From an extract of the book The invisible sex: Uncovering the true roles of Woman in Prehistory (review in Nature 3rd of May issue).
"science is not truth; it is, instead, a method for diminishing ignorance"
Showing posts with label opinion. Show all posts
Showing posts with label opinion. Show all posts
Friday, May 18, 2007
Monday, May 07, 2007
Evolution and medicine
Catriona MacCallum, an editor at PLoS Biology has posted the following essay (being PLoS, it is available to everybody) about medicine and evolution.
According to the article, physicians do not get much of a training in evolution as a method to study the origin of diseases. That is because most of the training of physicists is not to make them good scientists but to make them good at treating patients. Quoting the article: "does a mechanic need to understand the origins, history and technological advances that have gone into the modern motor vehicle in order to fix it?".
This approach is not entirely wrong and once can treat things that are the result of an evolutionary process without having to spend too much time studying evolution. A different thing is when the disease is not a result of evolution but they are evolution itself. They never mention cancer in the article but cancer and infectious diseases are clear cases of diseases in which evolution should be dealt with if the disease is to be cured or even contained. Without an understanding of evolution a physician will be unable to understand how the bacteria or cancer cells will react and evolve when a treatment is used or what phenotypical traits are more likely to be evolved and thus cause problems to or be exploited by the medical community.
According to the article, physicians do not get much of a training in evolution as a method to study the origin of diseases. That is because most of the training of physicists is not to make them good scientists but to make them good at treating patients. Quoting the article: "does a mechanic need to understand the origins, history and technological advances that have gone into the modern motor vehicle in order to fix it?".
This approach is not entirely wrong and once can treat things that are the result of an evolutionary process without having to spend too much time studying evolution. A different thing is when the disease is not a result of evolution but they are evolution itself. They never mention cancer in the article but cancer and infectious diseases are clear cases of diseases in which evolution should be dealt with if the disease is to be cured or even contained. Without an understanding of evolution a physician will be unable to understand how the bacteria or cancer cells will react and evolve when a treatment is used or what phenotypical traits are more likely to be evolved and thus cause problems to or be exploited by the medical community.
Friday, May 04, 2007
Cell article on science blogs
Blogs as a way to communicate science. This is quite an unusual topic for Cell that, as opposed to Science and Nature journals, devotes less space to the non-technical side of science. For those of you that are subscribed, the article is here.
According to the article there are approximately 20000 blogs with the label 'science'. That is quite an impressive number since most of my colleagues seem to be doing lots of things but not blogging. It seems that most of these science blogs are actually about pseudo science which would be the number of more conventional science blogs to around 1200 (always according to sources cited in the article). These are generally blogs like mine (of course in many cases better written and updated more often) which deal with fairly specific issues in a specific field of science.
These science blogs can be just about anything. Many do like I do and comment (what we personally find) interesting stuff in our own field of research that we find reading, mostly, papers and journals. Some do also include bits about their own lifes and produce some sort of hybrid between the conventional blog (understood as a personal diary) and the scientific blog. Some take the idea of science blog a step further and every day record their latest results online (although in some fields, like biology, this behaviour seems to be quite rare due to the extreme levels of competition between experimental biologists).
Why would any one start a science blog? On top of the conventional reasons why people start a blog (and weighted down by the fact that most of us do not carry sizable audiences) is the thought that when you write something with the expectation (as unlikely as it might be) that someone will read it that surely helps to clarify that something in your mind.
According to the article there are approximately 20000 blogs with the label 'science'. That is quite an impressive number since most of my colleagues seem to be doing lots of things but not blogging. It seems that most of these science blogs are actually about pseudo science which would be the number of more conventional science blogs to around 1200 (always according to sources cited in the article). These are generally blogs like mine (of course in many cases better written and updated more often) which deal with fairly specific issues in a specific field of science.
These science blogs can be just about anything. Many do like I do and comment (what we personally find) interesting stuff in our own field of research that we find reading, mostly, papers and journals. Some do also include bits about their own lifes and produce some sort of hybrid between the conventional blog (understood as a personal diary) and the scientific blog. Some take the idea of science blog a step further and every day record their latest results online (although in some fields, like biology, this behaviour seems to be quite rare due to the extreme levels of competition between experimental biologists).
Why would any one start a science blog? On top of the conventional reasons why people start a blog (and weighted down by the fact that most of us do not carry sizable audiences) is the thought that when you write something with the expectation (as unlikely as it might be) that someone will read it that surely helps to clarify that something in your mind.
Friday, April 27, 2007
evolution of multicellularity
A friend of mine has found this interesting essay in Nature entitled "Unity from conflict" that deals with the evolutionary mechanisms that allowed the emergence of multicellular organisms.
The problem of how multicellular organisms came about from single cells is quite intriguing. I heard from Lewis Wolpert that this is probably the most important of the seven transitions in evolution as described by Maynard Smith and Szathmáry in their book. In retrospect it is clear that such a transition is possible (since we are here) but, why did it happen?
Paul Rainey (whom I suspect might be a microbiologist) seems to be suggesting that with the right mutation rate (or right mutation bias) multi-cellularity should be possible. Organisms such as myxobacteria seem to be able to alter their mutation rate in response to stress in the environment so I guess that evolution fiddling with the right mutation rate is not unreasonable. In any case I'd rather see it from the point of view of my friend, that is, a harsh environment does enforce cooperation in a way that makes cheating very costly. In reality I would imagine that other factors such as the immune system (that in a way can be though of a police on the lookout for cheaters) or the fact that cells in a multicellular organism share the same DNA could also help explain why there is not that much cheating in our bodies.
This article is quite interesting for any one interested in cancer. At the end of the day a cancer cell is a normal cell that due to genetic or epigenetic reasons stops cooperating. Once they evolve the means to avoid the immune system and other mechanisms designed to maintain homeostasis I would imagine that the life expectancy of a tumour cell should be rather short (necrosis, running behind in the evolution game or due to a poor microenvironment) and thus crime might not pay, at least in the mid/long term (which still would leave room for a benefit in the short term that would be enough to kick-start somatic evolution).
It should be possible using a computational model to demonstrate that an aggressive microenvironment would favour cell cooperation. A mutlicellular organism in which individual cells suffer when exposed to the exterior would evolve a morphology that would minimise the interface with the outside world. it would be also quite likely that a niche of stem cells would evolve to be in charge of generating the cells in this interface that would be in need of constant repair and maintenance. That is what happens in places in which the environment is hostile to cells like the colon or the skin. If cells in the model are allowed to cheat (by means of mutations leading cells to try to avoid being part of the interface if that is their role) that would presumably affect negatively the overall fitness of the organism. However I am not sure that this would rule out other explanations for the evolution of multicellular organisms.
The problem of how multicellular organisms came about from single cells is quite intriguing. I heard from Lewis Wolpert that this is probably the most important of the seven transitions in evolution as described by Maynard Smith and Szathmáry in their book. In retrospect it is clear that such a transition is possible (since we are here) but, why did it happen?
Paul Rainey (whom I suspect might be a microbiologist) seems to be suggesting that with the right mutation rate (or right mutation bias) multi-cellularity should be possible. Organisms such as myxobacteria seem to be able to alter their mutation rate in response to stress in the environment so I guess that evolution fiddling with the right mutation rate is not unreasonable. In any case I'd rather see it from the point of view of my friend, that is, a harsh environment does enforce cooperation in a way that makes cheating very costly. In reality I would imagine that other factors such as the immune system (that in a way can be though of a police on the lookout for cheaters) or the fact that cells in a multicellular organism share the same DNA could also help explain why there is not that much cheating in our bodies.
This article is quite interesting for any one interested in cancer. At the end of the day a cancer cell is a normal cell that due to genetic or epigenetic reasons stops cooperating. Once they evolve the means to avoid the immune system and other mechanisms designed to maintain homeostasis I would imagine that the life expectancy of a tumour cell should be rather short (necrosis, running behind in the evolution game or due to a poor microenvironment) and thus crime might not pay, at least in the mid/long term (which still would leave room for a benefit in the short term that would be enough to kick-start somatic evolution).
It should be possible using a computational model to demonstrate that an aggressive microenvironment would favour cell cooperation. A mutlicellular organism in which individual cells suffer when exposed to the exterior would evolve a morphology that would minimise the interface with the outside world. it would be also quite likely that a niche of stem cells would evolve to be in charge of generating the cells in this interface that would be in need of constant repair and maintenance. That is what happens in places in which the environment is hostile to cells like the colon or the skin. If cells in the model are allowed to cheat (by means of mutations leading cells to try to avoid being part of the interface if that is their role) that would presumably affect negatively the overall fitness of the organism. However I am not sure that this would rule out other explanations for the evolution of multicellular organisms.
Tuesday, March 13, 2007
Columbus workshop and interactions with life scientists
Being a workshop on mathematical biology one of the issues we all face here is how to work with life scientists and thus one of the panel session yesterdays was precisely about that.
It seems that there are different kind of problems theoreticians might find when dealing with clinicians and experimentalists depending on a number of factors:
It seems that there are different kind of problems theoreticians might find when dealing with clinicians and experimentalists depending on a number of factors:
- What kind of people are they? Are they 'math-skeptic'? do they have affinity towards theory?
- Do you want them to share their expertise with you or do you want to influence the experiments they perform so they can be used in your theoretical model? The latter is significantly more difficult.
- Do you work with biologists or with physicians? There is a real difference between the average PhD and the average MD that does some research on the side when it comes to understand the usefulness of theory.
Wednesday, December 20, 2006
Quote of the week
Maybe this will start a new trend in this blog: quotes. I was recently rereading some old issues of Nature and found this article in the careers section. It is a nice article in which the authors give an alternative view to that of this other article of how long and hard should a PhD student work. According to the original view a researcher should work all the time. According to this other alternative view some scientists have many of the weaknesses commonly associated with humans and thus this approach is likely to be useless.
They cite this anecdote from Ernest Rutherford. It seems that he found a student working late on an evening and asked him if he also worked in the mornings. The student answered that that is what he usually did and Rutherford then asked "But, when do you think?". Some times I think to myself that my best ideas usually come in the most unexpected places and circumstances. Now I think that I never had any good idea while in the office in front of the computer. Since now I am off for Xmas holidays there is a chance I will have time for some good ideas.
They cite this anecdote from Ernest Rutherford. It seems that he found a student working late on an evening and asked him if he also worked in the mornings. The student answered that that is what he usually did and Rutherford then asked "But, when do you think?". Some times I think to myself that my best ideas usually come in the most unexpected places and circumstances. Now I think that I never had any good idea while in the office in front of the computer. Since now I am off for Xmas holidays there is a chance I will have time for some good ideas.
Tuesday, November 28, 2006
Speakers in Step conference
It has been a while since I came back from the Step conference in Brussels and I guess it is time to say something about some of the speakers I had the chance of listening to. Probably the most interesting ones from my highly subjective point of view were James Bassingthwaighte (University of Washington), Brian Goodwin (former Santa Fe Institute Faculty, now at Schumacher College) and Denis Noble (Oxford).
This Step conference was not meant to be about science per se so the talks were definitely not of a technical nature. James introduced the Physiome project which, as you might know, is about putting together all the current and future knowledge about the human phisiology with
the aim of improving health care. The ideal result would be a giant simulation of the human phisiology that could behave like a real whole organism. Such system would allow physicians and other researchers to test therapies quickly and without nasty side effects
and study 'what if' scenarios.What James thinks we need are:
* Training (No use of sophisticated systems if physicians don't use them)
* Databasing
* Standards (Too many groups out there and no way to compare or integrate their work)
* Modelling archives (I got a nice model, where do I put it for other people to play with?)
* Modelling tools
All in all a nice and light introductory talk. Everything he mentioned is quite reasonable although I am not sure if it is realistic to expect any of these things happening in the short term. People so far seem to be happy happy to come with their own models and not much effort is done to see if the results of one model are consistent with the results of the model of a different group.
Next talk came from Brian Goodwin who, although use to be in the Santa Fe Institute is know a professor of 'holistic science' (which looks quite a scary name for a professorship). The theme of his talk? Computational biology: a clash of cultures. The part of the talk which I found more interesting was when he dealt with the ambiguity of languages. Human languages are ambiguous and the meaning of a sentence gets shaped as we speak. This seems to be a good analogy to understand the language of genes which is also ambiguous (which is nice if you want to evolve it). In his view both human and gene languages have the property that are the best compromise between the effort that the speaker has to make to convey a message and the
effort of the listener. This is an interesting idea although I guess that proving it might be quite complicated (note to my self, should take a look at what has been published about this).
The talk from Denis Noble was also interesting despite the fact that his major point was: I have a new book ("The music of life") go and buy it (which I might do). He made a number of points:
1. There is no gene for function (no objections to that)
2. Transmission of information is not just one way (same here)
3. DNA is not the only transmitter of inheritance (heard that before)
4. Law of relativity in biology: there is no privileged level of causality. Message to Dawkins: the gene is not that important.
5. There is no genetic programme (message to Monod this time).
6. Actually there are no programmes at any level
7. ...and that means not even at the brain level
Thursday, November 09, 2006
The Step conference
I have just returned from my trip to Brussels for the Step conference in which a Physiome project was discussed. We had talks from some very nice speakers about which I will write in another post.
The Physiome project (or at least what I understood about it after being exposed to the idea for the very first time during this conference) is a highly ambitious project (and that is probably an understatement) whose aim is to integrate all the current and future knowledge about the human physiology. The idea is thus a multiscale modular framework in which all the models about the different parts of the human physiology could be integrated. Such a model would have a tremendous impact on our understanding of physiology, let alone the potential benefits for pharmaceutical companies. For all of you who have any experience doing modeling of biological processes I guess I don't need to tell you how (let's understate it once again) challenging this could be. In any case I am fine with any (extremly) difficult project as long as the intermediate steps are worth something.
In my opinion, the guys in the Step project should aim at something quite modest such as some system by which modelers can integrate just a few models together so different groups can check the consistency of their models and their assumptions. This process will probably take a long while but eventually most modellers will be used to think of their models not in isolation but as something that has to make sense in the context of all the models being developed elsewhere. There should be some infrastructure so the models can be shared between researchers and some protocols and interfaces between models at different scales or across the same scale (say molecular, cellular or tissue) so there can be integration.
One of the speakers mentioned that the keywords in this project are multiscale and modularity. I suggest taking a look at the field of software engineering in which different groups and companies work in different modules and at different levels of abstraction. The software produced is expected to work with other software modules. Of course the complexity to manage is different in the Physiome project but I still think it would be a good starting point.
The Physiome project (or at least what I understood about it after being exposed to the idea for the very first time during this conference) is a highly ambitious project (and that is probably an understatement) whose aim is to integrate all the current and future knowledge about the human physiology. The idea is thus a multiscale modular framework in which all the models about the different parts of the human physiology could be integrated. Such a model would have a tremendous impact on our understanding of physiology, let alone the potential benefits for pharmaceutical companies. For all of you who have any experience doing modeling of biological processes I guess I don't need to tell you how (let's understate it once again) challenging this could be. In any case I am fine with any (extremly) difficult project as long as the intermediate steps are worth something.
In my opinion, the guys in the Step project should aim at something quite modest such as some system by which modelers can integrate just a few models together so different groups can check the consistency of their models and their assumptions. This process will probably take a long while but eventually most modellers will be used to think of their models not in isolation but as something that has to make sense in the context of all the models being developed elsewhere. There should be some infrastructure so the models can be shared between researchers and some protocols and interfaces between models at different scales or across the same scale (say molecular, cellular or tissue) so there can be integration.
One of the speakers mentioned that the keywords in this project are multiscale and modularity. I suggest taking a look at the field of software engineering in which different groups and companies work in different modules and at different levels of abstraction. The software produced is expected to work with other software modules. Of course the complexity to manage is different in the Physiome project but I still think it would be a good starting point.
Friday, October 06, 2006
Recap from Lyon (II)
Philip Maini is one of the most entertaining speakers (entertaining in the good sense, of course) in the European biomathematical community. Prof. Maini is the director of the Centre of Mathematical Biology at Oxford University and gave in Lyon a talk entitled "Modeling aspects of cancerous tumour dynamics".
The modeling aspects he mentions are three different projects:
1) The first project, in which he collaborates with people like Gatenby (Arizona) and Gavaghan (Oxford) studies the acid mediated invasion hypothesis.
According to (my interpretation of) this hypothesis, when tumour cells lack oxygen and start to starve then a mutation might appear that would make some cancer cells switch to what is called glycolitic phenotype. This means that these cells have an alternative metabolism that works without oxygen and that is not as efficient as the regular one. The reason why this alternative phenotype has a chance of success is because the waste produced (galatic acid) can be used to degrade the extra cellular matrix and lead to invasion of other tissue. Gatenby, Gavaghan and Maini came with a model in which tumours contain cells with the glycolitic phenotype. The results is that tumours are not benign and that an possible explanation for the existence of necrotic cores (material generated when cells die disorderly because of starvation) can be the result of too much acidification of the environment, even for acid-resistant glycolitic-type tumour cells.
2) Metabolic changes during carcinogenesis. Also with Gavaghan and Gatenby and referring to research covered by a paper in Nature reviews cancer (vol 4, 891-889, 2004). They study somatic evolution in a system in which tumour cells can be of one of three different types: hyperplastic, glycolitic or acid-resistant. These cells inhabit the space of a 2D lattice in which there is oxygen, glucose and hydrogen that diffuse in a continuous manner. Altering the reach and concentration of these elements leads to different numbers of cells displaying one or the other phenotype.
For me this is a good place in which to see how game theory could be used to study the interactions of different players (cancer cells) using different strategies (the different phenotypes) to maximise their payoff from the environment (O,H,glucose).
3) Together with Benjamin Ribba (Lyon, organiser of the workshop and one guy I am working with as of lately) Maini works on a multiscale model on which to study the differences between the vasculature generated by the normal process of vasculogenesis and the ones generated by tumour cells capable of angiogenesis. One of the conclusions he mentioned: don't trust parameters.
The modeling aspects he mentions are three different projects:
1) The first project, in which he collaborates with people like Gatenby (Arizona) and Gavaghan (Oxford) studies the acid mediated invasion hypothesis.
According to (my interpretation of) this hypothesis, when tumour cells lack oxygen and start to starve then a mutation might appear that would make some cancer cells switch to what is called glycolitic phenotype. This means that these cells have an alternative metabolism that works without oxygen and that is not as efficient as the regular one. The reason why this alternative phenotype has a chance of success is because the waste produced (galatic acid) can be used to degrade the extra cellular matrix and lead to invasion of other tissue. Gatenby, Gavaghan and Maini came with a model in which tumours contain cells with the glycolitic phenotype. The results is that tumours are not benign and that an possible explanation for the existence of necrotic cores (material generated when cells die disorderly because of starvation) can be the result of too much acidification of the environment, even for acid-resistant glycolitic-type tumour cells.
2) Metabolic changes during carcinogenesis. Also with Gavaghan and Gatenby and referring to research covered by a paper in Nature reviews cancer (vol 4, 891-889, 2004). They study somatic evolution in a system in which tumour cells can be of one of three different types: hyperplastic, glycolitic or acid-resistant. These cells inhabit the space of a 2D lattice in which there is oxygen, glucose and hydrogen that diffuse in a continuous manner. Altering the reach and concentration of these elements leads to different numbers of cells displaying one or the other phenotype.
For me this is a good place in which to see how game theory could be used to study the interactions of different players (cancer cells) using different strategies (the different phenotypes) to maximise their payoff from the environment (O,H,glucose).
3) Together with Benjamin Ribba (Lyon, organiser of the workshop and one guy I am working with as of lately) Maini works on a multiscale model on which to study the differences between the vasculature generated by the normal process of vasculogenesis and the ones generated by tumour cells capable of angiogenesis. One of the conclusions he mentioned: don't trust parameters.
Subscribe to:
Posts (Atom)