Tag Archives: Matthew Rozsa

CRISPR/Cas9 used successfully to edit SIV (simian immunodeficiency virus, which is similar to HIV) out of monkey genome

Before reading further please note, the research discussed in this posting is based on animal testing, which many people find highly disturbing.

CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 (CRISPR-associated protein 9), or more familiarly CRISPR/Cas9, has been been used to edit simian immunodeficiency virus from infected monkeys’ cells according to a December 2, 2020 article by Matthew Rozsa for Salon.com (Note: Links have been removed),

With multiple coronavirus vaccines being produced as we speak, the COVID-19 pandemic appears to have an end in sight, though the HIV pandemic continues after more than 40 years. That might seem like a head-scratcher: why is HIV, a virus we’ve known about for decades, so much harder to cure than a virus discovered just last year? Part of the reason is that HIV, as a retrovirus, is a more complex virus to vaccinate against than SARS-CoV-2 — hence why a vaccine or other cure has eluded scientists for decades. 

Now, a surprising new study on a related retrovirus shows incredible promise for the potential to develop a cure for HIV, or human immunodeficiency virus. In an article published in the scientific journal Nature Communications, scientists revealed that they had used CRISPR – a genetic technology that can alter DNA and whose developers won the 2020 Nobel Prize in Chemistry [specifically, Jennifer Doudna and Emanuelle Charpentier received the Nobel for developing CRISPR-cas9 or CRISPR/Cas9 not CRISPR alone) — to successfully edit SIV (simian immunodeficiency virus), a virus similar to HIV, out of the genomes of non-human primates.  Specifically, the scientists were able to edit out the SIV genome from rhesus macaque monkeys’ infected cells.

For anyone who’s interested in how CRISPR was developed and the many contributions which have led to the current state-of-the-art for CRISPR gene editing, see the History subsection of Wikipedia’s CRISPR entry.

Getting back to Rozsa’s December 2, 2020 article,

“This study used the CRISPR CaS9 system, which has been described as molecular scissors,” Andrew G. MacLean, PhD, wrote to Salon. MacLean is an associate professor at the Tulane National Primate Research Center and the Department of Microbiology and Immunology at Tulane University School of Medicine and was a senior co-investigator of the study. “It uses a highly specific targeting system to cut out a specific portion of DNA that is necessary for HIV to be able to produce more virus.”

He added, “Our collaborators at in the Khalili Lab at Temple University have developed a method of ‘packaging’ this within a single so-called vector. A vector is a non-disease causing virus that is used as a carrier for the CRISPR CaS9 scissors to get it into the tissues of interest.”

The experiments with SIV are considered to be a gateway to understanding HIV, as HIV is believed to have evolved from SIV, and is genetically similar.

“The rhesus macaque model of HIV/AIDS is the most valuable model to test efficacy of new interventions or approaches for preventing or treating HIV infection, prior to human clinical trials,” Binhua Ling, PhD, associate professor at the Southwest National Primate Research Center, Texas Biomedical Research Institute, wrote to Salon. “This first proof-of-principal [emphasis mine] study on the rhesus macaque model indicates that this virus-vehicle-delivered-CRISPR system can reach many tissue sites of the body, and is able to effectively delete virus DNA in infected cells. This paves the way for applying the same technology to the human body, which could lead to a cure for HIV infection.”

Tricia H. Burdo, PhD, another senior co-investigator on the new study who works at the Lewis Katz School of Medicine at Temple University, explained to Salon by email that “HIV is in a class of viruses (retroviruses) that inserts itself into the DNA of the host, so you can really think of this now as a genetic disease” — in other words, the kind of thing that would be ripe for CRISPR’s scissors-like ability to remove errant or unwanted genetic material. Burdo notes that the CRISPR technology discussed in the article “cuts out this foreign viral gene.”

The study was conducted on eight Rhesus macaque monkeys. That is a very small number to start with and not all of the monkeys received the CRISPR/Cas9 treatment. From the ‘Animals used in the study and ethical statement‘ subsection of the study, “Animals were sacrificed for tissue collection 3 weeks after … .” Leaving aside how anyone may feel about ‘sacrificing …’, three weeks is not a long time for observation.

Should you be interested, there is a November 30, 2020 Tulane University news release announcing the research.

If you want to read the whole study, here’s a link and a citation,

CRISPR based editing of SIV proviral DNA in ART treated non-human primates by Pietro Mancuso, Chen Chen, Rafal Kaminski, Jennifer Gordon, Shuren Liao, Jake A. Robinson, Mandy D. Smith, Hong Liu, Ilker K. Sariyer, Rahsan Sariyer, Tiffany A. Peterson, Martina Donadoni, Jaclyn B. Williams, Summer Siddiqui, Bruce A. Bunnell, Binhua Ling, Andrew G. MacLean, Tricia H. Burdo & Kamel Khalili. Nature Communications volume 11, Article number: 6065 (2020) DOI: https://doi.org/10.1038/s41467-020-19821-7 Published: 27 November 2020

This paper is open access.

As Rozsa notes in his December 2, 2020 article, the Joint United Nations Programme on HIV/AIDS estimates that 32.7 million [24.8 million–42.2 million] people have died from AIDS-related illnesses since the start (1981?) of the epidemic to the end of 2019.

China, US, and the race for artificial intelligence research domination

John Markoff and Matthew Rosenberg have written a fascinating analysis of the competition between US and China regarding technological advances, specifically in the field of artificial intelligence. While the focus of the Feb. 3, 2017 NY Times article is military, the authors make it easy to extrapolate and apply the concepts to other sectors,

Robert O. Work, the veteran defense official retained as deputy secretary by President Trump, calls them his “A.I. dudes.” The breezy moniker belies their serious task: The dudes have been a kitchen cabinet of sorts, and have advised Mr. Work as he has sought to reshape warfare by bringing artificial intelligence to the battlefield.

Last spring, he asked, “O.K., you guys are the smartest guys in A.I., right?”

No, the dudes told him, “the smartest guys are at Facebook and Google,” Mr. Work recalled in an interview.

Now, increasingly, they’re also in China. The United States no longer has a strategic monopoly on the technology, which is widely seen as the key factor in the next generation of warfare.

The Pentagon’s plan to bring A.I. to the military is taking shape as Chinese researchers assert themselves in the nascent technology field. And that shift is reflected in surprising commercial advances in artificial intelligence among Chinese companies. [emphasis mine]

Having read Marshal McLuhan (de rigeur for any Canadian pursuing a degree in communications [sociology-based] anytime from the 1960s into the late 1980s [at least]), I took the movement of technology from military research to consumer applications as a standard. Television is a classic example but there are many others including modern plastic surgery. The first time, I encountered the reverse (consumer-based technology being adopted by the military) was in a 2004 exhibition “Massive Change: The Future of Global Design” produced by Bruce Mau for the Vancouver (Canada) Art Gallery.

Markoff and Rosenberg develop their thesis further (Note: Links have been removed),

Last year, for example, Microsoft researchers proclaimed that the company had created software capable of matching human skills in understanding speech.

Although they boasted that they had outperformed their United States competitors, a well-known A.I. researcher who leads a Silicon Valley laboratory for the Chinese web services company Baidu gently taunted Microsoft, noting that Baidu had achieved similar accuracy with the Chinese language two years earlier.

That, in a nutshell, is the challenge the United States faces as it embarks on a new military strategy founded on the assumption of its continued superiority in technologies such as robotics and artificial intelligence.

First announced last year by Ashton B. Carter, President Barack Obama’s defense secretary, the “Third Offset” strategy provides a formula for maintaining a military advantage in the face of a renewed rivalry with China and Russia.

As consumer electronics manufacturing has moved to Asia, both Chinese companies and the nation’s government laboratories are making major investments in artificial intelligence.

The advance of the Chinese was underscored last month when Qi Lu, a veteran Microsoft artificial intelligence specialist, left the company to become chief operating officer at Baidu, where he will oversee the company’s ambitious plan to become a global leader in A.I.

The authors note some recent military moves (Note: Links have been removed),

In August [2016], the state-run China Daily reported that the country had embarked on the development of a cruise missile system with a “high level” of artificial intelligence. The new system appears to be a response to a missile the United States Navy is expected to deploy in 2018 to counter growing Chinese military influence in the Pacific.

Known as the Long Range Anti-Ship Missile, or L.R.A.S.M., it is described as a “semiautonomous” weapon. According to the Pentagon, this means that though targets are chosen by human soldiers, the missile uses artificial intelligence technology to avoid defenses and make final targeting decisions.

The new Chinese weapon typifies a strategy known as “remote warfare,” said John Arquilla, a military strategist at the Naval Post Graduate School in Monterey, Calif. The idea is to build large fleets of small ships that deploy missiles, to attack an enemy with larger ships, like aircraft carriers.

“They are making their machines more creative,” he said. “A little bit of automation gives the machines a tremendous boost.”

Whether or not the Chinese will quickly catch the United States in artificial intelligence and robotics technologies is a matter of intense discussion and disagreement in the United States.

Markoff and Rosenberg return to the world of consumer electronics as they finish their article on AI and the military (Note: Links have been removed),

Moreover, while there appear to be relatively cozy relationships between the Chinese government and commercial technology efforts, the same cannot be said about the United States. The Pentagon recently restarted its beachhead in Silicon Valley, known as the Defense Innovation Unit Experimental facility, or DIUx. It is an attempt to rethink bureaucratic United States government contracting practices in terms of the faster and more fluid style of Silicon Valley.

The government has not yet undone the damage to its relationship with the Valley brought about by Edward J. Snowden’s revelations about the National Security Agency’s surveillance practices. Many Silicon Valley firms remain hesitant to be seen as working too closely with the Pentagon out of fear of losing access to China’s market.

“There are smaller companies, the companies who sort of decided that they’re going to be in the defense business, like a Palantir,” said Peter W. Singer, an expert in the future of war at New America, a think tank in Washington, referring to the Palo Alto, Calif., start-up founded in part by the venture capitalist Peter Thiel. “But if you’re thinking about the big, iconic tech companies, they can’t become defense contractors and still expect to get access to the Chinese market.”

Those concerns are real for Silicon Valley.

If you have the time, I recommend reading the article in its entirety.

Impact of the US regime on thinking about AI?

A March 24, 2017 article by Daniel Gross for Slate.com hints that at least one high level offician in the Trump administration may be a little naïve in his understanding of AI and its impending impact on US society (Note: Links have been removed),

Treasury Secretary Steven Mnuchin is a sharp guy. He’s a (legacy) alumnus of Yale and Goldman Sachs, did well on Wall Street, and was a successful movie producer and bank investor. He’s good at, and willing to, put other people’s money at risk alongside some of his own. While he isn’t the least qualified person to hold the post of treasury secretary in 2017, he’s far from the best qualified. For in his 54 years on this planet, he hasn’t expressed or displayed much interest in economic policy, or in grappling with the big picture macroeconomic issues that are affecting our world. It’s not that he is intellectually incapable of grasping them; they just haven’t been in his orbit.

Which accounts for the inanity he uttered at an Axios breakfast Friday morning about the impact of artificial intelligence on jobs.

“it’s not even on our radar screen…. 50-100 more years” away, he said. “I’m not worried at all” about robots displacing humans in the near future, he said, adding: “In fact I’m optimistic.”

A.I. is already affecting the way people work, and the work they do. (In fact, I’ve long suspected that Mike Allen, Mnuchin’s Axios interlocutor, is powered by A.I.) I doubt Mnuchin has spent much time in factories, for example. But if he did, he’d see that machines and software are increasingly doing the work that people used to do. They’re not just moving goods through an assembly line, they’re soldering, coating, packaging, and checking for quality. Whether you’re visiting a GE turbine plant in South Carolina, or a cable-modem factory in Shanghai, the thing you’ll notice is just how few people there actually are. It’s why, in the U.S., manufacturing output rises every year while manufacturing employment is essentially stagnant. It’s why it is becoming conventional wisdom that automation is destroying more manufacturing jobs than trade. And now we are seeing the prospect of dark factories, which can run without lights because there are no people in them, are starting to become a reality. The integration of A.I. into factories is one of the reasons Trump’s promise to bring back manufacturing employment is absurd. You’d think his treasury secretary would know something about that.

It goes far beyond manufacturing, of course. Programmatic advertising buying, Spotify’s recommendation engines, chatbots on customer service websites, Uber’s dispatching system—all of these are examples of A.I. doing the work that people used to do. …

Adding to Mnuchin’s lack of credibility on the topic of jobs and robots/AI, Matthew Rozsa’s March 28, 2017 article for Salon.com features a study from the US National Bureau of Economic Research (Note: Links have been removed),

A new study by the National Bureau of Economic Research shows that every fully autonomous robot added to an American factory has reduced employment by an average of 6.2 workers, according to a report by BuzzFeed. The study also found that for every fully autonomous robot per thousand workers, the employment rate dropped by 0.18 to 0.34 percentage points and wages fell by 0.25 to 0.5 percentage points.

I can’t help wondering if the US Secretary of the Treasury is so oblivious to what is going on in the workplace whether that’s representative of other top-tier officials such as the Secretary of Defense, Secretary of Labor, etc. What is going to happen to US research in fields such as robotics and AI?

I have two more questions, in future what happens to research which contradicts or makes a top tier Trump government official look foolish? Will it be suppressed?

You can find the report “Robots and Jobs: Evidence from US Labor Markets” by Daron Acemoglu and Pascual Restrepo. NBER (US National Bureau of Economic Research) WORKING PAPER SERIES (Working Paper 23285) released March 2017 here. The introduction featured some new information for me; the term ‘technological unemployment’ was introduced in 1930 by John Maynard Keynes.

Moving from a wholly US-centric view of AI

Naturally in a discussion about AI, it’s all US and the country considered its chief sceince rival, China, with a mention of its old rival, Russia. Europe did rate a mention, albeit as a totality. Having recently found out that Canadians were pioneers in a very important aspect of AI, machine-learning, I feel obliged to mention it. You can find more about Canadian AI efforts in my March 24, 2017 posting (scroll down about 40% of the way) where you’ll find a very brief history and mention of the funding for a newly launching, Pan-Canadian Artificial Intelligence Strategy.

If any of my readers have information about AI research efforts in other parts of the world, please feel free to write them up in the comments.