Tyler O'Neal, Staff Editor HEALTH

Iowa State researchers make sense of a universe of corn based on genomics, data analytics

Seed banks across the globe store and preserve the genetic diversity of millions of varieties of crops. This massive collection of genetic material ensures crop breeders access to a wealth of genetics with which to breed crops that yield better or resist stress and disease.

But, with a world of corn genetics at their disposal, how do plant breeders know which varieties are worth studying and which ones aren't? For most of history, that required growing the varieties and studying their performance in the real world. But innovative data analytics and genomics could help plant breeders predict the performance of new varieties without having to go to the effort of growing them.

Jianming Yu, a professor of agronomy at Iowa State University and the Pioneer Distinguished Chair in Maize Breeding, has devoted much of his research to "turbocharging" the seemingly endless amount of genetic stocks contained in the world's seed banks. Yu and his colleagues have published an article in the Plant Biotechnology Journal, a scientific publication, that details their latest efforts to predict traits in corn-based on genomics and data analytics. CAPTION Seed banks across the globe store and preserve the genetic diversity of millions of varieties of crops, including corn. Iowa State University researchers are developing ways to predict the traits of corn varieties based on their genomes CREDIT Jianming Yu{module INSIDE STORY}

Plant breeders searching for varieties to test might feel lost in a sea of genomic material. Yu said applying advanced data analytics to all those genomes can help breeders narrow down the number of varieties they're interested in much faster and more efficiently.

"We're always searching for the best genetic combinations, and we search the various combinations to see what varieties we want to test," said Xiaoqing Yu (no relation), a former postdoctoral research associate in Yu's lab and the first author of the study. "Having these predictions can guide our searching process."

The study focused on predicting eight corn traits based on the shoot apical meristem (SAM), a microscopic stem cell niche that generates all the above-ground organs of the plant. The researchers used their analytical approach to predict traits in 2,687 diverse maize inbred varieties based on a model they developed from studying 369 inbred varieties that had been grown and had their shoot apical meristems pictured and measured under the microscope.

The researchers then validated their predictions with data obtained from 488 inbreds to determine their prediction accuracy ranged from 37% to 57% across the eight traits they studied.

"We wanted to connect the research in foundational biological mechanisms of cell growth and differentiation with the agronomic improvement of corn," said Mike Scanlon, a professor of developmental biology at Cornell University and the lead investigator of the multi-institutional team behind the study. "SAM morphometric measurements in corn seedlings allow quick completion of the study cycle. It not only enables that connection but also extends the practice of genomic prediction into the microphenotypic space."

Jianming Yu said plant breeders can bump up the accuracy of those genomic predictions by increasing the number of plants per inbred for measurement and findings-improved prediction algorithms. More importantly, plant breeders can finetune their selection process for which inbreds to study closely by leveraging the "U values," a statistical concept that accounts for the reliability of estimates. Yu said the study shows that implementing a selection process that accounts for prediction and statistical reliability can help plant breeders zero in on desirable crop genetics faster.

For instance, analytical models might predict a particular inbred to have the modest potential for a given trait, but the U value, or the upper bound for reliability, might indicate a high degree of unreliability in those predictions. So plant breeders might elect to test inbreds that don't do as well in the predictive model simply because of their genetic uniqueness, being less related to those used in building the prediction models.

"We found that there can be a balance between selecting for optimizing short-term gain and mining diversity," Yu said. "It's a tricky balance for plant breeders. Those considerations sometimes go in different directions. Genetic improvement can be viewed as space exploration, either of the vast amounts of existing genetic materials in seed banks or of the innumerable breeding progenies constantly being generated. We want to develop better tools to guide those decisions in the process."

Researchers supercomputer simulations prove water has multiple liquid states

Tyler O'Neal, Staff Editor HEALTH

A newly published Science journal paper reveals that water can exist as two liquids of differing density

Water is a ubiquitous liquid with many highly unique properties. The way it responds to changes in pressure and temperature can be completely different from other liquids that we know, and these properties are essential to many practical applications and particularly to life as we know it. What causes these anomalies have long been a source of scientific inspiration with various theoretical explanations, but now an international team of researchers, which includes Nicolas Giovambattista, a professor at The Graduate Center, CUNY and chair for the Department of Physics at Brooklyn College, has proved that water can exist in two different liquid states -- a finding that can explain many of water's anomalous properties. Their research appears in a paper published in today's issue of the journal Science.

The possibility that water could exist in two different liquid states was proposed approximately 30 years ago, based on results obtained from supercomputer simulations," Giovambattista said. "This counterintuitive hypothesis has been one of the most important questions in the chemistry and physics of water, and a controversial scenario since its beginnings. This is because experiments that can access the two liquid states in water have been very challenging due to the apparently unavoidable ice formation at the conditions where the two liquids should exist." CAPTION The above graphic offers a conceptual view of how water can exist in two liquid states separated by a thin interface. The bottom liquid is more dense than the one on top, because it is composed of water molecules that are more cosely packed. CREDIT Jerker Lokrantz and Anders Nilsson {module INSIDE STORY} 

The usual "liquid" state of water that we are all familiar with corresponds to liquid water at normal temperatures (approximately 25 centigrade). However, the paper shows that water at low temperatures (approximately -63 centigrade) exists in two different liquid states, a low-density liquid at low pressures and a high-density liquid at high pressures. These two liquids have noticeably different properties and differ by 20% in density. The results imply that at appropriate conditions, water should exist as two immiscible liquids separated by a thin interface similar to the coexistence of oil and water.

Because water is one of the most important substances on Earth -- the solvent of life as we know it -- its phase behavior plays a fundamental role in different fields, including biochemistry, climate, cryopreservation, cryobiology, material science, and in many industrial processes where water acts as a solvent, product, reactant, or impurity. It follows that unusual characteristics in the phase behavior of water, such as the presence of two liquid states, can affect numerous scientific and engineering applications.

"It remains an open question how the presence of two liquids may affect the behavior of aqueous solutions in general, and in particular, how the two liquids may affect biomolecules in aqueous environments," Giovambattista said. "This motivates further studies in the search for potential applications."

Giovambattista is a member of the Physics and Chemistry Ph.D. programs at The Graduate Center of The City University of New York (CUNY).

The international team, led by Anders Nilsson, professor of chemical physics at Stockholm University, used complex experiments and supercomputer simulations to prove this theory. The experiments, described as "science-fiction-like" by Giovambattista, were performed by colleagues at Stockholm University in Sweden, POSTECH University in Korea, PAL-XFEL in Korea, and SLAC national accelerator laboratory in California. The supercomputer simulations were performed by Giovambattista and Peter H. Poole, professor at St. Francis Xavier University in Canada. The supercomputer simulations played an important role in the interpretation of the experiments since these experiments are extremely complex and some observables are not accessible during the experiments.

UCF researchers distinguish features that could make someone a virus super-spreader

Tyler O'Neal, Staff Editor HEALTH

Sneezes from people who have congested noses and a full set of teeth travel about 60% farther than from people who don't, according to a new study

New research from the University of Central Florida has identified physiological features that could make people super-spreaders of viruses such as COVID-19.

In a study appearing this month in the journal Physics of Fluids, researchers in UCF's Department of Mechanical and Aerospace Engineering used supercomputer-generated models to numerically simulate sneezes in different types of people and determine associations between people's physiological features and how far their sneeze droplets travel and linger in the air.

They found that people's features, like a stopped-up nose or a full set of teeth, could increase their potential to spread viruses by affecting how far droplets travel when they sneeze.

According to the U.S. Centers for Disease Control and Prevention, the main way people are infected by the virus that causes COVID-19 is through exposure to respiratory droplets, such as from sneezes and coughs that are carrying the infectious virus.

Knowing more about factors affecting how far these droplets travel can inform efforts to control their spread, says Michael Kinzel, an assistant professor with UCF's Department of Mechanical Engineering and study co-author. Sneeze velocity for four different nose and mouth types is shown. A is open nasal passage with teeth, B is open nasal passage without teeth, C is blocked nasal passage without teeth, and D is blocked nasal passage with teeth. {module INSIDE STORY} 

"This is the first study that aims to understand the underlying 'why' of how far sneezes travel," Kinzel says. "We show that the human body has influencers, such as a complex duct system associated with the nasal flow that actually disrupts the jet from your mouth and prevents it from dispersing droplets far distances."

For instance, when people have a clear nose, such as blowing it into a tissue, the speed and distance sneeze droplets travel decrease, according to the study.

This is because a clear nose provides a path in addition to the mouth for the sneeze to exit. But when people's noses are congested, the area that the sneeze can exit is restricted, thus causing sneeze droplets expelled from the mouth to increase in velocity.

Similarly, teeth also restrict the sneeze's exit area and cause droplets to increase in velocity.

"Teeth create a narrowing effect in the jet that makes it stronger and more turbulent," Kinzel says. "They actually appear to drive transmission. So, if you see someone without teeth, you can actually expect a weaker jet from the sneeze from them."

To perform the study, the researchers used 3D modeling and numerical simulations to recreate four mouth and nose types: a person with teeth and a clear nose; a person with no teeth and a clear nose; a person with no teeth and a congested nose; and a person with teeth and a congested nose.

When they simulated sneezes in the different models, they found that the spray distance of droplets expelled when a person has a congested nose and a full set of teeth is about 60 percent greater than when they do not.

The results indicate that when someone keeps their nose clear, such as by blowing it into a tissue, that they could be reducing the distance their germs travel.

The researchers also simulated three types of saliva: thin, medium, and thick.

They found that thinner saliva resulted in sneezes comprised of smaller droplets, which created a spray and stayed in the air longer than medium and thick saliva.

For instance, three seconds after a sneeze, when thick saliva was reaching the ground and thus diminishing its threat, the thinner saliva was still floating in the air as a potential disease transmitter.

The work ties back to the researchers' project to create a COVID-19 cough drop that would give people thicker saliva to reduce the distance droplets from a sneeze or cough would travel, and thus decrease disease-transmission likelihood.

The findings yield novel insight into the variability of exposure distance and indicate how physiological factors affect transmissibility rates, says Kareem Ahmed, an associate professor in UCF's Department of Mechanical and Aerospace Engineering and study co-author.

"The results show exposure levels are highly dependent on the fluid dynamics that can vary depending on several human features," Ahmed says. "Such features may be underlying factors driving super spreading events in the COVID-19 pandemic."

The researchers say they hope to move the work toward clinical studies next to compare their simulation findings with those from real people from varied backgrounds.

Study co-authors were Douglas Fontes, a postdoctoral researcher with the Florida Space Institute and the study's lead author, and Jonathan Reyes, a postdoctoral researcher in UCF's Department of Mechanical and Aerospace Engineering.

Fontes says to advance the findings of the study, the research team wants to investigate the interactions between gas flow, mucus film, and tissue structures within the upper respiratory tract during respiratory events.

"Numerical models and experimental techniques should work side by side to provide accurate predictions of the primary breakup inside the upper respiratory tract during those events," he says.

"This research potentially will provide information for more accurate safety measures and solutions to reduce pathogen transmission, giving better conditions to deal with the usual diseases or with pandemics in the future," he says.