understand the full picture of these tactile signals.

Robots, however, that have been programmed to see or feel can’t use these signals quite as interchangeably.

The new AI-based system can create realistic tactile signals from visual inputs, and predict which object and what part is being touched directly from those tactile inputs.

Teaching, Artificial Intelligence, Researchers
) A team of researchers at the Massachusetts Institute of Technology (MIT) have come up with a predictive Artificial Intelligence (AI). Pixabay

In the future, this could help with a more harmonious relationship between vision and robotics, especially for object recognition, grasping, better scene understanding and helping with seamless human-robot integration in an assistive or manufacturing setting.

“By looking at the scene, our model can imagine the feeling of touching a flat surface or a sharp edge”, said Yunzhu Li, PhD student and lead author from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL).

“By blindly touching around, our model can predict the interaction with the environment purely from tactile feelings,” Li added.

The team used a KUKA robot arm with a special tactile sensor called GelSight, designed by another group at MIT.

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Using a simple web camera, the team recorded nearly 200 objects, such as tools, household products, fabrics, and more, being touched more than 12,000 times.

Breaking those 12,000 video clips down into static frames, the team compiled “VisGel,” a dataset of more than three million visual/tactile-paired images.

“Bringing these two senses (vision and touch) together could empower the robot and reduce the data we might need for tasks involving manipulating and grasping objects,” said Li.

The current dataset only has examples of interactions in a controlled environment.

Teaching, Artificial Intelligence, Researchers
While our sense of touch gives us capabilities to feel the physical world, our eyes help us understand the full picture of these tactile signals. Pixabay

The team hopes to improve this by collecting data in more unstructured areas, or by using a new MIT-designed tactile glove, to better increase the size and diversity of the dataset.

“This is the first method that can convincingly translate between visual and touch signals”, said Andrew Owens, a post-doc at the University of California at Berkeley.

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The team is set to present the findings next week at the “Conference on Computer Vision and Pattern Recognition” in Long Beach, California. (IANS)