David Colquhoun facts for kids
Quick facts for kids
David Colquhoun
FRS MAE
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David Colquhoun in 2013
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| Born | 19 July 1936 Birkenhead, Cheshire, England
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| Awards | Humboldt Prize (1990) |
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| Thesis | The characterisation and adsorption of sensitising antibodies (1965) |
| Doctoral advisor | W.L.M. Perry W.E. Brocklehurst |
David Colquhoun (born 19 July 1936) is a British scientist. He is a pharmacologist at University College London (UCL). He has done important work on how our bodies' cells work. This includes how tiny channels in cells open and close.
He was a top professor of Pharmacology at UCL from 1985 to 2004. He was also the director of the Wellcome Laboratory for Molecular Pharmacology. In 1985, he became a Fellow of the Royal Society. This is a very high honor for scientists. Colquhoun also runs a website called DC's Improbable Science. On this site, he talks about why some ideas, like certain alternative medicines, are not based on good science.
Contents
Early Life and Education
David Colquhoun was born in Birkenhead, UK, on July 19, 1936. He went to Birkenhead School and Liverpool Technical College. He started as an apprentice pharmacist but wanted to do research instead.
He earned his first degree (BSc) in pharmacology from the University of Leeds. Then, he got his PhD from the University of Edinburgh. For his PhD, he studied how certain proteins called immunoglobulins attach to lung tissue. During his studies, he became very interested in statistics and random processes. These interests would shape his future research.
After his PhD, Colquhoun did more research at UCL from 1964 to 1969. He also wrote a book about statistics. Later, he worked at Yale University and the University of Southampton. He came back to UCL in 1979 and has been there ever since.
Scientific Discoveries
Colquhoun's research focused on how tiny "doors" in our cells, called ion channels, open and close. These channels control how signals move in our bodies. He also studied what makes these signals happen quickly.
Scientists Erwin Neher and Bert Sakmann invented a method called the patch clamp technique. This allowed researchers to watch single ion channels open and close. But these observations were often random. Colquhoun worked with a statistician named Alan G. Hawkes. Together, they created a special way to understand this random data. This helped them figure out how ion channels really work.
Colquhoun and Lucia Sivilotti have a website. It shares information about UCL's work on single ion channels. It also talks about how they use statistics in their research.
How Single Ion Channels Work
In 1977, Colquhoun and Hawkes made a prediction. They thought that ion channels would open in short bursts, not just one at a time. Later, experiments with Bert Sakmann proved this idea. This discovery helped scientists understand how certain drugs work. It helped them measure how strongly a drug binds to a cell and how well it causes a reaction.
A paper they wrote in 1985 was later called a "classic" by The Journal of Physiology. In 1982, Colquhoun and Hawkes published another paper. It explained the theory of these "bursts" of channel openings. They even showed an equation for the length of these bursts. This equation was so important it was put on a mug for a course!
It became clear that the length of these bursts controlled how quickly signals faded in the body. The exact relationship was figured out in 1998.
Understanding Missed Short Events
By 1982, the main ideas about single channel behavior were understood. But there was a problem. Recording equipment couldn't detect very short events, like openings or closings shorter than 20 microseconds. This made the channels seem to be open or shut for longer than they really were.
To use their statistical methods, they needed to know the true length of these events. In 1990, Hawkes and Jalali found a way to solve this. They found an exact solution for how long events actually lasted. This solution was complex at first. But in 1992, Hawkes and Jalali found a simpler way to use it.
This breakthrough allowed scientists to use a method called "maximum likelihood fitting." This method was put into a computer program called HJCFIT. This program has been very important for experiments ever since. The ways of describing these "apparent" open and shut times are often called HJC distributions.
Intermediate Shut States
Early research thought that cell receptors only had two states: open or shut. But when scientists studied the glycine receptor, they found something new. They found an "intermediate shut state." This state was between the resting state and the open state.
Later, this extra state was also found in the nicotinic acetylcholine receptor. In 2008, scientists found that some drugs, called "partial agonists," work differently than thought. They don't cause a weaker opening. Instead, they are less likely to move the receptor from its resting state to this intermediate shut state. The actual change from shut to open was similar for both strong and partial drugs. This new idea was confirmed by other scientists in 2009.
Statistics and Science
After working on single ion channels, Colquhoun became very interested in statistical inference. This is about how we draw conclusions from data. In 2014, he wrote a paper about how people often misunderstand p-values. A p-value is a number that helps scientists decide if their results are meaningful. His paper helped with a big discussion about how reliable scientific results are.
He wrote more papers exploring other ways to use statistics instead of just p-values. He showed that even a very small p-value (like 0.001) doesn't always mean a strong discovery. If an idea was very unlikely to begin with, even a small p-value could still mean a high chance of a false positive.
He suggested that scientists should not use words like "significant" or "non-significant." Instead, they should still report p-values and confidence intervals. But they should also include the "false positive risk." This helps everyone understand how likely it is that a result is just by chance. He suggested calculating the "minimum false positive risk" (FPR50). This can be done using special computer scripts or a web calculator.
