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A study conducted in Brazil and reported in an article published in Molecular Psychiatry suggests that schizophrenia may be associated with alterations in the vascularization of certain brain regions. Researchers at the State University of Campinas (UNICAMP), D’Or Research and Education Institute (IDOR) and the Federal University of Rio de Janeiro (UFRJ) found a link between astrocytes (central nervous system cells) from patients with schizophrenia and formation of narrow blood vessels.

Schizophrenia is a severe multifactorial mental health disorder affecting around 1% of the world population. Common symptoms include loss of contact with reality (psychosis), hallucinations (hearing voices, for example), delusions or delirium, disorganized motor behavior, loss of motivation and cognitive impairment.

In the study, the researchers focused on the role of astrocytes in development of the disease. These glial cells are housekeepers of the central nervous system and important to its defense. They are the central elements of the neurovascular units that integrate neural circuitry with local blood flow and provide neurons with metabolic support.

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Lasers are intense beams of colored light. Depending on their color and other properties, they can scan your groceries, cut through metal, eradicate tumors, and even trigger nuclear fusion. But not every laser color is available with the right properties for a specific job.

To fix that, scientists have found a variety of ways to convert one color of laser light into another. In a study just published in the journal Physical Review Applied, scientists at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory demonstrate a new color-shifting strategy that is simple, efficient, and highly customizable.

The new method relies on interactions between the laser and in the chemical bonds of materials called “.” These liquids are made only of positively and negatively charged ions, like ordinary table salt, but they flow like viscous fluids at room temperature. Simply shining a laser through a tube filled with a particular ionic liquid can downshift the laser’s energy and change its color while retaining other important properties of the laser beam.

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Michael Levin is an American developmental and synthetic biologist at Tufts University. His research interests include: bioelectrical signals by which cells communicate to serve the dynamic anatomical needs of the organism during development, regeneration, and cancer suppression; basal cognition and intelligence in diverse unconventional substrates; and top-down control of form and function across scales in biology.

Join us as we discuss.
- Bioelectricity.
- Regeneration.
- The future in medicine.
- The act of free will and more.

EPISODE LINKS:
Michael’s Twitter: https://twitter.com/drmichaellevin.
Michael’s Website: https://drmichaellevin.org.
Michael’s Publications: https://facultyprofiles.tufts.edu/michael-levin-1/publications.

PODCAST INFO:

Continue reading “Rekindi #29 — Bioelectricity, Regeneration, Cancer Suppression & Xenobots — with Michael Levin” | >

Mathematicians came up with the first examples of intransitive dice more than 50 years ago, and eventually proved that as you consider dice with more and more sides, it’s possible to create intransitive cycles of any length. What mathematicians didn’t know until recently was how common intransitive dice are. Do you have to contrive such examples carefully, or can you pick dice randomly and have a good shot at finding an intransitive set?

Looking at three dice, if you know that A beats B and B beats C, that seems like evidence that A is the strongest; situations where C beats A should be rare. And indeed, if the numbers on the dice are allowed to add up to different totals, then mathematicians believe that this intuition holds true.

But a paper posted online late last year shows that in another natural setting, this intuition fails spectacularly. Suppose you require that your dice use only the numbers that appear on a regular die and have the same total as a regular die. Then, the paper showed, if A beats B and B beats C, A and C have essentially equal chances of prevailing against each other.

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Physicists at Leipzig University have once again gained a deeper understanding of the mechanism behind superconductors. This brings the research group led by Professor Jürgen Haase one step closer to their goal of developing the foundations for a theory for superconductors that would allow current to flow without resistance and without energy loss. The researchers found that in superconducting copper-oxygen bonds, called cuprates, there must be a very specific charge distribution between the copper and the oxygen, even under pressure.

This confirmed their own findings from 2016, when Haase and his team developed an experimental method based on that can measure changes that are relevant to superconductivity in the structure of materials. They were the first team in the world to identify a measurable material parameter that predicts the maximum possible —a condition required to achieve superconductivity at . Now they have discovered that cuprates, which under pressure enhance superconductivity, follow the charge distribution predicted in 2016. The researchers have published their new findings in the journal PNAS.

“The fact that the transition temperature of cuprates can be enhanced under pressure has puzzled researchers for 30 years. But until now we didn’t know which mechanism was responsible for this,” Haase said. He and his colleagues at the Felix Bloch Institute for Solid State Physics have now come a great deal closer to understanding the actual mechanism in these materials.

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Why the recent surge in jaw-dropping announcements? Why are neutral atoms seeming to leapfrog other qubit modalities? Keep reading to find out.

The table below highlights the companies working to make Quantum Computers using neutral atoms as qubits:

And as an added feature I am writing this post to be “entangled” with the posts of Brian Siegelwax, a respected colleague and quantum algorithm designer. My focus will be on the hardware and corporate details about the companies involved, while Brian’s focus will be on actual implementation of the platforms and what it is like to program on their devices. Unfortunately, most of the systems created by the companies noted in this post are not yet available (other than QuEra’s), so I will update this post along with the applicable hot links to Brian’s companion articles, as they become available.

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Summary: Combining neuroimaging and EEG data, researchers recorded the neural activity of people while listening to a piece of music. Using machine learning technology, the data was translated to reconstruct and identify the specific piece of music the test subjects were listening to.

Source: University of Essex.

A new technique for monitoring brain waves can identify the music someone is listening to.

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Summary: A newly developed machine learning model can predict the words a person is about to speak based on their neural activity recorded by a minimally invasive neuroprosthetic device.

Source: HSE

Researchers from HSE University and the Moscow State University of Medicine and Dentistry have developed a machine learning model that can predict the word about to be uttered by a subject based on their neural activity recorded with a small set of minimally invasive electrodes.

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