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2020 Nobel Prize in Economic Sciences for improvements to auction theory and inventions of new auction formats to Paul R. Milgrom and Robert B. Wilson
Reporter: Aviva Lev- Ari, PhD, RN
Article ID #285: 2020 Nobel Prize in Economic Sciences for improvements to auction theory and inventions of new auction formats to Paul R. Milgrom and Robert B. Wilson. Published on 10/12/2020
WordCloud Image Produced by Adam Tubman
UPDATED on 10/16/2020
The Nobel Prize for economic sciences this year went to Paul MIlgrom and Robert Wilson. Milgrom is recognized as one of the world’s great experts in auction theory, and I interviewed him for my book In the Plex (finally out in paper next February!) about Google’s clever AdWords approach to bidding, which was crafted by Google engineer Eric Veach along with his boss Salar Kamangar. I’d asked Milgrom to compare the AdWords system to the competitor, Overture:
One fan of Veach’s system was the top auction theorist, Stanford economist Paul Milgrom. “Overture’s auctions were much less successful,” says Milgrom. “In that world, you bid by the slot. If you wanted to be in third position, you put in a bid for third. If there’s an obvious guy to win the first position, nobody would bid against him, and he’d get it cheap. If you wanted to be in every position, you had to make bids for each of them. But Google simplified the auction. Instead of making eight bids for the eight positions, you made one single bid. The competition for second position will automatically raise the price for the first position. So the simplification thickens the market. The effect is that it guarantees that there’s competition for the top positions.”
Veach and Kamangar’s implementation was so impressive that it changed even Milgrom’s way of thinking. “Once I saw this from Google, I began seeing it everywhere,” he says, citing examples in spectrum auctions, diamond markets, and the competition between Kenyan and Rwandan coffee beans. “I’ve begun to realize that Google somehow or other introduced a level of simplification to ad auctions that was not included before.” And it wasn’t just a theoretical advance. “Google immediately started getting higher prices for advertising than Overture was getting,” he notes.
Subject: Clarence Thomas wants to rethink internet speech. Be afraid
Paul Milgrom (left) and Robert Wilson share the 2020 Nobel prize in economic sciences for improvements to auction theory and invention of new auction formats.
Image Credit: Elena Zhukova for the Stanford Graduate School of Business
The 2020 Nobel prize in economic sciences rewards work on an ancient form of transaction that has acquired new complexity and urgency in the modern age: the auction.
Insights in auction theory made by Paul Milgrom and Robert Wilson, both of Stanford University in California, have found applications ranging from the pricing of government bonds to the licensing of radio-spectrum bands in telecommunications.
Diane Coyle of the University of Cambridge, UK, says that the Nobel, announced on 12 October, will be widely welcomed. “These two not only did foundational work themselves”, she says, “but also inspired cohorts of younger researchers.”
Economist Preston McAfee of Google agrees. “I, and thousands like me, use the fruits of their work on a daily basis to make markets work better — to improve pricing, to manage incentives, to facilitate decision-making, to increase efficiency.”
Their research has intersected with computer science and communications engineering to lay the foundations for many online platforms, Coyle adds.
Economist John Kagel of Ohio State University in Columbus, USA, called it “an outstanding selection”.
Online platforms such as eBay have raised public awareness of some of the complexities of auctions. There are many ways to stage them: for example, in a so-called “English auction” the item on offer simply goes to the highest bidder; whereas in a “Dutch auction” the selling starts from a high price, and bidders submit the price they are willing to pay.
But bidding is affected by many more factors that might reduce the seller’s final profit, cause losses for the winning bidder, create inefficiencies of allocation, or harm the public good. The work of the two laureates has helped to reduce these problems and to suggest new, more efficient ways for auctions to be conducted.
One problem is that different bidders can have different degrees of knowledge about an item for sale. For example, in a property auction, all bidders for a property will have access to some public information such as its resale value. But other kinds of information — such as hidden structural damage — will be private and not known to everyone.
A bidder who does not have such information might end up overpaying if they want to buy the property. They might be able to infer what others know about the value if bids are public – and people start to drop out – but not if bids are private.
In the late 1960s and 1970s, Wilson showed what happens to prices and profits in auctions when bidders have different degrees of private information.
Furthermore, if information about a property is highly uncertain — if the nature of the neighbourhood is rapidly changing, say — that could make buyers cautious and reduce the seller’s profit. In the 1980s, Milgrom — a former doctoral student of Wilson’s — developed models (partly in conjunction with Robert Weber of Northwestern University) that showed there is then an incentive for sellers to gather and share expert information with bidders, within different auction formats. The predictions of how such public information helps prevent losses to sellers and increases their revenue have been born out by experiments, says Kagel.
A spectrum of options
Auctions can be more complex when the goods for sale are divisible into parts or batches — for example, when governments sell licenses to companies bidding to operate in energy, telecommunications or transportation markets. One issue for such auctions is that sellers are vulnerable to collusion between buyers to keep the buying price down. Wilson’s work in the 1970s helped to identify these problems and to design new auctions to avoid them, for example in markets for electricity provision.
The sales of items might also be interdependent. A classic example in the 1990s was the sale of radio-frequency bands to telecom companies for mobile-phone networks — which many countries decided was best done through auctions.
If rights to frequency bands were simply auctioned region by region, a national telecoms company couldn’t be sure of acquiring the same frequency everywhere. And the value to them for one region would depend on whether they could buy the same frequency band elsewhere. The resulting patchwork of coverage would be inconvenient for users too.
To tackle such problems, Milgrom and Wilson (and independently, McAfee) devised the simultaneous multiple-round auction (SMRA). Here, bidders can place bids over several rounds of bidding. This gives them a chance to glean something about others’ private information while bidding, creating fairer and more efficient outcomes.
This approach was used in 1994 for auctioning telecom licenses in the United States, and has been adopted in Canada, India, and several European and Scandinavian countries. Milgrom has also devised other formats that ease some of the shortcomings of the SMRA.
“Unlike many theoreticians, Wilson and Milgrom brought their work to the real world, and transformed government policies toward auctions around the world,” says McAfee.
“There was no question that these two would win the Nobel prize at some point,” says economist Paul Klemperer of the University of Oxford. “It could have happened at any time in the past 20 years.”
“One could even imagine Paul Milgrom having a second Nobel prize,” he adds, for his work in information economics and industrial organization. Milgrom has given a Nobel acceptance speech before: in 1996, as a stand-in for William Vickery, who died three days after the announcement of his prize for laying the foundations of auction theory in the 1960s.
The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2020 was awarded jointly to Paul R. Milgrom and Robert B. Wilson “for improvements to auction theory and inventions of new auction formats.”
Prize announcement
Announcement of the 2020 Prize in Economic Sciences by Professor Göran K. Hansson, Secretary General of the Royal Swedish Academy of Sciences, on 12 October 2020.
“This prize is about avoiding the winner’s curse”
Immediately after the announcement, Tommy Andersson, member of the committee for the Prize in Economic Sciences, was interviewed by freelance journalist Joanna Rose regarding the 2020 Prize in Economic Sciences.
Press release: The Prize in Economic Sciences 2020
“for improvements to auction theory and inventions of new auction formats”
Their theoretical discoveries have improved auctions in practice
This year’s Laureates, Paul Milgrom and Robert Wilson, have studied how auctions work. They have also used their insights to design new auction formats for goods and services that are difficult to sell in a traditional way, such as radio frequencies. Their discoveries have benefitted sellers, buyers and taxpayers around the world.
People have always sold things to the highest bidder, or bought them from whoever makes the cheapest offer. Nowadays, objects worth astronomical sums of money change hands every day in auctions, not only household objects, art and antiquities, but also securities, minerals and energy. Public procurements can also be conducted as auctions.
Using auction theory, researchers try to understand the outcomes of different rules for bidding and final prices, the auction format. The analysis is difficult, because bidders behave strategically, based on the available information. They take into consideration both what they know themselves and what they believe other bidders to know.
Robert Wilson developed the theory for auctions of objects with a common value – a value which is uncertain beforehand but, in the end, is the same for everyone. Examples include the future value of radio frequencies or the volume of minerals in a particular area. Wilson showed why rational bidders tend to place bids below their own best estimate of the common value: they are worried about the winner’s curse – that is, about paying too much and losing out.
Paul Milgrom formulated a more general theory of auctions that not only allows common values, but also private values that vary from bidder to bidder. He analysed the bidding strategies in a number of well-known auction formats, demonstrating that a format will give the seller higher expected revenue when bidders learn more about each other’s estimated values during bidding.
Over time, societies have allocated ever more complex objects among users, such as landing slots and radio frequencies. In response, Milgrom and Wilson invented new formats for auctioning off many interrelated objects simultaneously, on behalf of a seller motivated by broad societal benefit rather than maximal revenue. In 1994, the US authorities first used one of their auction formats to sell radio frequencies to telecom operators. Since then, many other countries have followed suit.
“This year’s Laureates in Economic Sciences started out with fundamental theory and later used their results in practical applications, which have spread globally. Their discoveries are of great benefit to society,” says Peter Fredriksson, chair of the Prize Committee.
Paul R. Milgrom, born 1948 in Detroit, USA. Ph.D. 1979 from Stanford University, Stanford, USA. Shirley and Leonard Ely Jr. Professor of Humanities and Sciences, Stanford University, USA.
Robert B. Wilson, born 1937 in Geneva, USA. D.B.A. 1963 from Harvard University, Cambridge, USA. Adams Distinguished Professor of Management, Emeritus, Stanford University, USA.
The Prize amount: 10 million Swedish kronor, to be shared equally between the Laureates. Further information: www.kva.se and http://www.nobelprize.org Press contact: Eva Nevelius, Press Secretary, +46 70 878 67 63, eva.nevelius@kva.se Experts: Tommy Andersson, +46 73 358 26 54, tommy.andersson@nek.lu.se, Tore Ellingsen, +46 70 796 10 49, tore.ellingsen@hhs.se, Torsten Persson, +46 79 313 39 04, torsten.persson@iies.su.se, Committee for the Prize in Economic Sciences in Memory of Alfred Nobel
Why Do Some COVID-19 Patients Infect Many Others, Whereas Most Don’t Spread the Virus At All?
Guest Reporter: Jason S Zielonka, MD
One of the key parameters in COVID-19 pandemic epidemiology has been to define the spread metrics, basically identifying how a host spreads the virus to uninfected individuals. The pattern of spread can impact how and which preventative measures such as social distancing and hand washing can impact spread patterns. In particular, two metrics, the average number of new patients infected by each host (the reproduction number, R) and a factor representing the tendency to cluster (the dispersion factor, k) can be used to describe and model the spread of a virus quite well. Higher values of R mean more people are infected by a single host, i.e, the disease is more contagious; lower values of k mean that a host infects a larger number of new patients, i.e., the disease is more clustered.
The reproduction number, R, for SARS-CoV-2, without social distancing, is about 3. But this is an average, taken over an aggregate of patients. For most individuals, R is zero, i.e., most patients do not transmit the virus to others. For comparison, SARS and MERS, both coronaviruses, had R > 3 and the 1918 influenza pandemic had R >> 3. So what determines viral spread and how can we use that information to treat and eradicate SARS-CoV-2?
In 2005, by modeling the Chinese SARS outbreak and comparing the model to the real-world data, Lloyd-Smith and co-authors were able to determine that SARS had a k of about 0.16. MERS, in 2012, was estimated to have k around 0.25; the 1918 pandemic, by contrast, had a k of 1, meaning it had very little cluster effect. The current modeling indicates that k for SARS-CoV-2 is not conclusive, but it appears higher than k for either SARS or MERS.
This work has provided insights into some of the factors influencing cluster spread, which can be controlled in a more specific way than quarantining an entire population. There will be individual variance, but we know that people are particularly infectious over a certain time period; that certain activities are more conducive to droplet formation and wider spread, and that being outdoors rather than in confined and noisy indoor locations leads to less spread. This can all lead to better, faster and more tolerable approaches to either future pandemics or to a recurrence of SARS-CoV-2.
Science’s COVID-19 reporting is supported by the Pulitzer Center and the Heising-Simons Foundation.
Researchers have used CRISPR gene-editing technology to come up with a test that detects the pandemic coronavirus in just 5 minutes. The diagnostic doesn’t require expensive lab equipment to run and could potentially be deployed at doctor’s offices, schools, and office buildings.
“It looks like they have a really rock-solid test,” says Max Wilson, a molecular biologist at the University of California (UC), Santa Barbara. “It’s really quite elegant.”
CRISPR diagnostics are just one way researchers are trying to speed coronavirus testing. The new test is the fastest CRISPR-based diagnostic yet. In May, for example, two teams reported creating CRISPR-based coronavirus tests that could detect the virus in about an hour, much faster than the 24 hours needed for conventional coronavirus diagnostic tests.CRISPR tests work by identifying a sequence of RNA—about 20 RNA bases long—that is unique to SARS-CoV-2. They do so by creating a “guide” RNA that is complementary to the target RNA sequence and, thus, will bind to it in solution. When the guide binds to its target, the CRISPR tool’s Cas13 “scissors” enzyme turns on and cuts apart any nearby single-stranded RNA. These cuts release a separately introduced fluorescent particle in the test solution. When the sample is then hit with a burst of laser light, the released fluorescent particles light up, signaling the presence of the virus. These initial CRISPR tests, however, required researchers to first amplify any potential viral RNA before running it through the diagnostic to increase their odds of spotting a signal. That added complexity, cost, and time, and put a strain on scarce chemical reagents. Now, researchers led by Jennifer Doudna, who won a share of this year’s Nobel Prize in Chemistry yesterday for her co-discovery of CRISPR, report creating a novel CRISPR diagnostic that doesn’t amplify coronavirus RNA. Instead, Doudna and her colleagues spent months testing hundreds of guide RNAs to find multiple guides that work in tandem to increase the sensitivity of the test.
That’s still not as good as the conventional coronavirus diagnostic setup, which uses expensive lab-based machines to track the virus down to one virus per microliter, says Melanie Ott, a virologist at UC San Francisco who helped lead the project with Doudna. However, she says, the new setup was able to accurately identify a batch of five positive clinical samples with perfect accuracy in just 5 minutes per test, whereas the standard test can take 1 day or more to return results.
The new test has another key advantage, Wilson says: quantifying a sample’s amount of virus. When standard coronavirus tests amplify the virus’ genetic material in order to detect it, this changes the amount of genetic material present—and thus wipes out any chance of precisely quantifying just how much virus is in the sample.
By contrast, Ott’s and Doudna’s team found that the strength of the fluorescent signal was proportional to the amount of virus in their sample. That revealed not just whether a sample was positive, but also how much virus a patient had. That information can help doctors tailor treatment decisions to each patient’s condition, Wilson says.
Doudna and Ott say they and their colleagues are now working to validate their test setup and are looking into how to commercialize it.
The University of California has a proud legacy of winning Nobel Prizes, 68 faculty and staff have been awarded 69 Nobel Prizes.
Reporter: Aviva Lev-Ari, PhD, RN
Article ID #284: The University of California has a proud legacy of winning Nobel Prizes, 68 faculty and staff have been awarded 69 Nobel Prizes. Published on 10/11/2020
WordCloud Image Produced by Adam Tubman
PREVIOUS PRIZE WINNERS
The University of California has a proud legacy of winning Nobel Prizes that stretches all the way back to 1939, when Ernest O. Lawrence was awarded the prize in physics for his invention of the cyclotron. In the years since, dozens of other University of California faculty and staff have been awarded this highest international honor for their contributions in medicine, economics, physics and more.
Today, 68 faculty and staff have been awarded 69 Nobel Prizes.
View as grid
Name
Campus affiliation
Field of study
Year of award
Jennifer Doudna
UC Berkeley
Chemistry
2020
Andrea Ghez
UCLA
Physics
2020
Reinhard Genzel
UC Berkeley
Physics
2020
Randy Schekman
UC Berkeley
Physiology or medicine
2013
Lloyd Shapley
UCLA
Economics
2012
Shinya Yamanaka
UC San Francisco
Physiology or medicine
2012
Saul Perlmutter
UC Berkeley/Berkeley Lab
Physics
2011
Elizabeth Blackburn
UC San Francisco
Physiology or medicine
2009
Oliver E. Williamson
UC Berkeley
Economics
2009
Roger Y. Tsien
UC San Diego
Chemistry
2008
George Smoot
UC Berkeley/Berkeley Lab
Physics
2006
Richard R. Schrock
UC Riverside
Chemistry
2005
David Gross
UC Santa Barbara
Physics
2004
Finn E. Kydland
UC Santa Barbara
Economic sciences
2004
Irwin Rose
UC Irvine
Chemistry
2004
Robert F. Engle
UC San Diego
Economic sciences
2003
Clive Granger
UC San Diego
Economic sciences
2003
Sydney Brenner
UC San Diego
Physiology or medicine
2002
George Akerlof
UC Berkeley
Economic sciences
2001
Alan J. Heeger
UC Santa Barbara
Chemistry
2000
Herbert Kroemer
UC Santa Barbara
Physics
2000
Daniel McFadden
UC Berkeley
Economic sciences
2000
Louis J. Ignarro
UCLA
Physiology or medicine
1998
Walter Kohn
UC Santa Barbara
Chemistry
1998
Robert B. Laughlin
UC Livermore Lab
Physics
1998
Paul D. Boyer
UCLA
Chemistry
1997
Steven Chu
UC Berkeley/Berkeley Lab
Physics
1997
Stanley B. Prusiner
UC San Francisco
Physiology or medicine
1997
Paul Crutzen
UC San Diego
Chemistry
1995
Mario J. Molina
UC San Diego
Chemistry
1995
Frederick Reines
UC Irvine
Physics
1995
F. Sherwood Rowland
UC Irvine
Chemistry
1995
John Harsanyi
UC Berkeley
Economic sciences
1994
Harry Markowitz
UC San Diego
Economic sciences
1990
J. Michael Bishop
UC San Francisco
Physiology or medicine
1989
Harold E. Varmus
UC San Francisco
Physiology or medicine
1989
Donald J. Cram
UCLA
Chemistry
1987
Yuan T. Lee
UC Berkeley/Berkeley Lab
Chemistry
1986
Gerard Debreu
UC Berkeley
Economic sciences
1983
Czeslaw Milosz
UC Berkeley
Literature
1980
Roger Guillemin
UC San Diego
Physiology or medicine
1977
Renato Dulbecco
UC San Diego
Physiology or medicine
1975
George Emil Palade
UC San Diego
Physiology or medicine
1974
John Robert Schrieffer
UC Santa Barbara
Physics
1972
Hannes Alfven
UC San Diego
Physics
1970
Luis Walter Alvarez
UC Berkeley/Berkeley Lab
Physics
1968
Robert W. Holley
UC San Diego
Physiology or medicine
1968
Julian Schwinger
UCLA
Physics
1965
Charles H. Townes
UC Berkeley
Physics
1964
Maria Goeppert-Mayer
UC San Diego
Physics
1963
Francis Crick
UC San Diego
Physiology or medicine
1962
Melvin Calvin
UC Berkeley/Berkeley Lab
Chemistry
1961
Donald A. Glaser
UC Berkeley/Berkeley Lab
Physics
1960
Willard Libby
UCLA
Chemistry
1960
Owen Chamberlain
UC Berkeley/Berkeley Lab
Physics
1959
Emilio Segrè
UC Berkeley/Berkeley Lab
Chemistry
1959
Linus Pauling
UC San Diego
Chemistry, Peace
1954, 1962
Edwin McMillan
UC Berkeley/Berkeley Lab
Chemistry
1951
Glenn T. Seaborg
UC Berkeley/Berkeley Lab
Chemistry
1951
William Giauque
UC Berkeley
Chemistry
1949
John Howard Northrop
UC Berkeley
Chemistry
1946
Wendell Meredith Stanley
UC Berkeley
Chemistry
1946
Ernest Lawrence
UC Berkeley/Berkeley Lab
Physics
1939
Harold Urey
UC San Diego
Chemistry
1934
HOW UC NOBEL LAUREATES ARE COUNTED
Our list of Nobel Prize winners includes University of California faculty and staff who were affiliated with UC when they received their award. It also includes faculty and staff who joined UC after receiving their Nobel Prize. And although we are immensely proud of the many UC alumni who have gone on to receive Nobel Prizes, they are not counted here. Nor are visiting scholars or others who had short-term assignments with UC. Finally, our Nobelist list is a “lifetime” list and includes those living, retired or deceased.
Tiny biologic drug to fight COVID-19 show promise in animal models
Reporter : Irina Robu, PhD
A research team at University of Pittsburg School of Medicine identified an antibody component that is 10 times smaller than a full-sized antibody. Their research published in Cell, indicates that the drug, Ab8 based on it is effective in mice and hamsters. The research was started by screening a library of about 100 billion antibody fragments to identify candidates that bound tightly to the spike protein on SARS-CoV-2’s surface, which the virus uses to enter and infect human cells.
A typical antibody consists of two heavy chains and two light chains. The chosen molecule is the variable domain of the heavy chain of an immunoglobulin, which is a type of antibody. The heavy chain variable domain is essential for binding with an antigen. Ab8 was created by fusing the variable, heavy chain domain with part of the immunoglobulin tail region, giving it immune functions but doing so with a molecule that’s about half the size of a full immunoglobulin.
The smaller size of the antibody can improve the therapeutic efficacy for infectious diseases and can be delivered through inhalation. Their research showed that Ab8 completely neutralized SARS-CoV-2 in lab dishes. The drug developed showed that inhibited the virus in lung tissue in animal body even at the lowest dose 2 mg/kg as compared to untreated controls.
The research team is looking to determine the drug effect in hamsters, which were reported to have better clinical signatures of COVID-19. And the hamsters that got the drug display less severe pneumonia that did the control animals. Drugs with alternative administration routers could provide additions to the first wave of COVID-19 therapies and vaccines.
What is more important, Ab8 does not appear to bind to human cells which is a good sign that it won’t have negative side effects.
Llama inspired “AeroNabs” to strangle COVID-19 with an inhaler
Reporter : Irina Robu, PhD
Llama and other camelids fight off pathogens like viruses with tiny antibodies called nanobodies. A USCF team used protein engineering to make a synthetic nanobody that prevents the spike protein on the surface of SARS-CoV-2 from binding to healthy cells and infecting them. The team indicates promising preclinical results for aerosol formulation and can be used as a self-administered form of protein against the virus.
According to the UCSF team, an aerosolized form of nanobody exhibit SARS-CoV-2 incapable of binding to the ACE2 receptor on healthy cells that line airways. The synthetic nanobody stays functional after it was freeze-dried, exposed to heat and aerosolized.
The researchers ongoing screening a library of synthetic nanobodies, ultimately landing on 21 that banned the spike-ACE2 interaction. The scientists decided that in order to be truly efficient, a nanobody based treatment with interact with all three of the receptor binding domains on the spike protein that attaches to ACE2. Their solution was to engineer a molecular chain that connects three nanobodies together, which would ensure that when one of the nanobodies attached to RBD, the others would link to the two remaining RBD. This molecular chain resulted in a drug candidate proved to be 200,000 times more potent than a single antibody.
At the same time, ExeVir Bio is also developing an aerosolized COVID-19 treatment inspired by llamas and is currently trying to advance its candidate into clinical trials by the end of the year. Their main candidate, VHH-72Fc was considered to bind to an epitope that is found both in SARS-CoV-2 and SARS-CoV. Yet, the llama inspired treatments are still behind antibody efforts like that of Regeneron.
Even though, there are multiple vaccines in development, researchers at UCSF believe that AeroNabs can be used as a sort of personal protective equipment until vaccines become available. The same researchers are planning human trials and are in discussion with partners who can provide manufacturing and distribution backing.
AI-controlled sensors could save lives in smart hospitals and homes
Reporter: Irina Robu, PhD
Arnold Milstein, professor of medicine and director of Stanford’s Clinical Excellence Research Center along with Fei-Fei Li, computer science professor and graduate student Albert Haque believe that having the ability to build technologies into the physical spaces where health care is delivered minimize the rate of fatal errors that occur lately due to sheer volumes of patients and complexity of their care. Even though, the technology is a very promising, it also raises legal and regulatory issues as well as privacy concerns.
They believe that the AI can alert clinicians and patient visitors when they fail to sanitize their hands before entering hospital room for example. Also, AI tools can be built into smart homes where the technology can monitor the frail elderly for behavioral clues of a health crises and can let in-home caregivers, remotely located clinicians and patients to make life saving interventions.
Li and Milstein co-direct the 8-year-old Stanford Partnership in AI-Assisted Care (PAC), one of a growing number of centers, including those at Johns Hopkins University and the University of Toronto, where technologists and clinicians have teamed up to develop ambient intelligence technologies to help health care providers manage patient volumes, roughly 24 million Americans required an overnight hospital stay in 2018.
Haque, who compiled the 170 scientific papers cited in the Nature article, the availability of infrared sensors that are inexpensive enough to build into high-risk care-giving environments, and the rise of machine learning systems as a way to use sensor input to train specialized AI applications in health care.
The infrared technologies are of two types. The first is active infrared, such as the invisible light beams used by TV remote controls. Nonetheless as an alternative of simply beaming invisible light in one direction, like a TV remote, new active infrared systems use AI to compute the time it takes the invisible rays to bounce back to the source, like a light-based form of radar that maps the 3D outlines of a person or object.
These alert systems are being confirmed to see if they can reduce the number of ICU patients who get nosocomial infections due to failure of other people in the hospital to fully observe to infection prevention protocols.
The second type of infrared technology are passive detectors, that allow night vision goggles to generate thermal images from the infrared rays generated by body heat. In a hospital setting, a thermal sensor above an ICU bed would allow the governing AI to sense twitching beneath the sheets, and alert clinical team members to forthcoming health crises without continuously going from room to room.
Constant monitoring by ambient intelligence systems in a home environment could also be used to detect clues of serious illness or potential accidents, and alert caregivers to make timely interventions. . Researchers are still developing activity recognition algorithms that can examine through infrared sensing data to detect variations in habitual behaviors, and benefit caregivers get a more holistic view of patient health.
Noninvasive blood test can detect cancer 4 years before conventional diagnosis
Reporter : Irina Robu, PhD
Several international researchers at Fudan University and at Singlera Genomics have developed a noninvasive blood test, PanSeer that can detect whether a patient with five common type of cancers such as stomach, esophageal, colorectal, lung and liver cancer; four years before the condition can be diagnosed by the current methods. Early detection is significant for the reason that the survival of cancer patients increases when the disease is identified at early stages, as the tumor can be surgically removed or treated with suitable drugs. Yet, only a partial number of early screening tests exist for a few cancer types.
The blood test detected cancer in 91 percent of samples from individuals who have been asymptomatic when the samples were collected, but only diagnosed with cancer one to four years later. It was found that the test can accurately detect cancer in 88 percent from samples of 113 patience who were diagnosed. The blood test also detects cancer free samples 95 percent of the time.
What is clear is that the study is unique, in that the scientists had access to blood samples from patients who were asymptomatic but not diagnosed yet. This permitted the researchers to design a test that can find a cancer marker much earlier than conventional diagnosis. The sample were collected as part of 10-year longitudinal study started in 2007 by Fudan University in China.
The researchers highlight that the PanSeer assay is improbable to predict which patients will later go on to develop cancer. As a substitute, it is most possible identifying patients who already have cancerous growths, but continue to be asymptomatic for current detection methods. The team decided that further large-scale longitudinal studies are needed to confirm the potential of the test for the early detection of cancer in pre-diagnosis individuals.
FDA Authorizes Convalescent Plasma for COVID-19 Patients
Reporter: Irina Robu, PhD
The U.S. Food and Drug Administration authorized convalescent plasma therapy in August 2020 for people with coronavirus disease 2019. The convalescent plasma shows promising efficacy in hospitalized patients with COVID-19 and the benefits outweighs the risk and FDA gave emergency use authorization. The approval is not for any particular convalescent plasma product, but for preparation collected by FDA registered blood establishments from individuals whose plasma contains anti-SARS-CoV-2 antibodies, and who meet all donor eligibility requirements.
What exactly is convalescent plasma ? It is blood donated from patients who have recovered from COVID-19 has antibodies to the virus that causes it. The donated blood is processed by removing blood cells, leaving behind plasma and antibodies, which can be given to people with COVID-19 to boost their ability to fight the virus. According to FDA, COVID-19 covalescent plasma with high antibody titer can be effective in reducing mortality in hospitalized patients, but low antibody titer can be used based on health care provider discretion. FDA also indicated that COVID-19 convalescent plasma may be effective in lessening the severity or shortening the length of COVID-19 illness in some hospitalized patients.
To confirm the results, the FDA recommended randomized trialsas COVID-19 convalescent plasma does not yet describe a new standard of care based on the current available evidence.
Bioresorbable Stent Clinical Trials with New Esprit Below-the-knee Scaffold
Reporter: Irina Robu, PhD
Abbott announced on September 3, 2020, the beginning of the LIFE-BTK clinical trial to evaluate effectiveness and safety of the Esprit BTK Everolimus Eluting Resorbable Scaffold System. The Esprit BTK System consists of a thin strutted scaffold made of poly-L-lactide, a semi-crystalline bioresorbable polymer engineered to resist vessel recoil and provide a platform for drug delivery. The scaffold is coated with poly-D, L-lactide (PDLLA) and the cytostatic drug, everolimus.
This trial is the first Investigational Device Exemption in the US to assess a fully bioresorbable stent to treat blocked arteries below the knees, also known as critical limb ischemia in people battling advanced stages of peripheral artery disease. For people with CLI, blocked vessels weaken blood flow to the lower extremities, which can lead to severe pain, wounds, and in severe cases, limb amputation.
At this time, the standard of care for patients battling critical limb ischemia is balloon angioplasty, which depend on on a small balloon delivered via a catheter to the blockage to compress it against the arterial wall, opening the vessel and restoring blood flow. Yet, blockages treated only with balloon angioplasty have poor short- and long-term results, and in many cases the vessels become blocked again, lacking additional treatment.
Patients treated with balloon angioplasty often require several procedures on treated arteries, and a drug eluting resorbable device is if at all possible suited to provide mechanical support, decrease the chance of the vessel re-narrowing and then slowly disappear over time. At this time, there are no drug eluding stents, drug coated balloons or bare metal stents approved for use below the knee. Since, there is a limited number of options for stents below the knee, the FDA has granted Esprit BTK breakthrough device designation, which simplifies review and pre-market approval timelines.
According to Abbott, Espirit BTK System is not a permanent implant, but it does provide support to an artery right after a balloon angioplasty, stopping the vessel from reclosing. As soon as it is implanted, the scaffold distributes a drug over a few months that encourages healing and keeps the artery open. The scaffold is naturally resorbed into the body over time, like dissolving sutures, and eventually leaves only a healed artery behind.
The LIFE-BTK trial is the first Investigational Device Exemption trial in the U.S. to evaluate a fully dissoluble device to treat critical limb ischemia in people battling advanced stages of peripheral artery disease (PAD). The trial will be run by principal investigators Brian DeRubertis, M.D. (vascular surgeon, UCLA), Sahil Parikh M.D., (interventional cardiologist, New York-Presbyterian/Columbia University Irving Medical Center.
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