Lifeboat Foundation

Oxford Research has reveals how high blood glucose reprograms the metabolism of pancreatic beta-cells in diabetes, acting as a major causal factor of Type 2 diabetes. This is significant because glucose metabolites (chemicals produced when glucose is broken down by cells), rather than glucose itself, have been discovered to be key to the progression of Type 2 diabetes.

With diabetes, the pancreatic beta-cells do not release enough of the hormone insulin, which lowers blood glucose levels. This is because a glucose metabolite damages pancreatic beta-cell function. High blood glucose levels cause an increased rate of glucose metabolism in the beta-cell which leads to a metabolic bottleneck and the pooling of upstream metabolites.

Around 90 percent of global cases of diabetes are Type 2 diabetes (T2D). T2D normally presents in later adult life, and by the time of diagnosis, as much as 50 percent of beta cell function has been lost. In T2D, the beta-cells have a reduced insulin content and the coupling between glucose and insulin release is impaired.

A team of chemists and material scientists at the University of Tokyo has developed a new class of interlocking supramolecular systems by combining metal-organic frameworks with rotaxanes. In their study, reported in the journal Nature Communications, the group combined the two structures and found possible uses for the results.

Metal-organic frameworks (MOFs) are compounds made using metal ions in such a way as to create one-, two-, or three-dimensional structures. The resultant ligands are known in the chemistry world as linkers or struts. They are typically used to make products such as sensing equipment, machines that store energy or those that separate and purify liquids. They have also been used for biological imaging and drug delivery.

Rotaxanes are molecular structures that are interlocked in dumbbell shapes. They are created by threading cyclic molecules into other molecules and then applying end caps. They are typically used as molecular switches in electronics devices, and sometimes as shuttles. In this new effort, the research team developed a way to connect the two types of compounds to create new kinds of interlocking structures.

Biologists usually define ‘life’ as an entity that reproduces, responds to its environment, metabolizes chemicals, consumes energy, and grows. Under this model, ‘life’ is a binary state; something is either alive or not.

This definition works reasonably well on planet Earth, with viruses being one notable exception. But if life is elsewhere in the universe, it may not be made of the same stuff as us. It might not look, move, or communicate like we do. How, then, will we identify it as life?

Continue reading “Radical New Theory Gives a Very Different Perspective on What Life Is” »

Significantly improved electric vehicle (EV) batteries could be a step closer thanks to a new study led by University of Oxford researchers, published today in Nature. Using advanced imaging techniques, this revealed mechanisms which cause lithium metal solid-state batteries (Li-SSBs) to fail. If these can be overcome, solid-state batteries using lithium metal anodes could deliver a step-change improvement in EV battery range, safety and performance, and help advance electrically powered aviation.

One of the co-lead authors of the study Dominic Melvin, a PhD student in the University of Oxford’s Department of Materials, said: ‘Progressing solid-state batteries with lithium metal anodes is one of the most important challenges facing the advancement of battery technologies. While lithium-ion batteries of today will continue to improve, research into solid-state batteries has the potential to be high-reward and a gamechanger technology.’

Li-SSBs are distinct from other batteries because they replace the flammable liquid electrolyte in conventional batteries with a solid electrolyte and use lithium metal as the anode (negative electrode). The use of the solid electrolyte improves the safety, and the use of lithium metal means more energy can be stored. A critical challenge with Li-SSBs, however, is that they are prone to short circuit when charging due to the growth of ‘dendrites’: filaments of lithium metal that crack through the ceramic electrolyte. As part of the Faraday Institution’s SOLBAT project, researchers from the University of Oxford’s Departments of Materials, Chemistry and Engineering Science, have led a series of in-depth investigations to understand more about how this short-circuiting happens.

In a scientific first, researchers have used machine learning-powered AI to design de novo enzymes — never-before-existing proteins that accelerate biochemical reactions in living organisms. Enzymes drive a wide range of critical processes, from digestion to building muscle to breathing.

A team led by the University of Washington’s Institute for Protein Design, along with colleagues at UCLA and China’s Xi’an Jiaotong University, used their AI engine to create new enzymes of a kind called luciferases. Luciferases — as their name implies — catalyze chemical reactions that emit light; they’re what give fireflies their flare.

“Living organisms are remarkable chemists,” David Baker, a professor of biochemistry at UW and the study’s senior author, said.

Brain waves act as carriers of information. A recently proposed “Cytoelectric Coupling” hypothesis suggests that these wavering electric fields contribute to the optimization of the brain network’s efficiency and robustness. They do this by influencing the physical configuration of the brain’s molecular framework.

In order to carry out its multifaceted functions, which include thought, the brain operates on various levels. Information like objectives or visuals is depicted through synchronized electrical activity among neuronal networks. Simultaneously, a combination of proteins and other biochemicals within and surrounding each neuron physically execute the mechanics required for participation in these networks.

A new paper by researchers at MIT, City University of London, and Johns Hopkins University posits that the electrical fields of the network influence the physical configuration of neurons’ sub-cellular components to optimize network stability and efficiency, a hypothesis the authors call “Cytoelectric Coupling.”

The chemical origin of life on Earth is a puzzle that scientists have been trying to piece together for decades. Many hypotheses have been proposed to explain how life came to be and what chemical and environmental factors on early Earth could have led to it. A step required in a number of these hypotheses involves the abiotic synthesis of genetic polymers—materials made up of a sequence of repeating chemical units with the ability to store and pass down information through base-pairing interactions.

One such hypothesis is the RNA (ribonucleic acid) world hypothesis, which draws from this concept and suggests that RNA could have been the original biopolymer of life both for genetic information storage and transmission, and for catalysis. However, in the absence of chemical activation of RNA monomers, studies have found that RNA polymerization would have been inefficient under primitive dry-down conditions without specialized circumstances such as lipid or salt-assisted synthesis or mineral templating.

While this does not necessarily make the RNA world hypothesis less plausible, primitive chemical systems were quite diverse and could not have possibly been as clean to just contain RNA and lipids, suggesting that other forms of primitive nucleic acid polymerization may have also taken place.

Eventually, these molecules probably evolved a lipid (fatty) boundary separating the internal environment of the organism from the exterior, forming protocells. Protocells could concentrate and organize better the molecules needed in biochemical reactions, providing a contained and efficient metabolism.

Life on Repeat?

Abiogenesis could have happened more than once. Earth could have birthed self-replicating molecules several times, and maybe early life for thousands or millions of years just consisted of a bunch of different self-replicating RNA molecules, with independent origins, competing for the same building blocks. Alas, due to the ancient and microscopic nature of this process, we may never know.

This study demonstrates that AI can be incredibly effective in helping us identify new drug candidates – particularly at early stages of drug discovery and for diseases with complex biology or few known molecular targets.

A machine learning model has been trained to recognise the key features of chemicals with senolytic activity. It recently found three chemicals able to remove senescent cells without damaging healthy cells.

Molecular structure of oleandrin. Credit: Mplanine, CC BY-SA 4.0, via Wikimedia Commons.

Continue reading “AI finds potential anti-aging molecules” »