Nanoengineers send antibiotic-delivering micromotors into the body to treat cancer-causing infection

Nanoengineers have demonstrated for the first time how “micromotors” that measure half the width of a human hair can be used to transport antibiotics through the body.

Nanoengineers at the University of California San Diego tested the micromotors in mice with Helicobacter pylori infections, which can also be found in about two-thirds of the world’s population and while many people will never notice any signs of its presence it can cause peptic ulcers and stomach cancer.

The mice received the micromotors – packed with a clinical dose of the antibiotic clarithromycin – orally once a day for five consecutive days.

Afterwards, nanoengineers evaluated the bacterial count in each mouse stomach and found that treatment with the micromotors was slightly more effective than when the same dose of antibiotic was given in combination with proton pump inhibitors, which also suppress gastric acid production.

Micromotors administered to the mice swam rapidly throughout the stomach while neutralising gastric acid, which can be destructive to orally administered drugs such as antibiotics and protein-based pharmaceuticals.

Because gastric acid is so destructive to traditional antibiotics drugs used to treat bacterial infections, ulcers and other diseases in the stomach are normally taken with additional substances, called proton pump inhibitors.

But when taken over longer periods or in high doses, proton pump inhibitors can cause adverse side effects including headaches, diarrhea and fatigue. In more serious cases, they can cause anxiety or depression.

The micromotors, however, have a built-in mechanism that neutralises gastric acid and effectively deliver their drug payloads in the stomach without requiring the use of proton pump inhibitors.

“It’s a one-step treatment with these micromotors, combining acid neutralisation with therapeutic action,” said Berta Esteban-Fernández de Ávila, a postdoctoral scholar in Wang’s research group at UC San Diego and a co-first author of the paper.

The nanoengineers say that while the present results are promising, this work is still at an early stage.

To test their work, the team is planning future studies to into the therapeutic performance of the micromotors in animals and humans, and will compare it with other standard therapies used to combat stomach diseases.

UC San Diego nanoengineers also plan to test different drug combinations with the micromotors to treat multiple diseases in the stomach or in different sections of the gastrointestinal tract.

Overall, the researchers say that this work opens the door to the use of synthetic motors as active delivery platforms in the treatment of diseases.

Image and video courtesy of the Laboratory for Nanobioelectronics at UC San Diego.

Researchers believe they can diagnose depression by looking at Instagram photos

It may seem that everyone on Instagram is living their best life, but according to new research photos that are bluer, darker, and less populated might reveal a struggle with mental health.

Researchers from the University of Vermont and Harvard University, have found that they could diagnose depression by using machine learning to study the composition of Instagram photos.

According to the researchers, photos that are bluer, more gray, dark or with fewer faces indicate that the profile’s owner has depressive tendencies.

The computer’s detection rate of 70% is more reliable than the 42% success rate of general-practice doctors diagnosing depression in-person.

“This points toward a new method for early screening of depression and other emerging mental illnesses,” says Chris Danforth, a professor at the University of Vermont who co-led the new study. “This algorithm can sometimes detect depression before a clinical diagnosis is made.”

“So much is encoded in our digital footprint. Clever artificial intelligence will be able to find signals, especially for something like mental illness.”

Featured image courtesy of Ink Drop / Shutterstock.com.

To conduct the study, the researchers used the Instagram feeds of 166 people, around half of whom had reported having been clinically depressed in the last three years.

The researchers then collected and analysed 43,950 photos, using insights from well-established psychology research, about people’s preferences for brightness, colour, and shading. They also investigated the filters used by healthy and mentally ill people.

They found that healthy individual chose Instagram filters, like Valencia, that gave their photos a warmer brighter tone. Among depressed people the most popular filter was Inkwell, making the photo black-and-white.

Faces in photos also turned out to provide signals about depression. The researchers found that depressed people were more likely than healthy people to post a photo with people’s faces—but these photos had fewer faces on average than the healthy people’s Instagram feeds.

“People suffering from depression were more likely to favour a filter that literally drained all the colour out the images they wanted to share,” said Danforth and Andrew Reece of Harvard University who co-wrote the study.

“Fewer faces may be an oblique indicator that depressed users interact in smaller settings.”

Images courtesy of Reece and Danforth

More than half of a general practitioners’ depression diagnoses are false, but the computational algorithm was able to achieve a detection rate of 70%, while GPs are said to have only a 42% success rate.

The new study also shows that the computer model was able to detect signs of depression before a person’s date of diagnosis. “This could help you get to a doctor sooner,” Danforth says. “Or, imagine that you can go to doctor and push a button to let an algorithm read your social media history as part of the exam.”