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Machine learning is essential to designing the polymers, Murthy emphasizes, because they must be tailored to the specific gene therapy.

“There’s a tight interplay between the payload and in vivo mechanism of action, and the delivery vehicle needed to bring [the therapy] to that location,” he says. “You can’t have one without the other, so they have to be integrated at an early stage.”

The company hopes to use machine learning to explore the polymer design space, giving them a starting point to design a polymer. Subsequently, as the gene therapy moves from the preclinical to clinical stage, they can use artificial intelligence to tweak the polymer to make the therapy work better.

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Researchers at the University of Wisconsin–Madison and Academia Sinica of Taiwan have harnessed a combination of lab-grown cells to regenerate damaged heart muscle.

The study is published in Circulation. It addresses major challenges of using cells, called cardiomyocytes, grown from , and takes a crucial step toward future clinical applications.

Previous research has shown that transplanting cardiomyocytes made from induced (iPSC) can replace muscle in the hearts of mammals. Researchers have struggled to bring the treatment to the clinic, in part because the implanted cells haven’t developed enough life-sustaining blood vessels to survive very long.

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A UK-led team of researchers restrained mice for 6 hours to induce a stress response and then analyzed the rodents’ brains on a molecular level.⁠

This led to the discovery of increased levels of five microRNAs (miRNAs) — small molecules that help determine which genes in a cell are expressed and which aren’t — in the amygdala, the brain region implicated in anxiety. When the researchers took a closer look at the miRNA that reached the highest levels, miR-483-5p, they saw that it suppressed the expression of the Pgap2 gene — and that this suppression appeared to provide stress relief and reduce anxiety-related behavior.⁠

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The discovery of an “anxiety gene” — and a natural way to turn it off — in the brains of mice could lead to new treatments for anxiety disorders, which are the most common type of mental illness in the world.

Continue reading “Scientists discover “anxiety gene” in the brain — and a natural way to turn it off” | >

Progress update: Our latest AlphaFold model shows significantly improved accuracy and expands coverage beyond proteins to other biological molecules, including ligands.

Since its release in 2020, AlphaFold has revolutionized how proteins and their interactions are understood. Google DeepMind and Isomorphic Labs have been working together to build the foundations of a more powerful AI model that expands coverage beyond just proteins to the full range of biologically-relevant molecules.

Today we’re sharing an update on progress towards the next generation of AlphaFold. Our latest model can now generate predictions for nearly all molecules in the Protein Data Bank (PDB), frequently reaching atomic accuracy.

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In a new study, Deepmind and colleagues at Isomorphic Labs show early results from a new version of AlphaFold that brings fully automated structure prediction of biological molecules closer to reality.

The Google Deepmind AlphaFold and Isomorphic Labs team today unveiled the latest AlphaFold model. According to the companies, the updated model can now predict the structure of almost any molecule in the Protein Data Bank (PDB), often with atomic accuracy. This development, they say, is an important step towards a better understanding of the complex biological mechanisms within cells.

Since its launch in 2020, AlphaFold has influenced protein structure prediction worldwide. The latest version of the model goes beyond proteins to include a wide range of biologically relevant molecules such as ligands, nucleic acids and post-translational modifications. These structures are critical to understanding biological mechanisms in cells and have been difficult to predict with high accuracy, according to Deepmind.

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Nanotechnology sounds like a futuristic development, but we already have it in the form of CPU manufacturing. More advanced nanotech could be used to create independent mobile entities like nanobots. One of the main challenges is selecting the right chemicals, elements, and structures that actually perform a desired task. Currently, we create more chemically oriented than computationally oriented nanobots, but we still have to deal with the quantum effects at tiny scale.

One of the most important applications of nanotechnology is to create nanomedicine, where the technology interacts with biology to help resolve problems. Of course, the nanobots have to be compatible with the body (e.g. no poisonous elements if they were broken down, etc).

We dive into an interesting study on creating nanobarrels to deliver a particular payload within the bloodstream (currently in animals, but eventually in humans). This study is able to deliver RNA to cancer cells that shuts them down, without affecting the rest of the body. This type of application is why the market for nanotechnology keeps growing and will have a substantial impact on medicine in the future.

#nanotech #nanobots #medicine.

Continue reading “How nanobots and nanomedicine will improve our health” | >

https://youtube.com/watch?v=ZzsM2wd9h8k

C60 Evo delivers an incredible study that shows eradication of tumors & 90% increase In life with C60 Evo co-owners Patty Greer & Chris Burns and RedPill 78. We discuss the difference between industrial grade Carbon 60 and our Pure C60 “ESS60” made specifically for humans and pets. Three incredible organic edible oils, two different facial serum’s, hair, renewal products, and even lip balm’s infused with pure C60 ESS60 for maximum benefits. We sell all over the world, and people +are pets are healing daily! C60Evo.com

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