Nobel Prize in Physiology and Medicine was awarded for cell package delivery system - vesicles. Membranes not only separate cells from outside but also create separate compartments inside the cell - most notably nucleus and mitochondria - but there is also long series of something that looks almost like a tube system. Ribosomes stick to part of it and produce proteins. Those proteins end up inside and can be transported inside but the system is long and twisted. Just like it's faster to take a ferry from Gdańsk to Stockholm then drive all around the Baltic Sea it is faster to send a stuff packaged from one compartment to the other. In a vesicle. That transport is highly regulated and used for many different things. That's how cells absorb the food from outside, how they spit out and absorb hormones and how they transport transmembrane proteins. All the countless ours I spent learning how the phagocytosis and endoplasmic reticulum and Golgi apparatus worked I never thought about people who made all those discoveries. It's funny how at some point things like that become basic knowledge of the subject - something you just know.
Prof James Rothman, from Yale University, found proteins embedded in the vesicles which act as the docking mechanism meaning the cargo is released in the correct location. Prof Randy Schekman, from the University of California at Berkeley, discovered the genes which regulated the transport system in yeast. He found that mutations in three genes resulted in a "situation resembling a poorly planned public transport system". Prof Thomas Sudhof, originally from Germany but now at Stanford University in the US, made breakthroughs in how the transport system works in the brain so that neurotransmitters are released at the precise time. I was disappointed at the journalist disappointment because this is a very important system in the cell and the basic science Nobels are the ones touching the most important subjects.
Nobel Prize in Physics was awarded to people who theorized existence of Higgs boson -
Peter Higgs of the University of Edinburgh, UK, and François Englert of the Free University of Brussels, Belgium, have won for developing the theory of how particles acquire mass. The theory is 50 years old but the experimental confirmation is brand new - not even a year old - so the delay in the announcement wasn't that surprising. Ever since few spectacular mistakes at the beginning Nobel committee has preference for waiting long enough to see that no one disproves it and that multiple sources can repeat the results. Still this was a big thing in physics and a long awaited one. And if they didn't do it now there might've not been another chance. Both laureates are in their 80s and Nobels are not given to dead people. I'm most disappointed in comparisons of the problems of finding Peter Higgs for comment during his vacation with the search for Higgs boson.
The Nobel Prize in Chemistry went to theoretical chemists for devising computer simulations to understand chemical processes. Michael Levitt, a British-US citizen of Stanford University; US-Austrian Martin Karplus of Strasbourg University; and US-Israeli Arieh Warshel of the University of Southern California will share the prize. Modelling molecules is becoming a bigger and bigger thing in drug production where new molecular compounds are first tested for possible uses and molecular interactions before spending money on costly synthesis. It can also help predict protein shape and function which helps to understand how cell processes actually work. Those programs use the equations of quantum physics to simulate reactions as closely to reality as possible. It of course requires vast amounts of computing power to describe every electron and atomic nucleus so these detailed models are limited to small molecules with just a few atoms. To model larger molecules we still need to use classical computer models but they do not include descriptions of molecules' energy states, which is vital for simulating reactions. Still they both allow us to sift faster through the possibilities then any RL experiment and concentrate on most plausible possibilities making discoveries faster and drugs (just a little) cheaper.