New tool for exploring cells in 3D created

The new software can generate editable models of mid-size biological structures such as this one of HIV. Credit: Image created by Graham Johnson and Ludovic Autin of The Scripps Research Institute

Researchers can now explore viruses, bacteria and components of the human body in more detail than ever before with software developed at The Scripps Research Institute (TSRI).

In a study published online ahead of print December 1 by the journal Nature Methods, the researchers demonstrated how the software, called cellPACK, can be used to model viruses such as HIV.

"We hope to ultimately increase scientists' ability to target any disease," said Art Olson, professor and Anderson Research Chair at TSRI who is senior author of the new study.

Putting cellPACK to the Test

The cellPACK software solves a major problem in structural biology. Although scientists have developed techniques to study relatively large structures, such as cells, and very small structures, such as proteins, it has been harder to visualize structures in the medium "mesoscale" range.

With cellPACK, researchers can quickly and efficiently process the data they've collected on smaller structures to assemble models in this mid-size range. Previously, researchers had to create these models by hand, which took weeks or months compared with just hours in cellPACK.

As a demonstration of the software's power, the authors of the new study created a model of HIV showing how outer "spike" proteins are distributed on the surface of the immature virus.

The new model put to the test a conclusion made by HIV researchers from super-resolution microscopic studies -- that the distribution of the spike proteins on the surface of the immature virus is random. But by using cellPACK to generate thousands of models, testing alternative hypotheses, the researchers found that the distribution was not random. "We demonstrated that their interpretation of the distribution did not match that hypothesis," said Olson.

A Team Effort

The cellPACK software began as the thesis project of a TSRI graduate student, Graham Johnson, now a QB3 faculty fellow at the University of California, San Francisco (UCSF) who continues to contribute to the project. Johnson had more 15 years' experience as a medical illustrator, and he wanted to create an easy way to visualize mesoscale structures. cellPACK is an expansion of Johnson's autoPACK software, which maps out the density of materials -- from concrete in a building to red blood cells in an artery.

The researchers see cellPACK as a community effort, and they have made the autoPACK and cellPACK software free and open source. Thousands of people have already downloaded the software from http://www.autopack.org.

"With the creation of cellPACK, Dr. Olson and his colleagues have addressed the challenge of integrating biological data from different sources and across multiple scales into virtual models that can simulate biologically relevant molecular interactions within a cell," said Veersamy Ravichandran, PhD, of the National Institutes of Health's National Institute of General Medical Sciences, which partially funded the research. "This user-friendly tool provides a new platform for data analysis and simulation in a collaborative manner between laboratories."

As new information comes in from the scientific community, researchers will tweak the software so it can model new shapes. "Making it open source makes it more powerful," said Olson. "The software right now is usable and very useful, but it's really a tool for the future."

Source: Scripps Research Institute

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Self-repairing software tackles malware

Eric Eide, University of Utah research assistant professor of computer science, stands in the computer science department's "Machine Room" where racks of web servers sit. It is on these computers that Eide, U computer science associate professor John Regehr, and their research team created and tested A3, a suite of computer applications that defeat malware and automatically repair the damage it causes. The project could help lead to better consumer software defenses.
Credit: Dan Hixson/University of Utah College of Engineering

University of Utah computer scientists have developed software that not only detects and eradicates never-before-seen viruses and other malware, but also automatically repairs damage caused by them. The software then prevents the invader from ever infecting the computer again.

A3 is a software suite that works with a virtual machine -- a virtual computer that emulates the operations of a computer without dedicated hardware. The A3 software is designed to watch over the virtual machine's operating system and applications, says Eric Eide, University of Utah research assistant professor of computer science leading the university's A3 team with U computer science associate professor John Regehr. A3 is designed to protect servers or similar business-grade computers that run on the Linux operating system. It also has been demonstrated to protect military applications.

The new software called A3, or Advanced Adaptive Applications, was co-developed by Massachusetts-based defense contractor, Raytheon BBN, and was funded by Clean-Slate Design of Resilient, Adaptive, Secure Hosts, a program of the Defense Advanced Research Projects Agency (DARPA). The four-year project was completed in late September.

There are no plans to adapt A3 for home computers or laptops, but Eide says this could be possible in the future.

"A3 technologies could find their way into consumer products someday, which would help consumer devices protect themselves against fast-spreading malware or internal corruption of software components. But we haven't tried those experiments yet," he says.

U computer scientists have created "stackable debuggers," multiple de-bugging applications that run on top of each other and look inside the virtual machine while it is running, constantly monitoring for any out-of-the-ordinary behavior in the computer.

Unlike a normal virus scanner on consumer PCs that compares a catalog of known viruses to something that has infected the computer, A3 can detect new, unknown viruses or malware automatically by sensing that something is occurring in the computer's operation that is not correct. It then can stop the virus, approximate a repair for the damaged software code, and then learn to never let that bug enter the machine again.

While the military has an interest in A3 to enhance cybersecurity for its mission-critical systems, A3 also potentially could be used in the consumer space, such as in web services like Amazon. If a virus or attack stops the service, A3 could repair it in minutes without having to take the servers down.

To test A3's effectiveness, the team from the U and Raytheon BBN used the infamous software bug called Shellshock for a demonstration to DARPA officials in Jacksonville, Florida, in September. A3 discovered the Shellshock attack on a Web server and repaired the damage in four minutes, Eide says. The team also tested A3 successfully on another half-dozen pieces of malware.

Shellshock was a software vulnerability in UNIX-based computers (which include many web servers and most Apple laptops and desktop computers) that would allow a hacker to take control of the computer. It was first discovered in late September. Within the first 24 hours of the disclosure of Shellshock, security researchers reported that more than 17,000 attacks 

by hackers had been made with the bug.

"It is a pretty big deal that a computer system could automatically, and in a short amount of time, find an acceptable fix to a widespread and important security vulnerability," Eide says. 

"It's pretty cool when you can pick the Bug of the Week and it works."

Now that the team's project into A3 is completed and proves their concept, Eide says the U team would like to build on the research and figure out a way to use A3 in cloud computing, a way of harnessing far-flung computer networks to deliver storage, software applications and servers to a local user via the Internet.

The A3 software is open source, meaning it is free for anyone to use, but Eide believes many of the A3 technologies could be incorporated into commercial products.

Other U members of the A3 team include research associate David M. Johnson, systems programmer Mike Hibler and former graduate student Prashanth Nayak.

Source: University of Utah

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Researchers develop a system to reconstruct grape clusters in 3D, assess quality

Antonio José Sánchez Salmerón, researcher at the Instituto ai2 of the UPV, explains that, today, grape classification is based on an inspection by a panel of experts, that award it score depending on a series of parameters that determine its quality. Credit: Image courtesy of Asociación RUVID

Researchers of the Universitat Politècnica de València (UPV) have developed software to help reconstruct grape clusters with three-dimensional computer vision techniques. The system helps to automatically assess different parameters that define the quality of the wine grape during harvest time.

During the work, the researchers of the UPV collaborated with the Research Centre of Vine and Wine related Sciences of the University of La Rioja, the Spanish National Research Council (CSIC, in Spanish) and the Government of La Rioja. The results of this work were released last September in the journal Food Control.

Antonio José Sánchez Salmerón, researcher at the Instituto ai2 of the UPV, explains that, today, grape classification is based on an inspection by a panel of experts, that award it score depending on a series of parameters that determine its quality. Moreover, different tests are performed in the laboratory in order to estimate the quantity of sugar, the pH, the total acidity and the phenolic quality.

"Among the factors that define the quality of a wine, one of the most important is the quality of the grape as the raw material, but this concept is difficult to assess, due to problems such as subjective parameters, the short period of time available in the field to do the analysis during harvest time, the lack of measuring instruments and their high price, as well as the mixing of good quality and bad quality grape in the trucks. The introduction of this 3D grape reconstruction system helps assess different quality parameters for a wine grape cluster avoiding these problems. One of these parameters is the average size of the grape, which is a very important factor as it establishes the ratio between the quantity of skin and pulp," explains the researcher.

"Increasing the objectivity and automating the grape quality monitoring tasks would be a technological breakthrough with regard to the traditional evaluation system of the grape, based on the knowledge of an expert, and it would have a great impact on the wine industry," adds Sánchez.

Source: Asociación RUVID

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