America's steel city has weathered the rocky transition from an economy built on manufacturing to one driven by cutting edge research
Scientists are working on a promising new model
It’s peak mosquito season in the United States, which means the risk for the mosquito-borne West Nile is up. According to the U.S. Centers for Disease Control and Prevention (CDC), the agency sees the most cases of the disease between June and September.
As of July 21, 2015, the CDC reports that 33 states have reported West Nile in people, mosquitoes or animals and there have been 23 cases of West Nile in humans. Though many people with West Nile will not develop symptoms, the disease can cause inflammation of the brain or inflammation of the lining of the brain and spinal chord. Only about 1% of people will develop neurological illness from the virus. Unfortunately there are no drugs or vaccines for West Nile. Cases have been reported in every state except for Alaska and Hawaii.
Given the fact that there’s no cure or vaccine for West Nile, being able to predict when and where the disease could spread in the U.S. before it happens would be a boon for public health experts, and researchers are getting closer to that possibility. In May, scientists at the National Center for Atmospheric Research (NCAR) and the Centers for Disease Control and Prevention (CDC) published their recent findings that showed links between the weather and incidence of West Nile virus nationwide.
The researchers analyzed associations between temperature and precipitation and higher prevalence of West Nile virus disease in the U.S. from the years 2004 to 2012. The found notable and consistent patterns among different regions in the U.S. For instance, in the East, a drier than normal fall and spring was associated with an above average number of outbreaks. But patterns looked different in the West. Weather may influence breeding patterns as well as other vectors of the disease like birds.
The researchers are now in the process of using their findings to build a model using climate data to predict the risk of West Nile Virus transmission across the U.S. “If we can predict [West Nile virus] outbreaks, we can target public health messages to high risk regions of the country. And counties will have additional information to use for deciding about when, where, and if they should do mosquito control,” says researcher Micah Hahn a scientist at NCAR and CDC.
According to NCAR scientists Andrew Monaghan and Mary Hayden, who are also working on the model, additional data sets are being considered and implemented to help the model predict the number of cases expected in each U.S. county, including land use data, demographic data, and mosquito maps.
The hope is that the CDC will eventually adopt the model. According to Monaghan, having this information could help the CDC allocate resources to places that are likely going to be the most affected. The researchers want the model to be both informative and easily digestible to the average person. It’s also possible that the model could one day be translated to work for other mosquito-borne diseases in the United States besides West Nile.
Some researchers estimate that a functioning system will be available in about a year. Others involved are more broad in their estimations: “We continue to work on it but it may be several years before we have a validated model that we can use, if we get there at all,” says Dr. Marc Fischer of the CDC. Still, those in the community remain optimistic that such a system is possible, and may be available sooner rather than later.
Phone data could predict with 87% accuracy whether someone had depressive symptoms
Most of us are pretty attached to our phones, and researchers are starting to figure out what that connection can tell us about our health, including our mood. In fact, your phone may be able to tell if you’re depressed even better than a self-assessment of your own depression can, according to a small new study published in the Journal of Medical Internet Research.
“We found that the more time people spend on their phones, the more likely they are to be more depressed,” says David Mohr, one of the authors of the study and director of the Center for Behavioral Intervention Technologies at Northwestern University Feinberg School of Medicine. The researchers also found that spending lots of time at home was linked to depression—and that phone data like this could predict with 87% accuracy whether someone had symptoms of depression.
Northwestern researchers recruited 28 people ages 19-58 from Craigslist and souped up their smartphones with location-and-usage monitoring software. At the start of the study, they took a standardized questionnaire that measures depressive symptoms; half of the subjects had symptoms of depression, and half did not. For two weeks, the phones tracked GPS location information every five minutes and pinged the users with questions about their mood several times a day.
The phone data the researchers collected were rich: how many places the participants visited each day, how much time they spent in each of those places and how frequently they used their phones, says Sohrob Saeb, one of the study’s authors and a postdoctoral fellow and computer scientist in preventive medicine at Feinberg. The researchers then correlated this objective data with their depression test scores.
What they hoped to find was a connection between the objective markers of behavior—such as where the people were and how often they changed locations—and their depression test results. That way, the data derived from phones could become a useful way to track depression without the user having to report how they were feeling, which is often a barrier to depression treatment, says Mohr, who has studied depression for about 20 years. “One of the things that we find over and over again is that people don’t answer questions,” he says. “In apps, they’ll respond to questions for a few days and then get tired of it.”
Mohr and his team indeed found a strong correlation between these objective markers and depression. Phone data were even better than the daily questions the users answered to predict depression test results. “People who tend to spend more time in just one or two places—like people who stay at home or go to work and go back home—are more likely to have higher depression scores,” says Mohr. When a person moved around was important, too; people who stuck to a regular pattern of movement tended to be less depressed, they found. “This fits into a larger body of clinical research showing that people with mental health problems in general, their circadian rhythms get thrown off,” Mohr says. “Usually it’s looked at with sleep and activity, but here we’re seeing it also in terms of their movement through geographic space.” When people get depressed, he says, their mood may pull them off their routine.
Depressed people, too, spent an average of 68 minutes using their phones each day, while people without depression only spent about 17 minutes on their phones. The software didn’t track what people did on their phones—just whether or not they were using it. But the authors have some ideas about why they saw phone activity rise with depression. “One of the things we see when people are depressed is that people tend to start avoiding tasks or things they have to do, particularly when they’re uncomfortable,” Mohr explains. “Using the phone, going in and using an app, is kind of a distraction.”
It’s preliminary research, but Mohr hopes to add to the number of smartphone sensors and use these to subtly help manage depression and spot it more quickly, without requiring any work on behalf of the user. “Being able to get people timely treatment for depression is a critical failure point in public health right now,” Mohr says. An app that people download on their phones—without having to answer any questions—may help pinpoint their depressive states more effectively and help them get treatment.
Meet the wonder material that is one hundred thousandth of the thickness of a human hair, yet is a hundred times stronger than steel. Graphene has been called "the most exciting material of the 21st century," yet we have barely scratched the surface of what it is capable of doing
IBM's new prediction tool marries live weather forecasts with a hyperlocal map, painting in yellow and red the damages to come
Every city has what emergency response crews call its “critical assets.” They’re roads, power stations, water pumps and pipes — the collective infrastructure that has the power to keep a city humming or bring life to a grinding halt. The question for city officials is when and if, exactly, these critical assets might fail. In severe weather, they typically find out the hard way.
Just this week, severe thunderstorms and twisters forced more than 15 fire departments and rescue teams to fan out across central Illinois. With crews already stretched thin, forecasters are predicting another round of severe weather to pummel the region. Help might arrive sooner if emergency crews had a map of which roads would become treacherous, which power stations would fail and which water mains would burst before the storm rolled into town.
That, in a nutshell, is the pitch for a new predictive tool IBM has unveiled in partnership with The Weather Company, parent company of The Weather Channel. Dubbed the “Intelligent Operations Center for Emergency Management,” the new platform marries live weather forecasts with a hyperlocal map of a city’s infrastructure, painting in yellow and red the predicted damage to come. With natural and man-made catastrophes taking 7,700 lives and upwards of $110 billion in damages in 2014, according to estimates by insurer Swiss Re, the market potential for a predictive tool is promising, to say the least.
The new software comes amid a surge of investment in big data solutions for public safety. Startup Mark43 is digitizing police records in an attempt to map out criminal networks. Motorola is embedding sensors into equipment used by police and fire crews to tap into a live feed of data from first responders. But IBM’s solution marks perhaps the most ambitious attempt to tease out the underlying order of chaotic events.
“I’m watching how those assets are affected to figure out, ‘Where do you begin?'” says Stephen Russo, director of emergency management solutions at IBM. “How do you get the biggest bang for your efforts?'”
Russo and his team used historic data from natural catastrophes to ascertain the breakpoint of certain assets — like when a power line might snap under high winds. The risk of failure is often as capricious as the wind itself. “It’s not a linear relationship,” says Russo. Power outages rise exponentially as wind speeds climbs from 20 mph to 40 mph, for instance. “When it goes from 40 to 50 mph, the amount of outages is much greater,” says Russo. And that’s the easy part of IBM’s catastrophic calculus.
Harder still is predicting which critical buildings — hospitals, schools and shelters — are most likely to suffer an outage. Throw in a few more assets, and no human statistician could ever hope to calculate the odds. IBM is betting machine learning algorithms can weigh the probabilities of failure in an instant and spit out ever-changing snapshots of disaster zones.
“Everybody sees the same picture of what’s going on,” says Mark Gildersleeve, president of The Weather Company’s professional division. “You’ve quantified the impact. Objectively, what are the areas most under stress?”
IBM envisions the map as a canvas for communication between emergency workers in command centers and various outposts. Top officials will have a bird’s eye view of relief efforts, while field workers can populate the map with reports from the ground. In its most ambitious form, the map could scale out to actors in the private sector. “The big ox carriers during a disaster, the Walmart’s and Costco’s, could position their resources more accurately and take more of the burden off of the public sector, so that they are not having to stock a warehouse full of water and generators.” Insurers might also use the maps to send pinpointed alerts to policyholders, warning them to cover their cars, for instance, before a hail storm bursts overhead.
But first, IBM will have to get all of those myriad actors on board its system. Fortunately for its sales team, the platform doubles as an ordinary emergency response system, recording routine traffic accidents as well as nature’s most brutal events. But the true test of the system will come at those unpredictable moments when the skies open up and the earth shakes beneath users’ feet. With severe thunderstorms threatening 50 million Americans this week, the solution can’t come soon enough.
These startups are finally starting to look like true ride-sharing services
First, the bad news: carpooling has been on the decline in America for nearly four decades. That practice could be helping the environment and America’s commuters, who are needlessly stuck for hours each day on packed highways. Multiple people sharing a single ride to a common destination is a simple act that has the potential to reduce CO2 emissions, ease traffic, lessen fossil fuel dependency, reduce stress on commuters, and even drive down rents in dense cities. Yet the practice fell out of favor after reaching a peak in the 1970s.
Now, the good news: popular tech companies Lyft and Uber are leading a wave of new services that have the potential to revive shared rides. “What fascinates me about these things is: can they move us closer toward a vision of an integrated public transit system?” asks Susan Shaheen, co-director of the Transportation Sustainability Research Center at the University of California, Berkeley. “And can it move us closer to filling empty seats in vehicles?”
Despite referring to themselves as “ride-sharing” companies, Lyft and Uber have largely been in the business of what transportation experts call “ride-sourcing,” because they essentially provide the same service as taxis through their own platforms. “I’ve studied ride-sharing for a long time, and the definition of ride-sharing is really carpooling,” Shaheen says. “And a carpool is an incidental trip.” That is, it’s a trip that a driver was going to take regardless of whether anyone else was with them in that car.
The distinction isn’t just academic. When the thousands of drivers working for Uber and Lyft in San Francisco are picking up a single fare and taking them from Point A to Point B, it’s probable that they’re adding to unnecessary congestion, pollution and fuel consumption. But last summer, within hours of each other, the companies announced that they were rolling out UberPOOL and Lyft Line in San Francisco, passenger-pooling options that would give riders cheaper fares if they’d be willing to share their vehicle with strangers traveling a similar route.
The companies say customer interest has been high so far. Each company has since expanded the service to Austin, Los Angeles, and New York City, and Uber has launched POOL in Paris. Lyft says that 50% of rides in San Francisco are Lyft Line rides, and a little more than 20% of all Lyft rides in the city start or end within a quarter mile of commuter rail stops. “That’s notable,” says Shaheen. “It means people are taking this short trip in one of these vehicles and connecting it to a longer line-haul transit trip. It’s basically enabling somebody to not take a single-occupant vehicle for this long commute trip and to rethink how they commute.”
Uber crunched the numbers on their “matched trips” for one month in San Francisco, comparing them to the number of miles that vehicles would have traveled if all those rides had been taken individually. They estimated that UberPOOL rides taken between February and March amounted to 674,000 miles of saved driving. That’s the equivalent of 240 people driving round trip from L.A. to New York. “UberPOOL is really about trying to reinvent cities from a transportation perspective,” says product manager Brian Tolkin. “Part of that means making Uber so affordable that it’s really available to anyone and a better alternative to, say, owning a car.”
Of course, before these companies start patting themselves on the back for saving the environment, they have to offset the number of cars they’ve brought onto the road. They aren’t releasing data about that, and there is other crucial information missing. The most important piece, Shaheen says, is knowing what the people using these services were doing beforehand. If someone is now using a combination of Lyft Line and public rail rather that driving alone in a car from San Francisco to Cupertino, that represents a greater environmental offset than if that person was previously taking public rail and a public bus.
Carpooling took off in America during World War II, when the government asked people to start sharing rides to work so they could conserve rubber for the war effort. The practice gained popularity through the 1970s, spurred by volatile energy prices, employer-sponsored programs and the advent of HOV lanes. But as gas prices dropped, cars got cheaper and more people and companies decamped for far-out suburbs and exurbs, more workers began taking their own cars to the office. Carpooling became associated with the inconveniences of neighbors’ inflexible schedules, awkward reimbursements and a lack of privacy. Nearly one in four people shared a ride to work in the 1970s. By the time census workers asked about that practice in 2010, the number had dropped to about 10%.
It’s too early to tell if Lyft and Uber’s early efforts will reverse that trend. But it is clear that they are benefiting from a changed landscape. Smartphone ownership has exploded, allowing people to connect and share useful information about where they are. Familiarity with social networks can encourage strangers to trust each other. The algorithms matching riders and drivers—while keeping routes convenient—are constantly improving. And though car sales have continued to climb in recent years, younger urban residents say they’re less interested in driving and owning their own vehicle.
Perhaps the most promising trend line for these services is that Uber and Lyft are finally solving the problem that has derailed past attempts to solve America’s carpooling problem with technology. “When you have a new system with a really small number of people in it—which any system will when it’s new—there’s a very, very low probability that you’ll have a match between all the potential origins and destinations of a driver and a passenger,” says Emily Castor, Lyft’s director of transportation policy. “So those systems that had tried to do that have been pretty uniformly unsuccessful, because they have a high failure rate.”
That’s what happened to Zimride, an early incarnation of Lyft. Among the key lessons for Zimride’s founders when they rebranded as Lyft: always have drivers available, lest you deter potential customers. “We’ve been able to build up a network that has enough density that it actually is getting to the point now where we do have a ton of people using it,” says Castor. “So we’ve kind of overcome that chicken and egg problem and we now can start doing really interesting things.”
Those experiments include “Driver Destination,” which allows a driver to specify where they’re headed and signal that they’re available to pick someone up. The app will only link the driver to a passenger going the same way. This type of trip can help eliminate wasted space in cars and potentially keep superfluous cars off the road–an efficiency that experts like Shaheen call the holy grail. “The next phase for Lyft is to look at how we can increase that commuter carpooling activity and to expand on our vision to make it so any time any driver is on the road, [they] can be using the empty seats in their cars to give rides to other people,” Castor says.
The key to long-term success may be money. For these services to truly take hold, drivers will need to see the upside of bringing a few strangers along for the ride. Old-fashioned carpooling was set up for passengers to reimburse a driver for just gas and wear and tear, a piddling bit of change per mile. “That’s just not enough to make people notice and think about doing that,” Castor says. “But if you could earn $15 on your way to work and your way home, that would probably raise your eyebrows.”
They're not just a funny thing to feature on sitcoms
Most days, here are no actual humans manning the Suitable Technologies store on the main drag in Palo Alto, Calif. Instead, the salespeople remotely “beam in” from places like Hawaii and New York to operate the company’s roving BeamPro robots, five-foot tall rolling devices with speakers and screens on top. One of the robots has a leaf blower attached. Another one does a routine where the “pilot” drives it across the street to buy ice cream for potential buyers.
It’s a cute gimmick. But as these machines get more advanced, they could seriously change the way distance affects people’s lives. Here are seven ways how:
Helping families connect to each other and their homes. In a recent episode of Modern Family, Phil gets grounded by an ear infection and is unable to return home for his daughter Alex’s graduation party. So he sets up a robot (this $2,500 one made by Double Robotics) to act as his surrogate.
The subplot makes it clear that this early generation of wheeled machines has limitations—like not being great at going down stairs. But one can also see how much richer the connection is than handing a phone around from person to person. And you might notice that no one else has to sacrifice what they’re doing to take care of faux Phil, like what happens to the relative who gets stuck lugging a Skyping relative around on a laptop.
Today in the Suitable Technologies store is actual breathing human Tom Wyatt, a VP of sales at the company. He talks about how people have used the robots—both the $17,000 enterprise version and the $2,000 consumer version—to be virtual wedding guests and family reunion-ers. He has one in his house that his daughter, off at college, uses to have dinner with the family or sit around watching a San Francisco Giants baseball game with her brothers.
“We’re just hanging out,” he says. “Just like she’s here.”
Improving elder care. Other customers have bought the robots to stay better connected to aging parents. Because machines like the BeamPro can be controlled remotely, those aging parents never have to turn it on, control it or remember to charge it. Kids can check in to make sure they’re okay or that they’ve taken their medicine. Various robot manufacturers are making deals with assisted living facilities, who are touting these gadgets as an amenity that helps keep families connected once someone needs full-time care. There’s more potential for interaction than with a phone or computer screen, too — the robot can take a stroll down the hall with Nana, for instance. As people get older, they often get isolated. Social interactions that can really simulate having a human in the room could have serious health benefits.
Making the business world smaller. As these robots get cheaper, there will be more consumer usage. But the early adopters have been big businesses like Google who are using them to attract the best talent (“No need to move to Mountain View!”) and make collaboration better when all the key people can’t be in the room together. Though there are various companies making these roaming machines, Wyatt says he sees Suitable’s biggest competitor as traditional video conferencing. The situations where the robots thrive are ones where there needs to be movement or a greater sense of presence.
Rolling robots have given keynote speeches, moving around the stage like speakers would stroll. Convention centers have purchased them so they can rent them out by the hour to people who want to be at a conference for a half-day instead of shelling out for the plane ticket, hotel and so forth. Business owners who need to keep an eye on their factories in China have used them to check up on things so they have to make the trip half as often.
Giving recruiters an edge: The football coach at Stanford University, Wyatt says, uses robots for recruiting.
“You’re in a situation where you have a limited number of visits that each guy can do to each campus,” he says, alluding to NCAA regulations. “So this kid is in Iowa—or wherever—can beam in, drive around the athletic building, look at the weight facilities, plug in the 4G card, drive over to the practice facility, drive over to the stadium.”
Touring schools by robot could become standard practice for kids in the future, making the process of choosing a college far more economical. Tech companies and other businesses, meanwhile, can use the same scheme to lure future employees.
Making culture accessible. Institutions like the Smithsonian have used rolling robots to help bring the museum experience to disabled people. Rolling along viewing paintings and artifacts with a docent, people from all over the world can see exhibits up close. As machines get more rugged and have more robust connectivity, Yellowstone or Yosemite could have them on hand for visitors to explore national parks. Machines like the BeamPro come with technology similar to the type cars use to brake automatically when the vehicle detects something in front of it—like a kid running into the street—which can help make sure no one is driving these off cliffs.
Changing real estate. Real estate agents are using rolling robots to give people virtual tours of spaces they might want to purchase, like the couple from New York interested in a San Francisco apartment.
“People say, I’d love to buy that place, but what does my view look like? And what do the amenities look like?” says Wyatt. Right now, Suitable’s machines are being used mostly in static places—like a condo complex in Hawaii. But the robots could be popped in and out of an agent’s trunk and used all over the place, so long as they shelled out for a 4G connection or had listings with stable Wi-Fi.
Outsourcing jobs. At the Suitable Technologies store, the jobs are outsourced to make a point. But there are other human jobs that could be outsourced via rolling robots to save companies money, which could be unpopular with locals. Take the example of a security guard wandering around a parking lot on the Facebook campus in Menlo Park. A computer can’t do that job, but “there’s a guy in Nebraska that would probably be very willing to have that job and at a lower wage than anyone would around here,” Wyatt says.
Teachers could command a classroom remotely and wander down the hall to the faculty lounge. Specialist doctors could go up and down a hallway visiting bedridden patients, rather than being reliant on video equipment in every room. Wyatt has sold some robots to clinicians who want to be in more than one place.
“It’s that freedom and control piece that makes a difference,” he says. “It’s not that the traditional video conferencing system doesn’t work. It’s just limiting.”
Investors are pouring money into the field
Correction Applied Tuesday, June 9.
When you think of food, you probably don’t think of technology. However, technology has played a major role in the food world, whether it was taking farming from oxen-led plowing to tractor based harvesting to today’s discovery’s of natural pest controls to the controversial bioengineering of food. Technology, especially things like social networks and services like Facebook, Pinterest, Instagram, Yelp, OpenTable and Table 8 has had a big impact on the food industry and there are thousands of food blogs covering just about any related topic one could think of.
This past week, there was a fascinating conference held at the San Francisco 49ers’ stadium called Bite Silicon Valley, organized by Octagon Culinary that discussed the intersection of food and technology. Various chefs and industry speakers on the program talked about the major issues facing the food industry and more importantly, the real concern over how, by 2050, we’ll be able to feed a planet of 9 billion people.
The conference was held in Silicon Valley because the food industry and tech industry have started to intersect and companies like Google and Yahoo have major research projects related to the future of food. Many Sand Hill Road venture capitalists have placed major bets on various food technology and services. As a couple of venture capitalists at the event told me, food-related start-ups fit into their sustainability portfolios, alongside solar, energy or electric cars because they have the potential to positively impact our world.
The goal of some of these VC investors is to connect restaurants with food providers, or to create on-demand delivery services from local farms, or ready-to-cook dinner kits. Other goals I have been told about are to invent new foods, like creating cheese, meat and egg substitutes from plants. One of the companies that venture capital firm Kleiner Perkins, Bill Gates and Biz Stone have invested in is Beyond Meat. It was there giving tastings of its new plant-based Beast Burgers and beef crumbles. I tasted the Beast Burger and it’s one of the best plant-based burgers I have ever eaten. According to Tim Geistlinger, VP of research and development at the company, “the Beast Burger is not trying to be a meat substitute. It is designed to become a new type of protein-rich food product that does not use soy or have any GMO products in them but could be used as a meat substitute for the center of one’s plate.”
Beyond Meat believes there is a better way to feed the planet. Geistliner said that the “mission is to create mass-market solutions that perfectly replace animal protein with plant protein.” It is “also dedicated to improving human health, positively impacting climate change, conserving natural resources and respecting animal welfare.” This captures well the thinking of Bill Gates and other Valley tech investors who have identified with this vision.
Another company with similar goals is Impossible Foods. This company has raised $75 million from VCs so far and like Beyond Meat. Its quest is to create a plant-based meat substitute with high protein that could be used to feed people all over the world.
According to CB Insights, in 2012, VCs and others invested $350 million into food tech companies or projects, and that amount is rising about 37% every year. With all this Silicon Valley investment, especially in companies trying to create meat alternatives, it seems that this has become one of the tech world’s next holy grails.
The event included two days of tastings from local chefs and as a food event it was spectacular. But the event’s more noble purpose was to get the food and tech world talking about the serious issue of world hunger and the challenge of feeding the planet in the future.
One of the big messages that came from the conference is that there are significant environmental consequences and health issues associated with eating too much red meat, sodium or sugar and sugar substitutes, and while world hunger is a major problem, so is obesity in many places around the world. They had some great sessions about “What are we doing to enable to the planet to feed 9 billion people by 2050,” as well as sessions titled “the Challenge of Food Waste” and a “Renewed Debate about GMO’s.”
The keynote speaker at the event was Chef José Andrés, who TIME named to its 100 most influential people in 2012. Andrés has become an activist in the food industry to get folks who work in food to find ways to deal with the world hunger challenge. He has also put his money where his mouth is, investing in the World Central Kitchen. Its website states that “World Central Kitchen is hard at work ’empowering the people’ to be part of the solution – with focus on building ‘smart kitchens,’ training on clean cookstoves, creating jobs, and strengthening local business.” Andrés spends around six weeks a year devoted to these types of projects and said he came to this event to challenge Silicon Valley executives to join the food industry’s quest to deal with the massive issue of feeding a hungry world.
Andrés gets very animated and passionate when he talks about one serious problem he sees that he believes we must deal with immediately. He said that at least 3 billion people in the world still cook using stones and wood fires. The smoke from these fires causes all kinds of health issues including cancer, cataracts and asthma and impacts the women and children who do most of the cooking for the family’s daily meal. It also impacts the girls in the family who spend up to three hours a day gathering the wood or fuel for the fire, sometimes in hostile areas where many have been attacked. He has become a chief advocate for what he calls “clean cook-stoves” and has backed the use of solar stoves and less harmful fuels to be used in these villages and towns where people’s only form of cooking is fire and smoke.
I spoke with Andrés after his keynote and he told me that “he strongly believes in the power of food as a change agent” and he is devoted to making the food world a serious contributor to being a major part of providing a solution for these particular world problems. While Silicon Valley has some investments in this area, it needs to do more in the way of actual financing of new food tech companies and do extended research in this area with goals that are aligned with Andrés and others who understand the magnitude of this problem and how it will affect the worlds future. Silicon Valley is known for its exceptional problem solving skills and I certainly hope that the tech execs who heard Chef Andrés’ plea will join him and others in the food industry to help deal with this massive world problem.
Tim Bajarin is recognized as one of the leading industry consultants, analysts and futurists, covering the field of personal computers and consumer technology. Mr. Bajarin is the President of Creative Strategies, Inc. and has been with the company since 1981 where he has served as a consultant providing analysis to most of the leading hardware and software vendors in the industry.
Correction: This article originally misstated the company behind the Beast Burger. It is Beyond Meat.
Researchers say there are sound and possibly scientific reasons to pay more attention to the month you were born in+ READ ARTICLE
“Whenever I present our work, I have to allow for laugh time,” says Nicholas Tatonetti, a scientist at Columbia University Medical Center.
Not a common practice for a serious academic researcher, but then again, Tatonetti studies something quite unfamiliar to those more accustomed to the intricacies of biological and molecular explanations for the human condition. “I study the month people were born in, to see if that changes their risk of developing disease in their entire lifetime,” he says. And in his latest report, published in the Journal of the American Medical Informatics Association, those results are pretty eye-opening.
By delving into the extensive database of patients seen at Columbia Medical Center over 14 years, beginning in 2000, Tatonetti and his team did a first-of-its kind look at whether birth month has anything to do with disease risk. Some previous studies have looked at the potential connection, but these investigations focused on individual conditions such as asthma and brain conditions, and therefore might have suffered from disease- or population-biases.
Tatonetti found that among 1,688 conditions for which patients were seen, 55 showed a strong relationship with birth month that could not be explained by chance alone. These included 20 conditions that were already described from previous, smaller studies, and 16 completely new associations. These included a surprisingly large number of heart-related diseases.
“Not only was it surprising that nobody had studied the relationship between heart disease and birth month yet, but we found not just one association but several with the same trend of increased lifetime risk of heart disease for those born in late winter and early spring,” says Tatonetti. “That’s suggestive of a mechanistic relationship, although we don’t yet know what that is.”
Earlier studies, for example, had connected birth in late summer or fall with asthma or respiratory problems, since mothers pregnant during the winter may be more likely to catch the flu or other respiratory infections. Tatonetti’s group is collaborating with 40 other institutions around the world to standardize patient electronic health records so the anonymized data can be studied for possible explanations of the birth month trends. The database will include environmental data as well, since it’s well known that environmental exposures — to things such as pollution, second hand smoke and more — can influence expectant moms and their developing fetuses.
He prefers to call what he does a study of seasonality rather than birth month. “Astrology puts a lot of stock on what month you were born in, and that really hurts this type of research, since there isn’t much scientific evidence to support that,” says Tatonetti. “But seasonality is a proxy for variable environmental factors present at the time of your birth, and we are learning more about the very large role that environment, and gene-environment interactions, plays in our development. This could be one way to start mapping out those gene-environment effects.”
To see which conditions you might be more vulnerable to developing, find your birth month in the wheel below.
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