“This research contributes to the body of evidence linking poor respiratory health to exposure to environmental air pollution, especially combustion-derived particulate matter,” said study co-author Stephania Cormier, who leads the LSU Superfund Research Program.

Research conducted by LSU Superfund Research Program scientists has shown similar patterns for other respiratory diseases including asthma, and recent data suggest implications for COVID-19.

Using data from a Centers for Disease Control surveillance study of pediatric pneumonia and geographic information systems, the investigators identified high- and low-risk areas for CAP in the metropolitan area of Memphis, Tennessee. They collected information including the cause of the child’s pneumonia, such as a bacterial or viral infection, public versus private health insurance, age, race and exposure to particulate matter pollution less than 2.5 micrometers in diameter, or PM_2.5. These tiny particles in the air are released by industrial combustion, car exhaust and forest fires. PM_2.5 is one of the six air pollutants regulated by the Environmental Protection Agency, or EPA, and is linked to higher rates of respiratory tract infections and a plethora of other health problems, including cardiovascular disease.

When analyzed independently, race, type of insurance and exposure to PM_2.5 were all identified as significant risk factors associated with residence in areas with higher-than-expected CAP. However, race was the most significant factor associated with living in a high-risk area. In the Memphis metropolitan area, Hispanic and non-Hispanic Black children were hospitalized for pneumonia at significantly higher rates compared with white children.

Another important finding from this study is that the health risk associated with high PM_2.5 occurred at levels below the current regulatory maximum standard set by the EPA.

“The fact that we saw increased risk for pediatric pneumonia at PM_2.5 levels lower than what is currently allowed by the EPA is a concern and signals the need for continuous review and policy adjustment based on health effects evidence and exposure or risk information such as this,” Cormier said.

The World Health Organization recently lowered the maximum standards for environmental particulate matter globally to below the EPA’s current maximum level for the U.S.

This change in policy and this new research is especially significant in the context of the global COVID-19 pandemic, which is caused by severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2.

“COVID-19 also causes pneumonia, and our research suggests that PM_2.5 may contribute to higher rates of infection and enhanced disease among those who do get sick,” Cormier said.

A unique aspect of this study is that the researchers estimated PM_2.5 concentrations using satellite data.

“Through incredible advances in technology, we have access to high-resolution satellite data that accurately capture environmental pollution information anywhere around the world. We were able to use this data to hone in on specific neighborhoods that are experiencing higher than average hospitalization rates for pediatric pneumonia to find out why,” said Tonny J. Oyana, lead author and professor in the Department of Preventive Medicine at the University of Tennessee Health Science Center and principal of the College of Computing and Information Sciences at Makerere University, Uganda.

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The international team, led by the University of Cambridge, found that instead of starting from a single point in the brain and initiating a chain reaction which leads to the death of brain cells, Alzheimer’s disease reaches different regions of the brain early. How quickly the disease kills cells in these regions, through the production of toxic protein clusters, limits how quickly the disease progresses overall.

The researchers used post-mortem brain samples from Alzheimer’s patients, as well as PET scans from living patients, who ranged from those with mild cognitive impairment to those with full-blown Alzheimer’s disease, to track the aggregation of tau, one of two key proteins implicated in the condition.

In Alzheimer’s disease, tau and another protein called amyloid-beta build up into tangles and plaques – known collectively as aggregates – causing brain cells to die and the brain to shrink. This results in memory loss, personality changes and difficulty carrying out daily functions.

By combining five different datasets and applying them to the same mathematical model, the researchers observed that the mechanism controlling the rate of progression in Alzheimer’s disease is the replication of aggregates in individual regions of the brain, and not the spread of aggregates from one region to another.

The results, reported in the journal Science Advances, open up new ways of understanding the progress of Alzheimer’s and other neurodegenerative diseases, and new ways that future treatments might be developed.

For many years, the processes within the brain which result in Alzheimer’s disease have been described using terms like ‘cascade’ and ‘chain reaction’. It is a difficult disease to study, since it develops over decades, and a definitive diagnosis can only be given after examining samples of brain tissue after death.

For years, researchers have relied largely on animal models to study the disease. Results from mice suggested that Alzheimer’s disease spreads quickly, as the toxic protein clusters colonise different parts of the brain.

“The thinking had been that Alzheimer’s develops in a way that’s similar to many cancers: the aggregates form in one region and then spread through the brain,” said Dr Georg Meisl from Cambridge’s Yusuf Hamied Department of Chemistry, the paper’s first author. “But instead, we found that when Alzheimer’s starts there are already aggregates in multiple regions of the brain, and so trying to stop the spread between regions will do little to slow the disease.”

This is the first time that human data has been used to track which processes control the development of Alzheimer’s disease over time. It was made possible in part by the chemical kinetics approach developed at Cambridge over the last decade which allows the processes of aggregation and spread in the brain to be modelled, as well as advances in PET scanning and improvements in the sensitivity of other brain measurements.

“This research shows the value of working with human data instead of imperfect animal models,” said co-senior author Professor Tuomas Knowles, also from the Department of Chemistry. “It’s exciting to see the progress in this field – fifteen years ago, the basic molecular mechanisms were determined for simple systems in a test tube by us and others; but now we’re able to study this process at the molecular level in real patients, which is an important step to one day developing treatments.”

The researchers found that the replication of tau aggregates is surprisingly slow – taking up to five years. “Neurons are surprisingly good at stopping aggregates from forming, but we need to find ways to make them even better if we’re going to develop an effective treatment,” said co-senior author Professor Sir David Klenerman, from the UK Dementia Research Institute at the University of Cambridge. “It’s fascinating how biology has evolved to stop the aggregation of proteins.”

The researchers say their methodology could be used to help the development of treatments for Alzheimer’s disease, which affects an estimated 44 million people worldwide, by targeting the most important processes that occur when humans develop the disease. In addition, the methodology could be applied to other neurodegenerative diseases, such as Parkinson’s disease.  

“The key discovery is that stopping the replication of aggregates rather than their propagation is going to be more effective at the stages of the disease that we studied,” said Knowles.

The researchers are now planning to look at the earlier processes in the development of the disease, and extend the studies to other diseases such as Frontal temporal dementia, traumatic brain injury and progressive supranuclear palsy where tau aggregates are also formed during disease.

The study is a collaboration between researchers at the UK Dementia Research Institute at the University of Cambridge, University of Cambridge and Harvard Medical School. Funding is acknowledged from the Sidney Sussex College Cambridge, the European Research Council Grant Number, the Royal Society, JPB foundation, the Rainwater foundation, the NIH and the NIHR Cambridge Biomedical Research Centre which supports the Cambridge Brain Bank.

Seagrass meadows were previously common throughout the Morro Bay estuary but nearly disappeared over the last decade.

“Seagrass, like the eelgrass in Morro Bay, is important because it supports a range of marine life,” said Jennifer O’Leary, who led the research as a California Sea Grant extension specialist based at Cal Poly. O’Leary is now the Western Indian Ocean coordinator for the Wildlife Conservation Society. “It’s like the trees in a forest — these underwater plants provide food, structure, and shelter to many of the marine animals that live in the bay.”

Underwater seagrass meadows are one of the main habitats in coastal estuaries, and represent one of the most biologically productive biomes on our planet. Yet seagrass habitats are being lost at an alarming rate, and their decline now rivals those reported for tropical rainforests, coral reefs, and mangroves. Loss is usually the symptom of a larger problem, and seagrasses are therefore considered “coastal canaries.” Their decline signals important losses to biodiversity and often impacts the communities that depend on them.

Morro Bay, one of 28 estuaries that the U.S. Environmental Protection Agency designated as critical to the economic and environmental health of the nation, has seen a dramatic loss in its seagrass habitat. Once dominated by a common California eelgrass (Zostera marina), seagrass at this site has declined by more than 95 percent, from covering 344 acres in 2007 to less than 15 acres in 2017.

Seagrass meadows are a multifaceted habitat that secure sediments with their root systems, and provide food, shelter and nurseries for many types of fish and invertebrates. When seagrass meadows are lost, they are often replaced with a less dynamic, muddy seafloor habitat.

O’Leary and colleagues found that seagrass loss did not result in fewer fish but rather led to changes in the types of fish that live in the bay. The research team saw decreasing numbers of some seagrass-specialist fish species, such as the bay pipefish (Syngnathus leptorhynchus). With long thin bodies and olive green coloration, bay pipefish are adapted to hide among the seagrass blades.

In contrast, researchers observed an increase in flatfishes like the speckled sanddab (Citharichthys stigmaeus) and staghorn sculpin (Leptocottus armatus). These fish have flat bodies that are ideal for life along the muddy seafloor and are common residents in California bays and estuaries. These species have moved into the former eelgrass habitats and now make up the majority of the fish species present in Morro Bay.

The loss of eelgrass habitat along the California coast presents a larger problem for species that depend on seagrass, like the bay pipefish. If seagrass doesn’t recover, then the surviving meadows will be further apart and have a more fragmented, or patchy, distribution. This distance and patchiness of habitat may impact specialists, like pipefish, by impairing their ability to move to a new habitat to find food or mates. This community isolation may alter the genetic structure and diversity of the overall pipefish population over time.

“The relatively sudden and near complete collapse of eelgrass in Morro Bay has not only changed fish populations, but it has also resulted in substantial changes to estuary physics and geomorphology,” said study coauthor Ryan Walter, a Cal Poly physics professor who has been studying eelgrass loss through a California Sea Grant-funded research project that was launched in 2018.

Walter, O’Leary and other Cal Poly researchers, in conjunction with the Morro Bay National Estuary Program, continue to study the cause and consequences of the eelgrass decline. In another study, the team recently found that the loss of eelgrass in Morro Bay led to widespread erosion, or loss of sediment, throughout the estuary.

The new research sheds additional light on changes within Morro Bay that may inform how scientists learn about seagrass communities throughout California. There has not been an eelgrass decline on the United States Pacific Coast of this magnitude, making Morro Bay a novel event that may help predict future estuarine change.

A multifaceted approach to protect and enhance the remaining seagrass will be essential, according to the researchers. There is hope for the future as the remaining eelgrass is slowly expanding with protection and local planting initiatives, including successful transplant efforts led by the Morro Bay National Estuary Program. Walter and O’Leary have used drone-based surveys to document natural expansion and recovery of eelgrass in areas where it was lost. The mere 9.4 acres of seagrass left in Morro Bay in 2017 expanded to 36.7 acres by 2019. The researchers are still analyzing data from 2020 but are optimistic that the seagrass acreage continues to slowly increase.

The advance was made possible by development of new, ultrafast photon detectors, said Simon Cherry, professor of biomedical engineering and of radiology at the University of California, Davis and senior author on the paper.

“We’re literally imaging at the speed of light, which is something of a holy grail in our field,” Cherry said.

Experimental work was led by Sun Il Kwon, project scientist in the UC Davis Department of Biomedical Engineering and Ryosuke Ota at Hamamatsu Photonics, Japan, where the new photon detector technology was developed. Other collaborators included research groups led by Professor Yoichi Tamagawa at the University of Fukui, and by Professor Tomoyuki Hasegawa at Kitasato University.

The process of tomography is required to mathematically reconstruct cross-sectional images from the data in imaging that uses X-rays or gamma rays. In PET scans, molecules tagged with trace amounts of a radioactive isotope are injected and taken up by organs and tissues in the body. The isotope, such as fluorine-18, is unstable and emits positrons as it decays.

Ultrafast photon detection

Whenever one of these positrons encounters an electron in the body, they annihilate each other and simultaneously give off two annihilation photons. Tracking the origin and trajectory of these photons theoretically creates an image of the tissues tagged with isotopes. But until now, researchers were unable to do that without the extra step of tomographic reconstruction, because detectors were too slow to precisely determine the arrival times of two photons and thus pinpoint their location based on their time difference.

When the annihilation photons strike the detector, they generate Cherenkov photons that produce the signal. Cherry and his fellow researchers figured out how to detect these Cherenkov photonså with an average timing precision of 32 picoseconds. This meant they could determine where the annihilation photons arose with a spatial precision of 4.8 millimeters. This level of speed and accuracy enabled the research team to produce cross-sectional images of a radioactive isotope directly from the annihilation photons without having to use tomography.

In their paper, the researchers describe various tests they conducted with their new technique, including on a test object that mimics the human brain. They feel confident that this procedure is ultimately scalable to the level needed for clinical diagnostics and has the potential to create higher quality images using a lower radiation dose. Images can also be created more quickly with this method, potentially even in real time during the PET scan, as no after-the-fact reconstruction is needed.

PET scans are currently expensive and are technically limited in some ways, as the full information present in the travel time of the annihilation photons is not captured by current clinical scanners. This new discovery involves a compact equipment setup and could lead to inexpensive, easy and accurate scans of the human body using radioactive isotopes.

Additional coauthors are: Eric Berg at UC Davis; Fumio Hashimoto and Tomohide Omura, Hamamatsu Photonics; Kyohei Nakajima and Izumi Ogawa, University of Fukui.

The study was partly supported by grants from the NIH.

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Findings also indicated that the availability of more supermarkets could be protective against developing T2D, particularly in suburban and rural neighborhoods.

The study — notable for its large geographic breadth — uses data from a cohort of more than 4 million veterans living in 98 percent of U.S. census tracts across the country. It counted fast-food restaurants and supermarkets relative to other food outlets, and is the first, according to the researchers, to examine this relationship in four distinct types of neighborhoods (high-density urban, low-density urban, suburban, and rural) at the hyperlocal level nationwide.

“Most studies that examine the built food environment and its relationship to chronic diseases have been much smaller or conducted in localized areas,” said Rania Kanchi, MPH, a researcher in the Department of Population Health at NYU Langone and lead author of the study. “Our study design is national in scope and allowed us to identify the types of communities that people are living in, characterize their food environment, and observe what happens to them over time. The size of our cohort allows for geographic generalizability in a way that other studies do not.”

How the Study was Conducted

The research team used data from the U.S. Veterans Health Administration (the largest single-payer healthcare system in the country) that captures more than 9 million veterans seen at more than 1,200 health facilities around the country. Using this data, the researchers then constructed a national cohort of more than 4 million veterans without diabetes from the VA electronic health records (EHR) between 2008 and 2016. Each veteran’s health status was followed through 2018 or until the individual either developed diabetes, died, or had no appointments for more than two years.

Within each of four distinct neighborhood types, the proportion of restaurants that were fast food, and the proportion of food outlets that were supermarkets were tabulated within a one-mile walk in high- density urban neighborhoods, a two-mile drive in low-density urban neighborhoods, a six-mile drive in suburban communities, and a 10-mile drive in rural communities.

Veterans were followed for a median of five and a half years. During that time, 13.2 percent of the cohort were newly diagnosed with T2D. Males developed T2D more frequently than females (13.6 versus 8.2 percent). Non-Hispanic Black adults had the highest incidence (16.9 percent), compared to non-Hispanic Whites (12.9 percent), non-White Asian and Hispanics (12.8 percent), Native Hawaiian and Pacific Islanders (15 percent), and Native American and Alaskan Indians (14.2 percent).

When stratifying by community types, 14.3 percent of veterans living in high density urban communities developed T2D, while the lowest incidence was among those living in suburban and small town communities (12.6 percent).

Overall, the team concluded that the effect of the food environment on T2D incidence varied by how urban the community was, but did not vary further by region of the country.

“The more we learn about the relationship between the food environment and chronic diseases like type 2 diabetes, the more policymakers can act by improving the mix of healthy food options sold in restaurants and food outlets, or by creating better zoning laws that promote optimal food options for residents,” said Lorna Thorpe, PhD, MPH, professor in the Department of Population Health at NYU Langone and senior author of the study.

One limitation of the study, according to the authors, is that the study may not be fully generalizable to non-veteran populations, as U.S. veterans tend to be predominantly male and have substantially greater health burdens and financial instability than the civilian population. They are also at greater risk of disability, obesity, and other chronic conditions.

The next phase of the research, say Thorpe and Kanchi, will be to better understand the impacts of the built environment on diabetes risk by subgroups. They plan to examine whether or not the relationships between fast-food restaurants, supermarkets and community types vary by gender, race/ethnicity, and socioeconomic status.

Funding for the study was provided by the Centers for Disease Control and Prevention.

In addition to Thorpe and Kanchi, other NYU Langone researchers include Priscilla Lopez, MPH; Pasquale E. Rummo, PhD; David C. Lee, MD; Samrachana Adhikari, PhD; Mark D. Schwartz, MD, and Brian Elbel, PhD. Other research support was provided by Sanja Avramovich, PhD, Department of Health Administration and Policy, George Mason University; Karen R. Siegel, PhD; Deborah B. Rolka, MS and Giuseppina Imperatore from the Division of Diabetes Translation at the Centers for Disease Control and Prevention.