Reassessing the Global Dataset of Wave Climate Projections

A snapshot of significant wave height (defined as the average of the highest 33% of waves) from a simulated realization of the future, submitted to COWCLIP 2.0. Energetic waves (yellow) originating from tropical cyclones can be seen in the North Pacific. Large waves in the southern hemisphere are due to extra-tropical storms, of large spatial extent, that continuously blast the Southern Ocean. Credit: Ben Timmermans

Wind-generated ocean waves — “wind waves” — can be major disruptors of coastal communities, marine ecosystems, offshore industries, and shipping, causing considerable environmental, geophysical, and socioeconomic impacts across the globe. Large waves during past winter storms, for example, stripped volumes of sand from Monterey, California beaches, attacked vulnerable marine terraces, and ultimately caused steep cliffs near Big Sur to crash into the sea. And around the world, these kinds of extreme weather events are becoming increasingly frequent and intense.

So it is critical to understand how global and regional wave conditions may evolve under climate change. This knowledge can then be integrated into comprehensive assessments of future coastal hazards and vulnerabilities to guide climate adaptation strategies.

Waves are generated from wind stress on the ocean surface — stronger storms generate larger waves. However, factors like storm size, intensity, translation speed, and structure combine to create different wave conditions. Modeling how atmospheric wind fields can lead to different spatial patterns of surface waves is critical for forecasts on weather time scales, but predicting how climate change alters wave conditions is much more complicated. Addressing this problem requires high performance computing.

Researchers at Lawrence Berkeley National Laboratory (Berkeley Lab) are tackling this challenge by generating and analyzing ocean wave climate projections using supercomputing resources at the National Energy Research Scientific Computing Center (NERSC), a Department of Energy user facility located at Berkeley Lab. They are also helping compile the results of international wave climate studies, creating a global ensemble dataset for widespread use by stakeholders, governments, and the research community. In the past year, two community-wide papers covering this research — including work done at Berkeley Lab — were published, one in Nature Climate Change and, more recently, in Scientific Data, also a Nature publication.

Modeling Wind-Wave Climate

Scientists use numerical general circulation models (GCMs) to simulate the dynamics and thermodynamics of the Earth’s atmosphere. Increasingly, they employ coupled GCMs to simulate the atmosphere and ocean simultaneously — and even include other components such as land hydrology — allowing feedback between the various systems. These models enable scientists to investigate the properties of the Earth’s weather and climate, both in the past and possible futures.

Only the most recent coupled atmosphere-ocean climate models include in-line wind-driven wave calculations. In addition, many climate models generate data at fairly coarse resolution, which prevents the identification of more intense storms such as tropical cyclones. The research published in Climate Change and Scientific Data compared multiple off-line wind-driven wave calculations.

Among the co-authors on these papers is Ben Timmermans, a researcher at the National Oceanography Centre in the United Kingdom and a former post-doctoral fellow in Berkeley Lab’s Climate and Ecosystems Science Division. As a postdoc, Timmermans worked with Michael Wehner, a senior scientist in Berkeley Lab’s Computational Research Division, to develop a high-resolution climate projection of average wave conditions across the globe. This work relied on simulations that Wehner had previously generated based on atmospheric data, which were collected in three-hour increments with a spatial resolution of either 25-kilometer squared or 100-kilometer squared. Simulating a 25-kilometer dataset took 64 times more computational resources than a 100-kilometer one.

“These atmospheric model calculations would have been impossible without NERSC’s computers, scratch disk, and high performance storage system,” said Wehner. “We used several hundred million hours and about 7,000 processors on Hopper and Cori for the project.”

However, Wehner’s original atmospheric simulations did not model how the atmosphere interacts with wind waves. So Timmermans extended this work to also model and analyze global wave conditions, which represented both present and possible future wave climate. NERSC again played a critical role, supplying three million core hours that ran concurrently on 20 nodes of Edison. Using the high-resolution data and NERSC computing power, the Berkeley team was able to identify tropical storms and extreme waves that the lower-resolution data lacked.

“The abundance of resources at NERSC allowed me to push the wave model almost to its limits in terms of parallel computing capability,” Timmermans said. 

Assembling Wave Climate Projections

This Berkeley Lab project is part of a new generation of global wind-wave studies completed by several international modeling groups. These individual studies, however, use various statistical approaches, dynamical wind-wave models, and data structures, making comparisons between the analyses difficult. In addition, single studies alone cannot be used to quantify total uncertainty given the range and diversity of available wind-wave modeling methods. Without a broader research effort, it remains unclear why the standalone studies sometimes differ in their projected changes in wind-wave characteristics across the world’s oceans.

The Coordinated Ocean Wave Climate Project (COWCLIP) is trying to overcome this problem by creating a consistent multivariate dataset of global wave climate projections for widespread use. Berkeley Lab is one of ten contributing institutions to COWCLIP phase 2, as described in the Scientific Data paper; all ten contributing institutions validated their global wave projection datasets with respect to observations, an important part of the production process.

For example, Timmermans’ validation involved a comparison of his projections of wind speed and wave height distributions against observations from fixed-position oceanic data buoys maintained by the National Oceanic and Atmospheric Administration. However, the COWCLIP2 team also conducted validation on the entire ensemble of datasets, comparing against 26 years of global satellite measurements of significant wave height on a global and regional scale.

“COWCLIP is a coordinated community effort to gather and explore output from state-of-the-art simulations of ocean wave climate, identifying and quantifying the key sources of uncertainty,” Timmermans said. “This new dataset will support future broad-scale coastal hazard and vulnerability assessments and climate adaptation studies in many offshore and coastal engineering applications.”

Berkeley Lab’s high-resolution climate model output used to drive the wave model is suitable for many other types of analyses and is freely available at https://portal.nersc.gov/c20c/.

This is a reposting of my news feature, courtesy of Lawrence Berkeley National Laboratory. 

Behind the scenes with a co-director of The Pride Study

In our “Behind the Scenes” series, Stanford Medicine physicians, nurses, researchers and staff members share a glimpse of their daily lives.

For Stanford obstetrician/gynecologist Juno Obedin-Maliver, MD, MPH, there is no typical day. Part of what she loves about her job is that every day is different.

Obedin-Maliver practices the full spectrum of gynecology, including outpatient, inpatient, operative and emergency services. She also co-directs The PRIDE Study, which is a national prospective, longitudinal cohort of sexual and/or gender minority people — including but not limited to lesbian, gay, bisexual, transgender and queer people.

I was excited to speak with her about how she fits all of this into her day — both before and during the COVID-19 pandemic.

Pre-COVID morning routine

I get up between 5 a.m. and 6:15 a.m. I usually make some tea and have breakfast before getting my three-year-old son up, dressed and fed. Then, either my partner or I take him to school. Next, I head down to Stanford from San Francisco where I live.

Organizing the workweek

I see patients about 30% of the time, and the rest of the time I do research. Days that I don’t see patients are a mix of research writing and meetings — with overnight calls or surgery kind of sprinkled in here and there.

Part of my research team is at Stanford, part at the University of California San Francisco and part at our office in the Oakland City Center. So, I have meetings with folks all over the Bay, and also all over the country, because we have collaborators and stakeholders across the United States.

The PRIDE Study

The main focus of  The PRIDE Study is understanding the relationship between being a sexual and/or gender minority person and a person’s health. And we think about health broadly: physical health, mental health, social health and wellbeing. We want to understand in more detail the well-documented health disparities among sexual and gender minority people, but also their health resiliency. We’ve enrolled about 18,000 people in the study.

I’m also working to build an LGBTQ+ program at Stanford, which will include clinical care, research and education.

Juno Obedin-Maliver, MD, MPH, and Mitchell Lunn, MD, co-direct The PRIDE Study, a national prospective, longitudinal cohort of sexual and/or gender minority people.
Most productive time of the day

My most productive time is in the morning at home. I usually triage my email — deleting spam, putting actionable items on my to-do list and putting anything that requires significant time on my calendar. And if I get up at 5 am, I can get an hour of uninterrupted writing in before my son wakes up, which is awesome.

Evening ritual

I get home between 6 p.m. and 7:30 p.m., then I just hang out with my son and my partner. We give him dinner and a bath, read him books and get him to sleep. And then we have our own dinner. Sometimes we just hang out until bedtime. And sometimes, unfortunately, we get back on the computer to work.

In the evening, I like to meditate, if only for 10 minutes. I remember what I’m grateful for. And I generally read a novel before I go to bed. Right now, I’m reading a book called The Hakawati by Rabih Alameddine. It’s pretty great. I try to get to sleep by 10 or 10:30 p.m.

My day during the pandemic

I still see patients one day a week, and it’s a mix of in-person and video visits in the clinic. I also work some shifts on labor and delivery.

In terms of research, my team is still rocking and rolling, despite the challenges of COVID-19 and systemic violence around the country. I’m very luck to work with an inspiring team dedicated to equity and justice.

Professionally, it’s been a productive time, and we’ve published a number of papers. We’ve also launched a survey about the impact of COVID-19 for LGBTQ+ people, and a related survey about respiratory symptoms, and have had a few thousand responses already. The pandemic seems to be exacerbating systems of inequality, and that’s certainly true for LGBTQ+ — and even more so for LGBTQ+ people of color and those who are economically disadvantaged. As we enter Pride Month, we are also about to launch our fourth annual questionnaire on June 8, and celebrate having over 18,000 participants.

Having a 3-year-old at home and splitting his care throughout the day with my partner has been a big challenge though. Our kiddo misses his friends and school, as we all do. In many ways, we’re closer than ever, and have had a lot of opportunities to do crafts and bake — and we’re growing food on our porch (tomatoes, lettuce, peppers, chard and strawberries!).

On the other hand, trying to still fit in a full work day is a struggle; it means working before he is up and long after he goes to sleep, and unfortunately more screen time for him than ever before. That being said, we’re so lucky to be healthy, have access to food and have jobs that allow us to work at least some of the time from home while still being of service.

Photos by Steve Fisch

This is a reposting of my Scope story, courtesy of Stanford School of Medicine.

Physicians re-evaluate use of lead aprons during X-rays

When you get routine X-rays of your teeth at the dentist’s office or a chest X-ray to determine if you have pneumonia, you expect the technologist to drape your pelvis in a heavy radioprotective apron. But that may not happen the next time you get X-rays.

There is growing evidence that shielding reproductive organs has negligible benefit; and because a protective cover can move out of place, using it can result in an increased radiation dose to the patient or impaired quality of diagnostic images.

Shielding testes and ovaries during X-ray imaging has been standard practice since the 1950s due to a fear of hereditary risks — namely, that the radiation would mutate germ cells and these mutations would be passed on to future generations. This concern was prompted by the genetic effects observed in studies of irradiated fruit flies. However, such hereditary effects have not been observed in humans.

“We now understand that the radiosensitivity of ovaries and testes is extremely low. In fact, they are some of the lower radiation-sensitive organs — much lower than the colon, stomach, bone marrow and breast tissue,” said  Donald Frush, MD, a professor of pediatric radiology at Lucile Packard Children’s Hospital Stanford.

In addition, he explained, technology improvements have dramatically reduced the radiation dose that a patient receives during standard X-ray films, computerized tomography scans and other radiographic procedures. For example, a review paper finds that the radiation dose to ovaries and testes dropped by 96% from 1959 to 2012 for equivalent X-ray exams of the pelvis without shielding.

But even if the radioprotective shielding may have minimal — or no — benefit, why not use it just to be safe?

The main problem is that so-called lead aprons — which aren’t made of lead anymore — are difficult to position accurately, Frush said. Even following shielding guidelines, the position of the ovaries is so variable that they may not be completely covered.  Also,  the protective shield can obscure the target anatomy. This forces doctors to live with poor-quality diagnostic information or to repeat the X-ray scan, thus increasing the radiation dose given to the patient, he said.

Positioning radioprotective aprons is particularly troublesome for small children.

“Kids kick their legs up and the shield moves while the technologists are stepping out of the room to take the exposure and can’t see them. So the X-rays have to be retaken, which means additional dose to the kids,” Frush said.

Another issue derives from something called automatic exposure control, a technology that optimizes image quality by adjusting the X-ray machine’s radiation output based on what is in the imaging field. Overall, automatic exposure control greatly improves the quality of the X-ray images and enables a lower dose to be used.  

However, if positioning errors cause the radioprotective apron to enter the imaging field, the radiographic system increases the magnitude and length of its output, in order to penetrate the shield.

“Automatic exposure control is a great tool, but it needs to be used appropriately. It’s not recommended for small children, particularly in combination with radioprotective shielding,”  said Frush.

With these concerns in mind, many technologists, medical physicists and radiologists are now recommending to discontinue the routine practice of shielding reproductive organs during X-ray imaging. However, they support giving technologists discretion to provide shielding in certain circumstances, such as on parental request. This position is supported by several groups, including the American Association of Physicists in MedicineNational Council on Radiation Protection and Measurements and American College of Radiology.

These new guidelines are also supported by the Image Gently Alliance, a coalition of heath care organizations dedicated to promoting safe pediatric imaging, which is chaired by Frush. And they are being adopted by Stanford hospitals.

“Lucile Packard Children’s revised policy on gonadal shielding has been formalized by the department,” he said. “There is still some work to do with education, including training providers and medical students to have a dialogue with patients and caregivers. But so far, pushback by patients has been much less than expected.”

Looking beyond the issue of shielding, Frush advised parents to be open to lifesaving medical imaging for their children, while also advocating for its best use. He said:

“Ask the doctor who is referring the test: Is it the right study? Is it the right thing to do now, or can it wait? Ask the imaging facility:  Are you taking into account the age and size of my child to keep the radiation dose reasonable?”

Photo by Shutterstock / pang-oasis

This is a reposting of my Scope story, courtesy of Stanford School of Medicine.

Physicists curate list of COVID-19 projects to join

As we continue to deal with the global COVID-19 pandemic, biomedical researchers are racing to understand the virus that causes the disease, to evaluate its spread, and to develop tests, treatments and vaccines.

Physicists are volunteering to assist in these efforts, using their skills in data analytics, machine learning, simulation, software, computing, hardware development and project management. And an organization called Science Responds is helping to match them with projects that need their support.

As Savannah Thais, a postdoctoral researcher in high-energy physics and a co-founder of Science Responds, reported at the April meeting of the American Physical Society, physicists are assisting with a variety of types of projects, divided into the following categories:

Epidemiology

Epidemiology is the branch of medical science that studies public health problems and events in order to understand what causes them, how they are distributed among populations and possible ways to control them. Epidemiologists investigate diverse problems including pollution, foodborne illnesses, natural disasters and infectious diseases such as COVID-19.

Science Responds is connecting physicists with epidemiological projects that are working to model how the virus that causes COVID-19 might spread. Physicists hope to help address a major problem that the experts making these models face: incorporating data from a multitude of dissimilar sources.

Thais says physicists have the background and experience needed to provide epidemiologists this kind of support.

“We don’t think physicists should be building their own epidemiological models from scratch, because they don’t have the domain expertise of an epidemiologist or biologist about infectious diseases,” she says. But “physicists can be most effective by providing their computing and statistics skills to interdisciplinary research.”

One epidemiology project Science Responds encourages volunteers to join is HealthMap, which displays data about COVID-19 cases across the globe over time via an openly accessible website and mobile app. HealthMap integrates and filters data from diverse, publicly available sources—including online news aggregators and reports from governments and agencies such as the World Health Organization—and then creates intuitive visualizations of the state of the outbreak by location.

Other modeling projects use analyses of the genomic features of previously studied viruses to help estimate unreported COVID-19 cases; integrate health and hospital resource data to inform localized risk predictions; and incorporate information from previous animal and human outbreaks to improve model accuracy.

Diagnosis

An important part of dealing with an epidemic is determining who has the disease, but shortages of testing supplies have made diagnosis a challenge. Science Responds promotes projects that are trying to address this gap in different ways.

Some projects use artificial intelligence to process visual or audio data. The project CAD4COVID, for example, builds off an existing technology that has been highly successful in diagnosing tuberculosis through the analysis of chest X-rays. The project COVID Voice Detector, on the other hand, is collecting audio recordings to develop an AI that can recognize signs of COVID-19 infection in a patient’s voice.

Other projects are building tools to predict who is likely to experience the most severe effects of COVID-19. These machine-learning-based efforts identify indicators such as markers that appear in blood tests or specific features from lung biopsies to predict the likelihood of long-term hospitalization or death.

Treatments and cures

The race to develop COVID-19 vaccines and treatments begins with understanding the physical structure of the virus. On this front, Science Responds collaborators are providing key support for an effort called Folding@Home, which uses computer simulations to map out the proteins the SARS-CoV-2 virus uses to reproduce and suppress a patient’s immune system. Physicists are helping to develop the protein-folding simulations, but they are also playing a pivotal role in looking for help from anyone with a computer that Folding@Home can use remotely to run folding simulations.

In addition, physicists are helping process the massive amount of data related to the SARS-CoV-2 genome. They’re hoping to identify molecules that are important to the growth and spread of the virus and to understand its mutations.

Science Responds collaborators are also aiding efforts to use machine learning to identify drugs that could be repurposed to treat COVID-19. For example, they are using natural-language-processing algorithms to comb through a massive database of scholarly articles, called CORD-19, for relevant ideas. Other projects are using deep-learning-based models with existing data to predict how commercially available drugs will interact with the virus.

Supporting hospitals and healthcare systems

Science Responds participants are volunteering on projects to support frontline workers who are providing medical care to COVID-19 patients. These efforts include developing models to help predict hospital overload and to allow for the sharing of resources such as mechanical ventilators and personal protective equipment.

One example is the CHIME project, which gathers information on hospital resources and predicts when the needs of patients will exceed an institution’s capacity. CHIME has already been deployed in several hospitals, including the University of Pennsylvania Health System.

Another project in this area is COVID Care Map, which is using open-source data to map existing supplies of hospital beds, ventilators and other resources needed to care for COVID-19 patients such as available staff.

Other projects highlighted by Science Responds are aimed at improving telehealth. Enhanced at-home care could reduce the spread of COVID-19 by eliminating unnecessary hospital visits and improving access to care for rural areas.

Researchers are helping to develop AI-based chatbots that can be used to assess possible infections, educate patients and call on human providers when necessary. Other projects are working to combine in-home sensors and cameras with AI-assisted technologies to remotely monitor the health of vulnerable populations.

Socio-economic response

Finally, Science Responds volunteers are also working to address what they call “second-order effects,” not directly related to healthcare.

Some projects deal with infodemiology, research into what we can learn from user-contributed, health-related content on the internet. Researchers are analyzing millions of real-time tweets related to COVID-19 to answer questions like: How are people reacting to the outbreak? How is Twitter being used to pass on vital information? How is Twitter being abused to spread false information, panic and hate?

Physicists with data-analysis and data-engineering expertise can volunteer for projects aimed at bringing attention to at-risk populations. Thais leads a project that is developing a COVID-19 Vulnerability Index, an AI-based predictive model used to identify communities at high risk of socio-economic and health impacts associated with the spread of COVID-19.

The index looks at a wide range of measures, such as whether community members have access to home Wi-Fi, whether they are affected by non-COVID health issues such as diabetes, and whether healthcare resources are available to them.

Are you a physicist looking to volunteer? Thais recommends checking out the Science Responds website, which lists projects organized by their required skills, highlights available data sources, computing resources and funding opportunities, and provides instructions for getting connected.

Illustration by Sandbox Studio, Chicago with Ana Kova

This is a reposting of my news feature, courtesy of Symmetry magazine.

 

Nerve interface provides intuitive and precise control of prosthetic hand

Current state-of-the-art designs for a multifunctional prosthetic hand are restricted in functionality by the signals used to control it. A promising source for prosthetic motor control is the peripheral nerves that run from the spinal column down the arm, since they still function after an upper limb amputation. But building a direct interface to the peripheral nervous system is challenging, because these nerves and their electrical signals are incredibly small. Current interface techniques are hindered by signal amplitude and stability issues, so they provide amputees with only a limited number of independent movements. 

Now, researchers from the University of Michigan have developed a novel regenerative peripheral nerve interface (RPNI) that relies on tiny muscle grafts to amplify the peripheral nerve signals, which are then translated into motor control signals for the prosthesis using standard machine learning algorithms. The research team has demonstrated real-time, intuitive, finger-level control of a robotic hand for amputees, as reported in a recent issue of Science Translational Medicine.

“We take a small graft from one of the patient’s quadricep muscles, or from the amputated limb if they are doing the amputation right then, and wrap just the right amount of muscle around the nerve. The nerve then regrows into the muscle to form new neuromuscular junctions,” says Cindy Chestek, an associate professor of biomedical engineering at the University of Michigan and a senior author on the study. “This creates multiple innervated muscle fibers that are controlled by the small nerve and that all fire at the same time to create a much larger electrical signal—10 or 100 times bigger than you would record from inside or around a nerve. And we do this for several of the nerves in the arm.”

This surgical technique was initially developed by co-researcher Paul Cederna, a plastic surgeon at the University of Michigan, to treat phantom limb pain caused by neuromas. A neuroma is a painful growth of nerve cells that forms at the site of the amputation injury. Over 200 patients have undergone the surgery to treat neuroma pain.

“The impetus for these surgeries was to give nerve fibers a target, or a muscle, to latch on to so neuromas didn’t develop,” says Gregory Clark, an associate professor in biomedical engineering from the University of Utah who was not involved in the study. “Paul Cederna was insightful enough to realize these reinnervated mini-muscles also provided a wonderful opportunity to serve as signal sources for dexterous, intuitive control. That means there’s a ready population that could benefit from this approach.”

The Michigan team validated their technique with studies involving four participants with upper extremity amputations who had previously undergone RPNI surgery to treat neuroma pain. Each participant had a total of 3 to 9 muscle grafts implanted on nerves. Initially, the researchers measured the signals from these RPNIs using fine-wire, nickel-alloy electrodes, which were inserted through the skin into the grafts using ultrasound guidance. They measured high-amplitude electromyography signals, representing the electrical activity of the mini-muscles, when the participants imagined they were moving the fingers of their phantom hand. The ultrasound images showed the participants’ thoughts caused the associated specific mini-muscles to contract. These proof-of-concept measurements, however, were limited by the discomfort and movement of the percutaneous electrodes that pierced the skin.

Next, the team surgically implanted permanent electrodes into the RPNIs of two of the participants. They used a type of electrode commonly used for battery-powered diaphragm pacing systems, which electrically stimulate the diaphragm muscles and nerves of patients with chronic respiratory insufficiency to help regulate their breathing. These implanted electrodes allowed the researchers to measure even larger electrical signals—week after week from the same participant—by just plugging into the connector. After taking 5 to 15 minutes of calibration data, the electrical signals were translated into movement intent using machine learning algorithms and then passed on to a prosthetic hand. Both subjects were able to intuitively complete tasks like stacking physical blocks without any training—it worked on the first try just by thinking about it, says Chestek. Another key result is that the algorithm kept working even 300 days later.

“The ability to use the determined relationship between electrical activity and intended movement for a very long period of time has important practical consequences for the user of a prosthesis, because the last thing they want is to rely on a hand that is not reliable,” Clark says.

Although this clinical trial is ongoing, the Michigan team is now investigating how to replace the connector and computer card with an implantable device that communicates wirelessly, so patients can walk around in the real world. The researchers are also working to incorporate sensory feedback through the regenerative peripheral nerve interface. Their ultimate goal is for patients to feel like their prosthetic hand is alive, taking over the space in the brain where their natural hand used to be.

“People are excited because this is a novel approach that will provide high quality, intuitive, and very specific signals that can be used in a very straightforward, natural way to provide high degrees of dexterous control that are also very stable and last a long time,” Clark says.

Read the article in Science Translational Medicine.

Illustration of multiple regenerative peripheral nerve interfaces (RPNIs) created for each available nerve of an amputee. Fine-wire electrodes were embedded into his RPNI muscles during the readout session. Credit: Philip Vu/University of Michigan; Science Translational Medicine doi: 10.1126/scitranslmed.aay2857

This is a reposting of my news brief, courtesy of Materials Research Society.

Why do viruses like the coronavirus sometimes steal our sense of smell?

When you catch a severe cold, your nose stuffs up, you can’t smell anything and food tastes funny. Fortunately, most people regain their sense of smell once the cold runs its course. But for others, the complete (anosmia) or partial (hyposmia) loss of the sense of smell is permanent.

I spoke with Zara Patel, MD, a Stanford associate professor of otolaryngology, head and neck surgery, and director of endoscopic skull base surgery, to learn more about her research on olfactory disorders. In particular, we discussed her recent study on the possible association between post-viral olfactory loss and other cranial neuropathies, which are disorders that impair your nerves and ultimately your ability to feel or move. She also described how her work pertains to the COVID-19 pandemic.  

How does a virus impair someone’s sense of smell?

A variety of viruses can attack the cranial nerves related to smell or the mucosal tissue that surrounds those nerves. Cranial nerves control things in our head and neck — such as the nerves that allow us to speak by using our vocal cords, control our facial motion, hear and smell.

For example, COVID-19 is just one type of disease caused by a coronavirus. There are many other types of coronaviruses that cause colds and upper respiratory illnesses, as well as rhinoviruses and influenza viruses. Any of these viruses are known to cause inflammation, either directly around the nerve in the nasal lining or within the nerve itself. When the nerve is either surrounded by inflammatory molecules or has a lot of inflammation within the nerve cell body, it cannot function correctly — and that is what causes the loss or dysfunction of smell. And it can happen to anyone: young and old, healthy and sick.

How did your study investigate olfactory loss?

In my practice, I see patients who have smell dysfunction. But I’m also a sinus and skull base surgeon, so I have a whole host of other patients with sinus problems and skull-based tumors who don’t have an olfactory loss. So we did a case-control study to compare the incidence of cranial neuropathies — conditions in which nerves in the brain or brain stem are damaged — in two patient groups. Ninety-one patients had post-viral olfactory loss and 100 were controls; and they were matched as closely as possible for age and gender.

We also looked at family history of neurologic diseases — such as Alzheimer’s disease, Parkinson’s disease and stroke.

What did you find?

Patients with post-viral olfactory loss had six-times higher odds of having other cranial neuropathies than the control group — with an incidence rate of other cranial nerve deficits of 11% and 2%, respectively. Family history of neurologic diseases was associated with more than two-fold greater odds of having a cranial nerve deficit. Although we had a small sample size, the striking difference between the groups implies that it is worthwhile to research this with a larger population.

Our findings suggest that patients experiencing these pathologies may have inherent vulnerabilities to neural damage or decreased ability of nerve recovery — something beyond known risk factors like age, body mass index, co-morbidities and the duration of the loss before intervention. For example, there may be a genetic predisposition, but that is just an untested theory at this point.

How does this work pertain to COVID-19?

Smell loss can be one of the earliest signs of a COVID-19 infection. It can sometimes be the only sign. Or it can present after other symptoms. Although it may not affect every patient with COVID-19, loss of smell and taste is definitely associated with the disease. In some countries, including France, they’ve used this as a triage mechanism. People need to know that these symptoms can be related to the COVID-19 disease process so they aren’t going about their lives like normal and spreading the virus.

The pandemic also might impact how we treat patients with olfactory dysfunction in general. When someone has a viral-induced inflammation of the nerve, we sometimes treat it with steroids to decrease the inflammation. But treating COVID-19 patients with steroids might be a bad idea because of its effect on the inflammatory processes going on in their heart and lungs.

What advice do you have for people who have an impaired sense of smell?  

First, if you lose your sense of smell and it isn’t coming back after all the other symptoms have gone away, seek care as soon as possible. If you wait too long, there is much less that we can do to help you. Interventions, including olfactory training and medications, are more effective when you are treated early.

Second, if you lose your sense of smell or taste during this pandemic and you don’t have any other symptoms, contact your doctor. The doctor can decide whether you need to be tested for COVID-19 or whether you need to self-isolate to avoid being a vector of the virus in your family or community.

Image by carles

This is a reposting of my Scope story, courtesy of Stanford School of Medicine.

Harnessing AMReX for Wind Turbine Simulations

ECP ExaWind Project Taps Bereley Lab’s AMReX to Help Model Next-Generation Wind Farms

Driving along Highway 580 over the Altamont Pass in Northern California, you can’t help but marvel at the 4,000+ wind turbines slowly spinning on the summer-golden hillsides. Home to one of the earliest wind farms in the United States, Altamont Pass today remains one of the largest concentrations of wind turbines in the world. It is also a symbol of the future of clean energy.

Before utility grids can achieve wide-scale deployment of wind energy, however, they need more efficient wind plants. This requires advancing our fundamental understanding of the flow physics governing wind-plant performance.

ExaWind, a U.S. Department of Energy (DOE) Exascale Computing Project, is tackling this challenge by developing new simulation capabilities to more accurately predict the complex flow physics of wind farms. The project entails a collaboration between the National Renewable Energy Laboratory (NREL), Sandia National Laboratories, Oak Ridge National Laboratory, the University of Texas at Austin, Parallel Geometric Algorithms, and — as of a few months ago — Lawrence Berkeley National Laboratory (Berkeley Lab).

“Our ExaWind challenge problem is to simulate the air flow of nine wind turbines arranged as a three-by-three array inside a space five kilometers by five kilometers on the ground and a kilometer high,” said Shreyas Ananthan, a research software engineer at NREL and lead technical expert on the project. “And we need to run about a hundred seconds of real-time simulation.” 

By developing this virtual test bed, the researchers hope to revolutionize the design, operational control, and siting of wind plants, plus facilitate reliable grid integration. And this requires a combination of advanced supercomputers and unique simulation codes.

Unstructured + Structured Calculations

The principle behind a wind turbine is simple: energy in the wind turns the turbine blades, which causes an internal gearbox to rotate and spin a generator that produces electricity. But simulating this is complicated. The flexible turbine blades rotate, bend, and twist as the wind shifts direction and speed. The yaw and pitch of these blades are controlled in real time to extract as much energy as possible from a wind event. The air flow also entails complex dynamics  — such as influences from the ground terrain, formation of a turbulent wakefield downstream from the blades, and turbine-turbine interactions.

To improve on current simulations, scientists need more computing power and higher resolution models that better capture the crucial dynamics. The ExaWind team is developing a predictive, physics-based, and high-resolution computational model — progressively building from petascale simulations of a single turbine toward exascale simulations of a nine-turbine array in complex terrain.

A Nalu-Wind solution to the differential equations of motion for a wind turbine operating in uniform air flow (moving from left to right). Two of the three wind turbine’s blades are pictures (think blue rectangles on left). The slice in the background represents the contours of the whirling air’s motion, showing the vertical direction of the wake structure behind the turbine blades (red indicates swirl in counterclockwise direction and blue clockwise direction around blade tip).

“We want to know things like the air velocity and air temperature across a big three-dimensional space,” said Ann Almgren, who leads the Center for Computational Sciences and Engineering in Berkeley Lab’s Computational Research Division. “But we care most about what’s happening right at the turbines where things are changing quickly. We want to focus our resources near these turbines, without neglecting what’s going on in the larger space.”

To achieve the desired accuracy, the researchers are solving fluid dynamics equations near the turbines using a computational code called Nalu-Wind, a fully unstructured code that gives users the flexibility to more accurately describe the complex geometries near the turbines, Ananthan explained.

But this flexibility comes at a price. Unstructured mesh calculations have to store information not just about the location of all the mesh points but also about which points are connected to which. Structured meshes, meanwhile, are “logically rectangular,” which makes a lot of operations much simpler and faster.

“Originally, ExaWind planned to use Nalu-Wind everywhere, but coupling Nalu-Wind with a structured grid code may offer a much faster time-to-solution,” Almgren said.

Enter AMReX

Luckily, Ananthan knew about Berkeley Lab’s AMReX, a C++ software framework that supports block-structured adaptive-mesh algorithms for solving systems of partial differential equations. AMReX supports simulations on a structured mesh hierarchy; at each level the mesh is made up of regular boxes, but the different levels have different spatial resolution.

Ananthan explained they actually want the best of both worlds: unstructured mesh near the turbines and structured mesh elsewhere in the domain. The unstructured mesh and structured mesh have to communicate with each other, so the ExaWind team validated an overset mesh approach with an unstructured mesh near the turbines and a background structured mesh. That’s when they reached out to Almgren to collaborate.

“AMReX allows you to zoom in to get fine resolution in the regions you care about but have coarse resolution everywhere else,” Almgren said. The plan is for ExaWind to use an AMReX-based code (AMR-Wind) to resolve the entire domain except right around the turbines, where the researchers will use Nalu-Wind. AMR-Wind will generate finer and finer cells as they get closer to the turbines, basically matching the Nalu-Wind resolution where the codes meet. Nalu-Wind and AMR-Wind will talk to each other using a coupling code called TIOGA.

Even with this strategy, the team needs high performance computing. Ananthan’s initial performance studies were conducted on up to 1,024 Cori Haswell nodes at Berkeley Lab’s National Energy Research Scientific Computing Center (NERSC) and 49,152 Mira nodes at the Argonne Leadership Computing Facility.

“For the last three years, we’ve been using NERSC’s Cori heavily, as well as NREL’s Peregrine and Eagle,” said Ananthan. Moving forward, they’ll also be using the Summit system at the Oak Ridge Leadership Computing Facility and, ultimately, the Aurora and Frontier exascale supercomputers — all of which feature different types of GPUs: NVIDIA on Summit (and NERSC’s next-generation Perlmutter system), Intel on Aurora, and AMD on Frontier. 

Although Berkeley Lab just started partnering with the ExaWind team this past fall, the collaboration has already made a lot of progress. “Right now we’re still doing proof-of-concept testing for coupling the AMR-Wind and Nalu-Wind codes, but we expect to have the coupled software running on the full domain by the end of FY20,” said Almgren.

NERSC is a DOE Office of Science user facility.

Top figure: Some of the 4000+ wind turbines in Northern California’s Altamont Pass wind farm. Credit: David Laporte

This is a reposting of my news feature, courtesy of Berkeley Lab.

Hydrogel elicits switchable, reversible, and controllable self-trapping light beams

The next generation of optoelectronic and photonic systems — with wide-ranging potential applications in image transmission, light-guiding-light signal processing, logic gates for computing, and medicine — may be realized through the invention of circuitry-free, rapidly reconfigurable systems powered by solitons. Optical spatial solitons are self-trapped optical beams of finite spatial cross section that travel without diverging like freely diffracting beams. These nonlinear waves propagate in photoresponsive materials through self-inscribed waveguides, which are generated when the materials locally change their refractive index in response to light intensity. In conventional nonlinear materials, self-trapping requires high-powered lasers or external electric fields.

Now, a team of researchers from the University of Pittsburgh, Harvard University, and McMaster University have developed a pH-responsive poly(acrylamide-co-acrylic acid) hydrogel, a hydrophilic three-dimensionally connected polymer network, in which light self-trapping can be turned rapidly on and off many times in a controllable and reversible way using a low-intensity visible laser. They reported their work in a recent issue of Proceedings of the National Academy of Sciences.

Developed by Joanna Aizenberg’s group at Harvard University, the hydrogel contains critical covalently-tethered chromophores that absorb specific wavelengths of visible light and thereby transform their structure. In the absence of light, the gel is relaxed and the chromophores are predominantly in a ring-open merocyanine form. When the hydrogel is irradiated with visible light, the isomerization of merocyanine to its closed-ring spiropyran form triggers a local expulsion of water, a contraction of the hydrogel, and ultimately an increase in the refractive index along the irradiated path.

The novelty of this work is that this isomerization process is reversible. In the absence of light, the hydrogel reverts back to its original state.

The researchers demonstrated the reversible self-trapping process with experiments led by Kalaichelvi Saravanamuttu’s team at McMaster University—measuring the diameter and peak intensity of the beam over time using a 532 nm laser, optical lenses, neutral density filters, and a CCD camera. They also performed a series of control experiments, such as testing the hydrogel matrix without chromophores, to determine which parameters are critical for self-trapping.

“We determined it was important to have a hydrogel matrix that became more hydrophobic in the presence of light. It was important to have the chromophores covalently-tethered to the three-dimensional matrix to localize the refractive index change. And photoisomerization was critical in triggering this sequence of events,” says Saravanamuttu, an associate professor of chemistry and chemical biology and a senior author on the paper.

More surprising, when the researchers irradiated the hydrogel with two parallel lasers, the self-trapping beams interacted with each other when separated by distances up to 10 times the beam width. “They modulated each other, reducing their self-trapping efficiency, at remote distances through the interconnected and flexible network of the hydrogel,” Saravanamuttu says.

Being able to reversibly, predictably, and remotely control one self-trapped beam with another opens up the possibility of applications like all-optical computing using beams of ambient light. Traditional computations are performed using hard materials such as wires, semiconductors and photodiodes to couple electronics to light. Instead, the team hopes to control light with light. So far, they have already used the interactions of self-trapped beams to do basic binary arithmetic, says Saravanuamuttu.

These experimental results were confirmed by numerical simulations developed by senior authors Aizenberg, a professor of materials science and of chemistry and chemical biology at Harvard University, and Anna Balazs, a professor of chemical and petroleum engineering at the University of Pittsburgh, and their groups. Their model dynamically calculated the spatial and temporal evolution of the optical field as it propagated through the hydrogel, whose index of refraction was changing. Consistent with experiments, the model accurately captured the self-trapping dynamics and efficiency when using the single or double laser beams.

“This paper marks an interesting step forward that is indicative of the potential of one disruptive technology,” says John Sheridan, a professor of electrical and electronic engineering at the University College of Dublin, who was not involved in the research. “Technologies like this will provide core hardware components enabling the three-dimensional, all-optical connection and switching hardware needed for ‘Internet of things’ data integration and the 5G/6G telecommunications systems of the future.”

Currently, the speed of the waveguide formation and switching happens in seconds, though, rather than the nanoseconds typical of optoelectronic switches. So the researchers plan to investigate what parameters are slowing down the process and how to change them. For example, they will explore making the hydrogel more flexible to give the chromophores greater freedom to undergo isomerization in hopes of eliciting a faster response. They will also look at different types of isomerizable chromophores.

However, Saravanamuttu emphasizes they are not trying to replace digital computers that use conventional electronics, so speed may not be critical. Other potential applications include autonomous stimuli-responsive soft robotic systems for drug delivery or dynamic optics.

“This is particularly exciting because we see it as a material that can reciprocally interact with an environmental stimulus. It isn’t just turned on and off, but it actually changes its behavior in a dynamic way,” she says.

Read the article in Proceedings of the National Academy of Sciences

Figure caption: (a) Schematic illustration of the experimental setup used to probe laser self-trapping due to photoinduced local contraction of the hydrogel. A 532 nm laser beam is focused onto the entrance face of the hydrogel, propagated through the material, and imaged onto a CCD camera. (b) Illustration of beam-induced contraction of the hydrogel when continuously irradiated with a 532 nm laser beam. Credit: Saravanamuttu group, McMaster University, Aizenberg Group, Harvard University, Balazs Group, University of Pittsburgh; PNAS doi.org/10.1073/pnas.1902872117

This is a reposting of my MRS news brief, courtesy of the Materials Research Society.

Defend or delay? Grad students must decide whether to present their thesis virtually

Graduate students who are trying to finish their degrees amid the COVID-19 pandemic are finding, after years of research and months of preparation, that the big day of defending their thesis has to be delayed or done remotely.

Faced with a new order to shelter at her off-campus home, Anjali Bisaria, a graduate student in chemical and systems biology at Stanford, decided to forge ahead. She works in the lab of Tobias Meyer, PhD,  where they study how human cells move and divide to build, maintain and repair tissues and organs.

On the scheduled date and time, Bisaria logged into a Zoom session and defended her research to a virtual audience of advisors, classmates, friends and family members. She then virtually met with just her faculty examinees. After being declared a doctor, she celebrated with her lab via yet another Zoom session.

“I know it was the right thing to do to keep the community safe,” she said in a Stanford news story. “But it was a little bit sad because this is likely my last quarter on campus. So to not be able to interact with my classmates and not be able to enjoy that honeymoon phase of grad school felt unceremonious.”

Soon, microbiology and immunology graduate student Kali Pruss will face the same decision. Her in-person PhD oral is currently scheduled for May 22 at Munzer Auditorium on Stanford campus.

“I haven’t yet decided whether I’ll proceed with my defense via Zoom or delay my defense to later in the summer, in hopes that I would be able to have an in-person defense,” Pruss told me. “I was planning on staying through the summer, taking a writing quarter anyway. Thankfully, this gives me some flexibility in terms of timing.”

As a member of the lab run by Justin Sonnenburg, PhD, Pruss studies how Clostridium difficile — a bacteria that commonly causes diarrhea and colitis — adapts to the inflammation that it generates, she said.

Pruss is currently writing a paper on her research, but the pandemic is impacting that too. She told me that she’s doing more data analysis and relying less on experiments than she normally would — and she’s a bit worried about how this approach will be received.

“I’m concerned with how this is going to affect the review process, and whether I’ll be able to successfully address reviewer comments asking for additional experiments for my papers,” she said.

She added, “Ultimately, though, I feel incredibly privileged and grateful to be able to continue working remotely towards my dissertation. The question of how my research is being impacted, and whether to postpone my defense, has been a minor concern in the scope of what is currently happening at Stanford and around the world.”

Given the extension of the Bay Area’s shelter-at-home order to last through at least May 3, Pruss’s hopes of defending in-person on May 22 may not be realized. So, her extended family — from Wisconsin, Indiana and Illinois — canceled their travel arrangements. They hope to come in late summer if she delays her defense and sheltering orders have been lifted.  

Regardless of how she defends her thesis, she plans to celebrate her upcoming educational milestone.

“This is the one time we, as PhD students, get to celebrate our time in grad school as an accomplishment,” she said.

After graduation, Pruss plans to join Jeffrey Gordon’s lab at Washington University School of Medicine in St. Louis as a postdoc. Ultimately, she plans to run her own academic lab.

Photo by Anjali Bisaria

This is a reposting of my Scope story, courtesy of Stanford School of Medicine.

Twitter journal clubs: Sharing knowledge from a social distance

When I was an academic researcher, I attended many journal clubs — convening with my group in a conference room to discuss the methods and findings of a selected paper. These meetings are common in academic and medical education, allowing students to develop their presentation skills and helping everyone keep up with the flood of scientific literature.

In the era of social media, such in-person journal clubs are being replaced by Twitter journal clubs — now more than ever — and it’s led me to wonder, are 280 characters really enough?

I spoke with Roxana Daneshjou, MD, PhD, a dermatology resident at Stanford, to find out. She co-authored a recent editorial in JAMA that describes the advantages of using Twitter compared to the traditional format.

How do Twitter journal clubs work?

The journal club picks a paper to discuss, often using crowdsourcing to select something people are interested in. Everyone logs into Twitter at a specific time and has an online conversation with people from around the globe. Someone may facilitate and use pre-selected questions, but there’s also time for open discussion. You can string many tweets together, so you can basically write as much as you want.

Most journal clubs meet once a month for an hour, but the nice thing about Twitter is that the conversation is saved. So, if someone wants to comment the next day, the participants will see those responses whenever they log into Twitter. That’s important because participants are from different time zones. Having the conversation publicly recorded could be an issue for some people, but I think scientists and clinicians aren’t shy about asking questions and critiquing papers, even publicly.

Why did you start the first dermatology Twitter journal club?

I lurked in other journal clubs and participated in a dermatopathology one that was really interesting. But I wanted to have the same experience with medical dermatology, discussing disease management and new clinical discoveries.

I think Twitter journal clubs are particularly useful for small specialties like dermatology. They allow dermatologists to share knowledge across institutions. They also help promote the field of dermatology to a wider, cross-specialty audience, demonstrating the role that dermatologists can play for their patients. These interactions among specialists are easier with Twitter, compared to traditional journal clubs, because anyone can comment or ask a question about the topic, using the free Twitter website or app without advanced coordination.

Who participates?

We have over 1,700 people following our dermatology journal club, but we typically only have about 15 to 20 people actively participating in a meeting — with more people lurking. Our participants are a diverse group of residents, medical students, faculty and community physicians from across the country.

However, we’ve gotten a much larger group when we’ve done joint meetings with other specialties. For example, we did a joint journal club with nephrology — one of the largest Twitter journal clubs —  to discuss the role of dermatologists in helping manage immunosuppressed kidney transplant patients who are at higher risk of skin cancer. These cross-specialty Twitter interactions are great, because I’ve become friends with residents and faculty at other institutions and now feel comfortable sending them private messages if I have a question. For example, I met dermatologist Adewole Adamson, MD, MPP, through the journal club, and he provided me with a high level of mentorship to co-write the JAMA editorial.

How has the pandemic affected Twitter journal clubs?

Multiple Twitter journal clubs have discussed issues related to COVID-19 and their particular specialty. Our most recent dermatology journal club discussed how dermatologists were transitioning to virtual visits to help with social distancing and how resident training was continuing in dermatology with COVID-19. On April 6, infectious disease’s Twitter journal club will be discussing a paper entitled, “A Trial of Lopinavir-Ritonavir in Adults with Severe COVID-19.”

With social distancing, in-person journal clubs will be more difficult to have. Twitter is the perfect medium for having multiple conversations at once with many people. This is a really difficult time for many, and I hope Twitter journal clubs can help physicians and trainees continue to engage in academic conversations.

Image by Mohamed Mahmoud Hassan

This is a reposting of my Scope story, courtesy of Stanford School of Medicine.