DECCAN HERALD 3
Tuesday, May 9, 2017
Spectrum science
NON-INVASIVE DIAGNOSIS
A new nuclear magnetic resonance technique has the potential for non-invasive disease diagnosis using the current MRI technology, reveals a new report.
Machines that can smell illness reLiabLe CHeCKups For decades, researchers have been trying to figure out ways of building an inexpensive odour sensor for quick, reliable and non-invasive health diagnoses. the field finally seems to be on the cusp of succeeding, reports Kate Murphy
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lindfolded, would you know the smell of your mom, a lover or a co-worker? Not the smells of their colognes or perfumes, not of the laundry detergents they use — the smells of them? Each of us has a unique ‘odourprint’made up of thousands of organic compounds. These molecules offer a whiff of who we are, revealing age, genetics, lifestyle, and hometown — even metabolic processes that underlie our health. Ancient Greek and Chinese medical practitioners used a patient’s scent to make diagnoses. Modern medical research, too, confirms that the smell of someone’s skin, breath and bodily fluids can be suggestive of the illness. The breath of diabetics sometimes smells of rotten apples, experts report; the skin of typhoid patients, like baking bread. But not every physician’s nose is a precision instrument, and dogs, while adept at sniffing out cancer, get distracted. So, researchers have been trying for decades to figure out how to build an inexpensive odour sensor for quick, reliable and non-invasive diagnoses. The field finally seems on the cusp of succeeding. Convergence of technology “You’re seeing a convergence of technology now, so we can actually run large-scale clinical studies to get the data to prove odour analysis has real utility,” said Billy Boyle, co-founder and president of operationsatOwlstone,amanufacturerofchemical sensors in Cambridge, England. Billy, an electronics engineer, formed the company with two friends in 2004 to develop sensors to detect chemical weapons and explosives for customers, including the US government. But when Billy’s girlfriend and eventual wife, Kate Gross, was diagnosed with colon cancer in 2012, his focus shifted to medical sensors, with an emphasis on cancer detection. Kate died at the end of 2014. That she might still be alive if her cancer had been detected earlier, Billy said, continues to be a “big motivator.” Owlstone has raised $23.5 million to put its odour analysis technology into the hands of clinicians. Moreover, Britain’s National Health Service is funding a 3,000subject clinical trial to test Owlstone’s sensor to diagnose lung cancer. The sensor is a silicon chip stacked with various metal layers and tiny gold electrodes. While it looks like your mobile phone’s SIM card, it works like a chemical filter. The molecules inanodoursamplearefirstionised—given a charge — and then an electric current is used to move only chemicals of diagnostic interest through the channels etched in the chip, where they can be detected. “You can programme what you want to sniff out just by changing the software,” Billy said. “We can use the device for our own trials on colorectal cancer, but it can also be used by our partners to look for other things, like irritable bowel disease.” The company also is conducting a 1,400subject trial, in collaboration with the University of Warwick, to detect colon cancer from urine samples, and is exploring whether its chips can help determine the best drugs for asthma patients by sorting through molecules in their breath. A similar diagnostic technology is being developed by an Israeli chemical engineer,
BODY SCENT MATTERS Modern medical research confirms that the smell of someone’s skin, breath and bodily fluids can be suggestive of the illness. PHOTO CREDIT: VIKTOR KOEN/NYT
Hossam Haick, who was also touched by cancer. “My college roommate had leukaemia, and it made me want to see whether a sensor could be used for treatment,” said Hossam, a professor at Technion-Israel Institute of Technology in Haifa, Israel. “But then I realised early diagnosis could be as important as treatment itself.” His smelling machine uses an array of sensors composed of gold nanoparticles or carbon nanotubes. They are coated with ligands, molecular receptors that have a high affinity for certain biomarkers of disease found in exhaled breath. Once these biomarkers latch onto the ligands, the nanoparticles and nanotubes swell or shrink, thus changing how long it takes for an electrical charge to pass between them. This gain or loss in conductivity is translated into a diagnosis. Better diagnosis With artificial intelligence, he said, the machine becomes better at diagnosing with each exposure. Rather than detecting specific molecules that suggest disease, however, Hossam’s machine sniffs out the overall chemical stew that makes up an odour. It’s analogous to smelling an orange: Your brain doesn’t distinguish among the chemicals that make up that odour. Instead, you smell the totality, and your
Hossam Haick’s smelling machine uses an array of sensors composed of gold nanoparticles.
brain recognises all of it as an orange. Hossam and his colleagues published a paper in ACS Nano in December 2016 showing that his artificially intelligent nanoarray could distinguish among 17 diseases with up to 86% accuracy. There were a total of 1,404 participants in the trial, but the sample sizes for each disease were quite small. And the machine was better at distinguishing among some diseases than others. In the United States, a team of researchers from the Monell Chemical Senses Centre, Philadelphia and the University of Pennsylvania received an $815,000 grant in February from the Kleburg Foundation to advance work on a prototype odour sensor that detects ovarian cancer in samples of blood plasma. The team chose plasma because it is somewhat less likely than breath or urine to be corrupted by confounding factors like diet or environmental chemicals, including cleaning products or pollution. Instead of ligands, their sensors rely on snippets of single-strand DNA to do the work of latching onto odour particles. “We are trying to make the device work the way we understand mammalian olfaction works,” said Charlie Johnson, director of the Nano/Bio Interface Centre at the University of Pennsylvania, who is leading the fabrication effort. “DNA gives unique characteristics for this process.” In addition to these groups, teams in Austria, Switzerland and Japan also are developing odour sensors to diagnose disease. “I think the fact that you’re seeing so much activity both in commercial and academic settings shows that we’re getting a lot closer,”said Cristina Davis, a biomedical engineer and professor at the University of California at Davis, USA, who also is helping to develop an odour sensor to diagnose disease. “My estimate is it’s a three- to five-year time frame”before such tools are available to clinicians, she added. The researchers may be competing intensely, but all see possibilities for saving lives. “There’s a lot of good work going on out there,” Charlie said. “It will be interesting to see who comes out on top.” The New York Times
applying swarm intelligence to study molecules inspired by nature researchers are looking into how swarm intelligence can be used to determine the most stable configuration of a molecule, write rishabh shukla & spoorthy raman
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an that line of ants on the wall, or the flock of flying birds help us decipher the properties of a very large molecule? Yes, say scientists from the Indian Institute of Technology (IIT) Bombay, IIT Kanpur, IIT Guwahati and the Indian Association for the Cultivation of Science, Kolkata. In a recent study, they have described how the concept of swarm intelligence can be used to determine the most stable configuration of a molecule and its electronic structure. With this knowledge, scientists can design molecules with targeted properties for application in drugs, vaccines and polymers. This study was published in the International Journal of Quantum Chemistry. Swarm intelligence is a behaviour exhibited by simple ‘agents’ that interact with one another and with their environment by following a set of simple rules. These interactions, over time, lead to the emergence of an ‘intelligent’ global behaviour, unknown to the individual agents. For example, if you look at a single ant, it may not come across as smart enough or powerful enough to carry a big insect to its nest. However, when many ants from the colony come, the task seems doable! Many forms Now, the researchers of the study, led by Professor Shankar Prasad Bhattacharyya from IIT Bombay, have developed an evolutionary algorithm based on the concepts of swarm intelligence to calculate the energy configuration and electric charge distribution in a molecule of polythiophene, a polymer, on doping it at various levels. These polymers have excellent electrical conductivity and optical properties with dramatic colour shifts in response to changes in solvent, temperature, applied potential, and binding to other molecules. Hence, they are used as sensors in many applications. Every molecule consists of a group of atoms linked together by chemical bonds. The structure of the molecule is expressed in terms of the length and the angle of these chemical bonds formed between different atoms. A molecule can have various physical forms and properties based on the arrangement of its constituent atoms. For example, the high surface tension of water and the ability to dissolve many particles is because of the physical and electrical properties of the chemical bonds between two molecules of hydrogen and one molecule of oxygen. Such an arrangement of atoms in a particular configuration also corresponds to different energy levels of the molecule. Lower energy levels imply higher stability
of the configuration. These energies, when plotted against geometrical parameters, like bond length and angle, give rise to a potential energy surface in an ndimensional space. Each point on this surface corresponds to a unique structure having a particular level of energy and electronic structure. Search efficiency It is challenging to determine the global minimum potential energy point of a molecule and its electronic charge distribution simultaneously due to presence of multiple local maximum and minimum potential energy points. To address this challenge, the researchers have applied the technique of swarm intelligence. “To search for a global minimum point on a function, we can have multiple agents, known as swarm particles, exploring the space and communicating with each other to optimise the search efficiency,” says Rishabh Shukla from IIT, Guwahati, and the study’s lead author. So how does swarm intelligence work in this context? “Let’s say we start with 10 or 20 swarm particles with random positions and random initial velocities that will move in the n-dimensional space of the molecule of interest. While traversing their path, they will remember the point with minimum energy configuration found by them so far, called ‘individual best point’. If they come across a point, which is better than the individual best point, then it is updated. In addition, the swarm remembers its global best point. If an individual best point is found to be better than global best point, then global best point is updated,” explains Rishabh. Furthermore, the velocity of each particle is updated based on current velocity, its distance from the individual best point, and its distance from the global best point. This way, the swarm is continuously going towards better points and finally reaches the true global minimum, he adds. This study is a unique attempt to apply techniques of swarm intelligence to the study of molecular structures. “The work signifies that collective intelligence displayed by classical swarms can be exploited to search through the space of the nuclear degrees of freedom and bring in simultaneous evolution of the electronic charge distribution. The net outcome is a mixed quantum classical method that smoothly and simultaneously locates the global minimum energy configuration of nuclei and the associated electron density distribution in a large molecule,” concludes Professor Shankar. (The authors are with Gubbi Labs, a Bengaluru-based research collective)
CHALLENGING The swarm intelligence technique has been used to determine the global minimum potential energy point of a molecule. REPRESENTATIVE IMAGE
Latest LHC anomaly points at possible new particle
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he latest in a series of anomalies spotted in five-year-old data from the Large Hadron Collider (LHC) could pointthewaytoanentirelynewelementary particle, physicists hope. The most recent finding, reported at a seminar on April 18 at CERN,Europe’sparticle physics lab near Geneva, Switzerland, may turn out to be a statistical fluctuation that fades as new data is analysed. But it is intriguing because it seems to jibe with previously reported oddities. And it matches the predictions of new physics that some theorists had already made based on those earlier reports. Particular short-lived particles called Bmesons, created when the LHC smashes protons together, seem to be decaying in unexpected ways, Simone Bifani at the University of Birmingham in England, told physicists at the CERN seminar. The Standard Model of particle physics predicts that pairs of matter-antimatter particles should be among the B-mesons’ decay products — and specifically that electron-
positron pairs and muon-anti-muon pairs should be found in roughly equal numbers. (The muon is a heavy cousin of the electron.) But researchers see more of the electron-positron pairs, Simone said, based on data collected at the collider’s LHCb experiment. This could just be a statistical fluke, says Guy Wilkinson, a physicist at the University of Oxford in England and the spokesman for LHCb. In the latest study, researchers looked at two separate groups of data from LHCb on B-meson decays, and in each case found an anomaly with a statistical significance below 2.5 sigma (a measure of statistical confidence). That falls far short of the 5 sigma threshold usuNEW ELEMENTARY PARTICLE? Physicists are debating whether data from the LHCb, ally needed to claim a “discovery.” But the LHCb has already spotted a shown here, hints at a new particle, or is just a statistical artefact. PHOTO CREDIT: CERN number of similar anomalies related to meson decay, Guy notes, and in particular strange things happening over the last five searchers. CERN physicist André David, with various types of B-mesons. None is years,” he says. Some LHC physicists are for example, tweeted that “piling up a sigstatistically significant yet, but they point not so sure that the announcement was ma here and a sigma there”does not make in the same direction. “There have been worth the buzz it has received among re- for a discovery.
Still, theorists had already been positing new physics based on the earlier findings. And excitingly, the latest B-meson decay results are consistent with these ideas, says theorist David Straub at the Technical University of Munich. Straub posted a paper to the arXiv website on April 18 analysing the latest meson-decay results. Five other theory papers have also been posted, and more are likely to follow. “The community waswatchingtheseresultswithquitesome interest,” says Juan Rojo, a theorist at the Free University of Amsterdam.
of a ‘leptoquark’, a boson that would share some properties with both leptons and quarks. Neither of these particles occurs in theorists’favourite schemes for extending the Standard Model, but researchers say that if they exist, the LHC’s bigger experiments — ATLAS and CMS — should be able to create them directly, rather than looking at their effects on the decays of other particles. The LHCb’s latest analysis is entirely based on data from the LHC’s first run, whichendedinearly2013whenthecollider shutdownforanupgrade.Sincethecollider reopened in 2015 for its second run, LHCb and the other experiments have gathered considerablymoredata.SeveralmorestudiesofB-mesondecayarenowunderway.So, beforetheendoftheyear,themysterymight be solved. “We have enough data on tape to validate or disprove these effects. The truth will be revealed soon,”says Guy.
Solving the mystery The most obvious way to explain the results — if they are not a statistical fluke — is that as B-mesons decay, novel particles not predicted in the Standard Model make a fleeting appearance that affect the decay products, the six papers agree. One possibility is that there could be a heavier cousin of a particle known as the Z boson, called Davide Castelvecchi Z’. Another explanation is the existence The New York Times