COVID-19 in the Brain?

There is news circulating about COVID-19 and the brain that is worth a closer look. I first saw this in multiple news reports that did not cite the original article. A quick search pulled up a university press release that linked to the published article that studied the SARS-CoV-2 virus and inflammation in brains of infected mice.

Mice are often used to model human disease to study the source of the disease (viral, genetic, bacterial, etc.) and the pathology of disease (how it affects the body). This is often a good way to learn more about something, although great care has to be taken to develop a model that can be roughly translated to what happens in humans.

In this case, the mice, K18-hACE2, were made to express the human ACE2 receptor, the target of SARS-CoV and SARS-CoV-2. To mimic how this receptor is expressed in humans, it was given an epithelial promoter. Promoters tell a gene where it should be expressed. In this case, the promoter tells the gene to express in epithelial cells, which places the human receptor in the mice’s airways to allow the virus to infect cells similar to how it infects cells in a human. The specific promoter used is form keratin 18 (KRT18), which does have slightly broader expression than ACE2, but it’s a close approximation. Worth noting is that KRT18 does have low levels of expression in the brain, whereas ACE2 is undetectable.

Why go into so much detail about the mice model used in the study? The brains of these mice likely have more ACE2 receptors than a human brain would have. That does not invalidate the results of the study, but is a reason to give pause when comparing humans to the animal model. Also, this study doesn’t go into whether SARS-CoV-2 lingers in the brain because all of the mice died within six days. This is how a hypothesis is formed for further study. It is difficult, however, because you are limited to studying the virus in brains of people that died suddenly due to COVID-19 or from other causes, like car accidents, during an infection.

Something also worth noting is how scientific articles are summarized in press releases and news reports. University press offices put out these releases because it’s good publicity. They are often well written, but sometimes they overstate findings. In this case, the press release did include a quote from the researcher about the virus hiding in the brain, but the news reports are where statements about the virus later reactivating were inserted.

Viral reactivation typically refers to a virus that is coded in DNA and integrates into the host genome. This happens with the varicella-zoster virus (chickenpox that reactivates to cause shingles) and HSV1 (the virus that reactivates to cause cold sores). RNA viruses such as SARS-CoV-2 never get converted into DNA and do not have a dormant (lysogenic) part of their lives. It is possible that a virus may take longer to eliminate from certain organs or tissues, but this is not the same as reactivation that can occur months, years, or decades later.

Does this mean we should be worried about SARS-CoV-2 in the brain? The only immediate thing it would change is whether the disease adversely affects the parasympathetic nervous system and some treatments could better maintain things like breathing and heart rate. Does it mean that we have a possible avenue to explore to help explain long-term damage caused by COVID-19? Yes.

In short, I don’t see any changes in the short-term based on these findings, but it does encourage more research into these areas.

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Reaching for the End

We’ve been in the midst of a pandemic for over half a year now. We already know that masks provide short-term protection and, eventually, a vaccine will provide long-term protection.

Current estimates say roughly 40% of individuals with COVID-19 are asymptomatic (i.e., will never develop symptoms) and all other COVID-19 patients are presymptomatic (i.e., have not yet developed symptoms) for 2-14 days. The uppermost estimate from seroprevalence studies indicate up to 10× as many people infected, likely without severe symptoms. This means most people spreading SARS-CoV-2 probably aren’t even aware that they are contagious, making masks essential for reducing viral spread.

Facial coverings– from a well-fitting N95 mask, to a triple layer cloth mask, to a thinly stretched single-layer neck-gaiter– provide varying degrees of protection. The better the face covering, the better it protects both the wearer and the people around them. Ideally, we’d all be able to wear nice-fitting N95 masks, although washable triple-layer cloth masks are a thrifty alternative without the trash and litter we see from many disposable surgical masks.

Recent estimates for herd immunity state that a minimum of 50-70% of a population needs to be protected against COVID-19. The highest estimate from the WHO and some recent studies put the number of infected persons around 10% so far. Some diseases, e.g., measles or pertussis, require over 90-95% vaccination rates to prevent outbreaks. No vaccine is perfect and some persons are unable to receive vaccines, unable to develop a long-term response, or lack a sense of social responsibility, so we’ll never see an effective 100% immunization. Even though some outbreaks may occur in areas with lower vaccination rates, this overall rate can prevent or end a pandemic.

These are very rough estimates but, if masks are, on average, 50% effective, then 100% usage would be equivalent to a 50% immunization rate of a population. Because some masks are more effective (e.g., N95) and some are much less effective (e.g., neck gaiters), every person needs to be wearing facial coverings of a high enough quality to reach an average of at least 50% effectiveness. Short-term, this would make masks as effective as a vaccine will be in the long-term. It’s a rough approximation, but the idea is pretty simple and easy to grasp.

There is no question that universal masking would end the pandemic while we wait for a long-term alternative; the only question is whether enough people will wear masks and then choose to be vaccinated. To be fair, that’s not the only way out; we could just wait for at least 0.5% of the world’s population to die off instead (~40 million people).

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Wishful thinking and COVID-19

Most scientific theories and discoveries arise from the scientific method, with next steps based on the results. There are epiphanies (“Eureka!”*) that bypass this process, but those are rare. If a question is developed into a hypothesis, tested, reviewed, discussed, and yields an answer that furthers knowledge, then the scientific method has been applied; the next steps can be moved onto with confidence. Unfortunately, sometimes wishful thinking is applied instead. Wishful thinking may occasionally have a clear testable hypothesis, but when the test results are ignored or never even generated, then the scientific method has not been followed and the conclusion is baseless.

There is always a lot of wishful thinking, with or without a testable hypothesis. When wishful thinking contains a testable hypothesis, it may seem like the scientific method is being applied. It is when tests are performed that this type of wishful thinking can be differentiated from the scientific method. Any time science is discussed by the public, some people will resort to using wishful thinking to make their point, even when data resulting from the scientific method make wishful thinking appear as pure fantasy.

The Testable Hypothesis

The hypothesis that a significant portion of people in an area have had COVID-19 and are subsequently protected from infection by the novel coronavirus (SARS-CoV-2) is testable. Seroprevalence, which is a measurement of how many people have antibodies, can be determined by screening a sample of the target population for antibodies against the novel coronavirus. Fortunately, this is something that has been tested, although few large-scale studies are available. There was one study done in China in March, another in Spain in April, and a third in the United States in July.

For any study, it is important to recognize the limitations:

  1. It may take two to three weeks after the onset of symptoms for antibodies to develop, so newly exposed individuals will still be seronegative. When reviewing PCR studies, this timeline is limited to a 4-7 day window after exposure for a positive result.
  2. Specificity and sensitivity of the test is important, meaning they should have minimal detection of other antibodies and be able to detect low levels of the target antibody. The methods state 99.8% and 100% specificity with slightly lower sensitivity.
  3. Another limitation is how the sample population was selected and how it relates to the general population. If a study only uses patients from a particular clinic with a particular ailment, that can be extrapolated to the general population, but the level of error is increased.
  4. Another significant consideration in a rapidly evolving pandemic is time. Samples collected in February from the United States mean something very different than samples collected at the same time from Italy or China.


The three studies referenced above (also linked after this post) all took place at different times which can be compared to the known case numbers and deaths in each region or country to extrapolate the true number of cases and death rates. The first seroprevalence study in China focused on healthcare workers and the people they may have exposed, such as hotel workers at hotels set up for healthcare workers. Among healthcare workers in Wuhan (the capital of Hubei province and site of the first outbreak), seroprevalence was found to be close to 4% and as low as 1% when considering the surrounding areas. The authors acknowledged the limitation of sampling and the fact that newly exposed individuals may not yet be seropositive.


The study in Spain used a sample population with the same distribution of ages, genders, and other factors as the Spanish population. It took place in late April, so we can work with ~236,000 known cases on April 20 and a little over 25,000 deaths two weeks later. We’re using the deaths from two weeks later to account for the time until people die after being infected. They found a seroprevalence of ~5%; this would correspond to ~2.5 million cases and a fatality rate of just over 1%. This was the first population-based study to try and understand how prevalent COVID-19 was and measure how many people had antibodies against the virus that causes it.


The most recent study samples patients in the US in July. This study was limited in that it used samples from dialysis patients, which has a very different distribution than the population as a whole. The study authors did attempt to normalize these values to the general population, but this is still limited because dialysis patients may not have the same behavioural patterns as other people. While this may add significant variability to the data overall, the impact to regional trends is likely negligible. They identified a nearly 10% seroprevalence, with significant regional variability of <4% in parts of the western US and close to 30% in some parts of the northeastern US. Given that this is from July, we know there were roughly 3.5 million confirmed cases and over 152,000 confirmed deaths in the US two weeks later. If 10% of the population has had COVID-19, that would be ~33 million people, meaning only 10% of all US cases were detected with a death rate just over 0.4%. A key difference here is that the US study also took place during a time of rapidly increasing case numbers, while cases in Spain were leveling out. As far as effects of sampling, dialysis patients are probably going to be more careful about being exposed, potentially reducing their infection rate; they are also probably at a higher risk of death from COVID-19 due to reduced kidney function, but may be at a lower risk of death since they are already undergoing regular medical care.

What do these studies tell us?

From these studies, it seems clear that most cases of COVID-19 are missed by testing, possibly up to 90% of them. This is unsurprising since testing was in its early stages in Spain and was simply never fully implemented in the US. It also puts the death rate, when case numbers are low enough to prevent hospitals from being overwhelmed, at closer to 0.5%.

This is simply what can be gleaned from the studies that have been performed. The scientific method forces us to consider the hypothesis (we can estimate how many people have been exposed to SARS-CoV-2), test the hypothesis (seroprevalence), interpret the results, draw conclusions, and communicate the findings.

Wishful thinking does not require such studies or interpretation of the data; we can pretend we’ve reached herd immunity or that the death rate is whatever we want it to be and everything is fine. The scientific method tells us that we should not make such assumptions when we have the ability to test a hypothesis. If the scientific method is being applied, then all of these steps are performed; with wishful thinking, we can just make an assumption and ignore the work being done to answer these questions.

Making something out of thin air is for trees at high altitudes.

If you use wishful thinking to claim far more people have been exposed that we have data for, you may be right, but you are also making a strong case against herd immunity. Seroprevalence only works if antibodies persist long enough. If the antibodies don’t persist long enough, then we need to be even more careful than the experts initially warned, because there are a lot of people that are at risk of getting this disease repeatedly.

Study on prevalence in China:

Study on prevalence in Spain:

Study on prevalence in USA:

Numbers of confirmed cases and deaths:

*”Eureka!” here is a reference to Archimedes** and not the state motto of California nor the amazing TV show of the same name.

**Archimedes here refers to the Greek polymath and not the owl (nor the dove) with the same name.

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COVID-19: what is known and what do you need to know?

There’s a lot of information out there and justifiable anxiety even when looking at the facts. So what is it that we know about this disease, what causes it, where it came from, what we need to be aware of, and what we can do about it?

What is COVID-19?

COVID-19 is the disease caused by a novel coronavirus, SARS-CoV-2. The name stands for sudden acute respiratory syndrome, coronavirus 2. The disease, COVID-19, signifies a coronavirus disease that emerged in 2019. You may see other names that were used before the official naming, but these are the names used by the WHO and published by the International Committee on Taxonomy of Viruses in this manuscript. If the name looks familiar, that may be due to SARS and MERS both being coronaviruses that emerged in 2003 and 2012.

Where did this come from and why?

SARS-CoV-2 is believed to have originated in pangolins or bats. Being of non-human animal origin, this was a zoonotic disease. Zoonotic diseases are not uncommon, and arise when a pathogen, such as a virus, that normally exists in an animal population is transmitted to a human. The bigger problem arises when the pathogen is transmissible between humans and goes from being a zoonotic disease to being human disease. Zoonotic diseases such as anthrax, rabies, lyme disease and mosquito-borne illnesses are all familiar to us, but cannot be transmitted between people. Diseases such as the H1N1 and H5N1 influenza strains and SARS and COVID-19 are zoonotic in origin, but then began spreading between humans.

What do I need to know about COVID-19?

The first thing to know is how to kill it or prevent its spread. For this, we need to understand how this type of virus works. SARS-CoV-2 is enveloped; this means it has a membrane envelope surrounding the viral capsid. The details of the viral capsid, internal proteins, and RNA genome aren’t important here, but it is important to understand testing. Here’s what makes the envelope so important; envelopes are easily destroyed with soap!

Time for a quick biochemistry lesson… Envelopes are the outer layer of some viruses and are made up of lipids. Specifically, these are phospholipids, like a cellular membrane, which has proteins sticking out of it that work like a key that matches locks (receptors) on your cells. Fats and oils are made of lipids. Phospholipids are a little more complicated because they are amphiphilic, meaning they have both a hydrophobic and hydrophilic portion. Luckily, dissolving them still goes through the same process. Add a detergent, time, and agitation, and viola! You’ve destroyed the membrane. Remember how the viral membrane contains the proteins (keys) that tell your cells to let the virus in? No viral membrane means no infection. You’ll still be able to detect parts of the virus, like the RNA, but it’s dead, aka, noninfectious.

What can we do about it?

We’ve already talked about why soap is so effective, but other cleaners (not antibiotics!) are also helpful. Bleach will also disrupt the membrane, which is why it makes your skin feel slippery. Alcohol will also destroy it if applied in a proper concentration, usually 60-70%; too much and you’ll preserve many pathogens instead of killing them or it’ll just evaporate before it can work. But killing the particles is what you do if they are present. Whenever possible, the better thing to do is to avoid coming in contact. This can be done through self-quarantine, social distancing, avoiding public spaces, practicing good hygiene, and doing your part to protect both yourself and everyone you cannot avoid interacting with.

Testing, method of infection, treatments are also very important, but we’re just scratching the surface of part one here.

Stay home, stay safe, and trust science.

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GMO products and GMO labeling have been at the forefront of many people’s news feeds over the last few years. Some people have strong opinions one way or the other, but many people are unaware of what these terms mean or what their implications are. We’re going to delve into a little bit about why you should care about GMO foods and why discussions regarding their labeling are so important.

First, we need to be clear on terminology. All domesticated animals and crops have gone through some form of human modification. Many of them have been inbred over centuries and preferred traits are selected for future breeding. Historically, this is how we increased crop yields, the sweetness of a fruit, or the amount of milk a cow would produce. Crossbreeding to select for preferred traits is largely considered safe and acceptable, since these traits naturally occurred in other varieties or species of the same crop.Growing heirloom fruits and vegetables is a way to focus on the older varieties before as much crossbreeding was done, but even these are inbred for domestication. Even companies like Monsanto have streamlined crossbreeding and screening to develop new crop varieties based on these widely accepted techniques. Although all of these agricultural items are developed through a form of genetic selection and engineering, crossbreeding not not results in considering a plant or animal as as GMO or genetically modified organism.

Newer technologies allow for the direct manipulation of genes. Instead of waiting to crossbreed an insect resistant strain of wheat with a drought resistant strain of wheat, the genes can be directly inserted into the gametes to produce the desired outcome without having to wait for several generations of crossbreeding. This form of manipulation also allows for the insertion of traits that may not exist in other closely related strains or species. Perhaps a population suffers from a vitamin A deficiency or someone wants to make pink or reddish rice; a gene could be inserted into a strain of rice so that it makes beta-carotene. While the reddish color would be a clear indication that something is different about this rice, many modifications are less obvious. Any manipulation of an organism by directly modifying the DNA results in a GMO.

Basically, all domesticated plants and animals have been genetically modified by humans, but only the modifications performed in a lab by directly adding, removing, or altering genes result in a GMO.

So what?

Any genetic modification, whether crossbreeding on a farm or DNA manipulation in a lab, has the potential to be good or bad. Allowing a sweet and hot pepper plant to grow near each other will lead to peppers that are no longer only sweet nor extremely hot. A hypoallergenic plant may be crossed with the traditional strain resulting in a plant that could send someone into anaphylactic shock. The introduction of a pesticide gene into a crop may decimate a local insect population that feeds on that plant; similarly, a pesticide resistance gene may result in the overuse of pesticides, leaving the plants unharmed, but ravaging the local environment. While positive change is always the goal, the ramifications are often not immediately clear. The fact that an organism has been modified, either on a farm or in a lab, is no indication of its potential benefit or harm to the environment, industry, or consumers.

Aren’t these unknowns reason enough to ensure proper labeling of GMOs?

“Proper” labeling is a tricky point. Since not all modifications are created equal, simply labeling “GMO” is akin to saying “this cow sat down during inclement weather”. Was this cow ill or did it just prefer to sit down from time to time? One answer means you should not be consuming any part of it while the other is completely innocuous. The only way to discern the value of a modification would be to know what was changed and how. Would it be best to require plan labeling with additional details via the company’s website? Perhaps this would easily allow consumers to know that something was changed and find out for themselves what it was. However, the push against all GMOs makes it clear that many consumers view GMOs are inherently bad. In this case, a plain “GMO” label serves to stigmatize a product containing an innocuous modification. This would be like requiring labeling a food because a family of whooping cranes lives on a lake at the farm. Some consumers would think it is wonderful that the farm is supporting whooping cranes, but it would also raise questions as to why they are required to disclose this information. Do the cranes contaminate the water on the farm? Is there some unknown risk of cranes near foodcrops? Simply forcing such a disclosure says nothing about what the statement means. Furthermore, there is already some disclosure of GMO products through the USDA’s organic labeling. According to the USDA, “[t]he use of genetic engineering, or genetically modified organisms (GMOs), is prohibited in organic products”; although a GMO does not need to be labeled, an organic label already denotes a non-GMO product.

This is the danger of forced GMO labeling. Without knowing what, why, or how of a modification, the only thing accomplished by such labeling is applying a stigma. If the purpose of forced labeling is disclosure, then we should advocate for disclose. State what has been altered in any modified organism, e.g., “this soy has been bred to resist drought”, “neonicotinoid resistance has been inserted into this strawberry”, or “these apples lack the gene for browning.”

Let’s accept that large corporations on both sides of this issue are pouring money into the fight and focus on the science and what this means for the rest of us as consumers. Too often these discussions devolve into accusations that someone is being paid by one side or the other instead of focusing on the issues at hand and the vast majority of us who have nothing to gain but everything to lose if we fail to engage in useful discussions of this topic. The majority of people who care about these topics are not connected to any of the big agricultural corporations on either side (do you really think they are paying tens of thousands of people just to rant on Facebook?). It’s okay to be frightened when you don’t know what the impact of something is, but it is not ok to lash out at people because you don’t want to know. As Neil deGrasse Tyson said, “[t]he good thing about science is that it’s true whether or not you believe in it”.

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Communicating Science: Part 2

This is the continuation of talks on communicating science and confronting pseudoscience  at IFT16, a massive conference of food scientists. Part 1 can be found here.

We continue with a short summary of Ben Goldcare’s talk, “Telling the Story of Science in an Age of Misunderstanding”

Next up was Ben Goldcare of the University of Oxford’s Center for Evidence-Based Medicine. His background is as a physician, epidemiologist, and science writer. His talk went more toward proper communication of science. He used to write a weekly column, Bad Science, which ran for nearly a decade in The Guardian.

He presented several examples of misleading representations of data, ranging from inverted y-axes, uniquely scaled y-axes, and various graphs where the diagrams were not proportional to the values. (Stocks are almost always shown with a cropped y-axis so that even the smallest variations are visible on a graph.)

He goes on to point out that the Daily Mail (a British newspaper) has run headlines on almost everything both preventing and causing cancer. You can find references on the internet of many foods and ingredients both causing and preventing cancer. Since consumers cannot be expected to decipher all of these sources, some level of responsibility must be placed on the journalists. However, very few journalists are scientists, so they determine the impact of something by the press release. When press releases contain inaccuracies and exaggerations, the 58-86% of the news articles also contained exaggerate claims. For press releases that did not contain exaggerations, only 10-17% of the related news articles created such claims.

Goldcare also spoke about pulses. This was mostly interesting due to the way he said the word “pulses” and educated the audience about pulses, the dried seeds of legumes.

He also discussed the issue of multiple studies on the same topic with disparate results. With the amount and accessibility of data, the ability now exists to perform systematic reviews where data is weighted and considered as a whole. This sounded similar, and less complicated, than the way that FiveThirtyEight weighs polling data in building a model for election predictions in the USA. Skip down to around the 18th paragraph and Nate Silver starts talking about weighting polling averages ( He did get into some details of funnel plots in systematic reviews; suffice it to say, there are statistical analyses to help determine the validity of systematic reviews.

The last point we’ll make from Golcare’s talk is to direct you to a study on medical advice from doctors with daytime TV shows. (Spoiler alert: most of the advice is not good)

“Taming Dragons in the Age of Pseudoscience”

The last speaker on this topic was Bev Postma of Food Industry Asia. She had the honor of being front and center in Brussels when the European Commission was analyzing the previous 15 years of GMO use. For those unaware, GMOs have been used for over 30 years.

Despite 15 years of successful and safe GMO use in Europe, discussion turned negative as people were swept up in fear and confusion. The pseudoscientists and celebrities were referred to as dragons, mythical creatures striking fear into the populace. The inability of the scientific community to respond was a wake-up call to be effective communicators and always be accurate and consistent if there is any hope of a unified voice of science against an onslaught of fear and misunderstanding.


We leave you with a lovely Marie Curie quote used in Postma’s presentation:

Nothing in life is to be feared, it is only to be understood. Now is the time to understand more, so that we may fear less.

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Communicating Science: Part 1

This site was created to be good citizens of the scientific community and to help communicate scientific knowledge and understanding to our family, friends, and anyone else who wanted to listen. I recently attended the Institute of Food Technologists conference (with over 24,000 other people!) and was impressed by how prominent they made the topic of identifying and communicating accurate science. The largest conference room had three entire seminars on the topic; the topic was pervasive enough that it managed to surface in some of the scientific sessions as well. As this topic becomes a larger and more prominent discussion among scientists, expect to see more voices explaining similar concepts with similar messages. Scientists tend to have a hard time connecting with normal people; the scientific community is still figuring out how to talk to people like real people and how to navigate social media. The prevailing theme seemed to be that knowledge and information that has been properly vetted needs to be communicated accurately and consistently, especially when confronted with inaccuracies and emotion.

These two posts (it’s a lot for a single post) will be a little bit different than our others in that they will mostly be summaries of concepts conveyed during these talks and less original material with references. References for specific points will still be necessary but, unless the presentations are made public by the speakers or the conference, we won’t be able to share the slides in their entirety. The three sessions devoted to this topic were by Jacques Rousseau, Ben Goldcare, and Bev Postma. We’ll give the titles of each of their talks when we get there, but our take on the topics come down to the philosophy of knowledge, the dissemination and analysis of science, and the impact of pseudoscience.

We’ll lead off with Jacques Rousseau’s talk: “Science Versus Sensationalism and Soundbites: How Can Consumers Make More Informed Choices?”

Jacques Rousseau is the founder of the Free Society Institute which is a non-profit out of South Africa promoting, among other things, scientific reasoning. He is very direct and does not mince words when it comes to established science.

He points out that knowledge is not a democratic process. There is no popular vote on what is fact. It is decided by experts in a field who painstakingly gather data and share it with other experts in the same field until there is a consensus on what is known.

This leads into another point, reasserting the primacy of subject experts. It may seem obvious that the subject experts determine what we know about a subject, but their expertise is being undermined by outsiders without sufficient background to analyze data within the field.

Given that this was a conference of food scientists, the topic of genetic modifications and GMOs came up. Rousseau pointed out the wide discrepancy between the public and scientists on the relative safety of consuming genetically modified foods. This survey is not limited to food scientists and is based on the American Association for the Advancement of Science (AAAS) members covering a range of scientific disciplines. The vast majority (88%) of scientists said that GM foods were safe to eat, while only 37% of the general population agreed with that statement. The survey can be found here with a more detailed description including how they defined “scientists” here.

How do we address the lack of faith in experts as people place their faith in outside advocates for a cause? How did interpretation and determination of knowledge become a cause in the first place?

One of the most apropos lessons from Rousseau was his discussion of rules of argument put forth by game theorist Anatol Rapaport and summarized by Daniel Dennett.

We’ve noticed the conversations are much more fruitful when loosely following these rules; you may see some similarities in how we approached vaccines. There is no discussion if one party begins on the defensive and closed off to outside views.

How to compose a successful critical commentary:

1. Attempt to re-express your target’s position so clearly, vividly and fairly that your target says: “Thanks, I wish I’d thought of putting it that way.”

2. List any points of agreement (especially if they are not matters of general or widespread agreement).

3. Mention anything you have learned from your target.

4. Only then are you permitted to say so much as a word of rebuttal or criticism.

Roughly, you attempt to express your opponent’s viewpoint, identify common ground, express something new that you have learned from your opponent, then, and only then, you begin to introduce counterpoints or criticism. We were particularly intrigued by this formula and hope to refine our own discussions based on it.

If anyone has experience with engaging opposing viewpoints and stimulating discussion, please share. This is an ongoing process and, just like science, it can always be critiqued and improved upon.


To be continued here.

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So you think you can pH

Cells contain small membrane-bound compartments called vesicles. These vesicles can be so small that you can’t even see them in your typical light microscope. They are used for all sorts of things, from transporting compounds around the cell to deconstructing compounds or digesting bacteria. Some of these digesting vesicles, called lysosomes, use acid (low pH) and enzymes to tear apart molecules or entire bacteria. Since acidity is expressed in pH, a measure of how many hydrogen ions (H+ or protons) are floating around in solution, I started thinking…

Molecules are usually talked about in numbers too large to count — millions, quadrillions, or 1023 — but this is a small space, a really small space. In a space so incredibly small, how few free protons are there? (I can submit my own questions, right?)

In case you can’t tell from the question, this is going to get into some technical details pretty quickly, so if you have an aversion to mathematics, you may want to skip to the summary.

The vesicles in a cell can be as small as 20 nm across, which would have a volume of roughly 4.189×10-21 L ((4/3)πr3). At pH 5, the proton concentration is 10 mM or 10-5 M (pH=-log([H+])). This would mean that a 20 nm vesicle with a pH of 5 contains approximately 4.2×10-26 mol of H+ or 0.026 free protons per vesicle (6.022×1023 molecules/mol). Since you can’t have a fraction of a subatomic particle (yes, a proton can be divided into its three quarks, but they aren’t ever observed alone anyway), there must be something more to this simple definition of pH.

A common mistake is to forget that altering the proton concentration by a small amount (<10-7 M) does not contribute significantly to the proton concentration of water at neutral pH (pH 7). Although we’re talking about very small numbers of protons in these vesicles, the concentration is still well above that cutoff at 10-5 M. The other point to consider is that pH is a balance between the forces of acids and bases. Lowering the amount of basic ions (which is how a Lewis acid functions) relative to acidic ions would also make a solution more acidic. At pH 5, there should be 10000× more H+ than OH (water’s basic half). If the concentration of OH could be raised to 10-3 M (~2 molecules/vesicle), then H+ would have to be 10 M (~20000/vesicle) to obtain the desired pH. At least now we would be talking about whole molecules, this would also require lowering the concentration of H2O relative to H+ and OH can be lowered. This is where the dissociation constant of water becomes an issue. The typical concentration of dissociated water molecules is 10-14 M, but if the environment was under such tight constraints that the normal equilibrium of H+ + OH ⇌ HOH was shifted to the left, then the previously described hypothesis may hold true. The dissociation constant of water is affected by temperature, but such dramatic alterations of the dissociative properties of water in a controlled microenvironment is quickly escaping out capacity, so we’re hopeful for a simpler solution.

Stepping back for a moment, even with the tiny size of a vesicle, there are even smaller spaces in which we assume there is a maintained pH. Within and around proteins, there are microenvironments containing only a handful (if you had very small hands) of atoms and molecules. How can you claim such a small space has any particular pH when only five molecules are present?!


If the amino acid residues of a protein are sufficient to maintain a pH of 5, then surely a 20nm wide vesicle can maintain a pH of 5 without the need of impossibly small numbers of free protons. Much more likely is that pH really has nothing to do with the actual number of acid or alkaline ions at a given time; instead these numbers represent averages. If you spend an hour a day in your car, on average, your car would contain 0.04 people. This would not sound right, and you’re more likely to say that, 1/24 of the time, there is a person in your car. A molecule is considered more acidic if it has a proton that spends more time away from the molecule as it spends bound to it. Now let’s pretend that you are that proton and your car is a side-chain on a protein where the proton spends a small portion of its time. To get .026 free protons, the proton could be bound 97.4% of the time and free the other 2.6%.

Sometimes things in science seem confusing or impossible simply because science is not described in the same way that we speak and communicate. Even when the answer seems hard to find, translating science into terms we can all understand makes some things so much simpler.

Note: The back-of-the-envelope calculations were verified using Wolfram|Alpha, although I welcome any corrections.

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Citizens Hip in Science!

Today we give thanks to those citizens of the world who we consider to be hip in science.

Citizens Hip in Science

They’re with it. They’re hip.

Science wasn’t always hip. Science history is riddled with boring experiments ranging from watching planets and stars meander around the universe to bird watching while drifting around on the ocean with a beagle. However, our generation grew up watching Huey Lewis on the News talking about how it was hip to be square — the irony of being both interesting and bland at the same time. How could it be done? Scientists, in their white lab coats and monotone labs… what could be more square? How could they be hip?

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How I learned to stop worrying and love my bacteria (Part 2: The bad and the ugly)

In part one, we talked about the benefits of bacteria we live with every day. As you are likely aware, not all bacteria are friendly. In fact, there are plenty of bacteria that we never want to encounter. Nonpathogenic bacteria are the ones that are either necessary for survival, or simply not harmful; however, pathogenic bacteria are the ones that cause infections and disease. These are the ones we hear about when there is contamination of our food supply, a drug-resistant outbreak at a hospital, or when you get food poisoning. One of the most dangerous bacteria doesn’t even have to infect us at all. The toxins produced by Clostridium botulinum and its brethren are some of the most potent toxins known. Food contamination by these bacteria is sometimes noticed as those telltale bulges in canned food gone bad.

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