Surprisingly there are no pre-symptomatic screening methods for the common cold or the flu, allowing these viruses to spread unbeknownst to the infected. However, if we could detect when infected people will get sick even before they were showing symptoms, we could do a lot more to contain the flu or common cold and possibly save lives. Well, that’s what this group of researchers in this highly collaborative study set out to accomplish using data from wearable devices.
Participants of the study were given an E4 wristband, a research-grade wearable that measures heart rate, skin temperature, electrodermal activity, and movement. They then wore the E4 before and after inoculation of either influenza or rhinovirus. The researchers used 25 binary, random forest classification models to predict whether or not participants were infected based on the physiological data reported by the E4 sensor. Their results are pretty lengthy, so I’ll only highlight a few major discussion points. In one particular analysis, they found that at 36 hours after inoculation their model had an accuracy of 89% with a 100% sensitivity and a 67% specificity. Those aren’t exactly world-shaking numbers, but something the researchers thought was pretty promising nonetheless.
One major consideration for the accuracy of their model is the quality of the data reported by the wearable. Namely, if the data reported by the wearable isn’t reliable itself, no model derived from such data can be trustworthy either. We’ve discussed those points here at Hackaday before. Another major consideration is the lack of a control group. You definitely need to know if the model is simply tagging everyone as “infected” (which specificity does give us an idea of, to be fair) and a control group of participants who have not been inoculated with either virus would be one possible way to answer that question. Fortunately, the researchers admit this limitation of their work and we hope they will remedy this in future studies.
Studies like this are becoming increasingly common and the ongoing pandemic has motivated these physiological monitoring studies even further. It seems like wearables are here to stay as the academic research involving these devices seems to intensify each day. We’d love to see what kind of data could be obtained by a community-developed device, as we’ve seen some pretty impressive DIY biosensor projects over the years.
In the early 1950s, the only thing scarier than the threat of nuclear war was the annual return of polio — an easily-spread, incurable disease that causes nerve damage, paralysis, and sometimes death. At the first sign of an outbreak, public hot spots like theaters and swimming pools would close up immediately.
One of the worst polio epidemics in the United States struck in 1952, a few years into the postwar baby boom. Polio is more likely to infect children than adults, so the race to create a vaccine reached a fever pitch.
Most researchers were looking into live-virus vaccines, which had worked nicely for smallpox and rabies and become the standard approach. But Jonas Salk, a medical researcher and budding virologist, was keen on the idea of safer, killed-virus vaccines. He believed the same principle would work for polio, and he was right. Within a few years of developing his vaccine, the number of polio cases in the United States dropped from ~29,000 in 1955 to less than 6,000 in 1957. By 1979, polio had been eradicated in the US.
Jonas Salk is one of science’s folk heroes. The polio vaccine was actually his sophomore effort — he and Thomas Francis developed the first influenza vaccine in the 1940s. And he didn’t stop with polio, either. Toward the end of his life, Salk was working on an AIDS vaccine.
Continue reading “Jonas Salk, Virologist And Vaccination Vanguard”
Did you get a flu shot this year? How about last year? In a world of next-day delivery and instant downloads, making the yearly pilgrimage to the doctor or the minute clinic feels like an outdated concept. Even if you get your shots free at the office, it’s still a pain to have to get vaccinated every year.
Unfortunately, there’s really no other way to deal with the annual threat of influenza. There’s no single vaccine for the flu because there are multiple strains that are always mutating. Unlike other viruses with one-and-done vaccinations, influenza is a moving target. Developing, producing, and distributing millions of vaccines every year is a massive operation that never stops, or even slows down a little bit. It’s basically Santa Claus territory — if Santa Claus delivered us all from mass epidemics.
The numbers are staggering. For the 2018-19 season, as in last year, there were 169.1 million doses distributed in the United States, up from 155.3 million doses the year before. How do they do it? We’re gonna roll up our sleeves and take a stab at it.
Continue reading “The Strain Of Flu Shot Logistics”
Few people outside the field know just how big bioscience can get. The public tends to think of fields like physics and astronomy, with their huge particle accelerators and massive telescopes, as the natural expressions of big science. But for decades, biology has been getting bigger, especially in the pharmaceutical industry. Specialized labs built around the automation equipment that enables modern pharmaceutical research would dazzle even the most jaded CERN physicist, with fleets of robot arms moving labware around in an attempt to find the Next Big Drug.
I’ve written before on big biology and how to get more visibility for the field into STEM programs. But how exactly did biology get big? What enabled biology to grow beyond a rack of test tubes to the point where experiments with millions of test occasions are not only possible but practically required? Was it advances in robots, or better detection methodologies? Perhaps it was a breakthrough in genetic engineering?
Nope. Believe it or not, it was a small block of plastic with some holes drilled in it. This is the story of how the microtiter plate allowed bioscience experiments to be miniaturized to the point where hundreds or thousands of tests can be done at a time.
Continue reading “Go Small, Get Big: The Hack That Revolutionized Bioscience”