I am always blown away when a teacher tells me that something, that I would have previously considered heresy in the scientific sense, is now being considered as plausible due to new innovations of modern science. It really completes the circular nature of things. These ideas that seem common sense, we complicate a little bit. Then they become impractical. But we study further, and then they become inevitable. It’s a remarkable testament to human ingenuity that so many ideas follow this pattern.

Just last quarter Jean-Baptiste la Marck was someone who we looked at just last quarter as someone who imposed a foolish idea on our modern scientific view of descent with modification. He proposed that traits and attributes acquired by an individual would then be passed on to it’s offspring. We learned that this was not the case according to modern evolutionary theory. Evolution happens because a gene pool withing a species becomes sufficiently varied and eventually part of the species is split and isolated from the rest of the population. Through inbreeding, traits emerge over generations in an event called speciation from genes already present in the gene pool. If these traits are beneficial then these populations will survive and a new species is created.

A very specific notation was made here noting that traits acquired after the initial gene combination that results in the organisms DNA is inconsequential in the traits of the offspring.  LaMarck was proven incorrect. But my teacher told me about an emerging field in genetics called epigenetics in which genes can be turned on and off in response to the environment, and this can be passed on to future generations. Now he warned that this does not really mean that someone who has an arm cut off is not going to have 1 armed off-spring. If that were the case, LaMarck would never have been discounted. The idea is that stimulus that effects plascicity and neural connections, can in fact be directly passed down.

I looked into it and an interesting experiment was performed at MIT and published in the Journal of Neuroscience. Mice were genetically modified to have decreased brain activity and memory. They were then placed in a stimulating environment and given excersises to increase their memory. Now obviously this helped the mice as singular organisms, but the unexpected result was that the offspring which shared the genetic predisposition to decreased mental activity actually had retained the increased mental activity acquired by their parents.

I think that this has broad implications on the importance of nurture in conjunction with nature to give traits to organisms that are capable of lasting generations.

Not totally sure where this guy is headed, but he makes some pretty good points. Pablo Picasso said “All children paint like geniuses. What do we do to them that so quickly dulls this ability?” Wish it didn’t end with an iPhone endorsement.

I recently attended a lecture by the Chief Editor of Science News, Tom Siegfried here in Portland discussing probability and it’s uses and misuses science today. Every once in a while I see or hear a new idea that really sticks out to me as having a lot of large implications in the way things work.

I have never really found any interest in statistics or probability as it always appeared to me as an esoteric reduction of humanity into numbers in some sort of attempt to maximize profit margins. The mathematical persuit of misers.

It actually started with the philosopher Blaise Pascal, whom we all know is a gambling man. His friend wanted him to come up with a mathematical description of the probabilities in card games. Of course Pascal was happy to oblige, and what resulted after several generations of alterations is what we now come to know as Game Theory. The statistics that drive economic interactions between competing powers.

Pretty early on, people became interested in the applications of probabilities to modern science, especially within the last 100 years, as quantum theory has taken apart classical mechanics into something that can not be engaged with directly, but only with degrees of certainty. These degrees of certainty had convenient ties to the probabilistic work done driving the forces of economics, and so they were adopted unanimously across all scientific practices as research became less static.

Calculating what is referred to as a P-Value is an essential part of all modern scientific research, and this is the intriguing idea that was introduced to me. Read on below.

To understand a p-value it is important to understand something called a distribution curve, often referred to as a bell curve. This is kind of an anomaly really, much like the number pi or phi, or the Pythagorean theorem. It is something repeatedly seen as we analyse any number of things. It works like this. If I measured the weight of people in the state of Washington, and grouped them together, and made a bar graph for each weigh measured, I would have a graph that looks like the one at the top. There would be an average weight that is at the peak of the curve, and the number of people at the more extreme weights at each side of that average would taper off, and there would only be a few. It’s kind of rational when you think about it, but not intuitive when encountering people in small numbers like we normally do.

Now suppose that I measure the weight of people in Iowa, and get a similar bell curve, but the point on the bell curve is at a different weight than the one from Washington, suggesting that they are maybe 20 pounds heavier. This would create a similar shaped graph, but offset from the original, probably with some overlap.

Imagine that there is a factor that is effecting people in Iowa to be heavier than people in Washington, then I have to compare these to sets of data, and see where they overlap. I can do this by generating a formula for the bell curve, and using calculus to calculate the overlaping area under both curves. This is measured as a percentage of the area under the original curve, and the resulting number is called a P-Value.

So what does this P-Value tell us? Well let’s say that my hypothesis is that people in Iowa are more obese than people in Washington. Well I can’t measure every person in Iowa or Washington, but I can measure a large enough sampling to get data which will have a certain amount of overlap. Well if this is my hypothesis the P-Value tells me what the chances are, if my hypothesis is null, and there is no difference, that the measured difference would happen as a random event. This would make my hypothesis invalid.

For arbitrary reasons, when scientists first started using this they selected a maximum overlap for the null hypothesis to be 5 percent. If the overlap is more than 5 percent, then you cannot determine that your hypothesis is statistically significant. If it is less than 5 percent then you can say that the changes of random fluctuations causing this change in measurement is small enough that you can be reasonably sure that you have measured something that may confirm your hypothesis.

If this is the case and the overlap is less than 5 percent, then a study is deemed statistically significant. If you have ever heard the statement “Study’s show that this may significantly reduce your risk of ‘This-Or-That’ “, they are using the fact that the data is only measurable, and the significance does not imply the degree to which your risk is reduced. Tricky eh?

Now there is a problem that will keep you up at night which is summarized in the example below from the Siegfried lecture.

“Now suppose, based on previous testing, that experts have established that about 5 percent of professional baseball players use steroids. Now suppose you test 400 players. How many would test positive?

• Out of the 400 players, 20 are users (5 percent) and 380 are not users.

• Of the 20 users, 19 (95 percent) would be identified correctly as users.

• Of the 380 nonusers, 19 (5 percent) would incorrectly be indicated as users.

So if you tested 400 players, 38 would test positive. Of those, 19 would be guilty users and 19 would be innocent nonusers. So if any single player’s test is positive, the chances that he really is a user are 50 percent, since an equal number of users and nonusers test positive.”

I cannot think of very many wholesome uses for this device.

Morphine is a painkiller derived from the poppy plant. The naturally derived form of morphine from the poppy plant is what defines it as an opiate. For the last 200 years morphine has been used as one of the most effective painkillers we know of, interacting directly with the central nervous systems pain receptors.

Morphine as a very effective drug, in part because of its shape. Notice in the above figure, all the ring structures involved. There are essentially 5 rings, which all work together to lock the geometry of the molecule in place. This locking is very important, because it closely matches the shape of the pain receptors(which are actually meant to accept endorphins and have a similar structure) , which accept the nitrogen (Its the “N” on the diagram) as a base, effectively breaking its ring.

There has historically been one big problem with morphine. It’s cripplingly addictive. It you have ever had surgery, and been prescribed codeine afterwards, there is a reason for that. Codeine and Percocet are less effective forms of morphine, synthesized artificially, which gives them the classification Opioids. Although they are still very effective painkillers, they are very specifically made to wean people off of the heavy doses of morphine required for surgery.

We have not always been so lucky. In the late 1800s morphine use was on the rise, and people coming out of hospitals were hopelessly addicted. Around 1895 the German company Bayer released a substitute for morphine, that would provide similar effects to morphine, but without the addictive properties. Such a wonderful and heroic drug, could only have one name. Heroin. Of course in the late 1800s there was a lot of guess work as to the final outcome of these things, and we now know that heroin is not only far more potent than morphine, but it is way more addictive.

So whats the difference? It looks like on the picture there is just a couple ‘O’ things  tacked on. Well to see the difference we will go over the structure briefly and what it all means. Everywhere there is a line, that is a chemical bond containing 2 electrons. At the end of every line is an implied Carbon atom. We don’t actually write ‘C’ because it would take forever, and we have precious little time. Every where that there is something that is not carbon, there is a letter signifying which atom is there. O=oxygen, N=nitrogen, H=hydrogen. Those are the basic building blocks we are working with here.

Morphine has 2 alcohol groups (OH) on it. It gives the perfect fit for our brain as it requires this acidic group to be activated. If we could just put the morphine directly into our brain then we would be set. But there’s a problem. Our brain absorbs chemicals through a semipermeable membrane called the Blood Brain Barrier. This membrane lets through certain substances and keeps out others. By and large, this membrane prefers to let through hydrophobic (water hating) molecules.

What molecules hate water? Well there is a general rule in chemistry that ‘Like dissolves like’. Water is a polar molecule, which means that it is not electrically balanced. It has a large electronegative oxygen atom and 2 hydrogen atoms projecting out from it in a sort of a triangle. So we want the opposite for a water hating molecule to cross that membrane. We want a nonpolar group.

Well both of these molecules are polar, but one is significantly less polar than the other. The hydrogen molecules attatched to the oxygens on morphine, for reasons I wont go into here, polarize the molecule, making it less hydrophobic, and decreasing the amount that can cross that membrane. Heroin, however, has what is called an ester group in place of the OH, which has no hydrogens-oxygen bonds, and so has a reduced polarity. This makes it perfect for crossing unhindered across the blood brain barrier and into our cerebralspinal fluid en route to the brain.

Once the heroin has crossed that barrier it reacts with chemicals in the cerebralspinal fluid to convert the esters back into alcohol groups, effectively giving us the morphine molecule back again, but in larger doses to the brain. This would have been good to know in the early 1900s when countless people began using it to curb their addictions ranging from alcohol and cocaine to morphine.

One interesting side note, heroin usually comes as a hydrochloride salt, with the name diacetylmorphine hydrochloride. The reason for this is that the Nitrogen molecule often acts as a base because it has 2 lone electrons associated with it. This makes it partially reactive and hard to isolate. In the presence of HCl however, the base attaches to the hydrogen, and balances with the Chloride counter ion. This gives a solid that can be isolated with great amounts of purity. Note that if you pull the hydrogen away from the nitrogen, a cracking sound can be heard (Where crack got its name) as the pure form of the base is freed. In its pure form as in the illustration above, Heroin and morphine are freebases.

Better living through chemistry.

I started my first batch of beer last night with a recently acquired home brew set-up. It took about 3 hours start to finish, and the end product one month from now, will be 5 gallons of chocolate porter. It came from a basic starter recipe the guy at the brew shop recommended to me. Here’s the rundown of the process in the manner to which my organic chemistry class has made me accustomed.

Synthesis of ethanol by fermentation of malted barley

Purpose: Sugars from malted barleys will be reacted with activated yeast and fermentation will convert the sugars into a delicious ethanol containing beverage. An analysis of the density before and after the fermentation process will be used to calculate the specific gravity and the alcohol content. A percent yield will be calculated from the expected yield of 5 gallons, and the product will be analyzed by IR spectroscopy before being consumed by multiple bros.

Reagents:

6.6 lbs Unhopped Amber Malt Syrup – Viscous molasses like syrup extracted by kilning germinated barley.

1 dummy proof grain kit – Assembled by instructor(guy at home brew shop) (Consists of 0.25lb Roasted Barley, 0.25lb Chocolate Malt, 0.75lb 120L Crystal Malt)

2 oz. Fuggles Hops – Stinky, sticky green flowers

1 oz. Yakima Golding Hops – Stinky, sticky green flowers

0.75 cups corn sugar

1 packet safale yeast

Procedure:

Heat 2 gallons water to 150 degrees F. Add dummy proof grain kit to water in grain steeping bag, and continue to heat at constant temperature for 30 min, constantly monitoring temperature to avoid the release of tanins.

Remove grains from water, and bring to a gentle boil, and remove from heat, stirring in 1 cup of amber malt syrup. Add 2 ounces of fuggles hops in steeping bags, and return to a boil. Heat mixture at reflux taking care not to boil over, for approximately 60 minutes, adding 1 ounce Yakima golding hops for last 5 minutes of reflux.

Remove from heat and stir in remaining malt syrup, making sure to get it all over your hands and clothes.

Once the mixture is stirred completely, fill well sanitized carboy with 2 gallons of ice cold distilled water. Add hot wort mixture to the carboy using a sanitized funnel, and top with 1 gallon of ice cold distilled water.

Mix thoroughly and, using a small sample of the mixture, measure the specific gravity using a hydrometer. Record the value here.

Place carboy in bathtub full of ice-water, and monitor temperature carefully. Once temperature has dropped below 75 degrees F, add the packet of yeast, while swirling to airate the mixture. Fit the carboy with a sanitized air lock via a blow-off tube to release carbon dioxide.

Allow 2 weeks fermentation between 60-75 degrees F. Once fermentation slows, take a sample and record the specific gravity. Subtract this number from the original and multiply by 0.125 to obtain the alcohol content in percent by volume.

Bring 2 cups water to a boil and add 3/4 cups of corn sugar. Boil for 5 minutes. Place in a clean, sanitized carboy. Using a sanitized siphon, siphon the fermented mixture in on top of the sugarwater, taking care not to splash and filling from the bottom. Once siphoning is complete, fill and cap bottles with the mixture.

Allow 2 weeks for natural carbonation of corn sugar by yeast.

Take IR of the final product, and calculate a percent yield based on 5 gallon theoretical yield.

Chill remaining product and consume with nachos in the presence of bros.

I am currently in the fermentation stage, and it’s bubbling like crazy. I still have plenty of time to fowl this undertaking and receive my legendary low yield of product. Will post data, observations and conclusion section when the process is complete.

Here’s a shot of the sudzy crudy wort, just doin its thang.