Website of Prof. Pascal Tyrrell
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| For more info see Free Birds… |
Happy Canadian Thanksgiving!!!
A traditional holiday – originating from the native peoples of the Americas – to celebrate the completion and bounty of the harvest. Well, no harvest for me but I will take the time to appreciate some of the successes of our MiVIP program and this blog over the long weekend.
Well, OK maybe think Zotero. The Mask of Zorro was such a great movie I could not resist. Having said that, when starting a new research project it may be helpful for you to think of yourself as Zorro. It may give you that extra zip required to get you through the inevitable research project doldrums…
So what is this Zotero thing anyway? Well Zotero is an open source reference management software that can act as your personal research assistant – helping you to organize and cite the numerous articles that you will be reviewing.
I was talking to Ori the other day – who is in the Radiation Therapy program at the Michener Institute – and he is in the process of planning a research project. As it turns out he has been a member of the MiVIP family since the beginning so he is well aware of my earlier posts that will help him along:
1- Thoughts on how to become a researcher
2- What is in a research question?
3- What makes up a good research question with the F.I.N.E.R. series.
Now how about the reference management software thing? Well, I give you an easy, fun, and instructional e-learning module to help you along. Our group has just finished our first kick at the can (so to speak) and so I invite you to have a look. Here is the link:
MiEducation Zotero e-learning module
Tell us what you think by posting comments and suggestions to this post.
Maybe listen to Ylvis in What Does the Zorro Say? while you go through the module. Fox in spanish is zorro…
OK who hasn’t made rock candy as a kid? No? Give it a try. Maybe you have a little brother or sister you can impress. All you need is a super saturated solution of sugar, a surface for crystal nucleation (string), and lots of time…
Now what if you were to apply this technique to obtain crystals of DNA? I don’t suggest that you eat it as a treat but you could possibly try X-ray crystallography.
The challenge is that DNA, unlike proteins, is an exceedingly large molecule which does not lend itself to crystallisation. The result is a highly viscous suspension of spiderweb-like filaments. However, it is this very suspension that the DNA molecules were deduced to be neatly aligned alongside one another by studying the X-ray diffraction patterns. This initial challenge was successfully overcome by Rosalind Franklin. Her hard work then laid the ground work for Watson and Crick to piece together the puzzle of DNA structure (winning the 1962 Nobel Prize along with Wilkins).
Now the x-ray crystallography imaging technique is no pic-nic! It was first described by the Australian father-and-son duo William Henry Bragg and William Lawrence Bragg. Essentially x-rays are projected onto a crystalline solid and when analyzing the diffraction patterns it is possible to determine how its molecular atoms are positioned in relation to one another. This is due to x-rays having very short wave-lengths (see x-rays in the blog) and the mathematical analysis of predictable diffraction from the three dimensional structure of the crystal. It was Lawrence Bragg who developed the equation to describe this diffraction and is now known as Bragg’s Law. He and his father won the Nobel Prize for this work in 1915.
I used to listen to New Order back in the day and they are still singing (and dancing?) with a more recent release of Crystal by New Order. So, listen to the song while making rock candy and maybe you too will come up with a brilliant idea worthy of a Nobel Prize by the time the crystals are big enough to eat.
Now if you remember the rules:
1- I introduce and discuss a word.
2- You have to use the word in a sentence by the end of the day. No need to use it in the correct context – actually out of context is more fun and elicits a more entertaining response!
Today, we have to use “Bragg” in a sentence. Here are two examples to help you along:
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| Helena Lan Summer 2014 ROP |
What is research like? If you had asked me this
question several months ago, I would have answered, “You wear a lab coat and
goggles while mixing chemicals or observing organisms. Hopefully something
interesting will happen, so that you get to publish your findings!” Well, after
participating in the Research Opportunity Program (ROP) at the University of
Toronto, I discovered that medical imaging research is more than just
pipetting, and is all the more exciting!
So, what does medical imaging have to do with a Supernova? Well in the B-movie – Supernova a deep space medical ship responds to a distress signal from a nearby mining planet and gets too close to a Red Supergiant ready to go Supernova. Is your geek alert tingling?
Well, believe it or not Supernovas are explosions of giant stars. Nuclear fusion produces iron in the cores of these stars. Such dense matter at the core creates a tendency for the star to collapse on itself due to gravitational pull. This is kept in check by the massive amounts of energy the star is constantly releasing. But what happens when the star starts to run out of fuel? Yup, you guessed it. It collapses on itself and implodes. As the star rushes inwards, protons and electrons combine to produce neutrons that in turn collide with the core and produce a crazy big explosion. This sudden release of energy is accompanied by the production of x-rays. Yes, I am serious. What is left behind of the exploded star is either a neutron star or a black hole depending on the mass of the remains.
So, a supernova is essentially a giant x-ray machine? Maybe not. However, by studying these cosmic x-rays astronomers are able to help describe the structure of the universe (not Castle Greyskull). Cool.
Question for you: should we be concerned with being exposed to cosmic x-rays? No. Cosmic x-rays are pretty much completely filtered out by our atmosphere by the time they get to the surface. So, how do astronomers get readings? Good question. By placing their recording instruments on satellites and spacecraft, of course!
Now on to using supernova in a sentence today:
Serious example – So did you catch the last supernova in our galaxy? Happened about 400 years ago. No? The next one should be soon as it is overdue by about 300 years.
Less serious – Growing up I always loved the Chevy Nova SS. Especially when it was customized. It surely was a super Nova…
Enjoy Ray LaMontagne – Supernova to recover from today’s post and I’ll see you in the blogosphere.
Pascal Tyrrell
What!!? Do you find it on pizza or in the middle of green olives? Well actually, it is a word of Italian origin and describes minor changes in a painting during its composition. So, similar to erasing some of your hand writing and then writing over it again with the corrected text. I guess for you younger folk it would be like pressing back-space and then re-typing! The difference of course is that there would NOT be any pentimenti as there would no trace of your previous attempt…
So what does this have to do with medical imaging? In our last Mi word of the day we talked about x-rays. Now, today we take x-rays and our ability to peer inside the human body for granted. So what else can we see with x-rays? Believe it or not x-rays can also help to reveal how a painting evolved from first brush strokes to finished product. X-ray analysis can help to describe the paint composition to the different layers that may exist in the painting.
Consider, for example, “Patch of Grass” by Van Gogh seen above. It was discovered by x-ray analysis that this 1887 painting completely concealed a portrait of a woman that Van Gogh had painted over. He often did this to save money on canvases (maybe to buy Absinthe – how naughty!). In this case, in addition to Van Gogh’s pentimenti is his habit of painting over previous works. All of this adds to a type of “fingerprint” that art appraisers use to identify works of art from forgeries… Cool.
Today, we have to use “pentimenti” in a sentence (see rules here). Here are two examples to help you along:
Serious: I wonder how Van Gogh’s pentimenti differs from that of Rembrandt. Maybe I should ask the Musee du Louvre’s curator for some insight.
Last week I met with Helen, a clinical investigator program radiology resident from our department, about her research (shout out to Dr Laurent Milot’s research group). When discussing predictors and outcomes for her retrospective study it was suggested that some continuous variables be broken up into levels or categories based on given cut-points. This practice is often encountered in the world of medical research. The main reason? People in the medical community find it easier to understand results that are expressed as proportions, odds ratio, or relative risk. When working with continuous variables we end up talking about parameter estimates / beta weights and such – not as “reader friendly”.
Unfortunately, as Neil Sedaka sang about in his famous song Breaking Up Is Hard to Do, by breaking up continuous variables you pay a stiff penalty when it comes to your ability to describe the relationship that you are interested in and the sample size requirements (see loss of power) of your study.
You are now a newly minted research scientist (need a refresher? See Pocket Protector) and are interested in discovering relationships among variables or between predictors and outcomes. The more accurate your findings the better the description of the relationships and the better the interpretation/ conclusions you can make.The bottom line is that dichotomizing/ categorizing a continuous measure will result in loss of information. Essentially, the “signal” which is the information captured by your measure will be reduced by categorization and, therefore, when you perform a statistical test that compares this signal to the “noise” or error of the model (observed differences between your patients for example) you will find yourself at a disadvantage (loss of power). David Streiner (great author and great guy!) gives a more complete explanation in one of his papers.
Now, as we see in the funny movie with Vince Vaugh and Jennifer Aniston, The Break Up, there are times when categorization may make sense. For example when the variable you are considering is not normally distributed (see Are You My Type?) or when the relationship that you are studying is not linear. We will talk about these situations in a later post.
Don’t forget: you will get further ahead if you keep your variables as continuous data whenever possible.
See you in the blogosphere,
Pascal Tyrrell
Yup! Want some of that. Not only is Superman cool but he has x-ray vision. Unbelievable. Or is it? Radiologists have the same x-ray vision but without the Spandex suit – or at least they don’t wear it to work that I am aware of.
The word of the day is x-ray. You have already successfully used “Roentgen” in casual conversation last week (don’t know what I am talking about? See Mi Word of the Day Is… Roentgen!) and today I will talk a little about what Roentgen was first in measuring and describing – x-rays.
Let’s say you are in your lab and you are working with passing electrical discharges through vacuum tubes – a typical Saturday afternoon activity with friends. As chance would have it your little sister’s barium salts paintings happen to be drying near-by and you notice a faint glow emanating from them every time you run your experiments. No matter how much you try to block any light coming from your vacuum tubes the glow persists. What? That’s odd. How’s that happening? Well my friend, you have just crossed over into the Twilight Zone (awesome old tv series) and discovered a form of electromagnetic radiation.
Visible light is but a very small part of the electromagnetic spectrum. Moving from visible light to longer wavelengths and lower frequencies we find infrared (keeps food warm at restaurants), microwaves (to warm your pizza pop) and radio (not the one streamed through the internet!).
Now if you move in the opposite direction from visible light you find shorter wavelengths with higher frequencies starting with ultraviolet (what helps you get that summer tan), x-rays (word of the day), and finally gamma rays (topic for another day!). So x-rays are about the size of atoms and radio waves the size of buildings. Crazy. I think what is surprising is that with the naked eye we “see” so little and yet so much (philosophy anyone?).
So, x-rays are short wavelength, high frequency, high energy electromagnetic radiation that is able to penetrate some substances more easily than others. For example, they penetrate flesh more easily than bone, and bone more easily than lead. Thus they make it possible to see bones within flesh and a bullet embedded in bone. The ability of X rays to penetrate depends on their wavelength and on the density and thickness of the substance being scanned.
Less serious: Frank! Dude, I got them! My x-ray specs just came in the mail. Let’s go the beach…See you in the blogosphere,
Pascal Tyrrell
We have been talking about agreement lately (not sure what I am talking about? See the start of the series here) and we covered many terms that seem similar. Help!
Before you call the whole thing off and start dancing on roller skates like Fred Astaire and Ginger Roberts did in Shall We Dance, let’s clarify a little the difference between agreement and reliability.
When assessing agreement in medical research, we are often interested in one of three things:
1- comparing methods – à la Bland and Altman style.
2- validating an assay or analytical method.
3- assessing bioequivalence.
Agreement represents the degree of closeness between readings. We get that. Now reliability on the other hand actually assesses the degree of differentiation between subjects – so one’s ability to tell subjects apart from within a population. Yes, I realize this is a subtlety just as Ella Fitzgerald and Louis Armstrong sing about in the original Let’s Call the Whole Thing Off.
Now, often when assessing agreement one will use an unscaled index (ie a continuous measure for which you calculate the Mean Squared Deviation, Repeatability Standard Deviation, Reproducibility Standard Deviation, or the Bland and Altman Limits of Agreement) whereas when assessing reliability one often uses a scaled index (ie a measure for which you can calculate the Intraclass Correlation Coefficient or Concordance Correlation Coefficient). This is because a scaled index mostly depends on between-subject variability and, therefore, allows for the differentiation of subjects from a population.
Ok – clear as mud. Here are some very basic guidelines:
1- Use descriptive stats to start with.
2- Follow it up with an unscaled index measure like the MSD or LOI which deal with absolute values (like the difference).
3- Finish up with a scaled index measure that will yield a standardized value between -1 and +1 (like the ICC or CCC).
Potato, Potahtoe. Whatever.
Entertain yourself with this humorous clib from the Secret Policeman’s Ball and I’ll…
See you in the blogosphere!
Pascal Tyrrell
MC Hammer. Now those were interesting pants! Heard of the slang expression “Seems legit”? Well “legit” (short for legitimate) was popularized my MC Hammer’s song 2 Legit 2 Quit. I had blocked the memories of that video for many years. Painful – and no I never owned a pair of Hammer pants!
Whenever you sarcastically say “seems legit” you are suggesting that you question the validity of the finding. We have been talking about agreement lately and we have covered precision (see Repeat After Me), accuracy (see Men in Tights), and reliability (see Mr Reliable). Today let’s cover validity.
So, we have talked about how reliable a measure is under different circumstances and this helps us gauge its usefulness. However, do we know if what we are measuring is what we think it is. In other words, is it valid? Now reliability places an upper limit on validity – the higher the reliability, the higher the maximum possible validity. So random error will affect validity by reducing reliability whereas systematic error can directly affect validity – if there is a systematic shift of the new measurement from the reference or construct. When assessing validity we are interested in the proportion of the observed variance that reflects variance in the construct that the method was intended to measure.
***Too much stats alert*** Take a break and listen to Ice, Ice, Baby from the same era as MC Hammer and when you come back we will finish up with validity. Pants seem similar – agree? 🙂
OK, we’re back. The most challenging aspect of assessing validity is the terminology. There are several different types of validity dependent of the type of reference standard you decide to use (details to follow in later posts):
1- Content: the extent to which the measurement method assesses all the important content.
2- Construct: when measuring a hypothetical construct that may not be readily
observed.
3- Convergent: new measurement is correlated with other measurements of the same construct.
4- Discriminant: new measurement is not correlated with unrelated constructs.
So why do we assess validity? because we want to know the nature of what is being measured and the relationship of that measure to its scientific aim or purpose.
I’ll leave you with another “seem legit” picture that my kids would appreciate…
See you in the blogosphere,
Pascal Tyrrell