Biological clocks have sizeable effects on the performance of elite athletes. This conclusion was drawn by chronobiologists from the University of Groningen after studying the times achieved by swimmers in four different Olympic Games. Shifting the clock to reach peak performance at the right time could make the difference between winning and losing. The results were published on 8 October in the journal Scientific Reports.
‘In many sports, the differences between coming first or second, or winning no medal at all, are very small,’ explains Renske Lok, first author of the paper and former PhD student at the University of Groningen. ‘We wondered whether an athlete’s biological clock was playing a role.’ This clock determines our bodies’ daily rhythms: it regulates physiological characteristics such as core body temperature and blood glucose levels. ‘And we know that peak performance usually coincides with the peak in core body temperature,’ says Lok.
The dialogue between neurons is of critical importance for all nervous system activities, from breathing to sensing, thinking to running. Yet neuronal communication is so fast, and at such a small scale, that it is exceedingly difficult to explain precisely how it occurs. A preliminary observation in the Neurobiology course at the Marine Biological Laboratory (MBL), enabled by a custom imaging system, has led to a clear understanding of how neurons communicate with each other by modulating the “tone” of their signal, which previously had eluded the field. The report, led by Grant F. Kusick and Shigeki Watanabe of Johns Hopkins University School of Medicine, is published this week in Nature Neuroscience.
In 2016 Watanabe, then on the Neurobiology course faculty, introduced students to the debate over how many synaptic vesicles can fuse in response to one action potential (see this 2-minute video for a quick brush-up on neurotransmission). To
If you’ve eaten vegan burgers that taste like meat or used synthetic collagen in your beauty routine — both products that are “grown” in the lab — then you’ve benefited from synthetic biology. It’s a field rife with potential, as it allows scientists to design biological systems to specification, such as engineering a microbe to produce a cancer-fighting agent. Yet conventional methods of bioengineering are slow and laborious, with trial and error being the main approach.
Now scientists at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) have developed a new tool that adapts machine learning algorithms to the needs of synthetic biology to guide development systematically. The innovation means scientists will not have to spend years developing a meticulous understanding of each part of a cell and what it does in order to manipulate it; instead, with a limited set of training data, the algorithms are able