Occam's Rug?

Looking through the latest volume of the Annual Review of Biophysics I came across an interesting piece by Ido Golding: Decision making in living cells: lessons from a simple system. The article looks in great detail at the E. Coli and lambda bacteriophage system, showing that experimental results fit very nicely with theoretical and simulation based predictions. Instead of describing the paper in any detail (a job done very well by the paper itself) I thought I'd highlight some remarks made by Golding which caught my attention.

One of the papers core arguments (as per the title) is that much can be learned about decision making at the cellular level from a simple model system. However, the closing paragraph reads as follows:

...before applying the principles learned here to higher organisms, we must beware: As physicists studying living systems, we are always in jeopardy of over assuming universality. Against that ever-present temptation, one has to keep in mind the distinction between Occam’s razor and Occam’s rug: The former, of course, is the guiding rule for physicists, who will always choose the simplest, most universal explanation for an observed phenomenon. The principle of Occam’s rug, on the other hand, states the following: When studying a living system, a simple elegant narrative often implies that too much of the data was swept under the rug. In other words, always be wary of claims of simplicity and universality in biology.

I suspect the tension between Occam's razor and Occam's rug is at the heart of all biophysical models.

Mutual Information

Chapter 6 of Nelson introduces Shannon’s formula as a method for determining the information entropy contained within a string of words; an analogous problem to quantifying the entropy of a physical system. I was therefore not surprised to learn that Claude E. Shannon drew on much of the work of Boltzmann and Gibbs when devising his information theory. However, instead of focusing on this aspect of Shannon’s work (i.e. the connection with thermodynamics) I thought I’d give a brief overview of another of his legacies, namely, mutual information. What connection could this possibly have to biophysics I hear you ask? Well it is of critical importance to understanding the encoding, decoding, sending and receiving of information in the brain; a problem being tackled by biophysicists around the globe. (Not necessarily on a neurophysiology level but at a “we’re not scared of the maths” level.)

Shannon proposed that the key features of any information transmission system are:

where the noise source is modeled as an external rather than internal entity, but it is effectively the same thing.

As Nelson points out, the information entropy H for a distribution P(r) is a measure of the amount of information one can expect to gain on average from a single sample of that distribution. Suppose we have a distribution of Quantitatively this takes the form:

Lets take r to represent the received signal at the destination. This description of information only holds if there is perfect transmission, but all transmission introduces noise which in turn causes a loss of information so something is missing. One method of quantifying the noise entropy is to calculate how much of the response entropy comes from the variability in the response to the same signal, averaged across all signals. The entropy of responses to a given signal is given by:

and now averaged over all stimuli:

The mutual information is then given by I = H – H_noise which can be shown to be:

This result has a very nice property, note that if the signal and response are independent then P(r,s) = P(r)P(s) and since log(1) = 0 thus I = 0; which is what we would expect.

It should be stressed that there are many nuances to “optimal” information processing in our brains as different types of signals have different priorities. For example, while walking through a jungle at night, mistaking a cluster of leaves for a tiger is much safer than mistaking a tiger for a cluster of leaves. Bias and redundancy are as much a feature of our information processing system as optimizing mutual information.

A Neat Review Article- Quantum Dots Get Wet

I've been getting down to business writing my PHYS3900 pop science article on the contributions of physics to fluorescence microscopy (following on from my last post about nanodiamonds). Whilst reading about quantum dots I came across a `review' from Science Magazine and thought it was such a nice informative piece that I should post it here. It is quite readable and interesting without drowning in technical details (although there is a time and place for technicality!).

Quite briefly, quantum dots are small semiconductor structures which support delocalised electronic excitations, meaning that they can be fluorescent. The delocalisation ensures that the energy levels are determined by the size of the dot, rather than the atomic energy levels, so emitted light can take on a wide range of colours (no two dots are quite the same yet because they are self-assembled). They are attractive as fluorescent markers because of this property.

Drawbacks include cytotoxicity (ranging from severe to negligible, depending on the materials) and blinking (intermittent loss of fluorescence activity due to electron trapping).

I also found out that it is possible to make blue fluorescent nanodiamonds by coating them with a hydrophobic film.

My completed article will be posted soon!

Chapter 4 Exercises

4.2 (a-c only), 4.3, 4.7 . Due next friday (Sept. 9)

Consequences of the R^4 term in Hagen-Poiseuille relation

I seem to recall from last weeks class discussion that we found dividing a metabolic system into subsystems had an associated cost (a result of the B=kM^3/4 scaling law.) Implicit in this scaling law (as we saw in BIPH2000) are the properties of the circulatory system. In Chapter 5, Nelson uses the Hagen-Poiseuille relation of show that while two pipes with the same cross-sectional area doubles the flow of a single pipe (no surprise there), a single pipe with double the cross-sectional area has 4 times the flow, due to the R^4 term. Thus the relative about of energy needed to "drive" the flow (i.e. establish the pressure differential) will be less for larger pipes. This is perhaps the underlying physical cause for the cost of dividing a metabolic system.

[Not a fully formed idea but I thought I'd put it out there for discussion.]

Sugar Abuse

It's the wee hours of the morning and ScienceDaily has caught my eye yet again. What a treasure trove of weird and wonderful articles.

Asa Mackenzie is an associate professor of neuroscience at Appsala University who recently led a study on mice with inactive VGLUT (Glumate transporters), sugar and cocaine. Imagine that - mice doing blow.


As we all know, the brain has it's own way of rewarding us when we do exercise or if we eat something delicious etc - it gives us a good feeling. This good feeling is associated with the release of the neurotransmitter, dopamine. Illicit drugs can take advantage of this system and that's why (theoretically) is feels good to take drugs - "get high". Howoever, in comparison to the brain's rewards, cocaine etc, has effects which are too strong, and this gives rise to addiction. 

Dopamine has been observed to co-signal with glutamate (which is transported via VGLUT). As previously mentioned, mice which didn't have VGLUT (as well as the usual control group) were put on nutritious diet of sugar and cocaine. The study yeilded the following results: the mice with inactive VGLUT ate more (sugar and cociane, that is), and their memory show a huge increase in regards to places in the study environment associated with getting the sugar and cocaine. The non-VGLUT mice also showed hypersensativity (to the stimulants(?)) and their levels of dopamine showed a decrease. 


The research is significant in opening the door to future studies between VGLUT and its relationship with addiction. (Mackenzie, 2011)

Cocaine

It occurred to me while reading this that the part about the mice remembering where to get their goods made complete sense - obviously crack addicts know where to go get their fixes, otherwise they wouldn't have, and ergo, wouldn't be crack addicts. Furthermore, I'm interested to know how mice in general would react to stimulants such as cocaine and amphetamines - simultaneously cruel and hilarious. No mention of sugar-only, cocaine-only test groups were apparent in the source. 

Sucrose - table sugar

I read a book quite a while ago on sugar metabolism in the human body. While there are regulatory mechanisms to regulate the amount of fats and carbohydrates ingested, no such system exists to monitor sugar intake, as sugar (in the form we know it today, table sugar) in nature appears in such small concentrations, and is therefore supposed to comprise a minuscule portion of our diet.  Could this absence of a regulatory mechanism possibly contribute to enabling an addiction to sugar? 


One hopes not to see seedy crack smoking mice wobbling out of dark alley ways, noses bleeding with bags of table sugar in hand. 

Moves aside St.John's Wort

I came across this recently and thought it tied in nicely to a discussion we had in a BIPH meeting a few weeks ago, while Seth was absent, regarding mind-altering drugs for the treatment of depression/anxiety/ADHD. 

 Lactobacillus rhamnosus 

Canadian researchers from  the Alimentary Pharmabiotic Centre in University College Cork, and the Brain-Body Institute at McMaster University have recently uncovered from their clinical studies of feeding  mice probiotic bacteria,  Lactobacillus rhamnosus JB-1 (which is found as a preservative in many yoghurt products and has a high immunity against strong acids found in the gut), that levels of the hormone corticosterone, which is stress induced, were notably lower than those of mice in the placebo group.

 It was also found that the stress-related and anxiety and depression-related behaviours were reduced in the trial group. Other results included noticeable changes in the GABA neurotransmitter receptors when mice were fed the probiotics on a regular basis. ( Bravo & Cryan, 2011) 

The findings highlight pathways of communication between the gastrointestinal tract and the brain, and is significant in possible developments of microbial treatments of anxiety or depression (Cryan, 2011) The changes in GABA neurotransmitter receptor expression is significant in highlight the direct influence of the probiotics on brain chemistry.

The communication between the microbes, the gastrointestinal tract and the brain is referred to as microbiome-gut-brain axis. Future studies on this network may open the door for probiotic treatment of more psychiatric illnesses and disorders. (ScienceDaily, 2011) 

Serotonin

I found this very interesting, considering the nature of current treatments for anxiety and depression, such as SSRIs (selective serotonin re-uptake inhibitors) or SNRIs (Serotonin Norepinepherin Re-uptake Inhibitors), which essentially inhibit the re-uptake of serotonin (or norepinepherin) resulting in a higher extracellular concentrations of the either neurotransmitter, so more is actually in the synapse to be able to bind to the postsynaptic receptors.

So the concept of using the microbiome-gut-brain axis for treatment effectively means that the receptors will be altered instead of the neurotransmitter concentrations.