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Scientists develop visual tool to help people group foods based on their levels of processing
Fralin Biomedical Research Institute at VTC scientists studying ultra-processed foods have created a new tool for assessing the rewarding and reinforcing properties of foods that make up 58 percent of calories consumed in the United States. The foods have been linked to a wide range of negative health outcomes.
The work was based on the NOVA classification system — “nova” means new in Portuguese — which groups foods into four categories based on their level of processing. Nutrition researchers at the University of São Paulo in Brazil developed the scale while studying the country’s sharp increase in obesity rates.
The scale has its detractors.
“A major criticism of the NOVA scale is that it’s difficult to use or that foods are classified differently by different people,” said Alexandra DiFeliceantonio, corresponding author and assistant professor at the Fralin Biomedical Research Institute. “We found that people with education in nutrition generally agreed on the food classifications, providing some data that it might not be a valid criticism.”
What they did
The NOVA system assigns food to four categories: unprocessed or minimally processed, such as fresh fruit, legumes, or plain yogurt; processed culinary ingredients, such as cooking oils, butter, and salt; processed foods, which combine the two above through simple methods suc as cheese, canned vegetables, or freshly baked bread; and ultra-processed foods, such as soft drinks, flavored yogurt, processed meat, and most packaged breads, made through industrial processing and additives rarely found in a home pantry.
To develop the picture set, a team of psychologists, neuroscientists, and registered dietitians selected foods to represent either minimally processed or ultra-processed foods.
The foods were prepared in a lab, visually represented through professional photography, and controlled for consistency. Researchers also gathered price, food weights, and nutritional information — calories, macronutrients, sodium, and dietary fiber — for the food in each image.
Study participants rated images across a range of qualities to generate a final set of 28 pictures matched across 26 characteristics. To objectively measure NOVA classification, researchers recruited 67 nutrition professionals and asked them to classify the foods as minimally or ultra-processed.
“With this food picture set we can start to infer that any differences between food pictures is due to the degree of food processing, and not all these other factors that we know are potentially impactful,” said Zach Hutelin, the study’s lead author and a Fralin Biomedical Research Institute-based graduate student in the translational biology, medicine and health Ph.D. program.
Why this matters
Ultra-processed foods are linked with increased risk of developing obesity, Type 2 diabetes, heart disease, and cancer. They represent more than half of calories consumed in the United States, Canada, and the United Kingdom and have been identified as a global threat to public health.
“There is very little experimental research on ultra-processed foods, and part of what’s been holding us back is better tools for measuring and assessing their effects,” said DiFeliceantonio, who is also associate director of the Fralin Biomedical Research Institute’s Center for Health Behaviors Research. “The more tools we can provide, the more we can learn.”
The Virginia Tech team is making the pictures and associated data accessible through the Virginia Tech Data Repository of the Virginia Tech University Libraries. This will allow scientists to test hypotheses in behavioral economic and neuroimaging studies.
In the DiFeliceantonio lab, the photos are being used with functional MRI to reveal associated brain activity, with the images isolating the effects of food processing from other characteristics.
The study was funded by a National Science Foundation graduate research fellowship, the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health, and a grant from the Seale Innovation Fund, which supports innovative pilot research projects at the Fralin Biomedical Research Institute. DiFeliceantonio received a grant from the fund to investigate metabolic, neural, and behavioral data to better understand how our brains process nutrient availability and food preference.
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Light pollution a new Alzheimer’s risk factor
Outdoor light at night could be a significant risk factor in Alzheimer’s disease, according to new research from Rush.
The study was conducted at Rush University System for Health and published in Frontiers in Neuroscience.
“Our research shows that there is an association in the U.S. between Alzheimer’s disease prevalence and exposure to light at night, particularly in those under the age of 65,” said lead investigator, Robin Voigt-Zuwala, PhD, an associate professor?at Rush. “Nightly light pollution — a modifiable environmental factor — may influence risk for Alzheimer’s.”
High U.S. light levels
While legislation in some states aims to reduce light pollution, levels of nighttime light remain high in many parts of the country.
In studying light pollution maps, researchers looked at the lower 48 states and incorporated medical data associated with Alzheimer’s disease risk factors and divided the groups by light intensity. In the five groups, they found that light intensity was correlated with Alzheimer’s disease prevalence even when some well-established disease factors were not.
While the cause is unknown, higher nighttime light intensity was associated with a greater Alzheimer’s disease prevalence than any other risk factor examined in the study for those under the age of 65, suggesting that younger people may be more sensitive to the effects of light exposure at night.
“Certain genes can influence early-onset Alzheimer’s,and these same genes may cause increased vulnerability to the effects of nighttime light exposure,” Voigt-Zuwala explained. “Additionally, younger people are more likely to live in urban areas and have lifestyles that may increase exposure to light at night.”
Reducing light exposure
Exposure to light influences the body’s natural sleep-wake pattern, which is called a circadian rhythm. Exposure to light at night can disrupt a person’s circadian rhythm, which can promote inflammation and make a person less resilient and more prone to disease. Researchers did not examine light inside the home at night or how it might impact health.
Voigt-Zuwala said, “The good news is that simple changes can be made with minimal effort to reduce exposure to light at night — adding black out curtains or sleeping with an eye mask.”
The research results are limited to a subset of the population and further testing is needed to better understand the connection between evening outdoor light and Alzheimer’s disease.
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Microscale robot folds into 3D shapes and crawls
Cornell University researchers have created microscale robots less than 1 millimeter in size that are printed as a 2D hexagonal “metasheet” but, with a jolt of electricity, morph into preprogrammed 3D shapes and crawl.
The team’s paper, “Electronically Configurable Microscopic Metasheet Robots,” published Sept. 11 in Nature Materials. The paper’s co-lead authors are postdoctoral researchers Qingkun Liu and Wei Wang. The project was led by Itai Cohen, professor of physics. His lab has previously produced microrobotic systems that can actuate their limbs, pump water via artificial cilia and walk autonomously.
In a sense, the origins of the kirigami robot were inspired by “living organisms that can change their shape.” Liu said. “But when people make a robot, once it’s fabricated, it might be able to move some limbs but its overall shape is usually static. So we’ve made a metasheet robot. The ‘meta’ stands for metamaterial, meaning that they’re composed of a lot of building blocks that work together to give the material its mechanical behaviors.”
The robot is a hexagonal tiling composed of approximately 100 silicon dioxide panels that are connected through more than 200 actuating hinges, each about 10 nanometers thin. When electrochemically activated via external wires, the hinges form mountain and valley folds and act to splay open and rotate the panels, allowing the robot to change its coverage area and locally expand and contract by up to 40%. Depending which hinges are activated, the robot can adopt various shapes and potentially wrap itself around other objects, and then unfold itself back into a flat sheet.
Cohen’s team is already thinking of the next phase of metasheet technology. They anticipate combining their flexible mechanical structures with electronic controllers to create ultra-responsive “elastronic” materials with properties that would never be possible in nature. Applications could range from reconfigurable micromachines to miniaturized biomedical devices and materials that can respond to impact at nearly the speed of light, rather than the speed of sound.
“Because the electronics on each individual building block can harvest energy from light, you can design a material to respond in programmed ways to various stimuli. When prodded, such materials, instead of deforming, could ‘run’ away, or push back with greater force than they experienced,” Cohen said. “We think that these active metamaterials — these elastronic materials — could form the basis for a new type of intelligent matter governed by physical principles that transcend what is possible in the natural world.”
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Genes with strong impact on menopause timing also link to cancer risk
New research has found four genes with some of the largest known effects on the timing of menopause discovered to date, providing new insight into links between menopause timing and cancer risk.
Published in Nature, the large-scale analysis was funded by the Medical Research Council and Wellcome. The team first looked at variation in data from genetic sequencing of 106,973 post-menopausal female participants in the UK Biobank study. Researchers focussed on rare types of genetic changes which cause a loss of the protein, and investigated their effect on the timing of menopause.
The genetic changes studied are all rare in the population, however their influence on menopause is five times greater than the impact of any previously identified common genetic variant. The strongest effect was found from gene variants in ZNF518A, only found in one in 4,000 women. These variants shortened reproductive lifespan more than most previously identified genes.
Discovering the effect of the genes gives scientists a better understanding of the biological mechanisms underpinning menopause, and links to other diseases.
Study co-lead Professor Anna Murray, of the University of Exeter Medical School, said: “For decades, menopause has been under-researched, yet now this is a rapidly evolving area of science. The timing of menopause has a huge impact on women as they plan their careers and lives, and understanding the genetic changes is of particular interest in terms of potential treatments that could prolong reproductive life in future.”
When unrepaired DNA damage occurs in eggs, they can die. The rate at which eggs are lost determines when women experience menopause. The team’s previous work has shown that many genes that influence the timing of menopause are likely to do this by affecting the genetic integrity of eggs. The same factors affect other cells and tissue types in parallel, and in this new study, the team found that many of the genes linked to menopause timing are also risk factors for cancer. These include changes in the BRCA1 and BRCA2 genes, which result in earlier menopause and also in increased risk of cancer.
This is thought to be the process at play in a fifth new gene linked to menopause timing (SAMHD1). The team discovered that changes in this gene can cause women to go through menopause over a year later than average. The researchers also found for the first time that changes in this gene cause predisposition to various cancers in men and women.
Professor John Perry, co-lead from the MRC Epidemiology Unit at the University of Cambridge added: “Past research suggests the female ovary ages at a faster rate than other organ in the body, and this is a model system for understanding the biology of broader ageing. Our latest research builds on this concept, demonstrating that studying ovarian ageing will not only lead to a better understanding of the biology behind infertility and other reproductive disorders, but will enhance our understanding of fundamental processes that regulate DNA damage and cancer risk in the general population.”
Using data from the 100,000 Genomes project, led by Genomics England and NHS England, the team next found that mothers with a high number of genetic variants that cause earlier menopause tended to have more new changes in the DNA they passed onto their children. The study authors believe this is because the relevant genes are involved in repairing damage to DNA, so this function may be compromised in the ovaries, enabling new genetic changes to occur in the eggs.
Dr Hilary Martin, a study co-lead from the Wellcome Sanger Institute, said: “New changes to the DNA in the egg or sperm are the source of all genetic variation in humans, contributing to differences between individuals in their appearance, behaviours and risk of disease. Until now, we knew very little about what influences these new DNA changes, apart from parental age. This is the first time we’ve seen that existing common variation in DNA influences the rate of these changes.”
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