Genetic engineering is a rapidly progressing scientific discipline, with tremendous current application and future potential. It’s a bit dizzying for a science communicator who is not directly involved in genetics research to keep up. I do have some graduate level training in genetics so at least I understand the language enough to try to translate the latest research for a general audience.

Many readers have by now heard of CRISPR – a powerful method of altering or silencing genes that brings down the cost and complexity so that almost any genetics lab can use this technique. CRISPR is actually just the latest of several powerful gene-altering techniques, such as TALEN. CRISPR is essentially a way to target a specific sequence of the DNA, and then deliver a package which does something, like splice the DNA. But you also need to target the correct cells. In a petri dish, this is simple. But in living organism, this is a huge challenge. We have developed several viral vectors that can be targeted to specific cell types in order to deliver the CRIPR (or TALEN), which then targets the specific DNA.

Now I would like to present a different technique I have not previously written about here – alternative splicing. A recent study presents what seems like a significant advance in this technology, so it’s a good time to review it. “Alternative splicing” refers to a natural phenomenon of genetics. Genes are composed of introns and exons. I always thought the nomenclature was counterintuitive, but the exons are actually the part of the gene that gets expressed into a protein. The introns are the part that is not expressed, so they are cut out of the gene when it is being converted into mRNA, and the exons are stitched together to form the sequence that is translated into a protein. Alternative splicing refers to the fact that the way in which the introns are removed and the exons stitched together can vary, creating alternative forms of the resulting protein. This dramatically increases the number of different proteins that an organism’s genes can code for, because each gene can potentially code for multiple protein variants through alternative splicing.

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I get lots of e-mail, sometimes from people who want to convince me that their pet theory has merit – in explicit hope that I will champion their cause and spread their theory. They are always disappointed. The exchange is always the same, almost eerily so, as if they are all following the same script. I think to an extent they are – they are all absorbing the same narrative from the culture. So here is my generic response to all cranks, past and future.

Dear Crank,

I use that term not as a personal attack, but as an accurate description of your behavior. I want you to understand why that behavior is not serving you well, and what you can do the escape from a cycle of self-destructive, and frankly annoying, behavior. Hey – you e-mailed me, you jumped up in front of me waving your hands in order to get my attention. Well, you got it. And now I am going to do you a massive favor. I am going to give you a tiny slice of the attention you are so clearly desperate for and explain to you why you are a crank.

I understand you have a theory with which you are very impressed, and it includes a lot of math and facts and details. You may even have some scientific education and background. But if you think you have somehow seen through the fog, and have proven that the world’s scientists have all been hopelessly wrong for the last century or so, then you are likely suffering from not only a lack of proper humility, but overwhelming hubris. You may think that you have proven with one devastating argument that evolution is impossible, or global warming is not real, or that you have created free-energy, cured cancer, or changed everything we thought we knew about history (or whatever), but you haven’t.

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A new Pew survey updates their data on American’s trust in scientists. The “good news” is that overall, trust remains high, with 77% saying they trust scientists a great deal or a fair amount, and only 23% not too much or not at all. Actually, when you think about it these numbers are still pretty bad, but they seem good because our expectations are so low. More than one in five people don’t trust scientists. For more perspective, that 77% figure is the same for the military. The highest rated group was medical scientists at 80%. Elected officials were at 28%.

These numbers are also fairly stable over time. Interestingly they did bump up a bit during the pandemic, but then quickly returned to their historical levels. Some argue that these numbers are pretty good and we shouldn’t “freak out about the minority.” I disagree – not that we should freak out, but we do need to take these numbers seriously, and they are not necessarily good news.

One reason I am still concerned about these numbers is that there is a pretty significant partisan divide. Recent years have Democrats at around 90% with Republicans around 63%. More than a third of one major political party does not trust scientists, and they seem to be the political center of the party. This gets even worse if you look at the question of whether or not scientists should play an active role in policy debates. Only 66% of Democrats say yes, and only 29% of Republicans (down from 75 and 43 respectively). This, to me, is very telling. It’s one thing to say you trust scientists, but what does that mean that you also don’t want them to play an active role in policy?

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At a recent talk, during the Q&A an audience member asked me what I thought the consequences would be of the “idiocracy” we seem to be heading toward. I challenged the premise, that people in general are becoming less intelligent. I know it may superficially seem like this, but that has more to do with media savvy, echochambers, tribalism, and radicalization, not any demonstrable decline in raw intelligence.

In fact, I pointed out, in the last century there has been a consistent increase in IQ testing ability, by about 3 IQ points per decade (called the Flynn Effect). There is still debate about what this means, and it is important to point out that IQ testing does not equal “intelligence” which is multifaceted. But whatever standard IQ tests are measuring, performance is generally improving over time. Another measure, that of civic scientific literacy (in a longstanding series of studies by Jon Miller), increased from 1988 t0 2008 from 9% to 29%. It has since plateaued at that level.

There is no consensus as to why this is so, but I have some thoughts based on the literature. Technology is exposing people to more information, and this has only been increasing further with the advent of computers, the internet, and even social media. Regardless of any negative effects, people seem to know more stuff, and have improved problem-solving skills. Our brains are busier, they are exposed to more ideas and facts, we interact with a greater number of different people and opinions, and we have to interface with technology and information more. The workforce is shifting from manual labor to more intellectual labor. Even just going through your normal day likely involves interacting with technology that would have befuddled older generations.

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In the race to decarbonize our energy infrastructure as fast as possible, renewable energy gets most of the attention. This is will good reason – wind and solar are the cheapest new energy capacity to install, with solar beating out wind. But of course, as I have discussed before, we have to look at the whole energy infrastructure picture, not just the cost of installation. There are advantages and disadvantages to all forms of energy. Right now I think it is reasonable to prioritize energy with the lowest carbon footprint, but we cannot ignore other factors.

The primary disadvantage of wind and solar is that they are intermittent. We need some on-demand energy as well, which for non-fossil fuel sources includes grid storage, hydroelectric, nuclear, and geothermal. For wind and solar we also want to choose locations and amounts that have the least environmental impact and are the most functional for each power grid. We could not, for example, have 100% solar at this time, even though solar (when considered in isolation) is cheapest. This because the sun only shines during the day (when it’s not too cloudy) and it would take massive grid storage to shift all solar production to when it was needed.

While wind often plays second-fiddle to solar in terms of renewable energy, it has some significant advantages, and makes a good combination with solar. While wind is also intermittent, it is not as limited to a specific time of day like solar. The wind blows at night, and not all of the place at the same time. With enough wind capacity spread over a large enough area, it may literally be true that the wind is always blowing somewhere.

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Cosmologists have recently published the updated results of an extensive analysis of the overall structure of the cosmos, with interesting results. It both solidifies our current understanding of the universe, but also reinforces a conflict that scientists have not been able to solve.

The story begins with Type IA supernova. A supernova is when a star explodes because of runaway fusion in its core. Different stars of different masses and compositions will explode with different energies and therefore intrinsic brightness. But a Type IA is caused by a white dwarf star in a binary system which is leaching matter off its companion. The white dwarf slowly gains mass until it reaching the Chandrasehkar limit, the point at which its gravity overcomes the outward pressure of heat and energy, the star then collapses and goes supernova. This means that all Type IA supernova are the exact same mass when they explode, which further means that they should have the same intrinsic brightness. In reality there is some variability in peak brightness based on other variables like composition, but astronomers have learned to make adjustments so as to arrive at a precise measure of intrinsic brightness.

Knowing the intrinsic brightness of an astronomical object is hugely useful. It means we can calculate based on its apparent brightness exactly how far away it is. Such objects are known as standard candles, and the Type IA supernova are perhaps the most useful we have. Type IAs are also really bright, outshining entire galaxies, which further means we can see them really far away, about 10 billion light years. There is also a lot of them happening around the universe. Looking far away is also looking back in time, so Type IAs not only allow us to measure the cosmos, but also to measure it throughout its history (back to 10 billion years).

It was observations of Type IA supernova that allowed astronomers to first determine that the universe is not only expanding, it’s accelerating. Since then astronomers have been gathering data on Type IAs in a project called Pantheon. The catalogued more than 1,000 Type IAs providing the most precise measure of the rate of the universe’s expansion, called the Hubble Constant. Now they have published what they are calling Pantheon+, with an expanded database of over 1,500 Type IA supernova. They have also been able to tweak their methods to make more precise measurements, account for more factors, and essentially give a much more detailed account of the Hubble Constant at different times throughout the history of the universe.

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Imagine injecting microscopic robots into a patient that then can be guided to a specific location in the body where they deliver drugs or stem cells for therapy. This technology is actually not far off. Researchers have been developing multiple types of tiny medical robots, and some have been used successfully in animals.

The simplest form of such microbots is a tiny sphere that contains magnetic nanoparticles and has a nanoscale structured surface. The surface allow for stem cells to bind so that they can be delivered to the desired location. The movement of the microbots is controlled by an external magnetic field acting on the nanoparticles. Essentially they are a delivery system, and when their task is done they are biodegradable so they break down and are eliminated by the usual mechanisms. Microbots can also be designed to be infused with drugs to deliver to their target.

There are numerous applications for this technology. One obvious one is the targeting of tumors. Effective anti-cancer treatments are often limited by their toxicity, but if they can be delivered directly to a tumor then they are both more effective and less toxic to healthy tissue. Stem cells can also be delivered, and they can also be engineered to kill cancer cells. They could also be engineered to produce hormones or chemical, or they could support other cells or even take up function themselves.

Other microbots can be self-propelled, including:  “tailor-made motile bacteria and tiny bubble-propelled microengines to hybrid spermbots.” Another approach combines algae cells and nanoparticle to produce a microbot that can swim around specific organs, such as the lungs. This was tested in pneumonia in mice, and the microbots were able to swim around and kill the infecting bacteria.

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Humanity has an uncanny ability to turn any new potential boon into con. The promise of stem cell technology quickly spawned fraudulent stem-cell clinics to exploit the desperate. There is snake oil based on lasers, holograms, and radio waves. Any new tech or scientific discovery becomes a marketing scam, going back to electromagnetism and continuing today with “nanotechnology”. There is some indication that artificial intelligence (AI) will be no exception.

I am a big fan of AI technology, and clearly it has reached a turning point where the potential applications are exploding. The basic algorithms haven’t changed, but with faster computers, an internet full of training data, and AI scientists finding more ways to cleverly leverage the technology, we are seeing more and more amazing applications, from self-driving cars to AI art programs. AI is likely to be increasingly embedded in everything we do.

But with great potential comes great hype. Also, for many people, AI is a black box of science and technology they don’t understand. It may as well be magic. And that is a recipe for exploitation. A recent BBC article, for example, highlights to risks of relying on AI in evaluating job applicants. It’s a great example of what is likely to become a far larger problem.

I think the core issue is that for many people, those for whom AI is mostly a black box, there is the risk of attributing false authority to AI and treating it like a magic wand. Companies can therefore offer AI services that are essentially pure pseudoscience, but since it involves AI, people will buy it. In the case of hiring practices, AI is being applied to inherently bogus analysis, which doesn’t change the nature of the analysis, it just gives it a patina of impeachable technology, which makes it more dangerous.

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Science is fun, interesting, and empowering, but it is also hard, especially at advanced levels. Even at a basic level, science forces you to think clearly, precisely, logically, and objectively. It therefore challenges our preconceptions, our biases, our hopes and desires and replaces these things with indifferent reality. Science becomes progressively tricky the more advanced it becomes, requiring an increasing fund of knowledge and mastery over subtle concepts and technical skills in order to be able to take the next step. At the cutting edge of science, nothing short of years of dedicated study is necessary to engage meaningfully with the enterprise of advancing human scientific knowledge. You also have to be able to engage productively with a community of scientists, all picking apart each other’s work.

It’s for these reasons that there is a lot of bad science out there. There are also those who prioritize things other than the pursuit of scientific knowledge, such as money, fame, or advancing an ideology. Many people mean well, but simply get the science wrong. Even successful scientists can make egregious errors, stubbornly stick to false ideas, or let their own ideology get in the way. So what is the average science enthusiast to do? Unless you have a fairly high level of scientific expertise in general and also in a specific field, you cannot hope to engage with the cutting edge of that field. To some extent, you have to trust the experts, but what if the experts disagree, or some of them are just wrong?

There is no easy answer to this, but there are skills and methods other than actual expertise in a specific field that can help a layperson have a pretty good idea which experts to listen to. This requires some scientific literacy, especially about how proper science operates. It also requires a certain amount of critical thinking skills – knowing something about logic, self-deception, and the nature of evidence. Further, we can learn to recognize the different types of pseudoscience and pseudoscientific behaviors, which can act as reliable red-flags to help spot fake science. Recently promoters of the Electric Universe have appeared in the comments to this blog, and this is a good opportunity to review these red flags.

The idea of the electric universe (EU) is that electromagnetism actually does most of the large-scale heavy lifting when it comes to the structure of the cosmos, displacing gravity as the main long-distance force. There are different flavors of EU, with some doing away with gravity completely, and others allowing for some gravity (to help explain phenomena EU can’t) but still relegate it to a minor role. One major example is that EU proponents believe stars are fueled by electromagnetism, and not by gravity-induced fusion. Here are two great videos that give a concise summary of the history of EU belief and why it is complete and utter nonsense. But I will review the major problems with EU and use them as examples of crank pseudoscience.

Crank pseudoscience is a flavor of pseudoscience that operates at a technically sophisticated level, but is missing some of the key elements of actual science that doom proponents to absurdity. But it also contains many of the generic features of pseudoscience. Let’s review, starting with features more typical of crank pseudoscience.

Does not engage meaningfully with the scientific community.

Science is a collaborative effort, especially at the advanced cutting edge level. This is because it is so difficult at this level, you need the self-corrective process of peer-review, rejection of error, criticism of wrong ideas, challenges for evidence and by alternative theories, etc. Without this self-corrective process, fringe groups or individuals tend to drift off from reality into a fantasy land of their own creation, although gilded with the superficial trappings of science. EU proponent Montgomery Childs exemplifies this in an interview (in the second video above) when he tries lamely to justify not bothering to publish any of his findings in scientific journals. Actual experts in plasma physics and cosmology therefore just ignore his fringe work – unless they have data to look at, they don’t have much of a choice. This is a core feature of crank pseudoscience – cranks tend to toil alone or in small fringe echochambers and not engage with proper experts.

Work outside their actual area of expertise (if they have one).

Often we see scientists or engineering getting into crank science when they venture beyond their specific area of expertise. Sometimes this is just hubris – in fact we joke about the Nobel Prize effect, where some Nobel Prize winners go on to support pseudoscience later in their career. There is also an aging-scientist effect where researchers toward the end of their career start looking at their legacy, or lack of one, and want to make a big splash somewhere. Some choose a small fringe pond where their credentials make them a big fish, and start promoting nonsense. The problem, of course, if that being an expert in one area does not equip you to contradict actual experts in a separate field. Electrical engineers are not cosmologists or physicists. It is therefore helpful to see what the most appropriate experts say about a theory, not just anyone with letters after their name. Actual experts reject the EU as completely nonsense (with good reason), and its proponents are all in unrelated fields.

Make grandiose claims while minimizing actual scientific knowledge.

The EU claims to overhaul much of science, which is itself a red flag. It is hard to prove that established science is all wrong, and it’s getting harder as science advances and the foundational concepts of science are increasingly supported by evidence and derivative theories. What cranks often do is grossly exaggerate what is currently unknown in a scientific field, or the meaning of anomalies, and they downplay what is known with confidence. This often become simply lying, making boldly false claims about the state of the science. EU proponents, for example, ignore or deny the evidence for the Big Bang, black holes, stellar fusion, and gravity. The claim that they have overturned pretty much all of astrophysics, stellar astronomy, General Relativity, and more – all on the flimsiest of pretexts. In other words, they reject theories supported by a mountain of evidence, and replace them with theories that have (at best) an ant hill.

They don’t actually explain 0r predict anything.

Another core feature of science is that it makes testable predictions. What this means is that there has to be some way to determine if one theory is more correct than another, because they make different predictions about what we will observe in the universe or the result of experiments. Scientific theories also should have explanatory power (it can explain what we see) – but this is actually necessary but insufficient feature of science. Astrology has explanatory power – if you are willing to just make up BS explanations for stuff. It’s easy, and pattern-seeking humans are good at, finding explanations of stuff. The problem with EU is that it really does neither – predict or explain. In fact, shifting from current cosmological theories to EU would be a massive step backwards. EU cannot explain a ton of established phenomena that are well explained by current theories, such as the evidence for black holes or dark matter, the lifecycle of stars, the existence of neutrinos from stellar fusion, and many more. There are also fundamental problems with EU, such as the known behavior of electromagnetism and charged particles. What EU proponents do, rather, is simply hunt for patterns, and then make very superficial connections between some aspect of EU theory and some astronomical phenomenon.

This is what triggered some of the comments – the regular rings of dust found around WR140, caused by the periodicity of the wind-binary star system. EU proponents said – look, concentric rings. We see those in the plasma dohickey thing. They then count that as a “prediction” when it was actually just retrofitting, and not very well. They falsely call the rings “perfect” when it is the very imperfections in the rings that can be accounted for by the astronomical explanation.

Portray the scientific community as a conspiracy of the small-minded.

If you have a nonsensical fringe theory and don’t publish your findings (except in fringe journals created for that purpose), it’s likely that the broader scientific community with ignore or reject your claims. They should – you have not earned their assent by demonstrating your claims with objective and publicly available evidence. When that happens, cranks universally claim they are the victim of a conspiracy. They don’t self-correct, address legitimate criticisms, recognize the shortcomings of their theories, do better experiments or, in short, engage in legitimate science. They cry foul. They say something to the effect that “mainstream” science is all a conspiracy, and scientist are simply too dumb or too scared to recognize their towering genius. This is the point that self-comparisons to Galileo or Einstein are typically brought out.

EU proponents do this in spades. There is a large, vibrant, world-wide community of astrophysicists, all at different parts of their career, in different countries and institutions, just trying to figure out how the universe works and hopefully make a name for themselves doing so. Yet a few fringe scientists, without the proper expertise, allege they have proven all of them hopelessly wrong, because they are all biased or don’t know what they are doing. And they are stubbornly not convinced by silly superficial evidence its proponents won’t bother to publish. Imagine!

This is definitely the neuroscience news of the week. It shows how you can take an incremental scientific advance and hype it into a “new science” and a breakthrough and the media will generally just eat it up. Did scientists teach a clump of brain cells to play the video-game pong? Well, yes and no. The actual science here is fascinating and very interesting, but I fear it is generally getting lost in the hype.

This is what the researchers actually did – they cultured mouse or human neurons derived from stem cells onto a multi-electrode array (MEA). The MEA can both read and stimulate the neurons. Neurons spontaneously network together, so that’s what these neurons did.  They then stimulated the two-dimensional network of neurons either on the left or the right and at different frequencies, and recorded the network’s response. If the network responded in a way the scientists deemed correct, then they were “rewarded” with a predictable further stimulation. If their response was deemed incorrect, they were “punished” with random stimulation. Over time the network learned to produce the desired response, and its learning accelerated. Further, human neurons learned faster than mouse neurons.

Why did this happen? That is what researchers are trying to figure out, but the authors speculate that predictable stimulation allows the neurons to make more stable connections, while random stimulation is disruptive. Therefore predictable feedback tends to reinforce whatever network pattern results in predictable feedback. In this way the network is behaving like a simple AI algorithm.

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