Computerized genetic-design tools automate the process by which researchers design complex genetic circuits that can program cells — especially bacteria and yeast — to carry out specific actions, such as activating a particular enzyme or churning out a certain protein. Synthetic biologists have used single-celled organisms in this way to produce drugs, biological sensors that include cells or antibodies, enzymes for use in industry, and more.
On a cold morning in Minneapolis last December, a man walked into a research centre to venture where only pigs had gone before: into the strongest magnetic resonance imaging (MRI) machine built to scan the human body. First, he changed into a hospital gown, and researchers made sure he had no metal on his body: no piercings, rings, metal implants or pacemakers. Any metal could be ripped out by the immensely powerful, 10.5-tesla magnet — weighing almost 3 times more than a Boeing 737 aeroplane and a full 50% more powerful than the strongest magnets approved for clinical use. “This is a window we’ve just never had in the intact human brain,” says Ravi Menon.
People with glioblastoma multiforme, one of the most common forms of brain cancer, have a median survival of less than 15 months after diagnosis. If researchers could grow numerous small brain-like structures that contained a replica of the person’s tumour and then bathe them in various treatments, in the space of a few weeks, they might learn exactly which ones would have the best chance of fighting brain cancer in that individual. Howard Fine, a neuro-oncologist at Weill Cornell Medicine in New York City, is developing such models, known as cerebral organoids. Organoids are particularly valuable for studying brain cancer because neither human brain tumours transplanted into mice nor human tumour stem cells grown in a culture dish behave in the same way as their counterparts in the body.
Debilitating hand pain is always bad news, but Harold Pimentel’s was especially unwelcome. As a computational-biology PhD student, his work involved constant typing — and he was born with only one arm. “My adviser jokingly said, ‘Can’t you do this by voice?’” he recalls. Three years later, as a computational-genomics postdoc at Stanford University in California, he does just that.
Sometimes it’s hard to understand someone else’s research through a static scientific paper. Across countless universities and companies, at whiteboards and cafeteria tables, you’ll find scientists in animated conversations explaining their research to one another, asking questions, playing around with each other’s data: in short, interacting. Across the internet in recent years, people have extended these explanations to include interactive graphics and code.
Now a web-only machine-learning journal called Distill aims to provide a formal home for these interactive graphical explanations.
Parents who have one child with an autism diagnosis can more accurately spot signs of the condition in their younger child at 12 months of age than clinicians can, according to a new study1. The advantage fades by 18 months of age, however.
The findings suggest that surveying knowledgeable parents could move up the date of autism diagnosis, enabling therapy to begin sooner.
Biosimilars are a growing share of the U.S. pharmaceuticals market. But while there are at least 240 biosimilars in the development pipeline, just nine have achieved FDA approval and only three have reached the market.
What needs to change for more biosimilars to enter the U.S. market?
This is shaping up to be the year of DNA for cryptocurrency. One startup after another is offering to pay you in bitcoin-like tokens for sharing your genetic data.
But it’s hard to see how using blockchains and cryptocurrencies will substantially increase demand for genome sequencing. That’s a vexing problem because too few genomes have been sequenced and analyzed to generate as many meaningful insights as scientists had hoped.