Why did the chicken cross the road?

Call for research applications

Recently the European Research Council opened a series of calls for groups aiming to solve a number of classic, fundamental questions that have perplexed scientists throughout the ages. Interdisciplinary approaches were welcome; no restrictions were placed on the composition of research teams or the methods to be employed.

Below are some representative applications submitted under Topic 12: “Why did the chicken cross the road?”


Cancer research

Cancer remains an enormous threat to human health, with 9.6 million deaths reported world-wide in 2018. Mortality is most often caused by aggressive metastases, which occur when cells migrate from a tumor, traverse the circulatory system and invade other tissues. While the immune system recognizes and eliminates most cells with metastatic potential, some manage to colonize target tissues and eventually disrupt their functions. In an analogous process, chickens may also migrate from their points of origin and traverse the circulatory system. A few escape elimination by automobiles and make it to the other side of the road, where they frequently engage in disruptive behavior. In some of these fowl, tumors have been detected, at levels that should not necessarily be considered non-trivial. This project will exploit the close homology between the causative mechanisms and behavior of chickens and metastatic cancer cells, in hopes of understanding their ability to escape immuno- and vehicular surveillance with the aim of identifying new targets and novel approaches for therapies.



The canonical Wnt signaling pathway influences a number of processes crucial to the development of embryonic organs by targeting complexes which would otherwise degrade cytoplasmic beta-catenin, thus preventing it from localizing to the nucleus and activating target genes. Recently a knock-down of Wnt in chickens was shown to result in embryonic lethality, and as a consequence a total inhibition of road-crossing activity by adult hens and roosters. Our lab has shown that neither canonical nor non-canonical Wnt signaling offers a complete explanation for this association. This suggests that cells possess a hitherto undetected pathway by which Wnt exerts an influence on gene expression programs. Elucidation of this signaling cascade may resolve questions related to the development of embryonic tissues and the disruptions of developmental programs that lead to the rise of cancer stem cells, ornery chickens and other phenotypes.



2004 saw the completion of the first draft of the genome of Gallus gallus – otherwise known as the chicken – providing researchers with the complete DNA sequence of their first bird. They immediately began trying to separate the meat from the bones of an organism that has long been a main course on the menu of models for biomedical research. The chicken has more chromosomes than humans, partially accounting for extra features such as feathers, beaks, and packing its embryos in eggshells. But presently only 18,346 coding genes have been identified, perhaps accounting for noticeable deficits in their cognitive abilities. Our group recently carried out a comprehensive review of genome-wide association studies (GWAS) related to chickens that have appeared in peer-reviewed publications. We identified 712 gene variants significantly associated with mortality in road-crossing chickens compared to a control group of survivors. Interestingly, we also found a correlation between 5-week survival and susceptibility to various pathogens such as avian flu, perhaps because the longer a bird lives, the more likely it is to acquire an infection. These findings have implications in breeding programs, which may have to choose between extending the lifespans of birds and creating pandemics that cost millions of human lives.


Evolutionary biology

Road-crossing behavior has been observed in birds since the appearance of roads, somewhere around the beginning of recorded history. This activity is fraught with danger, as it makes the bird susceptible to death by horses, camels, elephants, automobiles, Roombas, and various other participants in stampedes. Yet the persistence of road crossing implies that it has some value for survival or reproduction. One possibility is that it promotes diversity within populations that would otherwise experience excessive inbreeding – hens living across the road are less likely to belong to a rooster’s brood. Natural selection through roads has caused distinct species of birds to adapt in different ways. Some developed flight; others hop along electrical lines. Chickens continue to cross roads the old-fashioned way; perhaps they have adapted by simply laying more eggs, ensuring that populations will survive despite significant decimations as road kill. In a few species, such as geese, traffic regulations seem to have become integrated into genetically programmed behavior that prompts them to take advantage of crosswalks and traffic lights. A similar phenomenon is observed in frogs and deer, which tend to cross roads at places where warning signs have been mounted, but these examples are most likely cases of convergent evolution rather than reflecting the principle of common descent.


Structural biology

The giant muscle protein titin is an essential component of sarcomeres, piston-like structures that expand and contract to give muscle fibers their elasticity. Without titin, organisms would basically be lumps of protoplasm, unable to cross roads or anything else without the application of some external force. Our lab uses the chicken as a model system to study the 244 domains which make up the titin protein, which partially unfold through the mechanical forces placed on sarcomeres. We are investigating the possibility that mutations cause truncated forms of the molecule that shorten the stride of chickens and thus result in higher mortality when they cross roads.


more to come soon…

THE EVOLUTION OF PIZZA: Novel insights into the fourth domain of life

Russ Hodge1*, Pablo Mier Munoz2, and Miguel Andrade2


  1. Max Delbrück Center for Molecular Medicine of the Helmholtz Association, 13125 Berlin, Germany
  2. Faculty of Biology and Center for Computational Sciences in Mainz (CSM), Johannes Gutenberg University Mainz, 55128 Mainz, Germany

* Corresponding author: Russ Hodge, hodge@mdc-berlin.de

Conflict of interests: This project has received no funding from the pizza industry or its competitors, and there are no other conflicts of interest.


Pizza has long held a stigma in biological research that dates back to Linneaus, who was intimately familiar with its properties as an aphrodisiac but failed to recognize it as a living organism. As a result, species of pizza found no place within his elaborate system of classification, and have consequently been entirely omitted in the clade systems developed by evolutionary biologists. Add to this the nigh impossibility of maintaining pizza in laboratories, from which it tends to spontaneously disappear through mechanisms that are poorly understood, and the result is that pizza has been forgotten in the deep freeze as the life sciences have moved forward in great strides.

The physiology of pizza makes it difficult to classify; on the one hand its structure bears striking similarities to a single cell, vastly scaled up, if you think of the crust as a membrane, and from that perspective the ingredients resemble organelles. Yet it also has properties we normally associate with highly developed multicellular organisms. One could also consider it a sort of complex ecosphere containing many subspecies. Data from an evolutionary study should show us which of these models is most appropriate, but the data will have to be new. The fact that pizzas never evolved a skeletal or exoskeletal system has led to a paucity of fossil remains which otherwise would surely have generated interest among the paleobiology community and provided insights into the descent of modern species.

The synthesis of Darwin’s theory of evolution with findings from genetics has led to modern, computational approaches that compare the features of modern organisms to reconstruct those of their common ancestors. Here we apply this basic principle of “common descent” to construct the first evolutionary tree of pizza.  We should note a potential confounding factor: Modern varieties have clearly been shaped by human domestication and selection, and a small number of mutant strains have spontaneously appeared in recent years, probably due to exposure to microwave radiation. While these factors confound the picture to some degree, the method does, in fact, permit a means of resolving questions about pizza biology that have long resisted analysis.

The resulting diagram introduces considerable clarity into the path by which current species of pizza arose from a single common ancestor, through stages that became the founders of major branches, and finally to modern forms. It permits us to hypothesize the existence of ancestral forms that have homologs in the varieties that exist today. Finally, it provides insights into fundamental biological processes that are unique to pizza, supporting a claim that these species represent a fourth domain of life which is distinct from archaea, bacteria, and eukarya, but which has clearly interacted with them in ways that have shaped its evolution.

We find evidence that pizza has managed to co-opt fundamental biological processes from the other domains of life and mix them in a way that hints at hitherto unexplored evolutionary mechanisms. Pizza appears to have snatched genes from various sources on its way to becoming an independent organism, then undergone a phase in which it became wholly dependent on human domestication, leading to a simplification of its biology. Our study suggests that the appearance of pizza in complex ecospheres containing other life forms influences them on several levels – from the neurological to the behavioral to the social, altering patterns of predation and other types of interspecies interactions.


We visited approximately 100 different Italian restaurants in a sample of no less than five European countries over a period of 4 years (extrapolated from social media statistics of the authors: FourSquareTM, GoogleTM Location History, etc.) to gather the names and ingredients present in a total of 58 different pizzas (Supp.File1). While we did not taste them all, we can attest that none are venomous and their organoleptic qualities can therefore be successfully transmitted mouth-to-mouth to the next generation of diners.

The ingredients were clustered in 9 groups according to their origin and use in cuisine (Table 1). Tomato sauce and mozzarella form their own groups, as they are not considered ingredients but inherent components of the pizza (Combet et al., 2014). The pineapple was set apart in a group by itself as an obvious aberration, due to the fact that it is universally recognized as a dysfunctional mutation that arises from a hybridization event (somewhat like the mule) and cannot produce viable offspring.

Table 1. Ingredients considered per group.

Class Ingredients
Tomato sauce Tomato sauce
Mozzarella Mozzarella
Extra sauce Cream, truffle cream
Extra cheese Gorgonzola, parmesan, ricotta cheese, fontina cheese, scamorza, stracchino, asiago
Meat / eggs Beef, salami, raw ham, ham, bacon, sausage, bresaola, egg
Fish / seafood Tuna, anchovies, seafood
Pineapple Pineapple
Condiments / herbs Pepper/green peppers, oregano, rosemary, parsley, genoese pesto, garlic, olive oil
Vegetables Artichoke, zucchini, asparagus, spinach, peas, eggplant, assorted vegetables, sliced tomato, courgette flower, onions, olives, mushrooms, rucola/rocket, potato, french fries, corn, polenta, radicchio

It is notable that not a single pizza contains more than three ingredients from the same group, which hints that this might lead to some sort of synthetic lethality, or a genetic event along the lines of the acquisition of excess chromosomes.

The pizzas were scored by counting the number of ingredients they contained per group. Exceptions are the tomato sauce and the mozzarella, which were counted as three ingredients each due to their importance in the general composition of the pizza. The data was analyzed using the R programming language and Rstudio, to cluster the pizzas based on their ingredients. The result was plotted in a clustered heatmap using the pheatmap R package (Kolde, 2015).

Tomato sauce and mozzarella are the key components in the pizza and serve as classifiers (Figure 1). Ingredients from the meat/eggs and/or vegetables groups are often used as the toppings to go together with the main components of the pizzas.

Figure 1. Clustering of the 58 types of pizzas analyzed based on their ingredient composition.


Here we present the first rigorous investigation of the origins and evolution of pizza, a form of life that has been shamefully neglected by science even as it has been shamelessly devoured by scientists. While the reasons are unclear, one cannot rule out some sort of large-scale conspiracy on the part of commercial entities. It would not be in their interest to recognize pizza as a life form; such recognition would likely trigger a cascade of intrusive regulatory measures that would curtail society’s wholly utilitarian approach to pizza’s handling and use. Ethical issues, too, have had an influence: in many societies, pizza is treated as an inanimate object, like a rock (only softer), and no consideration whatsoever is given to the possibility that it might possess some sort of limited awareness, possibly even experiencing feelings of distress or pain.

In modern times, pizza species have become entirely dependent on human cultivation, just like many plants, domesticated animals, and model organisms that are studied in laboratories. The biology of pizzas has become simplified through this dependency. Modern forms have, almost certainly, lost genes that were originally crucial to their ancestors’ survival. As a result, pizzas are no longer competent for survival in the wild. Although it should not be considered a parasite, pizza’s dependency on humans has likely sent it along an evolutionary path resembling that of pathogens and viruses.

Under normal processes of natural selection, one would expect organisms that are tastiest to their predators to be eaten more, and this would subject certain types of pizza to to intense negative selection. This would also be the case for pizza, particularly since it has no intrinsic means of locomotion that would allow it to escape from its human predators.

But domestication has reversed this trend, positively selecting for the forms that are most likely to be eaten.

Nutritional and Health Implications for Non-Pizza Species

Pizza is a fixture of worldwide ecosystems and global food chains, nourishing species as diverse as college students, police, bowling teams, and other categories of humans—and also dogs, cats, hamsters, pigs, rats, cockroaches, crocodiles, fish, etc. The decaying remains of pizza crusts that have fallen down cracks in sofas provide a rich environment for microbial life, including bacteria such as legionella, Yersinia pestis and Mycobacterium leprae, which might otherwise be in danger of extinction. In this way, pizza plays a central role in global biodiversity; one might even regard it as the glue that holds everything together. But this notion is somewhat speculative.

Technical obstacles have made it difficult to maintain pizza in laboratory cultures, creating a sort of black hole of knowledge with regards to its biology. This is alarming in light of the numerous epidemiological studies tying pizza to serious health problems including obesity, addiction, attention deficit disorders, frostbite, burnt tongues, and deaths related to placing aluminum foil in microwave ovens.

Excessive consumption retards human cognitive development, pushing adolescence far into the college years, a situation which can only be reversed by adding vegetables to the diet. Predatory consumption of pizza has led to a major reduction of human motility; delivery services have completely eliminated the hunter-gatherer activity that used to be required to obtain it.

Summary of Pizza’s Biological Features

By applying well-established methods of phylogenetic analysis to the features of pizza (namely, the ingredients found in 58 extant species) we derived the first systematic evolutionary account of its descent from an ancestral form. The results point firmly to a last common ancestor, providing insights into fundamental aspects of its biochemistry, development, and the selective forces that have shaped its evolution into diverse types. Our observations of pizza in situ suggest that its basic biology draws on unique features which are hard to reconcile with those of traditional biological models. A key finding is that the ancestral pizza exhibited very little elaboration of specialized structures. It consisted of only three tissues: dough, tomato sauce, and mozzarella. Each of these tossues exhibits a high degree of molecular complexity, while having stable biophysical properties that are crucial to maintaining the integrity of the organism over time.


Figure 2.  Artist’s reconstruction of the last common ancestor of all current species of pizza

  1. The Pizza Lifecycle

The pizza lifecycle is marked by the three phases embryogenesis, maturation, and decline.

Entry into a phase is determined by environmental factors: embryogenesis takes place at room temperature; maturation begins when the temperature dramatically rises to about 220 degrees Celsius and usually lasts 10-12 minutes. Returning to normal room temperature introduces a brief period of homeostasis after which pizza enters the phase of decline.

Laboratory experiments have shown that pizzas which have completed embryogenesis can be preserved through cryopreservation, which induces a state of dormancy or hibernation. They can be maintained this way for a year or two without any apparent damage. The decline phase can be prolonged by a day or two through cooling, after which a brief exposure to heat is used to revive the pizza. This may cause it to repeat the last stages of maturation and then enters the decline phase, which is now accelerated.

At the beginning of the decline phase, most pizzas separate into segments in a process we have termed alternative slicing. The result is a series of cracks or furrows that extend from one side through a mid-point and end exactly opposite around the circumference. Multiple slices develop, leading to wedge-shaped units—most often an even number (between 4 and 12) of segments. It is unclear whether this process begins at the middle and radiates outwards, or starts at an edge, traverses the middle, and arrives at the other side. The mechanisms required for these two processes would necessarily be fundamentally different. Either way, a number of fascinating questions arise: As each split begins, what molecular signal does it follow to stay on course rather than veer away? What determines the total number of divisions that will occur? How does one side of the pizza “know” what is happening on the other side, so that the proportions of the slices remain equal? We are exploring these questions through the “Virtual Pizza,” which we developed for use in computer simulations.

The biological functions of these subdivisions are unclear. We hypothesize that they have been sustained through a unique sort of evolutionary mechanism that does not directly benefit the pizza itself, for example by promoting its survival, but rather by ensuring a harmonious environment around it.  A failure of the pizza to divide would cause its predators to fight over the whole. Even if only a very small fraction of these conflicts were fatal, over long periods of time this would offer a slight advantage to animals that fed off the sliced form. Since pizza now exists only as a domesticated species, its genomic features can be seen, in a way, as an extension of the gene pools around it. For whatever reasons, this leads to better chances of survival for pizza variants that promoted harmony among the other species around it. The effect appears to be bi-directional: research has shown that just the presence of a slice of pizza triggers a release of dopamine among humans.  This makes them less aggressive and more sociable. So ultimately, the integration of pizza into the human diet appears to have played some role in the development of modes of primitive social organization that became more and more elaborate until they acquired the forms familiar to us today: priesthoods, the military, and governments. And bowling alleys, and pizza parlors.


Figure 3.  The Virtual Pizza: Computer modeling of alternative slicing

  1. Tissue Structure Through the Lifecycle

Dough begins as an elastic substance under room temperature, which is characteristic of the environment of embryogenesis; in the heating phase it becomes crisp, and remains that way as it cools, matures, and approaches death.

The sauce begins as a thick fluid which crystallizes somewhat at the pinnacle of the heating phase, remaining gummy through the first phases of cooling, then hardens until it is nearly all crystallized at the end of cooling.

Mozzarella begins as a rubbery substance, melts into a liquid under heat, and only hardens after an extended period of cooling over time.

These transformations of the three tissues do not alter the basic structural integrity of the whole, unless the pizza is subjected to unusual biomechanical forces such as it would encounter when flung through the air. An embryonic pizza would stretch and fly apart; the hardness of a mature pizza gives it the properties of a Frisbee.

pizza_quer copy

Figure 4.  Layers of pizza tissue structure (side view)

  1. Embryogenesis

The earliest stage of pizza’s embryonic development bears some similarities to Dictyostelium (“slime mold”), an organism that lies at the borderline between unicellular and multicellular life.

Dough assembles in an environment containing sufficient concentrations of the necessary chemical and biological ingredients: particles of wheat, water, sugar, and some form of oil. Such environments usually contain abundant populations of yeast cells, which get dragged along as the components are attracted to a central location, probably by sensing chemokine-like molecules that have been secreted by a cook’s hands.

Upon arrival, the components merge in a sort of symbiotic collective that draws on the genes of the wheat and yeast to trigger a series of metabolic reactions that derive energy from the sugar and oil. The result is to fuse everything into a pliant, undifferentiated mass of dough. Originally this is a ball-shaped mass with stem-cell like properties that may yield a single pizza, or be pinched off to form genetically identical twins.

The ball spreads across a surface to form a flat, circular basal membrane on which new layers will arise. The dough induces the formation of tomato sauce, rapidly followed by a layer of mozzarella. In more elaborated forms, additional organelles such as salami or anchovies arise through chemical interactions between the sauce and mozzarella. Yet the three-layered structure is retained.

This is highly reminiscent of the tissues that arise in animal gastrulation, but that process begins with a group of cells that have retained the ball-like shape, causing inner layers to interact in more complex ways. This difference is a determining factor in pizza evolution, because it leaves the lower layer attached to a substrate, while the upper remains naked and exposed to the environment. The lack of a membrane or shell means that the upper layers of a pizza must constantly contend with fluctuations in the surrounding environment.

This single difference, combined with the fact that embryonic pizza does not have a womb to protect it from dramatic changes in temperature, probably severely restricted the degree to which ancient pizzas could vary from the original design. While eventually pizzas developed specialized organelles such as salami and funghi, there was never much variation to serve as the basis for selection. So the type of evolutionary tinkering that occurred in animals, and shaped the formation of highly sophisticated organs such as the brain, never occurred in pizza.


Our investigation provides the first account of the evolutionary route by which modern species of pizza diverged from an ancient, ancestral form. We characterize the last common ancestor as sharing the three-layer structure of modern pizzas, which resembles the first stage of animal gastrulation. In contrast to animals, however, pizza got stuck there, and never added additional developmental stages.

It is interesting to speculate what might have happened if instead of flattening, dough had retained its original, ball-shaped form, and built layers of sauce and cheese inside. Pizza calzone, a modern species, obtains this type of structure by folding the membranous dough around to seal off the interior, but this is the very last stage in its embryonic development. If, in the distant past, this progression had advanced to the beginning of embryogenesis, pizzas might have followed an evolutionary path much more like our own. Potentially this could have made pizza, rather than humans, the preeminent form of intelligent life in the known universe.

Thinkers such as Richard Dawkins see the evolutionary value of intelligence in its promotion of the survival and reproduction of a species’ genes. Pizza found an alternative by entering into a dependency on humans, who gladly overtook measures to ensure its reproduction, which would have required the development of new social structures. Over time the dependency increased and ultimately restricted the evolution of pizza along paths toward the species we know today. But this notion is somewhat speculative.

Preliminary data suggest that it may be possible to push the knowable ancestry of pizza back even farther, to a point at which the last common ancestor diverged from other organisms such as crêpes, pancakes and burritos. We are currently digesting the data from that investigation, which has presented some technical challenges (mainly due to the fact that we have gained so much weight we no longer fit into our cars).  Once these issues have been resolved, we anticipate publishing the results at a later date,


“Development of a Nutritionally Balanced Pizza As a Functional Meal Designed to Meet Published Dietary Guidelines,” Emilie Combet, Amandine Jarlot, Kofi E. Aidoo, and Michael E.J. Lean, Public Health Nutrition, vol. 17, no. 11, 2014, pp. 2577-2586.

“pheatmap: Pretty Heatmaps,” R. Kolde, R package version 1.0.8, 2015. <https://CRAN.R-project.org/package=pheatmap&gt;



  • Combet E., Jarlot A., Aidoo KE., Lean ME. Development of a nutritionally balanced pizza as a functional meal designed to meet published dietary guidelines. Public Health Nutr. 2014 Nov;17(11):2577-86. doi: 10.1017/S1368980013002814.
  • Kolde R. (2015). pheatmap: Pretty Heatmaps. R package version 1.0.8. https://CRAN.R-project.org/package=pheatmap.

Supplementary files will be provided by the corresponding author upon request

It’s not over until the fat lady sings

An algorithm to end your paper with a bang, not a whimper

You’ve just finished the Best Paper Ever Written, but something’s missing: that perfect last sentence that will make your readers jump from their seats and shout, “Encore! Encore!” They shouldn’t leave before the soprano hits her highest note. What’s the secret? Here’s an algorithm – distilled from thousands of high-impact papers – that practically guarantees success.

Method:  Two readers, working independently, read the same paper and wrote down the last sentence. In a second step they met to drink very strong coffee and compare data. Surprisingly, the results were sometimes in disagreement. Whoever made the mistake had to buy the coffee. Subsequently, the same steps were repeated on 20,000 more papers, over a period of time that seemed infinite but was likely somewhat shorter. At regular intervals coffee was withheld and whiskey was administered, as a means of ameliorating neurological symptoms and reducing the likelihood of  cardiac incidents. When 20,000 sentences had been collected, a systematic comparison was undertaken. Initially this produced no results, due to the inability of the researchers to detect patterns or even stand up most of the time. After six months in a rehabilitation center, their cognitive abilities had returned somewhat and the data was submitted to a second round of analysis. This yielded a model and a powerful algorithm that generates the final sentence for any paper, in a high-throughput way, with very minimal input from the author.


Results:  Most high-impact papers end in this sentence (n = 13,521; p < 0.05):

This suggests that our work will surely open new avenues in the diagnosis of individuals suffering from cancer.

Astoundingly, this is true even for papers that don’t mention cancer at all and fail to provide evidence of any connection to cancer. Of course it’s almost impossible to rule out a connection; with a little creativity, anything can be connected to anything, including Kevin Bacon. We all know that the best way to demonstrate that something is connected to cancer is to claim, in print, that it is not: within days somebody will find some sort of link.

In nearly all the other papers, authors changed a few words to include their own content but kept the structure of the model sentence. This provided a template for the algorithm:

This  1   that   our  2  will    3      4    new  5   in the    6   of  7   suffering from   8 .

The algorithm can be used by anyone capable of following simple instructions: From each column below, choose the word that best fits your research, then put it in the corresponding slot in the following model sentence:


1 2 3 4 5 6 7 8
suggests work likely open avenues diagnosis individuals cancer
implies discovery surely lead to approaches treatment patients Alzheimer’s disease
proves findings definitely trigger insights quality of life domestic animals old age
indicates results obviously stimulate fields sanity children excessive verbosity
demonstrates project clearly boost disciplines health chickens domestic


urges secret videos inevitably excite ion channels sexual gratification teenagers hormone


concludes conclusions conclusively bring to a conclusion dead ends mortality senior citizens terminal old age
proclaims proclamations permanenty provoke pathways proselytization popes priapism
proclaims pronouncements omnisciently ignite mule paths removal of nutcases promiscuity
confirms excretions necessarily inflame intestinal canals presence of physicians lack of sleep
fantasizes random musings perfectly hurl gastrointestinal tracts longevity of political prisoners STDs
states considerations considerably push Autobahns socialization of condemned prisoners prion diseases
foresees algorithm astutely impassion windows education of students hallucinations
hints ideas definitively grope with hiking paths conceptual development of torreadors a case of the giggles
threatens witticisms assuredly throw open corridors disposal of stray pets poor hygeine
instructs teachings succinctly emit fish hatcheries recovery of vicious animals messiness
promulgates lessons exhaustively exude routes death of viruses body odor
presupposes commandments heavily reduce considerations occupational therapy of queens/ other titles of royalty poor self-esteem
attests theories limitlessly disgust red carpets domestic situation of insects split personality disorders
promotes hypotheses infinitely digest trap doors visa status of rocks the attention of a two-year-old
dispells treatises obnoxiously fling aside drive-throughs marital status of irrationally happy people public intoxication
concurs dissertation quirkily discard escalators enjoyment of saftey inspectors idiosyncracies
occludes paper dramatically continue litter boxes eyes of television


writer’s block
announces grant application significantly enhance start-ups pockets of alien life forms library fines
broadcasts YouTube video meaningfully display cat videos retirement parties of professors projectile


tweets workshop stultifyingly expose body parts electrical sockets of blind dates fatal hiccups
predicts examinations clearly sharpen views lenses of myopic people new bifocals

In rare cases, the most fitting words for your project will all be found in one row:

This  concludes  that   our  conclusions  will  conclusively  bring to a conclusion  new dead ends  in the  mortality  of  senior citizens  suffering from  terminal old age.

But in most cases you will need to mix items from different rows, producing sentences like this:

This proclaims that our project will omnisciently inflame gravel roads in the recovery of royalty suffering from poor self-esteem.


This hints that our witticisms will succinctly enhance new escalators in the recovery of chickens with poor hygeine.


The power of the algorithm lies in the number of possible combinations it can produce: namely, 258. Somewhere in this galaxy of sentences must be one that adequately describes your project. If not, you should probably change topics.


The sentence produced by this algorithm should be put at the end of the “Discussion” section. “Discussion” was coined by combining the words “Discus” and “concussion”, reflecting the fact that a good paper should have an impact. A good discussion compresses the paper’s data into a heavy object, if possible with a good aerodynamic shape, and hurls it high into the atmosphere. A high-impact paper will return with such force that anyone struck by it will require medical attention. To avoid being struck yourself, which is embarrassing, never throw your discussion straight up. This suggests that our work will surely open new avenues in the diagnosis of individuals suffering from cancer.

All material on this website copyright 2016 by Russ Hodge

Carmen Birchmeier’s Brains





on the occasion of
Carmen Birchmeier’s 60th birthday

“It’s complicated.”

– Walter Birchmeier



In 2013, unbeknownst to most of her colleagues, friends, enemies, distant cousins, and predoctoral students, although not necessarily in that order, Carmen Birchmeier adapted ancient procedures from Medieval alchemists, added some spices from old family recipes, and developed a method of extracting human brains from their natural environment and maintaining them in vitro in the lab. The second step was somewhat harder than the first. Debrainings have been performed before, of course, but the methods remain nearly as labor-intensive and time consuming as they were thousands of years ago. Birchmeier’s innovation was to develop an automated, high-throughput pipeline. But the more serious bottleneck was Step 2: keeping a human brain alive in the lab for more than, say, 10 seconds. That’s where the spices came in.

Once the brains were surviving long enough, Carmen’s carried out some relatively successful experiments to replace the brain in the head, usually that of the original owner, although in one case some sort of administrative error led to what is probably best termed an “involuntary exchange.” The problem was not detected for quite some time because as it turned out, each of the brains preferred its new habitat. Each brain knew that it was in the other body, but it didn’t know whether the other brain knew, and if it didn’t know, well what it didn’t know wouldn’t hurt it. This led to some strange conversations in which everyone was pretending to be someone else, which can be confusing, especially when you were sitting across from yourself. But you don’t need to know any of this. In fact, just forget the last paragraph, because nothing in it reached statistical significance.

The lab attempted to publish a paper on the subject, but reviewers rejected it on the grounds that it was “merely methodological” and “unlikely to have any practical clinical applications.”

Because she feels, however, that this work might be useful to other neuroscientists, her lab has collected a number of protocols describing the proper treatment of brains in the laboratory. This document is intended as a guide to other groups who might be interested in replicating her work.


– Russ Hodge, 2015


Removal of the brain


  1. Open the skull.
  2. Unplug the wires connecting the brain to the eyes.
  3. Unscrew the ears (in a counter-clockwise direction).
  4. Detach the jugular and carotid vessels. The jugular is blue; carotid, red. During reinstallation, reattaching the vessels to the wrong targets will cause the person to think backwards.
  5. Rotate the brain on the brainstem approximately 90 degrees (counterclockwise) until you feel a firm “click”.
  6. Remove the brain.
  7. Don’t forget to close the blood-brain barrier: turn the wheel-shaped handle in a clockwise direction.
  8. Check the surface and interior of the skull for any flora or fauna that have crept through the ears and established colonies. Gently swab with a disinfectant to remove.
  9. Check the brainstem and apply a little water if it seems dry.
  10. Recover Q-tips or any other objects, such as pencils, that have been pushed through an ear and fallen inside the brain cavity.
  11. Store the head (and any other parts of the body, as desired) in a cool, sterile environment for potential reuse.


Checking the overall status of the brain’s health


Hold the brain between your two hands and give it a gentle squeeze. A healthy brain should have the consistency of cauliflower. Is it firm or squishy? Does it smell like alcohol, garlic, or cigarette smoke?

Which type of cheese does the brain resemble most?

  • Edam? (Healthy)
  • Swiss? (Alzheimer’s)
  • Camembert? (An undefined but clearly pathological condition)

Perform the “drop test:”

  • Hold the brain approximately 1m above a firm, flat, clean surface.
  • Drop it.
  • Measure the maximum height of the first bounce. A healthy brain should attain approximately 50cm.
  • Catch it before it rolls away.

Check overall symmetry by rolling the brain over a level surface. If the owner has worn a hat for many years, it may be squished on one side.


Tests of memory and basic cognitive functions


Before removing the brain, you should obtain a general sense of its overall function. Since brain functions are based on electrochemical energy, two simple tests can be performed:


  1. Insert a device that can deliver an electrical stimulus at various degrees of strength (taser, cattle prod) into one ear, and attach a voltmeter to the other ear. Deliver the charge and measure the net loss in voltage.
  • If the net loss is > 50%, try another brain.
  • If you detect a burning smell, lower the charge and try again.
  • Do not be surprised if the voltmeter records a charge higher than the one you delivered, especially after repeated trials. This indicates long-term potentiation.

2. Insert a USB cable into the ear and see if the brain appears as an external device on your Mac computer (OS X.7 or higher). If you do not see the “brain” symbol on your desktop, try to mount it using the Disk Utility. If this does not succeed, try another brain. If the brain is password-protected, ask the owner for permission to access it.


“Do’s and don’ts:”

Basic protocols for handling brains in the lab


If kept outside the body for long periods of time, brains should be occasionally turned to avoid bedsores.

There is anecdotal evidence that brains enjoy an occasional massage.

If the brain is to be replaced in a new body, use a powerful magnet to erase old memories. The operating system may need to be reinstalled.

Brains may be frozen. For defrosting, use the LOWEST setting on the microwave oven.

The “three-second rule:” If a brain is accidentally dropped, but picked up within three seconds, it is unlikely to be contaminated. Simply brush off any visible dirt.

The brain’s expiration date should be written somewhere on the bottom. Check the date before reinstalling a brain. A brain may be kept past this date if it has been refrigerated and does not smell. Expired brains can be fed to pets.

Meticulously record all tune-ups and repairs in the service manual, which is generally found in a pocket inside the skull near the left ear.

Do not use the brain in games of Nerf basketball or other sports activities.

Do not allow pets to play with brains.

Don’t let the brain get bitten by mosquitoes. The itching will drive it insane.

Brains sunburn very easily, so any brain exposed to sunlight should be generously coated with a sun-blocker with a rating of 50 or above.

Advise patients to get brain insurance before any procedure so that they can receive compensation in case anything goes wrong, providing they remember.

Brains often shrink slightly when stored outside the body. Upon reimplantation, use bubble packing to make up for the extra space.

If the brain seems too large for the skull upon reimplantation, use Vaseline or some other petroleum-based lubricant to ease it in.

If you have replaced a brain and notice some extra parts lying around, such as the hippocampus, just put them in wherever there is space. They will automatically migrate back to the proper position.

A reimplanted brain may need to be reanimated with an electric charge to function. Any normal taser will do. Stick the business end in one ear and deliver a charge until the patient tells you to stop.

If upon brain removal you find a computer chip or some other electronic device, you should assume that it is government property. Destroying it is a federal offense accompanied by a mandatory sentence and a fine. Get rid of it, but make it look like an accident.

If the brain belongs to a friend or acquaintance, you may be tempted to carry out some slight alterations to improve its personality. Any such measures are, of course, unethical, unless they are intended to improve the person’s singing. Do not be tempted by additional suggestions for improvements from the patient’s spouse or family.

It is illegal to sell a brain, but you may pawn it for short periods of time. Do not bet a brain in a poker game, even among members of the lab.

Don’t dress it in a silly hat, doll’s clothes, or make distasteful drawings on it with a permanent marker. Only write on the brain with an erasable whiteboard marker.

There is no evidence that when a brain is removed from the body, it can control the minds of people around it. Of course, that’s what it would want us to think.

If the brain belongs to a famous person, don’t take it out in public and show it around, especially in a bar. You may, however, do whatever you like with the body, provided it is restored to its former condition before the brain is reinstalled.

Do not stick Post-its directly onto the surface of the brain.

Do not use a brain as a Halloween Jack-o’-lantern.

Although brains are highly similar in appearance, each brain is unique and gives off a distinct smell. Train a dog to distinguish them.

A brain is not a pet. Do not try to teach it tricks.


Twang science 2: Communication (Fake paper 2)

Dear editor,

I am writing with regard to the recent publication in your journal concerning the acquisition, maintenance, and loss of a type of speech called a twang. Terris et al. make only cursory mention of – and thus fail to do justice to – a hypothesis that speaking with a twang might be associated with a retrovirus or another pathogen. Our lab has been pursuing this question for over 20 years and I would like to clarify the current status of the debate.

Our search for a pathogen involved in language perception and speech began with a series of observations on the phenotype: in many ways, the spread of the phenotype resembles an epidemic that is tied to particular regions. For example, Valley Fever, or coccidiodomycosis, is caused by a fungus found in dry areas of the Southwestern United States. The fungus forms spores that are spread by winds, particularly when the soil has been disturbed by storms, construction, agriculture, four-wheel drive offroading, motorbiking, or other sports activities. Inhaling the spores leads to an infection in some people.

It is estimated that about a two-thirds of the population of some regions of the Southwest will test positive for the fungus Coccidioides spp. at some point in their lives. Only a fraction develop flu-like symptoms. In severe cases, nodules form on the lungs. Their onset and their severity vary from person to person, likely for genetic reasons, which also play a role in whether the pathogen affects organs beyond the lungs. A weakened immune system greatly increases susceptibility. Symptoms may disappear and reappear over the course of a lifetime.

In many ways the spread of the twang resembles such diseases, which are caused by a pathogen restricted to a particular geophysical niche. There are “hotspots”, particularly in the Midwest, where penetrance reaches nearly 100 percent, surrounded by zones of variable penetrance. Geographical barriers may play a role in limiting its spread. The Rocky Mountains, for example, divide an eastern region of pronounced twang from western areas where it is hardly found at all. There is some evidence that following the Dust Bowl, which saw massive migrations from Oklahoma to California, the pathogen was transported to the western coast, where it was responsible for the rise of “Valley Girl” speech. It has been estimated that in their clothing and shoes, immigrants brought approximately two tons of Oklahoma dust to California. The pathogen may have come along for the ride.

Infants seem particularly susceptible; virtually every child born in a hotspot will acquire the twang, independent of his or her genetic background. Some studies indicate that the degree of penetrance is associated with socioeconomic factors. This, too, is common for pathogens associated with dirt or a lack of sanitary infrastructure. An intriguing observation comes from recent epidemiological work that links the severity of a family’s twang to the number of open beer bottles and pizza boxes lying around the house. Another correlation is the number of rusty cars parked behind the house. In each case, the higher the number, the more severe the twang.

Those exposed during early childhood typically suffer from the twang to some degree their entire lives. Interestingly, those who leave a hotspot for many years – usually decades – may lose many of its features. However, if a person returns home, for example during Thanksgiving, he or she experiences a dramatic but temporary increase in twang speech patterns. This likewise reflects the behavior of some pathogens: removed from their ideal environment, they reproduce only slowly or enter a phase of latency. Contrarily, someone who moves to a hotspot later in life may at some point begin to show symptoms, but only after prolonged exposure.

The hypothetical pathogen does not seem to be transmitted from person to person. Children raised by twang-positive parents in a twang-negative environment do not typically show symptoms. Weaker phenotypes that are occasionally observed might be explained by transmission through contact with fomites such as dust-ridden clothing, furniture, or beer bottles that have accompanied the family without being properly cleaned before a move.

The findings of Terris et al. are intriguing but do not in any way contradict the pathogen hypothesis. A range of infectious agents are known to affect CpG methylation patterns and the expression of genes. Tumors in particular regions of the brain that affect speech patterns may cause symptoms by disturbing neural networks, but they may also be accompanied by changes in the epigenetic regulation of genes.

Validating the twang-pathogen hypothesis will require studies of the metabiome of those affected compared to controls. We have recently carried out such studies using a cohort similar to the patients and controls described in the paper by Terris et al. Our preliminary work, which is currently being revised for publication, has identified three potential candidates: the strongest correlation involves a retrovirus which bears some similarity to the feline leukemia virus, and there is a somewhat weaker association to two species of fungi whose spatial distribution closely matches that of the twang. At the moment we cannot rule out combinatorial effects caused by multiple pathogens, whose lifecycles depend on a delicate balance between body homeostasis and external factors in the environment.


Bob Luser

News and views: From the frontiers of Twang science (Fake paper 1)

The historical origin of the word “twang” is thought to be an example of onomatopoeia: a word that sounds like what it represents. A twang is the kind of tinny, nasal sound produced by an instrument such as a banjo. It also refers to a type of speech usually associated with the English-speaking population of regions of the Midwestern and Southern United States, as well as several country music singers. The behavior required to produce a twang is complex: speakers apply a nasal quality and usually a rise in pitch to several vowels. Acquiring a twang requires physiological mechanisms ranging from perception (infants hear the speech of those in their environment) to a feedback mechanism (imitation and self-correction) and all the body parts used to produce vowel sounds: the tongue, nasal cavity, mouth, and more extensive pharyngeal structures.

Complex speech phenotypes may have a molecular basis within cells and tissues. Speaking with a twang likely involves several regions of the brain associated with speech and learning as well as those responsible for the coordinated muscular activity of the tongue and soft palette and other parts of the mouth and nasal cavities. Researchers have proposed various mechanisms to account for twang acquisition and performance among speakers. Since the behavior is acquired and can be lost again through training or relocation to an environment where speakers have a different “accent”, it is feasible that epigenetic alterations of genes must be involved. (An early study proposing a retrovirus has been discounted.) There is also some evidence that lesions can be associated with the gain of a temporary or long-term twang, or to the loss of a preexisting twang, which may help in identifying regions of the brain that are involved in its performance.

In a study in the latest issue of Nature Genetics, Terris et al. have studied epigenetic markers around genes that have been implicated in language perception and production in previous studies. They compare the status of these genes in regions of the brain thought to play a part in speech and pronunciation to regions less likely to be involved in these behaviors.

The list of candidate genes was obtained from a database hosted at the Quantitative Neuroscience Lab of Boston University (http://neurospeech.org/–sldb). Additional candidates were obtained through a computational analysis of the PubMed literature, harvesting articles meta-labeled with tags such as the following: twang, speech, language, pronunciation, and nasality.

Tissue samples were obtained from speakers who had undergone brain surgery and were judged to have a pronounced twang (or not) by a mixed audience of native (US-born) linguists. Results were compared between this group and five sets of controls: speakers who had never had a twang, those who had had a twang earlier in life but had lost it, native speakers of French (whose speech is not estimated to have a “twang” but is highly nasal), and a few individuals who had lost or acquired a twang through a stroke or other type of cerebral damage. Evaluations were performed using a standardized “Twang scale” developed at a school of performing arts in Los Angeles. (This program was developed to remove the twang of young actors.) Speakers were graded on a scale of 0 to 10 (0 = British accent; 10 = Bob Dylan).

The lab carried out a comprehensive analysis of methylation patterns across the genome from brain tissue samples from target and control regions for all five groups. The primary method used was bisulfite sequencing, which is based on the treatment of DNA with bisulfite. This causes a chemical conversion of cytosine residues to uracil, but only if the cytosines are non-methylated. Methylated cytosines are protected from the change. Comparing the sequences of treated vs. non-treated DNA permits a base-by-base readout of loci where Cs have been transformed to Us, and those which have not. The results from each group were combined and averaged and filtered for significance. They were compared to each other and to a mixed population of all groups.

The resulting patterns were compared on a chart, which revealed spikes (upward = higher methylation, downward = lower) at specific genomic locations. Both extremes are interesting because the twang phenotype might be due to either higher levels of methylation at particular loci, lower levels, or some combination.

Interestingly, the study revealed a number of significant differences between these patterns in “plus-twang” and “minus-twang” groups. The most extreme variation was found in cells of the superior temporal gyrus and primary auditory cortex, with somewhat smaller (although still significant) peaks in adjacent tissue of the brain region known as Wernicke’s area. The highest difference was found in a region ca. 1 Mb from the FOXP2 gene on chromosome 7, a gene which is highly implicated in many aspects of language acquisition and performance. A bioinformatics analysis of this region revealed a high statistical likelihood that it plays a regulatory role in FOXP2 activation, and contains putative FOX transcription factor binding sites. Both this region and the FOXP2 gene have closely related orthologs whose sequences and relative positions are well conserved between mice and humans. Follow-up studies in mice revealed that deleting the putative regulatory region inhibited expression of the orthologous gene in several areas of the brain, and resulted in a shift in squeaking pitch.

The authors remain cautious about their findings. In the paper’s discussion they report: “The exact molecular mechanisms underlying differential methylation remain to be understood, as does the quantitative significance of the identified loci in twang acquisition (or loss).” To address the mechanistic interplay between methylated regions, their regulators, and the twang-phenotype, the group has developed transgenic Cre mice in which particular methylated regions, methyltransferases, and methyl binding proteins can be deleted in a neuron-specific manner. Additionally, libraries of small molecules are being screened for specific effects on squeaking pitch as a phenotypic marker for twang in the mouse model.

Ideally, a potential twang modulator might be found among approved drugs or natural substances, which can be used to study the methylation status of the FOXP2-associated region. The next step would be to assemble a cohort of patients (twang-plus and twang-minus) who have already tried the drug or substance, checking to see whether this exposure has altered their speech patterns.

The author would like to thank Robert Zinzen for critical review of this article.