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Dr. James Revill, Ph.D. — Head of Weapons of Mass Destruction & Space Security Programs, UNIDIR

Building A More Secure World — Dr. James Revill, Ph.D. — Head of Weapons of Mass Destruction & Space Security Programs, UNIDIR, UN Institute for Disarmament Research United Nations.


Dr. James Revill, Ph.D. (https://unidir.org/staff/james-revill) is the Head of the Weapons of Mass Destruction (WMD) and Space Security Program, at the UN Institute for Disarmament Research (UNIDIR).

Dr. Revill’s research interests focus on the evolution of the chemical and biological weapons and he has published widely in these areas. He was previously a Research Fellow with the Harvard Sussex Program at the Science Policy Research Unit, University of Sussex and completed research fellowships with the Landau Network Volta Center in Italy and the Bradford Disarmament Research Centre in the UK.

Dr. Revill holds a Ph.D. focused on the evolution of the Biological Weapons Convention from the University of Bradford, UK.

Dr. Revill’s areas of expertise include biological weapons, biosecurity, bioterrorism, chemical weapons, chemical terrorism, chemical weapons convention, compliance, verification, and improvised explosive devices.

Incredibly, Microbes Inside Our Mouths Turn Into a Superorganism That Moves Around

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Hello and welcome! My name is Anton and in this video, we will talk about unusual discoveries coming directly from within our mouths — biofilm complexity.
Links:
https://en.wikipedia.org/wiki/Biofilm.
https://www.pnas.org/doi/full/10.1073/pnas.2209699119
https://en.wikipedia.org/wiki/Quorum_sensing.
Slime: https://www.youtube.com/watch?v=spZwZLkMsYw.
Biofilm communication and bacterial cities: https://youtu.be/4M872c27bSc.
#biology #dentistry #biofilm.

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Meta AI creates first ever database of 600 million metagenomic structures

‘These structures provide an unprecedented view into the breadth and diversity of nature,’ say the researchers.

In a world first, Meta’s artificial intelligence (AI) has produced the structures of the metagenomic world at the scale of hundreds of millions of proteins, according to a blog by the company published on Tuesday.

“Proteins are complex and dynamic molecules, encoded by our genes, that are responsible for many of the varied and fundamental processes of life. They have an astounding range of roles in biology,” wrote the Meta research team who also published a paper on the matter in the preprint database bioRxiv.


It is common knowledge that a vast number of proteins exist beyond the ones that have been catalogued and annotated in well-studied organisms and now these proteins are coming to the surface.

Researchers From MIT Have Developed A New Machine Learning Based Approach With 90 Percent Accuracy To Screen Candidate Materials If They Are Topological For Next-Generation Computer Chips or Quantum Devices

Topological materials are a special kind of material that have different functional properties on their surfaces than on their interiors. One of these properties is electrical. These materials have the potential to make electronic and optical devices much more efficient or serve as key components of quantum computers. But recent theories and calculations have shown that there can be thousands of compounds that have topological properties, and testing all of them to determine their topological properties through experiments will take years of work and analysis. Hence, there is a dire need for faster methods to test and study topological materials.

A team of researchers from MIT, Harvard University, Princeton University, and Argonne National Laboratory proposed a new approach that is faster at screening the candidate materials and can predict with more than 90 percent accuracy whether a material is topological or not. The traditional way of solving this problem is quite complicated and can be explained as follows: Firstly, a method called density functional theory is used to perform initial calculations, which are then followed by complex experiments that involve cutting a piece of material to atomic-level flatness and probing it with instruments under high vacuum.

The new proposed method is based on how the material absorbs X-rays, which is different from the old methods, which were based on photoemissions or tunneling electrons. There are certain significant advantages to using X-ray absorption data, which can be listed as follows: Firstly, there is no requirement for expensive lab apparatus. X-ray absorption spectrometers are used, which are readily available and can work in a typical environment, hence the low cost of setting up an experiment. Secondly, such measurements have already been done in chemistry and biology for other applications, so the data is already available for numerous materials.

Brain Complexity and Consciousness

Read the accompanying news item: https://www.humanbrainproject.eu/en/follow-hbp/news/ebrains-…disorders/

Using the EBRAINS research infrastructure, scientists of the Human Brain Project have developed multi-scale simulations of the human brain that mimic hallmarks of activity during wake and deep sleep states. Such simulations can lead to a better understanding of biological mechanisms that regulate human consciousness and its disorders, which span from single neurons to whole brain scales.

Pong in a Dish

Ever hear of the Turk —the 19th-century mechanism topped by a turbaned head that played chess against all comers? In fact, hidden inside was a diminutive chessmaster, one you might imagine deadpanning, “Eh, It’s a living.

Then there’s its namesake, the Mechanical Turk —a 21st-century service offered by Amazon to mark up images on the Web with the help of crowdsourced freelancers. They, too, might intone, glassy-eyed, “It’s a living.”

Now we have a kind of Biological Turk. A mass of neurons act as a computer that mimics a human being playing the classic computer game Pong. The neurons, some taken from mouse embryos, others grown from human precursor cells, spread out into a one-layer, 800,000-cell mesh called a biological neural network, which lives in a giant petri dish called the DishBrain. There it interfaces with arrays of electrodes that form an interface to silicon hardware. Software mounted on that hardware provides stimulation and feedback, and the minibrain learns how to control a paddle on a simulated ping-pong table.

New large-scale virtual model of cortex highly successful in solving visual tasks

HBP researchers have trained a large-scale model of the primary visual cortex of the mouse to solve visual tasks in a highly robust way. The model provides the basis for a new generation of neural network models. Due to their versatility and energy-efficient processing, these models can contribute to advances in neuromorphic computing.

Modeling the brain can have a massive impact on artificial intelligence (AI): since the brain processes images in a much more energy-efficient way than artificial networks, scientists take inspiration from neuroscience to create neural networks that function similarly to the biological ones to significantly save energy.

In that sense, brain-inspired neural networks are likely to have an impact on future technology, by serving as blueprints for visual processing in more energy-efficient neuromorphic hardware. Now, a study by Human Brain Project (HBP) researchers from the Graz University of Technology (Austria) showed how a large data-based model can reproduce a number of the brain’s visual processing capabilities in a versatile and accurate way. The results were published in the journal Science Advances.

New technique helps identify genes related to aging

Researchers from North Carolina State University have developed a new method for determining which genes are relevant to the aging process. The work was done in an animal species widely used as a model for genetic and biological research, but the finding has broader applications for research into the genetics of aging.

“There are a lot of out there that we still don’t know what they do, particularly in regard to aging,” says Adriana San Miguel, corresponding author of a paper on the work and an assistant professor of chemical and biomolecular engineering at NC State.

That’s because this field faces a very specific technical challenge: by the time you know whether an organism is going to live for a long time, it’s old and no longer able to reproduce. But the techniques we use to study genes require us to work with animals that are capable of reproducing, so we can study the role of specific genes in subsequent generations.

Advanced Aesthetics report

When we think about aging, one of the first thoughts that comes to mind is wrinkled and sagging skin as well as the greying and loss of hair – simply put, the physical changes to appearance that we associated with advancing age. These changes are the most striking reflection of the underlying molecular aging processes that are happening inside our bodies.

The current size of the cosmetic industry alone highlights that physical appearance is important to people. As we continue developing strategies to improve longevity allowing us to live longer and in far better health, people will inevitably want a “youthful appearance” to match their newfound “youthful state”. Furthermore, as this report explains in more detail, aesthetic aging plays a significant and grossly underappreciated role in influencing the rate of biological aging.

It is fair to say that the cosmetic industry alone might not be enough to address aesthetic aging from a longevity point of view, as cosmetic products work to conceal the signs of aging. We need tactics that can address the underlying causes of skin and hair aging to achieve long-term benefits and halt the fine interlink between aesthetic aging and biological aging. This is where advanced aesthetics comes in.

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