Monthly Archives: January 2022

Researchers identify proteins that could predict liver transplant rejection – EurekAlert

Posted: January 27, 2022 at 11:55 pm

image:The Blood Proteoform Atlas (BPA) compiles ~56,000 proteoforms identified from 21 human cells types and plasma view more

Credit: Please credit Kelleher and Levitsky labs at Northwestern University

Northwestern University scientist have discovered families of proteins in the body that could potentially predict which patients may reject a new organ transplant, helping inform decisions about care.

The advancement marks the beginning of a new era for more precise study of proteins in specific cells.

Scientists tend to look at shifting patterns of proteins as if through goggles underwater, taking in just a fraction of available information about their unique structures. But in a new study to be published January 27 in the journal Science, scientists took a magnifying glass to these same structures and created a clarified map of protein families. They then held the map up in front of liver transplant recipients and found new indicators in immune cell proteins that changed with rejection.

The result, the Blood Proteoform Atlas (BPA), outlines more than 56,000 exact protein molecules (called proteoforms) as they appear in 21 different cell types almost 10 times more of these structures than appeared in similar previous studies.

Scratching the surface of potential

Were working to create the protein equivalent of the Human Genome Project, said Neil Kelleher, a leading expert in proteomics and co-corresponding author of the paper. The BPA is a microcosm of that, including a specific-use case.

Kelleher is the Walter and Mary Glass Professor of Molecular Biosciences and professor of chemistry in NorthwesternsWeinberg College of Arts and Sciencesand a professor of medicine inNorthwestern University Feinberg School of Medicine.He is also the director of theChemistry of Life Processes Institute(CLP) and faculty director ofNorthwestern Proteomics, a center of excellence within CLP that develops novel platforms for drug discovery and diagnostics.

Each human gene has at least 15 to 20 unique forms of processed proteins (proteoforms). And with 20,300 individual genes in the human body, there are millions of proteoforms created by genetic variation, modification or splicing. Kelleher said with a complete roadmap of each genes family of proteinsthe goal of a major science initiative known as the Human Proteoform Project discoveries about disease, aging and new therapeutics will accelerate.

The Kelleher lab uses state-of-the-art mass spectrometry and data analysis to identify proteofoms in cells and blood efficiently, keeping proteoforms intact in a form of top-down analysis rather than cutting them up into tiny pieces as with the industry standard.

Were starting to see the complexity, he said. In this paper, we demonstrate patient-, cell type- and proteoform-specific measurements, which allows us to get to better biomarkers.

A blood test for liver transplant rejection

Having team members across disciplines allows the project to conceptualize a move from lab bench to bedside. As Kelleher probes the scientific basis for phenomena in the cell, co-corresponding author and Northwestern Medicine transplant hepatologist Josh Levitsky works with him to understand how these could be applied to a specific system.

Levitsky, professor of medicine, surgery and medical education at Feinberg, originally connected with Kelleher through his leadership in the biomarkers space, in which measurable signs in the blood are used to predict health metrics in patients facing disorders and in this instance, liver transplant rejection.

It was really important for Neil that there was a biologically relevant example to contextualize how these proteoform panels can identify diseases non-invasively as markers, Levitsky said. And theres also a need in my field to have mechanistic biomarkers that are more relevant to their immune biological pathways. This could be the start of a new era in cell-specific markers.

Physicians must suppress the immune system with drug therapy and monitor liver transplant recipients for signs of rejection, often only responding after an episode has begun. Guesswork throughout this process could be eliminated with specific knowledge about whats happening at the most granular level.

With the BPA as a reference map, the team took blood samples from participants in one of Levitskys biomarker collection studies. They examined which proteoforms seemed to activate in response to the transplant and identified those that changed compared to patients without rejection.

Next, the Levitsky and Kelleher team developed a panel of 24 proteoforms from the initial study and looked at them in transplant recipient samples from across the country. They found the same proteoforms lit up as in the first trial.

Moving the field forward

The promise here is to be able to use this panel moving forward to be able to identify patients who have no signs of rejection versus those who have very early evidence of rejection, Levitsky said. If we can pick up on this several weeks before rejection actually happens, we might be able to modify immunosuppression.

Levitsky continues to examine how proteoforms change in transplant recipients over time to develop additional biomarkers that may inform how he treats patients down the line. Kelleher said as the number of cell types in the atlas grows, so too will potential ways to use it. In addition to broadening understandings of human biology, the BPA could have similar applications across immune disorders.

The study, The Blood Proteoform Atlas: A reference map of proteoforms in human hematopoietic cells, was conducted across six institutions with 26 scientists. Rafael D. Melani, a research assistant professor in the Kelleher Group, was the first author of the paper, along with Vincent R. Gerbasi, also from Northwestern, and Lissa C. Anderson from Florida State University.

The research was supported by the National Institute of General Medical Sciences of the National Institutes of Health (award numbers: P41 GM107569, R21LM013097, T32 GM105538 and R21 AI135827), the Human Biomolecular Atlas Program (award number: UH3 CA246635-02), Paul G. Allen Frontiers Program Award (award number 11715), the Knut and Alice Wallenberg Foundation grant (2016.0204) and the Swedish Research Council grant (2017-05327). Work performed at the National High Magnetic Field Laboratory is supported by the National Science Foundation Division of Materials Research and Division of Chemistry and the State of Florida.

The Blood Proteoform Atlas: A reference map of proteoforms in human hematopoietic cells

28-Jan-2022

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Researchers identify proteins that could predict liver transplant rejection - EurekAlert

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FDA Clears MCO-010 Gene Therapy as IND for Stargardt Macular Degeneration – MD Magazine

Posted: at 11:55 pm

A Phase 2 trial can begin investigations on MCO-010 gene therapy as treatment for patients with Stargardt disease. The multi-characteristic opsin ambient-light activatable optogenetic monotherapy may restore vision in patients with this rare macular degeneration.

The developer of MCO-010, Nanoscope Therapeutics Inc, announced that it received investigational new drug (IND) clearance from the US Food and Drug Administration (FDA).

The trial is expected to start in H1-2022. MCO-010 is designated as an orphan drug by the FDA for Stargardt disease and retinitis pigmentosa (RP).

The clincal-stage biotechnology company is currently conducting a Phase 2b multicenter, randomized, sham-controlled, double-masked study of MCO-010 for patients with retinitis pigmentosa.

Retinitis pigmentosa is a group of rare, genetic disorders associated with difficulty seeing at night and the inability to see peripherally due to the breakdown and loss of cells in the retina.

Stargardt is an inherited rare disease that affects children and adults. As a result of this retinal disease, photoreceptors in the eye degenerate. MCO-010 gene therapy makes them photosensitive by reprogramming the healthy retinal cells.

MCO-010 is a single intravitreal injection administered in a medical office setting. Proprietary AAV2 vectors deliver the MCO genes to the cells where they express polychromatic opsins and enable vision.

Patients with Stargardt and retinitis pigmentosa can utilize this therapy regardless of underlying gene mutations.

"Presently allexisting trialsattemptto slow down the progressionof vision loss in patients with Stargardt disease, Optogenetic approach is to restore vision. Thiscan bea groundbreaking attempt to evaluate optogenetic gene therapyto improve vision inStargardt patients. I'm excited by the potential MCO-010 has to restore vision for many patients with sight loss caused by outer retinal dystrophies including dry age-related macular degeneration," David Boyer, MD, Retina-Vitreous Associates Medical Group, adjunct clinical professor of ophthalmology, Keck School of Medicine, University of Southern California said in a statement.

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EdiGene Enters Strategic R&D Collaboration with Haihe Laboratory of Cell Ecosystem to Develop Hematopoietic Stem Cell Regenerative Therapies and…

Posted: at 11:55 pm

BEIJING & CAMBRIDGE, Mass.--(BUSINESS WIRE)--EdiGene, Inc., a global biotechnology company focused on translating gene-editing technologies into transformative therapies for patients with serious genetic diseases and cancer, announced a research and development collaboration with Haihe Laboratory of Cell Ecosystem to develop hematopoietic stem cell regenerative therapies and platform technology by combining resources and expertise from both sides.

The Haihe Laboratory of Cell Ecosystem, run by the Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, is focused on conducting fundamental research, innovation, and translation in the cell ecosystem.

Under the agreement, both parties will jointly develop hematopoietic stem cell regenerative therapies, including the development of innovative genetically-modified hematopoietic stem cell therapies and the exploration of novel biomarkers to optimize quality control for stem cell production.

With top-notch resources and industry-university-research cooperation, well facilitate the development of cell-based medicine and therapies, said Professor Tao Cheng, Deputy Director of Haihe Laboratory of Cell Ecosystem and President of the Institute of Hematology and Blood Diseases Hospital at the Chinese Academy of Medical Sciences and Peking Union Medical College, a leading hematology researcher who has made a series of discoveries relating to the regulatory and regenerative mechanisms of hematopoietic stem cells. Hematopoietic stem cells (HSCs) have the potential for long-term self-renewal and can differentiate into various types of mature blood cells. These stem cells can be harnessed to provide treatment for a broad range of diseases such as hematological tumors, autoimmune diseases, and hereditary blood disorders. We believe that this collaboration with EdiGene will accelerate the innovation and translation in the field of HSCs, thus enabling healthier patients with new therapies."

Professor Cheng was awarded the second prize of the National Natural Science Award 2020 as the first author of work on basic and translational research that advanced the development of adult hematopoietic stem cells for therapeutic applications.

EdiGene is scaling up clinical translation and development of the first gene-editing hematopoietic stem cell therapy in China following the 2021 approval by the China National Medical Products Administration its IND for its investigational therapy ET-01. Our team has extensive experience in the development and translation of cutting-edge technologies including hematopoietic stem cell and gene editing, said Dong Wei, Ph.D., CEO of EdiGene. "This collaboration with Haihe Laboratory of Cell Ecosystem will further our exploration in the field of hematopoietic stem cells. The partnership with this leading academic institute and our translational know-how enable us to move forward in bringing more innovative treatment options to patients in China and around the world.

In 2021, EdiGene initiated a Phase I multicenter clinical trial of ET-01, its gene-editing hematopoietic stem cell therapy for transfusion-dependent -thalassemia. EdiGene has enrolled the first patient at the Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. Currently, the clinical trial is being conducted in Tianjin and Guangdong-Hong Kong-Macao Greater Bay Area (Greater Bay Area). EdiGene also presented its latest research on new surface markers and migration of hematopoietic stem cells at the 63rd Annual Meeting of the American Society of Hematology (ASH) in 2021.

About Haihe Laboratory of Cell Ecosystem

The Haihe Laboratory of Cell Ecosystem ("the Laboratory"), run by the Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, is one of the five registered Haihe Laboratories approved by Tianjin Municipal People's Government. With the goal of promoting population health with cell ecosystem, the Laboratory adheres to developing technological frontier, enhancing peoples health, and promoting research, innovation, and development of cell ecosystem in five key areas: cellular ecosystem, cellular ecology and immunity, cellular ecological imbalance and major diseases, cellular ecological reconstruction and frontier technology of cellular ecological research.

About Institute of Hematology and Blood Diseases Hospital (IH), Chinese Academy of Medical Sciences & Peking Union Medical College (CAMS/PUMC)

Founded in 1957, IH is a tertiary specialty hospital under the National Health Commission of China and is the supporting unit of the National Clinical Research Center of Hematologic Diseases and the State Key Laboratory of Experimental Hematology. It is also the main founding unit of Tianjin Base, the core base of the Chinese medical science and technology innovation system with the goal of becoming "the innovation hub of hematology in China." IH mainly engages in basic research, applied research, clinical diagnosis and treatment of hematological diseases, standard-setting, new technology research, new drug evaluation, and translation in hematology and related fields. IH is leading in the diagnosis and treatment of hematological diseases in China and a global scale and has made original achievements. Since 2010, IH has been awarded first place in the Hospital Specialty Reputation Ranking (Hematology) for 12 consecutive years. It has won first place in the Hematology Specialty Ranking for ten consecutive years since 2010 and ranked the first in hematology by the Scientific and Technological Evaluation Metrics (STEM) for Chinese hospitals for eight consecutive years since 2014.

About EdiGene, Inc

EdiGene is a global, clinical-stage biotechnology company focused on translating gene editing technologies into transformative therapies for patients with serious genetic diseases and cancer. The company has established its proprietary ex vivo genome-editing platforms for hematopoietic stem cells and T cells, in vivo therapeutic platform based on RNA base editing, and high-throughput genome-editing screening to discover novel targeted therapies. Founded in 2015, EdiGene is headquartered in Beijing, with offices in Guangzhou and Shanghai, China and Cambridge, Massachusetts, USA. More information can be found at http://www.EdiGene.com.

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Bertrand Coste and the pressure receptor – American Society for Biochemistry and Molecular Biology

Posted: at 11:55 pm

The 2021 Nobel Prize in physiology or medicine was awarded to David Julius and Ardem Patapoutian for their discoveries of receptors that sense temperature and pressure, work that exemplifies how difficult research can be. Through hundreds of mice, tens of thousands of cells and millions of bacterial colonies, the research groups that made the winning discoveries persisted in asking important questions about how the brain detects its surroundings.

Researchers in Julius and Patapoutians labs who made key discoveries at the bench worked through many technical problems and disappointments in pursuit of the molecules behind sensation. The Secret History of Touch tells five stories of their persistence. Here is the fourth.

COURTESY OF THE NOBEL FOUNDATION

A schematic shows how Bertrand Coste used patch-clamp electrophysiology to discover piezo1, applying a mechanical force to a cell while also measuring current (top line). Later experiments showed that the protein is a channel that opens in response to mechanical forces against a nearby membrane.

In the mid-2000s, Ardem Patapoutian, known for his studies of temperature sensitive ion channels called TRPs, wanted to transition into studying mechanotransduction.

Patapoutian did not have time for an interview for this story, but in an email, he wrote, After studying temperature sensation for 10 years, it was a natural transition to ask how mechanical force is sensed.

Like the search for the cold receptor, it was another risky question, fraught with the possibility of failure. Sanjeev Ranade, who joined Patapoutians lab as a graduate student to study thermosensation, said, Many labs had been looking for the identity of the gene or genes that allow us to sense touch. Many labs were not successful in finding these genes.

Courtesy of the Nobel Foundation

A schematic shows how Bertrand Coste used patch-clamp electrophysiology to discover piezo1, applying a mechanical force to a cell while also measuring current (top line). Later experiments showed that the protein is a channel that opens in response to mechanical forces against a nearby membrane.

So when physiologist Bertrand Coste joined the lab as a postdoc to search for the protein that lets human neurons sense pressure, Ranade said, It was one of those almost I cant believe youre doing this kind of projects.

Like Makoto Tominaga in David Julius lab, Coste was an experienced electrophysiologist who came to a new lab in California with a reputation for receptor hunting and immediately began to build a new electrophysiology rig. He had studied mechanosensory neurons as a graduate student and was skilled at recording from a neuron with an electrode while gently prodding it with a tiny glass probe a technique that few others in the world used.

Recording these mechanically activated currents naturally pushed me to the question of what are the ion channels that are involved in this activity, Coste said. Patapoutians lab, which lately had cloned TRPA1 and TRPM8, struck him as the ideal environment to try to answer the question.

Coste initially planned to sift through the DRG to find neurons that respond to mechanostimulation and then extract their RNA and screen for the genes governing pressure sensation. But pilot experiments made it clear that the strategy was impractical. So he took a different approach: He tested as many cell lines as he could lay hands on, looking for one that would respond to pressure by depolarizing. With immortalized cell lines you have endless materials, he said. Its easy to use, and every cell is a clone of the other cells.

Scripps Research Institute

From left, Bertrand Coste, Ardem Patapoutian, Bailong Xiao and Seung Eun Kim when Coste and Xiaos paper and Kims paper were published together in Nature in 2012.

Coste found a neuroblastoma line that fit the bill and winnowed down its list of highly expressed genes to the most interesting candidates: transmembrane proteins with unknown function that shared some characteristics with ion channels.

That left a list of dozens of genes. Coste began to use siRNA to knock them down one at a time and then prodded the altered cells, watching for one that would fail to respond to mechanical stimulation. Electrophysiology is highly reliable but also very slow. He averaged about two candidate genes a week, and, for a year or more, every single candidate he tested had no effect on the cells response. Not making progress can be tough. A few months in, after many trials and no success, Coste said, My mood was declining very fast.

We are scientists. We like to think, to problem solve, he said. While planning the screen and working around the technical issues, hed had a chance to solve problems. But the screen itself was very repetitive. Coste brought the problem to Patapoutian, explaining that even though he was excited about the possible results of the project, the mindless grind of doing the same experiment over and over again and getting no result was difficult. Patapoutian, according to Coste, was understanding; he assigned a technician to help and suggested a second, more tractable project he could work at on the side. I was relieved of doing every day the same thing, every day having negative results, Coste said.

Scripps Research Institute

A structure of the piezo channel

Finally, after ruling out 72 candidate genes, Coste found an siRNA that blunted the cells response to mechanical stimulation. Ranade said, They could have easily quit at 72, and said, OK, its been a year, we have nothing. And yet, they found it at 73.

The gene was mysterious, but it was large, with an estimated 24 to 36 transmembrane domains. Besides controlling the neuroblastoma cells mechanical response, when cloned into mechanically inert cells, it made them sensitive. The team dubbed it Piezo, after the Greek word for pressure, and soon found that mice have two closely related Piezo proteins.

Coste said characterizing the channel was exhilarating: After one year of screening every experiment you do is telling you something interesting on the activity of this channel.

Coste and many colleagues in the Patapoutian lab would go on to show that Piezo1 and Piezo2 play integral roles in mammals sense of touch and many other physiological functions. Even before that, Ranade said, it was clear that the finding was important. Every single one of us in the lab, when Bertrand found Piezos, we all kind of knew that he struck gold.

What keeps researchers going through failure after failure? ASBMB Today asked psychologist Ayelet Fishbach, who studies motivation, work and learning from failure.

Fishbach and colleagues recently published a study investigating work-related one-time failures. After taking a two-option multiple choice quiz, Fishbach and colleagues found, participants who had received negative feedback performed worse on a follow-up quiz than those who had received positive feedback.

Although the study investigated one-time failure to guess an insignificant piece of information rather than the longer and more fraught process of research, Fishbach said that its conclusions reflect her own experience as a researcher and mentor.

There are two categories of problems with learning from failure, she said. Cognitively, it can be harder to learn from the unexpected than the expected and more difficult to seek out the reasons that a hypothesis missed the mark than to accept that it was correct. Getting people to pay attention to what didnt work is notoriously hard, she said.

The second category is emotional. It is easier to ignore a failure than to engage with it. And sometimes people especially those with relatively little expertise in a field learn the wrong lesson from failure, concluding that they are unable to execute the task at hand. Whats more, Fishbach said, Doing something with no sense of progress is psychologically hard. You can tell yourself that one day it will pay off, but its not today or yesterday or tomorrow. And people give up.

Much like David Julius, Fischbach said that social support, encouraging words and help with troubleshooting from others can help keep people motivated. But, Julius pointed out, Its not just me. They have to have their own gyroscope. He added that there are times when he has doubted the future of a project and has gotten inspiration from persistent trainees.

Michael Caterina and the capsaicin receptor

How the Julius lab found that an ion channel senses heatMakoto Tominaga, Toby Rosen and TRPV1 heat sensation

Nobelists postdoc searches for a receptor for mint and cold

Patapoutians postdoc unearths the powerful Piezo geneBertrand Coste and the pressure receptor

Nobelists lab pins down pressure sensing in miceSeung Hyun Woo, Sanjeev Ranade and Piezo2 in the sense of touch

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The Angry Preacher: ‘If you’re working against himyou’re working against freedom of speech’ Daily Bulldog – Daily Bulldog

Posted: at 11:54 pm

An officer speaks with Ed at the intersection of Broadway and Main in Farmington. (Facebook photo)

FARMINGTON The intersection of Broadway and Main has been eerily quiet the past few weeks with the absence of a man who many had grown accustomed to seeing. The tall, middle-aged, slight man, known locally simply as Ed, could be found almost daily from late summer and into early winter, standing on the street corner with various signs in hand. If not downtown, Ed would take a stance at a busy crosswalk on the University of Maine campus.

Seen or not, Ed could almost always be heard.

His voice would carry, insisting that passersby were bound for hell; and while his message may have offended hundreds, Eds actions are protected by the very amendment that the United States is famous for.

For a small town in Maine, Farmington has a long history of people publicly proclaiming their beliefs. From the Women in Black who stand for peace in front of the post office, to the topless march in 2013, and just recently a protest that held up traffic in the name of climate change. Public protest, or speaking ones mind, is not new to this community, and Ed has been careful to not break any laws.

But its complicated, and for Farmington Chief of Police Ken Charles, complaints about Ed have to be looked at carefully and individually.

Everything is case specific. Its multi-layered. Its not just what the message is, its how its portrayed, and obviously the bigger concern here is the content thats being said. I think a big piece of it is people dont like his messagebut people dont like a lot of messages that are out there, Charles said.

According to many people, Ed has shown a tendency of yelling louder at, or leaning in toward, anybody who doesnt fit into his confines of normal. UMF staff members voiced concerned for their students who identify as LGBTQ and students of color, saying they felt as though Eds words crossed the line to becoming an act of harassment. Ed was issued a criminal trespass warning by campus Public Safety Director Brock Caton, and is unable to go on UMF property. However, the sidewalk where Ed carefully chooses to stand is owned by the town.

Caton said that it was determined that there was no actionable conduct, either under the criminal code or the Maine Civil Rights Act. He and others spoke with Ed about modifying his behavior, which Caton said was largely successful.

What hes doing is hateful speech, but its not a hate crime, Charles explained. Words are not illegal.

A person is guilty of criminal threatening if he or she intentionally or knowingly places another person in fear of imminent bodily injury, the key word being imminent. Being told that someone is going to hell is not considered imminent, Charles said, and in fact it is simply Eds opinion.

Charles also said that the bulk of complaints regarding Ed were made by third party people, not by the people who were actually involved in any specific scenarios. Typically those third party complaints used the word harassment, he said, but even harassment doesnt describe what Ed is doing. A person is guilty of harassment if without reasonable cause the person engages in a course of conduct with the intent to harass, torment, or threaten another person. The important part being the code of conduct, meaning more than twice, and targeted. The challenge there is that Ed targets everybody. And while some people have witnessed him yelling a little louder at certain people, its tough to identify who he might actually be targeting.

When does our ability to just go around him trump his constitutionally protected right to free speech? If youre working against him then youre also working against freedom of speech, Charles said.

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Australia dubs Chinese threat to free speech of Beijing Olympic athletes ‘very concerning’ – Republic World

Posted: at 11:54 pm

Possible restrictions on the freedom of speech ofWinter Olympics athletes are "very concerning," Australian sports minister Richard Colbeck said on Thursday. He further informed that the government of Australia is strictly opposed to the Chinese advisory, whichaims to potentially muzzle athletes on facing "punishment" if they speak against authorities of China or advocate for human rights on any public platform.

"The International Olympics Committee (IOC) has made it clear that all athletes have the right to political opinions and freedom to express them, including through social media and media interviews," Sports Minister of Australia, Richard Colbeck, told The Sydney Morning Herald.

"Any threat aimed at the Australian athletes for speaking out, therefore, is very concerning and is not at all supported by the Australian government," he added.

Colbeck's statement comes after Chinese Deputy Director of International Relations for Beijing organising committee, Yang Shu, on Tuesday informed that "dedicated departments" will monitor athletes' comments during the Beijing Winter Olympics. "Any behaviour or speech that is against the Olympic spirit, especially against the Chinese laws and regulations, are also subject to certain punishment, Shu had said. She added, "any expression that is in line with the Olympic spirit, I am sure, will be protected."

On Thursday, Human Rights Watch (HRW) raised concerns over the authoritarianmeasures that China is undertaking to "sportswash" the country's reputation. Observing the threats, HRW warned athletes to be wary of their comments regarding Beijing's human rights record and treatment of Uyghur Muslims, Tibetans and other Turkic communities. HRW also asserted that they are worried about the "Orwellian surveillance state" thatathletes and visitors will be put under, including the use of specific mobile applications mandated for spectators, athletes and fans, the Guardian reported. "Anyone who is traveling to these Games - journalists, athletes, coaches - need to be aware that these kinds of surveillance could affect them," Dr. Sophie Richardson, China director of HRW had said.

Notably, the Games will open on February 4, 2022, against a backdrop of China launching a severe crackdown on minority communities, which "reflect Xi Jinping's assault on human rights since coming to power," HRW said. Meanwhile, several governments across the world have decided to withhold sending top-level delegation to Beijing as a diplomatic boycott of the Games. Countries like Canada, UK and Australia have joined the US suit to revoke representation at the Beijing Winter Olympics, citing human rights violations in northern provinces.

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How to know when AI is the right solution – ARNnet

Posted: at 11:53 pm

Artificial intelligence (AI) adoption is on the rise. According to a recent McKinsey survey, 55 per cent of companies use artificial intelligence in at least one function, and 27 per cent attribute at least 5 per cent of earnings before interest and taxes to AI, much of that in the form of cost savings.

As AI will dramatically transform nearly every industry it touches, its no surprise that vendors and enterprises are looking for opportunities to deploy AI everywhere they can. But not every project can benefit from AI and attempting to apply AI inappropriately can not only cost time and money but also sour employees, customers, and corporate leaders on future AI projects.

The key factors for determining whether a project is suitable for AI are business value, availability of training data, and cultural readiness for change. Heres a look at how to ensure those criteria are in line for your proposed AI project before your foray into artificial intelligence becomes a sunk cost.

Data scientists in particular gravitate toward an AI-first approach, says Zack Fragoso, data science and AI manager at pizza chain Dominos, which has more than 18,000 locations in over 90 countries around the world. But you cant apply AI everywhere.

Despite being a very traditional line of business, Dominos has been embracing change especially during the pandemic. Customers now have 13 digital ways to order pizzas, and the company generated more than 70 per cent of sales through digital ordering channels in 2020. That has opened up a lot of opportunity for making good on the promise of AI.

The key for Dominos in applying AI, Fragoso says, has been taking a simple approach. At the end of the day, the simple solution runs faster, performs better, and we can explain it to our business partners, he says. Explainability is a big part of it the more people understand the tools and methods we use, the easier it is to gain adoption.

The approach itself is simple: If theres a business problem that needs solving, Dominos looks at the simplest, most traditional solution, and then, if we go up from there, there needs to be a value-add in the performance of the model, Fragoso says.

For example, predicting how long it takes to cook a pizza and put it in a box is simple. We pull that right from our operations research. You can plug in the oven times, he says. But there are some problems that can only be solved with AI, he adds, such as those requiring image recognition or natural language processing.

For example, last year, Dominos ran a loyalty program that rewarded customers for eating pizza any pizza, from any pizza maker. We built a pizza classifier using millions of pictures of different kinds of pizza and put it into an app, Fragoso says.

That project offered two types of business value. First, it enhanced the customer experience, he says. Second, it created a collection of pizza images that the company then used to detect pizza quality and temperature. It was a really great full-circle AI project, he says.

A more practical AI project Dominos undertook was a predictor aimed at improving the accuracy of its pizza tracker, as customers want to know when exactly to come to the store to pick up their food, or when to expect their delivery to arrive, Fragoso says. Adding machine learning to the traditional if-then coding of Dominos pizza tracker resulted in a 100 per cent increase in accuracy, he says.

In building the model, Dominos stuck with its simplest-first principle. The first iteration was a simple regression model, he says. That got us close. Then a decision tree model, where we could look at more facets. Then we actually moved to a neural net because we could capture some of the same variables as in the decision tree but the neural net produces the answer faster. We want our customer experience on the website to be really fast.

There is a place for machine learning, says Sanjay Srivastava, chief digital officer at Genpact, particularly when a company is looking to build processes that are continually improving based on experience. But sometimes all thats needed is a simple correlation, which can be obtained from basic statistical modeling.

Ten-year-old practices around random forests and other statistical tool kits can get you the answer much faster and much cheaper than building a whole MLOps team around it, Srivastava says. You have to know when to fall back to existing techniques that are much simpler and much more effective.

One common area in which AI is often pitched a solution but is usually overkill is in chatbots, he says: In some scenarios, it makes sense. But in 90 per cent of scenarios you know the questions that are going to be asked because you can look at the questions that have been asked in the last three years and you know the answer to every question. Turns out, 90 per cent of chatbots can get away with simple question-and-answer pairs.

Any finite set of data can be fitted to a curve. For example, you can take previous years winning lottery numbers, and come up with a model that would have predicted them all perfectly. But the model will still be no better at predicting future winnings because the underlying mechanism is completely random.

The COVID-19 pandemic has been a prime example of how this happens in real life. There was no way to predict where lockdowns were going to lead to factory shutdowns, for example. As a result, companies saw a decline in the revenue gains they saw in many areas, according to McKinseys state of AI survey.

For example, 73 per cent of respondents saw revenue increases in strategy and corporate finance last year, while only 67 per cent did so this year. The difference was even more stark in supply chain management. Last year, 72 per cent saw revenue increases in this area but only 54 per cent did this year.

The fundamental characteristic of AI or machine learning is that youre using history to inform, says Donncha Carroll, partner in the revenue growth practice at Axiom Consulting Partners. You are wedded, chained, handcuffed by history. AI is good in circumstances where history is likely to repeat itself and youre okay with history repeating itself.

For example, he says, some of his clients have tried to use AI to predict future revenue. But often, revenue is influenced by factors that cant be predicted, that cant be controlled, and that the company doesnt have any data for. And if some of those factors have an outside impact on results, it can throw off the entire model.

Then it makes no sense to choose AI, he says. Are you going to invest hundreds of thousands of dollars in a solution that can be immediately made irrelevant by a change in one variable?

AI can still have a role here, he says, in helping to model various scenarios, or in surfacing insights that might not be otherwise apparent. Your likelihood of success goes up if your focus is more narrow.

AI will also fall short if the very presence of the AI changes the behavior of the system. For example, if AI is used to filter out hateful speech, people quickly learn what patterns the AI looks for and word things so that they get through the filters.

The best minds in the world have been trying to solve these problems and they have not been successful, Carroll says.

Kearney partner Bharath Thota once worked with a US$30-billion-plus global consumer products and goods conglomerate. The CFO leadership team wanted better visibility into the conglomerates financial metrics so they could see whether their growth was going up and down. The existing process was that they got PDFs of reports 30 days after the reporting period closed.

The data science team applied AI to forecast what the numbers would look like. They had good intent, says Thota. They wanted to provide the leadership with a futuristic view.

The mistake they made was in the financial data they were feeding into the algorithm. The financial analysts feeding in that data had to make a lot of assumptions, and so the data set wound up containing lots of individual biases.

The leadership was excited, says Thota. They had something forward-facing, not rearview-facing. But when the quarter ended, and they looked back at those predictions, they were completely off.

The entire project took months, says Thota. They had to figure out how to build this thing, do the architecture, research AI platforms, get everything to work together.

When a project like that fails, people lose interest and confidence in AI, he says. For this particular company, the solution was simply to build the CFO leadership team a financial dashboard that gave them the metrics they needed, when they needed them.

Eventually, Thota says, some AI was used as well, in the form of natural language generation, to automatically provide key insights into the data to the executives in plain-English terms.

It was a visibility problem, he says. And there was a simple solution to provide that visibility.

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The danger of AI micro-targeting in the metaverse – VentureBeat

Posted: at 11:53 pm

Did you miss a session from the Future of Work Summit? Head over to ourFuture of Work Summit on-demand libraryto stream.

If you ask most people to name the key technologies of the metaverse, theyll usually focus on the eyewear and graphics engines. If theyre sophisticated, theyll also bring up 5G and blockchain. But those are the nuts and bolts of our immersive future. The technology that will pull the strings, creating and manipulating our experience, is AI.

Artificial intelligence will soon become one of the most important, and likely most dangerous, aspects of the metaverse. Im talking about agenda-driven artificial agents that look and act like any other users but are virtual simulations that will engage us in conversational manipulation, targeting us on behalf of paying advertisers.

This is especially dangerous when the AI algorithms have access to data about our personal interests, beliefs, habits and temperament, while also reading our facial expressions and vocal inflections. Such agents will be able to pitch us more skillfully than any salesman. And it wont just be to sell us products and services they could easily push political propaganda and targeted misinformation on behalf of the highest bidder.

And because these AI agents will look and sound like anyone else in the metaverse, our natural skepticism to advertising will not protect us. For these reasons, we need to regulate some aspects of the coming metaverse, especially AI-driven agents. If we dont, promotional AI-avatars will fill our lives, sensing our emotions in real time and quickly adjusting their tactics for a level of micro-targeting never before experienced.

But of all the technologies headed our way, its the Elf that could be the most subtle form of coercion. These Electronic Life Facilitators will be the next generation of digital assistants like Alexa and Siri. But they wont be disembodied voices; theyll be anthropomorphized personas customized for each user. And because the metaverse will ultimately be an augmentation layer on the real world, these digital elves will follow us everywhere, whether were shopping, working, or just hanging out.

And like the marketing agents described above, these elves could have an agenda, nudging us towards actions and activities, products and services, even views and beliefs on behalf of a paying advertiser. And they wont be like the crude chatbots of today, but embodied characters well come to think of as trusted figures in our life a mix between a familiar friend, a helpful advisor, and a caring therapist. But your elf will know you in ways no friend ever could, for it could monitor your daily life down to your blood pressure and respiration rate (via your smart watch).

Yes, this sounds creepy and invasive, which is why platform providers will likely make them cute and non-threatening, with innocent features that seem more like a magical character than a human-sized assistant following you around. This is why I prefer the word elf to describe them, as they might appear to you as a fairy or gremlin, hovering over your shoulder a small character that can whisper in your ear or fly out in front of you to draw attention to things in your augmented world it wants you to focus on.

There are many positive uses of such technology, but when controlled by for-profit corporations, AI agents can too easily coerce us, steering us towards products and services without us even realizing. After all, the metaverse itself is designed to fool our senses when combined with the power of AI the dangers are very real. I raise these issues in hope the industry pushes for meaningful regulation before the problems become so ingrained that we accept them as inevitable. After all, we deserve a magical metaverse, free of excessive monitoring and hidden manipulation.

Louis B. Rosenberg is a computer scientist, entrepreneur, and prolific inventor. Thirty years ago while working as a researcher at Stanford and Air Force Research Laboratory, Rosenberg developed the first functional augmented reality system. He then founded one of the early virtual reality companies (Immersion Corp) and one of the early augmented reality companies (Outland Research). Hes currently founder and CEO of swarm intelligence company Unanimous AI.

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The danger of AI micro-targeting in the metaverse - VentureBeat

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New DOD Chief Digital and AI Office to start work by Feb. 1 – FedScoop

Posted: at 11:53 pm

Written by Jackson Barnett Jan 26, 2022 | FEDSCOOP

The Department of Defenses new top artificial intelligence office will reach initial operational capability February 1, the Navys chief data officer said Wednesday.

The new chief digital and AI officer will oversee the DODs chief data officer, Joint Artificial Intelligence Center and Defense Digital Service and serve as an integrator for their efforts. Navy CDO Tom Sasala said that the new office will help the DOD push forward on data initiatives and be helpful to the work his team has been doing to bring data-based decision making to the Navy.

Ithink thats a really important component, he said of the office during an webinar presented by C4ISRnet.

Sasala said he met Tuesday with DOD Chief Data Officer Dave Spirk and Jim Mitre, the official tasked with standing up the office, to offer specific recommendations on the new role.

The DOD has been shuffling its management of AI and emerging technology initiatives over the past few years. Most recently, the JAIC was moved to report directly to the deputy secretary of defense from the CIOs office by the fiscal 2021 National Defense Authorization Act. The CDAO role is being created to ensure AI and data initiatives receive more attention, given the vast portfolio of the departments chief operating officer.

The CDAO will serve as the Departments senior official responsible for strengthening and integrating data, artificial intelligence, and digital solutions in the Department, the memo creating the positions signed by the deputy secretary states.

The CDAOis expected to reach full operational capability by June 2022.

A DOD spokesperson said: We are looking both internally and external to the Department and actively reviewing potential candidates to ensure we have the right person to drive the kind of progress we need.

Thisstory was updated to include commentfrom the Department ofDefense.

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New DOD Chief Digital and AI Office to start work by Feb. 1 - FedScoop

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Russian Perceptions of Military AI, Automation, and Autonomy – Foreign Policy Research Institute

Posted: at 11:53 pm

President Vladimir Putin declared 2021 to be the Year of Science and Technology in Russia, with November named as the month of artificial intelligence (AI), signaling Russian leaderships strong interest in this umbrella term. The Russian defense sector is particularly captivated by the opportunities associated with AI-based technologies. In recent years, AI, robotics, as well as the further integration of automation and autonomy into weapons systems and military decision-making have all been highlighted as priorities for modernizing the Russian armed forces.

In 2017, Putin famously said that artificial intelligence is the future, not only for Russia, but for all humankind Whoever becomes the leader in this sphere will become the ruler of the world. Quoting these words, analysts often attribute Russias development, testing, and use of weaponized AI to the necessity of competing in the so-called global AI race or the global tech race with the current leading AI developers: the United States and China.

While the perceived need to compete and catch up is part of Russias motivations, its interest in military AI should not only be attributed to a quest for relative power. Understanding the depth and complexity of the debates surrounding AI, autonomy, and automation in Russia requires an examination of discussions about its strategic implications for the Russian army, the perceived benefits and risks of autonomy, and, more broadly, the importance of technological modernization and innovation for Russias place in the world.

This report aims to provide an overview of the different conceptions and motivations, both oriented towards domestic and international audiences, that have been and are guiding Russian political and military leaderships in their ambitions to pursue weaponized AI. First, it outlines the various factors, both external and internal, behind the quest for pursuing AI, autonomy, and automation in the Russian military. Second, it presents some of the Russian plans in this area, what is known about their capabilities, and the challenges to strengthening them. Third, it dives into Russian debates on autonomy, and especially autonomous weapons systems, as well as discussions on the ethics of developing so-called killer robots, or autonomous combat robots ( , or ), a term often used in the Russian-language literature.

The analysis is based on a survey of open-source materials, including media reports, press releases, official statements and speeches, peer-reviewed articles and think tank reports, as well as publications in Russian military journals. The author would like to present it as the first step in an ongoing doctoral research project, as well as a contribution to the emerging English-language literature on how weaponized AI is perceived in Russia.

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Russian Perceptions of Military AI, Automation, and Autonomy - Foreign Policy Research Institute

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