Can mathematics help us understand the complexity of our microbiome?

How do the communities of microbes living in our gastrointestinal systems affect our health? Carnegie’s Will Ludington was part of a team that helped answer this question.

In order to reveal a potential evolutionary trajectory biologists measure the interactions between genes to see which combinations are most fit. An organism that is evolving should take the most fit path. This concept is called a fitness landscape, and various mathematical techniques have been developed to describe it.

Like the genes in a genome, microorganisms in the gut microbiome interact, yet there isn’t a widely accepted mathematical framework to map the patterns of these interactions. Existing frameworks for genes focus on local information about interactions but do not put together a global picture.

Joswig and Ludington then joined with Holger Eble of TU Berlin, a graduate student working with Joswig, and Lisa Lamberti of ETH Zurich. Lamberti had previously collaborated with Ludington to apply a slightly different mathematical framework for the interactions to microbiome data. In the present work, the team expanded upon that previous framework to produce a more global picture by mapping the patterns of interactions onto a landscape.

But the sheer diversity of species in the human microbiome makes it very difficult to elucidate how these communities influence our physiology. This is why the fruit fly makes such an excellent model. Unlike the human microbiome, it consists of only a handful of bacterial species.

“We’ve built a rigorous mathematical framework that describes the ecology of a microbiome coupled to its host. What is unique about this approach is that it allows a global view of a microbiome-host interaction landscape,” said Ludington. “We can now use this approach to compare different landscapes, which will let us ask why diverse microbiomes are associated with similar health outcomes.”

Reference: https://www.sciencedaily.com/releases/2019/07/190703121353.htm

 

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Tiny motor can ‘walk’ to carry out tasks

Years ago, MIT Professor Neil Gershenfeld had an audacious thought. Struck by the fact that all the world’s living things are built out of combinations of just 20 amino acids, he wondered: Might it be possible to create a kit of just 20 fundamental parts that could be used to assemble all of the different technological products in the world?

Gershenfeld and his students have been making steady progress in that direction ever since. Their latest achievement, presented this week at an international robotics conference, consists of a set of five tiny fundamental parts that can be assembled into a wide variety of functional devices, including a tiny “walking” motor that can move back and forth across a surface or turn the gears of a machine.

Previously, Gershenfeld and his students showed that structures assembled from many small, identical subunits can have numerous mechanical properties. Their work offers an alternative to today’s approaches to constructing robots, which largely fall into one of two types: custom machines that work well but are relatively expensive and inflexible, and reconfigurable ones that sacrifice performance for versatility.

Using this simple kit of tiny parts, Langford assembled them into a novel kind of motor that moves an appendage in discrete mechanical steps, which can be used to turn a gear wheel, and a mobile form of the motor that turns those steps into locomotion, allowing it to “walk” across a surface in a way that is reminiscent of the molecular motors that move muscles.

The new system is a significant step toward creating a standardized kit of parts that could be used to assemble robots with specific capabilities adapted to a particular task or set of tasks.

Reference: https://www.sciencedaily.com/releases/2019/07/190702152751.htm

 

How you and your friends can play a video game together using only your minds

Telepathic communication might be one step closer to reality thanks to new research from the University of Washington. A team created a method that allows three people to work together to solve a problem using only their minds.

In BrainNet, three people play a Tetris-like game using a brain-to-brain interface. This is the first demonstration of two things: a brain-to-brain network of more than two people, and a person being able to both receive and send information to others using only their brain.

As in Tetris, the game shows a block at the top of the screen and a line that needs to be completed at the bottom. Two people, the Senders, can see both the block and the line but can’t control the game. The third person, the Receiver, can see only the block but can tell the game whether to rotate the block to successfully complete the line.

The team asked five groups of participants to play 16 rounds of the game. For each group, all three participants were in different rooms and couldn’t see, hear or speak to one another.

The Senders wore electroencephalography caps that picked up electrical activity in their brains. The lights’ different flashing patterns trigger unique types of activity in the brain, which the caps can pick up. So, as the Senders stared at the light for their corresponding selection, the cap picked up those signals, and the computer provided real-time feedback by displaying a cursor on the screen that moved toward their desired choice.

The team hopes that these results pave the way for future brain-to-brain interfaces that allow people to collaborate to solve tough problems that one brain alone couldn’t solve.

Reference: https://www.sciencedaily.com/releases/2019/07/190701163827.htm

 

Ultra-small nanoprobes could be a leap forward in high-resolution human-machine interfaces

Machine enhanced humans — or cyborgs as they are known in science fiction — could be one step closer to becoming a reality, thanks to new research Lieber Group at Harvard University, as well as scientists from University of Surrey and Yonsei University.

Researchers have conquered the monumental task of manufacturing scalable nanoprobe arrays small enough to record the inner workings of human cardiac cells and primary neurons.

The ability to read electrical activities from cells is the foundation of many biomedical procedures, such as brain activity mapping and neural prosthetics. Developing new tools for intracellular electrophysiology (the electric current running within cells) that push the limits of what is physically possible (spatiotemporal resolution) while reducing invasiveness could provide a deeper understanding of electrogenic cells and their networks in tissues, as well as new directions for human-machine interfaces.

If our medical professionals are to continue to understand our physical condition better and help us live longer, it is important that we continue to push the boundaries of modern science in order to give them the best possible tools to do their jobs. For this to be possible, an intersection between humans and machines is inevitable.

This work represents a major step towards tackling the general problem of integrating ‘synthesised’ nanoscale building blocks into chip and wafer scale arrays, and thereby allowing us to address the long-standing challenge of scalable intracellular recording.

Along with the possibility of upgrading the tools we use to monitor cells, this work has laid the foundations for machine and human interfaces that could improve lives across the world.”

Dr Yunlong Zhao and his team are currently working on novel energy storage devices, electrochemical probing, bioelectronic devices, sensors and 3D soft electronic systems.

Reference: https://www.sciencedaily.com/releases/2019/07/190703121358.htm