. Scientific Frontline

Tuesday, December 21, 2021

Ground-breaking sensors aboard NASA’s historic space telescope

After NASA launches the James Webb Space Telescope (JWST) on a historic mission this December, scientists anticipate their first glimpse of the most distant objects ever seen in the universe. Technology developed and tested at the University of Hawaiʻi Institute for Astronomy (IfA) and on Maunakea are behind JWST’s ability to gaze deeper into space than ever before.

Sixteen near-infrared (NIR) sensors known as HAWAII-2RGs are part of JWST’s science instruments, enabling it to capture near-infrared light from deep space, far surpassing the capability of NASA’s Hubble Space Telescope. These sensors are the culmination of years of research and development by IfA scientists and engineers. Early prototypes were developed and tested by UH astronomers Don Hall, Klaus Hodapp, and Doug Simons, along with IfA instrumentation engineer Shane Jacobson.

Monday, December 20, 2021

A superstar enzyme is ready for its close-up

This illustration features a cryo-EM “map” of the photosystem II complex. It is a 3D reconstruction, based on two-dimensional cryo-EM images, with different protein subunits of the complex colored individually. Source/Credit: Yale University

A Yale-led team of chemists has unveiled the blueprints for a key enzyme that may contain design principles for a new generation of synthetic solar fuel catalysts.

The research, led by Yale’s Gary Brudvig and Christopher Gisriel, uses cryo-electron microscopy on a microorganism called Synechocystis to get an extreme close-up picture of Photosystem II, the enzyme in photosynthesis that uses water as a solar fuel, enabling researchers to observe how the enzyme works.

The study, which appears in the journal Proceedings of the National Academy of Sciences, was co-authored by researchers from the University of California-Riverside, Boston College, and City University of New York.

Photosynthesis is the mechanism by which plants and certain microorganisms, like Synechocystis, use sunlight to synthesize food from carbon dioxide and water — and fill the atmosphere with oxygen as a byproduct. At the heart of photosynthesis is Photosystem II, an enzyme that oxides water molecules, taking away their electrons to use as fuel.

AI Innovation Incubator to advance artificial intelligence for applied science

Lawrence Livermore National Laboratory (LLNL) has established the AI Innovation Incubator (AI3), a collaborative hub aimed at uniting experts in artificial intelligence (AI) from LLNL, industry and academia to advance AI for large-scale scientific and commercial applications.

LLNL has entered into a new memoranda of understanding with Google, IBM and NVIDIA, with plans to use the incubator to facilitate discussions and form future collaborations around hardware, software, tools and utilities to accelerate AI for applied science. In addition, several existing projects will fall under the AI3 umbrella, including continued work with Hewlett Packard Enterprise (HPE) and Advanced Micro Devices Inc. (AMD) to demonstrate the power of AI and high performance computing (HPC) on the future exascale system El Capitan. This project focuses on innovative, AI-driven cognitive simulation and design optimization methods at unprecedented scales to devise novel approaches to inertial confinement fusion (ICF) experiments at the National Ignition Facility.

Other ongoing projects with AI accelerator/computing companies SambaNova Systems and Cerebras Systems and precision motion company Aerotech, Inc. will be further developed through AI3. More companies, universities and leaders in the AI space are encouraged to consider joining AI3, where early research areas are expected to include advanced material design, 3D printing, predictive biology, energy systems, “self-driving” lasers and fusion energy research.

PPPL unravels a puzzle to speed the development of fusion energy

Yichen Fu, center, lead author of the path-setting paper with co-authors Laura Xing Zhang and Hong Qin.
Photos of Fu and Qin by Elle Starkman/Office of Communications; collage by Kiran Sudarsanan.

Researchers at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory have developed an effective computational method to simulate the crazy-quilt movement of free electrons during experimental efforts to harness on Earth the fusion power that drives the sun and stars. The method cracks a complex equation that can enable improved control of the random and fast-moving moving electrons in the fuel for fusion energy.

Fusion produces enormous energy by combining light elements in the form of plasma — the hot, charged gas composed of free electrons and atomic nuclei, or ions, that makes up 99 percent of the visible universe. Scientists around the world are seeking to reproduce the fusion process to provide a safe, clean and abundant power to generate electricity.

Solving the equation

A key hurdle for researchers developing fusion on doughnut-shaped devices called tokamaks, which confine the plasma in magnetic fields, has been solving the equation that describes the motion of free-wheeling electrons as they collide and bounce around. Standard methods for simulating this motion, technically called pitch-angle scattering, have proven unsuccessful due to the complexity of the equation.

Measuring a quantum computer’s power just got faster and more accurate

Sandia National Laboratories has designed a faster, more accurate style of test for quantum computers, such as the one pictured here.
Photo by Bret Latter

What does a quantum computer have in common with a top draft pick in sports? Both have attracted lots of attention from talent scouts. Quantum computers, experimental machines that can perform some tasks faster than supercomputers, are constantly evaluated, much like young athletes, for their potential to someday become game-changing technology.

Now, scientist-scouts have their first tool to rank a prospective technology’s ability to run realistic tasks, revealing its true potential and limitations.

A new kind of benchmark test, designed at Sandia National Laboratories, predicts how likely it is that a quantum processor will run a specific program without errors.

The so-called mirror-circuit method, published today in Nature Physics, is faster and more accurate than conventional tests, helping scientists develop the technologies that are most likely to lead to the world’s first practical quantum computer, which could greatly accelerate research for medicine, chemistry, physics, agriculture and national security.

New Technique Visualizes Every Pigment Cell of Zebrafish in 3D

3D image of melanin in a zebrafish sample captured by micro-computed tomography.
Credit: Spencer R. Katz and Daniel J. Vanselow/Penn State College of Medicine

Researchers have developed a new technique that images every pigment cell of a whole zebrafish in 3D. The work, recently reported in the journal eLife, could help scientists understand the role of melanin in skin cancer.

Melanin is a natural pigment that gives color to the skin, hair, and eyes in humans and animals. Melanin also has implications in melanin-containing cancers, or melanomas, which are typically staged by the depth of penetration in skin.

But studying melanin directly with a conventional microscope is challenging because the pigment blocks light. So Keith C. Cheng, a distinguished professor of pathology, pharmacology and biochemistry, and molecular biology at Penn State College of Medicine, turned to X-ray imaging, which can pass through optically opaque matter like melanin.

To perform the imaging, Cheng partnered with Dula Parkinson, a staff scientist at Berkeley Lab’s Advanced Light Source (ALS), to image two sets of zebrafish samples – one with the normal pigmentation associated with the zebrafish’s characteristic black stripes, and another from a mutant zebrafish line with lighter stripes called golden. Over 15 years ago, Cheng and his lab discovered a key gene implicated in human skin color by studying golden zebrafish. That discovery highlighted the zebrafish’s utility as an animal model of human pigmentation in skin disorders such as albinism or melanoma skin cancer.

Omicron may be significantly better at evading vaccine-induced immunity, but less likely to cause severe disease

As the SARS-CoV-2 virus replicates and spreads, errors in its genetic code can lead to changes in the virus. On 26 Novembe
r 2021, the World Health Organization designated the variant B.1.1.529, first identified in South Africa, a variant of concern, named Omicron. The variant carries a large number of mutations, leading to concern that it will leave vaccines less effective at protecting against infection and illness.

Working in secure conditions, a team led by Professor Ravi Gupta at the Cambridge Institute of Therapeutic Immunology and Infectious Disease, University of Cambridge, created synthetic viruses – known as ‘pseudoviruses’ – that carried key mutations found in the Delta and Omicron strains. They used these to study the virus’s behavior.

The team, which included collaborators from Japan, including Dr Kei Sato of Tokyo University, has released its data ahead of peer review because of the urgent need to share information relating to the pandemic, and particularly the new Omicron variant.

Professor Gupta and colleagues tested the pseudoviruses against blood samples donated to the NIHR COVID-19 BioResource. The blood samples were from vaccinated individuals who had received two doses of either the AstraZeneca (ChAdOx-1) or Pfizer (BNT162b2) vaccines.

On average, Omicron required around a ten-fold increase in the concentration of serum antibody in order to neutralize the virus, compared to Delta. Of particular concern, antibodies from the majority of individuals who had received two doses of the AstraZeneca vaccine were unable to neutralize the virus. The data were confirmed in live virus experiments.

Researchers create artificial cell cortex, a system to study how cells divide

Animal cells are bound by a structure called a cell cortex—and this structure, researchers say, is a bit like a tent.

A tent is constructed of a shell with a zippered opening that controls what can go into and out of the tent. This shell is held up by a system of poles. Similarly, an animal cell cortex is composed of a cell membrane that controls what enters the cell.

The cortex also contains proteins, which help the cell keep its shape. One of these key proteins, called actin, is a polymer with a linear structure—like a tent pole. But unlike a tent, a cell’s cortical proteins aren’t stationary. They move along the cell membrane, freely assembling and moving apart over time, in a process called “cortical excitability.”

When these proteins begin to form wave patterns, it’s a sign that the cell is preparing to divide. But studying this process within the cell membrane is difficult. Now, University of Michigan researchers have developed an approach to study these wave patterns outside of a cell by developing a cell-free artificial cortex.

As a cell prepares to divide, its cell cortex proteins begin to move. First, its cortical proteins form an excitable wave, like spectators performing “the wave” at a football stadium. Second, cortical proteins organize into coherent oscillations, which behave like blinking holiday lights, associating and dissociating with the membrane at regular intervals.
Image credit: Jennifer Landino, A. Miller lab

Vaccine study flips traditional view of product scarcity driving demand

 The first doses of the Pfizer COVID-19 vaccine are administered
to Iowa State University health care employees on
Friday, December 18, 2020, at the Thielen Student Health Center.
Credit: Christopher Gannon/Iowa State University
Anyone who has taken an economics class probably remembers learning about scarcity. The concept of demand outpacing supply applies to the toilet paper shortage at the onset of the COVID-19 pandemic and helps explain how a spike in home-improvement projects last year contributed to skyrocketing lumber prices.

“Previous research on product scarcity shows people will desire something more when it isn’t as easily accessible. Since scarcity signals value, people are willing to make more of an effort or pay more to acquire it,” said Beatriz Pereira, assistant professor of marketing at Iowa State University.

Last year, as COVID-19 cases surged across the U.S., Pereira and a team of researchers knew the initial supply of vaccines would be limited. It seemed like the perfect opportunity to test whether vaccine scarcity drives demand. But the researchers’ newly published findings in Psychology & Marketing reveal the opposite: Participants were less interested in rolling up their sleeves when they thought vaccines were scarce. The researchers point to compassion for the vulnerable as a driving factor.

At the time of the first survey, COVID-19 vaccines were not yet available to the general public.

Over 300 college students were asked to imagine a scenario where manufacturers were working nonstop to produce enough vaccines for everyone, but due to limited supply, priority was being given to people considered high risk. Half of the participants were told that vaccine doses were limited in their area, while the other half were told there were plenty of doses available. The survey then asked both groups of participants the likelihood that they would book a vaccination appointment if their doctor said they could get a shot the following week.

“Interest in booking an appointment dropped by as much as 15% when the participants perceived vaccines as scarce,” said Pereira.

Gum disease increases risk of other illness such as mental health and heart conditions

A University of Birmingham-led study shows an increased risk of patients developing illnesses including mental ill-health and heart conditions if they have a GP-inputted medical history of periodontal (gum) disease.

Experts carried out a first of its kind study of the GP records of 64,379 patients who had a GP-inputted recorded history of periodontal disease, including gingivitis and periodontitis (the condition that occurs if gum disease is left untreated and can lead to tooth loss). Of these, 60,995 had gingivitis and 3,384 had periodontitis. These patients’ records were compared to those of 251,161 patients who had no record of periodontal disease. Across the cohorts, the average age was 44 years and 43% were male, while 30% were smokers. Body Mass Index (BMI), ethnicity and deprivation levels were also similar across the groups.

The researchers examined the data to establish how many of the patients with and without periodontal disease go on to develop cardiovascular disease (e.g., heart failure, stroke, vascular dementia), cardiometabolic disorders (e.g., high blood pressure, Type 2 diabetes), autoimmune conditions (e.g., arthritis, Type 1 diabetes, psoriasis), and mental ill-health (e.g., depression, anxiety and serious mental illness) over an average follow-up of around three years.

From the research, published today in journal BMJ Open, the team discovered that those patients with a recorded history of periodontal disease at the start of the study were more likely to go on and be diagnosed with one of these additional conditions over an average of three years, compared to those in the cohort without periodontal disease at the beginning of the research. The results of the study showed, in patients with a recorded history of periodontal disease at the start of the study, the increased risk of developing mental ill-health was 37%, while the risk of developing autoimmune disease was increased by 33%, and the risk of developing cardiovascular disease was raised by 18%, while the risk of having a cardiometabolic disorder was increased by 7% (with the increased risk much higher for Type 2 diabetes at 26%).

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