Genetic diseases are likely to be very difficult to cure. It is important, however, before any further explanation to define exactly what is meant by a 'genetic disease'; this could potentially mean: a disease caused by a single defective gene inherited from parents (e.g. cystic fibrosis); a disease which is contributed to by a large number of genes and which needs some form of environmental trigger (e.g. Crohn's disease, coronary heart disease); or a disease which results from genetic defects which are acquired during life (cancers).
It is only the first groups that at present is amenable to genetic treatment. Depsite this, attempts at gene therapy have been met with rather limited success. For example, in cystic fibrosis, the CFTR gene is defective - leading to among other problems recurrent severe chest infections - one method of therapy is to inhale virus particles genetically engineered to contain a functioning CFTR gene. This does improve chest problems, but as the lung cells die and are replaced, treatment has to be continuous as the replacement cells don't have functioning genes. It also doesn't help with the digestive and liver problems resulting from the disease.
The cause of Crohn's disease is not well understood, although it is related to the immune system and the genes that make everyone's immune system unique. However, it is not purely genetic as identical twins may not both get the disease, and similarly people with any genetic makeup can get the disease, although it is clear that particular genes do confer higher risk. This makes a potential cure based on genetics unlikely. At present, current treatments operate by reducing the immune response: steroids and other immunosuppresive drugs such as mesalazine and azathioprine are the mainstay - although there are other newer immunosupressants which may potentially be of benefit in very severe disease. It is likely that most advances in the near future are an evolution along this line.
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The brain stores information in the enormous network of interconnections between the individual brain cells. Information is learned by increasing and decreasing the importance of each of the billions of intrerconnections. To keep things simple, circuits that are active at the same time, tend to strengthen their interconnections - a microscopic version of Pavlov's dogs if you wish to think of it in that way.
The brain doesn't work like a calculator with discrete items of information - instead it integrates huge amounts of input and produces huge amounts of output - no particular input means much on its own, and no particular output will do much on its own. It doesn't produce exact answers, but approximates.
Some of the most difficult calculations it has to perform are of the control of movement - it has to convert the idea of moving a part of the body to a particular position, into a sequence of commands to the muscles, taking into account the limited axes and ranges and strengths of movement of the various joints. The equations that describe 'inverse kinematics' are pages long, and difficult for conventional comptuers to solve - yet the cerebellum (the small seperate part at the back of the brain) handles them with ease - the reason being the incredible interconnection between the cells. Each input cell may connect with 100,000 output cells, each of which may connect with 250,000 input cells - at the top of this picture is a rather splendind example of a
Purkinje Cell(one of the 'output' cells described above - notice the enormous number of branches used to receive all these inputs).