Faculty

Anseth earns international recognition with L’Oreal-UNESCO For Women in Science award

Anonymous — Tue, 18 Feb 2020 17:21:16 +0000

Anseth earns international recognition with L’Oreal-UNESCO For Women in Science award Anonymous (not verified) Tue, 02/18/2020 - 10:21

Jonathan Raab

CU �鶹ӰԺ Professor Kristi Anseth has received one of the most prestigious recognitions in the life sciences: a L’Oreal-UNESCO For Women in Science award.

Anseth, a distinguished professor and Tisone professor in the Department of Chemical and Biological Engineering, is being recognized for her “outstanding contribution in converging engineering and biology to develop innovative biomaterials that help tissue regeneration and drug delivery,” according to UNESCO.

She is one of only five women in the world, and the only recipient in North America, to receive the recognition this year.

“I am tremendously honored and feel so very fortunate to be part of the broader University of Colorado community,” Anseth said. “However, I must first acknowledge that this is a shared honor. I have the pleasure of mentoring an amazing group of undergraduate students, graduate students and postdoctoral associates in my laboratory, and these individuals have contributed tremendously to the basis for this recognition. I am so thankful to them for their dedication and CU’s commitment to supporting not only the education of these individuals but their transition to future leaders.”

Anseth said she’s eagerly anticipating the opportunity to celebrate women scientists and engineers and to play a more visible role for the next generation. The mother of a 12-year-old daughter, Anseth said she hopes her daughter’s generation is inspired to pursue careers in STEM and that girls see no bounds to their possible careers.

She also commended her colleagues in the Department of Chemical and Biological Engineering and the BIoFrontiers Institute for their support.

“I am fortunate to work in an environment with such brilliant colleagues who work tirelessly to advance our fields and educate students to develop technologies and ideas for supporting the well-being of people, society and the planet,” Anseth said.

Anseth, who is also the associate director of the BioFrontiers Institute, has a long and storied career in applying the principles of chemical engineering to the biomaterials field, authoring over 330 papers of extensive, highly impactful research and earning numerous awards and recognitions. She is one of only a handful of individuals worldwide elected to all three national academies: the National Academy of Engineering, the National Academy of Medicine and the National Academy of Sciences. She also has been elected to the American Academy of Arts and Sciences, the National Academy of Inventors and the International Academy of Medical and Biological Engineering.

“Professor Anseth has proven time and again, through her stellar career of research and achievement, as well as her teaching and mentoring, that she is a world-class scientist and engineer,” said Keith Molenar, interim dean of the College of Engineering and Applied Science. “The L’Oreal-UNESCO For Women in Science awards recognize the best of the best, and she is absolutely deserving of that honor. We’re proud that she calls the CU �鶹ӰԺ College of Engineering and Applied Science home, as she brings immeasurable value to the research and education happening here.”

“Kristi Anseth has been a leader in cutting-edge biomaterials research for over two decades,” said Charles Musgrave, chair of the Department of Chemical and Biological Engineering. “Her work in the tissue engineering and drug delivery fields has led to the development of key technologies that will have an incredible impact on regenerative medicine and drug delivery. I can’t think of anyone more deserving of this award than her. My colleagues and I are proud of her many accomplishments.”

Anseth earned her doctoral degree in chemical engineering from CU �鶹ӰԺ in 1994 and joined the faculty shortly thereafter, focusing her research on developing biomaterials for medical applications.

Rob Davis, dean emeritus of the College of Engineering and Applied Science and Tisone endowed chair in the Department of Chemical and Biological Engineering, nominated Anseth for the award. He cited her unparalleled research accomplishments in biotechnology and cell biology and the translation of her technologies into medical products, including in-situ-forming materials for enhanced bone regeneration, hydrogels for chondrocyte delivery and more.

He also emphasized her dedication to her students, recalling his first observation of her after she completed her PhD. She had volunteered to teach an 8 a.m. undergraduate course, winning over the sleepy and skeptical students with her enthusiasm and passion for the material.

Support for the nomination also came from other distinguished leaders in academia, including professors Paula T. Hammond and Robert Langer of MIT, Provost David A. Tirrell and Professor Mark E. Davis of the California Institute of Technology, and Professor Nicholas A. Peppas of the University of Texas at Austin.

The international For Women in Science awards, now in their 22nd year, recognize the accomplishments of women who work in the biotechnology, ecology, epigenetics, epidemiology and infectiology research fields. The L’Oreal Foundation and UNESCO bestow five of these awards each year, recognizing one researcher each from Africa and the Arab States, the Asia-Pacific region, Europe, Latin America and North America. Fifteen additional “Rising Talents” are recognized from these regions as well.

Anseth and the other awardees will be honored at a ceremony March 12 at UNESCO Headquarters in Paris. Each award recipient will receive €100,000 (about $109,000). The awards seek to increase the representation and awareness of women in science and their achievements to inspire more women to consider careers in the sciences.

The late Deborah Jin, a professor of physics and JILA fellow at CU �鶹ӰԺ, also received the award in 2012.

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The ALSAM Foundation funds new Anschutz-�鶹ӰԺ collaborative research

Anonymous — Tue, 18 Dec 2018 20:20:28 +0000

The ALSAM Foundation funds new Anschutz-�鶹ӰԺ collaborative research Anonymous (not verified) Tue, 12/18/2018 - 13:20

Lindsay Diamond

The ALSAM Foundation, a generous long-time donor to the CU Skaggs School of Pharmacy and Pharmaceutical Sciences (SSPPS), has provided $2M of funding for collaborative grants between the SSPPS and the BioFrontiers Institute. This donation supports the Therapeutic Innovation Grants Program that allows the SSPPS on the Anschutz Medical Campus to join forces with the BioFrontiers Institute on the �鶹ӰԺ Campus to encourage faculty collaboration in the development of innovative projects that will advance the health and wellness of people in our communities and around the globe.

“The ALSAM Foundation has been a transformative force for the SSPPS and for advancing therapeutic innovations through two therapeutic innovations research grant programs totaling over $5M in the past three years. We are enormously grateful to the Foundation for its continuing support and look forward to the outcomes of these multidisciplinary research projects that promise new insights into diseases with the goal of developing new therapeutics,” says SSPPS Dean Ralph Altiere.

Tom Cech, Director of the BioFrontiers Institute at CU �鶹ӰԺ adds, “This program will stimulate our BioFrontiers faculty and students to work with our SSPPS colleagues at Anschutz to develop new therapeutics in the areas of cancer, muscle disease and diabetes.”

The Therapeutic Innovation Grants Program will foster cross-disciplinary collaboration among pharmaceutical researchers at the SSPPS and the interdisciplinary bioscientists at the BioFrontiers Institute with the goal of transforming the development of a new generation of drugs by fueling discovery and translation of new therapeutics to the clinic to achieve better health outcomes for patients and families. The funded projects will address this goal by facilitating the collaboration of the best scientific and clinical research minds in Colorado in a manner that allows rapid testing of new ideas and approaches. This year’s Therapeutic Innovation Grants Program proposals included faculty from University of Colorado entities including SSPPS, BioFrontiers Institute, School of Medicine (SOM) and School of Public Health (SPH).

The newly funded projects address critical health issues related to cancer, vaccine design, diabetes, depression and alcoholism among others. The newly funded research partnerships aim to advance discoveries from the laboratory to the clinic.

Principle Investigator | Collaborating Investigators

Natalie Ahn (BioFrontiers) | Nichole Reisdorph (SSPPS)
Jared Brown (SSPPS) | Tom Flaig (SOM), Myles Cockburn (SPH), John Adgate (SPH)
Carlos Catalano (SSPPS) | Robert Garcea (BioFrontiers), Ted Randolph (UCB)
Shaodong Dai (SSPPS) | Aaron Michels (SOM)
Dan LaBarbera (SSPPS) | Terry Fry (SOM)
Bradley Olwin (BioFrontiers) | Nichole Reisdorph (SSPPS)
Amy Palmer (BioFrontiers) | Raj Agarwal (SSPPS)
Manisha Patel (SSPPS) | Diego Restrepo (SOM), Emily Gibson (SOM)
Nichole Reisdorph (SSPPS) | Kristine Kuhn (SOM), Cathy Lozupone (SOM)
Michael Wempe (SSPPS) | Richard Johnson (SOM), B Vogeli (SOM)

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Work with bees could unlock potential strength of natural designs in new materials

Anonymous — Mon, 17 Sep 2018 06:00:00 +0000

Work with bees could unlock potential strength of natural designs in new materials Anonymous (not verified) Mon, 09/17/2018 - 00:00

Josh Rhoten

The natural world has had billions of years of evolution to perfect systems, creating elegant solutions to tricky problems. CU �鶹ӰԺ Assistant Professor Orit Peleg’s work hopes to illuminate and explore those solutions with the long-term goal of applying the answers she finds to the materials we interact with daily.

Her most recent research with bees, recently published in Nature Physics, is a small step toward that goal. The project looked at the honeybee cluster swarms that hang in cone shapes from tree branches and are made up of hundreds of individual insects clinging to one another. While these swarms are hundreds of times the size of a single organism, the individual bees that comprise it are able to maintain the structure’s stability despite wind and gravity forcing changes in the overall shape.

Peleg, who is based in the Computer Science Department and the BioFrontiers Institute at CU �鶹ӰԺ, conducted the research during her time as a post-doctoral fellow at Harvard in 2017. She said the use of bees for the project “was a bit crazy,” but presented a good opportunity to work more on modeling and testing these types of systems at a low cost and with relatively simple imaging equipment.

“It is a good way to connect experiments to theory and go back and forth until we have a good understanding of the system,” she said.

The project tried to untangle how the cluster stayed together in various conditions by attaching one to a board that was shaken with varying amplitude, frequency and duration. The results showed that horizontally shaken clusters spread out to form wider, flatter cones, adapting to the movement, but also going back to normal given time. Something similar happened with sharp, pendular movements, but measurements before and after showed that the flattened cones deform less and relaxed faster than the elongated ones. Meanwhile, vertical movement put less strain on the structure which, in turn, required less change from the bees to adapt to the motion.

In the end, the experiment confirmed what Peleg’s agent-based simulations predicted and opened up new questions.

“Our goal in this experiment was to try to pinpoint local rules for behaviors of bees that dictate the mechanical stability of the structure. A bee on one side of swarm can’t say what another bee at the other side of the swarm is doing. It can only say what is happening in its local environment,” Peleg said. “So, by creating this structure, they have to solve this mechanical problem of stability by only using local information.”

But how do they know to do this? Or why? Peleg’s hypothesis is that individual bees respond to the strain they feel during movement, changing their position in the swarm to match it.

“We can think about a local role, where a bee senses those deformations through connections to other bees. If this exceeds a certain threshold, it moves around to address that,” she said. “It doesn’t consider up or down, it just takes the local gradient information. Going up gradient (magnitude) makes it harder for individual bee, but better for the swarm overall.”

Peleg is part of the Multi-functional Materials Interdisciplinary Research Theme at CU and said this work fits well with that theme’s goal of exploring new materials and applications. While there is still more work to be done in studying the fundamental biology at work, she said this research could have applications in swarm robotics or the creation of materials that can sense their environment and respond to it.

“There is a clear connection to structures that insects make like swarms or ant-towers, for example, that are dynamic and respond to things like temperature or mechanical changes,” she said. “The grandiose vison of this, which we are still far away from, is the creation of construction materials that can sense and respond to earthquakes and become more stable in the same sort of way.”

Peleg has an apiary on East Campus and is planning on continuing this kind of work and this project in particular. Specifically, she said there was still work to be done with imaging the inside of the swarms to help with overall understanding of how this process works.

“We still need to look at the internal structure of the swarm through x-rays, for example, as that is completely unknown right now and could be informative,” she said.

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Nothing unusual about 'the long peace' since WWII

Anonymous — Mon, 26 Feb 2018 07:00:00 +0000

Nothing unusual about 'the long peace' since WWII Anonymous (not verified) Mon, 02/26/2018 - 00:00

Jenna Marshall

Since the end of World War II, few violent conflicts have erupted between major powers. Scholars have come to call this 73-year period “the long peace.” But is this stretch of relative calm truly unusual in modern human history – and evidence that peace-keeping efforts are working? Or is it a cyclical peace, destined to be broken, with few lessons for preventing interstate conflict?

A new analysis by Aaron Clauset, an assistant professor of computer science at the University of Colorado at �鶹ӰԺ and the BioFrontiers Institute and an external faculty member of the Santa Fe Institute, aims to answer that long-standing question using novel statistical techniques to tease out how the “long peace” stacks up against historical trends of calm and conflict.

“There’s been a debate among people who think about conflict and war, policymakers and researchers, whether or not the pattern since World War II represents a trend,” Clauset says. Resolving this debate “is important because it shapes how we think about peace,” he adds.

Determining whether we are truly in the midst of a prolonged period of peace can help us understand what is an effective deterrent to war and what is not. If this really is a “long peace,” we can then examine why — and identify the mechanisms that have contributed to that peace. But if it’s not an anomaly, we may need to use caution in ascribing the current calm to particular policies or actions.

Using data on interstate conflicts worldwide between 1823 and 2003, Clauset looked for trends in the magnitude of those conflicts and the years between them, and then used that information to create models to determine the plausibility of a trend toward peace since World War II. “The tools, the framework and the models we built in this paper haven’t been used before, and they allow us to distinguish trends from fluctuations,” Clauset says.

What he found is that this prolonged period of peace is not so unusual. “The results of the study are that at least statistically speaking, the efforts to create peace have not changed the frequency of war,” Clauset says. “These periods of peace are relatively common. It doesn’t appear that the rules that generate war have changed.”

Between 1823 and 1939, there were 19 large wars, and a major conflict occurred about every 6.2 years. Then came an especially violent period: Between 1914 and 1939, which encompasses the onsets of the first and second world wars, 10 large wars erupted — about one every 2.7 years. In contrast, during the long peace of the 1940–2003 post-war period, there were only 5 large wars — about one every 12.8 years. So essentially, the long peace “has simply balanced the books,” counterbalancing the “great violence” of the early to mid 20th century, Clauset writes.

That’s not to say, however, that the current calm is insignificant. “This fact does not detract from the importance of the long peace, or the proposed mechanisms that explain it,” such as the spread of democracy and international diplomacy, he writes in the paper. “However, the models indicate that the post-war pattern of peace would need to endure at least another 100–140 years to become a statistically significant trend.”

Clauset compares this to flipping a coin over a period of time. “If I’m seeing a low number of heads out into the future, how long will the coins need to flip before the pattern really looks different? At what point does this pattern start to look unusual?”

Clauset says he is hopeful that the study will encourage a rethink of “the long peace.”

“I hope it will encourage caution,” Clauset says. “It’s a worthwhile exercise to check our assumptions about whether there’s a real trend or not.”

Part of the reason we tend to overstate the significance of the lack of major interstate conflict since World War II may be because of a human tendency to overestimate our ability to understand complexity, he notes in the paper. “Human agency certainly plays a critical role in shaping shorter-term dynamics and specific events in the history of interstate wars,” he writes. “But, the distributed and changing nature of the international system evidently moderates the impact that individuals or coalitions can have on longer-term and larger-scale system dynamics.

The research was supported by the One Earth Future Foundation, whose mission is to catalyze systems that eliminate the root causes of war.

Read the paper, “Trends and Fluctuations in the Severity of Interstate Wars," in Science Advances (February 21, 2018)

Read the article, "Are we in the middle of a long peace—or on the brink of a major war?" in Science (February 21, 2018)

Read the article, "War may be closer than we think," in Pacific Standard (February 23, 2018)

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Scant Evidence of Power Laws Found in Real-World Networks

Anonymous — Thu, 15 Feb 2018 07:00:00 +0000

Scant Evidence of Power Laws Found in Real-World Networks Anonymous (not verified) Thu, 02/15/2018 - 00:00

Erica Klarreich

A paper posted online last month has reignited a debate about one of the oldest, most startling claims in the modern era of network science: the proposition that most complex networks in the real world — from the World Wide Web to interacting proteins in a cell — are “scale-free.” Roughly speaking, that means that a few of their nodes should have many more connections than others, following a mathematical formula called a power law, so that there’s no one scale that characterizes the network.

Purely random networks do not obey power laws, so when the early proponents of the scale-free paradigm started seeing power laws in real-world networks in the late 1990s, they viewed them as evidence of a universal organizing principle underlying the formation of these diverse networks. The architecture of scale-freeness, researchers argued, could provide insight into fundamental questions such as how likely a virus is to cause an epidemic, or how easily hackers can disable a network.

Over the past two decades, an avalanche of papers has asserted the scale-freeness of hundreds of real-world networks. In 2002, Albert-László Barabási — a physicist-turned-network scientist who pioneered the scale-free networks paradigm — wrote a book for a general audience, Linked, in which he asserted that power laws are ubiquitous in complex networks.

Real-world networks exhibit a rich structural diversity that will likely require new ideas and mechanisms to explain.
Anna Broido and Aaron Clauset

“Amazingly simple and far-reaching natural laws govern the structure and evolution of all the complex networks that surround us,” wrote Barabási (who is now at Northeastern University in Boston) in Linked. He later added: “Uncovering and explaining these laws has been a fascinating roller coaster ride during which we have learned more about our complex, interconnected world than was known in the last hundred years.”

But over the years, other researchers have questioned both the pervasiveness of scale-freeness and the extent to which the paradigm illuminates the structure of specific networks. Now, the new paper reports that few real-world networks show convincing evidence of scale-freeness.

In a statistical analysis of nearly 1,000 networks drawn from biology, the social sciences, technology and other domains, researchers found that only about 4 percent of the networks (such as certain metabolic networks in cells) passed the paper’s strongest tests. And for 67 percent of the networks, including Facebook friendship networks, food webs and water distribution networks, the statistical tests rejected a power law as a plausible description of the network’s structure.

“These results undermine the universality of scale-free networks and reveal that real-world networks exhibit a rich structural diversity that will likely require new ideas and mechanisms to explain,” wrote the study’s authors, Anna Broido and Aaron Clauset of the University of Colorado, �鶹ӰԺ.

Network scientists agree, by and large, that the paper’s analysis is statistically sound. But when it comes to interpreting its findings, the paper seems to be functioning like a Rorschach test, in which both proponents and critics of the scale-free paradigm see what they already believed to be true. Much of the discussion has played out in vigorous Twitter debates.

Supporters of the scale-free viewpoint, many of whom came to network science by way of physics, argue that scale-freeness is intended as an idealized model, not something that precisely captures the behavior of real-world networks. Many of the most important properties of scale-free networks, they say, also hold for a broader class called “heavy-tailed networks” to which many real-world networks may belong (these are networks that have significantly more highly connected hubs than a random network has, but don’t necessarily obey a strict power law).

Critics object that terms like “scale-free” and “heavy-tailed” are bandied about in the network science literature in such vague and inconsistent ways as to make the subject’s central claims unfalsifiable.

The new paper “was an attempt to take a data-driven approach to sort of clean up this question,” Clauset said.

Network science is a young discipline — most of its papers date to the last 20 years — and the contentiousness surrounding the paper and the very vocabulary of scale-freeness stems from the field’s immaturity, said Mason Porter, a mathematician and network scientist at the University of California, Los Angeles. Network science, he said, is “still kind of in the Wild West.”

A Universal Law?

Many networks, from perfectly ordered lattices to purely random networks, do have a characteristic scale. In a two-dimensional square lattice, for instance, every node is connected to exactly four other nodes (so mathematicians say the node’s “degree” is four). In a random network, in which each pair of nodes has some constant probability of being connected to each other, different nodes can have different degrees, but these degrees nevertheless cluster fairly close to the average. The distribution of degrees is shaped roughly like a bell curve, and nodes with a disproportionately large number of links essentially never occur, just as the distribution of people’s heights is clustered in the 5- to 6-foot range and no one is a million (or even 10) feet tall.

But when a team led by Barabási examined a sample of the World Wide Web in 1998, it saw something very different: some web pages, such as the Google and Yahoo home pages, were linked to vastly more often than others. When the researchers plotted a histogram of the nodes’ degrees, it appeared to follow the shape of a power law, meaning that the probability that a given node had degree k was proportional to 1/kraised to a power. (In the case of incoming links in the World Wide Web, this power was approximately 2, the team reported.)

In a power law distribution, there is no characteristic scale (thus the name “scale-free”). A power law has no peak — it simply decreases for higher degrees, but relatively slowly, and if you zoom in on different sections of its graph, they look self-similar. As a result, while most nodes still have low degree, hubs with an enormous number of links do appear in small quantities, at every scale.

The scale-free paradigm in networks emerged at a historical moment when power laws had taken on an outsize role in statistical physics. In the 1960s and 1970s they had played a key part in universal laws that underlie phase transitions in a wide range of physical systems, a finding that earned Kenneth Wilson the 1982 Nobel Prize in physics. Soon after, power laws formed the core of two other paradigms that swept across the statistical physics world: fractals, and a theory about organization in nature called self-organized criticality.

By the time Barabási was turning his attention to networks in the mid-1990s, statistical physicists were primed to see power laws everywhere, said Steven Strogatz, a mathematician at Cornell University (and a member of Quanta’s advisory board). In physics, he said, there’s a “power law religion.”

There was a bandwagon effect in which people were doing stuff rather indiscriminately.
Mason Porter

Barabási’s team published its findings in Nature in 1999; a month later, Barabási and his then-graduate student Réka Albert (now a network scientist at Pennsylvania State University) wrote in Science, in a paper that has since been cited more than 30,000 times, that power laws describe the structure not just of the World Wide Web but also of many other networks, including the collaboration network of movie actors, the electrical power grid of the Western United States, and the citation network of scientific papers. Most complex networks, Barabási asserted a few years later in Linked, obey a power law, whose exponent is usually between 2 and 3.

A simple mechanism called “preferential attachment,” Albert and Barabási argued, explains why these power laws appear: When a new node joins a network, it is more likely to connect to a conspicuous, high-degree node than an obscure, low-degree node. In other words, the rich get richer and the hubs get hubbier.

Scale-free networks, Barabási’s team wrote in the July 27, 2000, issue of Nature, have some key properties that distinguish them from other networks: They are simultaneously robust against failure of most of the nodes and vulnerable to targeted attacks against the hubs. The cover of Nature trumpeted this last property as the “Achilles’ heel of the internet” (a characterization that has since been roundly disputedby internet experts).

Barabási’s work electrified many mathematicians, physicists and other scientists, and was instrumental in launching the modern field of network science. It unleashed a torrent of papers asserting that one real-world network after another was scale-free — a sort of preferential attachment in which Barabási’s early papers became the hubs. “There was a bandwagon effect in which people were doing stuff rather indiscriminately,” Porter said. The excitement spilled over into the popular press, with talk of universal laws of nature and cover stories in Science, New Scientist and other magazines.

From the beginning, though, the scale-free paradigm also attracted pushback. Critics pointed out that preferential attachment is far from the only mechanism that can give rise to power laws, and that networks with the same power law can have very different topologies. Some network scientists and domain experts cast doubt on the scale-freeness of specific networks such as power grids, metabolic networks and the physical internet.

Others objected to a lack of statistical rigor. When a power law is graphed on a “log-log plot” (in which the x– and y-axes have logarithmic scales) it becomes a straight line. So to decide whether a network was scale-free, many early researchers simply eyeballed a log-log plot of the network’s degrees. “We would even squint at the computer screen from an angle to get a better idea if a curve was straight or not,” recalled the network scientist Petter Holmeof Tokyo Institute of Technology in a blog post.

“There must be a thousand papers,” Clauset said, “in which people plot the degree distribution, put a line through it and say it’s scale-free without really doing the careful statistical work.”

In response to these criticisms, over the years some of the physicists studying scale-freeness shifted their focus to the broader class of heavy-tailed networks. Even so, a steady stream of papers continued to assert scale-freeness for a growing array of networks.

And the discussion was muddied by a lack of consistency, from one paper to another, about what “scale-free” actually meant. Was a scale-free network one that obeys a power law with an exponent between 2 and 3, or one in which this power law arises out of preferential attachment? Or was it just a network that obeys some power law, or follows a power law on some scales, or something even more impressionistic?

“The lack of precision of language is a constant frustration,” Porter said.

Clauset, who is active in outreach efforts, has found that many of the students he interacts with still think that the ubiquity of power laws is settled science. “I was struck by how much confusion there was in the upcoming generation of scientists about scale-free networks,” he said.

The evidence against scale-freeness was scattered across the literature, with most papers examining just a few networks at a time. Clauset was well-positioned to do something much more ambitious: His research group has spent the past few years curating a giant online compendium, the Colorado Index of Complex Networks (ICON), comprising more than 4,000 networks drawn from economics, biology, transportation and other domains.

“We wanted to treat the hypothesis as falsifiable, and then assess the evidence across all domains,” he said.

Sweeping Up the Dirt and Dust

To test the scale-free paradigm, Clauset and Broido, his graduate student, subjected nearly a thousand of the ICON networks to a series of increasingly strict statistical tests, designed to measure which (if any) of the definitions of scale-freeness could plausibly explain the network’s degree distribution. They also compared the power law to several other candidates, including an exponential distribution (which has a relatively thin tail) and a “log-normal” distribution (which has a heavier tail than an exponential distribution, but a lighter tail than a power law).

There is no general theory of networks.
Alessandro Vespignani

Broido and Clauset found that for about two-thirds of the networks, no power law fit well enough to plausibly explain the degree distribution. (That doesn’t mean the remaining one-third necessarily obey a power law — just that a power law was not ruled out.) And each of the other candidate distributions outperformed the power law on many networks, with the log normal beating the power law on 45 percent of the networks and essentially tying with it on another 43 percent.

Only about 4 percent of the networks satisfied Broido and Clauset’s strongest test, which requires, roughly speaking, that the power law should survive their goodness-of-fit test, have an exponent between 2 and 3, and beat the other four distributions.

For Barabási, these findings do not undermine the idea that scale-freeness underlies many or most complex networks. After all, he said, in real-world networks, a mechanism like preferential attachment won’t be the only thing going on — other processes will often nudge the network away from pure scale-freeness, making the network fail Broido and Clauset’s tests. Network scientists have already figured out how to correct for these other processes in dozens of networks, Barabási said.

“In the real world, there is dirt and dust, and this dirt and dust will be on your data,” said Alessandro Vespignani of Northeastern, another physicist-turned-network scientist. “You will never see the perfect power law.”

As an analogy, Barabási noted, a rock and a feather fall at very different speeds even though the law of gravitation says they should fall at the same speed. If you didn’t know about the effect of air resistance, he said, “you would conclude that gravitation is wrong.”

Clauset doesn’t find this analogy convincing. “I think it’s pretty common for physicists who are trained in statistical mechanics … to use these kinds of analogies for why their model shouldn’t be held to a very high standard.”

If you were to observe 1,000 falling objects instead of just a rock and a feather, Clauset said, a clear picture would emerge of how both gravity and air resistance work. But his and Broido’s analysis of nearly 1,000 networks has yielded no similar clarity. “It is reasonable to believe a fundamental phenomenon would require less customized detective work” than Barabási is calling for, Clauset wrote on Twitter.

“The tacit and common assumption that all networks are scale-free and it’s up to us to figure out how to see them that way — that sounds like a nonfalsifiable hypothesis,” he said.

If some of the networks rejected by the tests do involve a scale-free mechanism overlaid by other forces, then those forces must be quite strong, Clauset and Strogatz said. “Contrary to what we see in the case of gravity … where the dominant effects really are dominant and the smaller effects really are small perturbations, it looks like what’s going on with networks is that there isn’t a single dominant effect,” Strogatz said.

For Vespignani, the debate illustrates a gulf between the mindsets of physicists and statisticians, both of whom have valuable perspectives. Physicists are trying to be “the artists of approximation,” he said. “What we want to find is some organizing principle.”

The scale-free paradigm, Vespignani said, provides valuable intuition for how the broader class of heavy-tailed networks should behave. Many traits of scale-free networks, including their combination of robustness and vulnerability, are shared by heavy-tailed networks, he said, and so the important question is not whether a network is precisely scale-free but whether it has a heavy tail. “I thought the community was agreeing on that,” he said.

But Duncan Watts, a network scientist at Microsoft Research in New York City, objected on Twitter that this point of view “is really shifting the goal posts.” As with “scale-freeness,” he said, the term “heavy-tailed” is used in several different ways in the literature, and the two terms are sometimes conflated, making it hard to assess the various claims and evidence. The version of “heavy-tailed” that is close enough to “scale-free” for many properties to transfer over is not an especially broad class of networks, he said.

Scale-freeness “actually did mean something very clear once, and almost certainly that definition does not apply to very many things,” Watts said. But instead of network scientists going back and retracting the early claims, he said, “the claim just sort of slowly morphs to conform to all the evidence, while still maintaining its brand label surprise factor. That’s bad for science.”

Porter likes to joke that if people want to discuss something contentious, they should set aside U.S. politics and talk about power laws. But, he said, there’s a good reason these discussions are so fraught. “We have these arguments because the problems are hard and interesting.”

Clauset sees his work with Broido not as an attack but as a call to action to network scientists, to examine a more diverse set of possible mechanisms and degree distributions than they have been doing. “Perhaps we should consider new ideas, as opposed to trying to force old ideas to fit,” he said.

Vespignani agrees that there is work to be done. “If you ask me, ‘Do you all agree what is the truth of the field?’ Well, there is no truth yet,” he said. “There is no general theory of networks.”

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When it comes to genes, lichens embrace sharing economy

Anonymous — Thu, 08 Feb 2018 07:00:00 +0000

When it comes to genes, lichens embrace sharing economy Anonymous (not verified) Thu, 02/08/2018 - 00:00

Trent Knoss

CU �鶹ӰԺ researchers have discovered the first known molecular evidence of obligate symbiosis in lichens, a distinctive co-evolutionary relationship that could shed new light on how and why some multicellular organisms consolidate their genomes in order to co-exist.

The new study, which was published online today in the journal Molecular Ecology, finds that fungal organisms reduce their core genomic makeup while coalescing with algae to form a lichen partnership, one presumed to be "obligate" (i.e., requiring both partners) but had previously lacked direct genetic verification.

“Symbioses allows two different organisms to survive in areas where they otherwise might not be able to grow,” said Erin Tripp, Curator of Botany at CU’s Museum of Natural History and a co-author of the new study. “These findings are exciting because they illustrate a key genetic underpinning of this obligate pairing.”

Lichens are omnipresent worldwide and may cover up to six percent of the Earth’s land mass. There are over 20,000 known lichen species, some of which are well-suited to extreme environments like deserts and arctic tundra. Lichens play an important role in ecological processes such as soil formation and serve as bioindicators of environmental toxicity.

The genetic mechanisms and consequences of these fungal-algal unions, however, have remained poorly understood. Using samples collected from the southern Appalachian Mountains, the CU �鶹ӰԺ researchers sequenced DNA from 22 separate lichen species in order to better understand how the two unrelated organisms co-evolve on a molecular level.

The findings revealed that in some cases, the fungal partner of this symbiosis streamlined its mitochondrial genome, much like a couple moving in together might get rid of duplicate household furnishings.

“The fungus lost a crucial energy-producing gene while the algae retained a full-length copy of this gene,” said Cloe Pogoda, lead author of the study and a graduate researcher in CU �鶹ӰԺ’s Department of Molecular, Cellular and Developmental Biology. “We observed a parallel loss of this gene in three different lichen lineages. The fungus gives up this particular gene while its photosynthetic partner keeps it."

This obligate arrangement—in which one partner relinquishes its own mitochondrial power supply to likely become reliant on its partner for cellular energy—suggests a genetic division of labor that makes the resulting lichen more efficient, Tripp said, thereby perhaps conferring an ecological advantage.

The researchers plan to expand the study to include more lichen species in the future. The findings could also inspire new inquiries into the human gut microbiome, the complex bacterial colony that lives symbiotically inside each person and has been shown to influence various aspects of health.

“The implications are far-reaching, given how many symbiotic relationships we observe in nature,” said Tripp, who is also an assistant professor in CU �鶹ӰԺ’s Department of Ecology and Evolutionary Biology (EBIO). “Now we can expand our scope of study to look for genomic signatures of co-evolution in other organisms.”

CU �鶹ӰԺ undergraduates helped assemble the genomic information using sequencing resources at CU’s BioFrontiers Institute. Co-authors of the new research include Kyle Keepers and Nolan Kane of EBIO and James Lendemer of the New York Botanical Garden.

The National Science Foundation’s Dimensions of Biodiversity research program provided funding for the study.

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Professors Marv Caruthers and Larry Gold named 2017 National Academy of Inventors fellows

Anonymous — Wed, 03 Jan 2018 21:09:25 +0000

Professors Marv Caruthers and Larry Gold named 2017 National Academy of Inventors fellows Anonymous (not verified) Wed, 01/03/2018 - 14:09

Jim Scott

The National Academy of Inventors (NAI) named two CU �鶹ӰԺ faculty members to its class of fellows for 2017.

Distinguished Professor Marvin Caruthers of CU �鶹ӰԺ’s Department of Chemistry and Biochemistry was honored for his pioneering contributions to the chemical synthesis of DNA and RNA, making it possible to decode and encode genes and genomes.

Professor Larry Gold of the Department of Molecular, Cellular and Developmental Biology was honored for his DNA and RNA research, which led to the development of new families of drugs.

The NAI elected 155 fellows in 2017, representing research universities and government and non-profit research institutes. The 2017 fellows collectively hold nearly 6,000 U.S. patents.

Caruthers has won many prestigious honors during his career, including election to the National Academy of Sciences and the American Academy of Arts and Sciences. He was awarded the National Medal of Science in 2006 by President George W. Bush for his contributions to the advancement of knowledge in the science arena. Caruthers also co-founded numerous biotech companies, including Amgen in 1980.

A bioscience industry pioneer, Gold is also an elected fellow of the National Academy of Sciences and the American Academy of Arts and Sciences. He is currently chairman of the board of SomaLogic, one of three biotech companies he has founded while at CU �鶹ӰԺ.

Both Caruthers and Gold are recipients of CU �鶹ӰԺ’s Distinguished Research Lectureship award, one of the highest honors bestowed by faculty on a faculty member.

Those elected to the NAI are inventors on U.S. patents nominated by their peers for outstanding contributions in innovative discovery, technology and positive societal impact.

The 2017 NAI fellows will be honored in April as part of the Seventh Annual NAI conference in Washington, D.C. All 2017 fellows with be presented with a trophy, a medal and a rosette pin.

Three other CU �鶹ӰԺ faculty were previously elected to NAI: Distinguished Professor Kristi Anseth of chemical and biological engineering in 2015; Distinguished Professor Christopher Bowman of chemical and biological engineering in 2016; and Distinguished Professor Leslie Leinwand of molecular, cellular and developmental biology and chief scientific officer for the BioFrontiers Institute, in 2016.

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Arthritis, autoimmune disease discovery could lead to new treatments

Anonymous — Mon, 20 Nov 2017 21:13:07 +0000

Arthritis, autoimmune disease discovery could lead to new treatments Anonymous (not verified) Mon, 11/20/2017 - 14:13

Lisa Marshall

More than 23.5 million Americans suffer from autoimmune diseases like rheumatoid arthritis, scleroderma and lupus, in which an overzealous immune response leads to pain, inflammation, skin disorders and other chronic health problems. The conditions are so common that three of the top five selling drugs in the United States aim to ease their symptoms. But no cure exists, and treatments are expensive and come with side effects.

Now CU �鶹ӰԺ researchers have discovered a potent, drug-like compound that could someday revolutionize treatment of such diseases by inhibiting a protein instrumental in prompting the body to start attacking its own tissue.

“We have discovered a key to lock this protein in a resting state,” said Hang Hubert Yin, a biochemistry professor in the BioFrontiers Institute and lead author of a paper, published today in Nature Chemical Biology, describing the discovery. “This could be paradigm shifting.”

For years, scientists have suspected that a protein called Toll-like receptor 8 (TLR8) plays a key role in the innate immune response. When it senses the presence of a virus or bacteria, it goes through a series of steps to transform from its passive to active state, triggering a cascade of inflammatory signals to fight off the foreign invader. But, as Yin explained, “it can be a double-edged sword” leading to disease when that response is excessive.

Because TLR8 has a unique molecular structure and is hidden inside the endosome — an infinitesimal bubble inside the cell — rather than on the cell’s surface, it has proven an extremely difficult target for drug development.

“This is a long-sought-after target with very little success,” Yin said.

But his study shows a drug-like molecule called CU-CPT8m binds to and inhibits TLR8 and exerts “potent anti-inflammatory effects” on the tissue of patients with arthritis, osteoarthritis and Still’s disease, a rare autoimmune illness.

For the study, Yin and his co-authors used high-throughput screening to look through more than 14,000 small molecule compounds to determine whether they had the right chemical structure to bind to TLR8. They identified four that shared a similar structure. Using that structure as a model, they chemically synthesized hundreds of novel compounds in an effort to find one that perfectly bound to and inhibited TLR8.

Previous efforts to target the protein have focused on shutting it down when it is in its active state. But the compound Yin discovered prevents it from activating while still in its passive state.

“Before, people were trying to close the open door to shut it down. We found the key to lock the door from the inside so it never opens,” Yin said.

Much more research is necessary, but that could lead to treatments that strike at the root cause of autoimmune diseases, rather than just treating symptoms. With help from CU’s Technology Transfer Office, Yin has already filed a patent application and hopes to move on to animal studies and clinical trials within the next two years.

“Given the prevalence of these diseases, there is a big push for alternatives,” Yin said.

In the meantime, the new compound can serve as a first-of-its kind tool to understand exactly what TLR8 and the other nine toll-like receptors do in the body.

“Our study provides the first small molecule tool to shut this protein down so we can understand its pathogenesis,” Yin said.

The National Institutes of Health funded the study and researchers from the University of Tokyo, Tsinghua University and Peking Union Medical College Hospital in Beijing contributed to it.

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More Inclusive Scholarship Begins With Active Experimentation

Anonymous — Wed, 01 Nov 2017 06:00:00 +0000

More Inclusive Scholarship Begins With Active Experimentation Anonymous (not verified) Wed, 11/01/2017 - 00:00

Daniel Larremore , Allison Morgan , Aaron Clauset

To the Editor:

Today’s hyper-competitive environment makes it easy to forget that academe wasn’t always organized around measuring and rewarding merit. In fact, the simple idea that merit could be assessed from publications, and that scholarship should be published at all, was, as Andrew Piper and Chad Wellmon have recently described in “How the Academic Elite Reproduces Itself” (The Chronicle Review, October 8), a 19th-century invention that ultimately transformed the academy and accelerated discovery across fields. Despite the modern obsession with counts, rankings, and metrics, today’s system is clearly better than the old system of patronage and lineage alone.

Although the mechanics of scholarship have changed dramatically, Wellmon and Piper show that the pre-meritocratic winners adapted and their dominance remains intact. The inescapable question is whether this epistemic inequality limits the academy’s potential to create and share different kinds of knowledge. Wellmon and Piper answer by arguing that the university is a technology, and call for us to develop new practices that disrupt prestige hierarchies and quantify our way toward a more inclusive and productive meritocracy.

They are right to do so, but a better guiding analogy is biology, not technology. The university has evolved and diversified over the past century, adapting to new fields by remodeling its practices, traditions, and norms. While all these variations descend from Humboldt’s idea of a quantified meritocracy, the contrast between fields can be instructive. Take something as simple as double-blind peer review, which Wellmon and Piper say “underlies most academic publications.” On the contrary, this ‘genotype’ is rare across scientific journals, but common in the social sciences and humanities. The academic genome is diverse and diversifying. Digital technology will likely shake entire fields from their comfortable niches.

But diversity is only a strength if academics are bold enough to conduct experiments and propagate successful genes across disciplines — not all selection needs to be natural. For instance, the journal eLife combines an open-discussion review process with open access and open finances, and it eschews impact factors. Biologists adapted the physicists’ practice of uploading preprints to the open access arXiv by establishing their own bioRxiv website. Naturejournals recently imported an option for double-blind peer review. And, computer science has both investigated the consistency of its peer review practices and tested the anonymity of double-blind reviewing.

Using experiments to improve the academy requires that we further embrace measures and counts. In that sense, Piper and Wellmon have provided a valuable progress report on the meritocracy, and it isn’t entirely encouraging. Building a more inclusive and productive epistemic system remains a worthy goal, and the best path forward remains more experimentation, not less.

Daniel B. Larremore, Department of Computer Science and BioFrontiers Institute, University of Colorado, �鶹ӰԺ
Allison C. Morgan, Department of Computer Science, University of Colorado, �鶹ӰԺ
Aaron Clauset, Department of Computer Science and BioFrontiers Institute, University of Colorado, �鶹ӰԺ, and Santa Fe Institute

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Faculty careers can progress in many directions

Anonymous — Tue, 17 Oct 2017 06:00:00 +0000

Faculty careers can progress in many directions Anonymous (not verified) Tue, 10/17/2017 - 00:00

Viviane Callier

The canonical story of faculty productivity goes like this: A researcher begins a tenure-track position, builds their research group, and publishes as much as possible to make their case for being awarded tenure. After getting tenure, increased service and administrative responsibilities kick in and research productivity slowly declines. But now, a new study shows that, in computer science at least, the majority of faculty members have different—and more idiosyncratic—productivity trajectories. “There are lots of ways people make careers in academia,” says Daniel Larremore, professor of computer science at the University of Colorado in �鶹ӰԺ and one of the study’s lead authors. “There’s some space to revisit our expectations.”

Based on a comprehensive hiring and promotion dataset and a publication database for all 2453 computer science professors in the United States and Canada, Larremore and his co-authors found a huge range of publication trajectories, including the canonical one as well as many variations. That variability was not previously apparent because earlier studies of scholarly productivity typically focused on small datasets and were biased toward high achievers such as Nobel laureates, says Roberta Sinatra, assistant professor at the Central European University in Budapest.

Larremore’s team found that some faculty members remain very productive after tenure, with their publication rate peaking late in their careers and then declining abruptly. Others experience a productivity decline in the first few years on the tenure track, only to see an uptick in their fifth or sixth year. And still others don’t publish much early on but continually increase their output over the course of their careers. “Even though we have a canonical story about what a career in academia looks like, people are all over the map in reality,” Larremore says.

Ultimately, the authors write in the paper, “[t]his diversity in overall productivity, combined with the observation that an individual’s highest impact work is equally likely to be any of his or her publications, implies there are fundamental limits to predicting scientific careers.” For Jevin West, assistant professor in the Information School at the University of Washington in Seattle, that’s a good thing. “I don’t want young scholars to think their trajectory is somehow predestined,” he says. “There’s all sorts of things that lead to big discoveries.” However, cautions Henry Sauermann, associate professor of strategy at the European School of Management and Technology in Berlin, “the paper doesn’t tell us if all these paths are similarly successful in terms of getting tenure.”

It’s important to recognize that tenure committees rely on more than publication counts when evaluating candidates, says Donna Ginther, a professor of economics at the University of Kansas in Lawrence who studies scientific labor markets. These committees also take into account “the impact of the publications, and what the outside letter writers who are experts in the field have to say about the quality, quantity, and impact of the work,” Ginther says, which “may weigh more than the number of publications they’ve produced.” Larremore also emphasizes that publication count doesn’t necessarily reflect the true impact of a scholar’s work. “If you make a software package and it is used by thousands of hospitals, that may be a bigger contribution than five publications,” he says.

In light of the significant variation the new study reveals, funding agencies and hiring, tenure, and promotion committees need to appreciate the diversity of contributions and unpredictability of trajectories, the authors suggest. Evaluators who assume candidates should follow the canonical path may fail to reward people who are following different paths and end up missing out on talented researchers who still have great contributions to make, Sinatra agrees.

Although the data revealed a wide variety of career trajectories, there were also some notable trends. For one thing, men and women follow the canonical trajectory at equal rates, though men showed slightly higher initial and peak productivities. It’s not clear whether those differences are changing over time, moving toward parity in more recent cohorts, or whether differences at the time of hiring become exacerbated as careers progress. The researchers also found that faculty members at more prestigious institutions are more productive initially and have higher peak productivity, reflecting the higher publishing demands at higher-ranked institutions, Ginther notes. “You really need to know what you are getting into before you show up,” she says. “The postdoc can be used as a time to get a lot of work started so you get your publications rolling before you start on that tenure-track clock.”

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