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Category: food – Page 42

A new hypothesis paper appearing in the Journal of Parkinson’s Disease on World Parkinson’s Day unites the brain-and body-first models with some of the likely causes of the disease–environmental toxicants that are either inhaled or ingested.

Pointing to a growing body of research linking environmental exposure to Parkinson’s disease, the authors believe the new models may enable the scientific community to connect specific exposures to specific forms of the disease. This effort will be aided by increasing public awareness of the adverse health effects of many chemicals in our environment. The authors conclude that their hypothesis “may explain many of the mysteries of Parkinson’s disease and open the door toward the ultimate goal–prevention.”

In addition to Parkinson’s, these models of environmental exposure may advance understanding of how toxicants contribute to other brain disorders, including autism in children, ALS in adults, and Alzheimer’s in seniors. Dorsey and his colleagues at the University of Rochester have organized a symposium on the Brain and the Environment in Washington, DC, on May 20 that will examine the role toxicants in our food, water, and air are playing in all these brain diseases.

Additional authors of the hypothesis paper include Briana De Miranda, PhD, with the University of Alabama at Birmingham, and Jacob Horsager, MD, PhD, with Aarhus University Hospital in Denmark.

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Long suspected to exist, cancer stem cells were discovered in solid tumors about 20 years ago. Is this the long-sought root cause of cancer? Thousands of scientists now believe so. Then why haven’t you heard about this from your oncologist? We delve into the debate on CSCs, and explore which foods and food supplements are most effective in the lab at killing or blocking cancer stem cells.

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Can you wirelessly power wireless devices, thus improving and advancing the technology known an “Internet of Things” (IoT)? This is what a recent study published in Energy & Environmental Science hopes to address as a team of researchers from the University of Utah investigated how pyroelectrochemical cell (PECs) could be used to self-charge IoT devices through changes in immediate surrounding temperature, also known as ambient temperature. This study holds the potential to help a myriad of industries, including agriculture and machinery, by allowing IoT devices to charge without the need for electrical outlets.

“We’re talking very low levels of energy harvesting, but the ability to have sensors that can be distributed and not need to be recharged in the field is the main advantage,” said Dr. Roseanne Warren, who is an associate professor in the Mechanical Engineering Department at the University of Utah and a co-author on the study. “We explored the basic physics of it and found that it could generate a charge with an increase in temperature or a decrease in temperature.”

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One of the largest threats to human health is obesity, but now researchers from the University of Aberdeen Rowett Institute have made an important discovery in how the brain controls food intake.

Obesity and being overweight have become the “new normal” in modern times and can lead to a multitude of health problems. We know that excess weight is primarily caused by eating more calories than the body needs; however, new research published in Current Biology has found a specific cluster of cells in the brain that control body weight.

How the brain controls hunger has not been fully defined. The researchers discovered a cluster of brain cells that can be harnessed to reduce food intake and body weight. One way they do this is by turning down cells that stimulate hunger.

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A new study has shown that food-seeking cells exist in a part of a mouse’s brain usually associated with panic — but not with feeding. Activating a selective cluster of these cells kicked mice into ‘hot pursuit’ of live and non-prey food, and showed a craving for fatty foods intense enough that the mice endured foot shocks to get them, something full mice normally would not do. If true in humans, who also carry these cells, the findings could help address the circuit that can circumvent the normal hunger pressures of ‘how, what and when to eat.’

People who find themselves rummaging around in the refrigerator for a snack not long after they’ve eaten a filling meal might have overactive food-seeking neurons, not an overactive appetite.

UCLA psychologists have discovered a circuit in the brain of mice that makes them crave food and seek it out, even when they are not hungry. When stimulated, this cluster of cells propels mice to forage vigorously and to prefer fatty and pleasurable foods like chocolate over healthier foods like carrots.

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Agriculture is a cornerstone of human civilization, a testament to our ability to harness nature for sustenance. Yet, this age-old industry faces many challenges that hamper productivity, impact livelihoods, and threaten global food security.

By 2050, we must produce 60 percent more food to feed a world population of 9.3 billion, reports the Food and Agriculture Organization. Given the current industry challenges, doing that with a farming-as-usual approach could be tricky. Moreover, this would extend the heavy toll we already place on our natural resources.

This is where Artificial Intelligence can come to our rescue. The AI in Agriculture Market is projected to grow from $1.7 billion in 2023 to $4.7 billion by 2028, highlighting the pivotal role of advanced technologies in this sector. This article explores three significant issues agriculture faces today and shows how AI is helping tackle them using real-world examples.

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Scientists have developed a sustainable method to make high-performance plastics from agricultural leftovers, turning them into valuable materials.

In our rapidly industrialized world, the quest for sustainable materials has never been more urgent. Plastics, ubiquitous in daily life, pose significant environmental challenges, primarily due to their fossil fuel origins and problematic disposal.

Now, a study led by Jeremy Luterbacher’s team at EPFL unveils a pioneering approach to producing high-performance plastics from renewable resources.

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Since ChatGPT debuted in the fall of 2022, much of the interest in generative AI has centered around large language models. Large language models, or LLMs, are the giant compute-intensive computer models that are powering the chatbots and image generators that seemingly everyone is using and talking about nowadays.

While there’s no doubt that LLMs produce impressive and human-like responses to most prompts, the reality is most general-purpose LLMs suffer when it comes to deep domain knowledge around things like, say, health, nutrition, or culinary. Not that this has stopped folks from using them, with occasionally bad or even laughable results and all when we ask for a personalized nutrition plan or to make a recipe.

LLMs’ shortcomings in creating credible and trusted results around those specific domains have led to growing interest in what the AI community is calling small language models (SLMs). What are SLMs? Essentially, they are smaller and simpler language models that require less computational power and fewer lines of code, and often, they are specialized in their focus.

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