Your Future Smartphone May Detect Problems in Your Water
In 2014, the city of Flint, Michigan switched the residents' water supply to the Flint river, citing cheaper costs. However, due to improper filtering, lead contaminated this water, and according to the Associated Press, many of the city's residents soon reported health issues like hair loss and rashes. In 2015, a report found that children there had high levels of lead in their blood. The National Resource Defense Council recently discovered there could still be as many as twelve million lead pipes carrying water to homes across the U.S.
What if Flint residents and others in afflicted areas could simply flick water onto their phone screens and an app would tell them if they were about to drink contaminated water? This is what researchers at the University of Cambridge are working on to prevent catastrophes like what occurred in Flint, and to prepare for an uncertain future of scarcer resources.
Underneath the tough glass of our phone screen lies a transparent layer of electrodes. Because our bodies hold an electric charge, when our finger touches the screen, it disrupts the electric field created among the electrodes. This is how the screen can sense where a touch occurs. Cambridge scientists used this same idea to explore whether the screen could detect charges in water, too. Metals like arsenic and lead can appear in water in the form of ions, which are charged particles. When the ionic solution is placed on the screen's surface, the electrodes sense that charge like how they sense our finger.
Imagine a new generation of smartphones with a designated area of the screen responsible for detecting contamination—this is one of the possible futures the researchers propose.
The experiment measured charges in various electrolyte solutions on a touchscreen. The researchers found that a thin polymer layer between the electrodes and the sample solution helped pick up the charges.
"How can we get really close to the touch electrodes, and be better than a phone screen?" Horstmann, the lead scientist on the study, asked himself while designing the protective coating. "We found that when we put electrolytes directly on the electrodes, they were too close, even short-circuiting," he said. When they placed the polymer layer on top the electrodes, however, this short-circuiting did not occur. Horstmann speaks of the polymer layer as one of the key findings of the paper, as it allowed for optimum conductivity. The coating they designed was much thinner than what you'd see with a typical smartphone touchscreen, but because it's already so similar, he feels optimistic about the technology's practical applications in the real world.
While the Cambridge scientists were using touchscreens to measure water contamination, Dr. Baojun Wang, a synthetic biologist at the University of Edinburgh, along with his team, created a way to measure arsenic contamination in Bangladesh groundwater samples using what is called a cell-based biosensor. These biosensors use cornerstones of cellular activity like transcription and promoter sequences to detect the presence of metal ions in water. A promoter can be thought of as a "flag" that tells certain molecules where to begin copying genetic code. By hijacking this aspect of the cell's machinery and increasing the cell's sensing and signal processing ability, they were able to amplify the signal to detect tiny amounts of arsenic in the groundwater samples. All this was conducted in a 384-well plate, each well smaller than a pencil eraser.
They placed arsenic sensors with different sensitivities across part of the plate so it resembled a volume bar of increasing levels of arsenic, similar to diagnostics on a Fitbit or glucose monitor. The whole device is about the size of an iPhone, and can be scaled down to a much smaller size.
Dr. Wang says cell-based biosensors are bringing sensing technology closer to field applications, because their machinery uses inherent cellular activity. This makes them ideal for low-resource communities, and he expects his device to be affordable, portable, and easily stored for widespread use in households.
"It hasn't worked on actual phones yet, but I don't see any reason why it can't be an app," says Horstmann of their technology. Imagine a new generation of smartphones with a designated area of the screen responsible for detecting contamination—this is one of the possible futures the researchers propose. But industry collaborations will be crucial to making their advancements practical. The scientists anticipate that without collaborative efforts from the business sector, the public might have to wait ten years until this becomes something all our smartphones are capable of—but with the right partners, "it could go really quickly," says Dr. Elizabeth Hall, one of the authors on the touchscreen water contamination study.
"That's where the science ends and the business begins," Dr. Hall says. "There is a lot of interest coming through as a result of this paper. I think the people who make the investments and decisions are seeing that there might be something useful here."
As for Flint, according to The Detroit News, the city has entered the final stages in removing lead pipe infrastructure. It's difficult to imagine how many residents might fare better today if they'd had the technology that scientists are now creating.
Of all its tragedy, COVID-19 has increased demand for at-home testing methods, which has carried over to non-COVID-19-related devices. Various testing efforts are now in the public eye.
"I like that the public is watching these directions," says Horstmann. "I think there's a long way to go still, but it's exciting."
A new type of cancer therapy is shrinking deadly brain tumors with just one treatment
Few cancers are deadlier than glioblastomas—aggressive and lethal tumors that originate in the brain or spinal cord. Five years after diagnosis, less than five percent of glioblastoma patients are still alive—and more often, glioblastoma patients live just 14 months on average after receiving a diagnosis.
But an ongoing clinical trial at Mass General Cancer Center is giving new hope to glioblastoma patients and their families. The trial, called INCIPIENT, is meant to evaluate the effects of a special type of immune cell, called CAR-T cells, on patients with recurrent glioblastoma.
How CAR-T cell therapy works
CAR-T cell therapy is a type of cancer treatment called immunotherapy, where doctors modify a patient’s own immune system specifically to find and destroy cancer cells. In CAR-T cell therapy, doctors extract the patient’s T-cells, which are immune system cells that help fight off disease—particularly cancer. These T-cells are harvested from the patient and then genetically modified in a lab to produce proteins on their surface called chimeric antigen receptors (thus becoming CAR-T cells), which makes them able to bind to a specific protein on the patient’s cancer cells. Once modified, these CAR-T cells are grown in the lab for several weeks so that they can multiply into an army of millions. When enough cells have been grown, these super-charged T-cells are infused back into the patient where they can then seek out cancer cells, bind to them, and destroy them. CAR-T cell therapies have been approved by the US Food and Drug Administration (FDA) to treat certain types of lymphomas and leukemias, as well as multiple myeloma, but haven’t been approved to treat glioblastomas—yet.
CAR-T cell therapies don’t always work against solid tumors, such as glioblastomas. Because solid tumors contain different kinds of cancer cells, some cells can evade the immune system’s detection even after CAR-T cell therapy, according to a press release from Massachusetts General Hospital. For the INCIPIENT trial, researchers modified the CAR-T cells even further in hopes of making them more effective against solid tumors. These second-generation CAR-T cells (called CARv3-TEAM-E T cells) contain special antibodies that attack EFGR, a protein expressed in the majority of glioblastoma tumors. Unlike other CAR-T cell therapies, these particular CAR-T cells were designed to be directly injected into the patient’s brain.
The INCIPIENT trial results
The INCIPIENT trial involved three patients who were enrolled in the study between March and July 2023. All three patients—a 72-year-old man, a 74-year-old man, and a 57-year-old woman—were treated with chemo and radiation and enrolled in the trial with CAR-T cells after their glioblastoma tumors came back.
The results, which were published earlier this year in the New England Journal of Medicine (NEJM), were called “rapid” and “dramatic” by doctors involved in the trial. After just a single infusion of the CAR-T cells, each patient experienced a significant reduction in their tumor sizes. Just two days after receiving the infusion, the glioblastoma tumor of the 72-year-old man decreased by nearly twenty percent. Just two months later the tumor had shrunk by an astonishing 60 percent, and the change was maintained for more than six months. The most dramatic result was in the 57-year-old female patient, whose tumor shrank nearly completely after just one infusion of the CAR-T cells.
The results of the INCIPIENT trial were unexpected and astonishing—but unfortunately, they were also temporary. For all three patients, the tumors eventually began to grow back regardless of the CAR-T cell infusions. According to the press release from MGH, the medical team is now considering treating each patient with multiple infusions or prefacing each treatment with chemotherapy to prolong the response.
While there is still “more to do,” says co-author of the study neuro-oncologist Dr. Elizabeth Gerstner, the results are still promising. If nothing else, these second-generation CAR-T cell infusions may someday be able to give patients more time than traditional treatments would allow.
“These results are exciting but they are also just the beginning,” says Dr. Marcela Maus, a doctor and professor of medicine at Mass General who was involved in the clinical trial. “They tell us that we are on the right track in pursuing a therapy that has the potential to change the outlook for this intractable disease.”
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.