Yearly Archives: 2020

Professor Irit Ben Aharon

A first-of-its-kind study examining the assumption that cancer patients are an at-risk group for COVID-19 finds that these patients do not get infected any more than the general population and do not suffer from more severe disease symptoms. In fact, based on their findings, the researchers hypothesize that cancer treatments may affect the patients’ response to COVID19-induced “cytokine storm.”

From the moment the COVID-19 pandemic broke out, medical teams around the world operated under the assumption that cancer patients were an at-risk group in terms of contracting the virus. Defining cancer patients as an at-risk group had far-reaching implications for their treatment – this without any prior scientific basis. Patients were afraid to seek treatment for fear of contracting the coronavirus in hospitals, and in some countries, guidelines were issued for postponing oncology treatments in certain situations.

A new study conducted by researchers at Rambam Medical Center and the Technion reveals surprising findings, namely that cancer patients may not be associated with the broad range of at-risk groups of people suffering from morbidities. The research was led by Professor Yuval Shaked, head of the Rappaport  -Technion Integrated Cancer Center (R-TICC) and Professor Irit Ben Aharon, director of the Division of Oncology at Rambam and principal investigator at the R-TICC, in collaboration with Dr. Tal Goshen-Lago, head of the Translational Research Division of Oncology at Rambam. The findings were published in Cancers, in a special edition dealing with the impact of the coronavirus on cancer patients.

The study included 271 participants, including 164 cancer patients, who came to the Rambam Medical Center to receive ongoing treatment for their disease, and a control group of 107 healthy employees among the medical staff. In the study, which was conducted between March and June 2020, all participants underwent blood tests, at three different times, to examine changes in the profile of the immune system. The test monitored three antibodies – IgG, IgM and IgA – that represent antibody formation at different times of virus exposure.

“We were surprised to find that cancer patients and health subjects developed antibodies at similar rates,” said Prof. Ben Aharon. “2.4% of cancer patients who participated in the study and 1.9% of participants in the healthy control group developed antibodies for the coronavirus and all were asymptomatic. Moreover, throughout the entire study period, no symptomatic coronavirus patients were detected in the study population and among the general population of our oncology patients.” According to Prof. Ben Aharon, the CyTOF technology was used to map immune system cells, and a significant difference was found between the immune profile of cancer patients who were positive for coronavirus antibodies and the immune profile of the positive staff members.

“Our hypothesis is that the different response of cancer patients to the disease is related to the fact that anti-cancer treatment changes the profile of the immune system,” said Prof. Shaked. “The myeloid cells, which are vital cells in the immune system, are severely damaged by the coronavirus. In the general population and in the medical staff that participated in the study, the virus reduces the rate of myeloid cells by about 90%; in cancer patients, however, it reduces them by only 50%. This fact gives cancer patients relative protection.”

Prof. Yuval Shaked

Prof. Ben Aharon added that the hypothesis is that anti-cancer treatments may change the profile of the immune system and its function which may limit the ability of the coronavirus to induce severe inflammation in patients receiving these treatments. The researchers estimate that this is why the proportion of cancer patients with non-hematological malignancies who develop severe disease is relatively low compared to that of the general population according to the literature, and that severity may be affected by other comorbidities. The mechanism for this observation is being further explored nowadays. 

The research was supported by the Israel Cancer Research Fund (ICRF) and the European Research Council (ERC grant).

Prof. Irit Ben Aharon is a doctor and researcher and head of the Oncology Department at the Rambam Health Care Campus.

Prof. Yuval Shaked is head of the Technion Integrated Cancer Center in the Rappaport Faculty of Medicine (R-TICC). The center, established in 2016, promotes research that combines basic, clinical and engineering science in favor of developing new tools for cancer diagnosis, treatment and follow-up.

Click here for the paper in Cancers 

Exhibition winner Lidan Fridman

Fourth-year students were displaying their work at the annual project exhibition held at the Faculty of Biomedical Engineering last week, which took place this year online.

Student exhibits included systems for predicting epileptic seizures, mood tracking in cancer patients, and systems for the prevention of sudden death in athletes. The first prize was awarded to Lidan Fridman, who developed an innovative technology for an accurate physiological diagnosis of hearing loss.

“The display of the projects is the peak event of the year at the Faculty, and reflects our pursuit of close, continuous collaboration with the industry.” said Faculty Dean Prof. Shulamit Levenberg. “The projects on display are the epitome of many months of tackling practical challenges, complex technical difficulties and our requirement that students present meaningful solutions to real-world problems.”

The project course is led by Prof. Nati Korin. Projects were ranked by thirty judges, including Technion faculty members and researchers, entrepreneurs and senior executives in the biomed industry. As has been the custom each year, the prizes were contributed by entrepreneurs Doron and Liat Adler of Sanolla.

The Winners

Awards included five prizes for excellence, an entrepreneurship prize, and a people’s choice prize. As mentioned, the first prize was won by Lidan Fridman, who, under the supervision of Prof. Dvir Yelin and Ph.D. student Matan Hamara, developed a system for the diagnosis of early-stage hearing loss. According to Lidan, “Today, the diagnosis is to a great extent reached on the basis of information provided by the patient, a fact that introduces a subjective element to the process. Here, we have developed a compact system that creates high-resolution images of vibrations of the tympanic membrane, and is likely to be of help in the future in detecting hearing problems and more accurately diagnosing their causes”. The two major components of the system are the device’s housing and the software required for an analysis of the results, and Fridman hopes that within the next few years, the development will progress to clinical trials followed by subsequent widespread use.

The second prize went to Yael Zaffrani, who, under the supervision of Prof. Moti Freiman, developed a technology for the early diagnosis of Crohn’s Disease. She says, “The doctor diagnoses the current condition of the diseased bowel on the basis of numerous MRI images, but because the bowel is a convoluted organ it is hard to monitor its anatomy and reach an accurate, data-based decision”. Based on the MRI images, the system developed by Zaffrani provides the doctor with a single image that displays the bowel in the form of a straight and taut organ, free of convolutions, allowing for the detection of symptoms of severe inflammation with relative ease.

The third prize was won by Maya Hershko, who, under the supervision of Prof. Avi Schroeder of the Wolfson Faculty of Chemical Engineering, developed a technology designed to inhibit the uncontrollable proliferation of cancerous cells using nanoparticles.

The fourth prize went to Niv Rebhun and Sofia Rozenberg, who, under the supervision of Dr. Yoav Madan, developed a prosthetic hand for transhumeral amputations. The product is tailored to meet patient-specific needs, is relatively simple and easy, and does not require a lengthy learning curve. The project was executed with the assistance of the Haifa 3D nonprofit organization.

The fifth prize for excellence went to Worud Abu Alasal and Elia Khamesy, who executed their project under the guidance of Prof. Tzipi Kraus of the Faculty of Education in Science and Technology. The two studied the mother-child brain to brain synchrony during joint storytelling by measuring brain activity in ten pairs of mothers and children in Arab society and demonstrated that storytelling creates a stronger synchrony compared to other shared activities.

The people’s choice prize was won by Ayelet Lotan and Opal Nimni, who, under the supervision of Prof. Yael Yaniv, developed a wearable (non-invasive) digital technology for early diagnosis of heart disease.

In addition to the above prizes, the Faculty also awarded the entrepreneurship prize. This prize seeks to invite students into the world of entrepreneurship and encourage them to devote thought to business development and the realization of their developments through commercialization. The prize was won by Marina Tulchinsky, Roni Keshet and Ori Shahar for their Vocal Vibes – a remote speech therapy technology. The group was supervised by Dr. Oscar Lichtenstein and Shaked Ron, winner of the first prize in last year’s project contest. Vocal Vibes is a system that streamlines the work of the speech therapist through remote diagnosis and treatment – goals that have acquired special importance during the current COVID-19 crisis. The information originates in sensors embedded in a special collar worn by the user, and in recordings and photographs taken by a mobile phone. The new technology demonstrated its ability to diagnose dysphonia, a voice disorder in which the vocal cords do not function properly, resulting in an impaired voice, with 88% accuracy.

The development of entrepreneurship in the Faculty is being spearheaded by Dr. Yael Rozen, a consultant on applied research in the Faculty of Biomedical Engineering at the Technion. The students’ investor presentations were judged by Dr. Amir Toren, CTO and Business Development Director at New Generation Technology’s (NGT) incubator; Dr. Gideon Meiri, CEO of NanoMedTech, and Dr. Judith Zilberstein, CEO of the Alon Med-Tech incubator.

Technion – Israel Institute of Technology was the only Israeli institution among the top 30 leading institutions on the ranking of the ICML International Conference on Machine Learning this year. The ICML is the most important conference in the world in the field of computational learning. Competing digitally this summer, universities and companies were ranked according to the number of articles accepted at the conference.

The prestigious list of 30 is led by Google, followed by a significant margin by MIT. The Technion is ranked in the middle of the list – at 15th place, ahead of hi-tech giants such as Amazon and IBM, and ahead of universities such as Cornell and Georgia Tech.

An additional  ranking of the leading countries was also published, according to the number of articles contributed out of 1,088 articles received at the conference. The list is led by the United States; followed by a significant margin by Britain and China, with Israel ranked 8th – ahead of Japan, Singapore, India and others. Israel contributed 42 articles, with the majority (23) coming from the Technion.  

According to Prof. Irad Yavneh, former Dean of the Faculty of Computer Science and Director General of the Samuel Neaman Institute (SNI) at the Technion, “Israel plays an important role in machine learning, and ICML conference data provide quantitative evidence of this fact. At the Technion, it is very important for us to continue to develop knowledge in this vital field, and to that end, we encourage interdisciplinary and inter-departmental research.”

The Technion articles accepted for the conference were written by multidisciplinary researchers from the Center for Machine Learning and Intelligent Systems. The Technion has been consistently ranked as one of the best universities in the world in the field of machine learning, as reflected through other platforms such as the csrankings.

Due to the Coronavirus Pandemic, and to ensure the safety of all, this year’s doctoral award ceremony at Technion – Israel Institute of Technology took place virtually.

The main ceremony of doctoral awards took place on Wednesday, September 16, at 6:30 PM.

Asst. Prof. Yehonadav Bekenstein

Asst. Prof. Yehonadav Bekenstein of the Technion Department of Materials Science and Engineering has been awarded an ERC Starting Grant – a prestigious European grant for young academic faculty. With a total value of 677 million euros this year, the ERC grants are awarded as part of Horizon 2020, which is an innovation program within the European Union. The grants support brilliant young scientists in building winning research teams to conduct pioneering research. 

Microphotograph of domain structure of lead bromide perovskite thin film made by fluorescence mode in a microscope

Dr. Bekenstein received the grant for the development of halide perovskites materials. These special materials are characterized by high efficiency in energy conversion and are expected to revolutionize optoelectronic applications such as advanced detectors, solar energy, and even quantum communication. Unlike widely-used semiconductors (such as silicon and germanium), halide perovskites are only slightly affected by the presence of defects in the material, so they are effective in devices that require high efficiency. In a joint study with colleagues from Berkeley and Harvard, Dr. Bekenstein has already created perovskite nano-crystals in the form of dots, wires and plates. The control over the shape and dimensions of these materials determines the physical properties and enables their incorporation into devices for the benefit of man. The ERC funded study will focus on combinations of two-dimensional perovskites with other materials such as oxides and semiconductors to discover new functional properties.

Dr. Bekenstein completed his degrees in physics and chemistry at the Hebrew University of Jerusalem and his postdoctoral fellowship at the University of California, Berkeley, before joining the Technion faculty in 2018. Over the years, he has won numerous awards including the Käte and Franz Wiener Prize for excellence in a doctoral thesis, the prestigious Rothschild Scholarship for postdoctoral fellows, and the Alon Fellowship for supporting young scientists.

Neurofibromatosis mouse model shows impaired structural and functional brain connectivity that is rescued by targeted therapy.

New research conducted by Prof. Itamar Kahn of the Technion’s Rappaport Faculty of Medicine in Israel and Prof. Nancy Ratner of Cincinnati Children’s Hospital Medical Center (CCHMC) demonstrates a potential new treatment for cognitive impairments that are associated with disruption in the brain fibers that connect distal regions, also known as the brain white matter. The research shows that treating neurofibromatosis type 1 (NF1), a common genetic disorder, with a drug targeted at an abnormal cellular pathway that is critical for normal white-matter formation, rescues functional and structural connectivity and is thought to potentially alleviate some of the cognitive impairments seen in NF1.

Professor Itamar Kahn

The groundbreaking research, “Brain-wide structural and functional disruption in mice with oligodendrocyte-specific Nf1 deletion is rescued by inhibition of nitric oxide synthase,” was published in PNAS, the official journal of the National Academy of Sciences of the United States. Technion MD/PhD candidate Jad Asleh and Tel Aviv Medical Center neurosurgeon Dr. Ben Shofty (a former PhD student in the lab) were co-lead authors.

Prof. Nancy Ratner

By using a cell specific, hormonal triggered, genetically engineered mouse model, the team was able to confine disease manifestation to white matter producing cells (oligodendrocytes) and consequently directly examine the contribution of abnormal myelination to neurological disorders.

In this study, the international team demonstrated that disruption to normal myelin, which in the mouse model used here fails to tightly wrap the axons, the fibers that connect brain regions, leads to a motor deficit that corresponds to fine motor coordination deficits seen in some individuals with NF1. In addition, structural connectivity (as measured by structural MRI), and functional connectivity (as measured by functional MRI) are both impaired in these mice. Importantly, Prof. Ratner demonstrated in previous studies that nitric oxide synthase inhibitor to reduce the abnormally high levels of nitric oxide in these mice rescues function at cellular level. Here, the team demonstrated that it also ameliorates the abnormalities seen using MRI further support that this treatment may be effective in treating cognitive impairments in NF1 patients and that MRI can be used to gauge the success of the treatment.

This study further emphasizes the role of abnormal white matter in brain disorders and suggests a potential targeted therapy for NF1-associated myelin abnormalities. Based on the results of previous work from Prof. Ratner and this study, a preliminary clinical study is currently in progress to test the safety of this drug treatment and its potential in treating the cognitive impairments in NF1 pediatric patients.

For the full article in PNAS click here

Technion Researchers have developed an innovative mapping system for blind pedestrians. The study was carried out by Achituv Cohen, a doctoral student in the Transportation and Geo-Information Engineering division of the Technion Faculty of Civil and Environmental Engineering under the supervision of Asst. Professor Sagi Dalyot.

According to the World Health Organization, there are currently more than 40 million visually impaired people around the world. This population copes with many daily challenges, some of which are related to traveling within urban spaces. When walking, various environmental features pose danger: stairs, bicycles and cars, physical obstacles on the sidewalk, and more. These severely restrict mobility and independence, affecting the quality of life. There are existing technologies that improve visually impaired pedestrian mobility to some degree by indicating nearby road obstacles. However, those technologies lack significant information about the surrounding space.

The study, published in the journal Environment and Planning B: Urban Analytics and City Science, examined the possibility of using OpenStreetMap to map spatial data relevant to blind pedestrians while calculating optimized walking routes. OpenStreetMap is an open-source mapping infrastructure based on crowdsourcing of geographic data contributed by citizens all over the world. OpenStreetMap provides maximum flexibility in terms of inserting, editing, and analyzing. It also integrates accumulated mapping data and spatial information.

In his study, Achituv developed a route calculation software for generating walking routes adapted to the needs of blind pedestrians. The study included an in-depth investigation, observations, and interviews with orientation and mobility instructors, as well as with blind individuals. The fieldwork resulted in a clear definition of spatial criteria that best reflect aspects of mobility, accessibility, and safety, defined by four primary parameters: geometric complexity of the route; route type and what it is used for; route length, and; landmarks along the route. Other features were also integrated, such as accessibility of traffic signals. 

The software weighs the environmental and semantic data that are important to the vision impaired, with an emphasis on safe, accessible, and navigable routes. These criteria enable qualitative and quantitative examination of the various available road segments between the starting point and the destination, determining the level of accessibility and safety, thus recommending the most optimized route. The developed software was tested by blind volunteers and an orientation and mobility guide in several locations. Not only were the routes recommended by the new software identical to the routes defined by an experienced guide, but the volunteers noted that, in most cases, the route chosen by the software was indeed more accessible and safer for walking than the routes calculated by existing commercial software, such as Google Maps. 

These findings indicate that the software is an effective and useful tool, improving the lives of visually impaired individuals in terms of mobility, accessibility, and independence.

Click here for the paper in Environment and Planning B.

The collaboration yielded an innovative electronic receiver and satellite computer for the ADELIS-SAMSON Project;

Three nano-satellites are to perform autonomous formation flight

August 25, 2020 – A close technological and research collaboration between the Technion – Israel Institute of Technology and Israel Aerospace Industries (IAI) has yielded an advanced electronic receiver that constitutes a unique development in the nano-satellite category. The collaboration was part of Technion’s ” ADELIS-SAMSON” project, in which three nano-satellites will be launched into space in December. The three satellites, which will fly in an autonomous formation without human intervention, are tasked with receiving signals from Earth and detecting their precise location for search and rescue, remote sensing, and environmental monitoring missions. The software and algorithms that control the flight were developed at Technion’s Distributed Space Systems Lab in the Asher Space Research Institute.

Hovik Agalarian, Chief Electronics Engineer of the Asher Institute of Space Research, with the new receiver

The electronic receiver, developed and built especially for the ” ADELIS-SAMSON” project by Elta Systems, an IAI division and subsidiary, picks-up, identifies, and records signals from Earth. It comprises an information processing system that calculates the location of the transmission. The miniature system was developed particularly for nano-satellites in order to extend the scope of the missions they can perform. The system integrates with the three mission computers developed by IAI’s MABAT Division.

The ” ADELIS-SAMSON” project is headed by Professor Pini Gurfil, head of the Asher Space Research Institute and a faculty member in Technion Faculty of Aerospace Engineering and with the support of the ADELIS Foundation and the Israel Space Agency in the Ministry of Science and Technology

“We worked closely with IAI engineers on this development for more than five years,” said Prof. Gurfil. “The project showcases the benefits of academy-industry collaboration, which yielded an outstanding result in the form of an innovative space-borne system. We thank IAI engineers for their professionalism and commitment. The system we co-developed places ADELIS-SAMSON at the forefront of nano-satellite technology.”

IAI CEO, Nimrod Sheffer, said, “The new development will help promote a new space research area. Collaboration with the Technion and other academic institutions is invaluable to us, as it promotes academic research and our future technological ventures. The receiver developed for this project offers a new way for space geo-location of ground electromagnetic signals. It is based on IAI’s extensive engineering know-how and experience in satellites, electronic warfare, intelligence interpretation systems, and communication networks.”

Asher Space Research Institute researchers who worked with IAI’s engineers in the project included Avner Kaidar, Hovik Agalarian, Eviatar Edlerman, Dr. Alex Frid and Prof. Pini Gurfil.

The ADELIS-SAMSON project is supported by the ADELIS Foundation, the Goldstein Foundation, and Israel’s Space Agency. Other parties involved in the project include Israel’s Space Agency, RAFAEL, and IAI.

Professor Roi Reichart

A computational method developed at the Technion in Israel significantly improves the prediction of the basketball players’ performance. The study was led by doctoral students Amir Feder and Nadav Oved under the supervision of Professor Roi Reichart of the William Davidson Faculty of Industrial Engineering & Management.

Predicting an athlete’s performance is a research challenge that has long been pursued by researchers around the world, utilizing tools from psychology, statistics, computer science, and more. Until now, performance predictions have mainly relied on the limited prediction factor of the athlete’s past performance. The Technion researchers, however, have added a new predictive factor: “out-of-game” information, specifically – transcripts of pre-game interviews with the players. The concept and study have been published in the journal Computational Linguistics.

The researchers hypothesized that pre-game interviews contain important information that can improve predictions about a player’s behavior and performance in an upcoming game. The rationale is that a given player’s in-game behavior is very difficult to predict, as the activity takes place in a complex and dynamic space. Performance is influenced by the environment, rational decisions, and internal emotions. In turn, the dynamic environment at a game also influences those emotions. These dynamics cannot be predicted solely based on past performance.

Doctoral student Amir Feder

The study was based on a dataset consisting of pre-game and post-game media interviews alongside in-game performance metrics from the game following the interviews.  The dataset entailed 5,226 performance interview pairs of 36 prominent NBA players. Each of the pairs was assessed by the relationship between the interview and performance. Specifically, the relationship was measured through the correlation between the transcript of the interview and deviations in the performance indicators in the game – risk characteristics, behavior, and strategic decisions. An example of a risk is an attempt to make a long-range basket (three-point range). An example of behavior and strategy is choosing a defense approach.

The researchers designed several models, utilizing state-of-the-art deep neural networks for players’ actions prediction based on the language used in their open-ended interviews. The models are capable of both making predictions based on interview text alone, or a combination of interview text and past-performance metrics. The text-based models outperformed strong baselines based on performance metrics alone, demonstrating the importance of language for action prediction. The models that used both interview texts and players’ past performance metrics improved on some of the most challenging predictions and produced the best results.

Doctoral student Nadav Oved

For example, in a pre-game interview before the 2016 NBA Finals, LeBron James, then with the Cleveland Cavaliers, was asked about his mental state and how he was feeling based on his personal history (James was born in Cleveland, and returned to the team to bring its first championship). James described his positive mental state and concentration and feelings of ease going into the games. Accordingly, Prof. Reichart explained, “Our models processed the text and guessed that James’ offensive performance would be better than his past averages. In practice, the 2016 Finals series ended with Cleveland’s first – and only – winning championship. In these games, James surpassed himself and starred throughout the series, as our models predicted. ”

Chart: NBA player performance prediction accuracy. Columns from left to right: Dataset majority baseline – naive prediction method; Metric-only baseline – prediction based on past performance only; prediction based on interviews (method developed by Technion researchers); prediction on interviews and past performance.

Figure: Prediction accuracy of the model per player, relative to its accuracy for all players (black line), for each prediction task. Points to the right indicate better than average prediction.

COVID-19 testing is a key step in gaining control over the spread of the pandemic. Current molecular COVID-19 tests entail swab samples, shipping the samples to lab facilities, and a time-consuming laboratory procedure to determine results. As a result, there is a delay of several to many days between when tests are taken, and results are obtained. The delay – exacerbated by the overloading of laboratories – increases the chance of further spread, especially from pre-symptomatic individuals who may not adhere to quarantine. Moreover, overloading laboratories has created a burden on the healthcare system.

Professor Hossam Haick

Epidemiological data show that the COVID-19 pandemic propagates through “local community transmission.” This means that the spread of infection cannot be accurately traced back to a source. There is a need for a non-invasive, rapid, inexpensive testing method to screen COVID-19 positive individuals – especially pre-symptomatic or asymptomatic carriers. Such a test could significantly reduce the rate of transmission – saving lives.

A team led by F.M.W Academic Chair Professor Hossam Haick and Dr. Yoav Broza of the Technion Faculty of Chemical Engineering and Russell Berrie Nanotechnology Institute, in collaboration with researchers from Wuhan, China, has devised a novel breath analyzer test to rapidly detect the disease caused by the novel coronavirus. The testing device is an intelligent nanotechnology that can rapidly detect COVID-19 from specific volatile organic compounds (VOCs) in exhaled breath. The study is published in the journal ACS Nano and the technology is to be developed for the market by the company Nanose Medical.

The efficacy of the COVID-19 breath analyzer testing device, which is comprised of a nanomaterial-based sensor array, was successfully validated in March by a preliminary case-control clinical study in Wuhan, China. It can detect disease-specific biomarkers in exhaled breath with 92% accuracy, 100% sensitivity, and 84% specificity. While a larger cohort study is still needed to validate the results, the researchers envision the test’s utility as a screening tool for airports, shopping centers, and other public places where the risk of community spread is high.

Prof. Haick’s pre-screening diagnostic system could offer a screening solution that can be performed at home or point-of-care facilities, greatly reducing unneeded confirmatory tests and reducing the burden on hospitals. Importantly, the artificial intelligence of the device can be modified and applied to any other infectious diseases. Prof. Haick believes this approach can serve as a platform for a rapidly available diagnostic tool that can be used in the case of a new disease outbreak.

The research was funded by the Technion – Israel Institute of Technology.

For the full article in the journal ACS Nano click here