Lifeboat Foundation

Just as it’s hard to understand a conversation without knowing its context, it can be difficult for biologists to grasp the significance of gene expression without knowing a cell’s environment. To solve that problem, researchers at Princeton Engineering have developed a method to elucidate a cell’s surroundings so that biologists can make more meaning of gene expression information.

The researchers, led by Professor of Computer Science Ben Raphael, hope the new system will open the door to identifying rare cell types and choosing cancer treatment options with new precision. Raphael is the senior author of a paper describing the method published May 16 in Nature Methods.

The basic technique of linking gene expression with a cell’s environment, called spatial transcriptomics (ST), has been around for several years. Scientists break down tissue samples onto a microscale grid and link each spot on the grid with information about gene expression. The problem is that current computational tools can only analyze spatial patterns of gene expression in two dimensions. Experiments that use multiple slices from a single tissue sample—such as a region of a brain, heart or tumor—are difficult to synthesize into a complete picture of the cell types in the tissue.

The latest trial studied 706 adults who have alopecia, aged 18 to 65, for 24 weeks in the US, Canada and Europe. On average, the patients studied only had 16 percent of their hair at the start of the trial, with no one having more than 50 percent.

They were split into three groups: one was given a placebo, another an 8 milligrams twice-daily dose, and lastly a 12-milligram, twice-daily pill.

Both groups taking the non-placebo doses saw regrowth, with a total of 41.5 percent of the stronger dose recipients experiencing 80 percent of hair regrowth. Among those that received the lower dose, nearly 30 percent experienced the same amount of hair regrowth. In the placebo group, only 0.8 percent of the participants saw more than 80% of hair growth.

Epigenetic clocks can measure biological aging, but the relationship between epigenetic age and other hallmarks of aging is incompletely understood. Here the authors show that epigenetic age is associated with nutrient sensing, mitochondria activity and stem cell depletion but distinct from cellular senescence, telomere attrition and genomic instability.

Models suggest that a comet that split away in 1995 (and is still disintegrating) will approach our orbit, according to Earth Sky.

That means we’ll witness a spectacular meteor shower unlike anything we’ve seen in most of our lives.

Should we send messages into space in an effort to contact intelligent extra-terrestrial civilizations? Or should be fear them attacking us and transmit nothing? Two conflicting and oft-heard questions, but it turns out we may overlooking something rather important and completely obvious— it’s probably us that are the malicious aliens.

When I read that we’ve got more chance of being struck by a planet-killer asteroid than being invaded by aliens, I was intrigued.

So I got in touch with Alberto Caballero, the author of the though experiment-style paper published this week, to find out more. His paper is an attempt to determine how many malicious extraterrestrial civilizations there could be, and how likely it is that they would invade us.

A new training approach yields artificial intelligence that adapts to diverse play-styles in a cooperative game, in what could be a win for human-AI teaming.

As artificial intelligence gets better at performing tasks once solely in the hands of humans, like driving cars, many see teaming intelligence as a next frontier. In this future, humans and AI are true partners in high-stakes jobs, such as performing complex surgery or defending from missiles. But before teaming intelligence can take off, researchers must overcome a problem that corrodes cooperation: humans often do not like or trust their AI partners.

Now, new research points to diversity as being a key parameter for making AI a better team player.

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The experiment will investigate the Unruh effect, which is produced by a mixture of quantum mechanics and special relativity.

Scientists have long known that touching plants can set off a stress reaction in them – but until now it hasn’t been exactly clear how that worked at a molecular level, something that a new study hopes to shed light on.

The researchers behind the study have identified certain genetic keys inside plants that lead to two separate signaling pathways, explaining why plants react so strongly to being touched.

Understanding more about how this process works at a fundamental level could help researchers in a variety of different areas, from improving plant health to getting higher harvest yields from the same crop.