Tag Archives: Nir Peled

Sniffing out disease (Na-Nose)

The ‘artificial nose’ is not a newcomer to this blog. The most recent post prior to this is a March 15, 2016 piece about Disney using an artificial nose for art conservation. Today’s (Jan. 9, 2016) piece concerns itself with work from Israel and ‘sniffing out’ disease, according to a Dec. 30, 2016 news item in Sputnik News,

A team from the Israel Institute of Technology has developed a device that from a single breath can identify diseases such as multiple forms of cancer, Parkinson’s disease, and multiple sclerosis. While the machine is still in the experimental stages, it has a high degree of promise for use in non-invasive diagnoses of serious illnesses.

The international team demonstrated that a medical theory first proposed by the Greek physician Hippocrates some 2400 years ago is true, certain diseases leave a “breathprint” on the exhalations of those afflicted. The researchers created a prototype for a machine that can pick up on those diseases using the outgoing breath of a patient. The machine, called the Na-Nose, tests breath samples for the presence of trace amounts of chemicals that are indicative of 17 different illnesses.

A Dec. 22, 2016 Technion Israel Institute of Technology press release offers more detail about the work,

An international team of 56 researchers in five countries has confirmed a hypothesis first proposed by the ancient Greeks – that different diseases are characterized by different “chemical signatures” identifiable in breath samples. …

Diagnostic techniques based on breath samples have been demonstrated in the past, but until now, there has not been scientific proof of the hypothesis that different and unrelated diseases are characterized by distinct chemical breath signatures. And technologies developed to date for this type of diagnosis have been limited to detecting a small number of clinical disorders, without differentiation between unrelated diseases.

The study of more than 1,400 patients included 17 different and unrelated diseases: lung cancer, colorectal cancer, head and neck cancer, ovarian cancer, bladder cancer, prostate cancer, kidney cancer, stomach cancer, Crohn’s disease, ulcerative colitis, irritable bowel syndrome, Parkinson’s disease (two types), multiple sclerosis, pulmonary hypertension, preeclampsia and chronic kidney disease. Samples were collected between January 2011 and June 2014 from in 14 departments at 9 medical centers in 5 countries: Israel, France, the USA, Latvia and China.

The researchers tested the chemical composition of the breath samples using an accepted analytical method (mass spectrometry), which enabled accurate quantitative detection of the chemical compounds they contained. 13 chemical components were identified, in different compositions, in all 17 of the diseases.

According to Prof. Haick, “each of these diseases is characterized by a unique fingerprint, meaning a different composition of these 13 chemical components.  Just as each of us has a unique fingerprint that distinguishes us from others, each disease has a chemical signature that distinguishes it from other diseases and from a normal state of health. These odor signatures are what enables us to identify the diseases using the technology that we developed.”

With a new technology called “artificially intelligent nanoarray,” developed by Prof. Haick, the researchers were able to corroborate the clinical efficacy of the diagnostic technology. The array enables fast and inexpensive diagnosis and classification of diseases, based on “smelling” the patient’s breath, and using artificial intelligence to analyze the data obtained from the sensors. Some of the sensors are based on layers of gold nanoscale particles and others contain a random network of carbon nanotubes coated with an organic layer for sensing and identification purposes.

The study also assessed the efficiency of the artificially intelligent nanoarray in detecting and classifying various diseases using breath signatures. To verify the reliability of the system, the team also examined the effect of various factors (such as gender, age, smoking habits and geographic location) on the sample composition, and found their effect to be negligible, and without impairment on the array’s sensitivity.

“Each of the sensors responds to a wide range of exhalation components,” explain Prof. Haick and his previous Ph.D student, Dr. Morad Nakhleh, “and integration of the information provides detailed data about the unique breath signatures characteristic of the various diseases. Our system has detected and classified various diseases with an average accuracy of 86%.

This is a new and promising direction for diagnosis and classification of diseases, which is characterized not only by considerable accuracy but also by low cost, low electricity consumption, miniaturization, comfort and the possibility of repeating the test easily.”

“Breath is an excellent raw material for diagnosis,” said Prof. Haick. “It is available without the need for invasive and unpleasant procedures, it’s not dangerous, and you can sample it again and again if necessary.”

Here’s a schematic of the study, which the researchers have made available,

Diagram: A schematic view of the study. Two breath samples were taken from each subject, one was sent for chemical mapping using mass spectrometry, and the other was analyzed in the new system, which produced a clinical diagnosis based on the chemical fingerprint of the breath sample. Courtesy: Tech;nion

There is also a video, which covers much of the same ground as the press release but also includes information about the possible use of the Na-Nose technology in the European Union’s SniffPhone project,

Here’s a link to and a citation for the paper,

Diagnosis and Classification of 17 Diseases from 1404 Subjects via Pattern Analysis of Exhaled Molecules by Morad K. Nakhleh, Haitham Amal, Raneen Jeries, Yoav Y. Broza, Manal Aboud, Alaa Gharra, Hodaya Ivgi, Salam Khatib, Shifaa Badarneh, Lior Har-Shai, Lea Glass-Marmor, Izabella Lejbkowicz, Ariel Miller, Samih Badarny, Raz Winer, John Finberg, Sylvia Cohen-Kaminsky, Frédéric Perros, David Montani, Barbara Girerd, Gilles Garcia, Gérald Simonneau, Farid Nakhoul, Shira Baram, Raed Salim, Marwan Hakim, Maayan Gruber, Ohad Ronen, Tal Marshak, Ilana Doweck, Ofer Nativ, Zaher Bahouth, Da-you Shi, Wei Zhang, Qing-ling Hua, Yue-yin Pan, Li Tao, Hu Liu, Amir Karban, Eduard Koifman, Tova Rainis, Roberts Skapars, Armands Sivins, Guntis Ancans, Inta Liepniece-Karele, Ilze Kikuste, Ieva Lasina, Ivars Tolmanis, Douglas Johnson, Stuart Z. Millstone, Jennifer Fulton, John W. Wells, Larry H. Wilf, Marc Humbert, Marcis Leja, Nir Peled, and Hossam Haick. ACS Nano, Article ASAP DOI: 10.1021/acsnano.6b04930 Publication Date (Web): December 21, 2016

Copyright © 2017 American Chemical Society

This paper appears to be open access.

As for SniffPhone, they’re hoping that Na-Nose or something like it will allow them to modify smartphones in a way that will allow diseases to be detected.

I can’t help wondering who will own the data if your smartphone detects a disease. If you think that’s an idle question, here’s an excerpt from Sue Halpern’s Dec. 22, 2016 review of two books (“Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy” by Cathy O’Neil and “Virtual Competition: The Promise and Perils of the Algorithm-Driven Economy” by Ariel Ezrachi and Maurice E. Stucke) for the New York Times Review of Books,

We give our data away. We give it away in drips and drops, not thinking that data brokers will collect it and sell it, let alone that it will be used against us. There are now private, unregulated DNA databases culled, in part, from DNA samples people supply to genealogical websites in pursuit of their ancestry. These samples are available online to be compared with crime scene DNA without a warrant or court order. (Police are also amassing their own DNA databases by swabbing cheeks during routine stops.) In the estimation of the Electronic Frontier Foundation, this will make it more likely that people will be implicated in crimes they did not commit.

Or consider the data from fitness trackers, like Fitbit. As reported in The Intercept:

During a 2013 FTC panel on “Connected Health and Fitness,” University of Colorado law professor Scott Peppet said, “I can paint an incredibly detailed and rich picture of who you are based on your Fitbit data,” adding, “That data is so high quality that I can do things like price insurance premiums or I could probably evaluate your credit score incredibly accurately.”

Halpern’s piece is well worth reading in its entirety.

The gold beneath your skin (artificial skin, that is)

Artificial skin that can sense as if it were real skin isn’t here yet but scientists at Technion-Israel Institute of Technology have created a flexible sensor that could fulfill that promise. From a July 9, 2013 news item on Azonano,

Using tiny gold particles and a kind of resin, a team of scientists at the Technion-Israel Institute of Technology has discovered how to make a new kind of flexible sensor that one day could be integrated into electronic skin, or e-skin.

If scientists learn how to attach e-skin to prosthetic limbs, people with amputations might once again be able to feel changes in their environments. The findings appear in the June issue of ACS Applied Materials & Interfaces.

The July 8, 2013 American Technion Society news release by Kevin Hattori, which originated the news item, describes the problems with developing flexible sensors that can mimic natural skin,

Researchers have long been interested in flexible sensors, but have had trouble adapting them for real-world use. To make its way into mainstream society, a flexible sensor would have to run on low voltage (so it would be compatible with the batteries in today’s portable devices), measure a wide range of pressures, and make more than one measurement at a time, including humidity, temperature, pressure, and the presence of chemicals. In addition, these sensors would also have to be able to be made quickly, easily, and cheaply.

Here are more details about the sensor and about how the researchers created it,

The Technion team’s sensor has all of these qualities. The secret is the use of monolayer-capped nanoparticles that are only 5-8 nanometers in diameter. They are made of gold and surrounded by connector molecules called ligands. In fact, “monolayer-capped nanoparticles can be thought of as flowers, where the center of the flower is the gold or metal nanoparticle and the petals are the monolayer of organic ligands that generally protect it,” says Haick.

The team discovered that when these nanoparticles are laid on top of a substrate – in this case, made of PET (flexible polyethylene terephthalate), the same plastic found in soda bottles – the resulting compound conducted electricity differently depending on how the substrate was bent. (The bending motion brings some particles closer to others, increasing how quickly electrons can pass between them.) This electrical property means that the sensor can detect a large range of pressures, from tens of milligrams to tens of grams. “The sensor is very stable and can be attached to any surface shape while keeping the function stable,” says Dr. Nir Peled, Head of the Thoracic Cancer Research and Detection Center at Israel’s Sheba Medical Center, who was not involved in the research.

And by varying how thick the substrate is, as well as what it is made of, scientists can modify how sensitive the sensor is. Because these sensors can be customized, they could in the future perform a variety of other tasks, including monitoring strain on bridges and detecting cracks in engines.

According to research team leader Professor Hossam Haick the new sensor is more sensitive (x 10 or more) in touch than existing touch-based e-skin.

Here’s a link to and a citation for the published paper,

Tunable Touch Sensor and Combined Sensing Platform: Toward Nanoparticle-based Electronic Skin by Meital Segev-Bar , Avigail Landman, Maayan Nir-Shapira, Gregory Shuster, and Hossam Haick. ACS Appl. Mater. Interfaces, 2013, 5 (12), pp 5531–5541 DOI: 10.1021/am400757q Publication Date (Web): June 4, 2013

Copyright © 2013 American Chemical Society

The paper is behind a paywall.