Time Capsules in the Language of Science

In elementary school, I spent an art class layering greens. Jungle green fabric with a subtle coordinating stripe, delicate spring green tissue paper so translucent you could see through it, pieces of chunky emerald felt cut into the shape of leaves, sparkling seafoam and teal glitter, all of it pressed and glued onto a piece of tagboard in what my teacher called a monochromatic collage. All shades of one color. Mono: one. Chroma: color. I didn’t think about the word at the time because I was too busy glittering.

That same week, I took a science quiz on monocots and dicots and got the answer wrong. I couldn’t remember which plants had one seed leaf and which had two. When I got the test back and saw my error, it clicked. Of course a monocot has one seed leaf. I’d been using mono in art class while missing it on a science quiz down the hall. The root moved between rooms, but I hadn’t learned yet that it could.

That stuck with me. Although my formal education is in English and linguistics, my mind naturally sought out scientific connections. Greek and Latin roots were the place where those two interests didn’t have to compete. They had the precision of formulas, a combinatorial logic where twenty roots could unlock hundreds of words, and they worked on both sides of the hallway.

I write about science now, and the roots have remained my constant companion. A few weeks ago I was researching an organism called Rapaza viridis for a blog post on endosymbiosis. I’d never heard of it, but since viridis is Latin for green (the same root that gives us “verdant”), I already guessed this creature had something to do with photosynthesis. It does. R. viridis is a single-celled predator that steals chloroplasts from the algae it hunts and uses them to photosynthesize.

Learning more about the organism, I came across the term “transient chimerism.” Also new to me, but also immediately legible. The trans in “transient” is the same as in “transparent” and “transport”: ‘across,’ ‘through.’ Something passing through. Chimera: the Greek monster stitched together from a lion, a goat, and a serpent. Put together: a temporary state of being made from parts of more than one organism. The roots came through for me once again.

This keeps happening. I’ll hit a term I’ve never seen, and its pieces already feel familiar. I could spend this entire blog walking through terms and showing you their roots, but definitions only stay interesting for so long (and my family already compares me to the father in My Big Fat Greek Wedding). What I’ve become more interested in is something the roots do beyond defining. The roots that end up in a name tend to carry more than a definition. They carry an interpretation, an argument about the thing itself.

For years, I wondered about apoptosis. I knew apo meant ‘away from.’ I could see ptosis maybe shared something with “asymptote,” but I couldn’t figure out what cell death had to do with calculus. In 1972, John Kerr, an Australian pathologist, had been studying a form of cell death that looked nothing like anything he’d seen before. For most of pathology’s history, the only cell death anyone studied was the kind that showed up when something had gone wrong: a cell damaged by injury or infection or toxins, dying violently. That kind of death had a name: necrosis, from the Greek nekros (‘corpse’). The cell swells, ruptures, spills its contents, and triggers inflammation. Studying liver tissue, Kerr noticed a second kind of death happening quietly alongside it, in cells that hadn’t been damaged at all. The cell death he was watching was the opposite. The cell shrank, and its contents condensed. It broke apart into tidy packages that neighboring cells quietly absorbed. No mess. The body had planned this.

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New Approach Methodologies: Guidelines for Biological Ground Truths

FDA Regulation changes: The Problem is still Validation

In March 2026, the FDA published draft guidance that fundamentally changed how NAMs (New Approach Methodologies) are evaluated in drug development. If youโ€™re designing NAMs, whether that be spheroids, organoids, or organs-on-a-chip, your model now must meet specific validation criteria set by regulators. This draft document, titled ‘General Considerations for the Use of New Approach Methodologies in Drug Development’ provides requirements on the use of NAMs, including in vitro, in silico and in chemico methods (FDA & CDER, 2026). This guidance is a big shift from aspirational recommendations towards clearer regulatory recommendations.

It comes on the coattails of consistent feedback and challenges the market has seen over the past few years as they attempt to transition and optimize away from animal models. Mainly being:

โ€œHow can I be sure the data I get from this non-animal model is reliable, trustworthy and relevant?โ€

This regulatory mandate from the FDA requires researchers to use models and assays that meet four validation criteria:

  • Context of use
  • Human biological relevance
  • Technical characterization
  • Fit-for-purpose

This guidance initially applies to antibody development, biologics, and will eventually be relevant for small molecules. The momentum in the market is sound and indicates that there is a real need for assays that meet these new requirements.

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What Counts as Evidence

This is the third post of three in a series leading up to the 16th annual International Forum on Consciousness, taking place in Madison this May. Hosted by the BTC Institute, Promega and Usona Institute, the forum gathers scientists, philosophers, and practitioners from dozens of different fields to investigate the nature of the mind. This yearโ€™s theme, โ€œUnspoken Intelligence,โ€ explores forms of perception and knowing that fall outside conventional cognition.

In 1845, mathematician Urbain Le Verrier calculated where an unseen planet had to be based on irregularities in Uranus’s orbit, wrote a letter to an observatory telling them where to point their telescope, and Neptune was there. He found a planet without ever looking up.

This is what third-person inquiry looks like at its best: observe from the outside, measure what anyone with the right instruments can measure, build a model precise enough to predict what no one has seen yet. Then look. The history of science is full of such moments, equations pointing to phenomena that hadn’t been detected, particles that hadn’t been observed, forces that hadn’t been measured. The method works because it is ruthlessly disciplined about what counts as evidence. The observer is removed, the conditions controlled, and the measurement trusted.

That discipline is not a limitation. It is the engine of over four centuries of extraordinary results. It gave us germ theory, the structure of DNA, and the sequenced human genome. Every time something seemed to resist physical explanation, the method eventually found the mechanism and the method held. The winning streak was long enough that the assumption underneath it stopped looking like an assumption. Outside-in, third-person, measurable evidence stopped looking like one way of knowing. It started looking like the definition of knowing itself.

The assumption felt safe because it had earned its confidence. Digestion, heredity, mental illness, each had seemed to resist physical explanation until it didn’t. The pattern was consistent enough that the method felt inevitable rather than chosen.

Then science turned toward consciousness, and the winning streak entered dangerous territory.


Here is the problem, what philosopher David Chalmers named the “hard problem” of consciousness in 1995.

To understand what Chalmers meant, it helps to start with his own illustration. When you see red, something measurable happens. Light hits the retina. Signals travel along the optic nerve. Specific regions of the visual cortex activate in patterns that neuroscientists can map with increasing precision. All of that is, in principle, fully describable by the third-person, outside-in approach. Given enough time and instruments, you can trace the whole sequence.

What you cannot describe from the outside is what red looks like. The redness of red, that specific quality of experience that exists only in the moment of seeing it, is not in the neural map. No better scanner will find it there, because the felt quality of the experience isn’t a physical thing hiding in the data. It exists only from the inside. The outside measurement, however precise, cannot reach it.

Chalmers used “hard” deliberately, in contrast to what he called the “easy problems” of consciousness: how the brain integrates information, focuses attention, produces behavior. Those are genuinely difficult, but the outside-in approach knows how to go after them. The hard problem is different in kind. It’s the question that remains even after you’ve solved all of the “easy” ones: why does any of it feel like anything at all?

Think of it this way: everything the brain does could, in principle, happen without any felt experience attached. Processing, responding, behaving, all of it could run like a machine in the dark, with no one home. The question Chalmers is asking is why it doesn’t. Philosophers ask it this way: why is there something it’s like to be you, right now, reading this?

No amount of outside-in evidence, however precise, touches that question, not because the science is insufficient but because the method was specifically designed to exclude first-person data. That exclusion was the whole point. It’s what made the outside-in approach so powerful everywhere else.

With consciousness, the method’s central design decision runs into a question it wasn’t built to answer: how do you study first-person experience when your method was built to exclude first-person data?

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Moreย Than Beer and Cheese:ย Why Wisconsin Has Always Been Good Ground for Scienceย 

Challenging Assumptions About Innovation

When people talk about places where science and technology tend to flourish, a few names surface almost immediately. Silicon Valley, Boston, Seattle, Houston. Cities associated with density, competition and speed.

For many people outside the state, Wisconsin still collapses into a short list of associations: beer, cheese, cold winters, maybe a football team. Biotechnology rarely makes that list.

That hesitation usually has less to do with science itself and more to do with assumptions about where innovation is supposed to live. National Wisconsin Day, celebrated February 15, is a good moment to look past those assumptions and consider what Wisconsin has quietly offered for a long time: an environment and culture that is well-suited for scientific advances.

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The Science of Slippingโ€ฆ Blame the Molecules!

Whether itโ€™s Home Aloneโ€™s booby-trapped icy steps, Bambi learning his legs have zero traction, or an Ice Age chase scene defying gravity, ice has been comedy gold for decades. In real life, the joke lands a little harder (sometimes literally).

Slippery Ice

We all know ice is slippery. The more surprising part is why itโ€™s slippery and how long it took scientists to start agreeing on something closer to an answer. Researchers have long known the surface of ice behaves like itโ€™s wearing a microscopic โ€œwetโ€ layer that lubricates motion. What theyโ€™ve argued about for nearly 200 years is what creates that layer in the first place (3,4).

So, letโ€™s treat this like a mystery. Ice is the crime scene. Your dignity is the victim. Here are the main suspects.

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Why Do We Love Being Scared? The Science Behind Horror Movies

Haunted mansion with pointed towers in a foggy, moonlit forest, creating a spooky, eerie atmosphere.

Thereโ€™s something oddly captivating about watching a film that makes you jump, scream, or better yetโ€”a film that sticks with you long after watching. Millions of people embrace the fear, willingly diving into the dark world of horror movies. But why? What is the appeal of subjecting ourselves to terror? The reasons we watch and enjoy scary movies go far beyond the jump scaresโ€”theyโ€™re deeply psychological.

For those who find themselves covering their eyes or clutching the nearest pillow, it might be hard to understand. Yet, as the hair-raising month of October ends, many people spent the 31 days leading up to Halloween watching films designed to scare the daylights out of them. In this blog, we explore why people enjoy fear (or why theyย donโ€™t) and what psychology reveals about the movies that truly terrify us.

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The Casual Catalyst: Science Conversations and Cafes

There is no shortage of stories about great scientific collaborations that have taken root as the result of an excited conversation between two scientists over sandwiches and beer at a bar or a deli. One of the most famous examples of such a conversation was that between Herbert Boyer and Stanley Cohen when they attended a conference on bacterial plasmids in 1972โ€”that very conversation led to the formation of the biotechnology field as the two scientists worked together to clone specific regions of DNA (1).ย ย 

โ€œOver hot pastrami and corned beef sandwiches, Herbert Boyer and Stanley Cohen opened the door to genetic engineering and laid the foundations for gene therapy and the biotechnology industry.โ€  

Steven Johnson, author of Where Do Good Ideas Come From, credits the English coffee house as being crucial to the spread of the enlightenment movement in the 17th and 18th centuries (2). He argues that coffee houses provide a space where ideas can come together and form networks. In fact, he defines the concept of โ€œideaโ€ not as a single entityโ€”a grand thought that poofs into existence upon hard workโ€”but at its simplest level, a new idea is a new network of neurons firing in sync with each other.  

Johnson further argues that the development of great new ideas not only requires a space for ideas to bump into each other, connect and form a network, but also that great ideas are rarely the product of a single โ€œEurekaโ€ moment. Rather, they are slowly developing, churning hunches that have very long incubation periods (2).  

Science is Ripe with “Coffee House” Discoveries

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The Central Dogma of Promega: The Story and Science Behind Our Kit Packaging Design

An amazing transformation is taking place, unseen and unnoticed, within the microscopic bits that make you, you.

A tightly coiled lattice unspools to reveal a sinuous DNA stand. Along its length, tendrils of RNA sprout, growing bit by genetic bit. Eventually, the signal to stop and break away arrives, yielding a new strand of RNA that faithfully transcribes the DNA strand’s genetic code. Proteins trim and splice this new growth, pruning it so it takes its final form, messenger RNA. More proteins then ferry this mRNA strand through a pore in the nuclear envelope into the open space of the cellโ€™s cytoplasm. Ribosomes and codon-carrying tRNA alight onto the released mRNA strand, reading the instructions it has carried from the DNA in the nuclear nursery. From this trio new forms emerge, bulbous proteins shaped by their destined purpose.

And so it goes, every second of every day, in the tens of trillions of cells in your bodyโ€ฆ

โ€ฆAnd on the tens of thousands of kit packages we deliver to customers across the globe every year.

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Decades of Discovery: How the NCI-60 Revolutionized Cancer Drug Screening

The National Cancer Institute’s NCI-60 drug screening panel, comprised of 60 diverse human cancer cell lines, has been a cornerstone in advancing cancer research and drug discovery since its inception in the late 1980s. Developed in response to the need for more predictive and comprehensive preclinical models, the NCI-60 facilitates the screening of thousands of compounds annually, aiming to identify potential anti-cancer drugs across a broad spectrum of human cancers. This article traces the origins, development, and evolution of the NCI-60 panel, highlighting its significant role in advancing our understanding of cancer and therapeutic agents.  

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Knitting Needles, Balls of Yarn and the First Molecular Model

ball-and-stick model of a molecule

One day while reading a knitting blog I discovered in 1883 a Scottish chemist created the first โ€œball-and-stickโ€ model of a molecule using knitting needles and balls of yarn. This initial ball-and-stick molecule represents the structure of sodium chloride and is constructed of knitting needles, representing the bonds, and alternating balls of blue and red yarn, representing the atoms of sodium and chloride. It was displayed as part of the International Year of Chemistry 2011 activities.

The chemist who created this model was Alexander Crum Brown, distinguished chemistry and professor at the University of Edinburgh, and one of his particular interests was the arrangements of atoms in molecules and the depiction of these structures. Those of us who spent countless hours poring our organic chemistry books and molecular model sets trying to understand nucleophilic attacks and SN1 and SN2 reactions have Alexander Crum Brown to thank. Those students who now use computer 3D modeling programs to accomplish the same studies (without the delight of chasing down the last nitrogen atom that has rolled off the desk and under the dresser) are also indebted to Dr. Brown.

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