Bone marrow implants could forestall neurodegenerative diseases like Alzheimer’s, synthetic DNA sheds light on how life might’ve evolved elsewhere in the universe, and computer-designed DNA could combat uncontrollable microbial infections. Find out what has been bugging scientists in this week’s coolest scientific discoveries.
What is it? Transplanting bone marrow from young mice into old mice can slow cognitive decline in the old mice, improving memory and learning, according to research conducted at Cedars-Sinai Medical Center in LA and described in Communications Biology.
Why does it matter? The findings, which bolster scientists’ suspicions that cognitive decline might have something to do with the aging of blood cells, which are produced in the bone marrow. They could help researchers design treatments for neurodegenerative diseases like Alzheimer’s. (It may also warm the hearts of eccentric Silicon Valley gazillionaires who want to use the blood of the young to stop the aging process.)
How does it work? For the study, lab mice at the ripe old age of 18 months were given bone marrow transplants either from mice their own age or from 4-month-old mice, then tested six months later on activity levels and cognitive abilities, including memory. The mice that had received the younger bone marrow outperformed both the mice that had received the older bone marrow and a control group that had received no marrow at all. Researchers also examined the hippocampuses of the mice — a part of the brain responsible for forming long-term memories — and found that those receiving transplants of young marrow retained more synapses than others.
What is it? Artificial intelligence could help wind farm operators detect ice on the blades of their turbines.
Why does it matter? Ice is the enemy of wind turbines just like it’s the enemy of airplane wings, overstressing mechanical components or causing damage to the blades when it sheds. Meanwhile, wind farms are often located in remote and, er, windy regions like the mountains or the sea, making inspection and maintenance by humans a challenge. To combat the problem, a team of researchers in China and the U.S. has designed an AI protocol called WaveletFCNN, describing their findings in a new paper posted to arXiv.
How does it work? In the manner of many AI systems: complicatedly. The bottom line is that researchers trained WaveletFCNN with typical data collected by sensors on turbines — wind speed, temperature, power output, etc. — then designed an “anomaly-monitoring algorithm” to help it detect signs of frozen-over blades. In a test, the AI had an accuracy rate of more than 80 percent.
What is it? At Stanford, scientists are using machine learning to create theoretical DNA sequences that are “most likely to align with antimicrobial properties.”
Why does it matter? Bacterial infections are becoming ever harder to treat — and deadlier — because bacteria are developing resistance to antibiotics quicker than new antibiotics can be produced; the World Health Organization calls antibiotics resistance “one of the biggest threats to global health, food security and development today.” The antimicrobial proteins being developed on computers by the Stanford scientists don’t exist in nature, but the researchers say the scope of the threat requires some out-of-the-box thinking.
How does it work? Researchers created an algorithm, Feedback GAN, that produces massive amounts of DNA sequences, but it’s not just churning them out willy-nilly. Rather, the algorithm evaluates each snippet after it’s been produced; those that suggest antimicrobial properties are able to inform the design of future DNA sequences. “There's a built-in arbiter and, by having this feedback loop, the system learns to model newly generated sequences after those that are deemed likely to have antimicrobial properties,” said James Zou, a Stanford assistant professor of biomedical data science. The process is described further in Nature Machine Intelligence.
What is it? Speaking of DNA, we’re all agreed that it consists of four molecules, G, A, T and C, which bond in predictable pairs on a double helix to create the conditions necessary for all life — right? Right? Well, maybe not anymore: Chemist Steven Benner and colleagues have synthesized a new kind of DNA in the lab, adding four more molecules: S, P, B and Z. The new system is called hachimoji DNA, a combination of the Japanese words “hachi” (eight) and “moji” (letter — think emoji).
Why does it matter? Hachimoji DNA could be used in medical diagnosis and treatment, or in the emerging technology of DNA data storage: As opposed to current systems that degrade over time and have limited capacity, a single gram of DNA can store 215 million gigabytes of information with a much longer shelf life; and, like upgrading your iCloud subscription, twice as many DNA molecules could store twice as much information. On a theoretical level, this advance suggests that DNA molecules as we know them might not be universal precursors to life — that elsewhere in the cosmos, DNA structures might indeed look different than they do here. Andrew Ellington, a researcher on the project, said, “We do not suggest that this eight-letter alphabet arose prebiotically, any more than we think that DNA-RNA-protein arose together. However, we can imagine parallel processes.”
How does it work? “Benner’s team,” Nature reports, “created the synthetic letters by tweaking the molecular structure of the regular bases. The letters of DNA pair up because they form hydrogen bonds: each contains hydrogen atoms, which are attracted to nitrogen or oxygen atoms in their partner. Benner explains that it’s a bit like Lego bricks that snap together when the holes and prongs line up. ... By adjusting these holes and prongs, the team has come up with several new pairs of bases.” They then ran tests to verify that their synthetic DNA could work in sequences that — like the real stuff — would support life.
What is it? Maybe you’ve heard of graphene, a supermaterial so strong that just an atom-thick layer could support the weight of an elephant. Now scientists in China have designed a lightweight fiber from carbon nanotubes that can also be measured on the elephant scale: Just a cubic centimeter of the stuff could hold 160 of the pachyderms. Those who don’t have 160 elephants lying around, though, could settle for using the stuff to build an elevator to space.
Why does it matter? A space elevator, or even just a satellite anchored to Earth via cable, has long been a dream for scientists, but has remained — alas — pie in the sky: As the South China Morning Post reported last fall, in 2005 NASA put big money on a competition to design such a material, but nobody claimed the prize. NASA figures that a cable designed to reach space would need to have the tensile strength of 7 gigapascals, and the carbon nanotube fiber cooked up at Beijing’s Tsinghua University might be just the ticket: Researchers put the tensile strength of their new fiber at 80 gigapascals. (A gigapascal is 1 billion pascals, the unit that measures pressure and stress.)
How does it work? Carbon nanotubes themselves, according to the Morning Post, have the “highest known tensile strength of any material — theoretically up to 300 gigapascals.” The challenge is bonding them together into a cable that, to reach space, would have to stretch some 30,000 kilometers, and avoiding any defects in stitching the nanotubes together that would weaken the cable. The Tsinghua team described their method for doing so in Nature Nanotechnology.