Sunday, September 19, 2021

Self Test - Part II: the effect of ezetimibe on visceral fat

 

This post focuses on the power of smoothing, which is a process that picks out trends from noisy data.  We'll see that using a low-cost bathroom scale that has a visceral fat reading, we can see an observable effect that is correlated with the start of taking Ezetimibe, a cholesterol-reducing medication. 

My Yunmai bathroom scale provides a measure of visceral fat, that greasy stuff that lines our organs.  Higher percentages of it in our body increases risks of all sorts of diseases, so visceral fat is a good quantity to track and try to minimize.  The best way to reduce its percentage is to exercise to turn fat to muscle and to lose weight.

My scale has four electrodes, which are arranged in two pairs.  The left and right pair measure the resistance of the soles of each foot.  The resistance from one foot to the other measures the resistance of your body.  Combined with your weight and height, a formula is used to estimate the visceral fat.

I talked to an engineer at Cal Tech whose research was in the general area of biometrics, and she told me that such resistance measurements are related to the visceral fat, but they are not so accurate.  Furthermore, scales such as mine are biased towards the lower part of the body while those that use electrodes that you grasp in your hands is biased to the upper body.  So, corrections need to be made.

The bottom line is that I do not trust the absolute measurement but changes in the reading has some meaning provided that the scale is sensitive enough to detect the changes.  In my case, my reading ranges from 5 % to 9% percent as whole numbers.  The black points in the figure above show the visceral fat percentage as a function of date.  These points form horizontal lines at the whole numbers and alone give us very little useful information.

However, readings fluctuate between 8% and 9% at early times then between 7% and 8% and so on, implying that the visceral fat is falling with time.  Smoothing is the process of averaging adjacent points.  The red points show 50-point smoothing, where 25 consecutive points to the left of the data point and 25 to the right are averaged and plotted at the middle point of the range.  As a result, we get values between the whole numbers.  Suppose that my visceral fat is at 6.8%.  Then, the scale would read 7.0% more often that 6.0%, so the 50-point average would yield something around 6.8%.  Smoothing also eliminates day to day fluctuations that might hide the long terms trends.

The blue line shows 200-point smoothing, corresponding to over a half-year smoothing window.  This eliminates all but the most long-term trends.  The light blue vertical line in mid-2018 shows the date on which I started to take Ezetimibe, a medication that reduces cholesterol.  In my last post, I described how I used smoothing and a fit to a saturated exponential that found that my weight increased by 3 pounds after I started taking Ezetimibe.  The visceral fat data correlates with the observed weight gain.

To summarize the graph, smoothing shows my visceral fat falling from late 2016 and leveling off in early 2018 while I was on my high-fat diet.  This correlates with my weight loss.  Then, after taking Ezetimibe, my visceral fat started a long-term climb from 6% to about 6.5%.  Smoothing has allowed me to determine this rise to a precision that exceeds the whole numbers provided by the scale.

Finally, there is a dip in the 50-point smoothed curve that falls below 6%.  There is also one reading of 5% as seen by the black point.  The date corresponds to one week after my radical prostatectomy surgery and correlates with my initial weight loss then weight gain after the surgery.  Interestingly, the 200-point smoothed curve shows two plateaus – the first after starting the Ezetimibe and the second one after my prostate surgery.

As I have stressed in my past posts, this is a single experiment with potentially many confounding factors, so we cannot conclude that Ezetimibe increases visceral fat.  However, the result provides a hypothesis that could be tested with a larger number of participants.  Putting it all together, Ezetimibe drastically reduced my serum cholesterol (a huge effect that is consistent with controlled experiments) and is correlated with a small weight gain.  This added data shows that it might add to visceral fat.  This brings up the point that medications have complex effects on the body.  They work as intended to treat one condition, but the side effects might oppose some of the benefits.  In this case, the drop in cholesterol is far greater than the potentially ill effects of a small gain in visceral fat.

If there are others out there like me, pooling our data together could increase the confidence that the correlation is not a mere coincidence.  So give it a try!

Sunday, August 15, 2021

Self Testing - Part I

 Those of you who know me will not be surprised that I love data.  Even noisy data can bring a picture into focus if there is enough of it.  I collect data on all sorts of things but find biometrics fun because it’s easy to collect and it can potentially give useful insights.

A couple of previous posts alluded to some obvious trends that I have observed.  To all those people who mocked me decades ago for starting a low carb diet, contrary to their predictions that I would gain weight, I shed 50 pounds by eating mostly fat with a bit of protein and as few carbs as possible.  In the process, my cholesterol also dropped to healthy levels (see http://unknownphysicist.blogspot.com/2011/10/eating-lots-of-fat-to-lose-weight.html).  I kept my weight down for a decade.

After a trip to Belgium and then to Italy, I adopted a Mediterranean diet, which was a gateway to me eating lots of carbs again, which produced an upward spiral in my weight.  Then in 2012, when I had almost regained all the weight that I had lost, I went on a strict low carb diet for a second time.  Again, it worked, but over the last two years, I have struggled with a small weight gain, whose source I have tried to identify using my vast stores of data.

In the interim, PSA (prostate specific antigen) data that I had been tracking took off, as I described in my post describing my ordeal with prostate cancer. (see http://unknownphysicist.blogspot.com/2021/01/can-major-surgery-cure-depression.html and http://unknownphysicist.blogspot.com/2020/06/i-was-relieved-i-had-cancer.html)

The graph below shows my weight as a function of time.  There are a series of drops each followed by a plateau.  Also plotted are my measurements of total cholesterol and LDL cholesterol along with error bars that reflect the accuracy of my instrument.  LDL is the bad cholesterol.  My triglycerides were always very low, so I was not so concerned about my cholesterol while it slowly fell over 4 years (1500 days).  Then, for no apparent reason, my cholesterol shot up even as I was losing more weight.


  

Both my doctor and I got concerned with the rise, so he prescribed the highest dose of atorvastatin – which scrubs serum cholesterol.  My cholesterol remained high for months while taking it, so he sent me to a cardiologist, who suggested I add ezetimibe, which prevents cholesterol from being absorbed through the intestines.  I was reluctant to take ezetimibe because I had had a bad experience with Vytorin, which combines atorvastatin with ezetimibe.  I hadn’t realized how much energy Vytorin was sopping away (and resulting in weight gain) until I accidentally stopped taking it for a week.  I then regained my usual vigor.  That’s when I stopped Vytorin and went back to my strict diet.

My cardiologist suggested that I take an ultralow dose of Ezetimibe, which I did at the time shown by the vertical gray line in the plot.  Indeed, it drastically decreased my serum cholesterol, as you can see in the plots, and I retained my energy levels within my ability to notice.  And my weight appeared to remain stable, as shown within the gray dashed box.

The plot below shows a magnified view of my weight after starting to take Ezetimibe.  The raw data (points) is quite noisy and can vary by as much as 6 pounds over a few days.  That variation is real.  There are days when I exercise vigorously and might also dehydrate, so I could easily lose a few pounds, which I regain when hydrating and remaining sedentary for a few days.



The raw weight data does not appear to show any trends.  However, a plot of 50 (dark curve) and 100 point smoothed data (gray curve) shows a different story.  My weight appears to be increasing and it also fluctuates over time.  The fluctuations might also be real due to seasonal variations in my diet and activity.  The gray vertical dashed line falls on the date that I started taking Ezetimibe and the pink dashed line when I had prostate surgery.  Each seems to have been responsible for some weight gain.

Next I fit the raw data to saturated exponentials starting at the time I began my Ezetimibe regimen (light blue curve) and then after prostate surgery (magenta curve).   The fit shows that the Ezetimibe resulted in almost a 3 pound weight gain (when averaged over a couple months).  This is consistent with the fact that I observed a huge weight increase when I was taking a larger dose.  I gained a little less than two pounds after my radical prostatectomy.  Though minor, I have noticed a little edema around the incision area, so this increase is also explainable.

The skeptic might complain that the pink curve start lower than the flat part of the blue curve.  A closer examination of the data right after my surgery shows that my weight dropped by 5 pounds from the previous baseline for a week right after surgery, so that biases the early parts of the fit.  However, all of the fits and the smoothed data nicely follow each other aside from seasonal variations.

I would not conclude form my data that ezetimibe results in weight gain nor that prostate surgery does so too.  However, the data is suggestive that this might be the case and my data is consistent with secondary observations.  I find it amazing how such small effects can be drawn from the data and gives a small level of confidence that it might be true.

In the meantime, I continue to take and analyze the data to see if any other correlations emerge that might signal an interesting underlying cause.  Apologies for typos and the like, but my Fitbit just informed me that I missed my 250 step goal this hour while writing.  So I have to get up and walk...

Saturday, February 20, 2021

Facts should inform opinion

Opinions are open to debate, but scientific facts emerge from the scientific method after extensive debate between highly trained scientists.  Facebook posts, YouTube videos and editorials claiming the inefficacy of masks in mitigating virus transmission, denying anthropomorphic climate change, blaming vaccines for autism, and purporting adverse health effects of 5G rely on cherry-picked data to confirm biases, give credence to ideologues who are delusional or falsely claim expertise, advance conspiracy theories, and apply willful ignorance to credible evidence.

Reliable sources are non-partisan non-ideological experts in their fields who take pleasure in learning the truth and who publicly change their minds in light of new evidence.  Many career government employees fit the criteria, such as Dr. Fauci, who can be trusted to translate complex science to the public.  Serious journalists and geeky fact checkers, who carefully qualify their statements, can be found working for the major news outlets.  Facebook and Youtube, on the other hand, are populated with quacks, nutjobs and ideologues who spew nonsense that should be ignored.  Media outlets that provide only one political viewpoint are also untrustworthy.

In other words, Fox News argued that everyone knows that Tucker Carlson is not purporting to be reporting facts and his viewers know it.

Nightly programs on Fox News are unreliable.  As reported in the New York Times, a libel case against Fox was dismissed because: In reaching her decision (see tinyurl.com/Y55ecbvq), Judge Vyskocil relied in part on an argument made by Fox News lawyers that the “general tenor” of Mr. Carlson’s program signals to viewers that the host is “engaging in ‘exaggeration’ and ‘nonliteral commentary.’” The judge added: “Given Mr. Carlson’s reputation, any reasonable viewer ‘arrive[s] with an appropriate amount of skepticism’” about the host’s on-air comments.  In other words, Fox News argued that everyone knows that Tucker Carlson is not purporting to be reporting facts and his viewers know it.  Based on what I have read on these pages, many of you believe these programs and some act on the disinformation, like those who believe the lie that the presidential election was stolen and stormed the Capitol.

Turn to Scientific American magazine for trustworthy coverage of science and technology.  The authors are top scientists and journalists who are specialists in science and writing, and all articles are vetted for accuracy.   Errors in print that later come to light are promptly corrected, and a letters section offers informed exchanges.

Scientific American has published articles on COVID that show the physical structure of the virus, describe how scientific detective work found a bat cave in China where SARS-CoV-2 most likely originated, explain how the disease is transmitted, provide an appreciation for how researchers have learned its impact on the immune response through vast studies of samples collected from critically ill patients, etc.  Compare these nuanced narratives to those who arrogantly dismiss COVID as a hoax.
An article in the January 2021 issue of Scientific American describes how the number of COVID deaths determined from death certificates can be checked against excess deaths over the incredibly constant background death rate.  375,000 excess deaths were reported over the period from the first US COVID death through mid-November 2020 when US death certificates showed 250,000 lost lives due to COVID.  Researchers explain that these additional deaths are attributable to unreported COVID deaths and to preventable deaths from other causes that were untreated or under-treated because of stresses to medical resources during the pandemic.  So directly or indirectly, COVID has resulted in more deaths than reported.  If not COVID, what is the cause of these deaths?

So directly or indirectly, COVID has resulted in more deaths than reported.  If not COVID, what is the cause of these deaths?

Rather than debating the efficacy of masks – it’s been established that they reduce the spread, let’s debate our opinions on acceptable death rates.  Are some lives more valuable than others?  Let’s argue for appropriate levels of research funding.  The fast development of COVID vaccines relied on decades of research funded by the agencies that Trump consistently wanted to cut.  Let’s recognize the complexity of the world.  The choice is not between fighting COVID and saving the economy; the two are intertwined.  Let’s debate the right balance needed to attain the desired outcome and not allow ideology to stand in the way.  Let’s debate how much we should spend now compared with investing in the future to empower our children to deal with their challenges of climate change and future pandemics as our parents invested in us.  Let’s preserve our democracy by making the effort to learn the truth and base policies on facts, not lies.  Let’s accept Biden’s legitimate victory and move forward together.  And let's not fight over the facts, but instead, we would expend our energies on debating how best to implement solutions to the serious existential problems that are just around the corner.

Monday, January 11, 2021

Can Major Surgery Cure Depression?

The holidays are a good time to look back on our lives.  On this past Christmas eve, I was reading an article in the American Journal of Physics (AJP) on the topic of energy spectra for power-law potentials.  What a great coincidence that I had done this same calculation exactly a decade back, as I was reminded by a blog post from that time (see 2010 post).  I had not mentioned the details of the calculation in that post but was instead writing about how my wife Pat allowed me to isolate myself to work on this fun calculation while she and the rest of my family were preparing for our Ukrainian dinner.

At age 94, that would be my father’s last solo trip to Pullman, something I had expected at the time based on his cognitive decline.  Both our children were home for the holidays, waiting for the first visible star to appear, which would signal the time for our twelve-course Christmas Eve meal to begin -- a Ukrainian tradition that had been passed down through countless generations.

All morning, my father hovered over Pat in the kitchen to make sure that the cabbage was properly steamed, enough onions were sautéed for the butter topping and that the borsch had lots of garlic.  All the burners were on and the windows were painted in condensate that was crisscrossed by several rivulets that ended in miniature puddles on the windowsill.  Ukrainian Choral Christmas music blared over the speakers, drowning out the cooking sounds.  My father sang along with his rich operatic voice, with hands clasped behind him as he monitored the kitchen.  Our children were contacting old friends to plan for their yearly rendezvous at Ricos.  I was content in my calculations and secure in the presence of family.

My past posts consistently show the centrality of family and physics in my life.  Our families have grown -- both of our children with spouses and children of their own -- but I am now the father and the grandfather, taking the role of the patriarch.  My father briefly saw his first great grandchild (by Skype) just before he died in 2014.  Hopefully, I will see my own great grandchildren some day.

2020 was a year of illness and isolation.  I started the year by learning that I had prostate cancer.  My surgery coincided with the peak of COVID deaths in April (see link to the details).  It went well and the experience was a blip in the grand scheme of my life.  I kept busy writing papers (a couple which were accepted for publication in AJP and a massive review article that was accepted in the prestigious Advances in Optics and Photonics) and pondering new ideas, so my mind rarely wandered into the minefield of anxiety about my health.

PSA Data

My prostate surgery had other benefits.  I had been suffering with an undercurrent of depression since the passing of my father in December of 2014.  Though I had many reasons to be joyful since then, a deep-seeded darkness tugged at me, preventing me from feeling the unfettered happiness that was warranted by major events in my life.  This darkness lifted when I awoke from prostate surgery.  The experience reminded me of my mother’s depression years before she was diagnosed with cervical cancer.  Could it be that the human body signals the brain during a serious illness before other symptoms arise?  To investigate the plausibility of this hypothesis, I studied a plot of my Prostate Specific Antigen (PSA) test over time (see figure to the right).  Being measured as part of my yearly physical blood draw, my PSA data spans two decades.  In my younger years, the PSA data varied about the mean in a way that is characteristics of random noise.  But in 2014 (or perhaps as early as 2012), it started rising ever so slowly, following an exponential that a couple years ago pierced through to the level considered worrisome.  This proves nothing other than my depression being correlated with my father's death and the rise of my PSA.  But an intriguing correlation that my oncologist said he has independently observed...

My wife and I were isolated for most of 2020, but nevertheless we got COVID in November.  I traced

the probable location of my infection to the ice hockey rink, where I played masked with only 5 players. (The photo gives proof of us wearing masks -- but taken after I recovered from COVID).  Given the large separation between us, I was surprised that this was ground zero.  However, the  cold air and lingering breath droplets that it suspends, coupled with the heavy breathing associated with physical exertion no doubt made the ice a more dangerous place than I had expected.

We are fortunate that we had the mildest possible COVID symptoms and only for a short time.  I started feeling fatigue after playing ice hockey on a Sunday morning.  Most of the fatigue subsided after a 2-hour nap that afternoon after I had completed my weekend chores.  For the next couple days, I continued to feel mild fatigue, some achiness and had slight congestion that was comparable to what I normally experience from allergies.  I tested positive on the day after my symptoms appeared, and by Wednesday, I felt fine.  The only symptom that persisted for a couple weeks was the loss of the sense of smell, which returned gradually over time.

Overall, it was a good year, with the added benefit of the optimism I feel for 2021.

2021 has already started out well.  We visited my son, his wife and daughter on the other side of the country and also visited our daughter and her family.  Being immune to COVID (I tested positive for COVID antibodies) allows us to travel, so getting it was a net positive.  Also, I bought myself a nice Questar telescope (used on eBay), which I had coveted for decades, and plan to use it in our wilderness.  I will be teaching two graduate courses this spring, one of them a new prep (Thermodynamics), a topic that I am excited to revisit with the goal of deepening my understanding.  I am writing this post as I take a break from preparing my notes and doing the homework problems.

We will be using the thermodynamics textbook by Herb Callen, the professor that taught me the topic when I took his course at the University of Pennsylvania 40 years ago.  I recall the class being the worst in my graduate career – perhaps I was to blame.  But his book is fantastic, presenting the material clearly and resolving common points of confusion.  Working all the problems in the book consumes most of my time but doing so helps me to anticipate issues that students might have when learning the material.  And I am learning a lot through an enjoyable process of frustration followed by the satisfaction of success.

It is wonderful having a job that requires me to learn new things every day and a network of family and friends with whom I play and share my life.  Happy New Year!

 

Wednesday, October 21, 2020

How the Manuscript Review Process Should Work

The review process provides a level of quality control that insures that published papers are correct and of interest to the scientific community.  Since reviewers are themselves scientists with busy schedules, and being a reviewer provides no compensation aside from the satisfaction of being a good citizen, editors often find it difficult to get the best people for the job.  This has led to an increase in desk rejects by the editor, which avoids wasting reviewers' time on manuscripts that will most likely not be accepted.  The review system is frustrating to all parties involved.

I've been involved on all sides.  As an editor, I took lots of grief from angry authors.  In one case, I got a phone call from an irate author whose paper I had rejected.  He lectured me that as an editor of a prestigious journal decades prior, he would use at least one of the reviewers that the author had recommended.  Why had I not done so?  Because the review process is anonymous, I could not tell him that I used two of the three physicists that he had suggested, and they both recommended that the paper be rejected.  As a compromise, I selected his third choice of reviewer, along with yet another one.  Again, they all rejected the paper.  I could have avoided the next phone call and the indigestion that followed if I would have disclosed the fact that I had chosen at least one of his recommendations.  But I could not.

On another occasion, one of my colleges refused to act as a reviewer on a paper for which he was perfectly suitable.  That same colleague had an issue with one of his papers (not to my journal) where he needed my help, so I used it as leverage to get him to act as a reviewer for me.  There are all sorts of behind-the-scenes dynamics that are not always obvious to authors or reviewers.  The bottom line is that the process is far from perfect, which brings disdain from authors who are unhappy with the results.

I am writing this post to describe an example of a rainbow amidst the storm.

The American Journal of Physics is one of the coolest Physics publications on earth, so I read every monthly issue cover-to-cover.  There are always a few articles in each issue that surprise and delight.  They often point out subtleties in topics that you might think mundane, and bring insights that have been missed by the research community.

Being an author of a couple papers in AJP over the last two years, I have found the review process to be excellent.  The reviewers are knowledgeable and seem to spend lots of time trying to understand the work.  The exchanges are a real learning experience, and all parties are flexible -- admitting mistakes and savoring the process.  Here I describe an example of my experience with a paper that will be appearing in December (here is a link to the preprint).

The editor notified me that my paper had mixed reviews:

"Attached you will find copies of the reviewers' reports on your manuscript "Length as a Paradigm for Understanding the Classical Limit." Though the reports differ in recommendation, it is the content of the reports that is more important than the recommendation per se, and all three reviewers seem to be focusing on the same (or almost the same) issue: The justifiability of your model for what you call length. It will be necessary for you to address this issue in a revision. There are additional detailed corrections and suggestions that should also be carefully in a revision.

If you wish to revise your manuscript along the lines indicated, we would continue its editorial consideration once it has been resubmitted using the procedure indicated on the AJP website. If you do resubmit, please indicate in a single cover letter how you have responded to the various comments of the reviewers. DO NOT send separate replies for each reviewer.

Thank you for your interest in the American Journal of Physics."

The first thing that caught my eye was the fact that this was not the usual form letter used by most journals.  The editor had carefully read the reviews and noticed some common criticisms.  I eagerly dove into my revisions, finding that the reviewers' questions and confusion were the result of deficits in my paper.  I knew what I was trying to say, but my obtuse presentation of the material was only made obvious by their comments.  Most importantly, responding to the reviewers forced me to think more clearly about the physics.  As a result, I gained insights into my own work when making the revisions, increasing substantially the quality of presentation.

Exchange With Reviewers 

Particle in a Box

I will focus here on the common complaint made by all the reviewers, which centered on my use of the particle-in-a-box model.  Here are their complaints:

REVIEWER #1

My only concern is the basic assumption used to model the ``quantum'' systems.  The author is assuming the quantum system is inside a box with hard walls (it uses the infinite well model to derive the wave-function of one electron, and then generalizes it to non-interacting particles).  While this is a simple an intuitive model to work with, it is not clear that the results would carry on with more realistic potentials that might have different boundary conditions. 

REVIEWER #2

In the work, the focus lies on the electrons of a material and the nuclei are taken as a scaffolding for them, which is the usual approach for solid state physics. Yet, the wavefunction for the entire ruler will truly include the atoms as well. I would expect that the length of the ruler as calculated through this procedure will change when including these additional fermions, while I reality the length of the rod will remain the same. If this is so, it would jeopardize the numerical results in this work (although not its method)

REVIEWER #3

It is also strange the definition of the length of an object as the sum of the densities of the electrons confined in that potential, like the example of the particle in the box. The length of a real material should depend on the properties of the nuclei as well as of the electrons.

My Response:

Since all the reviewers brought up a similar point, I responded to them as a group.  Here is the verbatim response:

We interact with materials either by looking at them with our eyes (light scattering from electrons) or touching them (repulsion between electrons in the material and within us).  I believe that we all would agree that what we ``see" are the electrons, though their density does indeed depend on the presence of the nucleons.  So two materials with the same electron density but different nuclear positions would appear the same.  The mass, of course, is dominated by the nucleons, but we are viewing/touching the electrons when determining the length.  The length would be different if we did scattering experiments that are tuned to only probe the nucleons, but on the scale of human senses, we see only the electrons.  In either case, the lengths determined in these two ways would be similar for multi-atom quantum systems.

The positions of the nucleons are well represented by the Born-Oppenheimer Approximation, where the nuclear equilibrium positions are determined by the configuration with the lowest total energy.  Some of the electrons are involved in stabilizing the system -- which can be viewed as chemical bonds -- and in materials such as metals, the rest of the electrons are delocalized over the bulk material.  In the absence of defects, bulk metals appear smooth so each conduction electron moves approximately freely within the metal and encounters a large barrier at the edges.

This picture roughly holds for all materials and uniform electron densities are found is a variety of systems with delocalized electrons modeled by particles in a box.  These include small molecules such as the polyenes, as modeled by Kuhn in the 1940s, to metals as described in solid state textbooks, to nanoparticles that straddle the classical/quantum divide as recently reported by Scholl.

I would thus argue that the particle in a box is a good model that roughly holds well for many systems.  Much more sophistication is required to deal with the nuances.  I therefore believe that using the particle in a box model contains the correct physics that is assessable to a student.   Taking into account the reviewers' comments to explain this to the reader, I have added a third paragraph to Section III.A that reads:
 

"Models of materials with non-interacting electrons in a box roughly predict the electronic properties of small molecules such as the molecular class of polyenes,\cite{kuhn48.01} describe metals as found in solid state textbooks\cite{OpenStax20.01} and accurately portray the quantum to classical transition of nano-particles.\cite{schol12.01}  This shows that the effect of the nucleons on the electrons can be roughly taken into account with a box that confines the elections within.  We will thus model typical materials with uniform electron density as non-interacting electrons in a box.  The reader should keep in mind that this is a first step in modelling materials in which electrons are delocalized.  Later we treat materials made of such units that are ``pressed" together.  Then, the electrons are localized within domains rather than over the full material.  For simplicity, we will treat only one-dimensional systems.  Other potentials can be treated in the same way, but this exercise does not result in significant-enough insights about length itself  to make it worthwhile to treat in this paper."

The reviewers we satisfied with my response.  Here are excerpts from their second set of comments:

REVIEWER #2 - Second Response

I'm particularly satisfied with the argument to not include the
nucleons in the the total wavefunction. I've learned a new insight
here, using the Born-Oppenheimer approximation. Also, I think the
added paragraphs to section III add to the quality of the story.

REVIEWER #3 - Second Response

The author presented an improved manuscript that discusses the
difficult concept of quantum length. The language in the response
and the changes in the text greatly improved the manuscript.

Definition of Length


REVIEWER #3

This reviewer thought that my paper was wrong and should be rejected on the basis that I defined the length in a certain way that was arbitrary.  In the reviewer's own words:

It is my opinion that the manuscript is not technically correct as it starts with the definition of length of rod in terms of its uncertainty in the position.
 
The reviewer continues with technical details.  This comment led me to see that I was unclear in my presentation.  I responded with:

Your major criticism of this manuscript is with the ``definition of the length" and your argument against this definition is based on the fact that the coefficient $\sqrt{12}$ would change if the material were not uniform.  The original version treated only the uniform classical rod as the length element.  In the revised manuscript, an appendix describes how a non-uniform classical rod is treated, and is referred to in the main text.  Your argument is analogous to stating that the Pythagorean theorem can't be right because the expression would depend on the shape of the curve along the hypotenuse.  As with Pythagoras, where the length of the curve is obtained by dividing it into infinitesimal straight sections, so too the classical length is computed as the sum over uniform segments.  In retrospect, the original manuscript did a horrible job by neglecting this description.  I believe that using an appendix eliminates confusion yet maintains the flow of the narrative.

I have also added a couple paragraphs, as described above in the general section, which argues for the ansatz for the quantum length, a regime where it is no longer possible to subdivide a material without changing its properties.  I hope that these two major revisions remove confusion and makes you comfortable with the length expression that results from applying translational invariance and classical correspondence.

 

In response to my revisions, the reviewer adds: 

 
The added appendix lets the reader know that there are other
definitions that would converge to the proper classical limit. I
would like to see incorporated in the beginning of manuscript the
statement that the author made about how theories are developed.
This would be very helpful for the readership to explain how one
should approach making comparisons between new theories and their
classical limits. Incorporating these ideas on someone’s teaching
can help students navigate phenomena they are seeing for the first
time while relating them to things they are familiar with. These
ideas are incorporated in the Lessons Learned section, however,
helping the reader have this framework at the beginning of the
manuscript can guide the reader on understanding the assumptions
made, the development of the concepts, and finally understanding
the conclusions in the end.


It is my opinion that the manuscript might be published in the
present form, but it can still be improved by incorporating the
four points on theory developed in the introduction:


1. Setting the physical constraints. Here the length is required to
be translationally invariant and to give the correct classical
result.

2. Choosing the simplest ansatz that meets the constraints. The
uncertainty happens to meet the translational invariance criteria
but the length is NOT ad hoc defined as the uncertainty.

3. Demanding that the quantum theory in the classical limit gives
the classical result. Here, the quantum length and classical length
converge in the many-particle limit and for one particle in the
limit of it occupying the highest-energy state.

4. Investigating the Consequences. Here we apply the ansatz to
rulers and measurement.


In addition to being satisfied with my revisions, my comments to the reviewer led them to conclude that the response I had directed at the reviewer in my rebuttal was so useful that it should be added to the paper.  This was a great idea, and an example of what I was thinking when I was writing the paper, but something that I had not verbalized. This gave me the opportunity to carefully craft  what I think is an important takeaway message of my paper.

Conclusion

There are many other useful exchanges with the reviewers that would take too much time to summarize here and would add too much length to this post.  So instead, I have uploaded all the files with the reviewers' comments and my responses, to which I provide links below.  The end result is that I got great advice, which led to a much better paper not only in the presentation style, but in substantive additions to the content.  More importantly, I feel a deep kinship with these reviewers, who bared their minds to me in a frank dialog that gave me a more nuanced understanding of the topic.  I am indebted to these individuals who sacrificed their valuable time without compensation, other than to savor the satisfaction of learning about and understanding the subtleties of our world.