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An Engineered Protein Can Kill Cancer Cells in the Bloodstream

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Most cancer research focuses on the mechanisms of tumor development, despite the fact that tumor metastasis—the spread of tumor cells—is responsible for approximately 90 percent of cancer deaths. The team in the lab of professor Michael King at Cornell’s Meinig School of Biomedical Engineering has made a breakthrough discovery that could change the focus of cancer treatment by targeting the cells that lead to metastasis. Their study, published today in the Journal of Controlled Release, shows that a protein they engineered to fit onto nanoparticles successfully kills tumor cells in the bloodstreams of mice with prostate cancer.

King’s lab engineered tiny lipids called liposomes, which are approximately one-one-hundredth the size of white blood cells, with a protein known as TRAIL (tumor necrosis factor related apoptosis-inducing ligand) to create the nanoparticles. Once they are injected into the bloodstream, TRAIL proteins attach to white blood cells, called leukocytes, as they travel through the bloodstream and kill the cancer cells. 

“When we made these particles and introduced them to the bloodstream of the mice we were able to kill all the cancer cells in blood flow within a couple hours. This therapeutic worked so well, it was like a key fitting a lock. It solved the puzzle,” King tells mental_floss.

Mice in the control groups (“Buffer” and “ES”) showed widespread metastasis to internal organs, as indicated by the color map. In contrast, mice treated with E-selectin/TRAIL liposomes (“ES/T”) showed no spread of cancer to the other organs—as well as a reduction of the tumor burden in the prostate. Image credit: Wayne et al. in Journal of Controlled Release

King’s lab had previously been studying ways to kill cancer cells by getting the cells to adhere to a medical device, which killed them. “Our breakthrough was, instead of making medical device surfaces toxic to cancer cells, we took the adhesion TRAIL molecules and put them on the surface of nanoparticles," he says. "When we flipped the geometry like that, and injected those proteins into the bloodstream or lymphatic system, we had really astounding success.”

To test the protein’s cancer-killing abilities, cancerous cells were surgically introduced into the healthy mice, giving them prostate cancer. When the mice developed tumors in their prostates big enough for researchers to feel and see, tumor cells began to release into the blood and move throughout the body, which “is what happens in human disease as well,” says King.

Their hope was that injecting TRAIL into the bloodstream and lymphatic systems of the mice would prevent new tumors forming in distant organs. The results were even better than that. “It was a total success. It prevented metastases, and shrunk the original tumor in size, which we weren’t even expecting. That was a bonus,” King says. 

A chart showing the organization of the study. They started treatment on the mice three weeks after tumor implantation and repeated it every three days until the endpoint of the trial, at nine weeks. The mice were imaged once per week to track tumor growth. Image credit: Wayne et al. in Journal of Controlled Release

The TRAIL treatment is promising as a cancer therapeutic in humans, says King, because the protein is a natural product made by immune cells and has already been tested in humans. “We just make more of it and put it in the right place. It’s very well tolerated by human patients, with no side effects,” he says. “Dosages that we use in our system to completely prevent metastases are 1% of the dosages that have already been safely used in humans. We anticipate no adverse effects.”

They believe it has great potential as a therapy in association with cancer-removal surgeries or biopsies. “We think maybe just one dose before surgery and one or more dosages after surgery could have a noticeable and very successful suppression or prevention of metastases,” says King. “That’s something we still need to prove with animal trials. Any intervention, even needle biopsy, is a potential route for disseminating tumor cells all over the body. Scheduled surgery is a situation where you know when that event will occur so why not time it perfectly with a small number of doses.” 

Their next study will look at treating metastasis in breast cancer using a mouse model. “We would be treating the mouse exactly the way the human disease would be treated, so that would be very convincing if we are successful.”

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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
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Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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Here's How to Change Your Name on Facebook
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Whether you want to change your legal name, adopt a new nickname, or simply reinvent your online persona, it's helpful to know the process of resetting your name on Facebook. The social media site isn't a fan of fake accounts, and as a result changing your name is a little more complicated than updating your profile picture or relationship status. Luckily, Daily Dot laid out the steps.

Start by going to the blue bar at the top of the page in desktop view and clicking the down arrow to the far right. From here, go to Settings. This should take you to the General Account Settings page. Find your name as it appears on your profile and click the Edit link to the right of it. Now, you can input your preferred first and last name, and if you’d like, your middle name.

The steps are similar in Facebook mobile. To find Settings, tap the More option in the bottom right corner. Go to Account Settings, then General, then hit your name to change it.

Whatever you type should adhere to Facebook's guidelines, which prohibit symbols, numbers, unusual capitalization, and honorifics like Mr., Ms., and Dr. Before landing on a name, make sure you’re ready to commit to it: Facebook won’t let you update it again for 60 days. If you aren’t happy with these restrictions, adding a secondary name or a name pronunciation might better suit your needs. You can do this by going to the Details About You heading under the About page of your profile.

[h/t Daily Dot]

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