A robotic AI system has been developed by scientists that is capable of improving stem cell procedures that are utilized in regenerative medicine. The development of the robotic AI system was carried out by a joint research group led by Genki Kanda at the RIKEN Center for Biosystems Dynamics Research (BDR). The peer-reviewed research was published in the scientific journal eLife last week. One example of the AI system's utilization is having correctly determined the conditions necessary for regrowing retina layers in the eye, which is vital for vision. There were about 200 million possible conditions in which the AI controlled a trial and error process, according to the study.

In the age of Big Data in biology, data science and machine learning have flourished and benefitted from their interdisciplinary application to biology. As a graduate student in this discipline, I read a lot of papers to stay up to date on the literature (and still have a large reading list to catch up on!), and thought I would share what have been some of the best papers I've read this year. In about 80–90% of the single-cell papers you'll encounter, depending on the research question, there will be at least one or two tSNE or UMAP plots to visualize the data they've collected, usually single-cell RNA-sequencing (scRNA-seq) data, where individual cells are profiled for their RNA abundance across the genome. These unsupervised dimensionality reduction methods have been more or less accepted as the status quo for data visualization in the world of single-cell genomics, so it took Academic Twitter by storm this summer when a new preprint boldly challenged that norm, arguing that these methods do little to preserve the latent structure of the data it seeks to convey to our 3D minds. Using the extreme example of preserving equidistant cells in high-dimensional space, and later relaxing it to near-equidistance, they show how tSNE and UMAP distort the orientation of groups of cells with near-equidistance spacing in the original space, clustering them with groups of cells that are evenly spread further apart.

A dozen organisms designed by artificial intelligence known as xenobots (C-shaped; beige) beside loose frog stem cells (white). A dozen organisms designed by artificial intelligence known as xenobots (C-shaped; beige) beside loose frog stem cells (white). Scientists say they've witnessed a never-before-seen type of replication in organic robots created in the lab using frog cells. Among other things, the findings could have implications for regenerative medicine. The discovery involves a xenobot – a simple, "programmable" organism that is created by assembling stem cells in a Petri dish -- and is described by a team of researchers from Tufts University, Harvard University and the University of Vermont in a paper published this week in the Proceedings of the National Academy of Sciences.

Now scientists at the University of Vermont, Tufts University, and the Wyss Institute for Biologically Inspired Engineering at Harvard University have discovered an entirely new form of biological reproduction -- and applied their discovery to create the first-ever, self-replicating living robots. The same team that built the first living robots ("Xenobots," assembled from frog cells -- reported in 2020) has discovered that these computer-designed and hand-assembled organisms can swim out into their tiny dish, find single cells, gather hundreds of them together, and assemble "baby" Xenobots inside their Pac-Man-shaped "mouth" -- that, a few days later, become new Xenobots that look and move just like themselves. And then these new Xenobots can go out, find cells, and build copies of themselves. "With the right design -- they will spontaneously self-replicate," says Joshua Bongard, Ph.D., a computer scientist and robotics expert at the University of Vermont who co-led the new research. The results of the new research were published November 29, 2021, in the Proceedings of the National Academy of Sciences.

Over billions of years, organisms have evolved many ways of replicating, from budding plants to sexual animals to invading viruses. Now scientists at the University of Vermont, Tufts University, and the Wyss Institute for Biologically Inspired Engineering at Harvard University have discovered an entirely new form of biological reproduction--and applied their discovery to create the first-ever, self-replicating living robots. The same team that built the first living robots ("Xenobots," assembled from frog cells--reported in 2020) has discovered that these computer-designed and hand-assembled organisms can swim out into their tiny dish, find single cells, gather hundreds of them together, and assemble "baby" Xenobots inside their Pac-Man-shaped "mouth"--that, a few days later, become new Xenobots that look and move just like themselves. And then these new Xenobots can go out, find cells, and build copies of themselves. "With the right design--they will spontaneously self-replicate," says Joshua Bongard, Ph.D., a computer scientist and robotics expert at the University of Vermont who co-led the new research.

Scientists at the University of Vermont and Tufts University used a supercomputer to evolve a design for tiny living robots made out of frog cells, then assembled them. The tiny new creatures did what they were supposed to do --make their way across a Petri dish. They also had some surprises for the researchers. "These are novel living machines," Joshua Bongard, a computer scientist and robotics expert at the University of Vermont who co-led the new research, said in a statement. "They're neither a traditional robot nor a known species of animal. The research results were published Monday in the Proceedings of the National Academy of Sciences. The first author was UVM doctoral student Sam Kriegman. The new "biobots" were designed on the Deep Green supercomputer cluster at UVM's Vermont Advanced Computing Core. Bongard said that in 100 runs, the supercomputer considered billions of designs, looking for a design for a creature that would travel across the bottom of a Petri dish as quickly as possible. "The design we built wasn't imagined by a human.

One day in the future when you need medical care, someone will examine you, diagnose the problem, remove some of your body's healthy cells, and then use them to grow a cure for your ailment. The therapy will be personalized and especially attuned to you and your body, your genes, and the microbes that live in your gut. This is the dream of modern medical science in the field of "regenerative medicine." There are many obstacles standing between this dream and its implementation in real life, however. Cells often differ so much from one another and differ in so many ways that scientists have a hard time predicting what the cells will do in any given therapeutic scenario.

Adaptive behaviors ranging from self-assembly to self-healing showcase the ability of such systems to sense and adapt to dynamic environments based on signaling between living cells. This signaling takes on many forms--biochemical, mechanical, and electrical--and uncovering it has become as much the purview of regenerative medicine as of fundamental biology. We cannot reverse-engineer native tissues if we do not understand the fundamental design rules and principles that govern their assembly from the bottom up (1). Movement is fundamental to many living systems and driven primarily by skeletal muscle in human bodies. Disease or damage that limits the functionality of skeletal muscle severely affects human health, mobility, and quality of life.

A new partnership between the UK and Japan will see medical researchers and scientists join forces, in advancing research into chronic conditions - such as diabetes, heart disease and arthritis - green technology and AI. The collaboration, announced by British Prime Minister Theresa May, Business Secretary Greg Clark and Japanese Prime Minister Shinzo Abe, will see £30 million invested into a new partnership aimed at promoting technology and innovation in both Britain and Japan. The partnership includes a £10 million programme led by the UK's Medical Research Council (MRC) and Japan's Agency for Medical Research and Development (AMED) that will advance regenerative medicine. Greg Clark commented: "The UK and Japan are home to some of the most innovative businesses in the world, and we share the same fundamental belief in the power of enterprise to improve the lives of our citizens. This government wants to give older people at least five extra healthy independent years of life by 2035."

The longevity and biotechnology industries are focusing on aging in a big way, and it's beginning to show. The fields of Artificial Intelligence (AI) and regenerative medicine are putting their money on combating aging and age-related diseases, and the benefits are likely to be immense. While biotechnology and AI are relatively new concepts, the announcements of funding and collaboration yesterday by and between three companies are bringing those concepts that much closer to the forefront of medicine. Insilico Medicine, a Baltimore-based next-generation AI company specializing in the application of deep learning for target identification, drug discovery and aging research, yesterday announced a collaboration agreement with WuXi AppTec, a leading global contract research outsourcing provider based in Shanghai, China, serving the pharmaceutical, biotech, and medical device industries. "It's a big step not only for Insilico Medicine but for AI and the pharmaceutical industries," said Alex Zhavoronkov, PhD, CEO of Insilico Medicine, Inc.