Tag Archives: Hungary

Robot radiologists (artificially intelligent doctors)

Mutaz Musa, a physician at New York Presbyterian Hospital/Weill Cornell (Department of Emergency Medicine) and software developer in New York City, has penned an eyeopening opinion piece about artificial intelligence (or robots if you prefer) and the field of radiology. From a June 25, 2018 opinion piece for The Scientist (Note: Links have been removed),

Although artificial intelligence has raised fears of job loss for many, we doctors have thus far enjoyed a smug sense of security. There are signs, however, that the first wave of AI-driven redundancies among doctors is fast approaching. And radiologists seem to be first on the chopping block.

Andrew Ng, founder of online learning platform Coursera and former CTO of “China’s Google,” Baidu, recently announced the development of CheXNet, a convolutional neural net capable of recognizing pneumonia and other thoracic pathologies on chest X-rays better than human radiologists. Earlier this year, a Hungarian group developed a similar system for detecting and classifying features of breast cancer in mammograms. In 2017, Adelaide University researchers published details of a bot capable of matching human radiologist performance in detecting hip fractures. And, of course, Google achieved superhuman proficiency in detecting diabetic retinopathy in fundus photographs, a task outside the scope of most radiologists.

Beyond single, two-dimensional radiographs, a team at Oxford University developed a system for detecting spinal disease from MRI data with a performance equivalent to a human radiologist. Meanwhile, researchers at the University of California, Los Angeles, reported detecting pathology on head CT scans with an error rate more than 20 times lower than a human radiologist.

Although these particular projects are still in the research phase and far from perfect—for instance, often pitting their machines against a limited number of radiologists—the pace of progress alone is telling.

Others have already taken their algorithms out of the lab and into the marketplace. Enlitic, founded by Aussie serial entrepreneur and University of San Francisco researcher Jeremy Howard, is a Bay-Area startup that offers automated X-ray and chest CAT scan interpretation services. Enlitic’s systems putatively can judge the malignancy of nodules up to 50 percent more accurately than a panel of radiologists and identify fractures so small they’d typically be missed by the human eye. One of Enlitic’s largest investors, Capitol Health, owns a network of diagnostic imaging centers throughout Australia, anticipating the broad rollout of this technology. Another Bay-Area startup, Arterys, offers cloud-based medical imaging diagnostics. Arterys’s services extend beyond plain films to cardiac MRIs and CAT scans of the chest and abdomen. And there are many others.

Musa has offered a compelling argument with lots of links to supporting evidence.

[downloaded from https://www.the-scientist.com/news-opinion/opinion–rise-of-the-robot-radiologists-64356]

And evidence keeps mounting, I just stumbled across this June 30, 2018 news item on Xinhuanet.com,

An artificial intelligence (AI) system scored 2:0 against elite human physicians Saturday in two rounds of competitions in diagnosing brain tumors and predicting hematoma expansion in Beijing.

The BioMind AI system, developed by the Artificial Intelligence Research Centre for Neurological Disorders at the Beijing Tiantan Hospital and a research team from the Capital Medical University, made correct diagnoses in 87 percent of 225 cases in about 15 minutes, while a team of 15 senior doctors only achieved 66-percent accuracy.

The AI also gave correct predictions in 83 percent of brain hematoma expansion cases, outperforming the 63-percent accuracy among a group of physicians from renowned hospitals across the country.

The outcomes for human physicians were quite normal and even better than the average accuracy in ordinary hospitals, said Gao Peiyi, head of the radiology department at Tiantan Hospital, a leading institution on neurology and neurosurgery.

To train the AI, developers fed it tens of thousands of images of nervous system-related diseases that the Tiantan Hospital has archived over the past 10 years, making it capable of diagnosing common neurological diseases such as meningioma and glioma with an accuracy rate of over 90 percent, comparable to that of a senior doctor.

All the cases were real and contributed by the hospital, but never used as training material for the AI, according to the organizer.

Wang Yongjun, executive vice president of the Tiantan Hospital, said that he personally did not care very much about who won, because the contest was never intended to pit humans against technology but to help doctors learn and improve [emphasis mine] through interactions with technology.

“I hope through this competition, doctors can experience the power of artificial intelligence. This is especially so for some doctors who are skeptical about artificial intelligence. I hope they can further understand AI and eliminate their fears toward it,” said Wang.

Dr. Lin Yi who participated and lost in the second round, said that she welcomes AI, as it is not a threat but a “friend.” [emphasis mine]

AI will not only reduce the workload but also push doctors to keep learning and improve their skills, said Lin.

Bian Xiuwu, an academician with the Chinese Academy of Science and a member of the competition’s jury, said there has never been an absolute standard correct answer in diagnosing developing diseases, and the AI would only serve as an assistant to doctors in giving preliminary results. [emphasis mine]

Dr. Paul Parizel, former president of the European Society of Radiology and another member of the jury, also agreed that AI will not replace doctors, but will instead function similar to how GPS does for drivers. [emphasis mine]

Dr. Gauden Galea, representative of the World Health Organization in China, said AI is an exciting tool for healthcare but still in the primitive stages.

Based on the size of its population and the huge volume of accessible digital medical data, China has a unique advantage in developing medical AI, according to Galea.

China has introduced a series of plans in developing AI applications in recent years.

In 2017, the State Council issued a development plan on the new generation of Artificial Intelligence and the Ministry of Industry and Information Technology also issued the “Three-Year Action Plan for Promoting the Development of a New Generation of Artificial Intelligence (2018-2020).”

The Action Plan proposed developing medical image-assisted diagnostic systems to support medicine in various fields.

I note the reference to cars and global positioning systems (GPS) and their role as ‘helpers’;, it seems no one at the ‘AI and radiology’ competition has heard of driverless cars. Here’s Musa on those reassuring comments abut how the technology won’t replace experts but rather augment their skills,

To be sure, these services frame themselves as “support products” that “make doctors faster,” rather than replacements that make doctors redundant. This language may reflect a reserved view of the technology, though it likely also represents a marketing strategy keen to avoid threatening or antagonizing incumbents. After all, many of the customers themselves, for now, are radiologists.

Radiology isn’t the only area where experts might find themselves displaced.

Eye experts

It seems inroads have been made by artificial intelligence systems (AI) into the diagnosis of eye diseases. It got the ‘Fast Company’ treatment (exciting new tech, learn all about it) as can be seen further down in this posting. First, here’s a more restrained announcement, from an August 14, 2018 news item on phys.org (Note: A link has been removed),

An artificial intelligence (AI) system, which can recommend the correct referral decision for more than 50 eye diseases, as accurately as experts has been developed by Moorfields Eye Hospital NHS Foundation Trust, DeepMind Health and UCL [University College London].

The breakthrough research, published online by Nature Medicine, describes how machine-learning technology has been successfully trained on thousands of historic de-personalised eye scans to identify features of eye disease and recommend how patients should be referred for care.

Researchers hope the technology could one day transform the way professionals carry out eye tests, allowing them to spot conditions earlier and prioritise patients with the most serious eye diseases before irreversible damage sets in.

An August 13, 2018 UCL press release, which originated the news item, describes the research and the reasons behind it in more detail,

More than 285 million people worldwide live with some form of sight loss, including more than two million people in the UK. Eye diseases remain one of the biggest causes of sight loss, and many can be prevented with early detection and treatment.

Dr Pearse Keane, NIHR Clinician Scientist at the UCL Institute of Ophthalmology and consultant ophthalmologist at Moorfields Eye Hospital NHS Foundation Trust said: “The number of eye scans we’re performing is growing at a pace much faster than human experts are able to interpret them. There is a risk that this may cause delays in the diagnosis and treatment of sight-threatening diseases, which can be devastating for patients.”

“The AI technology we’re developing is designed to prioritise patients who need to be seen and treated urgently by a doctor or eye care professional. If we can diagnose and treat eye conditions early, it gives us the best chance of saving people’s sight. With further research it could lead to greater consistency and quality of care for patients with eye problems in the future.”

The study, launched in 2016, brought together leading NHS eye health professionals and scientists from UCL and the National Institute for Health Research (NIHR) with some of the UK’s top technologists at DeepMind to investigate whether AI technology could help improve the care of patients with sight-threatening diseases, such as age-related macular degeneration and diabetic eye disease.

Using two types of neural network – mathematical systems for identifying patterns in images or data – the AI system quickly learnt to identify 10 features of eye disease from highly complex optical coherence tomography (OCT) scans. The system was then able to recommend a referral decision based on the most urgent conditions detected.

To establish whether the AI system was making correct referrals, clinicians also viewed the same OCT scans and made their own referral decisions. The study concluded that AI was able to make the right referral recommendation more than 94% of the time, matching the performance of expert clinicians.

The AI has been developed with two unique features which maximise its potential use in eye care. Firstly, the system can provide information that helps explain to eye care professionals how it arrives at its recommendations. This information includes visuals of the features of eye disease it has identified on the OCT scan and the level of confidence the system has in its recommendations, in the form of a percentage. This functionality is crucial in helping clinicians scrutinise the technology’s recommendations and check its accuracy before deciding the type of care and treatment a patient receives.

Secondly, the AI system can be easily applied to different types of eye scanner, not just the specific model on which it was trained. This could significantly increase the number of people who benefit from this technology and future-proof it, so it can still be used even as OCT scanners are upgraded or replaced over time.

The next step is for the research to go through clinical trials to explore how this technology might improve patient care in practice, and regulatory approval before it can be used in hospitals and other clinical settings.

If clinical trials are successful in demonstrating that the technology can be used safely and effectively, Moorfields will be able to use an eventual, regulatory-approved product for free, across all 30 of their UK hospitals and community clinics, for an initial period of five years.

The work that has gone into this project will also help accelerate wider NHS research for many years to come. For example, DeepMind has invested significant resources to clean, curate and label Moorfields’ de-identified research dataset to create one of the most advanced eye research databases in the world.

Moorfields owns this database as a non-commercial public asset, which is already forming the basis of nine separate medical research studies. In addition, Moorfields can also use DeepMind’s trained AI model for future non-commercial research efforts, which could help advance medical research even further.

Mustafa Suleyman, Co-founder and Head of Applied AI at DeepMind Health, said: “We set up DeepMind Health because we believe artificial intelligence can help solve some of society’s biggest health challenges, like avoidable sight loss, which affects millions of people across the globe. These incredibly exciting results take us one step closer to that goal and could, in time, transform the diagnosis, treatment and management of patients with sight threatening eye conditions, not just at Moorfields, but around the world.”

Professor Sir Peng Tee Khaw, director of the NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology said: “The results of this pioneering research with DeepMind are very exciting and demonstrate the potential sight-saving impact AI could have for patients. I am in no doubt that AI has a vital role to play in the future of healthcare, particularly when it comes to training and helping medical professionals so that patients benefit from vital treatment earlier than might previously have been possible. This shows the transformative research than can be carried out in the UK combining world leading industry and NIHR/NHS hospital/university partnerships.”

Matt Hancock, Health and Social Care Secretary, said: “This is hugely exciting and exactly the type of technology which will benefit the NHS in the long term and improve patient care – that’s why we fund over a billion pounds a year in health research as part of our long term plan for the NHS.”

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

Clinically applicable deep learning for diagnosis and referral in retinal disease by Jeffrey De Fauw, Joseph R. Ledsam, Bernardino Romera-Paredes, Stanislav Nikolov, Nenad Tomasev, Sam Blackwell, Harry Askham, Xavier Glorot, Brendan O’Donoghue, Daniel Visentin, George van den Driessche, Balaji Lakshminarayanan, Clemens Meyer, Faith Mackinder, Simon Bouton, Kareem Ayoub, Reena Chopra, Dominic King, Alan Karthikesalingam, Cían O. Hughes, Rosalind Raine, Julian Hughes, Dawn A. Sim, Catherine Egan, Adnan Tufail, Hugh Montgomery, Demis Hassabis, Geraint Rees, Trevor Back, Peng T. Khaw, Mustafa Suleyman, Julien Cornebise, Pearse A. Keane, & Olaf Ronneberger. Nature Medicine (2018) DOI: https://doi.org/10.1038/s41591-018-0107-6 Published 13 August 2018

This paper is behind a paywall.

And now, Melissa Locker’s August 15, 2018 article for Fast Company (Note: Links have been removed),

In a paper published in Nature Medicine on Monday, Google’s DeepMind subsidiary, UCL, and researchers at Moorfields Eye Hospital showed off their new AI system. The researchers used deep learning to create algorithm-driven software that can identify common patterns in data culled from dozens of common eye diseases from 3D scans. The result is an AI that can identify more than 50 diseases with incredible accuracy and can then refer patients to a specialist. Even more important, though, is that the AI can explain why a diagnosis was made, indicating which part of the scan prompted the outcome. It’s an important step in both medicine and in making AIs slightly more human

The editor or writer has even highlighted the sentence about the system’s accuracy—not just good but incredible!

I will be publishing something soon [my August 21, 2018 posting] which highlights some of the questions one might want to ask about AI and medicine before diving headfirst into this brave new world of medicine.

Nanowire fingerprint technology

Apparently this technology from France’s Laboratoire d’électronique des technologies de l’information (CEA-Leti) will make fingerprinting more reliable. From a Sept. 5, 2017 news item on Nanowerk,

Leti today announced that the European R&D project known as PiezoMAT has developed a pressure-based fingerprint sensor that enables resolution more than twice as high as currently required by the U.S. Federal Bureau of Investigation (FBI).

The project’s proof of concept demonstrates that a matrix of interconnected piezoelectric zinc-oxide (ZnO) nanowires grown on silicon can reconstruct the smallest features of human fingerprints at 1,000 dots per inch (DPI).

“The pressure-based fingerprint sensor derived from the integration of piezo-electric ZnO nanowires grown on silicon opens the path to ultra-high resolution fingerprint sensors, which will be able to reach resolution much higher than 1,000 DPI,” said Antoine Viana, Leti’s project manager. “This technology holds promise for significant improvement in both security and identification applications.”

A Sept. 5, 2017 Leti press release, which originated the news item, delves further,

The eight-member project team of European companies, universities and research institutes fabricated a demonstrator embedding a silicon chip with 250 pixels, and its associated electronics for signal collection and post-processing. The chip was designed to demonstrate the concept and the major technological achievements, not the maximum potential nanowire integration density. Long-term development will pursue full electronics integration for optimal sensor resolution.

The project also provided valuable experience and know-how in several key areas, such as optimization of seed-layer processing, localized growth of well-oriented ZnO nanowires on silicon substrates, mathematical modeling of complex charge generation, and synthesis of new polymers for encapsulation. The research and deliverables of the project have been presented in scientific journals and at conferences, including Eurosensors 2016 in Budapest.

The 44-month, €2.9 million PiezoMAT (PIEZOelectric nanowire MATrices) research project was funded by the European Commission in the Seventh Framework Program. Its partners include:

  • Leti (Grenoble, France): A leading European center in the field of microelectronics, microtechnology and nanotechnology R&D, Leti is one of the three institutes of the Technological Research Division at CEA, the French Alternative Energies and Atomic Energy Commission. Leti’s activities span basic and applied research up to pilot industrial lines. www.leti-cea.com/cea-tech/leti/english
  • Fraunhofer IAF (Freiburg, Germany): Fraunhofer IAF, one of the leading research facilities worldwide in the field of III-V semiconductors, develops electronic and optical devices based on modern micro- and nanostructures. Fraunhofer IAF’s technologies find applications in areas such as security, energy, communication, health, and mobility. www.iaf.fraunhofer.de/en
  • Centre for Energy Research, Hungarian Academy of Sciences (Budapest, Hungary):  The Institute for Technical Physics and Materials Science, one of the institutes of the Research Centre, conducts interdisciplinary research on complex functional materials and nanometer-scale structures, exploration of physical, chemical, and biological principles, and their exploitation in integrated micro- and nanosystems www.mems.hu, www.energia.mta.hu/en
  • Universität Leipzig (Leipzig, Germany): Germany’s second-oldest university with continuous teaching, established in 1409, hosts about 30,000 students in liberal arts, medicine and natural sciences. One of its scientific profiles is “Complex Matter”, and contributions to PIEZOMAT are in the field of nanostructures and wide gap materials. www.zv.uni-leipzig.de/en/
  • Kaunas University of Technology (Kaunas, Lithuania): One of the largest technical universities in the Baltic States, focusing its R&D activities on novel materials, smart devices, advanced measurement techniques and micro/nano-technologies. The Institute of Mechatronics specializes on multi-physics simulation and dynamic characterization of macro/micro-scale transducers with well-established expertise in the field of piezoelectric devices. http://en.ktu.lt/
  • SPECIFIC POLYMERS (Castries, France): SME with twelve employees and an annual turnover of about 1M€, SPECIFIC POLYMERS acts as an R&D service provider and scale-up producer in the field of functional polymers with high specificity (>1000 polymers in catalogue; >500 customers; >50 countries). www.specificpolymers.fr/
  • Tyndall National Institute (Cork, Ireland): Tyndall National Institute is one of Europe’s leading research centres in Information and Communications Technology (ICT) research and development and the largest facility of its type in Ireland. The Institute employs over 460 researchers, engineers and support staff, with a full-time graduate cohort of 135 students. With a network of 200 industry partners and customers worldwide, Tyndall generates around €30M income each year, 85% from competitively won contracts nationally and internationally. Tyndall is a globally leading Institute in its four core research areas of Photonics, Microsystems, Micro/Nanoelectronics and Theory, Modeling and Design. www.tyndall.ie/
  • OT-Morpho (Paris, France): OT-Morpho is a world leader in digital security & identification technologies with the ambition to empower citizens and consumers alike to interact, pay, connect, commute, travel and even vote in ways that are now possible in a connected world. As our physical and digital, civil and commercial lifestyles converge, OT-Morpho stands precisely at that crossroads to leverage the best in security and identity technologies and offer customized solutions to a wide range of international clients from key industries, including Financial services, Telecom, Identity, Security and IoT. With close to €3bn in revenues and more than 14,000 employees, OT-Morpho is the result of the merger between OT (Oberthur Technologies) and Safran Identity & Security (Morpho) completed in 31 May 2017. Temporarily designated by the name “OT-Morpho”, the new company will unveil its new name in September 2017. For more information, visit www.morpho.com and www.oberthur.com

I have tended to take fingerprint technology for granted but last fall (2016) I stumbled on a report suggesting that forensic sciences, including fingerprinting, was perhaps not as conclusive as one might expect after watching fictional police procedural television programmes. My Sept. 23, 2016 posting features the US President’s Council of Advisors on Science and Technology (PCAST) released a report (‘Forensic Science in Criminal Courts: Ensuring Scientific Validity of Feature-Comparison Methods‘ 174 pp PDF).

International Women’s Day March 8, 2017 and UNESCO/L’Oréal’s For Women in Science (Rising Talents)

Before getting to the science, here’s a little music in honour of March 8, 2017 International Women’s Day,

There is is a Wikipedia entry devoted to Rise Up (Parachute Club song), Note: Links have been removed<

“Rise Up” is a pop song recorded by the Canadian group Parachute Club on their self-titled 1983 album. It was produced and engineered by Daniel Lanois, and written by Parachute Club members Billy Bryans, Lauri Conger, Lorraine Segato and Steve Webster with lyrics contributed by filmmaker Lynne Fernie.

An upbeat call for peace, celebration, and “freedom / to love who we please,” the song was a national hit in Canada, and was hailed as a unique achievement in Canadian pop music:

“ Rarely does one experience a piece of music in white North America where the barrier between participant and observer breaks down. Rise Up rises right up and breaks down the wall.[1] ”

According to Segato, the song was not written with any one individual group in mind, but as a universal anthem of freedom and equality;[2] Fernie described the song’s lyrics as having been inspired in part by West Coast First Nations rituals in which young girls would “rise up” at dawn to adopt their adult names as a rite of passage.[3]

It remains the band’s most famous song, and has been adopted as an activist anthem for causes as diverse as gay rights, feminism, anti-racism and the New Democratic Party.[4] As well, the song’s reggae and soca-influenced rhythms made it the first significant commercial breakthrough for Caribbean music in Canada.

L’Oréal UNESCO For Women in Science

From a March 8, 2017 UNESCO press release (received via email),

Fifteen outstanding young women researchers, selected
among more than 250 candidates in the framework of the 19th edition of
the L’Oréal-UNESCO For Women in Science awards, will receive the
International Rising Talent fellowship during a gala on 21 March at the
hotel Pullman Tour Eiffel de Paris. By recognizing their achievements at
a key moment in their careers, the _For Women in Science programme aims
to help them pursue their research.

Since 1998, the L’Oréal-UNESCO _For Women in Science programme [1]
has highlighted the achievements of outstanding women scientists and
supported promising younger women who are in the early stages of their
scientific careers. Selected among the best national and regional
L’Oréal-UNESCO fellows, the International Rising Talents come from
all regions of the world (Africa and Arab States, Asia-Pacific, Europe,
Latin America and North America).

Together with the five laureates of the 2017 L’Oreal-UNESCO For Women
in Science awards [2], they will participate in a week of events,
training and exchanges that will culminate with the award ceremony on 23
March 2017 at the Mutualité in Paris.

The 2017 International Rising Talent are recognized for their work in
the following five categories:

WATCHING THE BRAIN AT WORK

* DOCTOR LORINA NACI, Canada
Fundamental medicine
In a coma: is the patient conscious or unconscious?     * ASSOCIATE
PROFESSOR MUIREANN IRISH, Australia

Clinical medicine
Recognizing Alzheimer’s before the first signs appear.

ON THE ROAD TO CONCEIVING NEW MEDICAL TREATMENTS

* DOCTOR HYUN LEE, Germany
Biological Sciences
Neurodegenerative diseases: untangling aggregated proteins.
* DOCTOR NAM-KYUNG YU, Republic of Korea
Biological Sciences
Rett syndrome: neuronal cells come under fire
* DOCTOR STEPHANIE FANUCCHI, South Africa
Biological Sciences
Better understanding the immune system.
* DOCTOR JULIA ETULAIN, Argentina
Biological Sciences
Better tissue healing.

Finding potential new sources of drugs

* DOCTOR RYM BEN SALLEM, Tunisia
Biological Sciences
New antibiotics are right under our feet.
* DOCTOR HAB JOANNA SULKOWSKA, Poland
Biological Sciences
Unraveling the secrets of entangled proteins.

GETTING TO THE HEART OF MATTER

* MS NAZEK EL-ATAB, United Arab Emirates
Electrical, Electronic and Computer Engineering
Miniaturizing electronics without losing memory.
* DOCTOR BILGE DEMIRKOZ, Turkey
Physics
Piercing the secrets of cosmic radiation.
* DOCTOR TAMARA ELZEIN, Lebanon
Material Sciences
Trapping radioactivity.
* DOCTOR RAN LONG, China
Chemistry
Unlocking the potential of energy resources with nanochemistry.

EXAMINING THE PAST TO SHED LIGHT ON THE FUTURE – OR VICE VERSA

* DOCTOR FERNANDA WERNECK, Brazil
Biological Sciences
Predicting how animal biodiversity will evolve.
* DOCTOR SAM GILES, United Kingdom
Biological Sciences
Taking another look at the evolution of vertebrates thanks to their
braincases.
* DOCTOR ÁGNES KÓSPÁL, Hungary
Astronomy and Space Sciences
Looking at the birth of distant suns and planets to better understand
the solar system.

Congratulations to all of the winners!

You can find out more about these awards and others on the 2017 L’Oréal-UNESCO For Women in Science Awards webpage or on the For Women In Science website. (Again in honour of the 2017 International Women’s Day, I was the 92758th signer of the For Women in Science Manifesto.)

International Women’s Day origins

Thank you to Wikipedia (Note: Links have been removed),

International Women’s Day (IWD), originally called International Working Women’s Day, is celebrated on March 8 every year.[2] It commemorates the movement for women’s rights.

The earliest Women’s Day observance was held on February 28, 1909, in New York and organized by the Socialist Party of America.[3] On March 8, 1917, in the capital of the Russian Empire, Petrograd, a demonstration of women textile workers began, covering the whole city. This was the beginning of the Russian Revolution.[4] Seven days later, the Emperor of Russia Nicholas II abdicated and the provisional Government granted women the right to vote.[3] March 8 was declared a national holiday in Soviet Russia in 1917. The day was predominantly celebrated by the socialist movement and communist countries until it was adopted in 1975 by the United Nations.

It seems only fitting to bookend this post with another song (Happy International Women’s Day March 8, 2017),

While the lyrics are unabashedly romantic, the video is surprisingly moody with a bit of a ‘stalker vive’ although it does end up with her holding centre stage while singing and bouncing around in time to Walking on Sunshine.

Hypersensitivity to nanomedicine: the CARPA reaction

There is some intriguing research (although I do have a reservation) into some unexpected side effects that nanomedicine may have according to a Feb. 23, 2016 news item on phys.org,

Keywords such as nano-, personalized-, or targeted medicine sound like bright future. What most people do not know, is that nanomedicines can cause severe undesired effects for actually being too big! Those modern medicines easily achieve the size of viruses which the body potentially recognizes as foreign starting to defend itself against —a sometimes severe immune response unfolds.

The CARPA-phenomenon (Complement Activation-Related PseudoAllergy) is a frequent hypersensitivity response to nanomedicine application. Up to 100 patients worldwide suffer from severe reactions, such as cardiac distress, difficulty of breathing, chest and back pain or fainting each day when their blood gets exposed to certain nanoparticles during medical treatment. Every 10 days one patient even dies due to an uncontrollable anaphylactoid reaction.

Apart from being activated in a different way, this pseudoallergy has the same symptoms as a common allergy, bearing a crucial difference:  the reaction is taking place without previous sensitizing exposure to a substance, making it hard to predict, whether a person will react to a specific nanodrug or be safe. Intrigued by this vital challenge, János Szebeni from Semmelweis University, Budapest, has been working with scientific verve on the decipherment and prevention of the CARPA phenomenon for more than 20 years. With his invaluable support De Gruyter´s European Journal of Nanomedicine (EJNM) lately dedicated an elaborate compilation of the most recent scientific advances on CARPA, presented by renowned experts on the subject.

A Feb. 23, 2016 De Gruyter Publishers press release, which originated the news item, provides more detail,

Interestingly it´s pigs that turned out to serve as best model for research on the complex pathomechanism, diagnosis and potential treatment of CARPA. “Pigs´ sensitivity equals that of humans responding most vehemently to reactogenic nanomedicines”, Szebeni states.  In a contribution to EJNM´s compilation on CARPA, Rudolf Urbanics and colleagues show that reactions to specific nanodrugs are even quantitatively reproducible in pigs … . Szebeni: “This is absolutely rare in allergy-research. In these animals the endpoint of the overreaction is reflected in a rise of pulmonary arterial pressure, being as accurate as a Swiss watch”. Pigs can thus be used for drug screening and prediction of the CARPAgenic potential of nanomedicines. This becomes increasingly important with the ever growing interest in modern drugs requiring reliable preclinical safety assays during the translation process from bench to bedside. Results might also help to personalize nanomedicine administration schedules during for example the targeted treatment of cancer. The same holds true for a very recently developed in vitro immunoassay. By simply using a patient´s blood sample, it tests for potential CARPA reactions even before application of specific nanodrugs.

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

Lessons learned from the porcine CARPA model: constant and variable responses to different nanomedicines and administration protocols by Rudolf Urbanics, Péter Bedőcs, János Szebeni. European Journal of Nanomedicine. Volume 7, Issue 3, Pages 219–231, ISSN (Online) 1662-596X, ISSN (Print) 1662-5986, DOI: 10.1515/ejnm-2015-0011, June 2015

This paper appears to be open access.

As for reservations, I’m not sure what occasioned the news release so many months post publication of the paperand it should be noted that János Szebeni seems to be the paper’s lead author and the editor of the European Journal of Nanomedicine.

Blue Brain Project builds a digital piece of brain

Caption: This is a photo of a virtual brain slice. Credit: Makram et al./Cell 2015

Caption: This is a photo of a virtual brain slice. Credit: Makram et al./Cell 2015

Here’s more *about this virtual brain slice* from an Oct. 8, 2015 Cell (magazine) news release on EurekAlert,

If you want to learn how something works, one strategy is to take it apart and put it back together again [also known as reverse engineering]. For 10 years, a global initiative called the Blue Brain Project–hosted at the Ecole Polytechnique Federale de Lausanne (EPFL)–has been attempting to do this digitally with a section of juvenile rat brain. The project presents a first draft of this reconstruction, which contains over 31,000 neurons, 55 layers of cells, and 207 different neuron subtypes, on October 8 [2015] in Cell.

Heroic efforts are currently being made to define all the different types of neurons in the brain, to measure their electrical firing properties, and to map out the circuits that connect them to one another. These painstaking efforts are giving us a glimpse into the building blocks and logic of brain wiring. However, getting a full, high-resolution picture of all the features and activity of the neurons within a brain region and the circuit-level behaviors of these neurons is a major challenge.

Henry Markram and colleagues have taken an engineering approach to this question by digitally reconstructing a slice of the neocortex, an area of the brain that has benefitted from extensive characterization. Using this wealth of data, they built a virtual brain slice representing the different neuron types present in this region and the key features controlling their firing and, most notably, modeling their connectivity, including nearly 40 million synapses and 2,000 connections between each brain cell type.

“The reconstruction required an enormous number of experiments,” says Markram, of the EPFL. “It paves the way for predicting the location, numbers, and even the amount of ion currents flowing through all 40 million synapses.”

Once the reconstruction was complete, the investigators used powerful supercomputers to simulate the behavior of neurons under different conditions. Remarkably, the researchers found that, by slightly adjusting just one parameter, the level of calcium ions, they could produce broader patterns of circuit-level activity that could not be predicted based on features of the individual neurons. For instance, slow synchronous waves of neuronal activity, which have been observed in the brain during sleep, were triggered in their simulations, suggesting that neural circuits may be able to switch into different “states” that could underlie important behaviors.

“An analogy would be a computer processor that can reconfigure to focus on certain tasks,” Markram says. “The experiments suggest the existence of a spectrum of states, so this raises new types of questions, such as ‘what if you’re stuck in the wrong state?'” For instance, Markram suggests that the findings may open up new avenues for explaining how initiating the fight-or-flight response through the adrenocorticotropic hormone yields tunnel vision and aggression.

The Blue Brain Project researchers plan to continue exploring the state-dependent computational theory while improving the model they’ve built. All of the results to date are now freely available to the scientific community at https://bbp.epfl.ch/nmc-portal.

An Oct. 8, 2015 Hebrew University of Jerusalem press release on the Canadian Friends of the Hebrew University of Jerusalem website provides more detail,

Published by the renowned journal Cell, the paper is the result of a massive effort by 82 scientists and engineers at EPFL and at institutions in Israel, Spain, Hungary, USA, China, Sweden, and the UK. It represents the culmination of 20 years of biological experimentation that generated the core dataset, and 10 years of computational science work that developed the algorithms and built the software ecosystem required to digitally reconstruct and simulate the tissue.

The Hebrew University of Jerusalem’s Prof. Idan Segev, a senior author of the research paper, said: “With the Blue Brain Project, we are creating a digital reconstruction of the brain and using supercomputer simulations of its electrical behavior to reveal a variety of brain states. This allows us to examine brain phenomena within a purely digital environment and conduct experiments previously only possible using biological tissue. The insights we gather from these experiments will help us to understand normal and abnormal brain states, and in the future may have the potential to help us develop new avenues for treating brain disorders.”

Segev, a member of the Hebrew University’s Edmond and Lily Safra Center for Brain Sciences and director of the university’s Department of Neurobiology, sees the paper as building on the pioneering work of the Spanish anatomist Ramon y Cajal from more than 100 years ago: “Ramon y Cajal began drawing every type of neuron in the brain by hand. He even drew in arrows to describe how he thought the information was flowing from one neuron to the next. Today, we are doing what Cajal would be doing with the tools of the day: building a digital representation of the neurons and synapses, and simulating the flow of information between neurons on supercomputers. Furthermore, the digitization of the tissue is open to the community and allows the data and the models to be preserved and reused for future generations.”

While a long way from digitizing the whole brain, the study demonstrates that it is feasible to digitally reconstruct and simulate brain tissue, and most importantly, to reveal novel insights into the brain’s functioning. Simulating the emergent electrical behavior of this virtual tissue on supercomputers reproduced a range of previous observations made in experiments on the brain, validating its biological accuracy and providing new insights into the functioning of the neocortex. This is a first step and a significant contribution to Europe’s Human Brain Project, which Henry Markram founded, and where EPFL is the coordinating partner.

Cell has made a video abstract available (it can be found with the Hebrew University of Jerusalem press release)

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

Reconstruction and Simulation of Neocortical Microcircuitry by Henry Markram, Eilif Muller, Srikanth Ramaswamy, Michael W. Reimann, Marwan Abdellah, Carlos Aguado Sanchez, Anastasia Ailamaki, Lidia Alonso-Nanclares, Nicolas Antille, Selim Arsever, Guy Antoine Atenekeng Kahou, Thomas K. Berger, Ahmet Bilgili, Nenad Buncic, Athanassia Chalimourda, Giuseppe Chindemi, Jean-Denis Courcol, Fabien Delalondre, Vincent Delattre, Shaul Druckmann, Raphael Dumusc, James Dynes, Stefan Eilemann, Eyal Gal, Michael Emiel Gevaert, Jean-Pierre Ghobril, Albert Gidon, Joe W. Graham, Anirudh Gupta, Valentin Haenel, Etay Hay, Thomas Heinis, Juan B. Hernando, Michael Hines, Lida Kanari, Daniel Keller, John Kenyon, Georges Khazen, Yihwa Kim, James G. King, Zoltan Kisvarday, Pramod Kumbhar, Sébastien Lasserre, Jean-Vincent Le Bé, Bruno R.C. Magalhães, Angel Merchán-Pérez, Julie Meystre, Benjamin Roy Morrice, Jeffrey Muller, Alberto Muñoz-Céspedes, Shruti Muralidhar, Keerthan Muthurasa, Daniel Nachbaur, Taylor H. Newton, Max Nolte, Aleksandr Ovcharenko, Juan Palacios, Luis Pastor, Rodrigo Perin, Rajnish Ranjan, Imad Riachi, José-Rodrigo Rodríguez, Juan Luis Riquelme, Christian Rössert, Konstantinos Sfyrakis, Ying Shi, Julian C. Shillcock, Gilad Silberberg, Ricardo Silva, Farhan Tauheed, Martin Telefont, Maria Toledo-Rodriguez, Thomas Tränkler, Werner Van Geit, Jafet Villafranca Díaz, Richard Walker, Yun Wang, Stefano M. Zaninetta, Javier DeFelipe, Sean L. Hill, Idan Segev, Felix Schürmann. Cell, Volume 163, Issue 2, p456–492, 8 October 2015 DOI: http://dx.doi.org/10.1016/j.cell.2015.09.029

This paper appears to be open access.

My most substantive description of the Blue Brain Project , previous to this, was in a Jan. 29, 2013 posting featuring the European Union’s (EU) Human Brain project and involvement from countries that are not members.

* I edited a redundant lede (That’s a virtual slice of a rat brain.), moved the second sentence to the lede while adding this:  *about this virtual brain slice* on Oct. 16, 2015 at 0955 hours PST.

PlasCarb: producing graphene and renewable hydrogen from food waster

I have two tidbits about PlasCarb the first being an announcement of its existence and the second an announcement of its recently published research. A Jan. 13, 2015 news item on Nanowerk describes the PlasCarb project (Note: A link has been removed),

The Centre for Process Innovation (CPI) is leading a European collaborative project that aims to transform food waste into a sustainable source of significant economic added value, namely graphene and renewable hydrogen.

The project titled PlasCarb will transform biogas generated by the anaerobic digestion of food waste using an innovative low energy microwave plasma process to split biogas (methane and carbon dioxide) into high value graphitic carbon and renewable hydrogen.

A Jan. 13, 2015 CPI press release, which originated the news item, describes the project and its organization in greater detail,

CPI  as the coordinator of the project is responsible for the technical aspects in the separation of biogas into methane and carbon dioxide, and separating of the graphitic carbon produced from the renewable hydrogen. The infrastructure at CPI allows for the microwave plasma process to be trialled and optimised at pilot production scale, with a future technology roadmap devised for commercial scale manufacturing.

Graphene is one of the most interesting inventions of modern times. Stronger than steel, yet light, the material conducts electricity and heat. It has been used for a wide variety of applications, from strengthening tennis rackets, spray on radiators, to building semiconductors, electric circuits and solar cells.

The sustainable creation of graphene and renewable hydrogen from food waste in provides a sustainable method towards dealing with food waste problem that the European Union faces. It is estimated that 90 million tonnes of food is wasted each year, a figure which could rise to approximately 126 million tonnes by 2020. In the UK alone, food waste equates to a financial loss to business of at least £5 billion per year.

Dr Keith Robson, Director of Formulation and Flexible Manufacturing at CPI said, “PlasCarb will provide an innovative solution to the problems associated with food waste, which is one of the biggest challenges that the European Union faces in the strive towards a low carbon economy.  The project will not only seek to reduce food waste but also use new technological methods to turn it into renewable energy resources which themselves are of economic value, and all within a sustainable manner.”

PlasCarb will utilise quality research and specialist industrial process engineering to optimise the quality and economic value of the Graphene and hydrogen, further enhancing the sustainability of the process life cycle.

Graphitic carbon has been identified as one of Europe’s economically critical raw materials and of strategic performance in the development of future emerging technologies. The global market for graphite, either mined or synthetic is worth over €10 billion per annum. Hydrogen is already used in significant quantities by industry and recognised with great potential as a future transport fuel for a low carbon economy. The ability to produce renewable hydrogen also has added benefits as currently 95% of hydrogen is produced from fossil fuels. Moreover, it is currently projected that increasing demand of raw materials from fossil sources will lead to price volatility, accelerated environmental degradation and rising political tensions over resource access.

Therefore, the latter stages of the project will be dedicated to the market uptake of the PlasCarb process and the output products, through the development of an economically sustainable business strategy, a financial risk assessment of the project results and a flexible financial model that is able to act as a primary screen of economic viability. Based on this, an economic analysis of the process will be determined. Through the development of a decentralised business model for widespread trans-European implementation, the valorisation of food waste will have the potential to be undertaken for the benefit of local economies and employment. More specifically, three interrelated post project exploitation markets have been defined: food waste management, high value graphite and RH2 sales.

PlasCarb is a 3-year collaborative project, co-funded under the European Union’s Seventh Framework Programme (FP7) and will further reinforce Europe’s leading position in environmental technologies and innovation in high value Carbon. The consortium is composed of eight partners led by CPI from five European countries, whose complimentary research and industrial expertise will enable the required results to be successfully delivered. The project partners are; The Centre for Process Innovation (UK), GasPlas AS (NO), CNRS (FR), Fraunhofer IBP (DE), Uvasol Ltd (UK), GAP Waste Management (UK), Geonardo Ltd. (HU), Abalonyx AS (NO).

You can find PlasCarb here.

The second announcement can be found in a PlasCarb Jan. 14, 2015 press release announcing the publication of research on heterostructures of graphene ribbons,

Few materials have received as much attention from the scientific world or have raised so many hopes with a view to their potential deployment in new applications as graphene has. This is largely due to its superlative properties: it is the thinnest material in existence, almost transparent, the strongest, the stiffest and at the same time the most strechable, the best thermal conductor, the one with the highest intrinsic charge carrier mobility, plus many more fascinating features. Specifically, its electronic properties can vary enormously through its confinement inside nanostructured systems, for example. That is why ribbons or rows of graphene with nanometric widths are emerging as tremendously interesting electronic components. On the other hand, due to the great variability of electronic properties upon minimal changes in the structure of these nanoribbons, exact control on an atomic level is an indispensable requirement to make the most of all their potential.

The lithographic techniques used in conventional nanotechnology do not yet have such resolution and precision. In the year 2010, however, a way was found to synthesise nanoribbons with atomic precision by means of the so-called molecular self-assembly. Molecules designed for this purpose are deposited onto a surface in such a way that they react with each other and give rise to perfectly specified graphene nanoribbons by means of a highly reproducible process and without any other external mediation than heating to the required temperature. In 2013 a team of scientists from the University of Berkeley and the Centre for Materials Physics (CFM), a mixed CSIC (Spanish National Research Council) and UPV/EHU (University of the Basque Country) centre, extended this very concept to new molecules that were forming wider graphene nanoribbons and therefore with new electronic properties. This same group has now managed to go a step further by creating, through this self-assembly, heterostructures that blend segments of graphene nanoribbons of two different widths.

The forming of heterostructures with different materials has been a concept widely used in electronic engineering and has enabled huge advances to be made in conventional electronics. “We have now managed for the first time to form heterostructures of graphene nanoribbons modulating their width on a molecular level with atomic precision. What is more, their subsequent characterisation by means of scanning tunnelling microscopy and spectroscopy, complemented with first principles theoretical calculations, has shown that it gives rise to a system with very interesting electronic properties which include, for example, the creation of what are known as quantum wells,” pointed out the scientist Dimas de Oteyza, who has participated in this project. This work, the results of which are being published this very week in the journal Nature Nanotechnology, therefore constitutes a significant success towards the desired deployment of graphene in commercial electronic applications.

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

Molecular bandgap engineering of bottom-up synthesized graphene nanoribbon heterojunctions by Yen-Chia Chen, Ting Cao, Chen Chen, Zahra Pedramrazi, Danny Haberer, Dimas G. de Oteyza, Felix R. Fischer, Steven G. Louie, & Michael F. Crommie. Nature Nanotechnology (2015) doi:10.1038/nnano.2014.307 Published online 12 January 2015

This article is behind a paywall but there is a free preview available via ReadCube access.

Nanopaprika.eu celebrates 4th anniversary

It started as a social networking community for nanoscientists in 2007. From the Nov. 25, 2011 news item on Nanotechnology Now,

“It’s all started accidentally”
– recalls András Paszternák, PhD, founder of the portal. “One cold November morning, I met Professor Erika Kálmán, my PhD supervisor, at the corridor of the Chemical Research Center of Hungarian Academy of Sciences. She offer me to edit an already existing Hungarian nanowebpage. I asked for time to reflect, and in next day I suggested to start a community site, which will be updated with new content by members.” adds the Postdoctoral Fellow from Bar-Ilan University.

The page can be described as a place of constant renewal from the beginning. In 2011 it has become even more attractive with an international virtual poster conference, research teams and members “HOT papers” database.

Today there are many from USA, across Europe to Asia who are using the webpage to find new jobs, awards, or partners to start joint research projects.

The website Paszternák founded is nanopaprika.eu. From Nanopaprika’s About us page,

The heat is on for an online social networking community for nanoscientists. The International Nanoscience Community, TINC, was cooked up by Hungarian chemistry PhD student Andras Paszternak. It now provides a rich menu of communication tools for the international community of scientists working in the growing field of nanoscience and nanotechnology and recently passed the 5100 members mark.
The virtual nano community is fully equipped with all the functions one expects from a modern online networking site: personal chat, a scientific forum, more than 50 thematic groups, including microscopy, nanomedicine, and even a discussion forum on safety and toxicity. TINC is also a media partner for more than 45 nano conferences on different topics in 2009, 2010, 2011 and 2012.

The easiest way to describe nanopaprika would be to say that if the LinkedIn and Nanowerk websites had a child born in Europe, this would be it.