This cartoon depicts turning back the aging clock through cellular regeneration of progeria mice (credit: Juan Carlos Izpisua Belmonte Lab/Salk Institute)
Salk Institute scientists have extended the average lifespan of live mice by 30 percent, according to a study published December 15 in Cell. They did that by rolling back the “aging clock” to younger years, using cellular reprogramming.
The finding suggests that aging isreversible by winding back an animal’s biological clock to a more youthful state and that lifespan can be extended. While the research does not yet apply directly to humans, it promises to lead to improved understanding of human aging and the possibility of rejuvenating human tissues.
Scientists from MIT and Boston University have developed biological cells that can count and ‘remember’ cellular events by creating simple circuits through a series of genes that are activated in a precise order. These circuits, which the scientists say simulate computer chips, could be employed to tally the number of times a cell divides or to track a cycle of developmental stages. Such counting cells could also be used as biosensors to count the number of toxin exposures present in an environment.
Senolytics meets Synthetic biology so come along and ask them anything!
Hey folks, We are excited to announce that the CellAge longform AMA opens Friday for questions and the CellAge team will answer them from Monday 11am PST/2pm EST/6pm GMT. We will update the link to the Futurology AMA once it is ready.
CellAge are using synthetic biology to create new biomarkers for senescent cell detection, developing a new therapy to remove senescent cells which drive the aging process using custom synthetic biology. Come along and ask them all about it.
Creative Machines; however, are they truly without a built in bias due to their own creator/s?
Despite nature’s bewildering complexity, the driving force behind it is incredibly simple. ‘Survival of the fittest’ is an uncomplicated but brutally effective optimization strategy that has allowed life to solve complex problems, like vision and flight, and colonize the harshest of environments.
Researchers are now trying to harness this optimization process to find solutions to a host of science and engineering problems. The idea of using evolutionary principles in computation dates back to the 1950s, but it wasn’t until the 1960s that the idea really took off. By the 1980s the approach had crossed over from academic curiosities into real-world fields like engineering and economics.
Applying natural selection to computing
Evolutionary algorithms are numerous and diverse, but they all seek to replicate key features of biological evolution, such as natural selection, reproduction and mutation. Typically these methods rely on a kind of trial and error — a large population of potential solutions to a problem are randomly generated and tested against a so-called “fitness function.” This lets the system rank the solutions in order of how well they solve the problem.
By combining the fields of quantum physics and biology, researchers have developed more efficient solar cells inspired by photosynthesis.
With current solar cells wasting about 80 percent of the energy absorbed, it will be interesting to see what future innovative approaches will allow in the pursuit toward universal clean energy.
Science once again reaches a milestone in technology by modeling it after nature. Researchers have devised a new type of highly efficient photocell by studying photosynthesis in plants.
Nathan Gabor, assistant professor for physics and astronomy at the University of California, Riverside, led research spurred by a simple question as to why plants are green. This eventually led to a quest to mimic plants’ ability to efficiently harvest energy from the Sun regardless of how erratic the sunlight is.
The US Army Research Laboratory (ARL) are at an advanced stage of with their synthetic biology research. The work could see bacteria being used to send signals and sense in a way similar to computers, the advantage being that it could potentially provide a more intuitive sensory experience to a piece of tech, and bypass some of the pitfalls unique to electrical structures. The research also has application for new 3D printing materials.
The goal of roboticists has long been to make A.I. as efficient as the human brain, and researchers at the Massachusetts Institute of Technology just brought them one step closer.
In a recent paper, published in the journal Biology, scientists were able to successfully train a neural network to recognize faces at different angles by feeding it a set of different orientations for several face templates. Although this only initially gave the neural network the ability to roughly reach invariance — the ability to process data regardless of form — over time, the network taught itself to achieve full “mirror symmetry. Through mathematical algorithms, the neural network was able to mimic the human brain’s ability to understand objects are the same despite orientation or rotation.
Move over, chemists. Thanks to proteins from Icelandic bacteria, scientists at Caltech have managed to coax microbes into making silicon-carbon bonds, a feat that until now has been achieved only by humans in the lab.
The findings, published last week in the journal Science, could open the door to new avenues in organic chemistry and drug development — and could help scientists investigate essential mysteries, such as whether life could be based on silicon instead of carbon on other planets.
A University of California, Riverside assistant professor has combined photosynthesis and physics to make a key discovery that could help make solar cells more efficient. The findings were recently published in the journal Nano Letters.
Nathan Gabor is focused on experimental condensed matter physics, and uses light to probe the fundamental laws of quantum mechanics. But, he got interested in photosynthesis when a question popped into his head in 2010: Why are plants green? He soon discovered that no one really knows.
During the past six years, he sought to help change that by combining his background in physics with a deep dive into biology.
