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Our friends at the Methuselah Foundation are working on macular degeneration.


Typically, a fellowship and participation in a research study to cure a major disease would occur years after completing undergrad, possibly even after earning a PhD. But Jennifer DeRosa is not a typical student.

As early as high school, DeRosa was already in the lab, conducting research in plant biotechnology at the College of Environmental Science and Forestry (SUNY-ESF) before graduating valedictorian from Skaneateles High School. As a freshman student at Onondaga Community College, she continued to develop skills in molecular biology, analytical chemistry, and cell biology. She logged over 1,600 hours in academic and industry laboratories while maintaining a perfect 4.0 GPA, completing her associate’s degree in Math and Science in only one year.

Although she had planned to continue to a bachelor’s program, DeRosa elected to defer enrollment after being offered a Methuselah Foundation research fellowship. “The fellowship provides distinguished students a year-long stipend to work in any laboratory of their choosing that conducts work on age-associated diseases,” said Methuselah Foundation CEO David Gobel. “We are very pleased that she chose to complete her fellowship at Ichor Therapeutics, where she has been working as a paid intern. Methuselah Foundation has a high degree of confidence in the quality and scope of work being conducted there.”

New research published in the New Journal of Physics tries to decompose the structural layers of the cortical network to different hierarchies enabling to identify the network’s nucleus, from which our consciousness could emerge.

The is a very complex network, with approximately 100 billion neurons and 100 trillion synapses between the neurons. In order to cope with its enormous complexity and to understand how brain function eventually creates the conscious mind, science uses advanced mathematical tools. Ultimately, scientists want to understand how a global phenomenon such as consciousness can emerge from our neuronal network.

A team of physicists from Bar Ilan University in Israel led by Professor Shlomo Havlin and Professor Reuven Cohen used network theory in order to deal with this complexity and to determine how the structure of the human cortical network can support complex data integration and . The gray area of the human cortex, the neuron cell bodies, were scanned with MRI imaging and used to form 1000 in the cortical network. The white matter of the human cortex, the neuron bundles, were scanned with DTI imaging, forming 15,000 links or edges that connected the network’s nodes. In the end of this process, their network was an approximation of the structure of the human cortex.

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More insights on human conscientious in relation to its state after we die.

Personally, (this is only my own opinion) I believe much of the human conscientious will remain a mystery even in the living as it relates to the re-creation of the human brain and its thinking and decision making patterns on current technology. Namely because any doctor will tell you that a person’s own decisions (namely emotional decision making/ thinking) can be impacted by a whole multitude of factors beyond logical information such as the brain’s chemical balance, physical illness or even injury, etc. which inherently feeds into conscientious state. In order to try to replicate this model means predominantly development of a machine that is predominantly built with synthetic biology; and even then we will need to evolve this model to finally understand human conscientious more than we do today.


Sir Roger Penrose, a mathematical physicist at Oxford University, has asked “what right do we have to claim, as some might, that human beings are the only inhabitants of our planet blessed with an actual ability to be “aware”? It is hard to see how one could begin to develop a quantum-theoretical description of brain action when one might well have to regard the brain as “observing itself” all the time! Beneath all this technicality is the feeling that it is indeed “obvious” that the conscious mind cannot work like a computer, even though much of what is involved in mental activity might do so.

My new Vice Motherboard story on the Fermi Paradox, Jethro’s Window, and why we’ll never discover intelligent aliens:


Here’s the sad solution to Fermi’s Paradox: We’ve never discovered other life forms because language and communication methods in the Singularity evolve so rapidly that even in one minute, an entire civilization can become transformed and totally unintelligible. In an expanding universe that is at least 13.6 billion years old, this transformation might never end. What this means is we will never have more than a few seconds to understand or even notice our millions of neighbors. The nature of the universe—the nature of communication in a universe where intelligence exponentially grows—is to keep us forever unaware and alone.

The only time we may discover other intelligent life forms is that 100 or so years during Jethro’s Window, and then it requires the miracle of another species in a similar evolutionary time table, right then, looking for us too. Given the universe is so gargantuan and many billions of years old, even with millions of alien species out there, we’ll never find them. We’ll never know them. It’s an unfortunate mathematical certainty.

Zoltan Istvan is a futurist, author of The Transhumanist Wager, and a 2016 US Presidential candidateof the Transhumanist Party. He writes an occasional columnfor Motherboard in which he ruminates on the future beyond human ability.

I’m guessing you’d be like: surprised .

So, here’s the deal. My biohacker friends led by Peter Fedichev and Sergey Filonov in collaboration with my old friend and the longevity record holder Robert Shmookler Reis published a very cool paper. They proposed a way to quantitatively describe the two types of aging – negligible senescence and normal aging. We all know that some animals just don’t care about time passing by. Their mortality doesn’t increase with age. Such negligibly senescent species include the notorious naked mole rat and a bunch of other critters like certain turtles and clams to name a few. So the paper explains what it is exactly that makes these animals age so slowly – it’s the stability of their gene networks.

What does network stability mean then? Well, it’s actually pretty straightforward – if the DNA repair mechanisms are very efficient and the connectivity of the network is low enough, then this network is stable. So, normally aging species, such as ourselves, have unstable networks. This is a major bummer by all means. But! There is a way to overcome this problem, according to the proposed math model.

The model very generally describes what happens with a gene network over time – the majority of the genes are actually working perfectly, but a small number doesn’t. There are repair mechanisms that take care of that. Also, there are mechanisms that take care of defected proteins like heat shock proteins, etc. Put together all of this in an equasion and solve it, and bam! here’s an equasion that gives you the Gompertz law for all species that have normal aging, and a time independent constant for the negligibly senescent ones.

What’s the difference between those two aging regimes? The model suggests it’s the right combination of DNA repair efficiency and the combined efficiency of proteolysis and heat shock response systems, mediating degradation and refolding of misfolded proteins. So, it’s not the accumulation of damages that is responsible for aging, but rather the properties of the gene network itself. The good news is that even we are playing with a terrible hand at first, there is a chance we can still win by changing the features of our network and making it stable. For example, by optimizing misfolded protein response or DNA repair.

The hard problem of consciousness must be approached through the ontological lens of 20th century physics, which tells us that reality is information theoretic and quantized at the level of Planck scale spacetime. Through careful deduction, it becomes clear that information cannot exist without consciousness – the awareness of things. And to be aware is to hold the meaning of relationships of objects within consciousness – perceiving abstract objects, while enjoying degrees of freedom within the structuring of those relationships. This defines consciousness as language – a set of objects and an ordering scheme with degrees of freedom used for expressing meaning. And since even information at the Planck scale cannot exist without consciousness, we propose an entity called a “primitive unit of consciousness”, which acts as a mathematical operator in a quantized spacetime language. Quasicrystal mathematics based on E8 geometry seems to be a candidate for the language of reality, possessing several qualities corresponding to recent physical discoveries and various physically realistic unification models.

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A collaboration of physicists and a mathematician has made a significant step toward unifying general relativity and quantum mechanics by explaining how spacetime emerges from quantum entanglement in a more fundamental theory. The paper announcing the discovery by Hirosi Ooguri, a Principal Investigator at the University of Tokyo’s Kavli IPMU, with Caltech mathematician Matilde Marcolli and graduate students Jennifer Lin and Bogdan Stoica, will be published in Physical Review Letters as an Editors’ Suggestion “for the potential interest in the results presented and on the success of the paper in communicating its message, in particular to readers from other fields.”

Physicists and mathematicians have long sought a Theory of Everything (ToE) that unifies and quantum mechanics. General relativity explains gravity and large-scale phenomena such as the dynamics of stars and galaxies in the universe, while quantum mechanics explains microscopic phenomena from the subatomic to molecular scales.

The holographic principle is widely regarded as an essential feature of a successful Theory of Everything. The holographic principle states that gravity in a three-dimensional volume can be described by quantum mechanics on a two-dimensional surface surrounding the volume. In particular, the three dimensions of the volume should emerge from the two dimensions of the surface. However, understanding the precise mechanics for the emergence of the volume from the surface has been elusive.

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Computers use switches to perform calculations. A complex film with “quantum wells”—regions that allow electron motion in only two dimensions—can be used to make efficient switches for high-speed computers. For the first time, this oxide film exhibited a phenomenon, called resonant tunneling, in which electrons move between quantum wells at a specific voltage. This behavior allowed an extremely large ratio (about 100,000:1) between two states, which can be used in an electronic device as an ON/OFF switch to perform mathematical calculations (Nature Communications, “Resonant tunneling in a quantum oxide superlattice”).

Quantum wells

Efficient control of electron motion can be used to reduce the power requirements of computers. “Quantum wells” (QW) are regions that allow electron motion in only two dimensions. The lines (bottom) in the schematic show the probability of finding electrons in the structure. The structure is a complex oxide (top) with columns (stacked blue dots corresponding to an added element) where the electrons are free to move in only two dimensions. This is a special type of quantum well called a two-dimensional electron gas (2DEG). (Image: Ho Nyung Lee, Oak Ridge National Laboratory)

To meet our exponentially growing need for computing power without a corresponding jump in energy use, scientists need more efficient electronic versions of switches to perform calculations. Efficient switches need materials that switch between well-defined ON/OFF states. The results of this study could lead to a new class of energy-efficient electronics because these materials can ensure the electronic switches are ON or OFF. These electronic switches could lower power consumption in electronics enabling, for example, the development of high-speed supercomputers and cell phones with longer battery life.

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