Culture

Even the toughest coffee trees may be no match for climate change. A new study of the plant that produces robusta coffee suggests its heat tolerance has been consistently overestimated. Worse yet, when temperatures just slightly cross this point, yields plummet. The findings suggest the multibillion-dollar coffee industry could be facing a much tougher future on even a slightly warmer planet.

The study, published in Global Change Biology, was built on 10 years of yield observations on almost 800 farms across Southeast Asia. The analysis suggests that the optimal temperature range for robusta is 20.5 degrees C, which is markedly lower than the temperatures currently considered optimal. For every 1-degree increase over this new optimal range, yields decrease by 14 percent.

"Our results suggest that robusta coffee is far more sensitive to temperature than previously thought," said the authors. "Its production potential could decline considerably as temperatures increase under climate change, jeopardizing a multibillion-dollar coffee industry and the livelihoods of millions of farmers."

Scientists from the Alliance of Bioversity International and CIAT and the University of Southern Queensland (USQ) and ECOM Agroindustrial, a global commodity merchant and sustainable supply chain management company, conducted the research on farms in Vietnam and Indonesia, which supply about half the world's robusta beans.

The study's findings contrast with current estimates, based on historical botanical explorations in Central Africa, that had suggested robusta had a higher temperature tolerance.

"This should make us reassess the viability of some of our current options, like switching from arabica to robusta coffee as the climate warms to adapt production to climate change," said Jarrod Kath, the study's lead author from USQ.

Arabica coffee, which is preferred by coffee connoisseurs for its superb taste, is even more sensitive to temperature change. Coffee farmers at lower altitudes around the tropics have been switching out their arabica trees for robusta trees, while arabica farmers have been searching for higher altitudes and lower temperatures to maintain production.

"These findings provide baseline information for coffee farmers, private sector investors and governments to adapt their coffee production plans under climate change," said Alessandro Craparo, a co-author with the Alliance.

"Precipitation changes have long been a concern of the coffee industry," said co-author Laurent Bossolasco of ECOM. "Now it's clear that we need more in-depth analysis of temperature variations in the robusta region."

The research adds a new dimension to how the researchers and industry understand coffee, said Kath.

It highlights the importance of testing assumptions about agricultural production sensitivity to climate variability with large field-based datasets.

"Theory is only as good as the data used to test it," said Craparo.

What did the very first proteins look like -- those that appeared on Earth around 3.7 billion years ago? Prof. Dan Tawfik of the Weizmann Institute of Science and Prof. Norman Metanis of the Hebrew University of Jerusalem have reconstructed protein sequences that may well resemble those ancestors of modern proteins, and their research suggests a way that these primitive proteins could have progressed to forming living cells. Their findings were published in the Proceedings of the National Academy of Sciences (PNAS).

The proteins encoded in a cell's genetic material are the screws, springs and cogs of a living cell -- all of its moving parts. But the first proteins, we assume, appeared well before cells and thus life as we know it. Modern proteins are made of 20 different amino acids, all of them essential to protein-building, and all arranged in the form of a polymer - a long, chain-like molecule - in which the placement of each amino acid is crucial to the protein's function. But there is a paradox in thinking about how the earliest proteins arose. Because the amino acids needed to make proteins are themselves produced by other proteins - enzymes. It's a chicken-and-egg kind of question, and it has only been partially answered until now.

Scientists believe that the very first true proteins materialized from shorter protein segments called peptides. The peptides would have been sticky assemblies of the amino acids that were spontaneously created in the primeval chemical soup; the short peptides would have then bound to one another, over time producing a protein capable of some sort of action. The spontaneous generation of amino acids had already been demonstrated in 1952, in the famous experiment by Miller and Urey, in which they replicated the conditions thought to exist on Earth prior to life and added energy like that which could come from lightning or volcanoes. Showing amino acids could, under the right conditions, form without help from enzymes or any other mechanism in a living organism suggested that amino acids were the "egg" that preceded the enzyme "chicken."

Tawfik, who is in the Institute's Biomolecular Sciences Department, says that is all well and good, "but one vital type of amino acid has been missing from that experiment and every experiment that followed in its wake: amino acids like arginine and lysine that carry a positive electric charge." These amino acids are particularly important to modern proteins, as they interact with DNA and RNA, both of which carry net negative charges. RNA is today presumed to be the original molecule that could both carry information and make copies of itself, so contact with positively-charged amino acids would theoretically be necessary for further steps in the development of living cells to occur.

But there was one positively-charged amino acid that appeared in the Miller-Urey experiments, an amino acid called ornithine that is today found as an intermediate step in arginine production, but is not, itself, used to build proteins. The research team asked: What if ornithine was the missing amino acid in those ancestral proteins? They designed an original experiment to test this hypothesis.

The scientists began with a relatively simple protein from a family that binds to DNA and RNA, applying phylogenetic methods to infer the sequence of the ancestral protein. This protein would have been rich in positive charges - 14 of the 64 amino acids being either arginine or lysine. Next, they created synthetic proteins in which ornithine replaced these as the positive charge carrier.

The ornithine-based proteins bound to DNA, but weakly. In Metanis' lab, however, the researchers found that simple chemical reactions could convert ornithine to arginine. And these chemical reactions occurred under those conditions assumed to have prevailed on Earth at the time the first proteins would have appeared. As more and more of the ornithine was converted to arginine, the proteins came more and more to resemble modern proteins, and to bind to DNA in a way that was stronger and more selective.

The scientists also discovered that in the presence of RNA, that the ancient form of the peptide engaged in phase separation (like oil drops in water) - a step that can then lead to self-assembly and "departmentalization." And this, says Tawfik, suggests that such proteins, together with RNA, could form proto-cells, from which true living cells might have evolved.

During the pandemic lockdown, as couples have been forced to spend days and weeks in one another's company, some have found their love renewed while others are on their way to divorce court. Oxytocin, a peptide produced in the brain, is complicated in that way: a neuromodulator, it may bring hearts together or it can help induce aggression. That conclusion arises from unique research led by Weizmann Institute of Science researchers in which mice living in semi-natural conditions had their oxytocin producing brain cells manipulated in a highly precise manner. The findings, which were published in Neuron, could shed new light on efforts to use oxytocin to treat a variety of psychiatric conditions, from social anxiety and autism to schizophrenia.

Much of what we know about the actions of neuromodulators like oxytocin comes from behavioral studies of lab animals in standard lab conditions. These conditions are strictly controlled and artificial, in part so that researchers can limit the number of variables affecting behavior. But a number of recent studies suggest that the actions of a mouse in a semi-natural environment can teach us much more about natural behavior, especially when we mean to apply those findings to humans.

Prof. Alon Chen's lab group in the Institute's Neurobiology Department have created an experimental setup that enables them to observe mice in something approaching their natural living conditions - an environment enriched with stimuli they can explore - and their activity is monitored day and night with cameras and analyzed computationally. The present study, which has been ongoing for the past eight years, was led by research students Sergey Anpilov and Noa Eren, and Staff Scientist Dr. Yair Shemesh in Prof. Chen's lab group. The innovation in this experiment, however, was to incorporate optogenetics - a method that enables researchers to turn specific neurons in the brain on or off using light. To create an optogenetic setup that would enable the team to study mice that were behaving naturally, the group developed a compact, lightweight, wireless device with which the scientists could activate nerve cells by remote control. With the help of optogenetics expert Prof. Ofer Yizhar of the same department, the group introduced a protein previously developed by Yizhar into the oxytocin-producing brain cells in the mice. When light from the wireless device touched those neurons, they became more sensitized to input from the other brain cells in their network.

"Our first goal," says Anpilov, "was to reach that 'sweet spot' of experimental setups in which we track behavior in a natural environment, without relinquishing the ability to ask pointed scientific questions about brain functions."

Shemesh adds that, "the classical experimental setup is not only lacking in stimuli, the measurements tend to span mere minutes, while we had the capacity to track social dynamics in a group over the course of days."

Delving into the role of oxytocin was sort of a test drive for the experimental system. It had been believed that this hormone mediates pro-social behavior. But findings have been conflicting, and some have proposed another hypothesis, termed "social salience" stating that oxytocin might be involved in amplifying the perception of diverse social cues, which could then result in pro-social or antagonistic behaviors, depending on such factors as individual character and their environment.

To test the social salience hypothesis, the team used mice in which they could gently activate the oxytocin-producing cells in the hypothalamus, placing them first in the enriched, semi-natural lab environments. To compare, they repeated the experiment with mice placed in the standard, sterile lab setups.

In the semi-natural environment, the mice at first displayed heightened interest in one another, but this was soon accompanied by a rise in aggressive behavior. In contrast, increasing oxytocin production in the mice in classical lab conditions resulted in reduced aggression. "In an all-male, natural social setting, we would expect to see belligerent behavior as they compete for territory or food," says Anpilov. "That is, the social conditions are conducive to competition and aggression. In the standard lab setup, a different social situation leads to a different effect for the oxytocin."

If the "love hormone" is more likely a "social hormone," what does that mean for its pharmaceutical applications? "Oxytocin is involved, as previous experiments have shown, in such social behaviors as making eye contact or feelings of closeness," says Eren, "but our work shows it does not improve sociability across the board. Its effects depend on both context and personality." This implies that if oxytocin is to be used therapeutically, a much more nuanced view is needed in research: "If we want to understand the complexities of behavior, we need to study behavior in a complex environment. Only then can we begin to translate our findings to human behavior," she says.

Researchers from the Okinawa Institute of Science and Technology Graduate University (OIST) have shed light on the reproductive role of 'dark matter' DNA - non-coding DNA sequences that previously seemed to have no function.

Their findings, published today in Nature Communications, have revealed that a specific non-coding genomic region is essential for the proper development of the male and female reproductive organs in rice.

"Rice is one of the major global crops and is the staple food in many countries, including Japan," said Dr. Reina Komiya, senior author of the research paper and associate researcher from the OIST Science and Technology Group. "Further research into how these genomic regions affect plant reproduction could potentially lead to increased productivity and more stable yields of rice."

Many previous developmental studies have focused on genes - the sections of DNA that provide instructions for making proteins. But in complex creatures like plants and animals, a large fraction of the genome - typically between 90-98% - doesn't actually code for proteins.

The vast expanse of this 'junk DNA' has long puzzled biologists, with many dubbing it the 'dark matter' of the genome. But recent research suggests that many of these non-coding genomic regions may have a function after all, giving rise to non-coding RNA.

Scientists have now identified numerous types of non-coding RNA, ranging from small molecules only 20-30 nucleotide bases in length to long molecules of over 200 nucleotides. Although studies show that non-coding RNA plays a vital role in the regulation of gene expression - the process where a gene's instructions are used to make RNA or protein - the precise function of each specific non-coding RNA remains poorly understood.

Dr. Komiya is particularly interested in reproduction-specific RNAs. "These are non-coding RNAs that are produced as the reproductive system forms. I wanted to uncover what role they play in the development of stamens and pistils, the male and female reproductive organs in plants."

Making mutants

In the study, Dr. Komiya's group focused on a reproduction-specific microRNA - a major class of small non-coding RNAs - called microRNA2118.

The scientists created mutant rice strains by deleting a region of the genome that contains multiple copies of the specific DNA sequence that gives rise to microRNA2118. They found that the mutant strains were sterile and showed abnormalities in the structure of the stamens and pistils.

"This means that the role of microRNA2118 in the proper development of the stamens and pistils is essential for plant fertility," said Dr. Komiya.

Revealing RNA and probing proteins

In order to delve deeper into how microRNA2118 controlled development of the anther, the scientists then identified which other molecules were affected by microRNA2118.

They found that microRNA2118 triggered the cleavage of long non-coding RNA, producing many tiny RNA molecules, called secondary small RNAs.

"Interestingly, these small RNAs were rich in uracil, one of the four nucleotide bases found in RNA, which is very unusual compared to other small RNAs," said Dr. Komiya. "We hope to find out the exact function of these small RNAs - and whether this difference in nucleotide composition is important - in further research."

The scientists also discovered that two Argonaute proteins that were only produced in the stamen were dependent on the presence of microRNA2118. Previous research has shown that Argonaute proteins team up with small RNAs to carry out many regulatory functions, such as silencing genes and cleaving RNA.

Dr. Komiya's group therefore proposes that the Argonaute proteins may interact with microRNA2118 to trigger production of the secondary small RNAs. The proteins may also interact with the secondary small RNAs to silence specific regions of the genome. The team hopes to elucidate exactly how the Argonaute proteins and secondary small RNAs affect development of the plant reproductive system in further research.

"Reproduction is an important phenomenon of passing genetic information to the next generation and is essential for maintaining a stable yield supply. However, development of the reproductive system is complicated, and many aspects remain unknown," concluded Dr. Komiya. "This study shows that non-coding RNAs, derived from regions of the genome that were thought to be non-functional, are vital for plant reproduction. Exploring non-coding RNAs further is an exciting and important area of research."

Differences in the rate that genetic mutations accumulate in healthy young adults could help predict remaining lifespan in both sexes and the remaining years of fertility in women, according to University of Utah Health scientists. Their study, believed to be the first of its kind, found that young adults who acquired fewer mutations over time lived about five years longer than those who acquired them more rapidly.

The researchers say the discovery could eventually lead to the development of interventions to slow the aging process.

"If the results from this small study are validated by other independent research, it would have tremendous implications," says Lynn B. Jorde, Ph.D., chair of the Department of Human Genetics at U of U Health and a co-author of the study. "It would mean that we could possibly find ways to fix ourselves and live longer and better lives."

The study appears online in the journal Scientific Reports.

Scientists have long known that DNA damage constantly occurs in the body. Typically, various mechanisms repair this damage and prevent potentially harmful mutations, according to lead and corresponding author Richard Cawthon, M.D., Ph.D., a U of U Health research associate professor of human genetics.

As we get older, these mechanisms become less efficient and more mutations accumulate. Older parents, for instance, tend to pass on more genetic mutations through their germline (egg and sperm) to their children than younger parents.

However, Cawthon and colleagues theorized that these mutations could be a biomarker for rates of aging and potentially predict lifespan in younger individuals as well as fertility in women.

The researchers sequenced DNA from 61 men and 61 women who were grandparents in 41 three-generational families. The families were part of the Centre d'Etude du Polymorphisme Humain (CEPH) consortium, which was central to many key investigations that have contributed toward a modern understanding of human genetics.

The researchers analyzed blood DNA sequences in trios consisting of pairs of grandparents from the first generation and one of their children from the second generation. That's because germline mutations are passed on to their offspring. Mutations found in the child's blood DNA that were not present in either parent's blood DNA were then inferred to have originated in the parents' germlines. The researchers were then able to determine which parent each germline mutation came from, and, therefore, the number of such mutations each parent had accumulated in egg or sperm by the time of conception of the child.

Knowing that allowed the researchers to compare each first-generation parent to others of the same sex and estimate their rate of aging.

"So, compared to a 32-year-old man with 75 mutations, we would expect a 40-year-old with the same number of mutations to be aging more slowly," Cawthon says. "We'd expect him to die at an older age than the age at which the 32-year-old dies."

The scientists found that mutations began to occur at an accelerating rate during or soon after puberty, suggesting that aging begins in our teens.

Some young adults acquired mutations at up to three times the rate of others. After adjusting for age, the researchers determined that individuals with the slowest rates of mutation accumulation were likely to live about five years longer than those who accumulated mutations more rapidly. This is a difference comparable to the effects of smoking or lack of physical activity, Cawthon says.

Women with the highest mutation rates had significantly fewer live births than other women and were more likely to be younger when they gave birth to their last child. This suggests that the high rate of mutation was affecting their fertility.

"The ability to determine when aging starts, how long women can stay fertile, and how long people can live is an exciting possibility," Cawthon says. "If we can get to a point where we better understand what sort of developmental biology affecting mutation rates is happening during puberty, then we should be able to develop medical interventions to restore DNA repair and other homeostatic mechanisms back to what they were before puberty. If we could do that, it's possible people could live and stay healthy much longer."

A group of researchers, led by a UNSW sustainability scientist, have reviewed existing academic discussions on the link between wealth, economy and associated impacts, reaching a clear conclusion: technology will only get us so far when working towards sustainability - we need far-reaching lifestyle changes and different economic paradigms.

In their review, published today in Nature Communications and entitled Scientists' Warning on Affluence, the researchers have summarised the available evidence, identifying possible solution approaches.

"Recent scientists' warnings have done a great job at describing the many perils our natural world is facing through crises in climate, biodiversity and food systems, to name but a few," says lead author Professor Tommy Wiedmann from UNSW Engineering.

"However, none of these warnings has explicitly considered the role of growth-oriented economies and the pursuit of affluence. In our scientists' warning, we identify the underlying forces of overconsumption and spell out the measures that are needed to tackle the overwhelming 'power' of consumption and the economic growth paradigm - that's the gap we fill.

"The key conclusion from our review is that we cannot rely on technology alone to solve existential environmental problems - like climate change, biodiversity loss and pollution - but that we also have to change our affluent lifestyles and reduce overconsumption, in combination with structural change."

During the past 40 years, worldwide wealth growth has continuously outpaced any efficiency gains.

"Technology can help us to consume more efficiently, i.e. to save energy and resources, but these technological improvements cannot keep pace with our ever-increasing levels of consumption," Prof Wiedmann says.

Reducing overconsumption in the world's richest

Co-author Julia Steinberger, Professor of Ecological Economics at the University of Leeds, says affluence is often portrayed as something to aspire to.

"But our paper has shown that it's actually dangerous and leads to planetary-scale destruction. To protect ourselves from the worsening climate crisis, we must reduce inequality and challenge the notion that riches, and those who possess them, are inherently good."

In fact, the researchers say the world's affluent citizens are responsible for most environmental impacts and are central to any future prospect of retreating to safer conditions.

"Consumption of affluent households worldwide is by far the strongest determinant - and the strongest accelerator - of increased global environmental and social impacts," co-author Lorenz Keysser from ETH Zurich says.

"Current discussions on how to address the ecological crises within science, policy making and social movements need to recognize the responsibility of the most affluent for these crises."

The researchers say overconsumption and affluence need to be addressed through lifestyle changes.

"It's hardly ever acknowledged, but any transition towards sustainability can only be effective if technological advancements are complemented by far-reaching lifestyle changes," says co-author Manfred Lenzen, Professor of Sustainability Research at the University of Sydney.

"I am often asked to explain this issue at social gatherings. Usually I say that what we see or associate with our current environmental issues (cars, power, planes) is just the tip of our personal iceberg. It's all the stuff we consume and the environmental destruction embodied in that stuff that forms the iceberg's submerged part. Unfortunately, once we understand this, the implications for our lifestyle are often so confronting that denial kicks in."

No level of growth is sustainable

However, the scientists say responsibility for change doesn't just sit with individuals - broader structural changes are needed.

"Individuals' attempts at such lifestyle transitions may be doomed to fail, because existing societies, economies and cultures incentivise consumption expansion," Prof Wiedmann says.

A change in economic paradigms is therefore sorely needed.

"The structural imperative for growth in competitive market economies leads to decision makers being locked into bolstering economic growth, and inhibiting
necessary societal changes," Prof Wiedmann says.

"So, we have to get away from our obsession with economic growth - we really need to start managing our economies in a way that protects our climate and natural resources, even if this means less, no or even negative growth.

"In Australia, this discussion isn't happening at all - economic growth is the one and only mantra preached by both main political parties. It's very different in New Zealand - their Wellbeing Budget 2019 is one example of how government investment can be directed in a more sustainable direction, by transforming the economy rather than growing it."

The researchers say that "green growth" or "sustainable growth" is a myth.

"As long as there is growth - both economically and in population - technology cannot keep up with reducing impacts, the overall environmental impacts with only increase," Prof Wiedmann says.

One way to enforce these lifestyle changes could be to reduce overconsumption by the super-rich, e.g. through taxation policies.

"'Degrowth' proponents go a step further and suggest a more radical social change that leads away from capitalism to other forms of economic and social governance," Prof Wiedmann says.

"Policies may include, for example, eco-taxes, green investments, wealth redistribution through taxation and a maximum income, a guaranteed basic income and reduced working hours."

Modelling an alternative future

Prof Wiedmann's team now wants to model scenarios for sustainable transformations - that means exploring different pathways of development with a computer model to see what we need to do to achieve the best possible outcome.

"We have already started doing this with a recent piece of research that showed a fairer, greener and more prosperous Australia is possible - so long as political leaders don't focus just on economic growth.

"We hope that this review shows a different perspective on what matters, and supports us in overcoming deeply entrenched views on how humans have to dominate nature, and on how our economies have to grow ever more. We can't keep behaving as if we had a spare planet available."

Many countries are failing to comply with the non-binding commitments of the Paris Agreement, making it increasingly clear that we have to reconsider how to ensure collective action to limit global warming to less than 2°C above preindustrial levels. A new IIASA-led study supports a different approach to designing an international climate agreement that would incentivize countries to cooperate.

Although there is general consensus that global greenhouse gas emissions are too high, most governments would prefer other countries to reduce their emissions rather than reducing their own. The Paris Agreement is intended to solve this collective action problem, but according to a 2017 United Nations Environment Programme report, this landmark accord is likely insufficient. The authors of the study published in Scientific Reports explored one proposed solution to this problem, namely matching-commitment agreements. In such an agreement, each country can commit to reducing its emissions by an amount that depends on the emissions reductions of other countries. Using these commitments to conditional emissions reductions allows countries to incentivize other countries to reduce their emissions.

"Much of the current discussion around international climate agreements centers on how to induce countries to accede to a global carbon price, and prevent countries who do not impose such a tax from gaining an economic advantage over those who do. One prominent approach to doing so is the "climate club" approach, which incentivizes countries to cooperate by imposing trade sanctions on those who do not. While this approach is compelling and may avoid some of the shortcomings of the Paris Agreement, its implementation would be difficult, as international-trade law would need to be amended to allow for penalties on non-participants," explains study lead author Chai Molina, a researcher at IIASA, Princeton University, and the University of Pennsylvania. "We wanted to understand if it's possible to incentivize countries to cooperate by using a matching-commitment agreement rather than trade sanctions or asking them to make binding commitments to unilateral actions."

The study results indicate that such an agreement incentivizes countries to make matching commitments that in turn incentivize emissions reductions and reduce emissions from those expected without an agreement. In the one-shot "climate game" analyzed in the study, matching-commitment agreements successfully diverted two heterogeneous countries from a rational, stable outcome from which no country has an incentive to deviate, to a unique new, efficient equilibrium at which their emissions are lower than they would be in the absence of an agreement. At this new equilibrium, both countries are better off in terms of their economic payoffs than they would have been without the matching-commitment agreements.

The authors say that one of the aspects that makes their study different from other studies on matching-commitment agreements, is that most of them treat countries as if they were identical, assuming that they would suffer the same damages from climate change, and that they have the same selfish economic incentives to keep greenhouse gas emissions high. This research was inspired by a previous study that analyzed matching-commitment agreements between countries whose incentives may be different from one another. That study, however, considered a business-as-usual scenario in which some countries act irrationally, in the sense that they have an incentive to lower their emissions unilaterally, but do not do so. In this setting, it is unclear whether the matching-commitment agreement results in emissions reductions beyond those that would have been achieved without any agreement, if countries simply heeded their selfish incentives.

In their study, the authors analyzed a more realistic scenario in which countries consistently respond rationally to their incentives, both in the business-as-usual scenario and under a matching-commitment agreement. This new choice of business-as-usual is important, not just because it changes the payoffs countries obtain for different emissions reductions, but also because it allowed the authors to show that the matching-commitment agreement still results in reduced emissions, even if countries heed their economic incentives in the absence of an agreement.

The researchers emphasize that their work is a "proof of concept", and that further work on the subject will help to determine whether these agreements would work in practice. Nonetheless, the study results suggest that matching-commitment agreements are a promising approach to constructing an international environmental agreement. Moreover, a similar approach could in principle be used to tackle other public goods problems in situations in which enforcement is problematic.

BEER-SHEVA, Israel...June 19, 2020 - Chronic traumatic encephalopathy (CTE), a neurodegenerative disease caused by repeated head injuries often affecting athletes, can only be diagnosed currently through brain tissue analysis post-mortem. However, in a new study published in Brain, a Journal of Neurology, Ben-Gurion University of the Negev (BGU) researchers present a new test methodology. Using brain imaging techniques and analytical methods, they can determine whether football players have CTE by measuring leakage of the blood-brain barrier.

The blood-brain barrier (BBB) is a specialized interface between the blood and the brain environment that prevents the transfer of unwanted molecules or infectious organisms from the blood to the brain. Evidence shows that breaching the integrity of this barrier causes many brain diseases and neurodegeneration as a result of aging.

"Since a leaky BBB is also found in CTE and causes brain dysfunction and degeneration, it now seems that this test could provide the first (and so far the only) evidence for brain injury in the players we studied on the Israel football team," says Prof. Alon Friedman, M.D., a neurosurgeon and researcher at BGU and Dalhousie University in Canada.

"Importantly, we believe that those with persistent leak encompassing months or years are more likely to develop CTE. Many players seem to repair their BBB quickly, and if they do not suffer from repeated TBIs [traumatic brain injuries] or are not sensitive to brain injury, they are not likely to develop CTE."

The study population included 42 Israelis who play amateur American football in the Israeli Football League (IFL), and a control group comprising 27 athletes practicing a non-contact sport and 26 non-athletes. Magnetic resonance scans were also performed on 51 patients with malignant brain tumors, ischemic stroke or traumatic brain injury (TBI). The NFL sideline concussion assessment tool was used to document history of previous head injuries, including concussions, as well as symptoms assessment and Standardized Assessment of Concussion (SAC) tests.

The researchers developed a modified dynamic contrast-enhanced-MRI (DCE-MRI) protocol and analytical methods to investigate vascular pathology and blood-brain barrier disorder (BBBD) associated with repeated mild TBI in American football players. For the first time, using human brain imaging, they distinguished between fast and slow leakage through the pathological BBB and showed that localized, specific post-traumatic vascular pathology may persist for months in a subset of players.

"We generated maps that visualized the permeability value for each 3D section (voxel), Prof. Friedman says. "Our permeability maps revealed an increase in slow blood-to-brain transport in a subset of amateur American football players, but not in the control group. The increase in permeability was region specific (white matter, midbrain peduncles, red nucleus, temporal cortex) and correlated with alterations in white matter tracts. Importantly, increased permeability persisted for months, as seen in players who were scanned both on- and off-season.

"Not less important is the observation that few players who did not complain of severe symptoms also showed a leaky BBB. This suggests that DCE-MRI should be used in conjunction with symptom questionnaires before return to play is approved."

Football players were three times more likely to display a leaky BBB than controls as BBBD was detected in a subgroup (27.4%) of players. This individual variability may explain the wide range of cognitive deficits and neuropsychiatric impairments observed in players, likely reflecting differences in affected brain networks.

"Our findings show that DCE-MRI can be used to diagnose specific vascular pathology after traumatic brain injury and other brain pathologies," Prof. Friedman says.

The researchers note that while the present study was performed in otherwise-healthy amateur players, future studies are recommended to determine the prevalence and spatial-temporal characteristics of BBBD in professional players and/or retired players with and without CTE clinical signs and symptoms. Differences, if found, may improve the understanding of the effects of impact strength and frequency, age of onset, player's skill and extent of vascular injury.

Today's modern cities, from Denver to Dubai, could learn a thing or two from the ancient Pueblo communities that once stretched across the southwestern United States. For starters, the more people live together, the better the living standards.

That finding comes from a study published today in the journal Science Advances and led by Scott Ortman, an archaeologist at the University of Colorado Boulder. He's one of a growing number of antiquarians who argue that the world's past may hold the key to its future. What lessons can people living today take from the successes and failures of civilizations hundreds or thousands of years ago?

Recently, Ortman and Jose Lobo from Arizona State University took a deep dive into data from the farming towns that dotted the Rio Grande Valley between the 14th and 16th centuries. Modern metropolises should take note: As the Pueblo villages grew bigger and denser, their per capita production of food and other goods seemed to go up, too.

Busy streets, in other words, may lead to better-off citizens.

"We see an increasing return to scale," said Ortman, an assistant professor in the Department of Anthropology who is also affiliated with the Santa Fe Institute in New Mexico. "The more people work together, the more they produce per person."

Whether the same thing is true today remains an open question, especially amid the unprecedented impacts of the COVID-19 pandemic on cities and human proximity. But the results from the sunny Southwest suggest that it's an idea worth exploring.

"The archaeological record can help us to learn about issues we care about today in ways that we can't do using the data available to us from modern societies," Ortman said.

The good dishes

The research is an offshoot of an effort that Ortman leads called the Social Reactors Project, which has explored patterns of growth in civilizations from ancient Rome to the Incan world.

It's an attempt to chase down an idea first proposed in the 18th century by Adam Smith, often known as the father of modern economics. In The Wealth of Nations, Smith made the case for the fundamental benefits of market size--that if you make it easier for more people to trade, the economy will grow.

Just look at any city in the U.S. where you might find a hair salon next to a bakery next to a doggie daycare.

"As people interact more frequently, a person can make and do fewer things themselves and get more of what they need from their social contacts," Ortman said.

The problem, he explained, is that such "agglomeration-driven" growth is difficult to isolate in today's big and complex cities. The same isn't true for the Rio Grande Valley.

Before the arrival of the Spaniards in the 16th century, hundreds of villages spanned the region near what is now Santa Fe. These settlements ranged in size from a few dozen residents to as many as 3,000 people, most of whom made their living by growing crops like maize and cotton.

Such a subsistence lifestyle didn't mean that these communities were simple.

"The traditional view in ancient history was that economic growth didn't happen until the onset of the industrial revolution," Ortman said.

He and Lobo decided to put that assumption to the test. The duo pored through an exhaustive database of archaeological finds from the region--capturing everything from the number and size of rooms in Pueblo communities to the pottery from rubbish heaps.

They unearthed a clear trend: When villages got more populous, their residents seemed to get better off on average--exactly as Smith predicted. Living spaces grew in size and families collected more painted pottery.

"You might think of it as more sets of dishes for sharing meals together," Ortman said.

Social connection

That growth, the team discovered, also seemed to follow a pattern that researchers on the Social Reactors Project have seen in a range of civilizations throughout history. Every time villages doubled in size, markers of economic growth increased by about 16% on average.

Ortman said that the effect doesn't happen in the same way everywhere. Factors like inequality and racism, for example, can keep urban residents from working together even when they live in cramped spaces.

But, Ortman added, these Pueblo communities hold an important lesson for modern-day societies: the more people can connect with others, the more prosperous they become.

"All other things being equal, urbanization should lead to improvements in the material conditions of life for people everywhere," he said. "We suspect this is why the world continues to urbanize, despite all of the associated problems."

A well-trained athlete sprinting 100 yards performs a highly stereotyped, repetitive motor pattern. Neuroscientists understand that these rhythmic motor programs, such as walking, swimming and running, are produced by neural circuitry that generates repetitive patterns that are similar from cycle to cycle. Over a century ago, experiments on spinal cord led to the proposal that a simple neural network can produce such a rhythmic oscillatory firing pattern. These oscillatory networks are now known as central pattern generators. In analyzing the production of these firing patterns by central pattern generators, neuroscientists traditionally have focused on experimental preparations where the rhythmic output is nearly identical from cycle to cycle. However, for an animal or person to be successful, the motor program must be adaptable. The motor pattern of an individual walking on a wet slippery surface differs from the motor pattern of an individual walking on a dry smooth surface. The motor pattern of an individual eating granola with nuts and dried berries differs from the motor pattern of an individual eating plain oatmeal.

Generating variable motor programs is also initially essential to enable future learning. During development, a child learns to produce a mature motor pattern by beginning with a highly variable pattern. Early on, a toddler’s walking is very unstable, but before long they can walk with a consistent gait. The same process goes on when an older individual learns a new activity, such as swimming or ice skating. Gradually, the nervous system comes to consistently produce a more successful motor program. Birds that learn song go through a similar progression – early on the song is variable, but gradually it becomes more stereotyped or consistent.

How does the nervous system generate variable motor programs? Recently, researchers at Nanjing University in Nanjing and Peng Cheng Laboratory in Shenzhen, in collaboration with colleagues at Mount Sinai in New York, studied the motor program for feeding in the simple nervous system of the marine snail Aplysia. These investigators identified an important fundamental mechanism by which variability in the strength of excitatory inputs to the feeding central pattern generator results in flexibility in the feeding motor program. When one neuron provides input to another, it often induces an electrical response, i.e., a postsynaptic potential. It has long been recognized that single postsynaptic potentials are generally subthreshold for triggering a postsynaptic response. Furthermore, postsynaptic potential amplitude generally varies substantially over time, even over less than a tenth of a second. Although this might seem suboptimal, the authors demonstrate that under certain conditions, this variability can translate into behavioral flexibility.

The marine snail Aplysia has relatively few nerve cells, and the same individual nerve cells have characteristic properties and can be re-identified from one individual animal to another. Taking advantage of their ability to work with identified neurons, the authors demonstrated that synaptic inputs from either of two upstream identified neurons can drive activity in a pivotal central pattern generator neuron, which has a low level of excitability. The input from one upstream neuron is variable and quite weak and does not always cause the pattern generator neuron to fire. Consequently, motor programs that are induced when this upstream cell is activated are variable. In contrast, although the input from the second upstream neuron is similarly variable, it is substantially stronger. Consequently, the pattern generator neuron is reliably excited and the motor output is much less variable. Thus, whether the circuit produces a stereotyped or a variable pattern is determined by which upstream neuron drives activity. Elegant computational modeling studies reinforced the physiological findings and uncovered additional insights that clarified the specific contributions of synaptic variability and strength to the different degree of motor program variability.

In summary, the authors demonstrate that variability in the synaptic inputs combined with the low level of excitability of the central pattern generator neuron provides the snail with the ability to switch to a more variable behavioral pattern. Future research will reveal whether similar shifts in the variability of motor programs in mammals can be explained by a similar mechanism.

CHAMPAIGN, Ill. -- The livelihoods of millions of people living along the world's biggest river systems are under threat by a range of stressors caused by the daily economic, societal and political activity of humans - in addition to the long-term effects of climate change, researchers report.

A new paper by University of Illinois at Urbana-Champaign geology and geography professor Jim Best and University of Southampton professor Stephen Darby takes a big-picture approach to review the health and resiliency of the world's large river systems, their deltas and their vulnerability to extreme events.

The article is published in the journal One Earth.

Rivers respond to changes in the environment through self-adjusting processes of erosion and sedimentation, the researchers said. When not stressed by extreme events like flooding or drought, these responses typically allow rivers to absorb change. However, data from many new studies now suggest that the world's great waterways are becoming more vulnerable as the effects of human activity and climate change combine and compound.

"Climate change is of huge importance in terms of changing flood or drought frequency and intensity," Best said. "However, there is a range of other stressors affecting big rivers such as damming, sediment mining, pollution, water diversions, groundwater extraction and the introduction of nonnative species - all of which affect rivers on a timescale that has much more immediate consequences."

For example, the team reviewed past research on the drivers of flooding in the Mekong River Delta in Southeast Asia, which supports about 18 million people and a vast rice agricultural area. These studies suggest that delta subsidence - or sinking - because of groundwater extraction beneath the delta is now more of a problem, as the region receives far less sediment because of sediment trapping behind upstream dams and large-scale mining of sand from the bed of the delta's channels.

"The scale of the effects of sediment starvation and subsidence in driving increased flood risk is currently far greater than sea-level rise generated by global climate change," Best said. "But when all of these pressures are combined, there is now a real risk that we could cross a major tipping point in the next 10-20 years."

Politics also play a significant role in the health and resiliency of the world's major river systems, the paper reports. For example, the current COVID-19 pandemic is influencing regulatory enforcement of pollution monitoring in the United States, enabling polluters to avoid penalties if they argue violations are a result of the pandemic.

"We have seen evidence of the effect of these types of political and societal shocks on river systems in the past, too," Best said. "The stresses from the Gulf War led to increased river pollution in the Tigris-Euphrates River Basin, a situation that was also compounded by upstream damming in Turkey."

The researchers stress an urgent need for governance at the local level across to the international level to confront these issues effectively.

"There are some things we as scientists can do on the monitoring end of this issue, but it will demand collaboration and trust between nations for it to make a difference," Best said. "We can't take our eye off the ball - we've just got to devote more attention to these more frequent, shorter-timescale stressors. It's far from being just about climate change."

A new study finds that clinicians can use patient data, such as a history of co-occurring health conditions and medication, to predict the 5- and 10-year life expectancy of older people with diabetes.

The ability to make such predictions, the researchers say, may help clinicians and patients develop personalized treatment goals that balance risks and benefits.

The results appear June 19 in the journal Diabetes Care.

Drs. Kevin Griffith and Paul Conlin of the VA Boston Healthcare System led the study.

The researchers embarked on the study knowing that federal and professional society clinical practice guidelines recommend that treatment goals be individualized for older adults with diabetes.

Key factors that impact diabetes treatment goals include co-occurring health conditions (such as severe mental illness or cancer); diabetes complications, such as chronic kidney disease and heart failure; co-existing conditions, and life expectancy.

The benefits of lower blood sugar can take several years to occur. For some older adults with limited life expectancy, the treatment burden may not be worth the benefits.

"But the guidelines don't give doctors guidance for how to decide whether or not people fall into these different bins for life expectancy," Griffith noted. "Furthermore, clinicians are notoriously inaccurate in predicting life expectancy, with studies frequently showing both over- and underestimating. We developed models with high predictive validity of future mortality in a large sample of older Veterans with diabetes."

Conlin added: "Our goal was to use the best available information to inform decision-making in setting glucose control targets. Doctors and patients, of course, can then use their own judgment to make a decision."

The researchers reviewed the electronic health record data of more than 275,000 Veterans with diabetes who were at least 65 years old.

Using predictive modeling techniques, they identified 37 predictive factors that have previously been linked to, or are suspected to impact, mortality in older adults with diabetes: demographic variables (age, sex, marital status); prescriptions for insulin or sulfonylureas, a class of diabetes drugs; and biomarkers such as hemoglobin A1c, blood pressure, body mass index, and levels of cholesterol and triglycerides, a type of fat found in the blood.

The 37 predictive factors also included inpatient and outpatient history and more than 20 medical procedures and co-occurring health disorders.

The results placed patients in three time frames for expected death: within five years, 5 to 10 years, and more than 10 years.

The final predictive models for 5- and 10-year mortality had high predictive validity and demonstrate the importance of several individual and condition-specific characteristics that may inform clinicians and patients about life expectancy.

"We aren't saying, for example, that any of these risk factors result in decreased life expectancy," Griffith commented. "However, the more risk factors that individuals have, the greater the risk of higher mortality over time."

The researchers suggested that these results could assist clinicians in using shared decision-making to establish A1c target ranges that balance treatment benefits and risks.

The study has some important limitations. Since the analysis was based on a Veteran cohort and on older adults, it is possible that results may not generalize to other settings. However, the predictive models can be evaluated by other health care systems that have similar electronic health care records.

It is also possible that recent changes in the approach to older adults with diabetes, such as less emphasis on tight blood sugar control, as well as treatment advances especially for congestive heart failure and chronic kidney disease, could affect model results.

Conlin said he hopes that in the future, predictive models will come into use at the point of care to help clinicians and patients mutually set diabetes treatment goals. However, he noted that the study findings are immediately relevant to clinicians.

"Our results identify multiple common conditions that can easily be identified in clinical practice and assist clinicians in shared decision-making with patients, which is a key recommendation of the VA/DoD Diabetes Guidelines," said Conlin.

On a related note, VA recently launched an Understand Your Diabetes Numbers campaign to assist patients with treatment decisions.

Early signs of being more susceptible to type 2 diabetes as an adult can be seen in children as young as 8 years old, decades before it is likely to be diagnosed, according to a new study published in Diabetes Care today [19 June 2020].

The research looked at the effects of a genetic risk score for developing type 2 diabetes as an adult on metabolism measured from blood samples taken from the participants in the study when they were aged 8, 16, 18, and 25 years.

The study tracked over 4,000 participants in the Children of the 90s - a health study established at the University of Bristol in the early 1990s. Researchers combined genetic information with an approach called 'metabolomics', which involves measuring many small molecules in a blood sample, to try and identify patterns that are specific to early stages of type 2 diabetes development.

One of the leading investigators Dr Joshua Bell explained: "We knew that diabetes doesn't develop overnight. What we didn't know is how early in life the first signs of disease activity become visible and what these early signs look like. We addressed these by looking at the effects of being more genetically prone to type 2 diabetes in adulthood on measures of metabolism taken across early life. This would not have been possible without the Children of the 90s study.

"Diabetes is most common in older age, but we see signs of disease susceptibility very early on - about 50 years before it's usually diagnosed. Knowing what these early signs look like widens our window of opportunity to intervene much earlier and stop diabetes before it becomes harmful."

The study was conducted among young people who were generally free of type 2 diabetes and other chronic diseases to see how early in life the effects of being more susceptible to adult diabetes become visible. In particular, certain types of HDL cholesterol were reduced at age 8 before other types of cholesterol including LDL were raised; inflammation and amino acids were also elevated by 16 and 18 years old. These differences widened over time.

Dr Bell continued: "We're talking about the effects of susceptibility rather than of clinical disease itself. This does not mean that young people 'already have adult diabetes'; these are subtle differences in the metabolism of young people who are more prone to developing it later in life.

"These findings help reveal the biology of how diabetes unfolds and what features may be targetable much earlier on to prevent the onset of disease and its complications. This is important because we know that the harmful effects of blood glucose, such as on heart disease, are not exclusive to people with diagnosed diabetes but extend to a smaller degree to much of the population."

In a paper published by the Royal Society, a team of Bristol researchers observed the exploratory behaviour of ants to inform the development of a more efficient mathematical sampling technique.

Animals like ants have the challenge of exploring their environment to look for food and potential places to live. With a large group of individuals, like an ant colony, a large amount of time would be wasted if the ants repeatedly explored the same empty areas.

The interdisciplinary team from the University of Bristol's Faculties of Engineering and Life Sciences, predicted that the study species - the 'rock ant' - uses some form of chemical communication to avoid exploring the same space multiple times.

Lead author, Dr Edmund Hunt, said:

"This would be a reversal of the Hansel and Gretel story - instead of following each other's trails, they would avoid them in order to explore collectively.

"To test this theory, we conducted an experiment where we let ants explore an empty arena one by one. In the first condition, we cleaned the arena between each ant so they could not leave behind any trace of their path. In the second condition, we did not clean between ants. The ants in the second condition (no cleaning) made a better exploration of the arena - they covered more space."

In mathematics, a probability distribution describes how likely are each of a set of different possible outcomes: for example, the chance that an ant will find food at a certain place. In many science and engineering problems, these distributions are highly complex, and they do not have a neat mathematical description. Instead, one must sample from it to obtain a good approximation: with a desire to avoid sampling too much from unimportant (low probability) parts of the distribution.

The team wanted to find out if adopting an ant-inspired approach would hasten this sampling process.

"We predicted that we could simulate the approach adopted by the ants in the mathematical sampling problem, by leaving behind a 'negative trail' of where has already been sampled. We found that our ant-inspired sampling method was more efficient (faster) than a standard method which does not leave a memory of where has already been sampled," said Dr Hunt.

These findings contribute toward an interesting parallel between the exploration problem confronted by the ants, and the mathematical sampling problem of acquiring information. This parallel can inform our fundamental understanding of what the ants have evolved to do: acquire information more efficiently.

"Our ant-inspired sampling method may be useful in many domains, such as computational biology, for speeding up the analysis of complex problems. By describing the ants' collective behaviour in informational terms, it also allows us to quantify how helpful are different aspects of their behaviour to their success. For example, how much better do they perform when their pheromones are not cleaned away. This could allow us to make predictions about which behavioural mechanisms are most likely to be favoured by natural selection."