Archive for the 'Cancer' Category



26
Feb
10

feel good, look good, and live forever!

I spent almost all day yesterday listening to the health care reform summit. It triggered some recdollections.

Years ago — was it 15 or 20? — I attended a couple of conferences at Berkeley about managed care, the solution du jour for relentlessly rising health care expenditures. On one panel was Leonard Schaeffer, former president and CEO of WellPoint. (I emphasize “former” to insulate him from the heat the company has taken recently for double-digit premium increases to some customers.) He mentioned that he was often asked at meetings, “What to people want?” with respect to healthcare. His standard reply was: “They want to feel good, to look good, and to live forever.”

He said this only partly in jest. As the CEO of a major payer company he had seen that there was heavy demand by customers to pay not only for treatments alleviating physical ailments but also for treatment to relieve their distress, to make them look more like they thought they should, and to forestall the ravages of age and the ultimate insult, death. The boundaries of the three categories were so ill-defined that it was possible to expand what people wanted reimbursement for indefinitely. This resulted in the administrators dilemma: satisfying the customer’s expectations without utterly exhausting the bank.

Apparently not much has changed. Our expectations for medical relief remain largely unbounded. Perhaps it’s because after WWII we came to expect medical miracles: antibiotics that knocked down infections, vaccines that eliminated polio and communicable diseases, surgery that seemingly made anything possible. I recall watching open heart surgery on fuzzy black and white nationwide TV broadcasts because it was such an astonishing development. After that we sent men to the moon.

When I went to work in the cancer field we had an organizational slogan: “We want to wipe out cancer in your lifetime.” “Wipe out” as in totally eradicate. Seriously! It wasn’t a disingenuous promise; it only reflected the limits of what we knew about the complexity of the disease at the time. People in the cancer field had to let that notion go by the wayside as we began to see that terms like “cure” and “eliminate” were perhaps over-statements when dealing with a disease that stemmed from malfunctions of the most basic biological processes of living things.

The aim of much of the cancer community today is to shift more cancer cases into chronic conditions (as opposed to acute, lethal episodes). Well, that’s progress and perhaps an inevitable step in greater mastery of the disease; but one of the most serious problems we have in health care today is the rising cost of chronic diseases. A study published in Health Affairs a week ago indicated that half of the increase in Medicare spending 1997-2006 was due to increases in prevalence of cases of 10 diseases or to increased cost of treating cases. Cancer isn’t even in the top 5 of the chronic disease list…yet.  One of the biggest surprises of my career was that the financial barriers to state-of-the-art treatment would become a challenge nearly as serious as the intricacy of the disease itself.

We have a difficult time in America discussing pragmatic matters like to cost of protracted care in the same conversation with the good of “saving lives.” Extending life is taken as an unalloyed good. You can become a pariah for mixing the two (i.e., examining comparative effectiveness becomes “death panels” or “pulling the plug on grandma”). I don’t know how many times over the years I’ve listened to well-meaning people advocate efforts requiring a lot of resources with the argument that, “If we can save just one life it will be worth it.” Have I just become too callous when I react: “Uhm…maybe some good can be  done putting the resources elsewhere”? In my entire 40 years in public health I never heard a serious discussion about the unintended or down-side effects of doing whatever it takes to retard illness.

But it’s not a discussion that can be avoided much longer. During the health care debate yesterday everybody seemed to agree on a couple of things: 1) we needed reform for humanitarian reasons, and 2) the continued relentless rise in costs will bankrupt us. One of the Republican senators said something like (I’m paraphrasing), “In a perfect world we’d want everybody to have everything, but we can’t afford this.” I’m a lifelong, unrepentant liberal, but I thought that was a pretty straight statement, one that resonated with me. The truth of  that specific assertion can be argued either way, but it is a matter we have to address. It’s bigger than just the price of the the current health fix. We need to have some frank talk about allocating our less than infinite resources for many benefits that might be achieved. I’m hoping that the baby boomers — of which I’m one — currently heading into the nexus of this issue can bring forth some of the brashness with which we’ve talked about many things in our time (drugs, sex and rock ‘n roll, etc.) and break down the taboo about discussing the realities of life, death, and the price of peanuts.

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18
Feb
10

Using a couple of self-monitoring tools

I’ve mentioned before that I’m experimenting with e-tools to help me stay on track with my health goals. I’m also doing it to be able to comment on the emerging fields of personal health records and m-health (mobile health). Today I’ll be commenting on an iPhone app I use all the time to track my walking — iTreadmill — and a free graphing program I found about yesterday thanks to @accarmichael  — Tableau Public.

iTreadmill is a popular pedometer using the accelerometer in the iPhone. The app allows the recording of pace and time during a walk or run and calculates other measures.

  • Average Pace (pace over entire walk/run)
  • Average Speed
  • Calories burned
  • Distance
  • Pace (current pace, pace over past 30 secs)
  • Speed (current speed)
  • Step Count
  • Strike Rate (step rate, in steps/min)

I think iTreadmill does a good job recording these parameters, at least sufficient for my needs. They claim to have proprietary technology (trademarked PocketStep) that is supposed to enable the device to measure your movements whether your iPhone is in your pocket, clipped to your belt, or held in your hand. The stride parameter can be adjusted to fit with your stride. The app senses when you stop at, say, a stoplight and detects when you’re moving again so the elapsed time adjusts for interruptions. Pretty much everything else is calculated off your number of steps and time.

The data for each occasion can be stored so you can see your history. The latest version allows you to graph distance, steps, calories burned, and time over the past week, 30, 90 or 180 days. You can export the history by emailing the history file to yourself.

That’s a sore point with me. The FAQ says you can get a “well formatted” table from the email by copying it into a spreadsheet. But all the data from each event is just a string of characters with variable spaces between data elements. It isn’t comma-delimited so you can’t easily separate the data into fields for calculations. I tried various search-and-replace strategies to break it into separate fields but gave it up as too time consuming to be worthwhile. I’ve twice sent emails to iTreadmill asking for help with data formatting and suggesting they build in a better export format, but I’ve gotten no reply or results so far. I ended up manually re-keying my data from iTreadmill into OpenOffice spreadsheet: not my idea of how to facilitate better health behavior.

Indeed, I’m wondering if poor responsiveness isn’t pretty standard for the apps business. I’ve gotta think many of the 100,000 apps for the iPhone are done by one or two developers working out of their mom’s basement. I suspect limited support for technology is going to plague the e-health, m-health movement for some time to come.

That takes me to the next tool: Tableau Public. For me an essential quality of supporting my health program is being able to gather data with a minimum of fuss, store it, and manipulate it with ease. However, the overriding characteristic of the app world — as has been the case with IT for decades — is fragmentation and lack of common standards by which data from a variety of sources can be conveniently combined into something satisfactory. My goal is to export data from the apps I use, store it as a database (with or withyout the help of HealthVault or Google Health) and visualize it in a way that tells me how I’m doing. Since I’d manually re-keyed my iTreadmil ldata I was pleased to learn a versatile, sharable program for visualization has become available. I figured it was an omen to begin shareing my data on this blog, limited as it is.

I started only a couple of days ago with Tableau. It’s a poweful tool that’ll take me some time to master. You need to download a free desktop program. With it you open your spreadsheet or database from within Tableau, and it interprets your sheet to do a lot of the work of getting it ready for display. The resulting display files are stored “in the cloud” on Tableau’s servers. But the site sets the graphics up for embedding into various web apps such as blogs. I’ll be gathering more data, and it appears that Tableau may be a platform for integrating data into a coherent story. So, such as it is, here’s my graph for walking in January and February.

The distance walked is up and down, but when I put in the trend line (dashed line) at least it’s up. That’s encouraging!

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11
Feb
10

Health 2.0: four decades of experience

As I’ve posted before, I’m interested in Health 2.0. I say that from the perspective of someone with nearly 40 years of experience in social science and cancer public health. I hope my long-term perspective can add something to the discussion of this interesting trend, especially the recent discussion kicked off by the Susannah Fox and the infamous “Darthmed” concerning the value of Health 2.0.

If you’ll indulge me a little I’d like to step back to when I studied sociology in the late 1960s. The conventional methodology of sociology was survey research. Surveys as a social science tool go back to the 1940s, and many of the field thought we knew enough to reduce prejudice, poverty, crime and other social ills. I was in a PhD program in sociology and fell in with some rennegrade sociologists who were skeptical. They maintained surveys were not a sound basis for verifiable “scientific” sociology. They argued that the data had too many poorly understood variables in linguistics, scales that were not consistent with statistical mathematics, and data gathering interaction effects to claim it was a verifiable body of knowledge. Also efforts to apply sociology wasn’t getting much in the way of results. I ended up dropping out of the degree program because I realized we didn’t know enough about the platform — about consciousness, brain function, semantics, and behavior drivers — to have a solid scientific theory of human behavior.

I went to work in local public health for a couple years and then entered a school of public health to get an MPH in health education. I remember having debates about the ethics of using what some students though was such powerful behavior change technology that we needed to have rules for using it. You’d think we were talking about nuclear energy! I had to laugh and say, “Look, a year after you get out of here you’ll be willing to hit people over the head with a two-by-four to get them to change their health behavior!” I’d already gotten some experience with how difficult “good” change could be to produce.

When I graduated I eventually went to work for a nationwide cancer organization just as the first smoking cessation programs were being developed. Techniques of education and group support were being used to encourage people to give up cigarettes. It seemed simple: give rational people solid infomartion about how bad cigarettes were for them and they’d be motivated to give them up. It turned out not to be so simple. After years of effort and tweaks to programs it became clear that, as an old friend from Mississippi told me, “the juice ain’t worth the squeezin'”. It became clear we weren’t going to solve the smoking problem one person at a time. Because “activism” in the 1960s and ’70s was associated with confrontational marches in the streets protesting the war in Vietnam, most nonprofit organizations wouldn’t touch anything political like “advocacy” as we know it. Finally, however, some militants began to articulate “non-smoker‘s rights”. Before, the social norm was that smokers had a “right” to smoke in public and it was rude to ask them not to. Eventually the first excise tax on cigarettes was passed in California to increase their cost. Jacking up the price began to get behavior change. The social context began to change as well. People began to recognize that smoke hurt not only the smoker but anybody around, and non-smokers had a right to protest. Eventually higher taxes and laws to restrict smoking in public were passed across the country. It took a couple of decades but the social perception of smoking changed from accepting to negative and mass behavior change began to come about. When I look back over about 35 years of smoking wars I’m kind of amazed that there has been as much change. Because it took so long it seemed for years like nothing was happening. The key, at least for smoking, was monetary disencentives and– after perceptions changed — restrictive laws. So what lessons am I suggesting?

  • Individual change is difficult to get, especially if the society doesn’t have attitudes that reinforce the change.
  • You need to work on societal attitudes and even laws that may positively or negativel sanction the problem you’re trying to solve. Billions will be spent by commercial interests to maintain the behavior.
  • It takes a long time to achieve much change because there’s resistance on the individual, group, and economic levels.
  • Giving citizens more power and authority over their health today is part of a long trend. Another quick example: in the1970s the Women’s Health Collective wrote a book called Our Bodies, Ourselves because women were dissatisfied about how male gynecologists were treating them. It was a signature piece of the feminist movement that produced real change. I think “our bodies, ourselves” is a good slogan for all of us. To my mind Health 2.0 is another step in this tradition.
  • Health 2.0 is oriented to a lot of technology. By itself technology will not produce much change, but over time it can become a great platform to facilitate communication and information but only once social perceptions and attitudes change.

The technology of Health 2.0 is still primitive. It’s mainly, as far as I can see, preliminary, disconnected equipment and software. It needs to mature into an integrated system that works seamlessly for people, has supporting institutions at all levels, has just-in-time information at the user’s fingertips, and is premised on a model where the person is in charge, not the doctor-institutions we’ve adopted for the last couple of centuries. Health behavior change has never been easy. There’s nothing new in that situation. Health 2.0 fans need to keep moving ahead as early adopters and enthusiasts. But really visible results are not likelhy to emerge for years. It may take a new generation to see widespread adoption of someting that would be a real paradigm change. You’ve got to have patience and understand that all this will be in constant evolution. Whatever behavior you’re looking for needs to be well interlocked with complementary systems.

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05
Feb
10

Taking the measure of healthcare “elephant in the room”

I called this blog The Vortex because it seems to me we’re in the midst of some really big forces that’ll send us spinning. One of those — here in the US and elsewhere — is demographics. Specifically, the denoument of the Baby Boom generation — of which I am a member — is going to cause perhaps even more turbulence than our advent.

I seldom read George Will’s column in the WashPo because I almost never agree with his perspective on things, but the one he published yesterday brings up the issue of the cost of care of the elderly and its impact in the next couple of decades. I think the situation is of great concern even if I don’t agree with Will’s conclusions about what to do.

The column quotes data about the increase cost of care with age from “Forecasting the cost of US Healthcare” in  the American Enterprise Institute’s newsletter.  The author, Robert Fogel, cites what I think is pretty compelling data about the cost of the end-of-life and, by implication, the possible total cost of the expiration of my generation.

Figure 1

…In this figure, the burden of per capita healthcare costs, which is based on U.S. data, is standardized at 100 for ages 50–54. Figure 1 shows that the financial burden of healthcare per capita rises slowly in the 50s, accelerates in the 60s, accelerates again in the 70s, and accelerates even more rapidly after the mid-80s. The financial per capita burden at age 85 and older is nearly six times as high as the burden at ages 50–54. Notice that the financial burden of healthcare for ages 85 and older is over 75 percent higher per capita than at ages 75–79. However, the physiological prevalence rates (number of conditions per person) is roughly constant at ages 80 and over.

Costs rise, even though the number of conditions (comorbidities) per person remains constant, because the severity of the conditions increases or because the cost of preventing further deterioration (or even partially reversing deterioration) increases with age. It should be kept in mind that standard prevalence rates merely count the number of conditions, neglecting both the increasing physiological deterioration with age and the rising cost of treatment per condition.

Mr. Fogel goes on to discuss various ways the curve could play out over the next couple of decades and ends with what I think is an amazingly optimistic forecast that rising US incomes is going to inspire greater use of biotechnology that results in longer life, fewer chronic conditions and — by some calculus unclear to me — less than devastating total health care cost. In other words, not to worry about the hockey-stick graphs of huge long-term costs, and healthcare is a great business to be in. Read it for yourself and see what conclusion you reach.

This information is cited by George Will as part of a point I think is worth considering. The health care data sets up a contrast between the health care expenditures ahead for the US versus the very large expenditures being made for education in China as a stride toward having by the world’s largest economy by 2040. Will cites another article by Fogel in Foreign Policy titled: “$123,000,000,000,000*” — Fogel’s estimate of the total GDP of China in 2040. That’s a number intended to rock your world that will put China at 40% of world GDP while the US produces only 14%. So China replaces the US as the world’s economic hegemon less than 30 years from now.

The idea doesn’t make me shudder as badly as it would some other poeple, but I think the conundrum identified is valid: how is the US to allocate it’s resources? How much is going to be allocated to health care for us Baby Boomers versus how much is to be allocated to development of the next generations in a highly competitive world? That dilemma faces indivicual families as well. If grandma doesn’t have the money for things not covered by Medicare like long-term-care (which can run thousands of dollars per month), are you doing to wipe out the kids’ college funds?

During the recent health care reform debate calls for evidence-based treatment or comparative effectiveness were greeted by the demagogic  charge of “death panels.” Nevertheless, decisions about resources will be made, even if they’re only the path of least confrontation. This elephant-in-the-room isn’t going away, and it’s big.

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28
Jan
10

White blood cell vs the bacterium

While pursuing a favorite pastime — stumbling in Stumble-Upon — I stumbled across something educational as well as amusing. On a site called Maniac World there is a video posted of a white blood cell chasing a bacterium. I won’t spoil the ending, but, man, that white blood cell is determined!

If you watch it ask yourself at the end: Who were you rooting for, the cell or the little bacterium?

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26
Jan
10

Epigenomics in breast cancer

In my last post I talked about how empigenomics is a hot topic in understanding how genes get expressed in organismic development and how errant development can lead to disease. Well, here’s a specific case where epigenomics plays a role in a common form of cancer: breast cancer.

An article about research on Physorg.com — my favorite science news site — reports how epigenomics plays a role in breast cancer. The interesting thing is that, to understand it, you have to realize that there’s a kind of cellular double-back-flip involved. Let’s see if I can spell this out.

  1. There is a “signaling pathway” called tumor growth factor beta (TGF-beta) that gets over-expressed in some advanced cancers: in this case breast cancer.
  2. TGF-beta sustains the activity of an epigenetic molecule called DNA methyl transferase 1 when a cancerous cell divides and produces offspring cells. The combination of the two factors is key to sustaining the progression of the cancer because they block the expression of genes that have been turned off in the process of turning normal cells into cancer cells. In this case the “epigenetic environment” is essential to enabling the cancer promoting process to be passed on to new cancer cells.
  3. But if the TGFR-beta can be blocked it causes the methyl transferase — the epigenetic factor — to fade away. With the epigenetic factor reduced the offspring cells re-expresses normal genetics and retard the cancer characteristics.

In my last post on epigenetics I mentioned that epigenetics is ordinarily thought of as passing temporarily acquired factors from one generation of an organism to the next. But epigenetics happens also at the level of cell generations, and acquired, abnormal cancer characteristics need to be passed from one generation to the next for cancer cells to stay cancer cells through several generations as tumors grow.

So there you have it: epigenetics at work in cancer. But all this blocking and unblocking in order for cancer to be sustained opens up the possibility it can be disrupted by a drug and stop the disease.

25
Jan
10

Epigenetics: even Dr Oz is talking about it

A couple of days ago as I waited in line to buy a few groceries the cover of  Time Magazine among the tabloids caught my eye. The cover article was titled, “Why Your DNA Isn’t Your Destiny.” It turns out the article is about epigenetics, another one of the processes that produce options and variations in genetic impact. (A few days ago I mentioned RNA editing and how it affects gene expression.)

For a long time life scientists have debated whether some diseases or behaviors are a matter of “nature” or “nurture.” And if diseases — like various cancers — have a component of nurture (environmentally affected) how does that happen? Epigenetics is a kit of processes that modify how genes are expressed without permanently modifying the DNA that’s passed down generation after generation. Epigenetics is sort of the go-between of the nature v s. nurture conundrum. It’s another way genetics gets variability and complexity.

The odd thing about epigenetics is that things in the environment such as drugs or chemicals can change the chemical environment of DNA inside the nucleus of cells causing additional molecules (called methylation) to attach themselves to the DNA and change its expression. The result is cell characteristics that are different from unaffected genetic expression. Also these modifiers can be passed from parent to offspring, but they don’t change the DNA. The Time article says:

Can epigenetic changes be permanent? Possibly, but it’s important to remember that epigenetics isn’t evolution. It doesn’t change DNA. Epigenetic changes represent a biological response to an environmental stressor. That response can be inherited through many generations via epigenetic marks, but if you remove the environmental pressure, the epigenetic marks will eventually fade, and the DNA code will — over time — begin to revert to its original programming. That’s the current thinking, anyway: that only natural selection causes permanent genetic change.

Once again we find that the rather simplistic ideas that scientists had a few years ago about how genes turn into organisms needs to be further explored in light of this rather subtle process. All of these complicating factor might ultimately lead to disease solutions, but it’s going to take some time.

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22
Jan
10

What’s with the perverse link ‘tween cancer and brain disease?

Two weeks ago I posted a somewhat facetious piece about an epidemiological study that found lower risk of cancer in people diagnosed with Alzheimer’s disease and, inversely, lower risk of Alzheimer’s in those with cancer. That’s not just converse but perverse as well.

Now The Feinstein Institute for Medical Research reports that Katherine Burdick, PhD, looked at the relation between the proto-oncogene (a gene that, when mutated, can contribute to cancer) MET and schizophrenia. There are family data that suggest that having a higher risk for schizophrenia lowers a person’s risk of cancer.

Serious mental illness or debility is a lousy trade-off against cancer. But these are not choices you make; they’re biological outcomes that have a rather extraordinary association. The big issue here is that gene and biologic functions have effects that bridge what appear to be very different roles: brain function and cancer. There are clues.

“The results add to the growing evidence suggesting an intriguing relationship between cancer-related genes and schizophrenia susceptibility,” the scientists wrote.

It remains unclear exactly how the gene actually may increase the risk for schizophrenia while protecting against some forms of cancer. However, evidence from research on MET in autism provides some insight. Specifically, it is known that MET is activated (increased activity) when tumors develop and can increase the chance that cancer cells multiply and infiltrate other tissue.

The activation of MET during normal neurodevelopment is critical to ensure that neurons grow and migrate to position themselves correctly in the human cortex. In autism, it appears that while the brain is developing, reduced MET activity results in structural and functional changes in the brain that may increase a person’s risk for developing the disorder. The Feinstein investigators speculate that the same risk-inducing mechanism may be at play in its link to schizophrenia.

21
Jan
10

Turning the corner in nanotechnology

One of the things I like to write about is nanotechnology because — to put it directly — I think it’s going to be the technology that revolutionizes the 21st Century. To suggest it will be the next “industrial revolution” hardly covers it.

Back in 2000 when everybody was prognosticating about the next century I attended a conference put on by The Foresight Institute, an organization that has been pushing nanotechnology since the ’80s. They had a group of venture capitalists who were perhaps the first to invest anything in nanotech talking with an audience of geek enthusiasts and engineers from the Silicon Valley. The VCs were actually very reserved in their forecasts. Perhaps they were just trying to keep the audience from deluging them with proposals for the first billion-dollar nanotech start-up. They cautioned that VCs wanted things that were likely to start returning their investment in five or, at most, ten years. Investment capital is seldom very patient.

One of the really enormous ideas in the field is that nanotechnology will be able to make never-before-seen structures built with atoms placed precisely where they’re wanted. In other words, nano-manufacturing needs some sort of assembler that works in a robotical fashion diligently turning out one nano-widget after another. Imagine something like an auto assembly line where arms reach out to place parts and welds through the endless repetition of robot programs — except on a scale of billions of a meter. To make things that have significance in our macro-world billions and trillions of nano-devices will be needed.

In a recent post to h+— an e-zine that loves far-out, futuristic stuff — there’s a post about recent developments for assemblers.

In a 2009 article in Nature Nanotechnology, Dr. [Nadrian] Seeman shared the results of experiments performed by his lab, along with collaborators at Nanjing University in China, in which scientists built a two-armed nanorobotic device with the ability to place specific atoms and molecules where scientists want them. The device was approximately 150 x 50 x 8 nanometers in size — over a million could fit in a single red blood cell. Using robust error-correction mechanisms, the device can place DNA molecules with 100% accuracy. Earlier trials had yielded only 60-80% accuracy.

What Dr. Seeman is using is DNA origami and structural features of DNA that are used in genetic recombination. Once again — as I described in an earlier post about nano-manufacturing — we are taking lessons from nature’s own original nano-assembler: DNA.

13
Jan
10

Fireball gene machines

One of the themes of this blog — the ups and downs of the genetics revolution — just keeps on giving. Despite some skepticism about the efficacy of genetic research in finding solid diesease treatments, the likelihood of an avalanche of genetic data from sequencing seems inevitable. That trend is propelled by the furious competition of the last few years to build cheap, fast gene sequencers. The product development anticipates ubiquitous use of such information in biomedical research and in personalizing medical regimes. Two instances cropped up just this week:

  1. Illumina unveiled at this week’s JP Morgan investment conference an upgraded, updated version of its gene sequencing machine: the HiSeq2000 (in case you’re in the market). This $690,000 baby might even be tuned over the next year to bring the cost of sequencing a human genome to $2,500. Well, that’s enough for the Beijing Genomics Institute. They’re in for 128 of them! Geneticist Elaine Mardis, at Washington University in St. Louis says: “This really provides a platform that is going to propel studies of complex diseases like cancer and autism.”
  2. And, according to David Ewing Duncan on his FB page, in a stroke of one-upsmanship, Complete Genomics today promised a sequencing platform that will deliver the whole genome sequence for a mere $1,500. Remember, the so-called holy grail for human genomic sequencing is $1,000.

As Dr. Mardis suggests the availability of sequencers that can do the job so cheaply (ergo quickly) is going to shovel the coal to the fast-moving steam engine of genetics research. Skeptics would argue more data does not necessarily mean more useful results. I guess geneticists are adopting the attitude of the child in that old joke that has the punchline: “There’s got to be a pony in here somewhere.”




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