Feb. 26, 2021
The last thing people want to think about when this pandemic ends is the next one. A growing chorus of researchers says now is the time to get ready for what is sure to come.
Some have begun preliminary efforts to develop antivirals and monoclonal antibodies to prevent serious disease and vaccines that could stop a novel virus in its tracks.
Researchers at Lawrence Livermore National Laboratory, among others, are working to combat whatever might emerge next as humans expand contact with wildlife. Like weather forecasters, they use computer modeling and artificial intelligence to speed drug and vaccine development and predict the next novel virus and its most likely variants.
"Our goal is to be able to develop a new therapeutic in months rather than years," said Jim Brase, deputy associate director for Computing at the Lab. "We and other groups are beginning to show that's possible."
Following a terrorist bombing, can the bomb maker be identified by skin proteins left on the bomb components they handled?
To address this question, Lawrence Livermore researchers subjected notional bomb components handled by Lab volunteers to contained precision explosions. A small team of biology and explosives subject matter experts combined their knowledge and experience to successfully carry out a series of 26 confined detonations over a three-day period.
The identification of individuals through shed skin is an intense area of research for the Intelligence Advanced Research Projects Activity (IARPA) Proteos program, led by Kristen Jordan. The program is a culmination of years of IARPA support to the Lab’s Forensic Science Center (FSC) and is underpinned by capabilities developed under a Strategic Initiative Laboratory Directed Research & Development grant on protein-based identification.
The Proteos program focuses on human identification using shed skin cells associated with trace forensic samples. This investigation seeks to exploit the relationship between polymorphisms in the skin proteome, or genetically variable peptides (GVPs) and their underlying nonsynonymous single nucleotide polymorphisms (nsSNPs) to evaluate peptide mass fingerprinting as a reliable forensic analytic technique. In other words, mutations in our genomes manifest as small differences in our skin proteins. Using analytical chemistry, these differences in the peptide mass fingerprint can be used forensically to identify someone.
Lawrence Livermore National Laboratory scientists are leveraging their extensive experience studying the movement of airborne hazards to better understand the movement of virus-like particles including COVID-19 through the air and to identify effective countermeasures.
While the burden of airborne diseases is known to be large, its true scope is underappreciated. The new Lab research highlights well-established cases of airborne viruses, bacteria and fungal pathogens causing disease in plants, animals and humans over distance scales ranging from a few meters to continental.
According to Lab atmospheric scientist Michael Dillon, who leads the team's work: "By understanding the airborne disease transmission, we hope to offer science-based information that people can use to protect themselves and others."
The team is looking to study the physics of particle dispersion, analyzing how particles move around inside buildings and travel distances that may exceed six feet. They also are investigating key factors that may affect the movement of particles in a broad range of settings, including schools, offices, stores, restaurants and homes.
A near node local storage innovation called Rabbit factored heavily into Lawrence Livermore National Laboratory’s decision to select Cray’s proposal for its CORAL-2 machine, the Lab’s first exascale-class supercomputer, El Capitan. Details of this new storage technology were revealed by Livermore Computing CTO Bronis de Supinksi at the Riken-CCS International Symposium,\.
A two2-exaflops supercomputer slated for delivery at Livermore in late 2022 or early 2023, El Capitan is a partnership between the Department of Energy lab and HPE (which acquired Cray in 2019).
Under a non-recurring engineering (NRE) contract funded by Livermore, HPE is developing near node local storage technology that it calls its Rabbit program. De Supinski explained that NRE contracts allow procurers, such as Livermore, to improve elements of the overall system, and those innovations then flow to the broader HPC market through the partnering vendor’s portfolio.
At its core, Rabbit is a 4U solution for node local storage that encompasses 18 SSDs (16 and 2 spares) and one (AMD Epyc) storage processor. HPE refers to Rabbit as near node local storage that combined with its custom Rabbit software supports a wide range of use cases, including resolving network bursts, optimizing input, and even running analysis processes.
Outflows of matter are general features stemming from systems powered by compact objects such as black holes, active galactic nuclei, pulsar wind nebulae, accreting objects such as Young Stellar Objects (YSO) and mature stars such as our sun.
But the shape of those outflows, or astrophysical jets, vary depending on the magnetic field around them.
In new experiments, a Lawrence Livermore National Laboratory scientist and international collaborators found that outflow/magnetic field misalignment is a plausible key process regulating jet formation.
Using a high-powered laser at the École Polytechnique, the team created fast material outflows in a strong applied magnetic field as a surrogate for potential astrophysics conditions. The team specifically looked at the impact on jet formation of a misalignment between where the jet first forms and then the magnetic field.