School’s out, and I discovered a new website, TheTorah.com, which appears to be a project of a group of Modern Orthodox Jews to promulgate their acceptance of higher criticism (also called historical criticism). In other words, these are scholars who practice Orthodox Judaism but are not Biblical literalists. Their website proclaims a need for a “historical and contextual approach” to Torah study. Amen, and good luck to them!
Most of the articles on the Website are of no particular interest to me, but two caught my eye. Under “Biblical Scholarship 101,” an article on Noah’s flood shows in considerable detail how the story is composed of two interwoven and sometimes contradictory tales. The argument is used to support what is often known as the Documentary Hypothesis. It is hard to see how anyone could argue that both tales are literally true, and indeed I once used a shorter version of the same argument on Panda’s Thumb. I consider the Documentary Hypothesis to be so convincing that it is frankly a fact that the Bible is composed of four or more threads. Which leads me to the second article that caught my eye, below the figurative fold.
The majority of U.S. medical schools do not require evolutionary biology as a prerequisite for acceptance and do not offer courses dedicated to the subject. But as we talked about last time, adopting an evolutionary perspective on medical issues can potentially give new insights into disease treatment, prevention, and diagnosis. Where do we and should we begin to teach this kind of thinking? What resources are available to teachers and students to learn about evolution and its application to modern day problems?
Evolutionary training can help doctors look at diseases in a different light (Nesse et al, 2006). Take, for instance, sickle cell anemia: carriers of the sickle cell trait, a disease which is highly prevalent in tropical regions, are resistant to malaria, likely as a result of natural selection. This knowledge is helpful in developing ways to prevent malaria and perhaps similar evolutionary links between other diseases or infections and protective traits exist, but examining this hypothesis requires a thorough understanding of evolution and population genetics. Based on examples like this proponents of evolutionary medicine believe evolutionary biology should be considered a core subject for medical students, side by side with anatomy, physiology, biochemistry, and embryology, and that medical license exams should include questions about evolutionary biology.
People with sickle-cell anemia, whose bodies produce abnormal, crescent-shaped red blood cells, also carry genes that protect against malaria. This is most likely the reason sickle cell anemia is so common in areas where malaria is highly prevalent.
Image source: National Health Service
But while most medical schools do not offer much in the way of evolutionary education, there are some resources available for K-12 students and teachers as well as college undergraduates and graduates. One example is the BEACON Center for the Study of Evolution in Action at Michigan State, an interdisciplinary research team working on applying evolutionary principles to a wide range of problems in fields such as medicine, computer science, ecology, and engineering. Along with research, BEACON is focused on evolution outreach and education: researchers are conducting studies to see if integrating undergraduate cellular and molecular biology courses with evolution improves evolutionary understanding. The center also organizes K-12 summer programs, activities for K-12 teachers, and undergraduate and graduate-level courses.
While BEACON is enjoying great success, the NESCent (National Evolutionary Synthesis) Center, a center in North Carolina promoting multidisciplinary evolutionary research, will be closing this year after a decade of operation. Like BEACON, NEScent was also active in public outreach and education, organizing events like Darwin Day for K-12 students and training workshops for graduate students and teachers. But a new center is opening in the wake of NESCent: the Triangle Center for Evolutionary Medicine (TriCEM), which will focus on the partnership of evolutionary biology with human and veterinary medicine.
We’ve made the case for why an evolutionary understanding can improve research in medicine. But if we want to shift the paradigm of medical thought to one that emphasizes evolutionary biology, we need to reevaluate how we teach evolution from the earliest levels of education through medical school.
This series is supported by NSF Grant #DBI-1356548 to RA Cartwright.
From David Young on Facebook:
Number nerd warning: Today at 8:25.5 pm (local time) it will be 5 / 10 / 15 20 : 25 : 30.
“Measles vaccine protects against other deadly diseases,” proclaims an article in ScienceInsider. In reality, the protection is indirect: Getting measles disposes you to getting other potentially fatal diseases over the next several years. Evidently, measles, unlike, for example, whooping cough, not only weakens your immune system but also makes it “forget,” so you may even contract a disease that you already had and thought you were immune to. (As an aside, though it was supposedly impossible, I contracted mumps twice, as diagnosed both times by a physician. I now wonder whether I had contracted measles between the two cases of mumps.)
As described in the ScienceInsider article, Michael Mina and colleagues at the Emory University School of Medicine demonstrated a correlation between a child’s getting measles and subsequently dying of other diseases. Specifically, they showed that children who survive measles are especially vulnerable to contracting a fatal illness for an average of approximately 2.5 years after the measles infection. The result held true both before and after the widespread use of the measles vaccine. The researchers found no such vulnerability among children who had contracted whooping cough, so the result is apparently specific to measles.
Vaccination had practically eliminated measles from the United States by 2000. Since 2013 or so, we have experienced hundreds of cases, largely if not entirely due to the anti-vaccination movement (see, for example, MMR vaccine controversy, which details the fraudulent but influential paper by Andrew Wakefield). Little did we know that the anti-vaxxers have put children in danger of contracting not only measles (a serious disease on its own, incidentally), but also other serious and potentially fatal diseases as well.
We are aware of the issue with Google comment logins and are working on a fix.
It is going to take us a while to implement one due to various personal and software reasons.
NCSE tells us,
April 18-25, 2015, is the inaugural Climate Education Week, sponsored by Earth Day Network. To celebrate, the Climate Education Week website is providing K-12 educators with the Climate Education Toolkit – “a free, easy-to-use, ready-to-go resource with everything you need. The Toolkit includes a week’s worth of lesson plans, activities, and contests for K-12 students that meet Next Generation Science Standards and Common Core. Each day covers a different theme related to climate change with two highlighted activities handpicked by Earth Day Network for your use.” There are videos, contests, a downloadable Earth Day poster, and even an interactive on-line textbook for middle school students – all aimed at helping to promote climate education!
You may find NCSE’s resources on climate science and climate education on their Website.
What do Charles Darwin, wisdom teeth, and cancer have in common? They are all related to an emerging field called evolutionary medicine, the application of evolutionary principles to understanding why and how organisms get sick. Scientists in the field believe that an evolutionary perspective can help improve our diagnosis and treatment of disease.
In his keynote address at the inaugural meeting of the International Society for Evolution, Medicine, and Public Health (held March 19-21 in Tempe, AZ), Dr. Harvey Fineberg stated that an understanding of evolution is central to health. Fineberg, the former Dean of the Harvard School of Public Health, argued that an evolutionary viewpoint is necessary to explain structures and functions of the human body (like the fact that wisdom teeth were helpful in some way to our ancestors but serve no purpose now) and evolution can provide insight into diseases that develop and spread under evolutionary mechanisms, like infectious disease and cancer.
Antimicrobial resistance occurs when bacteria, viruses, and other infection-causing microorganisms evolve and develop mutations that enable them to resist drug therapies. Drug-resistant bacteria alone affect over two million Americans each year, according to the CDC. The process of microbial evolution follows the guiding principles of natural selection, so scientists can use their knowledge of evolution to understand how microbes attain resistance and perhaps even prevent it. For example, the current methods of treating bacterial infections target a mechanism of mutation called de novo mutation, but scientists have learned that antibiotic resistance mostly develops from a different method called horizontal gene transfer (Sterns, 2012), which suggests that we may need new therapies for bacterial infection.
Bacteria, like the mycobacteria above that cause tuberculosis, develop drug resistances by evolving and mutating under the influence of natural selection, just like all other organisms. Image source: CDC
Evolutionary medicine has also started to play a role in cancer research. Some scientists are using an evolutionary background to understand how cancers develop, spread, and metastasize as well as to find effective treatments. For instance, a group of scientists is trying to understand how large animals with long lifespans, like the blue whale, have evolved and developed cancer suppression techniques that are reportedly 1000 times better than those of humans. Many hypotheses attempting to explain this phenomenon exist: the lower metabolic rate of large animals might lead to a lower mutation rate, or perhaps tumors are so much bigger in large animals that they are actually less likely to become malignant than smaller tumors (Nagy et. al., 2007). Whatever the explanation, understanding why and how large animals evolved to gain such effective tumor suppressor mechanisms could provide new therapies for cancer in humans. (Caulin and Maley, 2012.)
Additionally, studying deviations from physiological homeostasis in an evolutionary light may suggest that we need to make changes in how we treat some conditions. As Dr. Joe Alcock of the University of New Mexico commented at the ISEMPH meeting, what is defined as “normal” for the human body may be different depending on the conditions. For instance, doctors typically test patients for normal levels of hemoglobin (the molecule that transports oxygen in the blood) and glucose. But evolution has led some populations to adapt to unique environments and develop abnormal levels of these molecules; those living at higher altitudes are found to have a higher base level of hemoglobin than normal, pregnant women exhibit lower concentrations of hemoglobin as an adaptation to pregnancy, and patients with sepsis, a severe complication of infection, have elevated glucose levels, which may be an adaptive survival response. When doctors detect these abnormal glucose and hemoglobin levels, they will often treat the patients to return them to normal; however, Alcock argues that trying to restore every patient to one standard level may in fact do more harm than good if deviation from normalcy has an adaptive purpose.
The growth in the field of evolutionary biology, along with the sharp decline in genome-sequencing costs, has led to a new discipline of treating and diagnosing diseases called phylomedicine (Kumar et. al., 2011). Studying the differences between genomic information of healthy and diseased people, scientists have discovered many genetic diseases and the DNA variations associated with them. For example, mutations in the ALDH1L1 gene are associated with an increased risk of stroke (Williams et. al., 2014). However, simply analyzing individual genomes to discover the variations linked with certain diseases is inefficient and produces an extremely high volume of data, not all of which are significant. Instead, scientists can combine this analysis with a multi-species evolutionary perspective to narrow down the list and determine which genetic markers are associated with disease. Once these markers, like the ALDH1L1 gene, are identified, we can use them for diagnosis and as potential therapeutic targets.
Evolutionary principles can give insight into a wide range of medical topics: besides cancer and infectious disease, evolutionary thinking has shed light on other diseases like jaundice, influenza, and mental disorders (Nesse and Stearns, 2008). Also, studying the timeline of animal evolution and trait development can tell us which animals are most accurate models of human physiology for drug and device preclinical testing.
Members of the discipline see evolutionary medicine as having the potential to revolutionize the way we think about medicine. Adopting a new, evolutionary viewpoint on some of our most complex diseases could greatly benefit patients.
In our next post, we’ll go into more detail about a specific clinical application of evolutionary medicine. Is there a topic you’d like to hear more about? Let us know in the comments section.
This series is supported by NSF Grant #DBI-1356548 to RA Cartwright.
Eudyptula Minor – little penguin, Kangaroo Island, Australia. These penguins are nocturnal, but are apparently blind to the red light. Unfortunately, according to Kangaroo Island Penguin Center, “Our nocturnal Penguin Tours ceased in November 2013 due to the very low numbers of Penguins in the Kingscote colony. Predation by the increasing numbers of New Zealand Fur Seals from 2010 onwards has decimated the Penguin Colony, because the seals kill the adult penguins as they swim ashore at night to feed their chicks and therefore the chicks also die. We apologise for this, but the situation has been beyond our control.”
This post is by Joe Felsenstein and Tom English
Back in October, one of us (JF) commented at Panda’s Thumb on William Dembski’s seminar presentation at the University of Chicago, Conservation of Information in Evolutionary Search. In his reply at the Discovery Institute’s Evolution News and Views blog, Dembski pointed out that he had referred to three of his own papers, and that Joe had mentioned only two. He generously characterized Joe’s post as an “argument by misdirection”, the sort of thing magicians do when they are deliberately trying to fool you. (Thanks, how kind).
Dembski is right that Joe did not cite his most recent paper, and that he should have. The paper, “A General Theory of Information Cost Incurred by Successful Search”, by Dembski, Winston Ewert, and Robert J. Marks II (henceforth DEM), defines search differently than do the other papers. However, it does not jibe with the “Seven Components of Search” slide of the presentation (details here). One of us (TE) asked Dembski for technical clarification. He responded only that he simplified for the talk, and stands by the approach of DEM.
Whatever our skills at prestidigitation, we will not try to untangle the differences between the talk and the DEM paper. Rather than guess how Dembski simplified, we will regard the DEM paper as his authoritative source. Studying that paper, we found that:
They address “search” in a space of points. To make this less abstract, and to have an example for discussing evolution, we assume a space of possible genotypes. For example, we may have a stretch of 1000 bases of DNA in a haploid organism, so that the points in the space are all 41000 possible sequences.
A “search” generates a sequence of genotypes, and then chooses one of them as the final result. The process is random to some degree, so each genotype has a probability of being the outcome. DEM ultimately describe the search in terms of its results, as a probability distribution on the space of genotypes.
A set of genotypes is designated the “target”. A “search” is said to succeed when its outcome is in the target. Because the outcome is random, the search has some probability of success.
DEM assume that there is a baseline “search” that does not favor any particular “target”. For our space of genotypes, the baseline search generates all outcomes with equal probability. DEM in fact note that on average over all possible searches, the probability of success is the same as if we simply drew randomly (uniformly) from the space of genotypes.
They calculate the “active information” of a “search” by taking the ratio of its probability of success to that of the baseline search, and then taking the logarithm of the ratio. The logarithm is not essential to their argument.
Contrary to what Joe said in his previous post, DEM do not explicitly consider all possible fitness surfaces. He was certainly wrong about that. But as we will show, the situation is even worse than he thought. There are “searches” that go downhill on the fitness surface, ones that go sideways, and ones that pay no attention at all to fitnesses.
If we make a simplified model of a “greedy” uphill-climbing algorithm that looks at the neighboring genotypes in the space, and which prefers to move to a nearby genotype if that genotype has higher fitness than the current one, its search will do a lot better than the baseline search, and thus a lot better than the average over all possible searches. Such processes will be in an extremely small fraction of all of DEM’s possible searches, the small fraction that does a lot better than picking a genotype at random.
So just by having genotypes that have different fitnesses, evolutionary processes will do considerably better than random choice, and will be considered by DEM to use substantial values of Active Information. That is simply a result of having fitnesses, and does not require that a Designer choose the fitness surface. This shows that even a search which is evolution on a white-noise fitness surface is very special by DEM’s standards.
Searches that are like real evolutionary processes do have fitness surfaces. Furthermore, these fitness surfaces are smoother than white-noise surfaces “because physics”. That too increases the probability of success, and by a large amount.
Arguing whether a Designer has acted by setting up the laws of physics themselves is an argument one should have with cosmologists, not with biologists. Evolutionary biologists are concerned with how an evolving system will behave in our present universe, with the laws of physics that we have now. These predispose to fitness surfaces substantially smoother than white-noise surfaces.
Although moving uphill on a fitness surface is helpful to the organism, evolution is not actually a search for a particular small set of target genotypes; it is not only successful when it finds the absolutely most-fit genotypes in the space. We almost certainly do not reach optimal genotypes or phenotypes, and that’s OK. Evolution may not have made us optimal, but it has at least made us fit enough to survive and flourish, and smart enough to be capable of evaluating DEM’s arguments, and seeing that they do not make a case that evolution is a search actively chosen by a Designer.
This is the essence of our argument. It is a lot to consider, so let’s explain this in more detail below:
As usual I will pa-troll the comments, and send off-topic stuff by our usual trolls and replies to their off-topic stuff to the Bathroom Wall
Tom Loftus reports in the Louisville Courier-Journal that Gov. Steve Beshear has asked a federal court to dismiss the Ark Park’s lawsuit on the grounds that “[p]roviding the public funding sought for religious purposes …would constitute an unlawful establishment of religion” and thereby violate both the state and federal constitutions. Governor Beshear and his co-plaintiff, state Treasurer Bob Stewart, told the Courier-Journal that “the state’s denial of public funds for the ark park [sic] ‘reflects no hostility toward Plaintiffs’ faith’ and does not prohibit Answers in Genesis and its affiliated organizations from following their religious beliefs.”
Update, March 31, 2015: Americans United for the Separation of Church and State has submitted a motion to intervene on behalf of four Kentucky taxpayers to “prevent taxpayer dollars from being used to unconstitutionally finance a religious ministry.” According to a press release, the taxpayers argue “that ‘[t]he tax rebates sought for Ark Encounter would effectively compel me, as a Kentucky taxpayer, to subsidize a religious ministry against my will.’” Two of the taxpayers are Christian ministers. AU has also submitted a proposed motion to dismiss, which I take it becomes active if the motion to intervene is granted.
A pair of recent articles on the Science website seems to think so. Staff writer Robert Service says Researchers may have solved origin-of-life conundrum and writes,
Chemists report today that a pair of simple compounds [HCN and H2S], which would have been abundant on early Earth, can give rise to a network of simple reactions that produce the three major classes of biomolecules—nucleic acids, amino acids, and lipids—needed for the earliest form of life to get its start. Although the new work does not prove that this is how life started, it may eventually help explain one of the deepest mysteries in modern science.
The title is certainly misleading, since the origin of life puzzle is still very far from “cracked.” Showing that biomolecules, even complex biomolecules, can be synthesized under plausible primordial conditions is very different from showing how those molecules could have assembled to produce the first cell. Only then can one claim to have cracked the puzzle.
That seems to me to be essentially correct, but then the author, Walter Steiner, adds, somewhat mysteriously, “Solving that puzzle will require the discovery of some currently unknown natural phenomenon.” Another commenter suggests some kind of broken symmetry.
The creationists, intelligent-design and otherwise, have moved in on the “conundrum” article, which is now about 1 week old and boasts almost 1000 comments, some of which actually make sense.
Today is Pi Day, and the time will be exactly pi at 3/14/15 9:26:53, or a little thereafter. We will not see another Pi Day till 2115, but I am sure that someone next year will point out that pi = 3.1416 within a thousandth of 1 percent or so. Won’t be the same, though!
Remember the two studies published at the end of last year that produced groundbreaking evolutionary trees of birds and insects? The researchers in these studies used data from whole sequenced genomes to construct these more reliable trees. This is a practice that is somewhat novel but gaining importance in phylogenomics. But we’ve talked about how large data sets, like genomes, can lead to incorrect conclusions if analyzed improperly. How did the researchers avoid this problem?
In the last post, we discussed the two major methods of improving genomic analysis. First, scientists can determine the informative subset of a genome and only obtain and analyze that set. Alternatively, they can develop algorithms to compare whole genomes to a well-established reference genome. But these methods have their drawbacks; subsets of genomes often are not reusable in other experiments and reference genomes, if unavailable, can take a lot of time and work to develop.
Genomes can consist of several billions of nucleotides, so we need different methods of analyzing such a large dataset.
Image source: Boise State University
That’s why our lab is developing SISRS (pronounced “scissors,” Site Identification from Short Read Sequences), a new software program that can analyze genomic data in a matter of days. This NSF- and ASU-funded software eliminates the need for a reference genome and does not require genetic markers, which can take months to determine. Thus, SISRS greatly reduces the time, effort, and cost required to construct a phylogenetic tree from genomic data.
So how does SISRS achieve all of this? From data sequenced via next-generation sequencing, SISRS randomly constructs a subset of data using reservoir sampling. The software then uses de novo assemblers (for example, a program called Velvet) to construct a composite genome from this subset to act as a reference. Because sequences shared among species occur frequently in the collected data, they are more likely to be chosen during the random sampling process than sequences unique to one species. Thus, the composite genome contains genetic information from each species and is a suitable reference genome.
Once the composite reference genome is assembled, SISRS aligns the raw data to the reference. Some species may be missing data in sites, which could be due to several reasons: a gene may not be present in all genomes, there could be variable regions of the genome to which the reference does not align well, or there could have been error in the genome sequencing process. SISRS removes these sites that are missing too much information and filters out other sites that may produce errors (like sites with paralogous, or duplicate, genes). Finally, SISRS outputs the phylogenetically informative sites for phylogeny construction.
To verify SISRS’ effectiveness, our team tested it with the genomic data of primates, whose phylogenetic tree is well-established. SISRS reconstructed the tree with 100% accuracy. Along with genomes, SISRS worked with transcriptomes (the complete set of RNA), estimated the mammal phylogeny very well, and showed promising preliminary results of estimating species divergence times.
SISRS is still under development, and future improvements will enable the program to analyze larger data sets more rapidly. SISRS makes it possible to analyze genomic data quickly, efficiently, and accurately with minimal work. As we continue to improve the software, we welcome feedback from anyone working in the field of phylogenetics; SISRS is available open-source here. We expect this software will have a major impact on phylogenetic analysis.
For more detail about SISRS, click here.
This series is supported by NSF Grant #DBI-1356548 to RA Cartwright.
That is one of the disquieting results of a new survey, Enablers of doubt, by Michael Berkman and Eric Plutzer. The two Penn State professors interviewed a total of 35 students on 4 Pennsylvania campuses in 2013. All the students were training to be biology teachers; many were not comfortable with the theory of evolution, and many were “concerned about their ability to navigate controversy initiated by a student, parent, administrator, or other members of the community.” Indeed, instead of relying on their knowledge of biology, they intended to fall back on classroom-management techniques to deal with creationist students. Notably, these were not education students, but rather biology students who “take a set of required courses in educational psychology, classroom management, and methods of instruction.” Their lack of expertise in science seems not to concern them; to the contrary, they thought they would use their skills at avoiding controversy to avoid any controversies.
PT readers may remember Professors Berkman and Plutzer for their book, Evolution, Creationism, and the Battle to Control America’s Classrooms, which we reviewed here a few years ago. The disquieting conclusion of that book was that only about 28 % of biology teachers actually teach evolution according to recognized standards. The present study may help explain why.
The students, who attended a large research university, an institution that granted degrees at the master’s level, a Catholic college, or a historically Black university (all unnamed), were interviewed in focus groups. The interviews lasted 50-65 min and were conducted by the authors. The focus groups do not provide a statistical sample, but the authors attempted to include several different kinds of educational institution, and they consider the findings “suggestive.” Below the fold, some representative comments.