Podcasts about environmental health research

Want to add a healthy habit to your daily routine that is absolutely free and incredibly effective? Looking to reduce insulin resistance and lose visceral fat? Want to boost mental health and improve cognitive function? Look no further than walking! Tune in to hear us unpack the myriad of research-supported benefits.   In this episode, we discuss the incredible benefits of walking, from lowering blood pressure to improving heart rate variability to reducing stress and so much more. Learn about the magic number when it comes to step count, our thoughts on walking in nature vs. on a treadmill, and get practical tips for getting those steps!    Also in this episode:  Naturally Nourished Teas are buy 3 get 1 FREE, use code FREETEA Gift cards at Naturally Nourished Detox Masterclass 1/8 Keto Masterclass 1/15 Walking Pad C2 use code ALIMILLERRD for savings Health Benefits of Walking Lowers Blood Pressure Hypertension: Brisk walking for 30 minutes, five days a week reduces blood pressure (Hypertension, 2020). Improves Cholesterol Levels Cholesterol: Effects on LDL and HDL cholesterol (Journal of the American Heart Association, 2021). Lipid Profiles: Walking improves triglycerides and HDL (Atherosclerosis, 2021). Reduces the Risk of Coronary Artery Disease Coronary Artery Disease Risk: 150 minutes of walking weekly (Circulation, 2022). Enhances Cardiorespiratory Fitness Reduces Systemic Inflammation Systemic Inflammation: Walking lowers CRP and IL-6 (Arteriosclerosis, Thrombosis, and Vascular Biology, 2020). Systemic Inflammation: Walking reduces inflammatory cytokines (The Journal of Endocrinology, 2022). Helps Maintain Healthy Weight and Prevent Obesity Improves Heart Rate Variability Heart Rate Variability: HRV improvement with regular walking (Heart, 2022). Prevents Peripheral Artery Disease Peripheral Artery Disease: Walking improves circulation and function in PAD patients (Journal of Vascular Surgery, 2021). Reduces Resting Heart Rate Enhances Endothelial Function Supports Recovery After Cardiac Events Improves Insulin Sensitivity Insulin Sensitivity: Improvements with post-meal walks (Diabetes Care, 2021). Enhances Glucose Regulation Boosts Fat Oxidation Fat Oxidation: Brisk walking boosts fat metabolism (Journal of Applied Physiology, 2022). Reduces Visceral Fat Reduction of visceral fat after 10,000 steps/day (Obesity, 2021). Promotes Energy Balance Energy Balance: 12,000 steps/day for maintaining weight (Medicine & Science in Sports & Exercise, 2020). Regulates Hormones Related to Metabolism Increases Mitochondrial Efficiency Improves Metabolic Flexibility Prevents Metabolic Syndrome Helps Manage Type 2 Diabetes Mental health Stress Reduction: Nature walks lower cortisol more than treadmill (Environmental Research, 2022). Stimulates Neurogenesis and Brain Plasticity Brain Connectivity: Walking improves default mode network activity (Journal of Aging Research, 2021). Enhances Neurotransmitter Balance Supports Autonomic Nervous System Regulation Improves Sensory Integration Vestibular Function: Enhancing balance and stability with walking (Frontiers in Neuroscience, 2021). Strengthens Cognitive Function Neurogenesis and Cognitive Function: Exercise-induced brain growth (Nature Neuroscience, 2021). Promotes Myelination and Nerve Health Enhances Emotional Regulation via the Vagus Nerve Reduces Neurological Disease Risk Synchronizes the Nervous System Through Rhythmic Movement Improves Sleep and Circadian Rhythm Bone and Joint Health Immune System Support Longevity and Reduced Mortality Gut Health Gut Health: Positive effects on microbiota diversity (Gut Microbes, 2020). The Science of Step Counts Thoughts on Nature vs. Treadmill Walking Cognitive Benefits: Nature walking improves attention restoration (Nature Neuroscience, 2021). Proprioception: Benefits of uneven terrain in natural settings (Journal of Sports Medicine, 2023). Motivation: Outdoor walkers maintain habits better than treadmill users (Behavioral Medicine, 2022). Immune Boosting: Increased NK cell activity in forest walkers (International Journal of Environmental Health Research, 2021).   Sponsors for this episode:  According to extensive research by the Environmental Working Group, virtually every home in America has harmful contaminants in its tap water. That's why you've got to check out AquaTru. AquaTru purifiers use a 4-stage reverse osmosis purification process, and their countertop purifiers work with NO installation or plumbing. It removes 15x more contaminants than ordinary pitcher filters and are specifically designed to combat chemicals like PFAS in your water supply. Naturally Nourished Podcast listeners can use code ALIMILLERRD at AquaTru.com to save 20% off. 

The NIEHS Superfund Research Program (SRP) is hosting a Risk e-Learning webinar series focused on using artificial intelligence (AI) and machine learning to advance environmental health research. The series will feature SRP-funded researchers, collaborators, and other subject-matter experts who aim to better understand and address environmental health issues by applying AI and machine learning approaches to complex issues. Recent advances in AI and machine learning methods show promise to improve the accuracy and efficiency of environmental health research. Over the course of three sessions, presenters will discuss how they use AI and machine learning approaches to improve chemical analysis, characterize chemical risk, understand microbial ecosystems, develop technologies for contaminant removal, and more. In the third and final session, ML & AI Applications to Understand Omics, Metabolomics, & Immunotoxicity and Optimize Bioengineering Using Datasets, Models, and Mass Spectrometry, speakers will discuss how they apply machine learning and artificial intelligence tools to analyze mass spectrometry and microscopy data and optimize models for understanding metabolomics, metabolite pathways, and immunotoxicology To learn about and register for the other sessions in this webinar series, please see the SRP website. Grace Peng, Ph.D., is a co-coordinator of the National Institutes of Health (NIH) Common Fund's Bridge to Artificial Intelligence (Bridge2AI) program, bridging the gap between the biomedical, behavioral and bioethics research communities and the data science/AI communities through a consortium of diverse experts to set the stage for widespread adoption of AI/ML in medicine. Dr. Peng will give an overview of the Bridge2AI program and introduce one of their projects at the University of California San Diego — Trey Ideker, Ph.D. Dr. Ideker will discuss the cell maps for AI (CM4AI) functional genomics project, one of four major data generation projects under the Bridge2AI program. The goal of the project is to provide a comprehensive map of human cellular components through generation of major spatial proteomics datasets. John Efromson, M.S., will present on Ramona Optic, Inc.'s Multi-Camera Array Microscope [MCAM(TM)], which is used to automate imaging and computer vision analysis of zebrafish and greatly improves previous throughput and analysis capabilities. Multiple applications of machine learning will be discussed, including behavioral pose estimation and phenotyping, morphological analysis, and cell counting and fluorescence quantification, as well as how these distinct analyses can be used together for pharmacology, toxicology, and neuroscience research. Speakers:Grace C.Y. Peng, Ph.D., Division of Discovery Science and Technology (Bioengineering), National Institute of Biomedical Imaging and Bioengineering and Trey Ideker, Ph.D., University of California San DiegoJohn Efromson, M.S., Ramona OpticsForest White, Ph.D., Massachusetts Institute of Technology (MIT)Moderator: Hunter Moseley, Ph.D., University of Kentucky To view this archive online or download the slides associated with this seminar, please visit http://www.clu-in.org/conf/tio/SRP-ML-AI3_112224/

The NIEHS Superfund Research Program (SRP) is hosting a Risk e-Learning webinar series focused on using artificial intelligence (AI) and machine learning to advance environmental health research. The series will feature SRP-funded researchers, collaborators, and other subject-matter experts who aim to better understand and address environmental health issues by applying AI and machine learning approaches to complex issues. Recent advances in AI and machine learning methods show promise to improve the accuracy and efficiency of environmental health research. Over the course of three sessions, presenters will discuss how they use AI and machine learning approaches to improve chemical analysis, characterize chemical risk, understand microbial ecosystems, develop technologies for contaminant removal, and more. In the third and final session, ML & AI Applications to Understand Omics, Metabolomics, & Immunotoxicity and Optimize Bioengineering Using Datasets, Models, and Mass Spectrometry, speakers will discuss how they apply machine learning and artificial intelligence tools to analyze mass spectrometry and microscopy data and optimize models for understanding metabolomics, metabolite pathways, and immunotoxicology To learn about and register for the other sessions in this webinar series, please see the SRP website. Grace Peng, Ph.D., is a co-coordinator of the National Institutes of Health (NIH) Common Fund's Bridge to Artificial Intelligence (Bridge2AI) program, bridging the gap between the biomedical, behavioral and bioethics research communities and the data science/AI communities through a consortium of diverse experts to set the stage for widespread adoption of AI/ML in medicine. Dr. Peng will give an overview of the Bridge2AI program and introduce one of their projects at the University of California San Diego — Trey Ideker, Ph.D. Dr. Ideker will discuss the cell maps for AI (CM4AI) functional genomics project, one of four major data generation projects under the Bridge2AI program. The goal of the project is to provide a comprehensive map of human cellular components through generation of major spatial proteomics datasets. John Efromson, M.S., will present on Ramona Optic, Inc.'s Multi-Camera Array Microscope [MCAM(TM)], which is used to automate imaging and computer vision analysis of zebrafish and greatly improves previous throughput and analysis capabilities. Multiple applications of machine learning will be discussed, including behavioral pose estimation and phenotyping, morphological analysis, and cell counting and fluorescence quantification, as well as how these distinct analyses can be used together for pharmacology, toxicology, and neuroscience research. Speakers:Grace C.Y. Peng, Ph.D., Division of Discovery Science and Technology (Bioengineering), National Institute of Biomedical Imaging and Bioengineering and Trey Ideker, Ph.D., University of California San DiegoJohn Efromson, M.S., Ramona OpticsForest White, Ph.D., Massachusetts Institute of Technology (MIT)Moderator: Hunter Moseley, Ph.D., University of Kentucky To view this archive online or download the slides associated with this seminar, please visit http://www.clu-in.org/conf/tio/SRP-ML-AI3_112224/

The NIEHS Superfund Research Program (SRP) is hosting a Risk e-Learning webinar series focused on using artificial intelligence (AI) and machine learning to advance environmental health research. The series will feature SRP-funded researchers, collaborators, and other subject-matter experts who aim to better understand and address environmental health issues by applying AI and machine learning approaches to complex issues. Recent advances in AI and machine learning methods show promise to improve the accuracy and efficiency of environmental health research. Over the course of three sessions, presenters will discuss how they use AI and machine learning approaches to improve chemical analysis, characterize chemical risk, understand microbial ecosystems, develop technologies for contaminant removal, and more. In the second session ML & AI Applications to Environmental Engineering Contaminants & Bioremediation, invited presenters will discuss how they apply machine learning and artificial intelligence to environmental engineering applications including contaminants and bioremediation using biosensors, microbiome compositions, and screening tools. To learn about and register for the other sessions in this webinar series, please see the SRP website. Kei-Hoi Cheung, Ph.D., has an extensive history in data science, and has leveraged that expertise to lead natural language processing (NLP) projects in annotating, extracting, and retrieving environmental exposure data. He will present on the use of these NLP methods combined with ontologies in the in the context of scientific literature on emerging water contaminants. Mohammad Soheilypour, Ph.D., will discuss the application of a suite of computational methods to identify and predict microbial metabolism of various chemical compounds, with a focus on gut and environmental microbiomes. Specifically, he will cover the potential application of machine learning models in this context and their integration with other computational methods to enhance both accuracy and utility. Paul Westerhoff, Ph.D., will highlight the work of his research team utilizing and comparing two advanced multiple data imputation techniques, AMELIA and MICE algorithms, to fill gaps in sparse groundwater quality datasets to support State agencies in prioritizing future sampling activities. Historic water quality databases are often sparse due to financial budgets for collection and analysis, posing challenges in evaluating exposure or water treatment effectiveness — and this project aims to account for those by accurately assessing and managing risks associated with inorganic pollutants using this technology. Speakers:Kei-Hoi Cheung, Ph.D., Yale University School of MedicineMohammad Soheilypour, Ph.D., Nexilico Inc.Paul Westerhoff, Ph.D., Arizona State UniversityModerator: Rodrigo Rimando, U.S. Department of Energy To view this archive online or download the slides associated with this seminar, please visit http://www.clu-in.org/conf/tio/SRP-ML-AI2_112024/

The NIEHS Superfund Research Program (SRP) is hosting a Risk e-Learning webinar series focused on using artificial intelligence (AI) and machine learning to advance environmental health research. The series will feature SRP-funded researchers, collaborators, and other subject-matter experts who aim to better understand and address environmental health issues by applying AI and machine learning approaches to complex issues. Recent advances in AI and machine learning methods show promise to improve the accuracy and efficiency of environmental health research. Over the course of three sessions, presenters will discuss how they use AI and machine learning approaches to improve chemical analysis, characterize chemical risk, understand microbial ecosystems, develop technologies for contaminant removal, and more. In the second session ML & AI Applications to Environmental Engineering Contaminants & Bioremediation, invited presenters will discuss how they apply machine learning and artificial intelligence to environmental engineering applications including contaminants and bioremediation using biosensors, microbiome compositions, and screening tools. To learn about and register for the other sessions in this webinar series, please see the SRP website. Kei-Hoi Cheung, Ph.D., has an extensive history in data science, and has leveraged that expertise to lead natural language processing (NLP) projects in annotating, extracting, and retrieving environmental exposure data. He will present on the use of these NLP methods combined with ontologies in the in the context of scientific literature on emerging water contaminants. Mohammad Soheilypour, Ph.D., will discuss the application of a suite of computational methods to identify and predict microbial metabolism of various chemical compounds, with a focus on gut and environmental microbiomes. Specifically, he will cover the potential application of machine learning models in this context and their integration with other computational methods to enhance both accuracy and utility. Paul Westerhoff, Ph.D., will highlight the work of his research team utilizing and comparing two advanced multiple data imputation techniques, AMELIA and MICE algorithms, to fill gaps in sparse groundwater quality datasets to support State agencies in prioritizing future sampling activities. Historic water quality databases are often sparse due to financial budgets for collection and analysis, posing challenges in evaluating exposure or water treatment effectiveness — and this project aims to account for those by accurately assessing and managing risks associated with inorganic pollutants using this technology. Speakers:Kei-Hoi Cheung, Ph.D., Yale University School of MedicineMohammad Soheilypour, Ph.D., Nexilico Inc.Paul Westerhoff, Ph.D., Arizona State UniversityModerator: Rodrigo Rimando, U.S. Department of Energy To view this archive online or download the slides associated with this seminar, please visit http://www.clu-in.org/conf/tio/SRP-ML-AI2_112024/

The NIEHS Superfund Research Program (SRP) is hosting a Risk e-Learning webinar series focused on using artificial intelligence (AI) and machine learning to advance environmental health research. The series will feature SRP-funded researchers, collaborators, and other subject-matter experts who aim to better understand and address environmental health issues by applying AI and machine learning approaches to complex issues. Recent advances in AI and machine learning methods show promise to improve the accuracy and efficiency of environmental health research. Over the course of three sessions, presenters will discuss how they use AI and machine learning approaches to improve chemical analysis, characterize chemical risk, understand microbial ecosystems, develop technologies for contaminant removal, and more. In the first session, AI & ML Applications to Understand Chemical Mixtures, Properties, and Exposures and their Relationship to Human Health, speakers will discuss how they apply machine learning and artificial intelligence techniques to understand chemical exposures and their effects on human health. To learn about and register for the other sessions in this webinar series, please see the SRP website. Naomi Halas, Ph.D., and Ankit Patel, Ph.D., will share updates on their work combining surface-enhanced spectroscopies (Raman and Infrared Absorption) with machine learning algorithms with the goal of developing simple and ultimately low-cost methods for the detection and identification of environmental toxins. As part of their discussion, they will share several approaches, including the use of machine learning algorithms to detect individual constituents in complex mixtures and the use of facial recognition strategies to identify specific chemical toxins in human placenta. Jacob Kvasnicka, Ph.D., will present on a project he supported while he was a postdoctoral researcher at Texas A&M University SRP Center's Risk and Geospatial Sciences Core. There, his work involved developing an ML framework for predicting safe exposure levels to chemicals to avoid cancerous and reproductive/developmental effects. Most chemicals lack toxicity data related to human health, and this study uses ML to fill this gap, greatly expanding the ability to characterize chemical risks and impacts. Trey Saddler will give attendees an overview of ToxPipe — a platform for performing retrieval augmented generation (RAG) over toxicological data. Comprised of a web interface, agentic workflows, and connections to various data sources, ToxPipe enables toxicologists to explore diverse datasets and generate toxicological narratives for a wide range of compounds. Speakers:Naomi Halas, Ph.D., and Ankit Patel, Ph.D., Rice UniversityJacob Kvasnicka, Ph.D., U.S. Environmental Protection AgencyTrey Saddler, NIEHS, Division of Translational ToxicologyModerator: David Reif, Ph.D., NIEHS, Division of Translational Toxicology To view this archive online or download the slides associated with this seminar, please visit http://www.clu-in.org/conf/tio/SRP-ML-AI1_110424/

The NIEHS Superfund Research Program (SRP) is hosting a Risk e-Learning webinar series focused on using artificial intelligence (AI) and machine learning to advance environmental health research. The series will feature SRP-funded researchers, collaborators, and other subject-matter experts who aim to better understand and address environmental health issues by applying AI and machine learning approaches to complex issues. Recent advances in AI and machine learning methods show promise to improve the accuracy and efficiency of environmental health research. Over the course of three sessions, presenters will discuss how they use AI and machine learning approaches to improve chemical analysis, characterize chemical risk, understand microbial ecosystems, develop technologies for contaminant removal, and more. In the first session, AI & ML Applications to Understand Chemical Mixtures, Properties, and Exposures and their Relationship to Human Health, speakers will discuss how they apply machine learning and artificial intelligence techniques to understand chemical exposures and their effects on human health. To learn about and register for the other sessions in this webinar series, please see the SRP website. Naomi Halas, Ph.D., and Ankit Patel, Ph.D., will share updates on their work combining surface-enhanced spectroscopies (Raman and Infrared Absorption) with machine learning algorithms with the goal of developing simple and ultimately low-cost methods for the detection and identification of environmental toxins. As part of their discussion, they will share several approaches, including the use of machine learning algorithms to detect individual constituents in complex mixtures and the use of facial recognition strategies to identify specific chemical toxins in human placenta. Jacob Kvasnicka, Ph.D., will present on a project he supported while he was a postdoctoral researcher at Texas A&M University SRP Center's Risk and Geospatial Sciences Core. There, his work involved developing an ML framework for predicting safe exposure levels to chemicals to avoid cancerous and reproductive/developmental effects. Most chemicals lack toxicity data related to human health, and this study uses ML to fill this gap, greatly expanding the ability to characterize chemical risks and impacts. Trey Saddler will give attendees an overview of ToxPipe — a platform for performing retrieval augmented generation (RAG) over toxicological data. Comprised of a web interface, agentic workflows, and connections to various data sources, ToxPipe enables toxicologists to explore diverse datasets and generate toxicological narratives for a wide range of compounds. Speakers:Naomi Halas, Ph.D., and Ankit Patel, Ph.D., Rice UniversityJacob Kvasnicka, Ph.D., U.S. Environmental Protection AgencyTrey Saddler, NIEHS, Division of Translational ToxicologyModerator: David Reif, Ph.D., NIEHS, Division of Translational Toxicology To view this archive online or download the slides associated with this seminar, please visit http://www.clu-in.org/conf/tio/SRP-ML-AI1_110424/

Pete Myers is founder and Chief Scientist of Environmental Health Sciences, a not-for-profit organization that promotes public understanding of advances in scientific research on environmental and human health, especially on how chemical exposure even at low doses can cause serious adverse effects. He is also a founder and board member of Sudoc LLC, a chemical company that makes catalysts that clean up bad stuff and also replace dangerous chemicals used as disinfectants and cleaners. Sudoc.com. For a dozen years beginning in 1990, Pete served as Director of the W. Alton Jones Foundation in Charlottesville, Virginia. Along with co-authors Dr. Theo Colborn and Dianne Dumanoski, Myers wrote “Our Stolen Future,” a best-selling book (1996) that explores the scientific basis of concern for how contamination threatens fetal development. Vice-President Al Gore wrote the foreword. Pete is actively involved in research on the impacts of endocrine disruption on human health. He is an Adjunct Professor of Chemistry at Carnegie Mellon University. He is on the boards of the Science Communication Network, the Food Packaging Forum of Zurich, and the Jenifer Altman Foundation. He has also served as board chair of the National Environmental Trust and the H. John Heinz Center for Science, Economics and the Environment. Over the last few years he has received 2 major national and international scientific awards: the first “Champion of Environmental Health Research” award from the U.S. National Institutes of Health; and the Laureate Award for Outstanding Public Service from The Endocrine Society. Myers lives just outside White Hall, Virginia. As he was growing up he lived near Baltimore and in Mexico, Nicaragua, Colombia, Uruguay and Paraguay. Dr. Myers holds a doctorate in the biological sciences from the University of California, Berkeley and a BA from Reed College.

Ever wanted to hear from one of the leaders in environmental health research? Toxic Tangents welcomes Dr. Carol Kwiatkowski to give you a rare glimpse into her work with TedX, PFAs regulation initiatives, and more. Learn more about how her work addresses environmental chemicals that affect human health. To find more information about PFAS, please visit >>https://greensciencepolicy.org/harmful-chemicals/pfas/If you are interested in health and toxicology data on PFAS, please visit >>>https://pfastoxdatabase.org/

Ever wanted to hear from one of the leaders in environmental health research? Toxic Tangents welcomes Dr. Carol Kwiatkowski to give you a rare glimpse into her work with TedX, PFAs regulation initiatives, and more. Learn more about how her work addresses environmental chemicals that affect human health. To find more information about PFAS, please visit >>https://greensciencepolicy.org/harmful-chemicals/pfas/If you are interested in health and toxicology data on PFAS, please visit >>>https://pfastoxdatabase.org/

We live in a time when investigators have overwhelming amounts of health-related data at their fingertips. In this podcast, Nicole Kleinstreuer explains how environmental health scientists are using machine learning to make sense of the information in those data—for example, predicting toxicological end points based on large curated data sets. But even as machine learning advances, researchers are working to set realistic expectations and performance thresholds for these new methods. Visit the podcast webpage to download the full transcript of this podcast. 

New research describes the benefits of just spending 20 minutes in nature.  In this episode, we explore the the beautiful ramifications of spending time in nature.  The study was was done by  H. Yuen & G. Jenkins and was titled "Factors associated with changes in subjective well-being immediately after urban park visit." International Journal of Environmental Health Research 2019.  To learn more about the Happiness Podcast, go to: http://www.HappinessPodcast.org. To learn more about Dr. Puff's Corporate Workshops, go to: http://www.SuccessBeyondYourImagination.com 

As fracking operations move closer to populated areas, communities are concerned about potential impacts on their health and safety. Dr. Gregory Howard, environmental public health scientist and consultant, describes various health study designs with a focus on the goals and needs of the community and the decision makers they are trying to reach as well as the challenges of doing such research.

Topic:Diversity Equity and Inclusion, Environmental Justice and Equitable Development series – revolutionary air quality monitoring Guest & Organization:https://infiniteearthradio.com/wp-content/uploads/2018/08/veronica-eady.jpg ()Veronica Eady is Assistant Executive Officer for Environmental Justice at the California Air Resources Board. In this capacity, Ms. Eady is responsible for overseeing Environmental Justice activities of the Board.Her role will be to serve as the primary internal and external contact for CARB on environmental justice issues and concerns and will be responsible for providing policy consultation and recommendations to CARB staff. She will also participate in decision making during the development and implementation of all major CARB programs to ensure that environmental justice and tribal concerns are considered. Ms. Eady was formerly the Vice President and Director of Conservation Law Foundation Massachusetts and was the Associate General Counsel and Director of Environmental Justice at New York Lawyers for the Public Interest, a non-profit civil rights law firm in New York City. Eady has also served as Director of the Environmental Justice and Brownfields Programs for the Massachusetts Executive Office of Environmental Affairs, where she was the principal author of Massachusetts Environmental Justice Policy. Eady was also Executive Director of Alternatives for Community and Environment, an environmental justice advocacy organization. She is the former chair of EPA’s federal advisory committee for environmental justice, the National Environmental Justice Advisory Council. Eady has held appointments on several faculties, including Europe-Viadriana University in Germany, Tufts University, in the Department of Urban and Environmental Policy and Planning, Fordham Law School, and at the Stanford Law School. Eady received her B.A. in journalism from the University of Southern California, and her J.D. from the University of California, Hastings College of the Law. https://infiniteearthradio.com/wp-content/uploads/2018/08/ccvlogo_black.png ()Luis Olmedo is the executive director of Comité Civico Del Valle, a community advocacy group serving Imperial County, California. Comite Civico Del Valle (CCV) is a 501 (c) (3) organization founded in 1987 that has grown to serve thousands of children, students, community residents, and professionals in California through a variety of programs: Promotoras, Outreach Events, Educator Training, Health Education, Environmental Health Research, and Environmental Conference. In 2007, the CCV expanded its programs to work with government agencies, academia, and underserved groups on specific neighborhood environmental justice problem solving that culminated in the implementation of the “First Environmental Justice Leadership Conference”. Our Environmental Conference has been the catalyst for major policy change in the U.S./Mexico Rural California Border Region. Resources: https://ww2.arb.ca.gov/ (California Air Resources Board) https://www.ccvhealth.org/ (Comite Civico Del Valle, Inc.) http://www.skeo.com/ (Skeo Solutions)

Video Podcast (CC)Aired date: 7/28/2016 12:00:00 PM Eastern Time

Audio PodcastAired date: 7/28/2016 12:00:00 PM Eastern Time

Experimental and epidemiological studies have provided evidence of associations between air pollution and cardiovascular health. More pollution-related deaths occur from heart disease than from any other cause.A recent study in Heart aimed to further current understanding of pathophysiological mechanisms by examining the strength and specificity of acute relationships between ambient air pollution and a range of CVD events. The key mechanistic question addressed is whether events of clear thrombotic origin, namely, acute MI, stroke and related outcomes, have a stronger association with air pollution than non-thrombotic outcomes.Lead author Ai Milojevic, Department of Social and Environmental Health Research, London School of Hygiene & Tropical Medicine, describes what they found.

For World AIDS Day 2013, Anna Marry, the Communications Manager at London International Development Centre (LIDC) sits down with SOAS alum, Dr. Andy Guise, a research assistant in the Department of Social and Environmental Health Research at the London School of Hygiene and Tropical Medicine and Margarita Dimova a SOAS PhD student in the department of Politics and International Studies at SOAS.

In the past several decades there has been a sharp increase in the amount of artificial dyes and flavorings children encounter daily in foods, beverages, medicines, and toiletries such as toothpaste. Over the same period there has been a marked increase in the number of diagnoses of neurobehavioral disorders such as attention deficit/hyperactivity disorder. Bernard Weiss began studying potential links between artificial food dyes and neurobehavioral effects in children in the late 1970s. In this podcast he discusses some of his earliest research and tells why he remains convinced the two are connected. Weiss is a professor in the Department of Environmental Medicine at the University of Rochester Medical Center. Visit the podcast webpage to download a full transcript of this podcast.