New study explains why you should look at your food before casting judgment

 The order in which your senses interact with food has a tremendous impact on how much you like it. That's the premise of a new study led by the University of South Florida (USF). The findings published in the Journal of Consumer Psychology show that food tastes better if you see it before smelling it.

Researchers came to this conclusion following four experiments involving cookies, fruit snacks and lemonade. In the first study, nearly 200 participants interacted with the food, each item wrapped in an opaque versus a transparent package. The team administered each item in different orders: visual before scent, scent before visual, only visual and only scent. Despite being the same product, participants rated the strawberry-flavored fruit snacks packaged in an envelope as tasting better when they could see the item before smelling it compared to their counterparts who smelled the item before seeing it. Researchers experienced the same results when they tested taste perception of the cookies.

"This is because being able to see a food item before smelling it helps in processing the scent cue with greater ease, which in turn enhances the food taste perception," said Dipayan Biswas, Frank Harvey Endowed Professor of Marketing at USF. "Basically, scents play a very critical role in influencing taste perceptions; however, interestingly, people can process a scent better in their brains when the scent is preceded by a corresponding visual cue, such as color."

The research team, which includes collaborators from Columbia University and the University of Rhode Island, experienced the same results when it focused on beverages. Researchers poured the same, yellow-colored lemonade into lidded clear plastic cups and lidded solid-colored plastic cups that were splashed with artificial lemon-scented oil. Similarly, participants preferred the drink that they could see before smelling and they drank more of it. Researchers tested consumption by purposely leaving the drinks in front of participants as they undertook an unrelated task. Additionally, the researchers provided the same drinks with the addition of odorless purple food coloring, a color typically not associated with lemon flavor. In this case, it had a negative effect on taste perception, as the color contradicted expectations.

"We tested this to get a better understanding of how the human sensory processing system evaluates a sequence of visual and scent-related cues," Biswas said.

These findings are highly beneficial to supermarkets and Biswas suggests they consider installing more glass cases to help facilitate a customer's ability to see a food item at a distance before smelling it. He suggests strategic displays with photos or samples be visible prior to entering a business, helping strengthen taste perceptions of food items, which can increase sales and overall impression of the business. Biswas emphasizes that the theory also applies to pantry food items, such as potato chips, which may attract more interest if they were sold in transparent packaging.

Read more at Science Daily

Brain regions responsible for intoxicating effects of alcohol

The slurred speech, poor coordination, and sedative effects of drinking too much alcohol may actually be caused by the breakdown of alcohol products produced in the brain, not in the liver as scientists currently think. That is the finding of a new study led by researchers from the University of Maryland School of Medicine (UMSOM) and the National Institute on Alcohol Abuse and Alcoholism. It was published recently in the journal Nature Metabolism and provides new insights into how alcohol may affect the brain and the potential for new treatments to treat alcohol misuse.

It is well known that the liver is the major organ that metabolizes alcohol, using the enzyme alcohol dehydrogenase to convert alcohol into a compound called acetaldehyde. Acetaldehyde, which has toxic effects, is quickly broken down into a more benign substance called acetate. This occurs through a different enzyme called acetaldehyde dehydrogenase 2 (ALDH2). Until now, alcohol and acetaldehyde, produced by the liver, have been considered important players in triggering the cognitive impairment associated with imbibing. Acetate, on the other hand, was considered relatively unimportant in producing effects like motor impairment, confusion, and slurred speech. Researchers also did not know which brain region or particular brain cells were most important for alcohol metabolism.

To learn more about the role played by the brain in alcohol metabolism, the researchers measured the distribution of ALDH2 enzyme in the cerebellum, using magnetic resonance (MR) scanners in both mice and in human tissue. They observed that ALDH2 was expressed in the cerebellum, in a type of nerve cell called an astrocyte, in both human brain tissue and in living mice.

The researchers found that this enzyme controlled the conversion of acetaldehyde into acetate in the brain. They also found alcohol-induced cellular and behavioral effects in specific regions of the brain where this enzyme was expressed. Acetate was found to interact with the brain messenger chemical called GABA, which is known to decrease activity in the nervous system. This decreased activity can lead to drowsiness, impair coordination, and lower normal feelings of inhibition.

"We found ALDH2 was expressed in cells known as astrocytes in the cerebellum, a brain region that controls balance and motor coordination," said Qi Cao, PhD, Assistant Professor of Diagnostic Radiology and Nuclear Medicine at the University of Maryland School of Medicine. "We also found that when ALDH2 was removed from these cells, the mice were resistant to motor impairment inducted by alcohol consumption."

Su Xu, PhDHe and his team also found the enzyme ALDH2 in other brain regions responsible for emotional regulation and decision-making (both impaired by excess alcohol consumption), including in the hippocampus, amydala, and prefrontal cortex.

These findings suggest that certain brain regions are important for alcohol metabolism and that abnormalities in the enzyme production in these brain regions can lead to detrimental effects associated with alcohol misuse. They also suggest that acetate produced in the brain and in the liver differ in their ability to affect motor and cognitive function.

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Satellite map of human pressure on land provides insight on sustainable development

 The coronavirus pandemic has led researchers to switch gears or temporarily abandon projects due to health protocols or not being able to travel. But for Patrick Keys and Elizabeth Barnes, husband and wife scientists at Colorado State University, this past year led to a productive research collaboration.

They teamed up with Neil Carter, assistant professor at the University of Michigan, on a paper published in Environmental Research Letters that outlines a satellite-based map of human pressure on lands around the world.

Keys, lead author and a research scientist in CSU's School of Global Environmental Sustainability, said the team used machine learning to produce the map, which reveals where abrupt changes in the landscape have taken place around the world. The map shows a near-present snapshot of effects from deforestation, mining, expanding road networks, urbanization and increasing agriculture.

"The map we've developed can help people understand important challenges in biodiversity conservation and sustainability in general," said Keys.

This type of a map could be used to monitor progress for the United Nations Sustainable Development Goal 15 (SDG15), "Life on Land," which aims to foster sustainable development while conserving biodiversity.

Eight algorithms to encompass data from around the world

Barnes, an associate professor in CSU's Department of Atmospheric Science, did the heavy lifting on the data side of the project.

While staggering parenting duties with Keys, she wrote code like never before, working with trillions of data points and training up to eight separate algorithms to cover different parts of the world. She then merged the algorithms to provide a seamless classification for the whole planet.

At first, the two researchers had to learn to speak the other's work language.

"Pat initially had an idea for this research, and I said, 'Machine learning doesn't work that way,'" said Barnes.

She then sketched out the components with him: The input is something we want to be able to see from space, like a satellite image; and the output is some measure of what humans are doing on Earth. The middle part of the equation was machine learning.

Keys said what Barnes designed is a convolutional neural network, which is commonly used for interpreting images. It's similar to how Facebook works when the site suggests tagging friends in a photo.

"It's like our eyes and our brains," he said.

In developing the algorithm, they used existing data that classified human impacts on the planet, factors like roads and buildings, and grazing lands for livestock and deforestation. Then, the convolutional neural network learned how to accurately interpret satellite imagery, based on this existing data.

From an analysis of one country, to the world

The researchers started with Indonesia, a country that has experienced rapid change over the last 20 years. By the end of the summer, after they were confident about what they identified in Indonesia using machine learning, Keys suggested that they look at the entire globe.

"I remember telling him it's not possible," said Barnes. "He knows whenever I say that, I will go back and try and make it work. A week later, we had the whole globe figured out."

Barnes said using machine learning is not fool-proof, and it requires some follow-up to ensure that data are accurate.

"Machine learning will always provide an answer, whether it's garbage or not," she explained. "Our job as scientists is to determine if it is useful."

Keys spent many nights on Google Earth reviewing over 2,000 places on the globe in the year 2000 and then compared those sites with 2019. He noted changes and confirmed the data with Barnes.

The research team also did a deeper dive into three countries -- Guyana, Morocco and Gambia -to better understand what they found.

In the future, when new satellite data is available, Keys said the team can quickly generate a new map.

"We can plug that data into this now-trained neural network and generate a new map," he said. "If we do that every year, we'll have this sequential data that shows how human pressure on the landscape is changing."

Keys said the research project helped lift his spirits over the last year.

Read more at Science Daily

Reliably measuring oxygen deficiency in rivers or lakes

 When wastewater from villages and cities flows into rivers and lakes, large quantities of fats, proteins, sugars and other carbon-containing, organic substances wind up in nature together with the fecal matter. These organic substances are broken down by bacteria that consume oxygen. The larger the volume of wastewater, the better the bacteria thrive. This, however, means the oxygen content of the water continues to decrease until finally the fish, muscles or worms literally run out of air. This has created low-oxygen death zones in many rivers and lakes around the world.

No gold standard for measurements until now

In order to measure how heavily the waters are polluted with organic matter from feces, government bodies and environmental researchers regularly take water samples. One widely used measurement method uses a chemical reaction to determine the content of organic substances. As an international team of scientists now shows, this established method provides values from which the actual degree of the water pollution can hardly be derived. Prof. Helmuth Thomas, Director of Hereon's Institute of Carbon Cycles is also a contributor to the study, which has now been published in the scientific journal Science Advances. "In the paper, we are therefore also introducing a new method for making the measurements much more reliable in the future," he says.

Using the conventional measurement method, water samples are mixed with the chemicals permanganate or dichromate. These are especially reactive and break down all organic substances in a short time. The quantity of consumed permanganates or dichromates can then be used to determine how much organic substance was contained in the water sample. Experts refer to this measurement as "chemical oxygen demand," COD. The problem with the COD measurements is that they do not differentiate between the organic substances that wind up in the water with the sewage, and those that arise naturally -- such as lignin and humic acids -- which are released when wood decays. This means that the water pollution can hardly be distinguished from the natural content of organic substances. "For the Han River in South Korea, for example, we have shown that the pollution with organic substances from wastewater in the past twenty-five years has decreased. The COD measurements, however, still show high values as they were before," says Helmuth Thomas, "because here the natural substances make up a large portion of the organic matter in the water."

Complicated biological analysis

But how can the actual pollution be measured more reliably? A biological measurement method has been established here for decades, but it is much more complex than the COD method and is therefore used more seldomly by government bodies and research institutions. In this case, a water sample is taken from the river or lake and the oxygen content of the water is measured as an initial value. Another "parallel sample" is immediately sealed airtight. Then this water sample rests for five days. During this time, the bacteria break down the organic substance, whereby they gradually consume the oxygen in the water. After five days, the container is opened and the oxygen is measured. If the water contains a great deal of organic matter, then the bacteria were particularly active. The oxygen consumption was then correspondingly high. Experts refer to the "biological oxygen demand" (BOD) in this measurement. "The BOD measurement is far more precise than the COD because the bacteria preferentially break down the small organic molecules from the wastewater but leave the natural ones, such as lignin, untouched," says Thomas. Nevertheless, the BOD measurement has its disadvantages, too. On the one hand, the BOD measurement takes five days, while the COD value is available after a few minutes. On the other, while filling, storing and measuring the water samples, meticulous care must be taken to ensure that no oxygen from the ambient air winds up in the sample and falsifies the measurement value. "Only a few people with a great deal of laboratory experience have mastered how to entirely handle the BOD measurement," says Thomas. "Therefore, government bodies and researchers even today still prefer the COD despite its greater uncertainties."

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Mindfulness can make you selfish

 Mindfulness is big business. Downloads of mindfulness apps generate billions of dollars annually in the U.S., and their popularity continues to rise. In addition to what individual practitioners might have on their phones, schools and prisons along with 1 in 5 employers currently offer some form of mindfulness training.

Mindfulness and meditation are associated with reducing stress and anxiety, while increasing emotional well-being. Plenty of scholarship supports these benefits. But how does mindfulness affect the range of human behaviors -- so-called prosocial behaviors -- that can potentially help or benefit other people? What happens when the research looks outwardly at social effects of mindfulness rather than inwardly at its personal effects?

It's within the area of prosocial behaviors that a new paper by University at Buffalo researchers demonstrates the surprising downsides of mindfulness, while offering easy ways to minimize those consequences -- both of which have practical implications for mindfulness training.

"Mindfulness can make you selfish," says Michael Poulin, PhD, an associate professor of psychology in the UB College of Arts and Sciences and the paper's lead author. "It's a qualified fact, but it's also accurate.

"Mindfulness increased prosocial actions for people who tend to view themselves as more interdependent. However, for people who tend to view themselves as more independent, mindfulness actually decreased prosocial behavior."

The results sound contradictory given the pop culture toehold of mindfulness as an unequivocal positive mental state. But the message here isn't one that dismantles the effectiveness of mindfulness.

"That would be an oversimplification," says Poulin, an expert in stress, coping and prosocial engagement. "Research suggests that mindfulness works, but this study shows that it's a tool, not a prescription, which requires more than a plug-and-play approach if practitioners are to avoid its potential pitfalls."

The findings will appear in a forthcoming issue of the journal Psychological Science.

Poulin says independent versus interdependent mindsets represent an overarching theme in social psychology. Some people think of themselves in singular or independent terms: "I do this." While others think of themselves in plural or interdependent terms: "We do this."

There are also cultural differences layered on top of these perspectives. People in Western nations most often think of themselves as independent, whereas people in East Asian countries more often think of themselves as interdependent. Mindfulness practices originated in East Asian countries, and Poulin speculates that mindfulness may be more clearly prosocial in those contexts. Practicing mindfulness in Western countries removes that context.

"Despite these individual and cultural differences, there is also variability within each person, and any individual at different points in time can think of themselves either way, in singular or plural terms," says Poulin.

The researchers, which included Shira Gabriel, PhD, a UB associate professor of psychology, C. Dale Morrison and Esha Naidu, both UB graduate students, and Lauren M. Ministero, PhD, a UB graduate student at the time of the research who is now a senior behavioral scientist at the MITRE Corporation, used a two-experiment series for their study.

First, they measured 366 participants' characteristic levels of independence versus interdependence, before providing mindfulness instruction or a mind wandering exercise to the control group. Before leaving, participants were told about volunteer opportunities stuffing envelopes for a charitable organization.

In this experiment, mindfulness led to decreased prosocial behavior among those who tended to be independent.

In the next experiment, instead of having a trait simply measured, 325 participants were encouraged to lean one way or the other by engaging in a brief but effective exercise that tends to make people think of themselves in independent or interdependent terms.

The mindfulness training and control procedures were the same as the first experiment, but in this case, participants afterwards were asked if they would sign up to chat online with potential donors to help raise money for a charitable organization.

Mindfulness made those primed for independence 33% less likely to volunteer, but it led to a 40% increase in the likelihood of volunteering to the same organization among those primed for interdependence. The results suggest that pairing mindfulness with instructions explaining how to make people think of themselves in terms of their relationships and communities as they're engaging in mindfulness exercises may allow them to see both positive personal and social outcomes.

Read more at Science Daily

Telescopes unite in unprecedented observations of famous black hole

 In April 2019, scientists released the first image of a black hole in galaxy M87 using the Event Horizon Telescope (EHT). However, that remarkable achievement was just the beginning of the science story to be told.

Data from 19 observatories released today promise to give unparalleled insight into this black hole and the system it powers, and to improve tests of Einstein's General Theory of Relativity.

"We knew that the first direct image of a black hole would be groundbreaking," says Kazuhiro Hada of the National Astronomical Observatory of Japan, a co-author of a new study published in The Astrophysical Journal Letters that describes the large set of data. "But to get the most out of this remarkable image, we need to know everything we can about the black hole's behavior at that time by observing over the entire electromagnetic spectrum."

The immense gravitational pull of a supermassive black hole can power jets of particles that travel at almost the speed of light across vast distances. M87's jets produce light spanning the entire electromagnetic spectrum, from radio waves to visible light to gamma rays. This pattern is different for each black hole. Identifying this pattern gives crucial insight into a black hole's properties -- for example, its spin and energy output -- but is a challenge because the pattern changes with time.

Scientists compensated for this variability by coordinating observations with many of the world's most powerful telescopes on the ground and in space, collecting light from across the spectrum. These 2017 observations were the largest simultaneous observing campaign ever undertaken on a supermassive black hole with jets.

Three observatories managed by the Center for Astrophysics | Harvard & Smithsonian participated in the landmark campaign: the Submillimeter Array (SMA) in Hilo, Hawaii; the space-based Chandra X-ray Observatory; and the Very Energetic Radiation Imaging Telescope Array System (VERITAS) in southern Arizona.

Beginning with the EHT's now iconic image of M87, a new video takes viewers on a journey through the data from each telescope. Each consecutive frame shows data across many factors of ten in scale, both of wavelengths of light and physical size.

The sequence begins with the April 2019 image of the black hole. It then moves through images from other radio telescope arrays from around the globe (SMA), moving outward in the field of view during each step. Next, the view changes to telescopes that detect visible light, ultraviolet light, and X-rays (Chandra). The screen splits to show how these images, which cover the same amount of the sky at the same time, compare to one another. The sequence finishes by showing what gamma-ray telescopes on the ground (VERITAS), and Fermi in space, detect from this black hole and its jet.

Each telescope delivers different information about the behavior and impact of the 6.5-billion-solar-mass black hole at the center of M87, which is located about 55 million light-years from Earth.

"There are multiple groups eager to see if their models are a match for these rich observations, and we're excited to see the whole community use this public data set to help us better understand the deep links between black holes and their jets," says co-author Daryl Haggard of McGill University in Montreal, Canada.

The data were collected by a team of 760 scientists and engineers from nearly 200 institutions, spanning 32 countries or regions, and using observatories funded by agencies and institutions around the globe. The observations were concentrated from the end of March to the middle of April 2017.

"This incredible set of observations includes many of the world's best telescopes," says co-author Juan Carlos Algaba of the University of Malaya in Kuala Lumpur, Malaysia. "This is a wonderful example of astronomers around the world working together in the pursuit of science."

The first results show that the intensity of the light produced by material around M87's supermassive black hole was the lowest that had ever been observed. This produced ideal conditions for viewing the 'shadow' of the black hole, as well as being able to isolate the light from regions close to the event horizon from those tens of thousands of light-years away from the black hole.

The combination of data from these telescopes, and current (and future) EHT observations, will allow scientists to conduct important lines of investigation into some of astrophysics' most significant and challenging fields of study. For example, scientists plan to use these data to improve tests of Einstein's Theory of General Relativity. Currently, uncertainties about the material rotating around the black hole and being blasted away in jets, in particular the properties that determine the emitted light, represent a major hurdle for these General Relativity tests.

A related question that is addressed by today's study concerns the origin of energetic particles called "cosmic rays," which continually bombard the Earth from outer space. Their energies can be a million times higher than what can be produced in the most powerful accelerator on Earth, the Large Hadron Collider. The huge jets launched from black holes, like the ones shown in today's images, are thought to be the most likely source of the highest energy cosmic rays, but there are many questions about the details, including the precise locations where the particles get accelerated. Because cosmic rays produce light via their collisions, the highest-energy gamma rays can pinpoint this location, and the new study indicates that these gamma-rays are likely not produced near the event horizon -- at least not in 2017. A key to settling this debate will be comparison to the observations from 2018, and the new data being collected this week.

"Understanding the particle acceleration is really central to our understanding of both the EHT image as well as the jets, in all their 'colors'," says co-author Sera Markoff from the University of Amsterdam. "These jets manage to transport energy released by the black hole out to scales larger than the host galaxy, like a huge power cord. Our results will help us calculate the amount of power carried, and the effect the black hole's jets have on its environment."

The release of this new treasure trove of data coincides with the EHT's 2021 observing run, which leverages a worldwide array of radio dishes, the first since 2018. Last year's campaign was canceled because of the COVID-19 pandemic, and the previous year was suspended because of unforeseen technical problems. This very week, for six nights, EHT astronomers are targeting several supermassive black holes: the one in M87 again, the one in our Galaxy called Sagittarius A*, and several more distant black holes. Compared to 2017, the array has been improved by adding three more radio telescopes: the Greenland Telescope, the Kitt Peak 12-meter Telescope in Arizona, and the NOrthern Extended Millimeter Array (NOEMA) in France.

"With the release of these data, combined with the resumption of observing and an improved EHT, we know many exciting new results are on the horizon," says co-author Mislav Balokovi? of Yale University.

Read more at Science Daily

New approach to centuries-old 'three-body problem'

 The "three-body problem," the term coined for predicting the motion of three gravitating bodies in space, is essential for understanding a variety of astrophysical processes as well as a large class of mechanical problems, and has occupied some of the world's best physicists, astronomers and mathematicians for over three centuries. Their attempts have led to the discovery of several important fields of science; yet its solution remained a mystery.

At the end of the 17th century, Sir Isaac Newton succeeded in explaining the motion of the planets around the sun through a law of universal gravitation. He also sought to explain the motion of the moon. Since both the earth and the sun determine the motion of the moon, Newton became interested in the problem of predicting the motion of three bodies moving in space under the influence of their mutual gravitational attraction (see attached illustration), a problem that later became known as "the three-body problem."

However, unlike the two-body problem, Newton was unable to obtain a general mathematical solution for it. Indeed, the three-body problem proved easy to define, yet difficult to solve.

New research, led by Professor Barak Kol at Hebrew University of Jerusalem's Racah Institute of Physics, adds a step to this scientific journey that began with Newton, touching on the limits of scientific prediction and the role of chaos in it.

The theoretical study presents a novel and exact reduction of the problem, enabled by a re-examination of the basic concepts that underlie previous theories. It allows for a precise prediction of the probability for each of the three bodies to escape the system.

Following Newton and two centuries of fruitful research in the field including by Euler, Lagrange and Jacobi, by the late 19th century the mathematician Poincare discovered that the problem exhibits extreme sensitivity to the bodies' initial positions and velocities. This sensitivity, which later became known as chaos, has far-reaching implications -- it indicates that there is no deterministic solution in closed-form to the three-body problem.

In the 20th century, the development of computers made it possible to re-examine the problem with the help of computerized simulations of the bodies' motion. The simulations showed that under some general assumptions, a three-body system experiences periods of chaotic, or random, motion alternating with periods of regular motion, until finally the system disintegrates into a pair of bodies orbiting their common center of mass and a third one moving away, or escaping, from them.

The chaotic nature implies that not only is a closed-form solution impossible, but also computer simulations cannot provide specific and reliable long-term predictions. However, the availability of large sets of simulations led in 1976 to the idea of seeking a statistical prediction of the system, and in particular, predicting the escape probability of each of the three bodies. In this sense, the original goal, to find a deterministic solution, was found to be wrong, and it was recognized that the right goal is to find a statistical solution.

Determining the statistical solution has proven to be no easy task due to three features of this problem: the system presents chaotic motion that alternates with regular motion; it is unbounded and susceptible to disintegration. A year ago, Racah's Dr. Nicholas Stone and his colleagues used a new method of calculation and, for the first time, achieved a closed mathematical expression for the statistical solution. However, this method, like all its predecessor statistical approaches, rests on certain assumptions. Inspired by these results, Kol initiated a re-examination of these assumptions.

The infinite unbounded range of the gravitational force suggests the appearance of infinite probabilities through the so-called infinite phase-space volume. To avoid this pathology, and for other reasons, all previous attempts postulated a somewhat arbitrary "strong interaction region," and accounted only for configurations within it in the calculation of probabilities.

The new study, recently published in the scientific journal Celestial Mechanics and Dynamical Astronomy, focuses on the outgoing flux of phase-volume, rather than the phase-volume itself. Since the flux is finite even when the volume is infinite, this flux-based approach avoids the artificial problem of infinite probabilities, without ever introducing the artificial strong interaction region.

The flux-based theory predicts the escape probabilities of each body, under a certain assumption. The predictions are different from all previous frameworks, and Prof. Kol emphasizes that "tests by millions of computer simulations shows strong agreement between theory and simulation." The simulations were carried out in collaboration with Viraj Manwadkar from the University of Chicago, Alessandro Trani from the Okinawa Institute in Japan, and Nathan Leigh from University of Concepcion in Chile. This agreement proves that understanding the system requires a paradigm shift and that the new conceptual basis describes the system well. It turns out, then, that even for the foundations of such an old problem, innovation is possible.

Read more at Science Daily

Unlocking richer intracellular recordings

 Behind every heartbeat and brain signal is a massive orchestra of electrical activity. While current electrophysiology observation techniques have been mostly limited to extracellular recordings, a forward-thinking group of researchers from Carnegie Mellon University and Istituto Italiano di Tecnologia has identified a flexible, low-cost, and biocompatible platform for enabling richer intracellular recordings.

The group's unique "across the ocean" partnership started two years ago at the Bioelectronics Winter School (BioEl) with libations and a bar napkin sketch. It has evolved into research published today in Science Advances, detailing a novel microelectrode platform that leverages three-dimensional fuzzy graphene (3DFG) to enable richer intracellular recordings of cardiac action potentials with high signal to noise ratio. This advancement could revolutionize ongoing research related to neurodegenerative and cardiac diseases, as well as the development of new therapeutic strategies.

A key leader in this work, Tzahi Cohen-Karni, associate professor of biomedical engineering and materials science and engineering, has studied the properties, effects, and potential applications of graphene throughout his entire career. Now, he is taking a collaborative step in a different direction, using a vertically-grown orientation of the extraordinary carbon-based material (3DFG) to access the intracellular compartment of the cell and record intracellular electrical activity.

Due to its unique electrical properties, graphene stands out as a promising candidate for carbon-based biosensing devices. Recent studies have shown the successful deployment of graphene biosensors for monitoring the electrical activity of cardiomyocytes, or heart cells, outside of the cells, or in other words, extracellular recordings of action potentials. Intracellular recordings, on the other hand, have remained limited due to ineffective tools...until now.

"Our aim is to record the whole orchestra -- to see all the ionic currents that cross the cell membrane -- not just the subset of the orchestra shown by extracellular recordings," explains Cohen-Karni. "Adding the dynamic dimension of intracellular recordings is fundamentally important for drug screening and toxicity assay, but this is just one important aspect of our work."

"The rest is the technology advancement," Cohen-Karni continues. "3DFG is cheap, flexible and an all-carbon platform; no metals involved. We can generate wafer-sized electrodes of this material to enable multi-site intracellular recordings in a matter of seconds, which is a significant enhancement from an existing tool, like a patch clamp, which requires hours of time and expertise."

So, how does it work? Leveraging a technique developed by Michele Dipalo and Francesco De Angelis, researchers at Istituto Italiano di Tecnologia, an ultra-fast laser is used to access the cell membrane. By shining short pulses of laser onto the 3DFG electrode, an area of the cell membrane becomes porous in a way, allowing for electrical activity within the cell be recorded. Then, the cardiomyocytes are cultured to further investigate interactions between the cells.

Interestingly, 3DFG is black and absorbs most of the light, resulting in unique optical properties. Combined with its foam-like structure and enormous exposed surface area, 3DFG has many desirable traits that are needed to make small biosensors.

"We have developed a smarter electrode; an electrode that allows us better access," emphasizes Cohen-Karni. "The biggest advantage from my end is that we can have access to this signal richness, to be able to look into processes of intracellular importance. Having a tool like this will revolutionize the way we can investigate effects of therapeutics on terminal organs, such as the heart."

Read more at Science Daily

Why some of us are hungry all the time

 New research shows that people who experience big dips in blood sugar levels, several hours after eating, end up feeling hungrier and consuming hundreds more calories during the day than others.

A study published today in Nature Metabolism, from PREDICT, the largest ongoing nutritional research program in the world that looks at responses to food in real life settings, the research team from King's College London and health science company ZOE (including scientists from Harvard Medical School, Harvard T.H. Chan School of Public Health, Massachusetts General Hospital, the University of Nottingham, Leeds University, and Lund University in Sweden) found why some people struggle to lose weight, even on calorie-controlled diets, and highlight the importance of understanding personal metabolism when it comes to diet and health.

The research team collected detailed data about blood sugar responses and other markers of health from 1,070 people after eating standardized breakfasts and freely chosen meals over a two-week period, adding up to more than 8,000 breakfasts and 70,000 meals in total. The standard breakfasts were based on muffins containing the same amount of calories but varying in composition in terms of carbohydrates, protein, fat and fibre. Participants also carried out a fasting blood sugar response test (oral glucose tolerance test), to measure how well their body processes sugar.

Participants wore stick-on continuous glucose monitors (CGMs) to measure their blood sugar levels over the entire duration of the study, as well as a wearable device to monitor activity and sleep. They also recorded levels of hunger and alertness using a phone app, along with exactly when and what they ate over the day.

Previous studies looking at blood sugar after eating have focused on the way that levels rise and fall in the first two hours after a meal, known as a blood sugar peak. However, after analyzing the data, the PREDICT team noticed that some people experienced significant 'sugar dips' 2-4 hours after this initial peak, where their blood sugar levels fell rapidly below baseline before coming back up.

Big dippers had a 9% increase in hunger, and waited around half an hour less, on average, before their next meal than little dippers, even though they ate exactly the same meals.

Big dippers also ate 75 more calories in the 3-4 hours after breakfast and around 312 calories more over the whole day than little dippers. This kind of pattern could potentially turn into 20 pounds of weight gain over a year.

Dr Sarah Berry from King's College London said, "It has long been suspected that blood sugar levels play an important role in controlling hunger, but the results from previous studies have been inconclusive. We've now shown that sugar dips are a better predictor of hunger and subsequent calorie intake than the initial blood sugar peak response after eating, changing how we think about the relationship between blood sugar levels and the food we eat."

Professor Ana Valdes from the School of Medicine at the University of Nottingham, who led the study team, said: "Many people struggle to lose weight and keep it off, and just a few hundred extra calories every day can add up to several pounds of weight gain over a year. Our discovery that the size of sugar dips after eating has such a big impact on hunger and appetite has great potential for helping people understand and control their weight and long-term health."

Comparing what happens when participants eat the same test meals revealed large variations in blood sugar responses between people. The researchers also found no correlation between age, bodyweight or BMI and being a big or little dipper, although males had slightly larger dips than females on average.

There was also some variability in the size of the dips experienced by each person in response to eating the same meals on different days, suggesting that whether you're a dipper or not depends on individual differences in metabolism, as well as the day-to-day effects of meal choices and activity levels.

Choosing foods that work together with your unique biology could help people feel fuller for longer and eat less overall.

Lead author on the study, Patrick Wyatt from ZOE, notes, "This study shows how wearable technology can provide valuable insights to help people understand their unique biology and take control of their nutrition and health. By demonstrating the importance of sugar dips, our study paves the way for data-driven, personalized guidance for those seeking to manage their hunger and calorie intake in a way that works with rather than against their body."

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Gene therapy shows promise in treating rare eye disease in mice

 A gene therapy protects eye cells in mice with a rare disorder that causes vision loss, especially when used in combination with other gene therapies, shows a study published today in eLife.

The findings suggest that this therapy, whether used alone or in combination with other gene therapies that boost eye health, may offer a new approach to preserving vision in people with retinitis pigmentosa or other conditions that cause vision loss.

Retinitis pigmentosa is a slowly progressive disease, which begins with the loss of night vision due to genetic lesions that affect rod photoreceptors -- cells in the eyes that sense light when it is low. These photoreceptors die because of their intrinsic genetic defects. This then impacts cone photoreceptors, the eye cells that detect light during the day, which leads to the eventual loss of daylight vision. One theory about why cones die concerns the loss of nutrient supply, especially glucose.

Scientists have developed a few targeted gene therapies to help individuals with certain mutations that affect the photoreceptors, but no treatments are currently available that would be effective for a broad set of families with the disease. "A gene therapy that would preserve photoreceptors in people with retinitis pigmentosa regardless of their specific genetic mutation would help many more patients," says lead author Yunlu Xue, Postdoctoral Fellow at senior author Constance Cepko's lab, Harvard Medical School, Boston, US.

To find a widely effective gene therapy for the disease, Xue and colleagues screened 20 potential therapies in mouse models with the same genetic deficits as humans with retinitis pigmentosa. The team chose the therapies based on the effects they have on sugar metabolism.

Their experiments showed that using a virus carrier to deliver a gene called Txnip was the most effective approach in treating the condition across three different mouse models. A version of Txnip called C247S worked especially well, as it helped the cone photoreceptors switch to using alternative energy sources and improved mitochondria health in the cells.

The team then showed that giving the mice gene therapies that reduced oxidative stress and inflammation, along with Txnip gene therapy, provided additional protection for the cells. Further studies are now needed to confirm whether this approach would help preserve vision in people with retinitis pigmentosa.

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