Data-ism in the Information Era

June 25th, 2015

I just finished reading the book “Data-ism” by Steve Lohr (check this talk the author gave about the book) and it really changed how I view big data and its impact. In general, the concept of data-ism is useful in the business world, where many companies may not have gone much further than a big data approach to helping them aggregate or mine copious amounts of data for different applications and business processes. People say we never had so much information on people and things. New cloud hosting solutions and other sophisticated data systems, especially software, have also led to the rise of data skeptics, who push back against the idea that good data handling can provide infinite results without other types of planning. Big data refers to a process that is used when traditional data mining and handling techniques cannot uncover the insights and meaning of the underlying data. Data that is unstructured, time sensitive or simply very large cannot be processed by relational database engines or by one person. This type of data requires a different processing approach called big data analytics, which uses massive parallelism on readily available hardware. Quite simply, big data reflects the changing world we live in. The more things change, the more the changes are captured and recorded as data; mainly personal information. For example, where we bought our new shoes, how much we spent in credit cards, where we are in real time, etc. Take weather as an example. For a weather forecaster, the amount of data collected around the world about local conditions is substantial, but sometimes wrong. Weather forecast relies on statistics. Logically, it would make sense that local environments dictate regional effects and regional effects dictate global effects, but it could well be the other way around. One way or another, this weather data reflects the attributes of big data, where real-time processing is needed for a massive amount of data, and where the large number of inputs can be machine generated, personal observations or outside forces like sun spots or magnetism. However, getting to that Big Data payoff is proving a difficult challenge for many organizations. Big Data is often voluminous and tends to rapidly change and morph, making it challenging to get a handle on and difficult to access. The majority of tools available to work with Big Data are complex and hard to use, and most enterprises don’t have the in-house expertise to perform the required data analysis and manipulation to draw out the answers that the business is seeking. New technologies tend to spawn utopian and dystopian thinking in equal measure. For all his caveats about the unproven promise of big data, the book author Steve Lohr is clearly one of the enthusiasts. He has been captured by data-ism, evincing open admiration for those on its leading edge. Perhaps for this reason, he focuses more on the benign “stumbles” of big data than on the serious ones: the humorous mistakes of intelligent IBM’s artificially computer system, Watson, as it trained to compete on the game show “Jeopardy!” (check the article “In ‘Data-ism’ Steve Lohr gives his take on how Big Data will shape our future” from The Washington Post). Controversial or not, data-ism is affecting both Science and Technology since these areas are becoming more and more data-driven. One example is how we can sequence genomes and get other clinical information from patients using sensors. The collection of 100,000 data points per second for several variables in a patient, for example, needs software and big data analytics tools to make sense of the data. Science that is dependent on single individuals generating and interpreting the information is endangered. We are living the Data-driven scientific era. Hypothesis-driven science will disappear, and Institutions and Enterprises will dispute Data Scientists. Just as a glimpse on the impact of data, in the last decade we already generated more information than in all the rest of the humankind history combined. Be prepared for a future full of information! The challenge will always be making sense of too much data, especially in science… Well, but science was always challenging, wasn’t it?


A Tale of a Scientist turned into Entrepreneur

May 14th, 2015

I once read that entrepreneurship is a combination of science and art. In some ways this is true. The main principle to be a Scientist is to create a hypothesis (or several) based on what is already described and somehow change the “status quo” and/or “invent” something new that will become a Thesis. In science, the final product, in general, is the scientific publication. In fact, that could become an Intellectual Property (IP) if the discovery has an application in the market (sometimes even not having a direct application, researchers patent specific methods and discoveries just to be “protected”; academia is highly competitive). Starting a company has some parallels to a Scientific Project: 1) you need lots of energy, creativity and knowledge; 2) Using this knowledge you need to ask questions; 3) You have to “create” something new that needs to be impactful (a new hypothesis, for example); 4) Based on the “creation” you need to test that hypothesis; 5) The hypothesis needs to be experimented (a new product in the market for example) and 6) a review of the data collected and a conclusion needs to be “drawn”. The same rules and principles could be applied in both science and to start a company (for more information check “The Scientific Method for Entrepreneurs: 6 Steps to Long-Term Success”). In some cases, you even need to pivot when the scientific project and your hypothesis proves to be wrong. Well, in some ways, this is my story – a scientist turned into entrepreneur. Not an easy task and I am still on it. I started my career with dreams of becoming famous and even winning a Nobel Prize (so naive at that time…). I did a Bachelor’s in Biology with a Major in Biochemistry, then a Ph.D. or Doctorate in Genetics (specifically in cancer epigenetics) and then moved to the United States to do a Post-Doctoral training (if you did not read my Intro in this Blog I am from Brazil and lived in the United States for 10 years). In summary, my academic professional life was: Bachelor’s Degree, check; Ph.D. in one of the best places in Brazil, check; Post-Doctoral training in Boston at Harvard University, check. After that, I’ve moved to Chicago and did a second Post-Doctoral training. That is when things started to change and the fairy tale became more like a nightmare. Unfortunately, when doing my second Post-Doctoral training at Northwester University the economic crisis hit the United States (around 2008-2009) and funds for research got slim. In parallel, to help cope with my deep frustration with the scientific system and how it became broken (for more information on how the scientific system is broken check my blog post “Science is Broken: How, Why and When?”), I co-founded a company and got involved in several company Incubators, Accelerators, Mentoring, etc, entering a new world that was totally different from the Academic System I was used to. What have I learned transitioning from academia to starting a company? I’ve learned that Innovation is the key connection between Science and Entrepreneurship, BUT this is applied differently in both fields. Why is that? Can we try to innovate academically and privately with similar outcomes? It depends. Academia expects that the ideas you generate and test with hypothesis to get public with scientific publications of articles (sometimes with patents) and startups (and the private sector in general) expect that the ideas that become “products” have legal protection before getting out to the public (companies are for profit in a world of capitalism). In my case, I continue to navigate both worlds since they have parallels. The bottom line is that it is possible to develop something impactful in Academia and transform that in a successful company. In doing that you can disrupt a market or create a new market. For example, Elizabeth Holmes, the founder of Theranos, envisioned a way to reinvent old-fashioned phlebotomy and, in the process, usher in an era of comprehensive superfast diagnosis and preventive medicine. That was a decade ago, when Holmes dropped out of Stanford University and founded Theranos with her tuition money (check the article about this history here “This Woman Invented a Way to Run 30 Lab Tests on Only One Drop of Blood”). Her company now is worth U$ 9 Billion Dollars and she innovated creating new and cheaper ways of doing blood tests. This is an example of success. I am still trying to find the key to success applying the academic knowledge into entrepreneurship. Maybe one day I will find my way. Who knows?

The Science of Networks

March 30th, 2015

Networks are everywhere. From the Internet to networks in economics, networks of disease transmission, etc, the imagery of the network pervades our modern culture. What exactly do we mean by a network? What different kinds of networks are there? And how does their presence affect the way that events happen? In the past few years, a diverse group of scientists and researchers, including mathematicians, physicists, computer scientists, sociologists, and biologists, have been actively pursuing these questions and building in the process the new research field of network theory, or the “science of networks”. The study of networks has had a long history in mathematics and natural sciences. Briefly, in 1736, the great mathematician Leonard Euler became interested in a mathematical riddle called the Königsberg Bridge Problem. The city of Königsberg was built on the banks of the Pregel River in what was then known as Prussia, and on two islands that lie in midstream. A popular brain-teaser of the time asked, “Does there exist any single path that crosses all seven bridges exactly once each?” Legend has it that the people of Königsberg spent many fruitless hours trying to find such a path before Euler proved the impossibility of its existence. In the 1780s, Euler invented network theory and for most of the last two hundred years, network theory remained a form of abstract mathematics. A network is made up of nodes and links and mathematicians assumed the links between the nodes were randomly distributed. If there exist, let’s say, 10 nodes and 50 links, they assumed the distribution would be random and each node would get, on average, five links. For years, mathematicians explored the properties of these random-distribution networks. Nowadays, we see the Internet as a source of networks: of people, of groups, of hashtags at Twitter, of social clusters at Facebook, etc. The Internet was originally designed by the American Military to be randomly distributed with no pattern in order to create a communications network that could survive an attack. In the 1990s, physicists began studying the internet because it was an example of a network in which all the nodes and links could be tracked. Computer scientists soon realized that the Web was not randomly distributed. Maps of the web showed that some nodes had huge numbers of links, while most nodes had only a few links. In biomedicine, the impacts of networks have just recently been tackled. In my article in 2013, on the cover of the journal Drug Discovery Today, I wrote that “Social networks can be seen as a nonlinear superposition of a multitude of complex connections between people where the nodes represent individuals and the links between them capture a variety of different social interactions. In addition, “…the emergence of different types of social networks has fostered connections between individuals, thus facilitating data exchange in a variety of fields.” (see my review article “Social networks, web-based tools and diseases: implications for biomedical research”). Networks of people and how to make sense of it are the hot wave today. A social network is a social structure made up of individuals (or organizations) called “nodes”, which are tied (connected) by one or more specific types of interdependency, such as friendship, kinship, common interest, financial exchange, dislike, sexual relationships, or relationships of beliefs, knowledge or prestige (for more information check “Social Network Analysis – Theory and Applications”). One can identify a person and the connections a specific person has, how influential he or she is and what social interactions a person has. In addition, the science of networks has been applied for businesses since companies that embed themselves into the social network of an industry by creating lots of contacts (links or nodes of the network) to other companies, suppliers, industry magazines, customers, government, and workers will have a tendency to grow, because the node with the most links will get more links. In life sciences, the science of networks transforms data collection into actionable information that will improve individual and population health, deliver effective therapies and, consequently, reduce the cost of healthcare. These novel tools might also have a direct impact in personalized medicine programs, since the adoption of new products by health care professionals in life sciences and peer-to-peer learning could be improved using social networks (see more at my article “The Impact of Online Networks and Big Data in Life Sciences”). Thus, the science of networks could also help the industry gain insights into how people use and react to pharmaceuticals and medical devices; and how they benefit from them. Such accumulation of information could be applied into the product development process as a “lean” process to test new products. The impact of the science of networks and social networking are immensurable in the scientific and biomedical communities. It is just the beginning for this area of research and I believe that there is a lot more to come. Welcome to the Networking Era!

Brazil, Soccer & Science

February 6th, 2015

Brazil is changing. Once the soccer country with five World Cup Trophies, it lost to Germany in the last World Cup in 2014 and did not impress the world like it used to. Soccer is changing. European countries, especially Germany, have been training, building infrastructure and a lower base of young professionals that was able to win big last year. Following this trend, science is also changing. Brazil won the first “big league” prize in a scientific field – the Brazilian Artur Avila won the Fields Medal in Math in 2014. This International Prize is comparable to the Nobel Prize, but in this case for Mathematics. Brazil never won a Nobel Prize in Science or in any field. We are a developing country that plays soccer well. But, not anymore… In this blog post I will discuss how Brazilian Soccer and Science have been changing. I will also discuss examples of scientists that have International recognition and do research in Brazil or in the United States. Brazil is still a poor country with several problems; bureaucracy, corruption, lack of investments, violence and poor education. But, as a Brazilian, I’ve learned one thing after living abroad for a decade: we are very creative people. We can solve problems in a different way. There is also an expression for this in portuguese: “jeitinho brasileiro”. Last year Brazil lost the biggest tournament and a source of hope in a country full of maladies: the Soccer World Cup. Brazil lost in the semi-finals to Germany in the most outrageous game score ever: 7×1. Who would imagine that? Is Brazil loosing the “jeitinho brasileiro” in Soccer? The answer is yes. What makes a country good at soccer? (for more read “The Score” article about this subject). The answer is that there is no formula or rule. If you can’t study or be educated you just go and play soccer with your friends in your neighborhood. It is simple like this. But that is somehow changing. The country has changed. Artur Avila showed last year, the same year we’ve lost the World Cup in the worst manner ever, that we can win big in Science (for more check the Fields Medal Website: “A Brazilian Wunderkind Who Calms Chaos”). He won the most prestigious International Prize in Math studying the Chaos Theory. This indicates a trend: Brazil is getting better at science and loosing the soccer skills. This can’t be quantified right now, it is just my “very” subjective observation. In my last blog post I have criticized science in general and how the system is broken (for more see “Science is Broken”). And it is. But, there are some things happening here and there. Artur Avila is an example of a scientist living in Brazil (he travels to Paris, France every month to lecture and do projects in collaboration in Europe but resides in Brazil). Another example is the Brazilian Scientist living in the United States Miguel Nicolelis. He has everything to do with soccer. His research provided the resources necessary to build a machine-man interface that was used in the World Cup’s first game (see the TED Talk by Miguel Nicolelis: “Brain-to-Brain Communication has arrived”). He is a Professor at Duke University and is building a Neuroscience Program and Institute at the city Natal in Brazil. He built a Mind-controlled robotic suit that a paralyzed patient was wearing to do the first kick in the opening game of the World Cup. That is an example of a scientist from Brazil living abroad that is researching amazing things in the field of neuroscience. He was able to unite the passion of Brazil, soccer, to science (for more information check “World Cup to Debut Mind-Controlled Robotic Suit”). Thus, things have been changing in the soccer country. Maybe that is a good sign: we are getting better in science and worse in soccer. Using our minds, not just our legs to play. I believe this is just a tendency, but it is definitely a big change for Brazil. Brazil is doing science better for sure. The best part is that with less and less resources. But we, Brazilians, are creative. We always find ways to make things work.

Science is Broken: How, Why and When?

November 17th, 2014

The title of this blog post is something that has been discussed a lot in the last months. The scientific system is broken everywhere and there is no easy solution to fix it. Well, three years ago, in 2011, I wrote a blog post after an Interview to the scientific journal Nature Medicine (see my interview here “Brazilians lured back home with research funding and stability”) about differences on how to do science in the United States and Brazil. At that time, I was in a limbo and stayed there until now. (For my entire blog post check out “My thoughts on Biomedicine in Brazil”). At that time, things were already shaky and federal funding was collapsing with cuts from budgets and the economic crisis in the United States. Brazil had a good economic prognosis and growth. Guess what? I am back to Brazil after working as a Post-Doc, Research Scientist, etc, etc in the United States. I am back not because things in Brazil are or have been better in Academia or Science, because they are not. I am back because the United States is in a huge scientific crisis. A recent article in the Boston Globe discusses (check the entire article entitled “Glut of postdoc researchers stirs quiet crisis in science”) that the lives of humble biomedical postdoctoral researchers was never easy mainly because of the obscurity in a low-paying scientific apprenticeship that can stretch more than a decade (exactly the timeframe I spent training in the United States). The long hours of work are not worth it for the expected reward and the chance to launch an independent laboratory and do science that could expand human understanding of biology and disease is slim nowadays. There is a bulk of very well and smart post-docs with Ph.D.s in Biomedical Science that are getting stuck in the eternity of a “Post-Doctoral Fellow”. And if the person is lucky to have funds from the government, the laboratory they work or from family donations they can do science. If they do not have it, they are in a limbo. In my case, I am very thankful for the Maeve McNicholas Family that lost a daughter with a brain tumor and have donated resources and money for 7 years to maintain my research in Chicago (for more on the Maeve McNicholas Memorial Foundation and also to donate click here). Matt and Denise McNicholas are the most wonderful people I ever met. From a very sad and burdening fact – loosing a child – they created a Foundation under their child’s name and also constructed a park with Maeve’s name. This makes a big difference now that federal funding is getting slim (check this NPR piece on the situation right now “Top Scientists Suggest A Few Fixes For Medical Funding Crisis”). Foundations such as The Bill and Melinda Gates, The Michael J Fox, and others can and will make the difference right now. I am not sad because I left the United States and will start my career from zero in Brazil. I am just frustrated for a generation of young investigators that cannot share their ideas in a totally closed system from the Medieval times. Science is broken and needs a fix right now! I also created a group on Facebook named “Science is Broken” to help reshape this broken system. Things are so bad right now that a group of scientists even wrote an article in PNAS (a well respect journal from the United States Academy of Science) giving suggestions for fixing the broken scientific system since they see lots of bright people leaving science to pursue other careers. A whole generation of very bright and smart people will choose not to go in a scientific and academic career because all they hear is that scientists, especially Post-Docs, are struggling and will struggle for a long time. The authors of the PNAS piece (for the entire article check out “Rescuing US biomedical research from its systemic flaws”) discuss that the long-held but erroneous assumption of never-ending rapid growth in biomedical science has created an unsustainable hypercompetitive system that is discouraging even the most outstanding prospective students from entering our scientific profession and making it difficult for seasoned investigators to produce their best work. The authors suggest that all the scientists; especially the ones with well-established laboratories, should rethink fundamental features of the whole biomedical research ecosystem. Specific suggestions are: 1) Planning for predictable and stable funding on science and 2) Bringing the biomedical enterprise in sustainable equilibrium by educating graduate students early on, by broadening the career path for young scientists, by changing the way post-doctoral fellows are trained and using more staff scientists. They also suggest a new way of evaluating the performance for scientific accomplishments of well-established researchers with more teaching and web-based tools. In addition, they question that the whole grant submission and analysis system needs to be changed. I believe the situation is really bad and complex. Since Medieval times science is done the same way. We need re-evaluations and changes that will impact now and not for future generations of researchers. The way things are going on in Academia, there will not be a next generation. People have lives, families and hobbies. Science is a devotion like religion for some, but things are changing. We, and by we I say all young scientists, have bills to pay and a whole life in front of us. We deserve respect and better paychecks! We deserve better opportunities! Science is broken but I will not follow this path. I am back in Brazil and will start a new life. Thank you America for these ten years of training at Harvard and Northwestern Universities and for not offering me a decent academic job in your land. I still have hope that this is not a goodbye forever. Changes are needed and time will tell if I will be back to the United States of America. For now, I will enjoy the weather and the summer in Brazil and fight for science here. (Photo by Toban Black)

Business Cards, Science and Personal Marketing

September 5th, 2014

The business card is a staple in most industries, it is how we show our face and who we are, but they are much less prevalent in science, particularly in the academic community. For many of us, the thought of handing out business cards congers up images of slimy douchebags at cheesy networking events. And when it comes to scientific events, everybody stares at you with a funny face. Yet, the reality is far from that fear.  The business card is a powerful professional tool that deserves serious consideration in all sectors, especially among scientists. Business cards are not just for business people. Consider the business card as a product of directed evolution in your career. Whether we’re aware of it or not, we spend a lot of time as scientists trying to figure out how to make our research stand out from the crowd, don’t have much time for networking needless to say distribute cards and make personal marketing.  We read the literature to figure out what’s been done in the past; we go to conferences to hear what others are working on and what is going on in our field; and we write grants targeting projects we think we can complete before anyone else.  It is indeed a stressful life with very few rewards and we all know it. That stuff is not easy at all. Yet, we often overlook the importance of standing out personally when meeting new colleagues, collaborators or potential employers. Luckily for us, most graduate students, postdocs and professors don’t use business cards.  Therefore, handing a card to a potential postdoctoral advisor will leave quite an impression.  In an industry like academic science where business cards are not provided to everyone upon hire, having one stands out. A card says you’re serious about your career path and take pride in doing it well. Building business cards involve two easy steps: 1) Design and 2) Production. For the first step of design, if you are in the academic sector, go to your Department and ask for one. Every institution is responsible to produce one to every scientist; even Ph.D. students and Post-Docs. If you are in the private sector, your boss needs to ask for a business card for you, so you can “show your face” when dealing with clients and/or in meetings. You can also design your own and there are plenty of websites and easy ways to do it. For example, BIZCard, Vistaprint and PrintsMadeEasy are three of the more well-known sites. Twenty bucks will get you more cards than you can give out and between frequent promotional deals on these sites, you can often get them much cheaper. I believe that scientists need and should have business cards. I have been to uncountable meetings and conferences where I would ask for somebody’s business card and the person would say “I do not have one. Do I need one?” These examples are mostly in the Academic Sector. Business cards represent your personal marketing and these days this could mean everything, even to get a new and better job. So, if you are a scientist, go ahead and make your own business card. It is about time!

Diabetes, Obesity and Genetics

July 18th, 2014

Doctors and researchers have found that obesity and diabetes are connected. People who are obese are at high risk for developing Type 2 diabetes (also known as “insulin-resistant” or “adult-onset” diabetes), particularly if a close family member is affected with diabetes. Therefore, it becomes very important to maintain a healthy body weight throughout your life in order to protect yourself from developing a chronic disease like diabetes. Researchers have also determined that only a slight predisposition for obesity is inherited. For example, the best way for children to avoid being overweight is to eat a diet that is balanced and is low in fat. This diet should consist of lots of fresh fruits and vegetables. Snacks like chips, cookies, ice cream, and soft drinks should be limited or eliminated. This may require a lifestyle change in a person’s life. It is very important that all children become involved in physical activities on a daily basis. Too many children spend their free time in front of computers, television, and video games, and this results in a growing number of kids who are obese and who will likely suffer medical consequences of obesity as adults. In order to become a diabetic, two factors need to be present. First, you need to inherit a predisposition to the disease, and second, the environment must trigger a response in your body. Your genes alone are not enough. This has already been shown in studies of groups of identical twins: when one of a pair of twins develops diabetes, there is only a slightly increased chance that the other sibling will develop the disease. Because identical twins are genetically similar, the environment of the individual might play a role in the development of diabetes. However, because both genetics and the environment are shared by family members, we recognize that people with a family history for diabetes have a greater risk for developing the disease. Another factor are epigenetic marks that change with diet and the environment. Molecular biology has shown the genetic and epigenetic basis for the development of both diseases. In recent years, expanded knowledge of the human genome has led to the development of new tools that facilitate the simultaneous analysis of thousands of genes for complex diseases. Researchers now rely on such tools in their search to uncover the gene networks associated to conditions such as diabetes and obesity. Today, geneticists use a number of forward approaches (for example, approaches that seek to find the genetic basis of a phenotype) in their efforts to understand how gene networks may contribute to these diseases. One such method is the genome-wide association study or GWAS; this high-throughput approach allows geneticists to scan the entire human genome in an unbiased manner, using statistical methods to determine associations between chromosomal loci and a given phenotype. For example, a recent genome-wide association study has reproducibly associated variants within introns of the gene FTO with increased risk for obesity and type 2 diabetes (for more information see “Obesity-associated variants within FTO form long-range functional connections with IRX3” by Smemo et al). Mutations in introns (noncoding regions) of the gene FTO have been widely investigated after genome-wide association studies revealed a strong link between FTO and diabetes. Yet, overexpressing or deleting FTO in animal models affects whole body mass and composition, not just fat, and experiments have failed to show that these obesity-linked introns affect the function of the FTO gene itself. Diabetes and obesity are directly involved since body fat and metabolism are strongly connected. This study showed that not just proteins are associated to obesity, but also non-coding regions such as enhancers and introns. Conformational changes in the DNA and epigenetics (mostly linked to diet and environmental exposure) might be the answer to better understand both diseases. However, until we completely uncover the mysteries of the genetics of metabolism, the best choice is to eat healthy and live well, independent on genetic predisposition and background. Like they say; you are what you eat. So, eat well and exercise.




Human Evolution and the Birth of Medicine

May 29th, 2014

There is no discussion: human and apes are close relatives with a common ancestor. Evolution studies confirm this hypothesis with different fossils differing in age with traces of genomic DNA and molecular features between these two species. Social science in apes also tells us that they are always in groups, have a structure of hierarchy and respect such as human societies. However, some questions remain, such as how primates deal with diseases and pain. In many traditional societies around the world people are very dependent in plants for both food and medicine. Close to a century ago, for example, a Tanzanian medicine man, Babu Kalunde, discovered an important treatment that saved the lives of many people in his village, who were suffering an epidemic of a dysentery-like illness. He learned about the potential medicinal value of a plant known as mulengelele by observing a sick animal eat the roots of the plant. This is a fact: animals in the jungle have to learn about medical plants and how to self-medicate. And this feature passes from generation to generation with parents teaching youngsters what to eat when they feel specific types of pain. Most of the details about two types of self-medicative behaviorin the great apes – namely, bitter-pith chewing and leaf swallowing – come from three study sites, Mahale and Gombe inTanzania and Kibale in Uganda, although these behaviors have been documented from 10 additional sites across Africa. The geographical, ecological, and climatic variation of these sites is great, ranging from low-elevation, moist tropical forest and woodland to forest. Such wide variation in geography, ecology, and climate where leaf swallowing and bitter-pith chewing are known to occur suggests that great ape populations elsewhere on the continent might also engage in these behaviors (for more information see “Self-Medicative Behavior in the African Great Apes: An Evolutionary Perspective into the Origins of Human Traditional Medicine” by Michael A. Huffman). Primates generally self-medicate with plants in the jungle and teach others what to eat depending on the pain. Specific plants for stomach pain are always shown to members of the community and offspring. The strong similarities in plant selection criteria among the African great apes in response to parasite infection and gastrointestinal upset, and the common use of some plants by chimpanzees and humans to treat such illnesses, are tantalizing evidence for the birth and evolution of medicine. Our earliest hominid ancestors may have exhibited some similarities in plant selection criteria with both extant apes and modern humans. Although the fossil record provides no direct evidence concerning specific feeding behavior and diet, it seems reasonable to hypothesize that early hominids would have displayed at least the range of extant ape self-medicative behavior. It appears that the fundamentals of perceiving the medicinal properties of a plant by its taste, smell, and texture have their roots deep in our primate history. A major turning point in the evolution of medicine is likely to have been the advent of language in early humans, which enabled people to share and pass on detailed experiences about plant properties and their effects against disease. That probably was the birth of medicine on earth. Since then, medicine continues to evolve, but if we go back to the jungle, primates use the same medical plants for generations to treat different types of pain. I believe we can learn a lot from them, especially to accelerate the development of new drugs for specific diseases. The bottom line is that primates are smarter than we think…



The Acquisition Boom in Technology

March 26th, 2014

In this post, I will leave science behind and discuss the technology “craziness” that has been happening. Billion Dollar acquisitions of companies that not even have revenue or profit. The Internet revolution now is eccentric and transforms youngsters with an app idea in millionaires and billionaires from day to night.  In less than 2 months, for example, Facebook acquired Whatsapp, the Drone maker Titan Aerospace and now the virtual reality company Oculus. A mix of software and hardware and new technologies are becoming the sexiest thing to acquire nowadays. Companies with tons of cash such as Facebook, Apple, Microsoft, Google, Yahoo and others can choose what to buy and how to buy. We are living in the new era of the internet. Working in Wall Street in the  financial district getting millions in investment deals is not the big American Dream anymore. The dream is to have an idea, build a start up and sell it for millions or billions of dollars to the big ones. Or even grow it to become the next Facebook or Google. One interesting case is Whatsapp, that was sold to Facebook by around 16 billion dollars. If you think about it, this is a lot of money, but strategically, it was a bold move. Whatsapp has no revenue whatsoever or even sell adds. It is simple, just a messaging app, but the number of Users builds its value. Let’s make the math: Facebook has around 1.2 billion users and of these probably millions use Whatsapp or have an account of it. However, millions that use Whatsapp (which is probably 200 million people) doesn’t have a Facebook account. Thus, Facebook indirectly bought new users that Whatsapp has to incorporate in its platform. I use Whatsapp to message people from family, friends and colleagues and see the trend in txt messaging. It is simple, useful, and the bottom line is that it does the job. Another example is Google buying Nest for 3 billion dollars. As its own early dive into wearables with Google Glass demonstrates, Google knows it can’t miss this next big leap in hardware. And Nest provides what they want in terms of geolocation of thermostats. The last big move occurred these days with Facebook buying the virtual reality company Oculus by 2 billion dollars. This is another example of a software company buying a hardware company. Facebook believes Oculus has the potential to be the most social platform ever by enabling sharing not just moments with your friends online, but entire experiences and adventures. This might be a competitive move by Facebook towards Google Glass Platform. Since after the burst of the bubble of the internet in the beginning of 2000, we have been watching another bubble of tech internet companies popping up and acquisitions of billions occurring. It has been all about strategy and new technology, not profits or revenue increase. The companies that are in the big “club” such as Facebook, Apple, Google, Yahoo and Microsoft are positioning themselves in a competitive scenario. The only question is who is going to be successful in the long run with these acquisitions. There is a promising future in the tech sector. Are we close to the movie “Minority Report” with virtual reality? Facebook believes so. We will see.

“Dallas Buyers Club” and HIV testing

February 3rd, 2014

What would you do if you were tested positive for HIV in a routine blood exam? Well, this question came up after I saw the movie Dallas Buyers Club. The movie portrays the life of Ron Woodroof, who was a Texas cowboy and drug user and was diagnosed with AIDS in the 1980s. He was initially given 30 days to live, but Woodroof (portrayed by actor Matthew McConaughey) begins taking azidothymidine (AZT), the only HIV drug legally available in America at that time. Woodroof goes on to travel the world, searching for medications that will keep him alive, and as a result, the Dallas Buyers Club is formed.  With the help of a doctor and another patient played by Jared Leto as a transsexual, Woodroof begins selling smuggled drugs out of a motel in Dallas, providing HIV-positive patients with alternative forms of treatment for their disease, since the FDA was still testing the drugs that are currently used. Interestingly, the storyline closely reflects the real life events of Ron Woodroof and provides a great example of how patient advocacy hastened the development of effective HIV medications during the 80s. I watched the movie and it was clear how the process of drug approval and lab testing is still rudimentary. Coming back to my question in the beginning of this blog post, what if your HIV test comes back positive? Well, what if I say that the standard tests done for HIV have problems with numerous false-positives? The main and most widely test used is an immunoassay called ELISA that measures antibodies against the virus. However, viruses are very similar and have building blocks or proteins that look alike. So, when you measure antibodies against a response of the human body for a viral infection, false-positives can occur. Indeed, I am writing this post to give people awareness that, for example, flu vaccination could cause a false positive for HIV. Like I said, the viruses are very similar. The HIV GP160 protein exists in several viruses and has a lot of similar regions (see more at this report on the New England Journal of Medicine “Influenza Vaccination and False Positive HIV Results”). This protein is present in other virions too, especially a variety of flu related viruses. Thus, vaccination against any type of flu could generate a cross-reaction in the aforementioned immunoassay. In fact, there are several reports and groups of discussion online in which the most discussed subject is a false positive test result for HIV. Yes, that is scary and weird, but it is more common that we imagine. Given the escalating international awareness of various influenza strains and flu vaccination, it is very important for clinicians and patients to keep in mind that influenza vaccination may cause cross-reactivity with HIV antibody assays. The time course for such cross-reactivity remains mostly uncertain, but could be for months. If your HIV test was positive, take into account this possibility and ask for the use of a nucleic acid amplification test instead of the “Western blot” assay to confirm the enzyme immunoassay. People should and need to be aware of that. The movie Dallas Buyers Club just reminded me how science and research can be misleading within its own “rules”. Ron Woodroof tried to overcome these rules to save lives and himself. We all need to take care of ourselves, of course, using the law to do it. The take home message is that we still do not understand enough about the biology of viruses and confusions such as the one I discuss here could happen. So be aware!