Friday, March 29, 2024

Bill Catterall (1946–2024)

William Catterall, known as “the father of ion channels,” died on February 28 at the age of 77. Russ Hobbie and I cite Catterall’s article on the structure of sodium ion channels in Chapter 9 of Intermediate Physics for Medicine and Biology.
Payandeh J, Scheuer T, Zheng N, Catterall WA (2011) The crystal structure of a voltage-gated sodium channel. Nature 475:353–358.
Catterall worked in the intramural program at the National Institutes of Health in the laboratory of Marshall Nirenberg. He then moved to the University of Washington, where he was a professor of Pharmacology for over 40 years. There he was a collaborator with Bertil Hille, the author of the landmark textbook Ion Channels of Excitable Membranes. An obituary published by the University of Washington website states
First and foremost, Bill was an exceptional scientist. He pioneered the biochemical investigation of calcium and sodium ion channels; molecular portals that allow the controlled passage of ions across cell membranes. The proper passage of ions into the cell is essential for healthy brain, heart, and muscle function. Early work from Catterall elucidated the molecular basis of ion channel gating whereas later studies with UW Pharmacology colleague Dr. Ning Zheng revealed details of how these clinically relevant macromolecular machines operate at the atomic level. With this latter information, Catterall was able to ascertain how a variety of toxins as well as local anesthetics and antiarrhythmic drugs act to “lock the gate” on these ion channels. Bill was recognized for these pivotal discoveries by election to the National Academy of Sciences USA and the Royal Society London. He also received prestigious awards including the Gairdner Award from Canada, the Robert R. Ruffolo Career Achievement Award in Pharmacology from the American Society of Pharmacology and Therapeutics, and a Lifetime Achievement Award from the International Union of Pharmacologists.

To learn more, listen to Catterall discuss his work in a three-part series of lectures for iBiology

William Catterall (U. Washington) Part 1: Electrical Signaling: Life in the Fast Lane  

https://www.youtube.com/watch?v=QnQQkWxAKwI

 


William Catterall (U. Washington) Part 2: Voltage-gated Na+ Channels at Atomic Resolution

 https://www.youtube.com/watch?v=hfXGsJCOC9A

 


William Catterall (U. Washington) Part 3: Voltage-gated Calcium Channels


Friday, March 22, 2024

Happy Birthday, Erwin Neher!

German biophysicist Erwin Neher turned 80 last week. Neher and Bert Sakmann received the 1991 Nobel Prize in Physiology or Medicine for their development of patch clamping: a method to record the current through individual ion channels. Russ Hobbie and I discuss Neher and Sakmann’s work in Chapter 9 of Intermediate Physics for Medicine and Biology.

I will turn over the rest of this post to Neher. In the two-minute video below, he offers advice to young scientists.

 

Erwin Neher's Advice to Young People: From a Nobel Prize Winner 

https://www.youtube.com/watch?v=vB3MNPuMFCI

 

In a ten-minute video, listen to Erwin Neher discuss advances in modern medicine.



Erwin Neher, Nobel Laureate for Medicine | Journal Interview 

https://www.youtube.com/watch?v=Rm3gHuxouZo



Finally, in this longer lecture, Neher describes the development of patch clamping. 



Lecture by Erwin Neher at the University of Hyderabad. The talk begins at approximately minute 18, after a rather long introduction.

https://www.youtube.com/watch?v=okB2coPEJJk




Happy Birthday, Erwin Neher!

Friday, March 15, 2024

A New Version of Figure 10.13 in the Sixth Edition of IPMB

Gene Surdotovich and I are hard at work preparing the 6th edition of Intermediate Physics for Medicine and Biology. One change compared to the 5th edition is that we are redrawing most of the figures using Mathematica. It’s a lot of work, but the revised figures look great and many are in color.

One advantage of redrawing the figures is that it forces us to rethink what the figure is all about and if it makes sense. This brings me to Figure 10.13 in the chapter about feedback. Specifically, it is from Section 10.6 about a negative feedback loop with two time constants. Without going into detail, let me outline what this figure is describing.

Chapter 10 centers around one particular feedback loop, relating the amount of carbon dioxide in your lungs (which we call x) to your breathing rate (y). The faster you breath, the more CO2 you blow out of your lungs, so an increase in y causes a decrease in x. But your body detects when CO2 is building up and reacts by increasing your breathing rate, so an increase in x causes an increase in y. There is one additional parameter, your metabolic rate, p. If your metabolic rate increases, so does the amount of CO2 in your lungs.

Our book emphasizes mathematical modeling, so we develop a toy model of how x and y behave. We assume that initially x and y are in steady state for some p, and call these values x0y0, and p0. At time t = 0, p increases from  p0 to p0 + Δp, which could represent you starting to exercise. How do x and y change with time? We define two new variables, ξ and η, that represent the deviation of x and y from their steady state values, so x = x0 + ξ and y = y0 + η. We then develop two differential equations for ξ and η,


The variables ξ and η have different time constants, τ1 and τ2. The parameters G1 and G2 are the “gains” of the system, determining how much ξ changes in response to η, and how much η changes in response to ξ. In our model, G1 is negative (an increase in breathing rate causes the amount of CO2 in the lungs to decrease) and G2 is positive (an increase in CO2 causes the rate of breathing to increase). The “open loop gain” of the feedback loop is the product G1G2. Finally, the constant a is simply a factor to get the units right.

All is good so far. But now let’s look at the 5th edition’s version of Fig. 10.13. 

Fig. 10.13 from the 5th edition of Intermediate Physics for Medicine and Biology.

What’s wrong with it? First, the calculation uses a positive value of G1 and a negative value of G2, so it doesn’t correspond correctly to our model, which has negative G1 and positive G2. Second, the calculation uses Δp = 0, so the steady state values of x and y don’t change and ξ and η both approach zero. That’s odd. I thought the whole point of the model was to look at how the system responds to changes in p. Finally, the initial values of ξ and η are not zero. What’s up with that? We know their values are zero for t < 0, when x = x0 and yy0. How could they suddenly change at t = 0?

In the 6th edition, the new version of Figure 10.13 is going to look something like this: 

Fig. 10.13 for the 6th edition of Intermediate Physics for Medicine and Biology.

The figure has color and switches from landscape to portrait orientation. Those changes are trivial. Here are the important differences:

  1. I made G1 negative and G2 positive, like in our breathing model. Now an increase in CO2 causes the body to increase the breathing rate, rather than decrease it as in the 5th edition figure.
  2. The parameter Δp is no longer zero. To be simple, I set aΔp = 1. The person starts exercising at t = 0.
  3. Because there is a change in metabolic rate, the new steady state values of ξ and η are not zero. In fact, they are equal to ξaΔp/(1-G1G2) and ηG2aΔp/(1-G1G2). Notice how the factor of 1-G1G2 plays a big role. Since the product G1G2 is negative, this means that 1-G1G2 is a positive number greater than one. It’s in the denominator, so it makes ξ smaller. That’s the whole point. The feedback loop is designed to keep ξ from changing much. It’s a control system to suppress changes in ξ. To make life simple, I set G1 = −5 and G2 = 5 (the same values from the 5th edition except for the signs), so the open loop gain is 25 and the steady state value of ξ is only 1/26 of what it would be if no feedback were present (in which case, ξ would rise monotonically to one while η would remain zero).
  4. The initial values of ξ and η are now zero, so there is no instantaneous jump of these variables at t = 0.

When revising the 5th edition of IPMB, I began wondering why Russ Hobbie and I never worried about the units for the time constants, the gains, a, or Δp. This motivated me to write a new homework problem for the 6th edition, in which the student is asked to rewrite the model equations in nondimensional variables Ξ, Η, and T instead of ξ, η, and t. Interestingly, such a switch results in a pair of differential equations for Ξ and Η that depend on only two nondimensional parameters: the ratio of time constants and the open loop gain. So, our plot in the 5th edition has the qualitative behavior correct (except for the signs of G1 and G2). The system oscillates because the open loop gain is so high. The correct units for the various parameters would only rescale the horizontal and vertical axes. 

Is the new version of Figure 10.13 in this blog post what you’ll see in the 6th edition of IPMB? I don’t know. I haven’t passed the figure by Gene yet, and he’s my Mathematica guru. He might make it even better.

What’s the moral of this story? THINK BEFORE YOU CALCULATE! That’s the motto I often would tell my students, but it applies just as well to textbook authors. The plot should not only be correct but also make physical sense. You should be able to explain what’s happening in words as well as pictures. If you can’t tell the story of what’s taking place by looking at the figure, something’s wrong.

Finally, is there really no physical problem that the original version of Fig. 10.13 describes? Actually, there is. Imagine you are resting throughout this “event”; you sit in your chair and don’t change your metabolic rate, so Δp = 0 meaning p is the same before and after t = 0. However, at time t = 0, your “friend” sneaks up on you, shoves a fire extinguisher in front of your face, and gives you a quick, powerful blast of CO2. Except for the sign issue on G1 and G2, the original figure shows how your body would respond.

Friday, March 8, 2024

Stirling's Approximation

I've always been fascinated by Stirling’s approximation,

ln(n!) = n ln(n) − n,

where n! is the factorial. Russ Hobbie and I mention Stirling’s approximation in Appendix I of Intermediate Physics for Medicine and Biology. In the homework problems for that appendix (yes, IPMB does has homework problems in its appendices), a more accurate version of Stirling’s approximation is given as

ln(n!) = n ln(n) − n + ½ ln(2π n) .

There is one thing that’s always bothered me about Stirling’s approximation: it’s for the logarithm of the factorial, not the factorial itself. So today, I’ll derive an approximation for the factorial. 

The first step is easy; just apply the exponential function to the entire expression. Because the exponential is the inverse of the natural logarithm, you get

n! = en ln(n) − n + ½ ln(2π n)

Now, we just use some properties of exponents

n! = en ln(n) en e½ln(2π n)

n! = (eln(n))n e−n √(eln(2π n))

n! = nn en √(2π n

And there we have it. It’s a strange formula, with a really huge factor (nn) multiplied by a tiny factor (en) times a plain old modestly sized factor (√(2π n)). It contains both e = 2.7183 and π = 3.1416.

Let's see how it works.

n n! nn e−n √(2π n)   fractional error (%)
1 1 0.92214 7.8
2 2 1.9190 4.1
5 120 118.02 1.7
10 3.6288 × 106 3.5987 × 106 0.83
20 2.4329 × 1018 2.4228 × 1018 0.42
50 3.0414 × 1064 3.0363 × 1064 0.17
100   9.3326 × 10157   9.3249 × 10157 0.083

For the last entry (n = 100), my calculator couldn’t calculate 100100 or 100!. To get the first one I wrote

100100 = (102)100 = 102 × 100 = 10200.

The calculator was able to compute e−100 = 3.7201 × 10−44, and of course the square root of 200π was not a problem. To obtain the actual value of 100!, I just asked Google.

Why in the world does anyone need a way to calculate such big factorials? Russ and I use them in Chapter 3 about statistical dynamics. There you have to count the number of states, which often requires using factorials. The beauty of statistical mechanics is that you usually apply it to macroscopic systems with a large number of particles. And by large, I mean something like Avogadro’s number of particles (6 × 1023). The interesting thing is that in statistical mechanics you often need not the factorial, but the logarithm of the factorial, so Stirling's approximation is exactly what you want. But it’s good to know that you can also approximate the factorial itself. 

Finally, one last fact from Mr. Google. 1,000,000! = 8.2639 × 105,565,708. Wow!


Stirling’s Approximation

https://www.youtube.com/watch?v=IJ5N28-Ujno


Friday, March 1, 2024

A Text-Book on Medical Physics

Intermediate Physics for Medicine and Biology provides, for the first time, a textbook about the role that physics plays in medicine.

Well… no.

I recently found a textbook that preceded IPMB by over a century. Below is its preface.
The fact that a knowledge of Physics is indispensable to a thorough understanding of Medicine has not yet been as fully realized in this country as in Europe, where the admirable works of Desplats and Gariel, of Robertson, and of numerous German writers, constitute a branch of educational literature to which we can show no parallel. A full appreciation of this, the author trusts, will be sufficient justification for placing in book form the substance of his lectures on this department of science, delivered during many years at the University of the City of New York.

Broadly speaking, this work aims to impart a knowledge of the relations existing between Physics and Medicine in their latest state of development, and to embody in the pursuit of this object whatever experience the author has gained during a long period of teaching this special branch of applied science. In certain cases topics not strictly embraced in the title have been included in the text—for example, the directions for section-cutting and staining; and in other instances exceptionally full descriptions of apparatus have been given, notably of the microscope; but in view of the importance of these subjects, the course pursued will doubtless be approved. Attention may be called to the paragraph headings and italicized words, which suggest a system of questions facilitating a review of the text.

In conclusion, the author will feel that his labor has not been in vain if the work should serve to call deserved attention to a subject hitherto slighted in the curriculum of medical education.
Readers of IPMB might be interested in a brief table of contents for this earlier book.
I. Matter
      1. Properties of matter
      2. Solid matter
      3. Liquid matter
      4. Gaseous matter
      5. Ultragaseous and radiant matter
II. Energy

               1. Potential energy 

               2. Kinetic energy 

               3. Machines and instruments 

               4. Translatory molecular motion 

               5. Acoustics 

               6. Optics 

               7. Heat 

               8. Electricity 

               9. Dynamic electricity 

             10. Magnetism 

             11. Electrobiology

Many of these topics are familiar to readers of IPMB. Yet, the list and the language seem quaint and just a little old-fashioned.
A Text-Book on Medical Physics,
by John C. Draper.

This should not be surprising. The book was titled A Text-Book on Medical Physics, written by John C. Draper, and published in 1885. Russ Hobbie and I are following a long tradition of applying physics to medicine and biology. In nearly 140 years much has changed, but also much has stayed the same. The last sentence of the preface could serve as our call to arms, and the subtitle of Draper’s book could be our own: “For the Use of Students and Practitioners of Medicine.” 

Below I post the definition of medical physics in the Text-Book. I love it. Draper should have written a blog!