The importance of clarity

Two recent newspaper articles reminded me of the importance of clarity when writing about complex topics. In “Our feel-good war on breast cancer,” which was the cover article of last week’s New York Times magazine, Peggy Orenstein tackled the question of whether campaigns to raise awareness of breast cancer and urge women to have mammograms do more harm than good.

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Orenstein’s reporting of the question’s medical, social, and economic aspects is impressive, as are her fluid narrative and engaging style. She also succeeds in clearly conveying the tricky topic of how risk is assessed and described. Five-year survival rate, I learned, is a potentially misleading statistic.

But to me, what makes her article admirably distinctive is her account of her own experiences with breast cancer. Even though she benefited from the early detection of a tumor, she does not advocate universal early screening. Quite the opposite. Her final paragraph reads:

It has been four decades since the former first lady Betty Ford went public with her breast-cancer diagnosis, shattering the stigma of the disease. It has been three decades since the founding of Komen. Two decades since the introduction of the pink ribbon. Yet all that well-meaning awareness has ultimately made women less conscious of the facts: obscuring the limits of screening, conflating risk with disease, compromising our decisions about health care, celebrating “cancer survivors” who may have never required treating. And ultimately, it has come at the expense of those whose lives are most at risk.

The other reminder of clarity’s importance came in the form of an editorial in Tuesday’s Washington Post. Under the title, “EPA speaks on how much radiation is too much,” the newspaper’s editorial board opined on a proposal, released on 15 April by the US Environmental Protection Agency, to update the agency’s guide to emergency services in the event of a nuclear accident or attack.

The Post‘s editorial board duly weighed activists’ objections to the proposal, yet found in favor of the EPA—but with this sting in the tail:

The activists are right, though, about one thing: The document is a confusing bore. If the EPA wants city, county and state officials to pay attention—if it wants to make the case for practicality over the activists’ hyperbole—the agency ought to rewrite the guidelines in plain English.

My first encounter with the controversy surrounding radiation protection guidelines arose when I was assigned to edit Zbigniew Jaworowski’s article “Radiation risk and ethics,” which appeared in Physics Today‘s September 1999 issue. The article amounted to a long, multifaceted argument against the assumption that any radiation dose, no matter how small, could cause cancer.

The article was easy to edit. Jaworowski had organized the article deftly and made his points directly and with well-chosen evidence to support them. I was gratified to see that it spawned 12 letters to the editor, which were split between the April and May 2000 issues. Whether they agreed with Jaworowski or not, the letter writers had evidently understood his arguments.

Of course, scientists should strive to be clear even when they’re not engaged in controversy. And they should be especially clear when they propose a revolutionary new theory or experimental result.

One of my favorite examples of a clear, bold proposal is the paper that launched the field of chaos theory: Edward Lorenz’s “Deterministic nonperiodic flow,” which appeared in the March 1963 issue of the Journal of Atmospheric Sciences. Here’s a sample of Lorenz’s style from the paper’s introduction:

Lack of periodicity is very common in natural systems, and is one of the distinguishing features of turbulent flow. Because instantaneous turbulent flow patterns are so irregular, attention is often confined to the statistics of turbulence, which, in contrast to the details of turbulence, often behave in a regular well-organized manner. The short-range weather forecaster, however, is forced willy-nilly to predict the details of the large-scale turbulent eddies—the cyclones and anticyclones—which continually arrange themselves into new patterns. Thus there are occasions when more than the statistics of irregular flow are of very real concern.

Although you might get bogged down in the main, technical section of the paper, the entire introduction is accessible. And if that extract has whetted your appetite for more clarity about chaos, I recommend Adilson Motter and David Campbell’s May 2013 Physics Today article, “Chaos at fifty,” which celebrates the half century of research that Lorenz’s paper begat.

Monte Carlo, colloids, and public health

C&Edec012_275 My first professional encounter with the Monte Carlo method came not during my long-abandoned career as an astronomer when I might have used the computational technique, but years later when I ran Physics Today‘s Search and Discovery department.

In 2004, I faced the task of describing a new Monte Carlo algorithm. Devised by Erik Luijten (while taking a shower, he told me), the new algorithm could do what the standard one, the Metropolis algorithm, couldn’t: efficiently simulate a colloid whose suspended particles had widely different sizes.

Suspecting that some of my readers might be unfamiliar with Metropolis, I included a short tutorial. I pointed out that using an alternative, more direct simulation method—molecular dynamics (MD)—was impractical: It’s possible to calculate the forces acting on all the colloid’s particles, but only for a modest number of consecutive time steps. The movie-like simulation that MD produces would be too brief to provide physical insight.

But the Metropolis algorithm, I told my readers, doesn’t follow every particle all the time. Rather, it calculates snapshots of the system and uses statistical mechanics to combine them. Comparing the two methods, I wrote:

So, if MD is like a movie, the Metropolis algorithm is like a sparse set of shuffled snapshots. If you simulated a cocktail party with the Metropolis algorithm, you wouldn’t see dynamical events, such as guests arriving and departing, or rare events, such as a waiter refilling a punchbowl. But, taken together, the Metropolis snapshots would fairly represent the party in full swing. From them, you could deduce whether, on average, people had enjoyed themselves.

My latest brush with Monte Carlo happened last week. Looking for research to write about, I came across a paper by Luis Zamora and his colleagues entitled “A Monte Carlo tool to study the mortality reduction due to breast screening programs.”

Screening for breast cancer is difficult and controversial. It’s difficult because the principal method, x-ray mammography, cannot by itself determine whether a lesion is malignant. Because of that limitation, follow-up biopsies are essential, but most lesions—roughly 4 in 5—turn out to be benign.

Controversy surrounds the question of when to start screening. Not only is the disease harder to detect in young women, it’s also less prevalent. Definitive evidence in favor of screening women aged between 40 and 49 years is lacking. Yet doctors—who treat individuals, not populations—are reluctant to tell patients under 49 that they don’t need a mammogram yet. Why take even a small risk?

The tool that Zamora and his colleagues have built simulates the fate of a population of women who enter a screening program. You can adjust the program’s age range and participation rate. Clinically derived parameters, such as the probability of detecting a tumor, are incorporated into the tool.

Zamora and his colleagues present their results in graphs and tables, which are hard to summarize in a short column. They predict, for example, that breast cancer mortality can be reduced by 29% if 100% of women aged 50–70 are screened every two years.

But they did discover what appears to be a critical parameter. For a screening program to be effective, its participation rate must be at least 50%. In the US, where 16.3% of the population lacks health insurance, that target is unfortunately ambitious.

This essay by Charles Day first appeared on page 88 of the March/April 2013 issue of Computing in Science & Engineering, a bimonthly magazine published jointly by the American Institute of Physics and IEEE Computer Society.

Rocks and bones

The availability of scientific papers online makes it easier not only to find the latest research but also to trace back through time a paper’s academic ancestry, which may or may not lie in the same field. That boon to the curious came to mind this morning when I encountered a paper in JASA Express Letters.

The paper is by Katsunori Mizuno of Doshisha University in Kyoto, Japan, and his colleagues. What caught my eye was its title: “Propagation of two longitudinal waves in a cancellous bone with the closed pore boundary.”

Cancellous bone, in case you didn’t know, is the spongy type of osseous tissue that constitutes the inside parts of long bones, especially at the ends, and of vertebrae. Cortical bone is the other type of osseous tissue. It provides cancellous bone with a solid casing and constitutes the inside and outside of small bones.

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Both types osseous tissue regenerate at their surfaces, but because of its porous structure, cancellous bone is more readily weakened than is cortical bone when regeneration fails to keep up with wear and tear. The two images show samples of cancellous bone taken from vertebrae. The top one comes from a 21-year-old man; the bottom one comes from a 65-year-old woman.*

Mizuno and his colleagues are trying to develop an ultrasound-based method for assessing the condition of bones. Although doctors already have methods based on x rays at their disposal, an ultrasound diagnostic would likely be cheaper and more convenient.

Water-saturated rocks

Not knowing much about the propagation of ultrasound in bones, I was surprised to learn from the antecedents to Mizuno’s paper that his line of research springs, in part, from a paper about water-saturated rocks. In 1956 Maurice Biot published a theoretical description of what happens when sound waves travel through a fluid-filled porous medium.

At that time Biot worked for an oil company. I’m not sure whether his paper helped anyone to find oil deposits. It did, however, help to establish the field of poromechanics. It also predicted that porous, fluid-filled media support two distinct compressional waves: the normal shear wave and a so-called slow wave that arises from refraction and mode conversion at the solid–fluid boundaries.

Biot’s prediction was verified in 1979 by another oil-company researcher, Thomas Plona, who detected the slow wave when he sent ultrasound pulses through a medium that consisted of sintered glass spheres immersed in water.

Judging by the papers that Mizuno and his coauthors cite, it took another two decades before anyone recognized the relevance of Biot’s slow wave to bone tissue. In 1995 Atsushi Hosokawa and Takahiko Otani detected the fast and slow waves in a sample of cancellous bone from a cow. What’s more, they showed that the normal waves propagate through bone, whereas the slow waves propagate through the soft, viscous material that fills the pores.

Before Biot’s theory can be turned into an in vivo diagnostic, more research is needed into how ultrasound propagates in whole, intact bones, whose structure is not isotropic, as Biot’s theory presumes. Mizuno and his collaborators took a further step in that direction by examining a sample of cancellous bone that retained its casing of cortical bone.

Having learned something of Biot’s theory, I became curious about the man himself. If you are too, you can read about his distinguished career in his obituary, which appeared in Physics Today in May 1986.

Charles Day

* The images come from “Plasticity and toughness in bone,” an article by Robert Ritchie, Markus Buehler, and Paul Hansma, which appeared in Physics Today‘s June 2009 issue.

The surprising spinoff of Projects Bumblebee and SQUID

Basic research, its proponents argue, is worth funding because of its sometimes surprising and valuable spinoffs. When Glenn Seaborg and his colleagues began making new transuranic elements in the 1940s, they didn’t have in mind the use of one of them, americium, in household smoke detectors. Applied research, even mission-directed research, can have surprising spinoffs, too.

In 1945 John Fenn was invited by James Mullen of Bell Labs join Project Bumblebee, a program to develop ram-jet powered antiaircraft missiles for the US Navy. Up to that point, Fenn, who had earned a PhD at Yale in electrochemistry, had worked for Monsanto in Anniston, Alabama, and for Sharples Chemicals in Wyandotte, Michigan. He had no experience in jet combustion and propulsion.

Then, having acquired at least a reputation for expertise in jets, Fenn was recruited to lead Project SQUID, a program at Princeton University funded by the Office of Naval Research. Like Bumblebee, SQUID was about jet propulsion, but it was more open-ended. Its goal was to elucidate the physics and chemistry of hot gases expelled from nozzles.

If you read the article by Dawn Manley, Andrew McIlroy, and Craig A. Taatjes, “Research needs for future internal combustion engines” (Physics Today, November 2008, page 47), you might remember that ignition and combustion are difficult to study in detail. Indeed, it remains impossible to model what goes on inside a car engine on all the relevant scales of length and time.

Tackling a similar modeling challenge but with 1950s tools, Fenn realized that he could make more progress by studying a simpler system: the expansion through a nozzle of jets of cold molecular gas. In 1989, having worked on molecular jets for three decades, Fenn and his colleagues published the unexpected culmination of that realization in Science.

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In that paper, Fenn’s team demonstrated a new method for determining the molecular weight of bulky biomolecules. Squirting a solution of molecules through an electrified nozzle forms a spray of ionized droplets. The solvent surrounding each molecule evaporates to leave single molecular ions, whose mass can be measured by a mass spectrometer.

The photo shows Fenn’s first electrospray ionization mass spectrometer, an invention for which he shared the 2002 Nobel Prize in Chemistry.

Another unexpected spinoff from applied research—again with a naval history—arose from a commission that Lord Rayleigh received in 1917 from the British Admiralty. Why, the admiralty wanted to know, were the rapidly spinning propellers of turbine-driven warships deteriorating so rapidly?

Rayleigh identified the cause: cavitation. As a ship’s propeller spins, it subjects the surrounding water to rapid and intense changes in pressure. At low pressure, voids—cavities of vapor—form on the propeller surface. At high pressure, the cavities collapse and in doing so direct a jet of liquid at the surface. The cumulative effect of that bombardment eventually creates pits in the propeller’s steel surface.

The formulas that Rayleigh developed to characterize cavitation apply in a quite different and beneficial context: extracorporeal shock wave lithotripsy, the noninvasive destruction of kidney stones using ultrasound.

Charles Day

Cell motility, tissue stiffness, and cancer

If you open a biology textbook, you’ll probably encounter microscope images of single cells, stained and stuck to glass slides. Imaging—and more generally, studying—cells in two dimensions is much easier than in three, not least because a microscope’s focus doesn’t have to be continually adjusted.

But that convenience is not without cost. At the Biophysical Society’s annual meeting in Baltimore, I learned yesterday that some cells behave differently in 3D than they do in 3D. As Denis Wirtz of the Johns Hopkins University pointed out in his talk, the cells that participate in wound healing or metastatic cancer follow 3D paths through 3D tissue. Understanding that behavior is medically important.

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Wirtz and his collaborators study focal adhesions (FAs), the dynamic bundles of fibrous proteins that mediate a cell’s mobility and adhesion. In 2D—that is, on a flat surface in a shallow medium—cells spread out like fried eggs and large FAs form on the cell’s bottom surface.

In a fully 3D medium, however, Wirtz and his group discovered that cells adopt fluid, less flattened shapes and occasionally sprout appendages that resemble an amoeba’s pseudopodia. What’s more, Wirtz couldn’t see any FAs in his 3D-dwelling cells. The various proteins that make up FAs in 2D-dwelling cells still mediate mobility, but they’re spread more or less evenly inside the cell.

Tumor stiffness

In the talk that followed Wirtz’s, Valerie Weaver of the University of California, San Francisco, described her group’s research into the dynamic interplay between tumor cells and their microenvironment. Weaver noted that tumors are stiffer than the healthy tissue that surrounds them. Could stiffness be a prerequisite of tumor growth in addition to being a property of tumors themselves?

Weaver’s group found in 2005 that cancer cells are indeed more malignant in stiff environments. Her group’s more recent work shows why that’s the case.

In general, a cell’s attachment to the extracellular matrix (ECM) is mediated by transmembrane proteins called integrins. Weaver and her team stiffened the ECM by promoting crosslinkng among the ECM’s collagen fibers. Cancer cells responded by invading the stiffened ECM. Significantly, the invasion could be stopped or accelerated by, respectively, inhibiting or promoting integrin’s activity. Weaver speculates that integrin, which is a signaling protein, somehow communicates with cancer genes.

It’s not clear whether integrin or another molecule that mediates a cell’s mechanical properties could become a “drugable target,” to use a pharmacological term. However, cell and tissue stiffness could become reliable predictors of risk and disease progression.

Charles Day

Practical holography at SPIE Photonics West

I’m in San Francisco this week for SPIE Photonics West, “the world’s leading photonics, laser, and biomedical optics event,” according to the conference slogan. The conference is huge. In fact, it consists of five separate but contemporaneous conferences: BiOS (1771 research papers), LASE (662), MOEMS-MEMS (202), OPTO (1320), and Green Photonics (270).

Faced with such a cornucopia, I chose to spend my first morning attending an OPTO session entitled “Scientific Holography, Applications and Experimental Techniques I.” Here, I thought, was a session that represents what Photonics West is all about: an interesting and important application of light.

My favorite talk of the morning was by Tokyo University’s Naoya Tate. He and his colleagues are using nanotechnology to embed information on the nanoscale within information on the macroscale.

That goal is hard to reach if, as is the case with Tate’s scheme, the information is to be retrieved optically. “Nanoscale” is a somewhat loose term, but it usually refers to features that are 1 to 100 nm long. Visible light, which ranges in wavelength from 380 nm (violet) to 750 nm (red), can’t ordinarily resolve subwavelength features.

However, if you bring your probe into the near-field region—that is, within one wavelength of an object’s surface—you can resolve subwavelength features. In Tate’s scheme, which he calls a nanophotonic hierarchical hologram, the subwavelength features belong to a nanoscale metallic grid-like structure embedded within a sandwich of holographic gratings.

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When illuminated from a macroscopic distance, the gratings project a hologram of a three-dimensional, macroscale object. When illuminated and viewed from a nanoscale distance, the nanoscale grid reveals the information encoded in its structure.

Security is one possible application. The nanoscale grid could serve as a covert watermark on a hologram. Besides a near-field microscope, no special equipment would be needed to check it.

In his talk, Tate noted that the idea of embedding information on short length scales in a larger image has been used before. Last year, scientists examining the Mona Lisa discovered that Leonardo da Vinci had written tiny letters on Lisa del Giocondo’s pupils.

Charles Day

Plate tectonics, Heliobacter pylori, and the physics of nerves

Tuesday’s New York Times included an obituary for Jack Oliver. In 1964 he and two of his former graduate students, Bryan Isacks and Lynn Sykes, set up seismographs in Tonga and Fiji. The trio detected unexpectedly deep earthquakes that originated in the subduction of the Pacific plate beneath the Indo-Australian plate. The discovery provided further, and ultimately conclusive, evidence that Earth’s continents drift about on the surface of the globe.

Remarkably, the idea of continental drift was proposed decades earlier, in 1912 by Alfred Wegener. Although Wegener could point to circumstantial evidence to support his idea—the coasts of Africa and South America look as though the two continents were split then pushed apart, for instance—he couldn’t tell skeptics what processes powered the titanic motions.

The detailed mechanism behind continental drift remains uncertain. But by 1965, evidence from paleomagnetism, ocean bathymetry, and seismology vindicated Wegener’s then 53-year-old theory. Born in Berlin in 1880, Wegener might have lived to savor his victory over the skeptics. Unfortunately, he died in Greenland in 1930 while conducting meteorological experiments.

Barry Marshall and Robert Warren didn’t have to wait to prove their skeptics wrong. In the early 1980s, they succeeded in growing colonies of a bacterium, Heliobacter pylori, outside its usual habitat, the human stomach. To vindicate their theory that H. pylori causes stomach ulcers, Marshall drank a beaker of the bacteria. Several days later he became ill with gastritis. Twenty years later he and Warren shared a Nobel Prize.

Skepticism is a core value of science. Qualifying for inclusion in the body of scientific knowledge is, and should be, a rigorous, if not a difficult, process. Wegener’s skeptics were justified in pointing out the lack of a mechanism and direct evidence. Unlike Marshall and Warren, Wegener couldn’t satisfy his critics in a direct, straightforward way.

Which brings me to a paper that I received recently from Bill Brownell of Baylor College of Medicine’s department of otolaryngology. Written by Thomas Heimburg of the Niels Bohr Institute, the paper bears the title “The Physics of Nerves.” Its abstract reads

The accepted model for nerve pulse propagation in biological membranes seems insufficient. It is restricted to dissipative electrical phenomena and considers nerve pulses exclusively as a microscopic phenomenon. A simple thermodynamic model that is based on the macroscopic properties of membranes allows explaining more features of nerve pulse propagation including the phenomenon of anesthesia that has so far remained unexplained.

In Heimburg’s model the membrane carries the neural signals as a local change of state from liquid to solid. The membrane’s electric potential still changes as ions pass back and forth through the membrane, but the potential’s role is to mediate the signal-carrying phase change, rather than to carry the signal itself. To support his case, Heimburg evokes various experiments that evince mechanical and thermodynamic changes in nerves as they transmit signals.

Heimburg argues that his model can also explain the still-unresolved mechanism of chloroform and other general anesthetics. Biochemical evidence has ruled out the possibility that general anesthetics work in the same way as neurotoxins—that is, by binding to, and thereby jamming, ion channels. Rather, anesthetics work, he argues, by lowering the membrane’s melting point and putting the all-important phase change out of reach.

Even though my background is astronomy, not biophysics, I’m skeptical of Heimburg’s model. Sperm whales can function at the sea surface, where the pressure is 1 atm; at depths of 3 km, where the pressure is 300 atm; and at all depths in between. Given that melting temperature depends on pressure, Heimburg’s model would seem to require some sort of continuous adaptation to ambient pressure.

As for general anesthetics, a computer simulation published in 2002 suggests that they do indeed alter the fluidity of the membrane, but in a way that makes the embedded ion channels floppier and therefore less effective.

My skepticism aside, a cell membrane, being made up of interacting particles, has mechanical and thermodynamic propertiees. It is not implausible that nature has found a way to adjust and exploit them.

Charles Day

Physics and the fight against cancer

At first glance, cancer might seem defenseless against the weapons devised by physicists or built from their discoveries.

The resolution of magnetic resonance imaging scanners, for instance, is a few cubic millimeters. Nascent tumors can in principle be detected when they’re small, isolated, and easiest to treat. And when a tumor is found, high-energy x rays, gamma rays, protons, and other forms of radiation can be directed at tumors in beam patterns of increasing sophistication and effectiveness.

But having written about cancer over the years, I’ve learned that there’s more to beating the disease than locating and zapping tumors.

One of the biggest challenges arises from the nature of cancer. Ironically, given that the disease is characterized by rampant cell division, tumors grow slowly and, for the most part, stealthily. The ability to resolve a lentil-sized tumor is little help if you don’t know where to look.

And that ability is even less help if you don’t know whether to look in the first place. In rich countries, cancer ranks below heart disease and noncancerous respiratory diseases as a leading cause of death. Most people don’t die of cancer. Routine, image-based screening for the general population would reveal too few tumors to offset its huge cost.

Compounding the detection problem, especially for breast cancer, is the number of false positives. Five years ago, in the course of looking for research to write about, I came across a paper in the Proceedings of the National Academy of Sciences by MIT’s Michael Feld and his collaborators. Its introduction began with this striking and somewhat depressing paragraph (with my emphasis added):

In the United States, ≈216 000 new cases of breast cancer are diagnosed each year, and 40 000 women die from the disease. Mammography, the most common technique for detecting nonpalpable, highly curable breast cancer, employs x-rays to quantitatively probe density changes in breast tissue. Because these density changes are not uniquely correlated with breast cancer, mammography serves as a screening technique rather than a diagnostic tool. Thus, a lesion found through either clinical breast examination or mammography is always biopsied. Because of current limitations, 70–90% of mammographically detected lesions are found to be benign upon biopsy. Breast biopsy is most often performed by surgical excision that removes the entire lesion or by core needle biopsy that removes 5–12 cores of tissue, typically 1 mm in diameter and several centimeters long, to ensure proper sampling. The complete diagnostic process, from start to finish, may take months and may include multiple biopsies.

But if you can detect cancer early, the prognosis following prompt treatment is good. Table 8-2 in The Biological Basis of Cancer (Cambridge U. Press) compiles three-, five-, and ten-year survival rates for seven malignancies. All except the ten-year survival rate for breast cancer are above 57%.

How could physics help to achieve a survival rate of 100%? As a former astronomer, I’m not qualified to answer, but as a writer, I can imagine what an ideal treatment might look like.

Early detection would be carried out through a noninvasive, nonimaging method. A blood test would be ideal. To kill the tumor, the patient would ingest an agent that would make its way to the tumor, stick to it, then inject a cancer-killing drug into the tumor cells. A blood test after the treatment could confirm its success.

How fanciful is that scenario? And where does physics fit in? I’m not sure about the first question, but the second is easier to answer because physicists are already working with scientists in other disciplines to solve it.

A blood test might arise from the statistical analysis of the cancer genome. Nanoparticles that can adhere to tumor cells have already been developed. Research that seeks to discover how viruses inject their RNA or DNA into cells could point to how artificial viruses could accomplish the same thing with anticancer drugs. Physicists are also working on how to repair p53, a key, cancer-fighting protein that fails to protect cells when it suffers certain mutations.

But before that research bears fruit, physicists are improving current therapies and diagnostics. The latest innovation that I’ve come across, stereotactic body radiation therapy, entails treating tumors with short, intense bursts of radiation.

From my inexpert perspective, the prospects for defeating cancer look good.

Charles Day