Hello everyone,
It's always a joy to host a carnival where you read things written by your peers that are so insightful, truthful and enjoyable. Thank you everyone who wrote to me with posts and those who suggested posts, and without any further ado, the carnival.
Regrets Regrets
I wanted to know what all of you would have done differently if you could, and the spectrum of answers was fascinating. Dr. Brazen Hussy wouldn't change a thing, barring the occasional drunken quarrels with her advisor. Day by Day wouldn't change much either in the balance, she regrets only not spending enough time with her friends from grad school. Lou proposes that we all appreciate the here and now and learn from our pasts rather than regret them, and Propter Doc has a detailed and insightful analysis of what she would have changed given her current perspective. Katie at Minor Revisions has a frank and honest essay on regretting the time she has wasted and the questions she should have asked. And comes up with one the most memorable quotes I have heard in a while: "Post-docs are a renewable resource here." and goes on to compare postdocs to plankton. Fabulous and fabulously apt. Ragey One, Apparently and I do have some regrets, Ragey would not have accepted her current position knowing what she knows now, Apparently would have done her postdoc experience differently, and I would have interviewed more.
Dealing with other diverse subjects, other postdoc or former-postdoc bloggers have some great things to say. Sunil at balancing life wonders why Ph.Ds are so long, Incoherently scattered ponderings has some advice for what not to have on a CV and YoungFemaleScientists discusses whether its easier for foreign postdocs to find jobs here as opposed to US postdocs looking elsewhere. Marianne at the Eternal Postdoc tells us why being a postdoc is so hard, and Chall at Dreams and Hopes of a Scientist believes that your PI will find it easier to believe in you when someone else does. Chris at Highly Allochthonous finds that the postdoc is willing but the equipment isn't and a group of postdocs formed the postdoc union (wonder how they are doing?). Also, no to be discriminatory, but I have to mention some lovely women in science, Micella Phoenix DeWhysse at Science Careers has a whole series on Educated Women, here's one, and women in science as always has cool things to say.
And finally, the utterly apt and necessary PostDoc Oath, from the Girl from Ipanema. Say it with me everyone, " I X postdoc, do solemnly swear that..."
Thursday, August 23, 2007
What would I have done differently?
Interviewed more.
I don't believe in regrets and hand-wringing. I am self-aware enough to know that I made an informed choice and I saw most of the red flags in my current lab when I interviewed. I didn't expect them all to be true, but that is a different matter.
I interviewed over one long weekend, in one area. I did restrict myself geographically for personal reasons, and that geographical restriction is turning out to be the best past of this experience. Anyway, over that weekend, I interviewed with five PIs and three labs. One experience was excellent, saw some potential problems, figured awareness was half the battle. One experience was really good, but I would have ended up being the senior person in the lab and the PI wasn't even directly offering me the job anyway. The other three were washouts. I was already pretty fed up with the process, because I had a few pre-screening rejections based on the tight funds at the time and my average but not sexy CV. So I didn't send out more applications and accepted offer from said excellent interview experience.
Red flags and all. And everything I thought might possibly go wrong did. Everything possible. Which really sucks, but I thought they were all possible. I also think that every lab has its, shall we say, quirks. I didn't expect the personality of the PI and the community of the lab to be this negative. I have some wonderful colleagues, so it makes it easier, but otherwise, not good. And the general research environment is not conducive to one's greater professional development.
So, I made an informed decision and took a chance, it didn't pan out. I'm dealing. But, in restrospect I should have interviewed more, seen more places, other labs, other dynamics and then decided.
Oh well.
I don't believe in regrets and hand-wringing. I am self-aware enough to know that I made an informed choice and I saw most of the red flags in my current lab when I interviewed. I didn't expect them all to be true, but that is a different matter.
I interviewed over one long weekend, in one area. I did restrict myself geographically for personal reasons, and that geographical restriction is turning out to be the best past of this experience. Anyway, over that weekend, I interviewed with five PIs and three labs. One experience was excellent, saw some potential problems, figured awareness was half the battle. One experience was really good, but I would have ended up being the senior person in the lab and the PI wasn't even directly offering me the job anyway. The other three were washouts. I was already pretty fed up with the process, because I had a few pre-screening rejections based on the tight funds at the time and my average but not sexy CV. So I didn't send out more applications and accepted offer from said excellent interview experience.
Red flags and all. And everything I thought might possibly go wrong did. Everything possible. Which really sucks, but I thought they were all possible. I also think that every lab has its, shall we say, quirks. I didn't expect the personality of the PI and the community of the lab to be this negative. I have some wonderful colleagues, so it makes it easier, but otherwise, not good. And the general research environment is not conducive to one's greater professional development.
So, I made an informed decision and took a chance, it didn't pan out. I'm dealing. But, in restrospect I should have interviewed more, seen more places, other labs, other dynamics and then decided.
Oh well.
Tuesday, August 21, 2007
The Damage Response Framework
The Damage Response Framework of Microbial Pathogenesis is an idea, put forward by Liise Anne Pirofksi and Arturo Casadevall in 1999. I first heard of it when I heard Arturo Casadevall give a talk: and what a talk! If you ever get to see him speak, do so, its well worth it. The point of this idea, or framework of ideas, is to find a way to describe “pathogenesis” in the most universally applicable way.
What is pathogenesis?
It means the genesis and progress of disease. A pathogen (as described in the sidebar) is an organism that causes disease, a simple enough definition, and fairly all-inclusive one may think. Maybe not. What about an organism that doesn’t cause disease in a normal healthy “immunocompetent” host, but causes disease in hosts that have deficient immune system fro some reason? These normally harmless microbes cause harm only in immunocompromised individual (Immunocompromised: possessing a compromised immune system. A fine example of the immuno-rule, if you want to make a term immunologically relevant, add the prefix immuno to it). An extreme example from Casadevall and Pirofski: harmless useful baker’s yeast Saccharomyces cerevisiae is considered a non-pathogen most of the time, in fact we consume it with great gusto. However, in some severely immunocompromised people, it causes disease. So is it a pathogen?
The Damage Response Framework
The key words in the previous paragraph are immunocompetent and immunocompromised, words used to describe the host. As illustrated by the baker’s yeast example, a “non-pathogenic” microbe can cause disease depending on the immunocompetence of the host. So, the pathogenicity, or disease-causing potential of a microbe is partly determined by the immune state of the host it infects, and a disease is the outcome of the interaction between the host and the microbe. This is the (paraphrased) first tenet of the damage response framework. This may seem obvious, but it is a really novel way of looking at disease, as the interplay between the host and the microbe, with the microbe contributing virulence, and the host contributing either resistance or susceptibility. It is a fine balance in other words, with the occurrence of disease depending on the balance between said virulence and susceptibility at any given time.
The second tenet of the damage response framework refers to the definition of disease itself: that the degree of disease caused is determined by how much damage is caused to the host. If one accepts that individuals have different susceptibilities to a certain microbe, then is follows that they will be affected by it to different degrees. Some individuals will show no symptoms despite being infected, some will show moderate symptoms, and some will be felled. They are all infected, does that mean that they all have disease? Not if one uses the damage response framework to measure disease. It doesn’t matter if an individual is infected, i.e. the microbe has entered their body, it only matters if their body has suffered damage, and to what extent.
The third tenet of this framework is that the damage caused by infection with a microbe can be caused either by the host or the microbe. Microbes can cause damage in many ways: they can kill host tissues, they can form big aggregates that physically impede blood flow or digestion, they can alter the basic metabolic balance of the host. The immune system is fast, robust and precise for the most part, however, it works by sending cells and cytokines out into the body to whirl around and do their thing. Immune cells eliminate infection by killing host tissues that are infected; it stands to reason then that there will be some collateral damage. This collateral damage can be minimal and go unnoticed, or it can be measurable but worth it because the microbe is eliminated, or it can be so extensive that it causes most of the damage to the host. Tuberculosis is a good example of the third case, the granulomas that are such distinctive features of clinical tuberculosis are large collections of highly activated immune cells, raring to go and damaging large swathes of the host along the way.
The Practical Applications
The most useful direct application of the damage response framework is to eliminate the subjective classification of microbes as strong or weak pathogens, as opportunistic pathogens or non-pathogens. This is achieved by using a new system of classification (because everyone wants to be Linnaeus!). The damage causing ability of a pathogen is plotted on a damage response curve, and the pathogen is classified based on its characteristic curve. The curves plot host damage and benefit on positive and negative y-axes respectively and the host immune response on the x-axis, going from weak to strong. I don’t want to reproduce the figure from Nature Reviews here, but I’ll try and describe the curves. The most easily visualizable are Class 3 pathogens that have a U-shaped curve, with high damage caused when the host immune response is either too weak or too strong. The difference would be that the damage is caused by the microbe when the host response is too weak and by the host when the response is too strong.
These curves are really nice and interesting, but ironically, their main weakness is that they are too subjective. Strong and weak are relative terms, so these curves have limited application until we can quantify both damage and the host immune response in amore universal way. Another thing is the role of time. Infections take various courses over time, for example some viruses infect the host and become latent, hiding out in the host till they become activated upon which they cause damage. If the host immune response manages to overcome the activated virus the damage is limited and the virus reenters a state of latency, and has the potential to reactivate, propagating the cycle. A necessary component of the damage response curves is time then, on a third axis. This is probably pretty complicated computationally, also we I don’t really think there is enough data yet to make these for many pathogens. Especially since data needs to be collected with these curves in mind, a mindset change that yet needs to happen. Effectively, we would also need a massive though exercise in which we place all the data we have on microbes and the host responses they provoke together with the damage they cause are placed in a kind of giant multidimensional matrix and look for correlations and points of intersection. The biologist in me quakes at the scale, and the extremely rudimentary mathematics training I have had leaves me bug-eyed at the thought.
Extolling the coolness and a Summary
The Damage Response Framework of Microbial pathogenesis is incomplete and imperfect, but it is simple, clear, and phenomenally novel in its simplicity. It takes into account the interaction of both the host and the microbe, for after all they both affect each other constantly and while convenient, it makes little sense to treat them as separate independent entities while studying disease. I like to think of the host and microbe as trains on two separate but curving tracks. The host is headed towards a state of susceptibility and the microbe towards fitness to cause damage. At a given time, the curves of the tracks get close enough together and if the host train loses its balance on the track a little, becoming sufficiently susceptible, it collides with the microbe train and damage results. The extent of the damage depends on the angle of the collision (host susceptibility) and the momentum of travel. A limited and involved metaphor, but it helps me to visualize these interactions.
If you’d like to read about this idea in Pirofski and Casadevall’s own words, a great review is in Nature Reviews Microbiology in 2003, Volume 1, page 17. I’ve only skimmed the surface, there are so many implications and possible applications- not to mention caveats- that I haven’t gone into. It’s a seminal idea, and makes for very interesting reading and thinking.
What is pathogenesis?
It means the genesis and progress of disease. A pathogen (as described in the sidebar) is an organism that causes disease, a simple enough definition, and fairly all-inclusive one may think. Maybe not. What about an organism that doesn’t cause disease in a normal healthy “immunocompetent” host, but causes disease in hosts that have deficient immune system fro some reason? These normally harmless microbes cause harm only in immunocompromised individual (Immunocompromised: possessing a compromised immune system. A fine example of the immuno-rule, if you want to make a term immunologically relevant, add the prefix immuno to it). An extreme example from Casadevall and Pirofski: harmless useful baker’s yeast Saccharomyces cerevisiae is considered a non-pathogen most of the time, in fact we consume it with great gusto. However, in some severely immunocompromised people, it causes disease. So is it a pathogen?
The Damage Response Framework
The key words in the previous paragraph are immunocompetent and immunocompromised, words used to describe the host. As illustrated by the baker’s yeast example, a “non-pathogenic” microbe can cause disease depending on the immunocompetence of the host. So, the pathogenicity, or disease-causing potential of a microbe is partly determined by the immune state of the host it infects, and a disease is the outcome of the interaction between the host and the microbe. This is the (paraphrased) first tenet of the damage response framework. This may seem obvious, but it is a really novel way of looking at disease, as the interplay between the host and the microbe, with the microbe contributing virulence, and the host contributing either resistance or susceptibility. It is a fine balance in other words, with the occurrence of disease depending on the balance between said virulence and susceptibility at any given time.
The second tenet of the damage response framework refers to the definition of disease itself: that the degree of disease caused is determined by how much damage is caused to the host. If one accepts that individuals have different susceptibilities to a certain microbe, then is follows that they will be affected by it to different degrees. Some individuals will show no symptoms despite being infected, some will show moderate symptoms, and some will be felled. They are all infected, does that mean that they all have disease? Not if one uses the damage response framework to measure disease. It doesn’t matter if an individual is infected, i.e. the microbe has entered their body, it only matters if their body has suffered damage, and to what extent.
The third tenet of this framework is that the damage caused by infection with a microbe can be caused either by the host or the microbe. Microbes can cause damage in many ways: they can kill host tissues, they can form big aggregates that physically impede blood flow or digestion, they can alter the basic metabolic balance of the host. The immune system is fast, robust and precise for the most part, however, it works by sending cells and cytokines out into the body to whirl around and do their thing. Immune cells eliminate infection by killing host tissues that are infected; it stands to reason then that there will be some collateral damage. This collateral damage can be minimal and go unnoticed, or it can be measurable but worth it because the microbe is eliminated, or it can be so extensive that it causes most of the damage to the host. Tuberculosis is a good example of the third case, the granulomas that are such distinctive features of clinical tuberculosis are large collections of highly activated immune cells, raring to go and damaging large swathes of the host along the way.
The Practical Applications
The most useful direct application of the damage response framework is to eliminate the subjective classification of microbes as strong or weak pathogens, as opportunistic pathogens or non-pathogens. This is achieved by using a new system of classification (because everyone wants to be Linnaeus!). The damage causing ability of a pathogen is plotted on a damage response curve, and the pathogen is classified based on its characteristic curve. The curves plot host damage and benefit on positive and negative y-axes respectively and the host immune response on the x-axis, going from weak to strong. I don’t want to reproduce the figure from Nature Reviews here, but I’ll try and describe the curves. The most easily visualizable are Class 3 pathogens that have a U-shaped curve, with high damage caused when the host immune response is either too weak or too strong. The difference would be that the damage is caused by the microbe when the host response is too weak and by the host when the response is too strong.
These curves are really nice and interesting, but ironically, their main weakness is that they are too subjective. Strong and weak are relative terms, so these curves have limited application until we can quantify both damage and the host immune response in amore universal way. Another thing is the role of time. Infections take various courses over time, for example some viruses infect the host and become latent, hiding out in the host till they become activated upon which they cause damage. If the host immune response manages to overcome the activated virus the damage is limited and the virus reenters a state of latency, and has the potential to reactivate, propagating the cycle. A necessary component of the damage response curves is time then, on a third axis. This is probably pretty complicated computationally, also we I don’t really think there is enough data yet to make these for many pathogens. Especially since data needs to be collected with these curves in mind, a mindset change that yet needs to happen. Effectively, we would also need a massive though exercise in which we place all the data we have on microbes and the host responses they provoke together with the damage they cause are placed in a kind of giant multidimensional matrix and look for correlations and points of intersection. The biologist in me quakes at the scale, and the extremely rudimentary mathematics training I have had leaves me bug-eyed at the thought.
Extolling the coolness and a Summary
The Damage Response Framework of Microbial pathogenesis is incomplete and imperfect, but it is simple, clear, and phenomenally novel in its simplicity. It takes into account the interaction of both the host and the microbe, for after all they both affect each other constantly and while convenient, it makes little sense to treat them as separate independent entities while studying disease. I like to think of the host and microbe as trains on two separate but curving tracks. The host is headed towards a state of susceptibility and the microbe towards fitness to cause damage. At a given time, the curves of the tracks get close enough together and if the host train loses its balance on the track a little, becoming sufficiently susceptible, it collides with the microbe train and damage results. The extent of the damage depends on the angle of the collision (host susceptibility) and the momentum of travel. A limited and involved metaphor, but it helps me to visualize these interactions.
If you’d like to read about this idea in Pirofski and Casadevall’s own words, a great review is in Nature Reviews Microbiology in 2003, Volume 1, page 17. I’ve only skimmed the surface, there are so many implications and possible applications- not to mention caveats- that I haven’t gone into. It’s a seminal idea, and makes for very interesting reading and thinking.
Monday, August 20, 2007
Postdoc Carnival: (Renewed) Call for Posts
Hello All,
We are definitely entering the plea category. If you have anything you'd like to say, or have already said, about postdoc-ing or postdocs, send me an e-mail with a link to
veoclaramente@gmail.com
by Wednesday night. For the Carnival to be posted on Thursday the 23rd.
Looking forward to it!
We are definitely entering the plea category. If you have anything you'd like to say, or have already said, about postdoc-ing or postdocs, send me an e-mail with a link to
veoclaramente@gmail.com
by Wednesday night. For the Carnival to be posted on Thursday the 23rd.
Looking forward to it!
Wednesday, August 15, 2007
Tuesday, August 14, 2007
Never feel bad anymore?
The saddest happy song ever.
Island in the Sun by Weezer “..We’ll never feel bad anymore..”. Lovely fifties-sixties-ish chords. The “ hey hey”. Gets me every time.
“…We’ll run away together
We’ll spend some time forever
We’ll never feel bad anymore…”
Definitely not one of those days. Feels like I will be borderline bored forever. I know that’s not true, it’s a phase of the project, It’s all me really, I should plan better, I should be proactive, do more, fulfill my potential.
Don’t want to. Sighs.
Off to culture cells.
Island in the Sun by Weezer “..We’ll never feel bad anymore..”. Lovely fifties-sixties-ish chords. The “ hey hey”. Gets me every time.
“…We’ll run away together
We’ll spend some time forever
We’ll never feel bad anymore…”
Definitely not one of those days. Feels like I will be borderline bored forever. I know that’s not true, it’s a phase of the project, It’s all me really, I should plan better, I should be proactive, do more, fulfill my potential.
Don’t want to. Sighs.
Off to culture cells.
Monday, August 13, 2007
The Lab Wardrobe
I played against type today, I am wearing a skirt, pretty shirt and cute shoes. To Lab. It's a good thing I have a lot of computer work planned!
Ah dressing like a scientist. The bleach-proof scruffy eternally dreary clothes. To be honest, there is something to be said for jeans, t-shirt and sneakers, after all that takes care of the general ick factor of exposed skin in the animal room or the slight overall scariness of working with radioactivity. But how long can one go on dressing "like a scientist"? Company t-shirts, jeans from six seasons ago. I'm tired of it, I have a whole wardrobe that doesn't get worn enough.
I think the true revolution is the ballet flat. They are great! Closed toes, flat, comfortable and go with everything. Practical and attractive, imagine that, whole new worlds have opened up. Bringing on the new wardrobe...
Ah dressing like a scientist. The bleach-proof scruffy eternally dreary clothes. To be honest, there is something to be said for jeans, t-shirt and sneakers, after all that takes care of the general ick factor of exposed skin in the animal room or the slight overall scariness of working with radioactivity. But how long can one go on dressing "like a scientist"? Company t-shirts, jeans from six seasons ago. I'm tired of it, I have a whole wardrobe that doesn't get worn enough.
I think the true revolution is the ballet flat. They are great! Closed toes, flat, comfortable and go with everything. Practical and attractive, imagine that, whole new worlds have opened up. Bringing on the new wardrobe...
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