I guess some good came out of Brexit. The EU essentially has banned GMO (genetically modified organisms) products, which I believe is unscientific and overly restrictive. Anti-GMO attitudes are demonstrably correlated with poor knowledge about agriculture and genetics. That’s because anti-GMO attitudes were largely created by a propaganda campaign based on lies and disinformation. For example, many people who oppose GMOs claim that Monsanto sued farmers over accidental contamination. This is absolutely not true, but it successfully demonized the industry.

The UK is now free to make up their own regulations regarding GMOs and they appear to on the verge of loosening their restrictions. However – they are limiting this loosening to “gene-edited” organisms and only plants (not animals). It’s a half-step, but at least it’s in the right direction. What is the difference between genetically modified and gene-edited?

“Gene-edited” is a new category, covering genetic changes that were previously lumped in under GMO, primarily because of the availability of new technology. A gene-edited crop is one in which one or more genes were either turned on or off, but no new genetic material was added. GMO is now limited to organisms where new genetic material is added (either cisgenic if from the same species, or transgenic if from a different species). Why the difference? It’s all ultimately arbitrary, not based on any rational science. For example, you can use radiation or chemicals to rapidly mutate crops, plant hundreds of the mutants, and then select the ones that happen to have desired traits (a process called mutation farming). That’s OK, and not considered genetically modified. Such plants even count as “organic” (another arbitrary label). But if you precisely insert a known gene, that somehow is considered a GMO and demonized by a large segment of the population.

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Memory research, both at the psychological and neurological level, is fascinating, partly because memories are so essential to who we are. We often don’t perceive the underlying mechanisms by which memories are formed, stored, and recalled, but they dramatically affect our mental life. Further, being aware of how our memories work is a critical part of neuropsychological humility – human memory is not perfect, it’s not like a tape recorder, it is a dynamic and flawed process. For example, different aspects of a memory and different memories are linked together, but these connections can be jumbled. We may fuse the detail of one memory to another, alter details completely, and even remember things that happened to someone else as if they happened to us.

This is partly because memory did not evolve to be a perfect recorder of our life experiences, but rather to create a meaningful and adaptive narrative of our past. One critical component of the adaptive nature of memories is that our brains can link different memories together, because they apparently have a meaningful connection. A recent study tries to elucidate one aspect of this process, and as a result may have turned up a clinically useful bit of information.

For a little background, our brains function as massively parallel processors. One of their core functions is to make associations between different things – when we remember one thing that triggers other memories, including details about the original memory but also other memories. Our brains are association machines. This is not only intrinsic to how we remember but how we think. Much of literature, storytelling, metaphor, and creativity derives from association. How does this work at a neuronal level? It’s safe to say that it’s complicated, but the researchers were trying to elucidate one tiny piece of the picture.

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By now many people have heard of graphene, an allotrope of carbon that is “2-Dimensional”, meaning that it is a sheet of carbon one atom thick. The carbon atoms are arranged like in a chicken wire. Graphene is considered a modern “wonder material” because it is flexible yet strong and has superior temperature and electrical conducting properties. You can also “dope” the graphene with many other elements to create novel properties. We are really just at the beginning of exploring the potential of this material, but already it us being used as an additive to make materials like plastic stronger and more conductive. A limiting factor is the ability to manufacture graphene in bulk and at high quality (with few errors in the arrangement of carbon atoms), but research is extensive because of the incredible potential of the material.

Before graphene has really hit its stride, scientists have now made for the first time a related carbon allotrope called graphyne. This is also a 2-Dimensional material with similar amazing properties like graphene, but may be even better. Previous scientists have only been able to make nanometer scale amounts of graphyne, but a recent study report the production of graphyne in bulk.  Graphyne has a different arrangement of carbon atoms than graphene. It is more complex and combines different types of carbon binding. That was the trick, to combine different types of carbon in the same material.

Carbon is an extremely useful element (and the basis of organic life) because of its unique properties. It has four available electrons with which it can form bonds with other elements, in either single, double, or triple bonds, which creates a lot of potential configurations. Carbon bonds are either sp3, sp2, or sp, depending on which electrons orbits are being used to share electrons and form a bond. You can read the details here if you are interested, but it has to do with the specific type of bonds using the different orbitals. Graphite uses only sp2 bonds, while diamond uses sp3 bonds (both are allotropes of carbon). Graphene is also sp2.

Graphyne, on the other hand, combines sp and sp2 carbon atoms which can give it useful properties:

Unlike graphenes, which consist solely of sp²-hybridized carbons, graphynes contain sp-hybridized carbons periodically integrated into an sp²-hybridized carbon framework. It was predicted that graphyne would exhibit intriguing and unique electron-conducting, mechanical and optical properties. Specifically, the electron conduction in graphynes would be exceptionally fast, as it is in graphene. Yet, the electron conduction in some graphynes could be controlled in a defined direction, unlike the multidirectional conduction in graphene, because the triple bonds can create distortion in Dirac cones.

Essentially graphyne has all the cool properties of graphene – it’s light, strong, and highly conductive to electricity and heat – but has the additional property of having controllable unidirectional conduction. Graphene, on the other hand, conducts in all directions. Controlling the direction of the conduction of electricity is critical to many electronic applications.

We are still in the “potential” stage here. Graphyne is getting a lot of attention because chemists predicted for years that it would be an incredibly useful material for electronics, but no one could manufacture it. Now a group has used a new technique to make it in bulk, which has reignited interest in the material. Further, now researchers can get their hands on the material and begin to explore its actual properties (not just theoretically predicted properties).

In the meantime, further research is needed to refine the production process, to make it quicker and cheaper for hopefully industrial scale production. This is often a deal-killer for new technologies. If you cannot produce it at an industrial scale it will remain a laboratory curiosity, or at best a high-end niche application. We may see it is probes NASA sends to the outer solar system, but not in your home or car.

Both graphene and graphyne still command incredible attention and investment because of their potential to revolutionize several industries. They could be used to make batteries with far greater energy density and specific energy than current lithium-ion batteries. They could be used in micro-optics, in superfast computers, and also wearable technology (because the materials are thin and strong). As it typically the case hype tends to get ahead of reality by 10-20 years. It takes time to work out the kinks and figure out how to make a technology actually work. It’s also possible we may never figure out a way to mass produce either material in sufficient quantities and qualities to realize the most promising applications, but given how the field is progressing we can be optimistic.

Graphyne now adds a new dimension to the promise of these new carbon 2-dimensional materials.

Demand for electric vehicles (EVs) is increasing, but still there is lingering hesitancy to make the switch to EVs. Sales of EVs have been increasing geometrically over the last decade, with global sales reaching 6.6 million in 2021, compared to 66.7 million total vehicles sold. While this trend is encouraging, there is still a long way to go and the global warming clock is ticking. So what barriers remain to more complete adoption of EVs?

Up front cost is still an issue, but this has been largely mitigated by the availability of more EV options that are in the range of comparable internal combustion engine (ICE) vehicles. Also the total cost of owning an EV is cheaper. According to a 2020 analysis:

For all EVs analyzed, the lifetime ownership costs were many thousands of dollars lower than all comparable ICE vehicles’ costs, with most EVs offering savings of between $6,000 and $10,000. While new EVs were found to offer significant cost savings over comparable ICE vehicles, the cost savings of 5- to 7-year-old used EVs was found to be two or three times larger on a percentage savings basis.

That was also before the recent spike in gasoline prices, and such spikes are not rare and likely to happen during the course of owning an EV. I wrote recently about the local health benefits of reducing pollution. I own an EV and I can also attest to other practical benefits. The driving performance is excellent, better than any ICE car I have driven. I can “fill up” at home and never have to take the car to a gas station. There is also limited routine maintenance – no oil changes or all the other things that go with an ICE. Because of regenerative braking the brake pads also last much longer. The tires are really the only thing that require attention. It is simply a superior car-owning and driving experience, and the money saving is nice.

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Having a working understanding of the biases and heuristics that our brains use to make sense of the world is critical to neuropsychological humility and metacognition. They also help use make better sense of the world, and therefore make better decisions. Here’s a fun example. Let’s say you increase your driving speed from 40 mph to 60 mph over a 100 mile journey. How much would you need to increase your speed from a starting point of 80 mph in order to save the same amount of time on the journey? Is it 100 mph or 120 mph?

Many people follow the linear bias, the false assumption that most systems follow a linear path. It is an interesting question as to why this bias is so deeply rooted in human psychology, but research shows that it is. Others may follow the ratio heuristic, and consider that 60 mph is 50% more than 40 mph so you would have to increase your speed to 120 mph to get the same 50% increase. But this too is wrong. The real answer is 240 mph. Do the math for yourself. While the ratio heuristic seems more reasonable, in this context it fails because you are not considering the fact that at higher speeds the overall trip time is less and therefore the potential time saving is also less.

When the linear and ratio biases are applied to time, in fact, psychologists refer to this as the time-saving bias. We tend to underestimate how much time we can save when starting at a slow speed and vastly overestimate time saving when starting at a relatively high speed. This bias applies to more than just driving, but also to any task. We feel that if we push our speed or efficiency higher, there will be substantial gains, but there usually isn’t. At the same time, we need to realize that bottlenecks where speed is very low present an opportunity for significant increases in efficiency. We know this, but we still tend to underestimate its effects, especially relative to increasing already high speeds.

So in any operation, whether driving on a journey, completing a task at work, or maximizing the efficiency of a factory, it is best to focus on the slowest components. There is significantly diminishing returns when improving already fast processes, and they are probably not worth it.

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What if there were a change we could make in our society that would save, in the US alone, more than 50,000 lives per year and avoid more than $600 billion every year in health care costs and lost productivity? How much should we invest each year to make the necessary changes? Even if we invested $3 trillion over the next 10 years, that would only be half as much as we would save over the same length of time (in addition to preventing have a million premature deaths). Would you say that was worth it? It sounds like a good deal, but of course we have to delve into the details.

I am talking, as you probably guessed from the title, about clean energy. Burning fossil fuels releases particulate matter into the atmosphere, which causes respiratory illness and increases the risk of stroke and heart attack. Coal is worse than oil is worse than natural gas, but they are all a problem. A newly published study set out to estimate the societal costs just from the perspective of health to the energy, transportation, and manufacturing industries and their use of fossil fuel. Here are the key findings from the abstract:

In this study, we estimate health benefits resulting from the elimination of emissions of fine particulate matter (PM2.5), sulfur dioxide, and nitrogen oxides from the electric power, transportation, building, and industrial sectors in the contiguous US. We use EPA’s CO-Benefits Risk Assessment screening tool to estimate health benefits resulting from the removal of PM2.5-related emissions from these energy-related sectors. We find that nationwide efforts to eliminate energy-related emissions could prevent 53,200 (95% CI: 46,900–59,400) premature deaths each year and provide $608 billion ($537–$678 billion) in benefits from avoided PM2.5-related illness and death. We also find that an average of 69% (range: 32%–95%) of the health benefits from emissions removal remain in the emitting region.

Even if these estimates are off by a factor of two or three, which is unlikely, we are still talking about 2-3 hundred billion dollars per year. Therefore, from a purely economic perspective, investing in clean energy is a good deal for the US, its people, and our economy. It would be economically irresponsible if we did not heavily invest in making the transition to clean energy as quickly as possible. It is important to realize the bottom line here – we can justify heavy investment in clean energy just from a health and health-related cost perspective alone. Even if you are a denier of global warming and its impacts, you should still support clean energy and rapidly phasing out fossil fuels.

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After years of requesting tiny samples of lunar soil, plant scientists at the University of Florida were finally granted 12 grams to work with (out of the 382 kg brought back during the Apollo missions). They had proposed a simple experiment – could seeds germinate and plants grow in lunar soil? It turns out the answer is yes, sort of.

The researchers used Arabidopsis, or rockcress, which is a genus that contains the first plant to have its entire genome sequenced and is therefore a favorite of plant biologists.  They added nutrient rich water to one gram pots of lunar soil and planted Arabidopsis seeds in them. As controls they planted the same seeds with the same nutrients in regular soil, and simulated lunar and Martian soil, plus Earth soil but from extreme environments. All of the seeds sprouted. For about the first six days the plants all seemed to be doing equally well, but then it became clear that the plants growing in lunar soil were smaller, more varied in size, and were showing signs of stress.

The experiment was therefore a partial success – the plants grew surprisingly well but did not thrive in the lunar soil. Because they used Arabidopsis, they were able to also track gene expression in the plants. The plants growing in lunar soil had increased expression of genes related to stress, reinforcing the conclusion that there is something about the lunar soil that is not friendly to the plants, causing them to react as if they were growing in an extreme environment.

Interestingly, the researchers had two different type of lunar soil from different locations. One type is referred to as “mature” lunar soil, which was exposed directly to the solar wind. They also had not mature lunar soil, in which the plants fared a little better.

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The healing potential of stem cells came to the public consciousness in 2001, when president George Bush banned federal funding for any research involving new embryonic stem cell lines. This sparked a public and professional debate, with proponents touting the amazing potential of stem cells to cure serious diseases, with Alzheimer’s and Parkinson’s frequently mentioned as examples. Critics were worried about the harvesting of human embryos to fuel this research. Bush’s ban was meant to be a compromise, allowing research on existing stem cell lines but banning the creation of new lines. But in practice it was a thorough ban, because existing lines were limited, and also the ban was applied to all federal funding of an entire institution in which any lab was involved in prohibited research. The US likely lost a decade of stem cell research as a result.

The Bush ban was reversed by Obama in 2009. Perhaps more importantly, starting in 2007 scientists were publishing research showing how to turn adult cells into pluripotent stem cells. These are not quite as good as embryonic stem cells, which are totipotent (pluripotent can turn into any type of cell in the body, while totipotent can turn into any cell type, including placental cells). But they are close, and also are extremely useful. Over the next decade this research continued, finding new and easier ways to program adult cells into pluripotent stem cells, called “induced” pluripotent stem cells (iPSC). These cells also have a potential advantage – they can be harvested from a person for use in that person, and therefore eliminates the issue of rejection.

Throughout the last two decades, despite the ban, stem cells have been hyped as a potential cure-all, the ability to replace or regenerate tissue and outright cure even the worst degenerative diseases. But reality has not lived up to the hype. There are many technical hurdles to using stem cells in this way – they have to survive and even thrive, take up their desired function, form anatomical structures or connections to other cells, and not form into tumors. That last bit has been a huge barrier to their therapeutic use.

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Human behavior is complex and can be very difficult to predict. This is one of the challenges of safe driving – what to do when right of way, for example, is ambiguous, or there are multiple players all interacting with each other? When people learn to drive they first master the rules, and learn their driving skills in controlled situations. As they progress they gain confidence driving in more and more complicated environments. Even still there are about 17,000 car accidents per day in the US.

It should not have been surprising, therefore, that autonomous or self-driving car technology would also find the task incredibly challenging. Self-driving algorithms not only have to learn the rules, and master the basic technology of sensing the environment with sufficient accuracy and in real time, but also to master increasingly complex and inherently unpredictable environments. A decade ago, when the technology was rapidly advancing, enthusiasts predicted that the technology would be essentially ready for the mass market by the early 2020s – so, now. But they realized that the last 5% or so of performance ability was perhaps more challenging than the first 95%. Some problems become exponentially more difficult to solve when new variables are added (we still haven’t solved the three-body problem). We have seen this with other technologies, like fusion, general AI, speech recognition, and some applications of stem cells, where early predictions were overly optimistic.

This is the challenge that AI specialists are working on now – how to get self-driving car AI systems to perform well-enough to handle the challenging situations that crop up with regularity while driving? The further complicate the issue, these systems have to function in real time, so the solution cannot involve a dramatic increase in computing that would slow down the whole system.

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Is it even theoretically possible to image in any detail the surface of an exoplanet light years away? An optical telescope would need to be many times the diameter of the Earth to produce such images. This “brute force” method of just building a giant telescope is probably never going to happen. Instead we need to find a more clever way, a method of exploiting the laws of physics to magnify distant images orders of magnitude beyond current technology. One idea gaining attention is using the sun as a giant gravitational lens.

In 1916 Einstein published his theory of General Relativity, which conceptualized gravity as a distortion of spacetime. He predicted that an object with a large gravitational field would even bend light. His predictions were validated with the 1919 total solar eclipse. During totality stars could be seen around the edge of the sun, and their apparent positions indicated that light from those stars had been bent as they passed near the sun. That validation gave a huge boost to acceptance of Einstein’s theory and made him a scientific superstar. Building on this idea he later predicted that a distant massive object with a light source directly behind it from the perspective of Earth would be surrounded by a ring of light from that more distant object – called an Einstein ring. Although relatively rare because they require a precise alignment, Hubble has found many examples.

In 1979 Von R. Eshleman wrote a paper in which he proposed that Einstein’s gravitational lens effect could be leveraged to image objects at interstellar distances. He wrote:

“The gravitational field of the sun acts as a spherical lens to magnify the intensity of radiation from a distant source along a semi-infinite focal line. A spacecraft anywhere on that line in principle could observe, eavesdrop, and communicate over interstellar distances, using equipment comparable in size and power with what is now used for interplanetary distances.”

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