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.
The esoteric world of pure math doesn’t usually play much of a role in promoting fairness in the U.S. political system, but Tufts mathematicians Moon Duchin and Mira Bernstein believe that needs to change. It is math, they say, that could help overcome gerrymandering—the practice of drawing legislative districts that favor one party, class or race.
Aviv Regev likes to work at the edge of what is possible. In 2011, the computational biologist was collaborating with molecular geneticist Joshua Levin to test a handful of methods for sequencing RNA. The scientists were aiming to push the technologies to the brink of failure and see which performed the best. They processed samples with degraded RNA or vanishingly small amounts of the molecule. Eventually, Levin pointed out that they were sequencing less RNA than appears in a single cell.
To Regev, that sounded like an opportunity. The cell is the basic unit of life and she had long been looking for ways to explore how complex networks of genes operate in individual cells, how those networks can differ and, ultimately, how diverse cell populations work together. The answers to such questions would reveal, in essence, how complex organisms such as humans are built.
Every day in the U.S., about 22 people die waiting for an organ transplant. If scientists could 3-D print organs like kidneys, livers and hearts, all those lives could be saved. For years, people have been touting personalized organ printing as the future.
But despite decades of promising work in bioengineered bladders and other kinds of human tissue, we’re not close to having more complicated organs made from scratch. Harvard professor Jennifer Lewis, a leader in advanced 3-D printing of biological tissue, has only recently developed the ability to print part of a nephron, an individual unit of a kidney.
I asked Lewis what it will take to someday print a full kidney or a similarly complex organ.