Iron acquisition by amino acids under flow - Microbiology Research
In nature, bacteria encounter environments with fluctuating mixtures of nutrients, often at low concentrations that limit growth. Nutrient levels are influenced by physical processes such as fluid flow that either remove or renew nutrients, and bacteria adapt to nutrient availability to sustain their growth. However, efforts to study how low nutrient concentrations and rapid renewal shape…
Absolute Quantification of Nucleic Acids with Droplet Digital PCR
Polymerase chain reaction (PCR) revolutionized molecular biology by enabling the exponential amplification of specific DNA sequences, with applications spanning from disease diagnosis to forensic analysis. Over the years, researchers rapidly evolved PCR technology, developing quantitative PCR (qPCR), which provides real-time target quantification via fluorescence monitoring. However, qPCR relies…
20-Year Mystery Solved: Scientists Discover an Entirely New Way Cells Transport Bile Acids - Science News
A long-standing mystery in bile acid biology has been solved. Bile acids are often introduced as digestion helpers, but they are also powerful chemical messengers that help coordinate metabolism throughout the body. To do their jobs, these cholesterol-derived molecules must be shuttled efficiently between the liver, the intestine, and the blood in a recycling loop […]
Enjoy safe chemistry experiments for kids and families, using household items to explore reactions, acids, bases, and states of matter with fun, educational projects.
The Complete Guide To Layering Acids In Your Skincare Routine
“Error: skincare overload! Skincare overload!” Remember when the mere thought of putting acids on your skin made you run in the opposite direction? Now you can’t get enough of them. Glycolic acid. Lactic acid. L-Ascorbic Acid. You’re using all of them and then you’re wondering why your skin’s all dry and flaky all of a sudden… 🙄 Acids are powerful. They work. They give you results. Fast. It’s…
At LiposoMore, we specialize in developing high-quality liposomal amino acid ingredients designed for enhanced absorption and bioavailability. Unlike conventional amino acid supplements, liposomal amino acids are encapsulated in phospholipid bilayers, allowing them to bypass digestive degradation and deliver directly to cells. This advanced delivery system ensures better nutrient utilization, making it ideal for muscle recovery, energy metabolism, cognitive function, and overall cellular health. LiposoMore’s liposomal amino acid solutions are perfect for use in cutting-edge dietary supplements, including capsules, powders, liquids, and gummies—helping brands create more effective, science-driven products that meet the demands of modern consumers.
What are the Benefits of Lipoamino Acids?
1. Enhanced Absorption Efficiency
Lipoamino acids are encapsulated in liposomes, allowing for superior bioavailability compared to standard amino acids. This ensures more of the active nutrient reaches the bloodstream and cells.
2. Targeted Nutrient Delivery
Thanks to liposomal technology, lipoamino acids are delivered directly into cells, improving their effectiveness in muscle repair, recovery, and protein synthesis.
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Unlike some free-form amino acids, lipoamino acids reduce the risk of stomach irritation or degradation in the GI tract, making them suitable for sensitive users.
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Key ingredients like liposomal L-Leucine, L-Isoleucine, and L-Valine promote faster muscle recovery, improved endurance, and reduced fatigue—ideal for athletic and active lifestyles.
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LiposoMore’s lipoamino acids are non-GMO, allergen-free, and compatible with clean-label trends—meeting consumer demand for natural, effective, and science-backed supplements.
Is Liposomal Glutathione an Amino Acid?
Glutathione is Not a Single Amino Acid
While glutathione is often associated with amino acids, it is actually a tripeptide, made up of three amino acids: glutamine, cysteine, and glycine.
Liposomal Glutathione is a Delivery-Enhanced Tripeptide
Liposomal glutathione refers to glutathione encapsulated in liposomes, which significantly improves its absorption, stability, and bioavailability compared to regular forms.
Supports Cellular Detox and Antioxidant Defense
Though not a standalone amino acid, liposomal glutathione plays a critical role in detoxification, immune function, and neutralizing oxidative stress at the cellular level.
Improved Effectiveness Through Liposomal Technology
LiposoMore’s liposomal glutathione protects the active tripeptide from degradation in the digestive tract, ensuring it reaches cells intact for maximum antioxidant impact.
Often Combined with Amino Acid-Based Formulas
Due to its amino acid-derived structure, liposomal glutathione is commonly used alongside liposomal amino acids in advanced wellness and anti-aging supplement formulations.
Amino acids act as ‘anti-salt’: New insight into how small molecules stabilize proteins - New Study/Science Updates
Biologists have long known that amino acids can help stabilize proteins, for example as additives to pharmaceutical formulations. In trying to understand why this works, EPFL and MIT researchers have discovered a fundamental stabilizing effect of all small molecules, creating exciting possibilities for controlling particles in solution.
Summary EPFL and MIT researchers have discovered that small…
There are two big definitions of acids and bases. There’s Arrhenius’ definition, which involves Hydrogen and Hydroxide ions, and there’s Brønsted and Lowry’s definition, which involves proton transfers.
According to Arrhenius, an acid is a compound that produces hydrogen ions (H+) when dissolved in water. A base is then a compound that produces hydroxide ions (OH-) when dissolved in water.
According to Brønsted and Lowry, on the other hand, an acid is a compound that gives away/loses/donates protons (H+), and a base is a compound that accepts/receives them.
—
A strong acid is one that completely dissociates in water, as in your products are all ions.
A weak acid is one that partially dissociates in water, so there are some of your products are ions, but you still have some of the original acid molecules as well.
For example:
HCl being a strong acid, and HF being a weak acid.
The same goes for strong and weak bases, with one of the ions being OH-
There is no way to distinguish strong acids/bases from weak acids/bases (as far as I know) other than knowing them, and being able to recognize them.
The strong acids are HCl (hydrochloric acid), HNO3 (nitric acid), HI (hydroiodic acid), HBr (hydrobromic acid), HClO4 (perchloric acid) and H2SO4 (sulfuric acid)
The strong bases are LiOH (lithium hydroxide), NaOH (sodium hydroxide), KOH (potassium hydroxide), Ba(OH)2 (barium hydroxide), Ca(OH)2 (calcium hydroxide) and Sr(OH)2 (strontium hydroxide)
—
A neutralization reaction is a reaction that adds a base to an acid (and vice versa), and results in the formation of an ionic compound (a salt), and possibly water.
Adding a base to an acid neutralizes it in that it weakens the acid, until it is no longer an acid.
If an acid is a substance that dissociates in water, completely if strong, partially if weak, and the addition of a small amount of a base causes some of the present dissociated ions to form a salt, then the solution has the same layout(? Concentration of ions and molecules) as a weak acid.
As you add more of your base, more of the ions are taken up and become a compound, until there are no ions left, and your solution is neutral.
Why You Should Add Amino Acids To Your Skincare Routine
They’re popping out everywhere, skin care products with amino acids. They’re the new kid on the block people notice, but don’t make much of a fuss about. I’m not surprised. The best skincare ingredients are SO underrated. So if you’ve been thinking, “Amino whaaaaaaat? Are they really important for skin?,” I’ve got you covered. Let’s give these little gems the space they deserve in your skincare…
Repurposing Protein Folding Models for Generation with Latent Diffusion
PLAID is a multimodal generative model that simultaneously generates protein 1D sequence and 3D structure, by learning the latent space of protein folding models.
The awarding of the 2024 Nobel Prize to AlphaFold2 marks an important moment of recognition for the of AI role in biology. What comes next after protein folding?
In PLAID, we develop a method that learns to sample from the latent space of protein folding models to generate new proteins. It can accept compositional function and organism prompts, and can be trained on sequence databases, which are 2-4 orders of magnitude larger than structure databases. Unlike many previous protein structure generative models, PLAID addresses the multimodal co-generation problem setting: simultaneously generating both discrete sequence and continuous all-atom structural coordinates.
From structure prediction to real-world drug design
Though recent works demonstrate promise for the ability of diffusion models to generate proteins, there still exist limitations of previous models that make them impractical for real-world applications, such as:
All-atom generation: Many existing generative models only produce the backbone atoms. To produce the all-atom structure and place the sidechain atoms, we need to know the sequence. This creates a multimodal generation problem that requires simultaneous generation of discrete and continuous modalities.
Organism specificity: Proteins biologics intended for human use need to be humanized, to avoid being destroyed by the human immune system.
Control specification: Drug discovery and putting it into the hands of patients is a complex process. How can we specify these complex constraints? For example, even after the biology is tackled, you might decide that tablets are easier to transport than vials, adding a new constraint on soluability.
Generating “useful” proteins
Simply generating proteins is not as useful as controlling the generation to get useful proteins. What might an interface for this look like?
For inspiration, let’s consider how we’d control image generation via compositional textual prompts (example from Liu et al., 2022).
In PLAID, we mirror this interface for control specification. The ultimate goal is to control generation entirely via a textual interface, but here we consider compositional constraints for two axes as a proof-of-concept: function and organism:
Learning the function-structure-sequence connection. PLAID learns the tetrahedral cysteine-Fe2+/Fe3+ coordination pattern often found in metalloproteins, while maintaining high sequence-level diversity.
Training using sequence-only training data
Another important aspect of the PLAID model is that we only require sequences to train the generative model! Generative models learn the data distribution defined by its training data, and sequence databases are considerably larger than structural ones, since sequences are much cheaper to obtain than experimental structure.
Learning from a larger and broader database. The cost of obtaining protein sequences is much lower than experimentally characterizing structure, and sequence databases are 2-4 orders of magnitude larger than structural ones.
How does it work?
The reason that we’re able to train the generative model to generate structure by only using sequence data is by learning a diffusion model over the latent space of a protein folding model. Then, during inference, after sampling from this latent space of valid proteins, we can take frozen weights from the protein folding model to decode structure. Here, we use ESMFold, a successor to the AlphaFold2 model which replaces a retrieval step with a protein language model.
Our method. During training, only sequences are needed to obtain the embedding; during inference, we can decode sequence and structure from the sampled embedding. ❄️ denotes frozen weights.
In this way, we can use structural understanding information in the weights of pretrained protein folding models for the protein design task. This is analogous to how vision-language-action (VLA) models in robotics make use of priors contained in vision-language models (VLMs) trained on internet-scale data to supply perception and reasoning and understanding information.
Compressing the latent space of protein folding models
A small wrinkle with directly applying this method is that the latent space of ESMFold – indeed, the latent space of many transformer-based models – requires a lot of regularization. This space is also very large, so learning this embedding ends up mapping to high-resolution image synthesis.
To address this, we also propose CHEAP (Compressed Hourglass Embedding Adaptations of Proteins), where we learn a compression model for the joint embedding of protein sequence and structure.
We find that this latent space is actually highly compressible. By doing a bit of mechanistic interpretability to better understand the base model that we are working with, we were able to create an all-atom protein generative model.
What’s next?
Though we examine the case of protein sequence and structure generation in this work, we can adapt this method to perform multi-modal generation for any modalities where there is a predictor from a more abundant modality to a less abundant one. As sequence-to-structure predictors for proteins are beginning to tackle increasingly complex systems (e.g. AlphaFold3 is also able to predict proteins in complex with nucleic acids and molecular ligands), it’s easy to imagine performing multimodal generation over more complex systems using the same method.
If you are interested in collaborating to extend our method, or to test our method in the wet-lab, please reach out!
Further links
If you’ve found our papers useful in your research, please consider using the following BibTeX for PLAID and CHEAP:
@articlelu2024generating,
title=Generating All-Atom Protein Structure from Sequence-Only Training Data,
author=Lu, Amy X and Yan, Wilson and Robinson, Sarah A and Yang, Kevin K and Gligorijevic, Vladimir and Cho, Kyunghyun and Bonneau, Richard and Abbeel, Pieter and Frey, Nathan,
journal=bioRxiv,
pages=2024--12,
year=2024,
publisher=Cold Spring Harbor Laboratory
@articlelu2024tokenized,
title=Tokenized and Continuous Embedding Compressions of Protein Sequence and Structure,
author=Lu, Amy X and Yan, Wilson and Yang, Kevin K and Gligorijevic, Vladimir and Cho, Kyunghyun and Abbeel, Pieter and Bonneau, Richard and Frey, Nathan,
journal=bioRxiv,
pages=2024--08,
year=2024,
publisher=Cold Spring Harbor Laboratory
You can also checkout our preprints (PLAID, CHEAP) and codebases (PLAID, CHEAP).
Some bonus protein generation fun!
Additional function-prompted generations with PLAID.
Unconditional generation with PLAID.
Transmembrane proteins have hydrophobic residues at the core, where it is embedded within the fatty acid layer. These are consistently observed when prompting PLAID with transmembrane protein keywords.
Additional examples of active site recapitulation based on function keyword prompting.
Comparing samples between PLAID and all-atom baselines. PLAID samples have better diversity and captures the beta-strand pattern that has been more difficult for protein generative models to learn.
Acknowledgements
Thanks to Nathan Frey for detailed feedback on this article, and to co-authors across BAIR, Genentech, Microsoft Research, and New York University: Wilson Yan, Sarah A. Robinson, Simon Kelow, Kevin K. Yang, Vladimir Gligorijevic, Kyunghyun Cho, Richard Bonneau, Pieter Abbeel, and Nathan C. Frey.
SpaceTime Series 28 Episode 40 The Astronomy, Space and Science News Podcast Largest Organic Molecule Discovered on Mars, Parker Solar Probe’s Close Encounter with the Sun, and New Insights into Earth’s Formation In this episode of SpaceTime, we discuss the remarkable discovery made by NASA’s Curiosity Rover, which has identified the largest organic molecules ever found on Mars. These molecules, potentially remnants of fatty acids, suggest that prebiotic chemistry may have progressed further on the Red Planet than previously thought. We delve into the implications of these findings for future Mars sample return missions and the search for signs of past life. Parker Solar Probe’s Record-Breaking Philip We also cover the Parker Solar Probe’s successful close encounter with the Sun, where it reached an unprecedented distance of just 6.1 million kilometers from the solar surface. This flyby allowed for unique scientific observations of the Sun’s corona and solar wind, providing crucial data that can enhance our understanding of solar phenomena and their impact on space weather. New Insights into Earth’s Early Formation Additionally, we explore a groundbreaking study that challenges existing assumptions about the formation of Earth’s lower mantle. Researchers have found evidence suggesting that the dynamics of Earth’s early formation may have involved low-pressure crystallization, altering our understanding of how terrestrial planets evolve. 00:00 Space Time Series 28 Episode 40 for broadcast on 2 April 2025 00:49 Discovery of largest organic molecules on Mars 06:30 Implications for prebiotic chemistry and sample return missions 12:15 Parker Solar Probe’s record-setting solar encounter 18:00 Observations of the Sun’s corona and solar wind 22:45 New insights into Earth’s lower mantle formation 27:00 Summary of recent scientific developments 30:15 Discussion on healthy aging and dietary patterns www.spacetimewithstuartgary.com www.bitesz.com 🌏 Get Our Exclusive NordVPN deal here ➼ www.bitesz.com/nordvpn. Enjoy incredible discounts and bonuses! Plus, it’s risk-free with Nord’s 30-day money-back guarantee! ✌ Check out our newest sponsor - Old Glory - Iconic Music and Sports Merch and now with official NASA merchandise. Well worth checking out… Become a supporter of this Podcast for as little as $3 per month and access commercial-free episodes plus bonuses: https://www.spacetimewithstuartgary.com/about ✍️ Episode References Proceedings of the National Academy of Sciences https://www.pnas.org/ NASA https://www.nasa.gov Nature https://www.nature.com/ Become a supporter of this podcast: https://www.spreaker.com/podcast/spacetime-space-astronomy–2458531/support.
Keeping a swimming pool clean and safe requires careful attention to water chemistry. One of the key elements in maintaining a balanced pool is managing its pH levels. Many pool owners use hydrochloric acid for pools to lower high pH and alkalinity, ensuring the water remains clear and comfortable for swimmers.
Why pH Balance Matters?
The pH level of pool water measures how acidic or alkaline it is. It is typically maintained between 7.2 and 7.8 for optimal swimming conditions. When the pH level is too high, the water can become cloudy, and scale deposits may form on pool surfaces and equipment. On the other hand, if the pH level is too low, the water can become too corrosive, causing damage to pool surfaces and irritation to swimmers’ eyes and skin.
How Acid Helps in Pool Maintenance?
Acid plays a crucial role in keeping the water balanced. It is used to lower high pH levels and prevent problems such as calcium buildup and reduced chlorine effectiveness. When the pH is too high, chlorine cannot disinfect the water properly, leading to the growth of algae and bacteria. By adding the right amount of acid, pool owners can maintain a safe and clean swimming environment.
Signs That Your Pool Needs Acid
Knowing when to adjust the pH of your pool is important. Some common signs that indicate a high pH level include:
Cloudy water
Scale buildup on pool surfaces and equipment
Reduced effectiveness of chlorine
Skin and eye irritation after swimming
Regularly testing the water using a pH test kit can help detect imbalances before they become major issues.
Safe Handling and Usage of Acid
Using acid in a pool requires careful handling to avoid accidents and damage. Here are some safety tips:
Always wear protective gloves and goggles when handling acid.
Add acid to water, never water to acid, to prevent dangerous reactions.
Pour the acid slowly and distribute it evenly around the pool.
Store acid in a cool, well-ventilated area, away from other chemicals.
Alternative Methods for pH Control
While acid is commonly used for lowering pH, some alternatives can also help in maintaining water balance. These include:
Using CO2 injection systems to lower pH without affecting alkalinity
Adding pH stabilisers to reduce fluctuations
Regularly monitoring water chemistry to prevent extreme pH shifts
Conclusion
Maintaining proper pH levels is essential for a safe and enjoyable swimming experience. Acid plays a vital role in balancing pool water, preventing scale buildup, and ensuring chlorine remains effective. By understanding when and how to use it safely, pool owners can keep their water clear and comfortable throughout the year.
As more informed consumers, we’ve come a long way since the anti-fat rhetoric that pervaded the nutrition space for a few years. We now know that fat is an important part of a balanced diet and fatty acids like omega-3s are beneficial to our health. But what exactly are fatty acids, and are they the same as fat? Why are they good for us? Here’s what you need to know. What Are Fatty Acids? Fatty…
AI Just Simulated 500 Million Years of Evolution – And Created a New Protein!
Evolution has been fine-tuning life at the molecular level for billions of years. Proteins, the fundamental building blocks of life, have evolved through this process to perform various biological functions, from fighting infections to digesting food. These complex molecules comprise long chains of amino acids arranged in precise sequences that dictate their structure and function. While nature has produced an extraordinary diversity of proteins, understanding their structure and designing entirely new proteins has long been a complex challenge for scientists.
Recent advancements in artificial intelligence are transforming our ability to tackle some of biology’s most significant challenges. Previously, AI was used to predict how a given protein sequence would fold and behave – a complex challenge due to the vast number of configurations. Recently, AI has advanced to generate entirely new proteins at an unprecedented scale. This milestone has been achieved with ESM3, a multimodal generative language model designed by EvolutionaryScale. Unlike conventional AI systems designed for text processing, ESM3 has been trained to understand protein sequences, structures, and functions. What makes it truly remarkable is its ability to simulate 500 million years of evolution—a feat that has led to the creation of a completely new fluorescent protein, something never before seen in nature.
This breakthrough is a significant step toward making biology more programmable, opening new possibilities for designing custom proteins with applications in medicine, materials science, and beyond. In this article, we explore how ESM3 works, what it has achieved, and why this advancement is reshaping our understanding of biology and evolution.
Meet ESM3: The AI That Simulates Evolution
ESM3 is a multimodal language model trained to understand and generate proteins by analyzing their sequences, structures, and functions. Unlike AlphaFold, which can predict the structure of existing proteins, ESM3 is essentially a protein engineering model, allowing researchers to specify functional and structural requirements to design entirely new proteins.
The model holds deep knowledge of protein sequences, structures, and functions along with the ability to generate proteins through an interaction with users. This capability empowers the model to generate proteins that may not exist in nature yet remain biologically viable. Creating a novel green fluorescent protein (esmGFP) is a striking demonstration of this capability. Fluorescent proteins, initially discovered in jellyfish and corals, are widely used in medical research and biotechnology. To develop esmGFP, researchers provided ESM3 with key structural and functional characteristics of known fluorescent proteins. The model then iteratively refined the design, applying a chain-of-thought reasoning approach to optimize the sequence. While natural evolution could take millions of years to produce similar protein, ESM3 accelerates this process to achieve it in days or weeks.
The AI-Driven Protein Design Process
Here is how researchers have used ESM3 to develop esmGFP:
Prompting the AI – Initially, they input sequence and structural cues to guide ESM3 toward fluorescence-related features.
Generating Novel Proteins – ESM3 explored a vast space of potential sequences to produce thousands of candidate proteins.
Filtering and Refinement – The most promising designs were filtered and synthesized for laboratory testing.
Validation in Living Cells – Selected AI-designed proteins were expressed in bacteria to confirm their fluorescence and functionality.
This process has resulted to a fluorescent protein (esmGFP) unlike anything in nature.
How esmGFP Compares to Natural Proteins
What makes esmGFP extraordinary is how distant it is from known fluorescent proteins. While most newly discovered GFPs have slight variations from existing ones, esmGFP has a sequence identity of only 58% to its closest natural relative. Evolutionarily, such a difference corresponds to a diverging time of over 500 million years.
To put this into perspective, the last time proteins with similar evolutionary distances emerged, dinosaurs had not yet appeared, and multicellular life was still in its early stages. This means AI has not just accelerated evolution – it has simulated an entirely new evolutionary pathway, producing proteins that nature might never have created.
Why This Discovery Matters
This development is a significant step forward in protein engineering and deepens our understanding of evolution. By simulating millions of years of evolution in just days, AI is opening doors to exciting new possibilities:
Faster Drug Discovery: Many medicines work by targeting specific proteins, but finding the right ones is slow and expensive. AI-designed proteins could speed up this process, helping researchers discover new treatments more efficiently.
New Solutions in Bioengineering: Proteins are used in everything from breaking down plastic waste to detecting diseases. With AI-driven design, scientists can create custom proteins for healthcare, environmental protection, and even new materials.
AI as an Evolutionary Simulator: One of the most intriguing aspects of this research is that it positions AI as a simulator of evolution rather than just a tool for analysis. Traditional evolutionary simulations involve iterating through genetic mutations, often taking months or years to generate viable candidates. ESM3, however, bypasses these slow constraints by predicting functional proteins directly. This shift in approach means that AI could not just mimic evolution but actively explore evolutionary possibilities beyond nature. Given enough computational power, AI-driven evolution could uncover new biochemical properties that have never existed in the natural world.
Ethical Considerations and Responsible AI Development
While the potential benefits of AI-driven protein engineering are immense, this technology also raises ethical and safety questions. What happens when AI starts designing proteins beyond human understanding? How do we ensure these proteins are safe for medical or environmental use?
We need to focus on responsible AI development and thorough testing to tackle these concerns. AI-generated proteins, like esmGFP, should undergo extensive laboratory testing before being considered for real-world applications. Additionally, ethical frameworks for AI-driven biology are being developed to ensure transparency, safety, and public trust.
The Bottom Line
The launch of ESM3 is a vital development in the field of biotechnology. ESM3 demonstrates that evolution shouldn’t be a slow, trial-and-error process. Compressing 500 million years of protein evolution into just days opens a future where scientists can design brand-new proteins with incredible speed and accuracy. The development of ESM3 means that we can not just use AI to understand biology but also to reshape it. This breakthrough helps us to advance our ability to program biology the way we program software, unlocking possibilities we’re only beginning to imagine.
SpaceTime Series 28 Episode 15 The Astronomy, Space and Science News Podcast Building Blocks of Life on Asteroid Bennu, New Asteroid Threat, and Lunar Dome Mission In this episode of SpaceTime, we uncover groundbreaking discoveries from the asteroid Bennu, where scientists have detected the molecular building blocks of life in samples returned by NASA’s Osiris Rex spacecraft. These findings indicate a rich history of salt water on Bennu, suggesting that the essential conditions for life may have been widespread throughout the early solar system. The analysis reveals 14 amino acids and five nucleobases, hinting at the potential for life beyond Earth. A New Asteroid Threat to Earth We also discuss the newly identified asteroid 2024 YR4, which poses a significant risk with a 1 in 83 chance of impact on December 22, 2032. This near-Earth object, measuring between 40 and 100 meters wide, has astronomers concerned due to its potential for causing a powerful airburst explosion or even a surface impact. Investigating Mysterious Lunar Domes Additionally, NASA is gearing up for a mission to explore the enigmatic Gruthusen domes on the Moon, as part of the Lunar Vice mission by Firefly Aerospace. This mission aims to unravel the origins of these dome-like structures and assess the Moon’s volcanic history, providing insights into its evolution and potential resources for future exploration. 00:00 Space Time Series 28 Episode 15 for broadcast on 3 February 2025 00:49 Discovery of building blocks of life in Bennu samples 06:15 New asteroid threat 2024 YR4 12:30 NASA’s Lunar Vice mission to study lunar domes 18:00 CIA assessment on COVID-19 origins 22:45 Elderberry juice and metabolic health 27:00 Feathered dinosaur tail preserved in amber 30:15 Link between UFO sightings and economic conditions www.spacetimewithstuartgary.com www.bitesz.com 🌏 Get Our Exclusive NordVPN deal here ➼ www.bitesz.com/nordvpn.Enjoy incredible discounts and bonuses! Plus, it’s risk-free with Nord’s 30-day money-back guarantee! ✌ Check out our newest sponsor - Old Glory - Iconic Music and Sports Merch and now with official NASA merchandise. Well worth a look… Become a supporter of this Podcast for as little as $3 per month and access commercial-free episodes plus bonuses: https://www.spacetimewithstuartgary.com/about ✍️ Episode References NASA https://www.nasa.gov Nature https://www.nature.com Nature Astronomy https://www.nature.com/natureastronomy/ Current Biology https://www.cell.com/current-biology/home Journal of Nutrients https://www.mdpi.com/journal/nutrients Australian Skeptics https://www.skeptics.com.au
Toward sustainable decarbonization of aviation in Latin America
According to the International Energy Agency, aviation accounts for about 2 percent of global carbon dioxide emissions, and aviation emissions are expected to double by mid-century as demand for domestic and international air travel rises. To sharply reduce emissions in alignment with the Paris Agreement’s long-term goal to keep global warming below 1.5 degrees Celsius, the International Air Transport Association (IATA) has set a goal to achieve net-zero carbon emissions by 2050. Which raises the question: Are there technologically feasible and economically viable strategies to reach that goal within the next 25 years?
Chief among those options is the development and deployment of sustainable aviation fuel. Currently produced from low- and zero-carbon sources (feedstock) including municipal waste and non-food crops, and requiring practically no alteration of aircraft systems or refueling infrastructure, sustainable aviation fuel (SAF) has the potential to perform just as well as petroleum-based jet fuel with as low as 20 percent of its carbon footprint.
Focused on Brazil, Chile, Colombia, Ecuador, Mexico and Peru, the researchers assessed SAF feedstock availability, the costs of corresponding SAF pathways, and how SAF deployment would likely impact fuel use, prices, emissions, and aviation demand in each country. They also explored how efficiency improvements and market-based mechanisms could help the region to reach decarbonization targets. The team’s findings appear in a CS3 Special Report.
SAF emissions, costs, and sources
Under an ambitious emissions mitigation scenario designed to cap global warming at 1.5 C and raise the rate of SAF use in Latin America to 65 percent by 2050, the researchers projected aviation emissions to be reduced by about 60 percent in 2050 compared to a scenario in which existing climate policies are not strengthened. To achieve net-zero emissions by 2050, other measures would be required, such as improvements in operational and air traffic efficiencies, airplane fleet renewal, alternative forms of propulsion, and carbon offsets and removals.
As of 2024, jet fuel prices in Latin Americaare around $0.70 per liter. Based on the current availability of feedstocks, the researchers projected SAF costs within the six countries studied to range from $1.11 to $2.86 per liter. They cautioned that increased fuel prices could affect operating costs of the aviation sector and overall aviation demand unless strategies to manage price increases are implemented.
Under the 1.5 C scenario, the total cumulative capital investments required to build new SAF producing plants between 2025 and 2050 were estimated at $204 billion for the six countries (ranging from $5 billion in Ecuador to $84 billion in Brazil). The researchers identified sugarcane- and corn-based ethanol-to-jet fuel, palm oil- and soybean-based hydro-processed esters and fatty acids as the most promising feedstock sources in the near term for SAF production in Latin America.
“Our findings show that SAF offers a significant decarbonization pathway, which must be combined with an economy-wide emissions mitigation policy that uses market-based mechanisms to offset the remaining emissions,” says Sergey Paltsev, lead author of the report, MIT CS3 deputy director, and senior research scientist at the MIT Energy Initiative.
Recommendations
The researchers concluded the report with recommendations for national policymakers and aviation industry leaders in Latin America.
They stressed that government policy and regulatory mechanisms will be needed to create sufficient conditions to attract SAF investments in the region and make SAF commercially viable as the aviation industry decarbonizes operations. Without appropriate policy frameworks, SAF requirements will affect the cost of air travel. For fuel producers, stable, long-term-oriented policies and regulations will be needed to create robust supply chains, build demand for establishing economies of scale, and develop innovative pathways for producing SAF.
Finally, the research team recommended a region-wide collaboration in designing SAF policies. A unified decarbonization strategy among all countries in the region will help ensure competitiveness, economies of scale, and achievement of long-term carbon emissions-reduction goals.
“Regional feedstock availability and costs make Latin America a potential major player in SAF production,” says Angelo Gurgel, a principal research scientist at MIT CS3 and co-author of the study. “SAF requirements, combined with government support mechanisms, will ensure sustainable decarbonization while enhancing the region’s connectivity and the ability of disadvantaged communities to access air transport.”
Financial support for this study was provided by LATAM Airlines and Airbus.
