New Class of Colloids
One of the main drivers in new technology is material science. People out there have a ton of great ideas, but are unable to realize them because the combination of properties in a single material don’t yet exist. For example, skyscrapers weren’t built until the advent of steel, high-tech airplanes require titanium and carbon fiber, and body armor wasn’t feasible before Kevlar.
Earlier this year, a team of researchers at the University of Illinois Steve Granick developed a brand new way to create a class of materials called colloids. Trust me, you’re already familiar with them. A colloid is a substance microscopically dispersed evenly throughout another substance.
Still confused? Think of air bubbles being captured in a network of fat droplets in whipped cream, gelatin holding together a sweet liquid in Jell-O, or blood cells distributed throughout plasma coursing through your veins.
What these all have in common, however, is that they occur naturally. They’re biological. The team from Illinois discovered that they could use tiny latex spheres dubbed “Janus spheres” that attract each other in water on one side, but repel each other on the other. By carefully adjusting the salinity of the water they are placed in, the team can control how the spheres behave. In different concentrations, they clump together in different ways, automatically forming new complex structures and creating new materials with specifically designed properties.
What’s more, these structures are unnatural. None of the examples in nature take on these types of shapes. So the team is now working on engineering other structures to build new supermolecules in order to achieve greater control over their formation.
Fastest Fast Four Ever
Measuring the T2* through the basal ganglia using multivoxel pattern analysis – specifically the caudate nucleus, putamen and nucleus accumbens – can predict how quickly you learn to destroy a space fortress while avoiding dangerous hazards.
MRI images of brain activity in regions associated with procedural learning, coordinated movement and feelings of reward can predict how quickly you improve on a video game called Space Fortress incredibly accurately.
Oh. Okay. Neat.
Why Going Across Town Seems Such a Pain in the Ass
Tell me if this sounds familiar. You move to a new part of town, a completely different city or perhaps across the country. Once there, you start exploring the area, zipping around the city and perhaps even driving an hour or two away to see what awaits. But after a time, the adventure erodes. Soon, you don’t even want to go to the post office because it’s all the way across town.
The thing is, across town is only 10 minutes away. Not exactly a trek across Manhattan.
What’s going on here? Do people just become lazy? Too busy once they’re settled in?
According to new research from David Uttal of Northwestern University, this phenomenon happens because people become more biased.
And more accurate.
It sounds counterintuitive, but both are true. The longer you live somewhere, the more accurate your estimates of the distances between places becomes. But at the same time, you become biased towards taking the time to leave your immediate surroundings.
By Uttal’s best guess, it’s not that 10 minutes is really too far to drive and you just didn’t used to realize how far away it was. He believes it comes from a natural tendency to form part of a group; a northsider or southsider. Or perhaps preferring downtown, old town or campus.
It may seem like a harmless phenomenon that just keeps people put, but there are negative consequences. Communities don’t form on a big scale when places are segregated and distinct.
“As other researchers have shown, in segregated areas, people may tend to believe that they are farther apart than they really are,” Uttal said. “And if we’re trying to bring people together, we have to address the cognitive biases that they create. You tend to see the area that you’re close to as closer and the areas that are socially and cognitively further from you as being geographically farther. “
Where’s Waldo, I Mean, the Cherry Red Nucleoli?
At times, pathology can be like Where’s Waldo. Part of the job is picking up a slide that was created using samples from the patient and scan the cells for abnormalities. And part of the job is doing this hundreds of times a day. I don’t care who you are, boredom and fatigue will set in. Not only that, maybe something is wrong that you miss or can’t identify.
After all, it’s almost never Lupus.
However, thanks to an incredible advance made possible by a collaboration between University of Michigan’s Ulysses Balis, the Massachusetts General Hospital and Harvard University, pathology just got a helping hand.
The program can easily spot abnormalities. The user can either identify an abnormal cell already spotted on the sample or choose from a large database, and the program will quickly scan the entire slide, highlighting the areas with the most potential to be matches. The amazing part is that it can recognize similar cells whether they’re rotated 90 degrees, upside down, bigger, smaller or even a mirror image.
It can readily separate calcifications from malignancies in breast tissue samples, search for and count particular cell types in a bone marrow slide, or quickly identify the cherry red nucleoli of cells associated with Hodgkin’s disease.
The trick is that the algorithm searches using circles rather than squares. It follows a circle around, noting changes along the way, and then looks for circles with the same attributes no matter the size, location, orientation or angle. This technique wouldn’t work with a square or rectangular-shaped search structure because those shapes don’t remain symmetrical as they rotate.
“It’s one of those things that’s only obvious in hindsight,” Balis says.
Put perhaps most impressively, it really can be used to find Waldo.
“You just have to generate a vector for his face,” explains Jason Hipp, M.D., Ph.D., co-lead author of the paper. “Just as one would generate a vector to recognize calcifications in breast tissue.”