Technology helpful in motivating young struggling readers, particularly boys, to read — Dara Rossi
SMU’s Dara Rossi was interviewed by the summer reading program Shelly’s Summer Bookworms for Dallas TV station WFAA.
Rossi is a clinical assistant professor and director of SMU’s Teach for American Teacher Education Program in the Simmons School of Education and Human Development. She was asked how using technology can help young students learn to read.
Rossi is an experienced educator with a strong science background, including K-12 curriculum development and administration.
New model allows pharmacological researchers to dock nearly any drug and see how it behaves in P-glycoprotein, a protein in the cell associated with failure of chemotherapy
Drugs important in the battle against cancer responded the way they do in real life and behaved according to predictions when tested in a computer-generated model of one of the cell’s key molecular pumps — the protein P-glycoprotein, or P-gp.
Biologists at Southern Methodist University, Dallas, developed the computer generated model to overcome the problem of relying on only static images for the structure of P-gp, said biologist John G. Wise, lead author on the journal article announcing the advancement.
The new SMU model allows researchers to dock nearly any drug in the P-gp protein and see how it will actually behave in P-gp’s pump, said Wise, an associate professor in SMU’s Department of Biological Sciences.
“The value of this fundamental research is that it generates dynamic mechanisms that let us understand something in biochemistry, in biology,” he said. “And by understanding P-gp in such detail, we can now think of ways to better and more specifically inhibit it.”
P-gp is the cellular pump that protects cells by pumping out toxins. But that’s a problem when P-gp targets chemotherapy drugs as toxic, preventing chemo from killing cancer cells. Scientists are searching for ways to inhibit P-gp’s pumping action.
The SMU researchers tested Tariquidar, a new P-gp inhibitor still in clinical trials. Inhibitors offer hope for stopping P-gp’s rejection of chemotherapeutics by stalling the protein’s pumping action. Pharmacology researchers disagree, however, on where exactly Tariquidar binds in P-gp.
When run through the SMU model, Tariquidar behaved as expected: It wasn’t effectively pumped from the cell and the researchers observed that it prefers to bind high in the protein.
“Now we have more details on how Tariquidar inhibits P-gp, where it inhibits and what it’s actually binding to,” Wise said.
SMU researchers report that their computer model simulation reveals the binding sites of Tariquidar (orange blob) — a P-gp inhibitor. (Image: James McCormick)
Also using the model, the researchers discovered greater detail than previously known about the behavior of other drugs as well, and how those drugs bind in P-gp to stop its pumping action.
The study was funded in part by the National Institutes of Health. The lab was recently awarded a second NIH grant for the research.
A still image of the modeled protein in action will appear on the cover of the October through December issues of Biochemistry.
Testing the virtual P-gp model by virtually docking real drugs
Wise and his colleagues tested one of the workhorse drugs of chemotherapy, daunorubicin, a close cousin of Adriamycin.
An aggressive chemotherapeutic, daunorubicin stops DNA replication in the cell, and is a classic target for P-gp to pump out of a cell, Wise said.
“For a long time, it’s been thought that there are at least a couple of distinct binding sites for drugs,” Wise said. “Sure enough, with our models, we found that daunorubicin, at least, prefers to bind on one side of the P-gp model, while verapamil – a commonly prescribed blood pressure medicine – prefers the other side.”
SMU researchers report that their computer model simulation reveals the binding sites of Tariquidar (orange blob) — a P-gp inhibitor — as the “pump” opens and closes. (Image: James McCormick)
Not only did the researchers show computationally that there are two different starting points for drugs, they also showed that there are two different pathways to get the drugs through.
“The two different drugs start at different sites and they’re funneled to the outside by being pushed by the protein,” Wise said. “But the actual parts of the protein that are pushing the drugs out are different.”
Molecular model can aid in fight against multi-drug resistance of cancer cells
The capability of watching molecular machinery up close, while doing its job the way it does in real life, may spark new drug discoveries to fight cancer.
“Having an accurate model that actually moves – that shows the dynamics of the thing – is incredibly helpful in developing therapies against a molecular target to inhibit it. The only other ways to do it are blind, and the chances of success using blind methods are very low,” Wise said.
“Scientists have tried for 30 years to find inhibitors of this pump and have done it without knowing the structure and with only little knowledge about the mechanism, screening more or less blindly for compounds that inhibit the thing,” Wise said. “They found drugs that worked in the test tube and that worked in cultured cells, but that didn’t work in the patient. With our model, because we can see the pump moving, we can probably predict better what’s going to make an inhibitor actually work well.”
Vogel and Wise led a team of researchers in using the P-gp model to virtually screen millions of publically available drug-like compounds.
Verapamil (green blob), inhibits the P-gp pump. Until now, the workings of the pump could not be observed so researchers didn’t know exactly where Varapamil “binds” in P-gp. SMU researchers report that their simulation reveals the binding sites. (Image: McCormick)
They discovered three new drug leads that could ultimately inhibit P-gp and offer better odds of survival to prostate cancer patients. The researchers reported those findings this month in the journal Pharmacology Research & Perspectives, http://bit.ly/1XGjN5w.
New SMU model simulates molecular machinery in action
Researchers look for drug compounds that can temporarily stop or inhibit the P-gp pump, so that the chemotherapy drugs that enter the cancer cell will stay there and do the job of killing the cancer. Finding the right pump inhibitor requires understanding the pumping action. That’s difficult without seeing the pump at work.
The structures of proteins similar to P-gp have been previously available in a static state through X-ray crystallography. Scientists use X-ray crystallography as a tool that essentially draws the details of biological structures by identifying their atomic and molecular structure through diffraction of X-rays by the atoms themselves.
Scientists often contribute the resulting protein structures to the U.S. Protein Data Bank repository for public use.
Detailed data combined with several trillion calculations produced model
To build the P-gp model, Wise used structures from the repository, showing various stages of transport, to simulate four points of reference. From there, SMU’s ManeFrame supercomputer was fed parameters and characteristics of the protein as well as how it should behave physically, including when kinetic energy was added to bring the protein and its surrounding membrane and water up to body temperature. The animated model resulted from calculating differences between two structures and using targeted molecular dynamics programs to slightly nudge the model to the next step.
“You do that several million times and make several trillion calculations and you arrive at the next structure,” Wise said. “In this way, we can nudge P-gp through a full catalytic transport cycle.”
Finally, using a docking program, the researchers individually introduced daunorubicin and other drugs into the protein, and watched the drugs move through P-gp’s catalytic cycle.
“What happened was — the drugs moved,” Wise said. “And they moved the way they should move, clinically, biochemically, physiologically, to pump the compounds out of the cell.”
Vogel added that, “in some of the zoom-ins of the model, you can actually see the amino acids paddle down the drugs.”
Further challenging and testing the model
The researchers ran a critical control to further test if the model worked.
“We thought maybe anything you put in the protein, relevant or not, would get pumped through. So we put in something that is not a transport substrate of P-gp, something that biochemically would never be transported by P-gp,” Wise said. “We put it in, starting where daunorubicin is effectively pumped out, and very quickly the compound left the protein — but it left the opposite way, back into the cell. This experiment gave us more confidence that what we are seeing in these models is reflecting what happens in the cell.”
Wise admits that until he saw it for himself, even he had doubts the virtual P-gp model would behave like real-life P-gp.
“It’s a crude approximation of a complex, sophisticated human protein, but it’s so much better than the static images available now,” Wise said. “I’ve got to emphasize for all the disbelievers, for the ‘culture of doubters’ out there, that this model works — it moves the drugs through the membrane. That speaks for itself. What P-gp does in the cell, cancerous or normal, it does in our simulations.”
New drug-like compounds have low toxicity to noncancerous cells, but inhibit the human protein often responsible for chemotherapy failure
Researchers at Southern Methodist University, Dallas, have discovered three new drug-like compounds that could ultimately offer better odds of survival to prostate cancer patients.
The drug-like compounds can be modified and developed into medicines that target a protein in the human body that is responsible for chemotherapy resistance in cancers, said biochemist Pia D. Vogel, lead author on the scientific paper reporting the discovery.
So far there’s no approved drug on the market that reverses cancer chemotherapy resistance caused by P-glycoprotein, or P-gp for short, said Vogel, a biochemistry professor at SMU. One potential drug, Tariquidar, is currently in clinical trials, but in the past, other potential drugs have failed at that stage.
“The problem when a person has cancer, is that the treatment itself is composed of cellular toxins — the chemotherapeutics that prevent the cells from dividing. Usually upon the first chemotherapy treatment the cancer responds well, and initially goes away. Ideally it doesn’t come back,” said Vogel, director of SMU’s Center for Drug Discovery, Design and Delivery.
Three drug-like compounds bind in human P-glycoprotein, reversing chemotherapy resistance in prostate cancer cells in culture. (Image, James McCormick)
“Sometimes, however, the cancer returns,” she said. “The reason often is that some of the cancer cells “learn,” after the first rounds of chemotherapy, how to make a lot of this P-gp pump. The normal function of P-gp is to pump toxins from cells, so it has evolved to protect cells against a large variety of toxins, including almost all currently available chemotherapeutics. After initial exposure, the cells surviving the chemo make so much P-gp that it allows the cells to pump the chemotherapy drugs straight back out of the cells during subsequent rounds of treatment.”
As a result, P-gp causes resistance of the diseased cells to a majority of drugs currently available for the treatment of cancer, as well as drugs used for treatment of infectious diseases like HIV/AIDS.
Using computer-generated model speeds up the drug discovery process The new drug-like compounds discovered by Vogel and her co-authors offer hope that using a computer-generated P-gp model, developed to accurately mimic the physical, chemical and biological functions of the protein in the human body, will speed up the drug discovery process and work in real life as well.
P-glycoprotein’s pumping action is stalled, when a drug-like compound (dark blue) prevents the power source (red) from being used by P-glycoprotein, the protein that transports toxins from a cell. (Image: James McCormick)
“These are not drugs yet. We still have to develop them before they can go in the clinic,” Vogel said. “But what we know now is that they’re not toxic — they have low toxicity to noncancerous cells, so that’s a pretty good predictor that they may be good candidates for drug development. But we need to do much more work.”
A pharmaceutical hit compound, like those discovered by Vogel and her co-authors, is a compound that is a promising candidate for chemical modification so it can eventually be delivered to patients as a therapeutic drug. In the case reported here, the compounds were commercially available for testing. The timeline from drug discovery to development to clinical trials and approval can take a decade or more.
Vogel and her co-authors, SMU biologist John G. Wise, and doctoral candidates Courtney A. Follit and Frances K. Brewer, reported their findings in the journal Pharmacology Research & Perspectives. The article, “In silico identified targeted inhibitors of P-glycoprotein in culture,” is published online at http://bit.ly/1JjFizg.
The research was funded in part by the National Institutes of Health. The lab was recently awarded a second grant from the Institute.
Researchers virtually screened 15 million drug-like compounds via SMU supercomputer
The SMU researchers discovered the three hit compounds after virtually screening more than 15 million small drug-like compounds made publically available in digital form from the pharmacology database Zinc at the University of California, San Francisco.
Using SMU’s ManeFrame high performance computer, Wise ran the compounds through a computer-generated model of P-gp. The virtual model, designed and built by Wise, is the first computational microscope of its kind to simulate the actual behavior of P-gp in the human body, including interactions with drug-like compounds while taking on different shapes.
The ultra-high throughput computational searches by ManeFrame led the researchers to 300 compounds that looked like they may inhibit P-gp. The researchers then tested 38 of those in their physical lab and found four that inhibited the biochemical function of P-gp, stopping it in its action.
Each of the four compounds was then tested in the lab to see how it would affect a line of prostate cancer cells relatively sensitive to the chemotherapeutic Paclitaxel, commonly used to treat prostate cancer patients. Also, each was tested on a companion cell line already multi-drug resistant, as if the patient already had undergone chemotherapy using Paclitaxel.
The researchers found that with three of the four compounds, they were able to push back the sensitivity of the resistant cancer line to the level of the non-resistant one.
“So the compounds re-sensitized the cancer cell lines to a really high degree, just as if the cancer was seeing the chemotherapy for the first time,” Vogel said.
About 14 percent of men will be diagnosed over their lifetime with prostate cancer, according to the National Cancer Institute. Survival is highest if diagnosed early before it has spread, the institute reports.
Scientists have sorted through millions of cosmic ray strikes and zeroed in on neutrino interactions in their quest to learn more about the abundant yet mysterious particles that flit through ordinary matter as though it isn’t there.
Initial data from a new U.S.–based physics experiment indicates scientists are a step closer to understanding neutrinos, the second most abundant particle in the universe.
Neutrinos are little understood, but indications are they hold clues to why matter overwhelmingly survived after the Big Bang instead of just energy in the form of light.
The first data from NOvA, the experiment in northern Minnesota, indicates that NOvA’s massive particle detector — designed to observe and measure the behavior of neutrinos — is functioning as planned.
“In the 18 or so months the experiment has been up and running we’ve analyzed about 8 percent of the data we anticipate collecting over the life of the experiment,” said physicist Thomas Coan, Southern Methodist University, Dallas.
Coan, a professor in SMU’s Department of Physics, is a principal investigator on NOvA, a collaboration of the U.S. Department of Energy’s Fermi National Laboratory. “So we’re really just at the beginning. But it’s a great start, and it’s gratifying that the beginning has begun so well.”
More than 200 scientists from the U.S. and six other countries make up the collaboration.
Specifically, they predict that the experiment’s data will tell them the relative weight of the three different types or “flavors” of neutrinos, as well as reveal whether neutrinos and antineutrinos interact in the same way.
Answers to those questions will add information to theories of matter’s existence and why it wasn’t annihilated during the Big Bang, Coan said.
The completed NOvA far detector in Ash River, Minnesota, stands 50 feet tall, 50 feet wide and 200 feet long. The pivoting machine that was used to move each block of the detector into place now serves as the capstone on the end of the completed structure. Photo: Fermilab
“If we want to understand the universe on a large scale, we have to understand how neutrinos behave,” he said. “Experimental observations from NOvA will be an important input into the overarching theory.”
Neutrinos flit through ordinary matter almost as if it weren’t there, so it takes a massive detector to capture evidence of their behavior. Coan likens NOvA to a gigantic pixel camera with its honeycomb array of thousands of plastic tubes encasing highly purified mineral oil.
Neutrinos are not observed directly, so scientists only see the tracks of their rare interactions with atoms. An accelerator at Fermilab in Illinois shoots a neutrino beam, observed first by a near detector there, then by a far detector some 500 miles away in Minnesota.
The far detector, or “pixel camera,” is 50 feet tall by 50 feet wide and 200 feet long.
Oscillating neutrinos change from one “type” to another: electron, muon or tau
As the neutrinos travel they change from one type or “flavor” to another. That “oscillation” confirms the NOvA detector is functioning as designed.
A graphic representation of one of the first neutrino interactions captured at the NOvA far detector in northern Minnesota. The dotted red line represents the neutrino beam, generated at Fermilab in Illinois and sent through 500 miles of earth to the far detector. The image on the left is a simplified 3-D view of the detector, the top right view shows the interaction from the top of the detector, and the bottom right view shows the interaction from the side of the detector. Illustration: Fermilab
The results were culled by scientists who sorted through millions of cosmic ray strikes to zero-in on neutrino interactions.
“People are ecstatic to see our first observation of neutrino oscillations,” said NOvA co-spokesperson Peter Shanahan, Fermilab. “For all the people who worked over the course of a decade on the designing, building, commissioning, and operating this experiment, it’s beyond gratifying.”
Researchers have collected data aggressively since February 2014, recording neutrino interactions in the 14,000-ton far detector in Ash River, Minnesota, while construction was still underway. This allowed the collaboration to gather data while testing systems before starting operations with the complete detector in November 2014, shortly after the experiment was completed on time and under budget. NOvA construction and operations are supported by the DOE’s Office of Science.
The neutrino beam generated at Fermilab passes through the underground near detector, which measures the beam’s neutrino composition before it leaves the Fermilab site.
The particles then travel more than 500 miles straight through the earth, changing types along the way. About once per second, Fermilab’s accelerator sends trillions of neutrinos to Minnesota, but the elusive neutrinos interact so rarely that only a few will register at the far detector.
Neutrino-atom interaction releases a signature trail of particles and light
The beam fires neutrinos every 1.5 seconds, but only for 10 microseconds, Coan said. Including downtime for maintenance, neutrinos are produced two minutes total over the course of a year.
“We could make the detector out of iron or granite to get more target atoms and have more interactions, but we’d never be able to observe the interactions in iron and granite,” Coan said. “So the detector has to be transparent somehow, a sort of camera. Those two goals are somewhat contradictory. So it takes some cleverness to figure out how to have a massive detector and still see events in it.”
When a neutrino bumps into an atom in the NOvA detector, it releases a signature trail of particles and light depending on which type it is: an electron, muon or tau neutrino. The beam originating at Fermilab is made almost entirely of one type – muon neutrinos – and scientists can measure how many of those muon neutrinos disappear over their journey and reappear as electron neutrinos.
If oscillations had not occurred, experimenters predicted they would see 201 muon neutrinos arrive at the NOvA far detector in the data collected; instead, they saw a mere 33, proof that the muon neutrinos were disappearing as they transformed into the two other flavors
Similarly, if oscillations had not occurred scientists expected to see only one electron neutrino appearance, due to background interactions, but the collaboration saw six such events, which is evidence that some of the missing muon neutrinos had turned into electron neutrinos.
NOvA observations are nearly equivalent results to those at world’s other neutrino experiments
Similar long-distance experiments such as T2K in Japan and MINOS at Fermilab have seen these muon neutrino-to-electron neutrino oscillations before. NOvA, which will take data for at least six years, is seeing nearly equivalent results in a shorter time frame, something that bodes well for the experiment’s ambitious goal of measuring neutrino properties that have eluded other experiments so far.
“One of the reasons we’ve made such excellent progress is because of the impressive Fermilab neutrino beam and accelerator team,” said NOvA co-spokesperson Mark Messier of Indiana University. “Having a beam of that power running so efficiently gives us a real competitive edge and allows us to gather data quickly.”
Fermilab’s flagship accelerator recently set a high-energy neutrino beam world record when it reached 521 kilowatts, and the laboratory is working on improving the neutrino beam even further for projects such as NOvA and the upcoming Deep Underground Neutrino Experiment. Researchers expect to reach 700 kilowatts early next calendar year, accumulating a slew of neutrino interactions and tripling the amount of data recorded by year’s end.
Most abundant massive particle in the universe is still poorly understood
Neutrinos are the most abundant massive particle in the universe, but are still poorly understood. While researchers know that neutrinos come in three types, they don’t know which is the heaviest and which is the lightest. Figuring out this ordering — one of the goals of the NOvA experiment — would be a great litmus test for theories about how the neutrino gets its mass.
While the famed Higgs boson helps explain how some particles obtain their masses, scientists don’t know yet how the Higgs is connected to neutrinos, if at all.
The measurement of the neutrino mass hierarchy is also crucial information for neutrino experiments trying to see if the neutrino is its own antiparticle.
Like T2K, NOvA can also run in antineutrino mode, opening a window to see whether neutrinos and antineutrinos are fundamentally different. An asymmetry early in the universe’s history could have tipped the cosmic balance in favor of matter, making the world we see today possible. Soon, scientists will be able to combine the neutrino results obtained by T2K, MINOS and NOvA, yielding more precise answers about scientists’ most pressing neutrino questions.
“The rapid success of the NOvA team demonstrates a commitment and talent for taking on complex projects to answer the biggest questions in particle physics,” said Fermilab Director Nigel Lockyer. “We’re glad that the detectors are functioning beautifully and providing quality data that will expand our understanding of the subatomic realm.”
The NOvA collaboration comprises 210 scientists and engineers from 39 institutions in the United States, Brazil, the Czech Republic, Greece, India, Russia and the United Kingdom. — Fermi National Laboratory, SMU
NOvA stands for NuMI Off-Axis Electron Neutrino Appearance. NuMI is itself an acronym, standing for Neutrinos from the Main Injector, Fermilab’s flagship accelerator. The Fermilab Accelerator Complex is an Office of Science User Facility.
SMU is a nationally ranked private university in Dallas founded 100 years ago. Today, SMU enrolls nearly 11,000 students who benefit from the academic opportunities and international reach of seven degree-granting schools. For more information see www.smu.edu.
Fermilab is America’s premier national laboratory for particle physics and accelerator research. A U.S. Department of Energy Office of Science laboratory, Fermilab is located near Chicago, Ill., and operated under contract by the Fermi Research Alliance LLC. Visit Fermilab’s website at www.fnal.gov, and follow Fermilab on Twitter at @Fermilab.
The DOE Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, please visit science.energy.gov.
SMU has an uplink facility located on campus for live TV, radio, or online interviews. To speak with an SMU expert or book an SMU guest in the studio, call SMU News & Communications at 214-768-7650.
Now Walkington has asked students to test motion capture software as a tool for teaching math. The students are enrolled in summer video game design camps at Guildhall, SMU’s premier graduate video game education program.
Students practiced a motion capture software program that teaches geometry. The program was created by Walkington in partnership with Extreme Reality, an industry leader in motion capture software. Results of the preliminary testing will be included in a grant proposal Walkington is preparing to test the software further.
Book a live interview
To book a live or taped interview with Candace Walkington in the SMU Studio call SMU News at 214-768-7650 or email SMU News at news@smu.edu.
For the preliminary test, Walkington asked students to read problems on a computer and then move their arms to either signal their answers or advance the math questions to the next sequence.
The study is one of several for Walkington, whose previous studies have focused on how abstract mathematical concepts can be grounded in students’ out-of-school interests, experiences and everyday reasoning practices.
Another of Walkington’s recent studies, published in the Journal of Educational Psychology, draws data from Pennsylvania classrooms using an in-school intelligent tutoring system for Algebra I. The software personalizes instruction to match the pace of each student, detects a student’s current state of knowledge, determines which kinds of problems to present and what feedback and help are needed, and tracks each child’s progress. Walkington has a long-time collaboration with Carnegie Mellon University’s Pittsburgh Science of Learning Center.
She has also been awarded a grant as part of the Spencer Postdoctoral Fellowship Program of the National Academy of Education. The $55,000 grant supports early career scholars working in critical areas of education research.
Walkington earned B.S. and M.S. degrees in mathematics from Texas A&M University, and had planned to have a career as a financial mathematician. She changed her career path after completing a National Science Foundation graduate teaching fellowship at a high-poverty rural school in Iola, Texas.
There Walkington discovered firsthand the satisfaction of designing innovative strategies to help struggling fifth and sixth graders learn math. The experience brought back memories of her own seventh-grade struggle with algebra, which had threatened to derail her interest in math.
While working on her Ph.D. at the University of Texas at Austin, Walkington collaborated on research geared toward identifying what teacher behaviors are a strong predictor of student success on standardized math tests. The research was incorporated into the Gates Foundation’s Measures of Effective Teaching Project, one of the largest research efforts in U.S. history to identify and understand effective teaching. The project is shaping educational policy nationally.
Walkington and research colleague Michael P. Marder, executive director of UTeach Science Program, University of Texas at Austin, contributed protocols to the MET Project based on their findings, including one finding that classrooms where the teacher focuses specifically on students deeply understanding math have higher test scores compared to classrooms where teachers focus on drill and standardized test preparation. In addition, they also found that classroom management was a necessary, but not sufficient, condition for learning.
SMU is a nationally ranked private university in Dallas founded 100 years ago. Today, SMU enrolls nearly 11,000 students who benefit from the academic opportunities and international reach of seven degree-granting schools. For more information see www.smu.edu.
Physicists tune Large Hadron Collider to find “sweet spot” in high-energy proton smasher