How do I personally justify medical school?  In terms of a strictly business & professional approach, it makes sense to quantify the amount of my time that my profession takes up and then compare just how much I would be compensated for my labor.  The problem with an MD, however, is that this is widely variable across the field.  It even varies wildly between sub-specialties under the same umbrella.

Luckily, there’s another person who’s already taken a look at this metric using data made public by JAMA in 2008.  This chart gives an overview of salaries, number of hours, and finally average hourly compensation by specialty.  http://pantheon.yale.edu/~jlb236/salary_per_hour2.htm

SIDENOTE:  I just got distracted by MDapplicants.com and will be checking that out for the next 20 minutes.  This post is being cut short.

(Although the conclusion was basically that ophthalmology & hematology/oncology are sitting at the top of my list right now…)

DAMAGE TO…

1. …growth-promoting proto-oncogenes
2. …growth inhibiting tumor suppression genes
3. …genes that regulate cell death
4. …genes affecting cell repair

And one final step is necessary in order to achieve a malignant tumor that will invade until it’s leached it’s host dry of any life.  That step is:

TELOMERASE ACTIVATION

But what the heck is telomerase??  Basically telomerase is an enzyme that acts on the telomeres of DNA.  These are the sections at the 3′ end of DNA strands, and everyone remembers that DNA is read & transcribed by RNA polymerase from 5′ to 3′.  Once the polymerase gets to the end of the DNA coding for protein synthesis it hits the telomere section, which has multiple repeated segments of the code, “TTAGGG”.  This code does not get translated into proteins, but rather signals the end of a chromosome.

Each time chromosomes divide & replicate, a portion of this end cap is lost.  Normally this means that each cell can only divide a finite number of times before the telomere “end cap” is completely lost and genes coding for proteins are degraded.  Enter telomerase: the enzyme that adds extra stop code — TTAGGG — to the telomere. This is a really cool function for an enzyme to accomplish; this act allows cells to continue growing and dividing for a longer period of time.  This pathway can also act as a feedback mechanism since enzyme up/down-regulation is governed in a complex fashion.

Now I’ll get back to why Telomerase is necessary for cancer’s Final Solution: without enhanced telomerase levels, rapidly dividing cancer cells would burn through the telomeres of chromosomes really, really FAST. Thus high levels of telomerase are necessary to keep these cells diving indefinitely.  I’m sure there are clinical studies that support this, seeing as I learned most of this from my current general pathology course in conjunction with wikipedia.  If I didn’t have sleep to catch up on and a test to take in <2 days, I’d do a literature search and see what kind of therapies targeting this site are being used / tested :).

And with that, I begin to take baby steps in the direction on the path of getting an MD to complement my pending PhD!

Feb 22-28
1696 - 1639 = 57 miles

Coming soon: small spreadsheet .exe to track miles over time & chart it.  Compute simple averages and predictions.

Go here to download Girl Talk’s Feed The Animals.

Girl Talk: Feed The Animals

Ian playing the hangover blues (click for full size)

Winter 2006, Sunday early afternoon.

Canon S2 IS
f/3.1
1/60s

© 2006 Matthew Rinehart
Please email me prior to using this image for any public use.  Any use on a site intended for profit is at my sole discretion.  If otherwise used, I will generally allow posting with a link back to my website.

compliments of xkcd.com

Taking fourier transforms of things is really popular nowadays, especially in the realm of discrete time-signal analysis and also image processing.  I am in the process of learning how to use fourier transform analysis to extract the phase of interferometric images (read: holograms), but more on that another day.

Matlab is absolutely great for doing numerical simulations with large datasets, but I find it has some major shortcomings when it comes to fourier transforms, and really everything else analytical.  Mathematica wins here, except for needing a couple custom parameters to produce a unitary fourier transform of a function.  However I have managed to find a pretty nice work around for Matlab’s fast fourier transform function (’FFT’).  The three main issues that arise with FFTs are:

1. Frequency scaling doesn’t work out properly (ie - FFT(sin(x)) does NOT give you a peak at 2π automatically)
2. Positive and negative frequencies get all mixed up.
3. Apparently the amplitude is off too.

Quan Quach at blinkdagger has come up with a very convenient function script that deals with these problems on a basically satisfactory level.  I’d like to delve further into what this does and how to extract meaningful data from a Matlab FFT, but I think I’ll save that for a future post.  Looks like Quan has a full category on fourier transforms, which is a MUCH better place to start than the matlab help file for FFT or FFT2 (2-dimensional version of the fourier transform).  Check it out here.

You’ll learn how to take this:

… and produce this:

Really quite nifty!  While this got me started with fourier transforms, I’d really like to dig into the meaning of fourier transforms of space and digital image processing.  In the world of optics, this gives a lot of helpful knowledge when processing data from lens focal planes, from holograms, or even when numerically simulating an electromagnetic field and you’re interested in far-field diffraction patterns.  Actually on that note, it’s time for me to get back to my homework…

Photo by Ken Conley

BY THE NUMBERS:

Today
Leipheimer:
d = 24km (15 mi)
t = 0:30.40
v = 46.96 kph (29.35 mph)

Nearest competitor:
t = 0:30.48
v = 46.75 kph (29.22 mph)

Physical margin of victory:
~104 meters (341 feet)

Overall - Leipheimer:
Total time in Tour of California: 24:12.00 (1st place)
Current Lead: 36s
Total Distance:  957.24 km (594.8 mi)
Average speed:  39.6 kph (24.6 mph)

Remaining distance: 298.9 km (185.7 mi)

Levi celebrates his third year of winning the Tour of California TT

I’m excited to see Levi dominate the last two stages coming up.  It’s also encouraging to see that after 24 hours of riding, he’s only averaging ~24.5 mph.  Hey, I averaged 22 mph in my first road race last weekend!  But it was only 18 miles long…