(Octopi is the Latin ending. Octopuses is the English ending. Same applies to cacti, syllabi, nuclei. Take your pick, both are right.)

While invertebrate animals are used to study things like camouflage and microbial interactions, they’re generally hard to come by in life science research. Mice, rats, pigs, and chimpanzees are more commonly used for their similarity (or sometimes dissimilarity) to human anatomy. These are in vivo studies, which directly translates to “in life.” Different animal models provide a range of advantages and disadvantages in their care requirements, cost, and relevance to humans. And in some cases, I’d argue that human subjects research are “models” meant to loosely represent the broader population.

Animal models aren’t the only option in life science research, though! In vitro (literally “in glass”) models are less complex systems that we can still use to study individual cells or small groups of cells and their reactions to different stimuli. More recently, in silico (“in silicon”) models have been used to computationally predict specific outcomes in different organisms, which omits the need for real life models almost entirely. Animal models are often highlighted in media as being subject to violence and cruelty. Some consumers might specifically shop for cruelty-free cosmetics and household goods, but as of 2026, these terms have no legal definition in the United States. On the surface, using animals in research does sound cruel. Here, we’ll discuss more about the protocols already in place for protecting animal in research, and some ethical perspectives on what it means to choose the “right” animal for a specific study.

Let Yourself Engage With a Nuanced Point

It seems easy for this discussion to head towards something like “where do we draw the line?” But that isn’t what should motivate a researcher’s choice of model. There are no models that are “on” or “off” the table when designing a study. Until the budget, length of study, and research question have been established, you could hypothetically use any organism (or less than an organism. A mixture of chemicals with no life could still be an in vitro model depending on who you ask.)

But as more and more about the project becomes more and more defined, the choices quickly narrow. Is this a mechanistic study, or a black-box approach? Is the length scale minutes, hours, days, or years? Is the goal to generate a preliminary finding to support an upcoming grant proposal, or make strong progress towards commercialization and adoption of a new intervention?

Chemical Model

The simplest system to work in for life sciences is a chemical model. Here, you might study an interaction between two molecules, the rate of transfer across a barrier, or another reaction that doesn’t require live organisms to study. This is typically where we have the most “mechanistic” insight, i.e. we can determine exactly what is going on, where, and how (given sufficient experimental design). It’s also the most convenient to perform, and typically the fastest.

Cell Model

A step above a chemical model is a cell model. In this system, cells are grown in single layers in a laboratory setting and treated with something to assess some response. Traditionally, this is known as 2D cell culture, because the cells will assemble as one continuous layer across the bottom of a plastic Petri dish. This is usually a single cell type grown under a very specified set of conditions. Similar to a chemical model, cell models are also highly controllable and inexpensive in the life sciences. These are traditionally known as in vitro models, though some people also refer to chemical models as in vitro.

Organs and Organoids

Though, the highly simplified system of a cell model doesn’t account for the 3D organization of cells in real tissues. If you wanted to understand more about the spatial organization of cells in a 3D tissue, you would transition to spheroid or organoid cultures. These are popular in disciplines focused on specific organs (e.g. brain, lung) that have complex structures. Things can get tricky here because 3D cell cultures are very vulnerable to nutrient depletion, and analysis techniques used in 2D culture often need some modifications for 3D culture systems. For example, in 2D culture, all of the cells have pretty much equal access to sugar, nitrogen, micronutrients, and oxygen. In a 3D spheroid culture, the cells buried in the center of the tissue have a more difficult time accessing nutrients compared to the cells positioned at the surface.

These types of models—chemical, cell, and organ—typically don’t receive much media scrutiny as these tissues aren’t canonically “sentient.” While these systems do respond to actively respond to their surroundings, they don’t possess the same amount of consciousness compared to that of a rat or a mouse that might raise some eyebrows from people interested in protecting animal rights.

Rats, Mice, and Invertebrates

But at some point, just looking at tiny cells isn’t enough information. It becomes necessary to study an organism with a full anatomy. The “simplest” animal models (these organisms are by no means simple, they are moreso thought of this way because they are easy to manipulate) are typically flies, rats, and mice. Sometimes zebrafish are thought of in this category too, but these are usually used for more niche systems like limb regeneration.

These organisms have the benefit of 1) historical precedence 2) relative cost to rear and 3) size. Flies, mice, and rats have been used for so long that there are highly detailed, highly repeatable instructions on how to raise and study them. For the case of mice, there are strains of mice that have been inbred (purposely) for many decades to produce a population of nearly genetically identical organisms. This is an important advantage over a collection of genetically-diverse mice to use for a study because genetics can change the outcomes of a study a LOT even if you don’t mean for it to!

Even if these are relatively cheap animals to raise, that doesn’t make them cheap. Whereas you might keep a 2D cell culture alive for days to weeks, mice can take 6-8 weeks to progress to adulthood and live for 2-3 years. There’s often a flat rate to purchase the mouse, daily food and water, and a per diem for mice to be housed. Usually mice and rat studies are cited in the news for testing of pharmaceuticals, specific food ingredients, or psychological phenomena.

To even consider doing research using animal models, the National Institute of Health requires adherence to strict policies designed to protect the rights of animals as much as possible. Researchers are required to submit a full report on what animals, how many animals, what they will be subject to, and what knowledge will be gained before the project can begin. These reports are reviewed very closely by the Institutional Animal Care and Use Committee (IACUC), which every American institution is required to have if they engage in federally-funded animal vertebrate model research (recall, the Nature editorial calling for more stringent protection of invertebrates). Once the study is over and published, the authors are also required to disclose exactly what protocols they followed when raising and studying the animals (these generally vary by country, which is why it’s necessary to disclose which protocol was used).

Pigs

But mice and rats are not close approximations of people. What we observe in a mouse might not translate to humans for a number of reasons, which creates a difficult choice for many life science researchers. When mice, rats, and other little critters aren’t representative enough of people, it often makes sense to study pigs and other mammals (An alternative reason is if your research question is specific to pigs or some other large animal.). Pigs are generally smarter, and they are more similar to humans in terms of their genetics, anatomy, and metabolism. For example, this study examined how well a lab-simulated model of the intestine matched the mechanics of a pig intestine, as a proxy for human anatomy (In this case, we have a chemical model approximating an animal model, and the animal model was previously used to approximate what happens in a human. It’s models all the way down).

Apes & Monkeys

And in some cases, even the pig as an animal to represent a human isn’t close enough. Chimpanzees are the most common animal model used in vaccine and infectious disease research to most closely replicate a human’s response to a virus. Proposing to do research on animals that are regarded as generally highly intelligent (pigs, chimpanzees) generally means the study will be under even more scrutiny. These trials are expensive, risky (to both animal and human scientist), and are simply not necessary for the majority of life science research. Even chimpanzee studies are quite rare now.

People!

And at the top of the animal model chain, we arrive at human clinical trials. These are the ultimate “approximation” of YOU that you will ever find in a study. And even clinical trials are not always applicable to the entire human population. Treatment effects can differ between sexes, diets, exercise levels, professions, ages, and every other demographic I don’t have time to name. Analogous to IACUC, any academic study involving humans will require approval from the Institutional Review Board (IRB) at a university. IRB approval is not reserved for just medical-type studies either; sometimes you need to study humans because only a human could articulate to you what the texture of a food is, or whether a pointy polygon is Kiki and a rounded one is Bouba.

I was once taught about how the American government places guards between animal models and the American people to ensure we don’t end up ingesting even close to the lethal dose of aspartame from Diet Coke (or another compound). I was taught this using two important sentiments:

1. Mice aren’t people (in the case of a mouse study).

2. People aren’t people (you and I are different, and we are also different from David Bowie).

For example, the U.S. Acceptable Daily Intake (ADI) of a compound is calculated first by assessing the dose at which no harmful effects are observed in a mouse (called the NOAEL), and dividing by 10 (mice aren’t people), and dividing by 10 again (people aren’t people). This essentially means that for a reasonable person (a bold assumption), you will be limited to ingesting 100 times less what a mouse would ingest, and that mouse would STILL not observe a harmful effect in a study.

In vino veritas

So, deciding which animal model to use is not always a question of what animals are “allowable” for experimentation, but rather which animal model will maximize the knowledge gained and minimize the cost (time, money, and wellbeing). In this decision, we also collectively acknowledge that certain organisms are more difficult to control, rear, and study, which often shortcuts to “certain organisms hold more value than others.” But engaging in ethical animal model research is not mutually exclusive from having respect from living things. And in each different model, starting from chemical all the to chimpanzee, there is some truth to be learned about some in vitro or in vivo system, just as in vino veritas, or “in wine, there is truth.”

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Dr. Chris Buck detailed the experience in a series of posts on his own Substack, “Viruses Must Die,” and he’s also been featured in a very well-written article in Science News.

To give a short recap about his beer vaccine: Dr. Buck first observed in a mouse experiment that yeast carrying dead viruses could impart a vaccine-like effect when they ate the yeast rather than inhaled it or absorbed it from the skin. This finding implies that administering this GMO yeast as food might be an effective strategy to protect against polyomavirus, an infection deadly for immunocompromised people.

We typically consume yeast as bread and beer, but there’s also yeast in fermented foods (kombucha, soy sauce), and nutritional yeast. But what would be a suitable food to deliver this virus to the public?

Dr. Buck chose beer. And I think that’s the issue we’ll focus on today, though there are many issues I invite you to consider from his feature in Science, his own Substack, and other outlets covering this story.

[Does vaccine beer strengthen or weaken people’s confidence in public health systems? What about vaccine beer brewed outside of research ethics-approved studies and consumed in private? Is it appropriate for one highly educated virologist to drink his own home-brewed experimental beer and claim it’s in the name of safety? Food and medicine are regulated differently; whose jurisdiction does this fall under, and is it necessary to conduct a clinical trial even though this is a “food?”]

While it’s tempting for us to focus on the fact that Dr. Buck circumvented the research ethics approval system and brewed his vaccine beer in his own kitchen (drinking it in front of a reporter for his Science feature), there is another problem in his selection for how to deliver this vaccine.

Beer is Morally Loaded

Beer is a culturally significant part of human history. The oldest beers date back to 13,000 years ago as a ritualistic food for a nomadic tribe in the Middle East. For a time, beer was actually safer to drink than water because beer wort is boiled, killing off any harmful microbes. Today, beer holds up the economy, engaging stakeholders from agriculture, manufacturing, brewing, hospitality, and more. It’s is a critical part of the arts and culture, especially in settings like sports and music festivals.

But beer can also hurt you acutely, chronically, and psychologically. Alcohol poisoning kills. We’re only just finding out the long-term health effects of drinking alcohol at even one standard drink per day. Alcohol is now classified as a Group 1 carcinogen, the same as tobacco. The WHO has clear messaging based on recent studies that there is no safe dose of alcohol. Moreover, alcoholic beverages are expensive, so vaccine via beer may create financial stress or even widen the wealth gap.

Let’s not forget that alcohol is an age-restricted beverage, with purchasing being regulated variably state-to-state. Polyomavirus can be an especially serious infection in children. How could you tell a child—quite literally screaming in pain, as Dr. Buck recounts in a visit to a pediatric hospital— that he wasn’t old enough to drink vaccine beer because it had alcohol?

So, beer may seem like a playful, economically-relevant choice to deliver this vaccine.

What food would I have picked? Excellent question, but not the right one.

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Sigh

At the end of my work week, the last CNN headline I want to see is anything related to “sequenced Hitler’s DNA.” Recently, some famous geneticists and historians collaborated to sequence Hitler’s genome from a bloodstained piece of fabric recovered in 1945.

It used to be very, very expensive and time consuming to sequence human DNA. It took roughly 13 years and an estimated $3 billion to sequence the first human genome in the early 2000s as part of the Human Genome Project. We have better sequencing tools available now, and some cost estimates sit at just a few hundred dollars for one human genome.

But here’s what you need to know so we can talk some (educated, evidence-based) trash.

Sequencing is Not Objective

Sequencing DNA does not reveal objective truths. The researcher in charge of sequencing data makes many assumptions and subjective decisions about how to interpret, clean, and manage the data. The news tends to view sequencing as a foolproof, impartial method, but if you learn anything from this blog, let it be that sequencing is not objective. There are ways to make it more rigorous, but just like all science, we are not dealing in truths.

In fact, to combat bias, scientists are expected to make their data analysis methods and raw data publicly available, and their data can be subject to audits by the funding agency at any time. There are extensive databases where sequences are uploaded and can be annotated by scientists at other institutions to ensure the conclusions we make from DNA sequences are verifiable across universities and research centers.

There’s No Preprint

In the publishing world, it’s becoming more and more common to make your papers available as “preprints.” Preprint articles, managed by journals like bioRxiv (pronounced “bio-archive”), are publication drafts that are released before a paper has completed the peer-review process.

Why does it matter if someone publishes a preprint? Preprinting allows more people to critically review the work, even if they are not the official reviewers that will approve or reject the paper for publication. There’s always the caveat that the preprint article may not be the same as the final version of the publication, but the main body of the work will be mostly unchanged. There are a handful of reasons you may elect not to publish an article as a preprint:

1. You cannot afford to wait longer for the peer-review process to finish

2. It is too difficult to adapt your publication draft to a journal’s preprint policies.

3. You are afraid someone will copy your study and publish it before your paper has made it through the peer review process.

Now, if I was the one sequencing Hitler’s DNA and claiming he was higher genetic risk for stigmatized mental health disorders and delayed puberty, these issues would not apply to me. The authors of this study are very high profile geneticists and have historically been involved in genetic identification of major historical figures. They can afford to submit to preprint and delay the process by a few months. They are experienced with the publishing world, they have surely submitted other articles for preprint.

And lastly, they are the only ones in the world with access to Hitler’s DNA. Nobody can copy their study and publish it before they do.

The Study is Untargeted

The main research questions motivating this study are unclear to me, and in my opinion, it’s unlikely they had a targeted hypothesis. Their test subject is one of the most famous, well-documented, and hated figures in human history. If it were me, it would be easy to take a more untargeted approach to get some media attention on an already controversial topic. In other words, this is a “see where the data takes you” study, rather than a “we designed the study to test one specific prediction.”

Not all untargeted research studies are poor ones. Some of the most important scientific discoveries have been “accidents.” CRISPR gene editing technology interestingly had roots in the dairy industry. Post-it notes were a complete accident. Potato chips. The list goes on.

So why don’t I like this study?

There is No Good Research Outcome

Hitler’s life is one of the most well-documented in history. He was constantly, constantly surrounded by people who wrote down his mannerisms, decisions, emotions, favorite meals, whether he tied his left or right shoe first. It wasn’t like he was trying to keep anything secret (see Mein Kampf). What new information about his life is his DNA going to contribute?

An obvious counterargument is understanding his genomics may clarify why he was the way he was: irritable, arrogant, full of hatred, and yet a compelling, decisive leader. So, maybe his genes could reveal distinct differences from the average, non-hateful person to explain these traits.

This is an exciting idea for a certain subset of the population, except we must remember that Hitler was a person just like the rest of us. The study found genetic indicators for autism, ADHD, and schizophrenia. There have been millions of people over human history with these disorders that have not had violent tendencies. A well-trained scientist would refrain from saying this finding may indicate his personality and violent tendencies could be driven by these genetic differences. But the media will not refrain from making this conclusion.

The study further proposes Hitler may have had a condition known as Kallmann syndrome, which can prevent or significantly influence puberty. I wish I was kidding, but the main author of the study was careless enough to admit to the reporter that some patients with Kallmann syndrome have a micropenis. Though, Hitler was known to have some genital irregularities that may overlap with symptoms of Kallmann syndrome.

My main point here is the authors have not exercised any restraint in discussing the implications of their study. If you tell a reporter that you think Hitler could be genetically at risk for Kallmann syndrome, they will take away that Hitler had Kallmann syndrome. And if you tell them that it’s possible to have a micropenis and have Kallmann syndrome, they will take away that Hitler had a micropenis.

If the authors didn’t discover anything significant in Hitler’s DNA, the best case scenario would be once again confirming that Hitler was a terrible person.

I don’t have a familial connection to this wretched part of human history, but if I did, I would be enraged at the idea that someone even think of proposing a genetic excuse for Hitler’s behavior. It is not worth our time to rationalize on a biological level why he acted the way he did. There is no good outcome to this research, even if the main authors may think the findings are significant.

There’s not much else to discuss about this study until the findings are officially published. And if there’s something new to say about it, we’ll revisit the findings.

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I didn’t think anything of it this morning—I thought that, at best, Colossal Biosciences had recovered the dire wolf genome from a fossil.

In the few hours since I saw that post, my entire feed has blown up with headlines. Dire wolf resurrected. 10,000 year-extinct species revived. Colossal Biosciences brings back the dire wolf. Game of Thrones is real.

Let’s discuss, Trash Talkers. Maybe we’ll even talk some trash.

Who is Colossal Biosciences?

Colossal Biosciences is a biotechnology company based in Dallas, Texas. Their primary focus is to facilitate “de-extinction,” or what the rest of us might peg as wildlife conservation. They want to prevent major biodiversity loss on our planet, especially as our climate changes and threatens vulnerable species. That’s a noble cause; Earth’s biodiversity has both intrinsic (perhaps an animal’s right to life) and extrinsic value (how we interact with animals and what services they provide our ecosystem, like beavers building dams or chickens laying eggs).

Where they lose me is the ultra-techno-futurized language and aesthetic. Let’s take a look at their website.

The landing page is an incredible feat of graphic design. Short clips of snow-white dire wolves trotting in the forest, scientists handling samples in the lab, scenic forest foliage (from the POV of prey, might I add), and other “aesthetic” shots alternate in a looped video. Right in the middle, some text:

“The science of genetics. The business of discovery.”

Wow. We don’t have time to unpack all of that.

If we scroll down, we see various collages of different animals overlayed with text akin to futuristic computer output or code. Lots of messages about the pressing need to protect extinct and critically endangered species.

Scroll farther down, more interesting images. I actually really like this one—zebras, deer, giraffes, bears, and fish amble (or swim) along a picturesque fossil or maybe a winding path of rocks.

Ah, the wonderful “Wikipedia defines this term as” tactic. Webster’s dictionary defines wedding as the fusion of two hot metals, for any Office fans. Here’s where we get to Colossal’s major claim: that they can make something de-extinct. De-extinction of course, is the process of creating something that looks like or actually is an extinct animal.

“Revival” of the Dire Wolf

Through genetic engineering, Colossal Biosciences claims to have revived the long-extinct dire wolf. According to their website, Colossal states that there were only two samples of usable dire wolf DNA in the entire world: a tooth, and a 72,000-year-old skull. They isolated DNA from these samples and sequenced the entire genome—essentially all of the written instructions that make the dire wolf what it is. Sequencing is a very common genetic tool; we sequence bacteria, yeast, mice, and other organisms in research all the time. It’s harder to sequence genomes for macroscopic life because they have more genes. For example, the Human Genome Project was a long-time effort to sequence the entire human genome, spanning over 13 years of work.

Your genes make you. The dire wolf genome makes the dire wolf.

(In this video, they say that it’s “incredible” to generate an entire genome for a species. I would argue it is not incredible. Maybe it is more resource-intensive and takes more time for a mammal like a wolf, but it’s not far-fetched from my limited knowledge of genetics.)

So, now they’ve got the genome of the extinct dire wolf. How do you make a physical dire wolf?

Colossal’s strategy is to “map” the dire wolf genome against a close living relative, the gray wolf. If you can take a set of genes that are already pretty close to your genes of interest, you can make small edits until you have a genome resembling the sequenced genome. You take the gray wolf and make genetic changes (Colossal claims they make hundreds of edits at a time) until you have what you believe to be a dire wolf.

They don’t do this part with actual wolves, by the way (and you reasonably couldn’t do that). They make genetic changes to gray wolf cells in little plastic Petri dishes.

Then comes the “making a dire wolf” part. If you remember Dolly the sheep—the first cloned animal—this process is technologically the same. Scientists at Colossal stick a dire wolf cell inside an egg cell from a gray wolf or even a domesticated dog, which makes a dire wolf embryo. Then, the embryo is inserted into a surrogate dog, and a few short months later, dire wolf puppies.

I’ll admit—they are quite cute: Romulus and Remus are six months old, and Khaleesi is three months old:

You can even track their development on Colossal’s website.

Pretty stunning animal.

What are the Implications?

I’ll admit I’m known to have intense knee-jerk reactions to news like this. I’m generally skeptical of efforts that attempt to play God beyond a reasonable amount. Genetic modification of corn, soy, and canola are already widespread—I have no problem with those. But reintroducing a long-extinct species for (what I believe to be) an indefensible reason doesn’t cut it for me.

Colossal claims they do all of this to correct humanity’s past, current, and potentially future mistakes. If we were responsible for the extinction of a species or harmed their wellbeing, Colossal believes we have a duty to fix it. That’s a pretty easy position to stand in. We messed something up, we should fix it.

But what does “fix it” mean? Why do we have the right to reintroduce species or pretend we even know how to? Even Colossal admits that their technologies rely on our still-changing understanding of fundamental biology; for example, can we identify specific genes that make something a dire wolf versus a gray wolf? They already share a lot of similarities—how do we know which ones are responsible for their differences? And, are we certain that those genes don’t affect other traits, too?

On a macroscopic scale, what if we introduced a previously-extinct animal into an area it wasn’t fit for? Or worse, what if it was overly fit and wiped other keystone species out of the area? For species that have been extinct for a long, long time like the Dodo bird, woolly mammoth, or the dire wolf (coincidentally, all species that Colossal is focused on reviving), it’s difficult for us to predict what ecological niche they fill. What habitat, what food web, what ecosystem do they fit into if the rest of biological life has evolved without them? Save for the last blip of evolutionary time where humans have made quite a dent in the Earth, organisms become extinct because they cannot survive. Unless something about the organism or its place in the ecosystem has substantially changed, it will not survive. Things do not re-evolve back after extinction.

Hearts & Elbows

There’s a famous question in biology:

Why doesn’t your heart grow on your elbow?

It might seem absurd—of course your heart is meant to be inside your body, protected from the elements, central to your veins and arteries to maximize nutrient delivery. And we know that that makes sense. Your organs need to be in the specific places they are, or things get wonky. But how does your body know where to put the heart, hair, teeth, and fingernails?

I find this video by Hank Green best explains the sheer wonder of the human body and our somewhat limited understanding of how it came to be:

@hankgreen1#stitch with @Anna Redman Bodies are amazing.

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“Where everything knows where to stop and what to be” is the best way I have thought to put it. We are made up of billions and billions of tiny evolutionary decisions (a more accurate but less wondrous term would be “evolutionary probabilities”) over an extraordinary length of time.

I’ll invite you to apply Hank Green’s whimsical sentiment to Colossal Biosciences and their dire wolves. How will we know where to stop and what to be?

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A slight deviation from my alt protein timeline series, this week we’re taking a look at the authorship dilemma, which is the challenge of determining who should be listed as an author on a peer-reviewed publication and in what order. Disclaimer: this post raises more questions than answers.

Publishing

At the very top of a peer-reviewed journal article, you’ll find the article title, journal, date of publication, and the contributing authors. Years ago, it was typical that most research articles, textbooks, and other academic works had only one or two authors. If the article was part of a graduate student’s thesis, the student is typically listed first and then the advisor or mentor. All in all, the first author is credited with the bulk of the work. My peers often distinguish their publications by first- or co-author status, signifying they have more ownership and involvement in those projects

But what happens when you have five, ten, or a dozen contributing authors? Who is permitted to be credited with the work? Who deserves the title of “first author?”

…Nobody Knows

There are no standardized guidelines for first authorship or authorship order. This is a growing problem in the publishing world, especially as scientists are encouraged to collaborate on larger and larger projects. One idea is to simply list authors alphabetically, removing the ownership component entirely; each author is perceived as having equal importance. However, not every author contributes “equally” to a project. It’s a little too idealistic to expect equal contribution.

Another common strategy is to list authors in order of contribution level, from greatest to least, except the advisor or mentor is listed last (confusingly, I’ll admit). So, a paper with four authors might follow the formula:

Most contributing author, next most contributing author, least contributing author, The Boss™.

It’s not that authorship is a question of seniority, though often the authors that “came up with the idea” are more senior and removed from the mundane tasks (like data collection), which are often assigned to graduate students and undergraduate researchers. Graduate students arguably bear the most responsibility of these parties. (Aside—this is a contentious area in research. Graduate students perform most of the science, but professors and advisors are often credited the most with the work, which creates a lot of tension. Students are seen as students, but really they’re employees, which academic institutions use as an excuse to keep stipends and benefits low but research outputs high.)

The more authors you add, the more confusing authorship and credit become. A more recent requirement in some journals is to disclose what each author specifically contributed since, interestingly, being listed as an author doesn’t necessarily mean you wrote the paper. Typical contributions are: study conception, study design, data collection, figure design, data analysis, manuscript writing, and manuscript editing or reviewing.

But even this disclosure raises a new issue: what is the perceived value of each task, and should that value dictate authorship credit? Should the person who collected the data be listed first, since our interpretations are ultimately based on their work? Should the person who analyzed the bulk of the data be listed first because this work constitutes the highest intellectual skill? Should the main writer of the manuscript be listed first simply because we’re reading their work at this very moment?

I can definitively say as a graduate student, papers resulting from my thesis will be published with me listed as the first author. That’s an easy distinction because my degree is contingent upon developing skills in study conceptualization, experiment design, data collection, data analysis, and scientific writing. It makes sense that graduate students are first authors on their own projects.

Who is the second, third, or fourth author, if that many people contribute to my paper? Of course, I’ll include my advisor as the conventional last author. But what about undergraduate students who help with data collection or other graduate students with relevant expertise that I consulted significantly throughout the project? If I was co-advised, in what order would I list my advisors?

To complicate it even further, many papers have an Acknowledgements section at the end, commonly used to list funding agencies or institutions that donated samples or equipment.

Let’s say I needed to be trained on microscopy to pursue my project, and I consulted my institution’s (imaginary) Center for Microscopy. If a staffer at this center trained me on a microscope, and then I published data using that training and that microscope, what credit does the staffer deserve? I would argue the Acknowledgements section is the appropriate distinction for these peripheral parties that help in the scientific process, but at what point is someone “promoted” from Acknowledgements to author? Even a step below Acknowledgements is to be cited in the References. All of these sections of a paper—authors, Acknowledgements, and References—are sections that award respect, but in differing capacities.

Some institutions have written explicit guidelines for determining authorship, like the International Committee of Medical Journal Editors, which defines authorship criteria as:

1. Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; AND

2. Drafting the work or reviewing it critically for important intellectual content; AND

3. Final approval of the version to be published; AND

4. Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Notice the comparative and non-specific language in these guidelines, like “substantial” and “reviewing.” Are authors required to be part of the writing of the whole manuscript, or just the bits and pieces they worked on? These criteria don’t provide clear answers. Even “interpretation of data” is listed as a good-enough reason to be listed as an author. What if I brought my data to one of my committee members in an effort to parse out my findings? Does that make them an author?

I called my partner while drafting this post for advice—should I list him as an author?

Gifts & Ghosts

On the flip side, sometimes people are included as authors without actually contributing anything to the project, an unethical practice known as gift authorship. Gift authorship is often granted as a result of social pressures or extreme (nearing unnecessary) respect for a researcher.

Interestingly, the opposite concept is also an issue in authorship and publishing: ghostwriting. Ghostwriting is when the person who wrote the work is not listed as an author. In book publishing, dedicated ghostwriters, especially in fiction, are still paid for their work, but their name isn’t listed on the final product. They still receive compensation.

Ghostwriting in academia, on the other hand, is a little fishier. As academics, we collectively agree to preserve academic integrity, which includes the agreement to not steal or plagiarize intellectual works. Explicitly listed authors on ghostwritten papers may not be fulfilling their obligation to foster a community with strong academic integrity. And, in many cases, the ghostwriter on a peer-reviewed publication may be from an institution in the private sector with obvious competing financial interests, which compromises the integrity of the published work. Both parties lose.

A World Record

The current record-holder for most contributing authors on a peer-reviewed journal article is a publication in Physical Review Letters, with over 5,000 authors. Five. Thousand. Somehow the actual paper is only 9 pages, with the following 24 pages used just to list the authors.

(If you’re an academic, I know what you’re thinking—is PRL a respected journal? PRL is regarded as the most prestigious journal in the field of physics.)

What does it even mean to be part of a 5,000-author collaboration? Or, perhaps more importantly, what does it mean to first-author a 5,000-author paper (I use first-author as a verb because this issue is so pervasive.)? That might be the ultimate scientific feat—our physicist friend G. Aad takes home the biggest authorship prize ever awarded. Even the eight authors listed after G. Aad take home a big win here—how did they decide that these eight would be listed at the beginning of the article?

My Internal Conflict

In my undergraduate, I had an independent research project in chemical engineering that I would say was comparable in complexity and intensity to at least an M.S.-level project (and maybe even PhD). When I say independent, I mean I wasn’t paired with a graduate student. In many research labs, undergraduate students work directly with graduate students on the same project, but that wasn’t true for me. At the beginning it was by chance; my advisors hadn’t recruited for my project yet, and then things ended up changing. But I took the opportunity and ran with it.

Because I was the only student on the project, I was in charge of its direction, which I thoroughly enjoyed. I had the freedom to ask the research questions that I cared about answering. I had the autonomy to identify the right methods and data visualization techniques to tell this scientific story. I loved having this level of control over my project.

On the other hand, my project being mine meant that I was also solely responsible for writing a manuscript that would result from my experiments. It was my job to report what I had done, and my advisors would be there to read and review my manuscript when I had written it.

I never wrote the paper. In my head, I had a million reasons for not writing it—I was taking seven classes and had no time, I needed to repeat an experiment, I didn’t have enough data, I didn’t know how to interpret my data, whatever. The reality is, people have published papers on less information than I had from my project. I could have managed it.

I have peers that have published in their time as undergraduate researchers. Publishing is a major milestone on a project, and people should celebrate when their papers are accepted. But to be frank, some people are just in the right place at the right time, and they are lucky enough to get listed as an author (though maybe not a first author).

I felt cheated. I felt cheated that my project was regarded as being high-quality, highly innovative, yet I didn’t get the same recognition. I’ve presented this work a half dozen times, and every time people ask where they can find my papers. Professors have even nominated me for internationally-competitive scholarships for early-career, high achieving scientists thinking I’m published. People are genuinely surprised that I don’t have papers.

And this is what I didn’t know about science when I started: you have to stop at some point to report what you did, or no one will know. You have to tell someone that you learned something new so they can learn it, too! You have a duty as a scientist to report what you’ve found.

That’s where I failed—I didn’t even know I had this obligation. I just thought that, at some point, the work will get published when I’m finished with it—but you’re never finished with it. When grad students graduate, 90% of the time their project is handed off to the next student, who asks some new questions and generates some new data, only for the cycle to repeat. (Even my undergraduate project has morphed into a graduate-level project now for a new student. Maybe I should just take that as a win.) There is no concrete end to the project, but you have to work in the time to publish or you’ll end up like me, with all of the effort expended and none of the credit.

So, a toast to gifts & ghosts, the over-recognized and under-recognized. Being a published author is great, but it isn’t everything, and sometimes it isn’t even anything (if you’re a gift author).

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