For flowers, too much light at night could lead to a pollination hangover by day.
Far from any urban street, researchers erected street lights in remote Swiss meadows to mimic the effects of artificial light pollution. In fields lit during the night, flowers had 62 percent fewer nocturnal visitors than flowers in dark meadows, researchers report August 2 in Nature.
For one of the most common flowers, daytime pollination didn’t make up for nightly losses, says ecologist Eva Knop of the University of Bern in Switzerland. In a detailed accounting of the pollination life of cabbage thistles (Cirsium oleraceum), Knop and colleagues found that night-lit plants produced 13 percent fewer seeds overall than counterparts in naturally dark places. Night lights could affect the entire network of plants and pollinators, the team suggests. In the test fields, nighttime pollination wasn’t just the business of a few kinds of specialized moth-loving plants. Flowers that fed a wide range of nighttime visitors also attracted a broad buzzing circus of different kinds of daytime pollinators. If the daytime insects don’t make up for nocturnal losses, a flower’s population might dwindle. And a lot of insects, both day and night, might then feel the loss of nectar and foliage, Knop says.
More than 80 percent of flower species get some help from animals in making seeds, and none evolved with light after sundown. “I hope people start to realize that it’s really something that changes the whole ecosystem,” Knop says. The new study is the first to show how artificial light affects plants’ ability to make seeds, she says. The test is also unusual because it considers all kinds of insect pollinators instead of focusing on, say, only night-flying moths. This big-picture view was so not easy to achieve. Finding possible dead-dark sites in highly developed Europe to set up LED lamps was impossible, so researchers worked in 14 dark-as-possible, remote meadows in land rising toward the Alps. But that created a problem. “If you don’t have light, you don’t have power,” Knop points out. To avoid generator growls and smells confounding their results, researchers painstakingly scouted sites where possible near water-powered energy sources and overall used “really long cables.” For the sites with natural night, researchers measured pollination by patrolling set paths and catching any insect wriggling on a flower — in complete darkness, of course. The team used night-vision goggles but still didn’t have a perfect view, she says. It’s “not that easy to catch insects without three-dimensional vision.”
Besides paying special attention to the commonly visited cabbage thistle, researchers pieced together the whole network of which pollinator species visited which plant species day or night. Analysis of this Matterhorn of data suggested that changes in the night crew could affect daytime meadows.
The idea that night light could have broad knock-on effects on daytime pollinators is still speculation at this point, says ecologist Darren Evans of Newcastle University in England, who also studies light pollution and pollination. But the risk of such spillover warrants more attention.
A string of state-directed, targeted mass killings left a bloody stain on the 20th century. A genocide more recent than the Holocaust is providing new insights into why some people join in such atrocities.
Adolf Hitler’s many accomplices in his campaign to exterminate Jews throughout Europe have justifiably attracted the attention of historians and social scientists. But a 100-day spasm of unprecedented violence in 1994 that wiped out about three-quarters of the ethnic Tutsi population in the African nation of Rwanda has the potential to reveal much about how mass killings unfold at ground level. There is no guarantee that a better, although inevitably incomplete, understanding of why certain members of Rwanda’s majority Hutu population nearly eliminated a Tutsi minority will prevent future large-scale slaughters. The research is worth the effort, though, especially in a 21st century already marked by massacres of hundreds of thousands of people in western Sudan’s Darfur region and in Syria.
Researchers have an advantage in Rwanda. When hostilities ended, Rwanda’s government gathered extensive data on genocide victims and suspected perpetrators through a national survey. And local courts tried more than 1 million cases of alleged involvement in the violence, making the case documents available to researchers.
Genocide studies have often split offenders into organizers — mainly political and community leaders — and “ordinary men” who kill out of blind obedience to central or local authorities and hatred of those deemed enemies. But the extensive data from Rwanda tell a different story: An individual’s willingness to take part in genocidal violence depends on many personal and social factors that influence whether and how deeply a person participates, says sociologist and Rwanda genocide researcher Hollie Nyseth Brehm of Ohio State University in Columbus.
Nyseth Brehm’s findings may not apply to some of Rwanda’s most avid killers, who eluded capture and fled the country as soon as hostilities stopped. But when it comes to the ordinary citizens swept up in the deadly campaign, involvement was not primarily about following political leaders’ orders to eliminate Tutsis.
New reports by Nyseth Brehm and others fuel skepticism about the popular idea that regular folks tend to do as they’re told by authorities. And a fresh look at a famous 1960s psychology study adds further doubt that people will blindly follow orders to harm or kill others. In reality, only about 20 percent of Hutu men, an estimated 200,000, seriously injured or killed at least one person during the genocidal outbreak, estimates Rwanda genocide researcher Omar McDoom of the London School of Economics and Political Science.
“Why did four in five Hutu men not engage in the killing?” McDoom asks. That puzzle goes against the ordinary man thesis that “implies there are no individual differences in genocide participation,” he says. He suspects participation hinged on personal motivations, such as wanting to defend Rwanda from enemies or make off with a Tutsi neighbor’s possessions. Social circumstances, such as living in high-violence areas or having friends or family members who had already murdered Tutsis, probably played a role too. Nyseth Brehm agrees.
Local triggers Genocides often fester before exploding. In Rwanda, Tutsi rebels attacked the Hutu-led government and set off a civil war several years before mass killings started. A turning point came when unidentified forces killed Rwanda’s president, shooting down his plane on April 6, 1994. Over the next three months, the government orchestrated a massacre of Tutsis and any Hutus deemed friendly or helpful to Tutsis. Most scholars place the death toll at around 800,000, although estimates range from 500,000 to 1.2 million. Bands of Hutus scoured the countryside for their sworn enemies. Killings took place at roadblocks and in raids on churches, schools and other community facilities. Hutu women killed on a much smaller scale than men did, although they often aided those involved in the carnage.
In many parts of Rwanda, local authorities appointed by the national government recruited Hutu men into groups that burned and looted homes of their Tutsi neighbors, killing everyone they encountered, says political scientist Scott Straus of the University of Wisconsin–Madison. In his 2016 book Fundamentals of Genocide and Mass Atrocity Prevention, Straus describes how Rwandan recruitment efforts coalesced into a killing machine. Politicians, business people, soldiers and others encouraged Hutu farmers to kill an enemy described as “cockroaches” in need of extermination. Similarly, Nazis portrayed Jews as cockroaches and vermin.
Despite the Rwandan state’s best efforts to encourage nationwide Tutsi annihilation, local conditions shaped how the 1994 genocide unfolded, Nyseth Brehm reported in February in Criminology. She looked at 142 of the nation’s 145 municipalities, known as communes. Some experienced as few as 71 killings, while in others, as many as 54,700 people were murdered, she found.
Communes with the fewest killings were those that had the highest marriage and employment rates, Nyseth Brehm says. In those settings, mainly farming communities where people knew and trusted each other, most citizens valued a peaceful status quo and discouraged a descent into mass killing, she suspects. Curiously, violence was worse in areas with the largest numbers of educated people. That points to the effectiveness of anti-Tutsi teachings in Rwandan schools, Nyseth Brehm suggests.
Her study relied on data from a postgenocide survey, published in 2004 by Rwanda’s government, intended to document every person killed during the atrocity. Citizens throughout Rwanda told interviewers about individuals in their communities who had been killed during the outburst of slaughter. Reported and confirmed deaths were checked against records of human remains linked to the 1994 genocide. Comparisons were also made to Rwanda’s 1991 census.
However, any data on killings during mass violence, including from the Rwandan survey, will be incomplete, Nyseth Brehm cautions. So she also analyzed data from 1,068,192 genocide-related cases tried in local Rwandan courts from 2002 to 2012. Of particular note, although most nongenocidal murders in Rwanda are carried out by men in their 20s, the average age of accused genocide perpetrators was 34.7 years old, Nyseth Brehm reported in the November 2016 Criminology.
Hutu men in their 30s joined the genocidal fray as a way to fulfill adult duties by defending their communities against an outside threat, she suggests. Preliminary analyses show that perpetrators tended to cluster in families; if one of several brothers killed Tutsis, the others were far more likely to follow suit.
Additional scouring of court data indicated that Rwandans who had siblings convicted of genocide killings were especially likely to have murdered Tutsis themselves. In earlier interviews of 130 Rwandans, some who had killed Tutsis and others who hadn’t, McDoom similarly found that perpetrators tended to cluster in families.
Missing murderers Unfortunately, the Rwandan genocide’s most prolific players have eluded both the law and science, says political scientist Cyanne Loyle of Indiana University Bloomington. Investigators have so far interviewed only a handful of the powerful “big fish” who orchestrated the genocide, plus several hundred people tried and imprisoned for genocide participation. Survey and court data are limited to killers who either stayed in Rwanda after atrocities ended or were caught trying to flee the country.
But perpetrators with the most blood on their hands traveled in bands, wiping out tens of thousands of people at a time before hiding abroad, Loyle says. For instance, local officials lured large numbers of Tutsis to a school near the town of Murambi, where Hutu militias used machine guns, explosives and other weapons to kill more than 40,000 people in just three days.
“Scholars have studied Rwandans who killed on the sidelines while a larger and deadlier campaign was under way,” Loyle says. “They have mistaken a sideshow for the main event.”
Perpetrators of colossal atrocities at Murambi and elsewhere were less powerful than the government’s genocide masterminds, Loyle says. These “murderers in the middle,” however, were better equipped and far more effective at killing than common folk who got caught up in events, she contends.
There are no good estimates of how many members of large-scale killing squads escaped Rwanda and now live elsewhere. From 15,000 to 22,000 members of the Rwandan army and local militia groups were at large in the Democratic Republic of the Congo, near Rwanda’s border, in January 2003, according to a report by the International Crisis Group, a nonprofit organization.
Nyseth Brehm acknowledges the difficulty of accounting for genocide perpetrators who eluded justice. She and others, including Straus, have interviewed genocide offenders who stayed in Rwanda, often imprisoned for their crimes. Many of those who fled must have traveled in groups that murdered on a grand scale, she says. Those mass killers represent crucial missing data on who participates in genocide, and for what reasons. Vicious virtue In interviews by Nyseth Brehm, McDoom and others, perpetrators listed many reasons for joining the 1994 killing spree — hatred of Tutsis, a perceived need to protect nation and family, a desire to claim a neighbor’s property or a decision to join a suddenly popular cause, to name a few. Blind obedience to brutal leaders was far from the only reason cited.
That finding conflicts with the late psychologist Stanley Milgram’s interpretation of his famous “obedience to authority” experiments. Milgram described those trials, in which volunteers were told to administer increasingly intense shocks to another person, as a demonstration of people’s frequent willingness to follow heinous commands. He saw the experiments as approximating the more extreme situations in which Germans had participated in the Holocaust. On closer inspection, though, Milgram’s study aligns closely with what’s known about Rwandan genocide perpetrators, says S. Alexander Haslam, a psychologist at the University of Queensland in Australia. In Milgram’s experiments, as in Rwanda and Nazi Germany, “those willing to harm others were not so much passive ciphers as motivated instruments of a collective cause,” Haslam says. “They perceived themselves as acting virtuously and doing good things.”
Although Milgram’s tests upset some volunteers, most participants identified with his scientific mission to understand human behavior and wanted to prove themselves as worthy of the project, Haslam and psychologist Stephen Reicher of the University of St. Andrews in Fife, Scotland, conclude in a research review scheduled to appear in the 2017 Annual Review of Law and Social Science.
Milgram conducted 23 obedience experiments with New Haven, Conn., residents in 1961 and 1962 (SN: 9/21/13, p. 30). Most attention has focused on only one of those experiments. Volunteers designated as “teachers” were asked by an experimenter to continue upping the intensity of what they thought were electric shocks to a “learner” — who was actually in league with Milgram — who erred time and again on a word-recall test. Through screams, shouts and eventually dead silence from the learner, 26 of 40 volunteers, or 65 percent, administered shocks all the way to a maximum of 450 volts.
But experiments that undermined participants’ identification with the scientific mission lowered their willingness to deliver the harshest shocks, Haslam and Reicher say. Fewer volunteers shocked to the bitter end if, for instance, the study was conducted in an office building rather than a university laboratory or if the experimenter was not physically present. An analysis of data available from 21 of the 23 experiments finds that 43.6 percent of 740 volunteers shocked learners to the limit. Participants were most compliant when an experimenter encouraged them to continue shocking for the sake of the experiment (by saying, “The experiment requires that you continue”), the psychologists add. Participants never followed the order: “You have no choice, you must continue.”
Milgram’s archives at Yale University contain letters and survey responses from former participants reporting high levels of support for Milgram’s project and for science in general. Many former volunteers told Milgram that they administered shocks out of a duty to collaborate on what they viewed as important research, even if it caused them distress at the time. Still, Milgram’s recruits often admitted having had suspicions during the experiments that learners were not really being zapped.
Milgram was right that his experiments applied to real-world genocides, Haslam concludes, but erred in assuming that obedience to authority explained his results. From Milgram’s laboratory to Rwanda’s killing squads and Nazi concentration camps, orders to harm others are carried out by motivated followers, not passive conformists, he asserts.
If anything, that makes genocide all the more horrifying.
When the Aug. 21 solar eclipse unveils the sun’s normally dim atmosphere, the corona will look like an intricate, orderly network of loops, fans and streamers. These features trace the corona’s magnetic field, which guides coronal plasma to take on the shape of tubes and sheets.
These wispy coronal structures arise from the magnetic field on the sun’s visible surface, or its photosphere. Unlike the corona, the photosphere’s magnetism is a complete mess. “It’s not a static surface like the ground, it’s more like an ocean,” says solar physicist Amir Caspi of the Southwest Research Institute in Boulder, Colo. “And not just an ocean. It’s like a boiling ocean.”
Because the corona’s loops and streamers all originate in the turbulent photosphere, their roots should get twisted and turned around.
“And yet these structures in the corona are not tangled and snarled and matted like kelp or seaweed in the ocean,” Caspi says. “They seem to still be these organized, smooth loops. Nobody understands why.”
To unknot the photosphere’s tangled mats, the corona must release some of the energy stored there, Caspi says. So during the eclipse, he and his colleagues will be looking for the release valves that set the corona free. One possibility is that wave motion in the corona’s magnetic field lines helps untie the snarls. Magnetic waves in plasma, called Alfvén waves, are thought to ripple through the sun’s magnetic field lines like vibrations in a guitar string. Researchers have directly observed Alfvén waves in the lower corona, within about half a solar radius of the surface (SN: 4/11/09, p. 12), but not farther out where similar waves with higher amplitudes would travel. Those close-in waves were too weak to explain the corona’s features, but perhaps more distant waves could shake things up enough. Another option is that little hypothetical spurts of magnetic energy could help release the tangles. These nanoflares and nanojets would be like solar flares but with a billionth of the energy. By going off all the time, nanoflares and nanojets could collectively release enough energy to give the corona some structure, simulations have shown.
“Both are symptoms of tiny rearrangements of the magnetic field — magnetic reconnection,” says solar physicist Craig DeForest, also at the Southwest Research Institute. Solar flares and bigger outbursts called coronal mass ejections are also signs of magnetic reconnection, but they’re not frequent enough to account for the corona’s smoothness. “Nanojets and/or nanoflares in the middle corona would be a smoking gun that would explain why the corona is so organized,” DeForest says.
No one has actually seen any nanoflares or nanojets. Theories suggest that they’re too small and quick to see individually — but they should be visible as a cacophony of little pops when the solar eclipse reveals the lower corona.
The shaking from Alfvén waves and the flickers of nanoflares could not only loosen up the tangled skein of magnetism, but also transfer heat high up into the corona. Caspi, DeForest and their colleagues hope to see both effects on August 21, when they fly a pair of telescopes on twin NASA WB-57 high-altitude research jets along the path of the eclipse (SN Online: 8/14/17).
“We’re taking high-speed movies of the sun and analyzing them for things that look like waves,” Caspi says. “We’re just overall looking at the structure of the corona.”
Some people might think that online privacy is a, well, private matter. If you don’t want your information getting out online, don’t put it on social media. Simple, right?
But keeping your information private isn’t just about your own choices. It’s about your friends’ choices, too. Results from a study of a now-defunct social media site show that the inhabitants of the digital age may need to stop and think about just how much they control their personal information, and where the boundaries of their privacy are.
When someone joins a social network, the first order of business is, of course, to find friends. To aid the process, many apps offer to import contact lists from someone’s phone or e-mail or Facebook, to find matches with people already in the network.
Sharing those contact lists seems innocuous, notes David Garcia, a computational social scientist at the Complexity Science Hub Vienna in Austria. “People giving contact lists, they’re not doing anything wrong,” he says. “You are their friend. You gave them the e-mail address and phone number.” Most of the time, you probably want to stay in touch with the person, possibly even via the social media site.
But the social network then has that information — whether or not the owner of it wanted it shared.
Social platforms’ ability to collect and curate this extra information into what are called shadow profiles first came to light with a Facebook bug in 2013. The bug inadvertently shared the e-mail addresses and phone numbers of some 6 million users with all of their friends, even when the information wasn’t public.
Facebook immediately addressed the bug. But afterward, some users noticed that the phone numbers on their Facebook profiles had still been filled in — even though they had not given Facebook their digits. Instead, Facebook had collected the numbers from the contact lists innocently provided by their friends, and filled in the missing information for them. A shadow profile had become reality. It’s no surprise that a social platform could take names, e-mail addresses and phone numbers and match them up with other people on the same platform. But Garcia wondered if these shadow profiles could be extended to people not on the social platform at all.
He turned to a now-defunct social network called Friendster. A precursor to sites like MySpace and Facebook, Friendster launched in 2002. In 2008, the social site boasted more than 115 million users. But by 2009 people began to jump ship for other sites, and in 2015 Friendster closed for good. Millions of abandoned public profiles vanished into the ether.
Or did they? The Internet Archive — a nonprofit library — has an archive of more than 200 billion web pages, including Friendster. Garcia was able to use that repository to get data on 100 million public accounts from the social media site. Garcia dug through the records in a process he calls Internet Archaeology, after a satirical video from The Onion in which an internet archaeologist announces that he has, ironically, discovered Friendster. “The time scale of online media is very fast, but it’s still studying things in society that don’t exist anymore,” he explains.
Garcia hunted for patterns in the data. Most people don’t have a random assortment of friends. Married people tend to be friends with other married people, for example. But people also have connections that complicate the ability to predict who’s connected to who. People who identified as gay men were more likely to be friends with other gay men, but also likely to be friends with women. Straight women were more likely to be friends with men.
Using this information, Garcia was able to show that he could predict characteristics such as the marital status and sexual orientation of users’ friends who were not on the social media network. And the more people in the social network who shared their own personal information, the more information the network received about their contacts, and the better the prediction about people not on the network got.
“You are not in full control of your privacy,” he concludes. If your friend is on a social platform, so are you. And you don’t have a choice in the matter. Garcia published his findings August 4 in Science Advances.
This does not mean that social platforms are creating shadow profiles of your social media–averse friends, Garcia notes. But with the information people give to social networks and with the platforms’ computing abilities, they certainly could. To prevent the data being used this way, Garcia only used the most basic, public information. He didn’t predict anything about specific people. He only checked to see if it was possible. Garcia also kept the power of his predictions low and very general. And he was careful to not construct an algorithm that could actually build a shadow profile, to make sure that others cannot misuse the findings.
But the results do show that information from your friends on a social network could accurately predict your marital status, location, sexual orientation or political affiliation — information that you may not want anyone to know, let alone in a social network you’re not even on.
“It’s a good illustration of an issue we have in society, which is that we no longer have control over what people can infer about us,” says Elena Zheleva, a computer scientist at the University of Illinois in Chicago. “If I decide not to participate in a certain social network, that doesn’t mean that people won’t be able to find things about me on that network.”
This means we might need to think differently about what privacy means. “We’re used to thinking of having a private space,” Garcia says. “We think we’ve got a room with keys and we let some people in.” But a better image, he argues, might be to imagine ourselves covered in the wet paint of our personal information. If we touch someone else, we leave a handprint. “The more you touch other people, the more you leave on them,” he explains. Touch enough people, and anyone who looks at those people and their paint-covered sleeves will be able to pick out your personal shade of teal.
And because we are no longer in full control of our privacy, Garcia notes, it also means that protecting privacy isn’t something any one person can do. “In some sense it resembles climate change,” he says. “It’s not something you can solve on your own. It’s everyone’s problem or it’s no one’s problem.”
Earthworms are great for soil, right? Well, not always. In places where there have been no earthworms for thousands of years, foreign worms can wreak havoc on soils. And that can cause a cascade of problems throughout an area’s food web. Now comes evidence that invader worms in the Upper Great Lakes may be stressing the region’s sugar maples.
There are native earthworms in North America, but not in regions that had been covered in glaciers during the Ice Age. Once the ice melted, living things returned. Earthworms don’t move that quickly, though, and even after 10,000 years, they’ve only made small inroads into the north on their own.
But people have inadvertently intervened. Sometimes they’ve dumped their leftover bait in worm-free zones. Or they’ve accidentally brought worms or eggs in the soil stuck to cars or trucks. And the worms took up residence as far north as Alberta’s boreal forests.
Earthworms “are not really supposed to be in some of these areas,” says Tara Bal, a forest health scientist at Michigan Technological University in Houghton. “In a garden, they’re good,” she notes. They help to mix soil. But that isn’t a good thing in a northern forest where soil is naturally stratified and nutrients tend to be found only in the uppermost layer near the leaf litter. “That’s what the trees have been used to,” Bal says. Those trees include sugar maples, which have shallow roots to get those nutrients. But worms mix up the soils and take away that nutrient-rich layer. Bal didn’t start out studying worms in northern regions. She and her colleagues were brought in to address a problem that sugar maple growers were experiencing. Some of the trees appeared to be stressed out. They were experiencing what’s called dieback, when whole branches die, fall off and regrow. This is worrisome because if enough of the tree dies off, “it’s a slow spiral from there,” Bal says — the whole tree eventually dies. To investigate, the researchers collected data on trees and anything that could be affecting them, from soil type to slope to insects. They looked at trees in 120 plots in Michigan, Wisconsin and Minnesota. And they compared trees that were on growers’ land with those on public land, thinking that how the trees were managed might have some effect. When the researchers analyzed the data, “the same thing that kept coming up over and over again was the forest floor condition,” Bal says. “That is directly related to the presence of earthworms.” They didn’t go out to look for the worms, but they could see signs of them in the amount of carbon in the soil and in changes in the ground cover. Wildflowers, for instance, were replaced by grasses and sedges, the researchers report July 26 in Biological Invasions.
Bal and her team can’t say what this means for maple syrup production. It might not mean anything at all. But “worms are ecosystem engineers,” she notes. “They’re changing the food chain.” Everything from insects to birds to salamanders could be affected by the arrival of worms.
Even if the sugar maples take a hit, though, there could be an upside, Bal says. These trees are often grown with few other types of trees around. Such a grove is naturally less resilient to climate change and extreme weather. So replacing some of those sugar maples with other trees could result in a healthier, more resilient forest in the future, Bal says.
Zika’s damaging neurological effects might someday be enlisted for good — to treat brain cancer.
In human cells and in mice, the virus infected and killed the stem cells that become a glioblastoma, an aggressive brain tumor, but left healthy brain cells alone. Jeremy Rich, a regenerative medicine scientist at the University of California, San Diego, and colleagues report the findings online September 5 in the Journal of Experimental Medicine.
Previous studies had shown that Zika kills stem cells that generate nerve cells in developing brains (SN: 4/2/16, p. 26). Because of similarities between those neural precursor cells and stem cells that turn into glioblastomas, Rich’s team suspected the virus might also target the cells that cause the notoriously deadly type of cancer. In the United States, about 12,000 people are expected to be diagnosed with glioblastoma in 2017. (It’s the type of cancer U.S. Senator John McCain was found to have in July.) Even with treatment, most patients live only about a year after diagnosis, and tumors frequently recur. In cultures of human cells, Zika infected glioblastoma stem cells and halted their growth, Rich and colleagues report. The virus also infected full-blown glioblastoma cells but at a lower rate, and didn’t infect normal brain tissues. Zika-infected mice with glioblastoma either saw their tumors shrink or their tumor growth slow compared with uninfected mice. The virus-infected mice lived longer, too. In one trial, almost half of the mice survived more than six weeks after being infected with Zika, while all of the uninfected mice died within two weeks of receiving a placebo.
Using a virus to knock out cancer isn’t a completely new idea. Treatments that rely on modified polioviruses to target tumors such as glioblastomas are already in clinical trials in the United States, and there’s a modified herpesvirus approved by the U.S. Food and Drug Administration for treating melanoma.
These cancer-fighting viruses seem to work in two ways, says Andrew Zloza, head of surgical oncology research at the Rutgers Cancer Institute of New Jersey in New Brunswick. First, the viruses infect and kill cancer cells. Then, as those cancer cells split open, previously hidden tumor fragments become visible to the immune system, which can recognize and fight them.
“Right now we don’t know what kind of viruses are best” for fighting cancer, Zloza says — whether it’s more effective to use a common virus that many people have been exposed to or something more unusual. But now, Zika is yet another candidate.
Further testing is needed to determine whether the virus is safe and effective in humans. Since Zika’s effects are more harmful in developing brains, a Zika-based cancer therapy might be safe only in adults. And the virus would need to be genetically modified to make it safer and less transmissible. Rich and colleagues are now testing in mice whether combining Zika with traditional cancer treatments such as chemotherapy is more effective than either treatment by itself. Because Zika targets the cells that generate tumor cells, it might prevent tumors from recurring.
Here’s some heartbreaking news for people pinning their hopes on online matchmaking sites: It’s virtually impossible to forecast a love connection.
Maybe that’s not so shocking to survivors of the dating wars. But now science is weighing in. Extensive background data on two individuals — comparable to that collected by digital dating services — can’t predict whether that pair will romantically click during a four-minute, face-to-face speed date, say psychologist Samantha Joel of the University of Utah in Salt Lake City and colleagues.
People know when an in-person meeting on a speed date has gone smoothly or felt right — and that bodes well for mutual attraction, the investigators report online August 30 in Psychological Science. But on paper, no blend of personal qualities and partner preferences thought to influence mate choices pegged which opposite-sex duos would hit it off, Joel’s group concludes.
Joel expected that, say, a person who reported being attracted to extroverted people would generate the most chemistry with speed daters who reported being extroverted. Or, two people who reported being good-looking and having particularly warm personalities would feel especially attracted to one another after brief dates. But that’s not what Joel and coauthors Paul Eastwick of the University of California, Davis and Eli Finkel of Northwestern University in Evanston, Ill., found. The researchers studied 350 heterosexual college students — almost evenly split between males and females — who participated in one of 15 speed-dating events in 2005 or 2007. Participants filled out either 182-item or 112-item questionnaires about their personality traits and preferences in romantic partners. The students then completed about 12 speed dates. Afterward, participants rated their interest in and sexual attraction to each person they met.
Some qualities romance seekers said they wanted — such as extroversion and warmth — predicted individual speed daters’ greater attractiveness to others in general. But a statistical analysis of participants’ responses found that no traits or preferences, or combinations of traits and preferences, predicted how much one person especially desired another person after a speed date.
Joel’s team has not analyzed evidence from online matchmaking services to see if their questionnaires frequently pair people who generate romantic heat. “But our findings suggest that it’s quite difficult to predict initial romantic attraction using self-report measures before two people have met,” Joel says.
Biological anthropologist Helen Fisher, a senior researcher at Indiana University’s Kinsey Institute in Bloomington, agrees. “You’ve got to meet someone in person to trigger the brain circuitry for romantic love,” Fisher says.
That comes as no surprise to operators of online dating sites, she adds. These sites typically don’t promise customers romantic connections, says Fisher, who is a consultant for online dating site Match.com and founded its affiliated website, Chemistry.com. The aim is to provide an array of potential dates with background and personality traits requested by a customer. The rest is up to those who decide to go on dates.
Bats, with their superb ability to echolocate, are inspiring advanced technologies — from better Navy sonar to gadgets that might deliver packages or help farmers manage crops. And engineers aren’t waiting for neuroscientists to work out every detail of how the bats’ brains manage the task.
“We think we have enough information to be useful to us, to develop a bio-inspired sensor,” says research engineer Jason Gaudette of the Naval Undersea Warfare Center Newport Division in Rhode Island. Like bats, the Navy uses sonar to find and visualize objects in the deep. But current versions are far less elegant than the flying mammals’ system. The Navy’s sonar arrays can be huge, encompassing hundreds of “ears” that listen for sonar pings from atop a submarine’s dome or trailing behind it in a long tail. Bats, Gaudette notes, dodge obstacles and find mosquito-sized meals with just two ears. He and colleagues have developed a bat-inspired prototype device that they hope can perform more like bats do. Mounted on the nose of a half-meter-long, torpedo-shaped autonomous undersea robot, the sonar system has one sound transmitter and three receivers (Gaudette hopes to eventually get that number down to two or even one). The system uses algorithms inspired by research in bats to interpret returning sonar echoes for navigation. If it works, the system could help the Navy perform sonar imaging using less space and less money while offering sharper images, Gaudette says.
Researchers in Israel are hoping to help farmers with a bat-inspired kind of sonar. Neuroecologist Yossi Yovel of Tel Aviv University is creating computer algorithms describing how bats might interpret returning echoes to distinguish different plants. Yovel collaborates with Avital Bechar, a researcher at the Institute of Agricultural Engineering near Rishon LeZion, Israel, who wants to help farmers predict their crops’ yield, which can vary widely from year to year. The same acre of tomato plants, for example, could yield 30 or 120 tons of fruit, Bechar estimates. Such a wide range puts farmers at a disadvantage in negotiating a price for crops and forces the farmers to guess how much equipment and how many pickers they’ll need at harvest time.
Bechar’s sonar system, which emits batlike sounds and records via microphones that mimic bat ears, can penetrate three rows of plants deep — farther than cameras could. Then it calculates the number of leaves and pounds of fruit per plant, based on Yovel’s algorithms. Bechar has mounted the scanner on a prototype robot and plans to affix it to a drone to count fruit in 15-meter-high date palms. The researchers also hope to add weed-detection capability. Bechar expects it to be “a game changer in agriculture, because it will reduce the unknowns.” At Virginia Tech in Blacksburg, engineer Rolf Mueller is learning tricks from the physical structures of bats’ noses and ears. Certain bat groups, such as horseshoe bats (one species Mueller works with is Rhinolophus ferrumequinum), send out their echolocation calls through their noses, like a snort. Complex, fleshy formations called nose-leaves change the outgoing sound as it comes out of the nose. And the bats’ ears have more than 20 muscles, which rapidly change shape as the bat listens for echoes, Mueller says. That flexibility gives the animals more information, he suspects: “It’s like seeing the world with a different perspective, at the same time, [from] one echo.”
His group developed a prototype robot with mechanical “nose-leaves” and shape-shifting “ears,” and sent it zooming through forested areas on a zip line to record how the bot perceives trees and branches. Eventually, Mueller envisions an autonomous underwater bot or an airborne drone with a similar sonar setup. The drone could be useful for delivering packages in forested or otherwise complicated areas without crashing.
A boy who lived in what’s now South Africa nearly 2,000 years ago has lent a helping genome to science. Using the long-gone youngster’s genetic instruction book, scientists have estimated that humans emerged as a distinct population earlier than typically thought, between 350,000 and 260,000 years ago.
The trick was retrieving a complete version of the ancient boy’s DNA from his skeleton to compare with DNA from people today and from Stone Age Neandertals and Denisovans. Previously documented migrations of West African farmers to East Africa around 2,000 years ago, and then to southern Africa around 1,500 years ago, reshaped Africans’ genetics — and obscured ancient ancestry patterns — more than has been known, the researchers report online September 28 in Science. The ancient boy’s DNA was not affected by those migrations. As a result, it provides the best benchmark so far for gauging when Homo sapiens originated in Africa, evolutionary geneticist Carina Schlebusch of Uppsala University in Sweden and her colleagues conclude.
In line with the new genetically derived age estimate for human origins, another team has proposed that approximately 300,000-year-old fossils found in northwestern Africa belonged to H. sapiens (SN: 7/8/17, p. 6). Some researchers suspect a skull from South Africa’s Florisbad site, dated to around 260,000 years ago, qualifies as H. sapiens. But investigators often place our species’ origins close to 200,000 years ago (SN: 2/26/05, p. 141). There is broad consensus that several fossils from that time represent H. sapiens.
Debate over the timing of human origins will continue despite the new evidence from the child, whose remains came from previous shoreline excavations near the town of Ballito Bay, says Uppsala University evolutionary geneticist and study coauthor Mattias Jakobsson. “We don’t know if early Homo sapiens fossils or the Florisbad individual were genetically related to the Ballito Bay boy,” he says.
Thus, the precise timing of humankind’s emergence, and exact patterns of divergence among later human populations, remain unclear. Researchers have yet to retrieve DNA from fossils dating between 200,000 and 300,000 years old that either securely or possibly belong to H. sapiens. However early human evolution played out, later mixing and mingling of populations had a big genetic impact. DNA evidence from more recent fossils, including those studied by Schlebusch’s group, increasingly suggests that Stone Age human groups migrated from one part of Africa to another and mated with each other along the way (SN: 10/20/12, p. 9), says Harvard Medical School evolutionary geneticist Pontus Skoglund. In the Sept. 21 Cell, he and his colleagues report that DNA from 16 Africans, whose remains date to between 8,100 and 400 years ago, reveals a shared ancestry among hunter-gatherers from East Africa to South Africa that existed before West African farmers first arrived 2,000 years ago.
That ancient set of common genes still comprises a big, varying chunk of the DNA of present-day Khoisan people in southern Africa, Skoglund’s group found. Earlier studies found that the Khoisan — consisting of related San hunter-gatherer and Khoikhoi herding groups — display more genetic diversity than any other human population.
Schlebusch’s team estimates that a genetic split between the Khoisan and other Africans occurred roughly 260,000 years ago, shortly after humankind’s origins and around the time of the Florisbad individual. Khoisan people then diverged into two genetically distinct populations around 200,000 years ago, the researchers calculate.
Ancient DNA in Schlebusch’s study came from seven individuals unearthed at six South African sites. Three hunter-gatherers, including the Ballito Bay boy, lived about 2,000 years ago. Four farmers lived between 500 and 300 years ago.
Comparisons to DNA from modern populations in Africa and elsewhere indicated that between 9 percent and 30 percent of Khoisan DNA today comes from an East African population that had already interbred with Eurasian people. Those East Africans were likely the much-traveled farmers who started out in West Africa and reached southern Africa around 1,500 years ago, the researchers propose.
For Chong Liu, asking a scientific question is something like placing a bet: You throw all your energy into tackling a big and challenging problem with no guarantee of a reward. As a student, he bet that he could create a contraption that photosynthesizes like a leaf on a tree — but better. For the now 30-year-old chemist, the gamble is paying off.
“He opened up a new field,” says Peidong Yang, a chemist at the University of California, Berkeley who was Liu’s Ph.D. adviser. Liu was among the first to combine bacteria with metals or other inorganic materials to replicate the energy-generating chemical reactions of photosynthesis, Yang says. Liu’s approach to artificial photosynthesis may one day be especially useful in places without extensive energy infrastructure.
Liu first became interested in chemistry during high school, and majored in the subject at Fudan University in Shanghai. He recalls feeling frustrated in school when he would ask questions and be told that the answer was beyond the scope of what he needed to know. Research was a chance to seek out answers on his own. And the problem of artificial photosynthesis seemed like something substantial to throw himself into — challenging enough “so [I] wouldn’t be jobless in 10 or 15 years,” he jokes. Photosynthesis is a simple but powerful process: Sunlight helps transform carbon dioxide and water into chemical energy stored in the chemical bonds of sugar molecules. But in nature, the process isn’t particularly efficient, converting just 1 percent of solar energy into chemical energy. Liu thought he could do better with a hybrid system. The efficiency of natural photosynthesis is limited by light-absorbing pigments in plants or bacteria, he says. People have designed materials that absorb light far more efficiently. But when it comes to transforming that light energy into fuel, bacteria shine.
“By taking a hybrid approach, you leverage what each side is better at,” says Dick Co, managing director of the Solar Fuels Institute at Northwestern University in Evanston, Ill.
Liu’s early inspiration was an Apollo-era attempt at a life-support system for manned space missions. The idea was to use inorganic materials with specialized bacteria to turn astronauts’ exhaled carbon dioxide into food. But early attempts never went anywhere.
“The efficiency was terribly low, way worse than you’d expect from plants,” Liu says. And the bacteria kept dying — probably because other parts of the system were producing molecules that were toxic to the bacteria.
As a graduate student, Liu decided to use his understanding of inorganic chemistry to build a system that would work alongside the bacteria, not against them. He first designed a system that uses nanowires coated with bacteria. The nanowires collect sunlight, much like the light-absorbing layer on a solar panel, and the bacteria use the energy from that sunlight to carry out chemical reactions that turn carbon dioxide into a liquid fuel such as isopropanol.
As a postdoctoral fellow in the lab of Harvard University chemist Daniel Nocera, Liu collaborated on a different approach. Nocera had been working on a “bionic leaf” in which solar panels provide the energy to split water into hydrogen and oxygen gases. Then, Ralstonia eutropha bacteria consume the hydrogen gas and pull in carbon dioxide from the air. The microbes are genetically engineered to transform the ingredients into isopropanol or another liquid fuel. But the project faced many of the same problems as other bacteria-based artificial photosynthesis attempts: low efficiency and lots of dead bacteria. “Chong figured out how to make the system extremely efficient,” Nocera says. “He invented biocompatible catalysts” that jump-start the chemical reactions inside the system without killing off the fuel-generating bacteria. That advance required sifting through countless scientific papers for clues to how different materials might interact with the bacteria, and then testing many different options in the lab. In the end, Liu replaced the original system’s problem catalysts — which made a microbe-killing, highly reactive type of oxygen molecule — with cobalt-phosphorus, which didn’t bother the bacteria.
Chong is “very skilled and open-minded,” Nocera says. “His ability to integrate different fields was a big asset.”
The team published the results in Science in 2016, reporting that the device was about 10 times as efficient as plants at removing carbon dioxide from the air. With 1 kilowatt-hour of energy powering the system, Liu calculated, it could recycle all the carbon dioxide in more than 85,000 liters of air into other molecules that could be turned into fuel. Using different bacteria but the same overall setup, the researchers later turned nitrogen gas into ammonia for fertilizer, which could offer a more sustainable approach to the energy-guzzling method used for fertilizer production today.
Soil bacteria carry out similar reactions, turning atmospheric nitrogen into forms that are usable by plants. Now at UCLA, Liu is launching his own lab to study the way the inorganic components of soil influence bacteria’s ability to run these and other important chemical reactions. He wants to understand the relationship between soil and microbes — not as crazy a leap as it seems, he says. The stuff you might dig out of your garden is, like his approach to artificial photosynthesis, “inorganic materials plus biological stuff,” he says. “It’s a mixture.”
Liu is ready to place a new bet — this time on re-creating the reactions in soil the same way he’s mimicked the reactions in a leaf.
