Posts Tagged ‘influenza’

Study Turns Up Viral Key That Might Lead to Universal Flu Treatment

Researchers have found a novel method for stopping the spread of influenza viruses, a finding that could lead to a universal treatment for flu. The method involves stopping the genetic process by which the virus replicates itself. Researchers can essentially flip a switch that stops RNA in its tracks.

The influenza A virus contains eight individual single-stranded RNA segments, each of which has to make protein as well as new segments, in processes called transcription and replication. The multitasking strands must prioritize their work, so they must start with transcription and move on to replication. Researchers at Mount Sinai School of Medicine in New York figured out how to prevent RNA from starting the replication process. Their results were published June 1 online in the Proceedings of the National Academy of Sciences.

Using a novel process called deep sequencing, the team found a small viral RNA segment, or svRNA, that is integral to the change. Inhibiting the svRNA from doing its work stymies replication, and therefore slows the spread of the virus.

Even better, influenza A shares this trait with its viral cousins, influenza B and C, meaning the svRNA switch can be used to stop all kinds of flu -- even the H1N1 flu. As an added bonus, if the virus is prevented from replicating, it stays in transcription mode and produces more proteins. This helps the body's immune system build up its defenses, according to Benjamin tenOever, an assistant microbiology professor at Mount Sinai and a study author.

The process used to make this discovery is also groundbreaking, the researchers say. The deep sequencing allowed the scientists to obtain millions of small RNAs from cells in an unbiased fashion, according to a Mount Sinai release.

The next step is to find a way to introduce RNA "antagonists" to inhibit the svRNA's switch function, tenOever says. That's still a long way off, but the knowledge that RNA can be switched off means that a universal flu treatment is a possibility.

[Science Daily]

Darpa’s Genetic Diagnostic Suite Will Know You’re Sick Before You Do

Long before you even feel sick, a new Darpa-funded bio-sensor will know what ails you. Researchers at Duke University are developing a device that can betray exposure to a virus even before a person's first sneeze, Wired's DangerRoom blog reports.

The sensor detects changes in gene expression that occur in people exposed to viruses like the common cold, flu, or the respiratory syncytial virus.

Led by Dr. Geoffrey Ginsburg, director of Duke's Institute for Genome Science & Policy, the team identified 30 genetic markers that are activated by viruses. In some cases, the changes occurred hours or days before symptoms started.

This approach would let doctors and public-health officials make quick diagnoses before someone even appears sick. Current tests look for presence of the actual pathogen, but that takes longer and doesn't work until a person has symptoms, Ginsburg says.

The team started human trials last year, monitoring 80 people in four studies. Healthy people were exposed to three viral strains, and their blood, urine and saliva were then tested for specific gene signatures that would characterize illness, DangerRoom reports.

The next step is to analyze an ongoing study of Duke freshmen living in dorms. Participants were asked to file daily reports about their health and provide blood and other samples as requested, according to a university news release.

Darpa provided $19.5 million to fund the study, seeing potential in a system that can evaluate military personnel before they're deployed. An early-warning system could also help quarantine troops before they can infect others.

The research could lead to public-health benefits well beyond the military, however. The team also found that genetic signatures for viral infections are different from those triggered by bacterial infections. Definitive information about a patient's ailment can make antibiotic-resistant superbugs less likely, if fewer doctors prescribe antibiotics when they're not necessary.

What's more, public health agencies could use the technology to isolate outbreaks of influenza virus, possibly stemming pandemics before they can spread.

Mathematical Model Analyzes Facebook Networks to Prioritize Who Should Receive Vaccinations

People who are "bridges" among different social groups appear as good vaccination bets

With vaccine supplies limited, social butterflies on Facebook could find themselves targeted for real-world injections. Stanford University researchers have created an algorithm that uses social networking data to identify the people who are "bridges" between different tight-knit circles of friends or communities, so that limited vaccine supplies can be used wisely.

The mathematical model focused on the fact that just a few individuals often form the links between different social groups. It also made use of data that came from back in 2005, when Facebook was only open to college students.

The relationships and interactions on five university campuses provided a useful starting scenario for the model to recognize clusters of people and predict bridges between them.

"When a new virus starts spreading, neither the time nor the necessary doses of vaccine to immunize everyone is available," said Marcel Salathe, a postdoc biology researcher at Stanford University. So you'd want a strategy that allows you to protect a population as much as possible given the limited resources that you have."

More details on the Stanford work appear in the April 8 issue of the PLoS Computational Biology.

Scientists have made growing use of social networking data that contains once-personal info. HP Labs researchers recently announced that they used Twitter data to predict the box office success of the latest Hollywood films. And the Pentagon's DARPA challenged people to sift through the disinformation available on social networks such as Twitter and hunt down the physical location of 10 red balloons located around the U.S.

[Stanford Report]