Pacific Nut Producer Magazine

Tag: Penn State

  • Replacing Other Snacks with Pecans May Improve Cholesterol, Diet Quality

    Switching daily snack foods to pecans improved cholesterol levels and enhanced overall diet quality, according to a new study by researchers in the Penn State Department of Nutritional Sciences.

    The researchers randomized adults who live with or are at risk for metabolic syndrome — a set of conditions that increase a person’s risk for several chronic diseases — to either consume pecans instead of their usual snacks or to continue eating their usual diet. Participants who ate pecans in lieu of their usual snacks demonstrated reductions across cholesterol measurements linked to poorer heart health compared to those that did not snack on pecans. Additionally, diet quality, as measured by adherence to the Dietary Guidelines for Americans, was 17% higher at the conclusion of the study for participants who consumed pecans.

    Results of the study were published in American Journal of Clinical Nutrition.

    “Replacing typical snacks with pecans improved key risk factors for heart disease including blood cholesterol levels and diet quality,” said Kristina Petersen, associate professor of nutritional sciences at Penn State and co-author of the study. “These results add to the large evidence-base supporting the cardiovascular benefits of nuts and add additional insights into how adults can incorporate nuts into their diet to improve the overall quality of their diet.”

    The study included 138 adults with one or more criteria for metabolic syndrome, including abdominal obesity, high triglycerides, low HDL, high blood pressure and high fasting blood glucose. Participants were 25 to 70 years old and were randomly assigned into two equal groups: pecan snacking group, who were asked to consume two ounces of pecans per day in place of snacks typically consumed, and the usual diet group, who were asked to continue their regular diet.

    Vascular health data and blood work were collected at the start and conclusion of the 12-week study, and self-reported 24-hour recalls were collected nine times during the research. All participants were also instructed to stop eating all other types of nuts and to keep their non-snacking dietary behavior and lifestyle consistent throughout the study.

    In the study, pecan snackers experienced reductions in total cholesterol, low-density lipoprotein (LDL) cholesterol, non-high-density lipoprotein (HDL) cholesterol, the ratio of total cholesterol to HDL cholesterol and triglycerides compared to non-pecan snackers. LDL cholesterol can build up in arteries and increase the risk of stroke or heart attack. HDL — sometimes known colloquially as “good cholesterol” — carries cholesterol back to the liver for removal from the body. So, both lowering LDL and reducing the ratio of total cholesterol to HDL can reduce the risk for cardiovascular disease. Triglycerides are a necessary lipid for energy storage and metabolism, but high levels of triglycerides also increase the risk of cardiovascular disease.

    In addition, study participants who ate pecans showed higher overall adherence to the Dietary Guidelines for Americans 2020-2025, with increased intakes of other under-consumed food groups, such as plant proteins and seafood.

    According to the team, prior research by others in the field suggests that chemical compounds with anti-inflammatory properties called polyphenols in pecans may support endothelial function, a key factor in maintaining healthy blood vessels. The current study did not find differences in vascular health outcomes between the two groups, but the researchers said people in the United States should consider consuming more foods with polyphenols — like pecans, fruits, vegetables and whole grains — to support heart health and improve overall diet quality.

    “The improved diet quality among pecan snackers — including a higher percentage of calories from polyunsaturated fats and increased fiber and polyphenols — likely also contributed to the observed cholesterol improvements, particularly the LDL-lowering effects,” Petersen said.

    The researchers said that replacing a person’s usual snacks with pecans each day could improve cholesterol levels and diet quality, especially if they are at risk of metabolic syndrome.

    Tricia Hart, doctoral student in nutritional studies at Penn State, and Penny Kris-Etherton, retired Evan Pugh University Professor of Nutritional Sciences at Penn State, also contributed to this research.

    This study was supported by the Clinical Research Center, a unit in the Penn State Clinical and Translational Science Institute.

    The American Pecan Council funded this study.

  • Genetic ‘Signatures’ Provide Insight Into What Stresses Wild Bees

    A new method of examining gene expression patterns called landscape transcriptomics may help pinpoint what causes bumble bees stress and could eventually give insight into why bee populations are declining overall, according to a study led by researchers at Penn State. The team published their findings in the journal Molecular Ecology.

    This study was the first test of the emerging field of landscape transcriptomics, recently envisioned by an interdisciplinary team led by scientists in Penn State’s College of Agricultural Sciences. The team hypothesized that it would be possible to collect animals and plants from the wild and determine which stressors they experienced based on specific patterns or signatures in their gene expression profiles.

    In this study, the scientists used an artificial intelligence approach known as machine learning to evaluate gene expression profiles of individual bumble bees. The researchers found that the method could accurately identify genetic signatures of stressors, such as excessive heat and cold, in bees both in the lab and in the wild.

    Gabriela Quinlan, who led the study when she was a postdoctoral scholar in the College of Agricultural Sciences, said the findings suggest landscape transcriptomics could be used to accelerate conservation efforts for at-risk species.

    “This is a really big step in demonstrating this new strategy for identifying at-risk populations and showing how these machine learning models can be used both in the lab and out in the field,” she said. “We also found directly applicable insights such as sets of genes that are associated with different stressors in bumble bees, which we didn’t have before.”

    Bees — like many other species of plants and animals — are currently in decline around the world, the researchers said, suggesting that something is causing enough stress to trigger population declines. However, understanding exactly what those stressors are can be challenging.

    That’s where landscape transcriptomics comes in, according to Christina Grozinger, Publius Vergilius Maro Professor of Entomology and director of the Huck Institutes of the Life Sciences.

    “It’s like forensic biology, where you can look at an organism’s gene expression patterns and identify a signature or fingerprint that relates to the stress it’s experiencing,” Grozinger said. “Landscape transcriptomics should allow us to identify stressed populations of target species much more rapidly than traditional approaches, which require collecting and analyzing many samples over long periods of time.”

    While previous studies have found that it was possible to detect transcriptional signatures of specific stressors in organisms reared and treated in the lab under very controlled conditions, the research team wanted to see whether the method would still be feasible in organisms living in the wild.

    “In typical laboratory studies, we use organisms from the same genetic background, the same age, reared in the same way, and which are exposed to stressors at tightly controlled levels and periods of time,” Grozinger said. “But collecting organisms from the wild, we know nothing about them or the stressors they’ve experienced, so we were curious if we could still see these specific stress-related transcriptional fingerprints.”

    For this study, the researchers first did an experiment in the lab in which they exposed bumble bees to different types of stressors, including heat, cold and immune challenges. They then extracted the bees’ RNA — the genetic material used to build proteins and help regulate biological functions — and sent the samples to the Penn State Genomics Core Facility for high throughput sequencing.

    This gave the researchers information on the number of RNA strands corresponding to each gene, which represents the gene expression patterns.  The RNA profiles from individuals that were exposed to different stressors were then used to train a machine learning model, which is a type of artificial intelligence, to recognize which patterns of gene expressions were associated with each type of stressor.

    A strength of this study, Quinlan said, was the approach they took to training their machine learning model to recognize the different genetic signatures for each stressor.

    “We know that in nature, organisms are going to be subjected to multiple stressors at the same time, so how do we differentiate one stressor versus another?” she said. “We used an algorithm that takes all the inputs from all the genes and finds the patterns that emerge when the bees were experiencing each stressor. We were able to get a model with 92% accuracy, which we could then use to assess wild bees.”

    For their second experiment, the team collected wild bees from two sites: one in the Arboretum at Penn State and another in a forested, more mountainous area.

    The sites were chosen to increase the likelihood that the bees would be exposed to different stressors — those at the Arboretum had access to abundant floral resources and lots of sun, while the bees from the second site experienced more shade and might not have as many flowers to forage.

    After analyzing the transcriptomes of these bees, the researchers found that the model was once again very accurate in predicting which stressors the bees were experiencing. However, the researchers found that these signatures didn’t last long in the bees’ RNA. In bees collected the morning after a heat wave, when environmental temperatures had gone back to normal, their genetic signatures for heat stress were no longer visible.

    But this also meant that the researchers could glean precise details about how bees go about their day. For example, they discovered that many bees exhibited signatures of starvation stress when they were collected in the morning as compared to the evening, which might give insight into how bees forage and their motivation to forage.

    Quinlan said in the future, additional work could train these models to pick up on stressors that bees have experienced for longer periods of time.

    “The initial motivation for this study was to see longer-lived signatures so we can learn what is stressing these bees long term and might be contributing to population decline,” she said. “Transcriptomics is very acute in that it picks up on what’s going on in the moment, so it might be a matter of training these models to pick up on these longer term, more subtle differences.”

    Heather Hines, associate professor of biology and entomology, also co-authored this study.

    The Penn State College of Agricultural Sciences Strategic Networks and Initiatives Program and the U.S. National Science Foundation Postdoctoral Research Fellowship in Biology Program supported this research. — By Katie Bohn, Pennsylvania State University