It’s widely understood that human genetics can influence culture, but increasingly, the idea that culture can also affect genetics is gaining ground. The theory of gene-culture coevolution suggests that “the cultural practices we adopt change the costs and benefits of having certain genes,” explains Catharine Cross, a researcher at the University of St Andrews. “A gene that is advantageous under one cultural practice is not necessarily advantageous under another.”
For example, yam cultivation in West Africa led to deforestation and an increase in standing water, which creates a breeding ground for mosquitoes and malaria. This meant that yam farmers with a particular genetic resistance to malaria were more likely to survive than farmers with susceptibility to malaria. Yam farmers in the region have been found to have a higher incidence of this genetic trait than nearby groups—even speakers of the same language—who farm other crops.
A recent study published in Nature Communications has suggested that stone tool-making practices among the ancestors of modern humans may have put evolutionary pressure on individuals who weren’t very good at communicating, helping to select for the genes that would become involved in language. The study found that the use of verbal teaching, compared to learning by imitation, significantly improved the quality and speed production of stone tools. This suggests that individuals with gestural or verbal communication skills could have learned to make tools faster and better, giving them an advantage over individuals who could only imitate.
It has been a bit of a head scratcher. Records of sea level during the last few million years tell us that there have been some warm periods where sea level may have been as much as 20 meters higher than it is today. When fed the conditions that prevailed at the time, however, our computer models of ice sheets haven’t been able to reproduce such a swelling of the ocean.
The models can simulate that much sea level rise, but it requires temperatures much higher than were seen during those warm periods. Realistic losses of ice from Greenland and the fragile, western part of Antarctica (the West Antarctic Ice Sheet) could only provide something in the neighborhood of 3 to 10 meters of sea level rise. That leaves 10 to 17 meters for the East Antarctic Ice Sheet—the largest and most stable ice sheet—to chip in. Convincing the miserly East Antarctic Ice Sheet to be that generous with its contents isn’t easy, which is why the models required such high temperatures.Updating the models
So what are the models missing? Penn State’s David Pollard and Richard Alley, and University of Massachussetts, Amherst’s Robert DeConto had an idea for something to try. Two things to try, really. They added a pair of physical processes to an ice sheet model that weren’t simulated previously. The first was hydrofracturing. When water reaches the ice sheet from rain or ice melt at the surface, it fills crevasses in the ice.
The New York Times Magazine recently ran a cover article about mapping the connectome, all of the connections that link all of the neurons in someone's brain. Many of these connections are formed and reinforced as a result of our experiences, and their sum total constitutes everything about our personalities: the memories we've formed, the skills we've learned, the passions that drive us.
There is even data suggesting that some neurological disorders are in fact "connectopathies," characterized by either aberrant connections or an unusual extent of connections among neurons. Some studies have found that autism spectrum disorder (ASD) is associated with decreased functional connectivity in the brain, but other experiments have found increased connectivity in autistic brains. A new study may have reconciled these contradictory findings. Researchers at the Weizmann Institute of Science in Israel determined that brain regions with high interconnectivity in controls have reduced connectivity in ASD, and regions with lower connectivity in controls have elevated connectivity in people with ASD.
The scientists analyzed fMRI scans from high functioning autistic adults and controls, obtained from five different data sets. When the scans from the controls were superimposed upon each other, a typical, canonical template of connectivity was clear. Certain regions had high inter hemispheric (between the right and left sides) connectivity: primary sensory-motor regions like the sensorimotor cortex and the occipital cortex. Others showed low interhemispheric connectivity: regions like the frontal cortex and temporal cortex, which are involved in higher order association. Overall, the control brain scans looked pretty much the same as each other.
How can you not cry at the end of Baz Luhrmann's Moulin Rouge!, when the courtesan Satine passes away in her lover Christian's arms after he throws money at her and calls her a whore in front of a packed theater only to then learn that she really does love him and had to break up with him to save his life from the wealthy but evil Duke who had sworn to kill him? Yes, it's been foreshadowed by the fact that she had been coughing up blood for the past two hours, but still—it's tragic.
Satine died of consumption—tuberculosis—which was the big microbial menace of the mid-to-late nineteenth century Western world. Why that particular bug, at that particular time and place?
Mycobacterium tuberculosis, the bacterium that causes tuberculosis, can remain latent inside of an infected person for decades. When humans lived in small, isolated bands—as they did until the Neolithic Revolution made agriculture widespread—this was a very effective means of transmission for the bacteria. Once it infected everyone in the group, it had no new victims; so it just hung out, dormant, in the same group of people until those people reproduced. Voila—new victims!
This week, a study was released by researchers at the University of Pennsylvania that found a surprising correlation when studying two kinds of maps: those that mapped the county-level frequency of cardiac disease, and those that mapped the emotional state of an area's Twitter posts.
In all, researchers sifted through over 826 million tweets, made available by Twitter's research-friendly "garden hose" server access, then narrowed those down to roughly 146 million tweets that had been posted with geolocation data from over 1,300 counties (each county needed to have at least 50,000 tweets to sift through to qualify). The team then measured an individual county's expected "health" level based on frequency of certain phrases, using dictionaries that had been put through scrutiny over their application to emotional states. Negative statements about health, jobs, and attractiveness—along with a bump in curse words—would put a county in the "risk" camp, while words like "opportunities," "overcome," and "weekend" added more points to a county's "protective" rating.
Not only did this measure correlate strongly with age-adjusted heart disease rate data, it turned out to be a more efficient predictor of higher or lower disease likelihood than "ten classical predictors" combined, including education, obesity, and smoking. Twitter beat that data by a rate of 42 percent to 36 percent.