Molecular dynamics of cyclically contracting insect flight muscle in vivo

Flight in insects--which constitute the largest group of species in the animal kingdom--is powered by specialized muscles located within the thorax. In most insects each contraction is triggered not by a motor neuron spike but by mechanical stretch imposed by antagonistic muscles. Whereas 'stretch activation' and its reciprocal phenomenon 'shortening deactivation' are observed to varying extents in all striated muscles, both are particularly prominent in the indirect flight muscles of insects. Here we show changes in thick-filament structure and actin-myosin interactions in living, flying Drosophila with the use of synchrotron small-angle X-ray diffraction. To elicit stable flight behaviour and permit the capture of images at specific phases within the 5-ms wingbeat cycle, we tethered flies within a visual flight simulator. We recorded images of 340 micros duration every 625 micros to create an eight-frame diffraction movie, with each frame reflecting the instantaneous structure of the contractile apparatus. These time-resolved measurements of molecular-level structure provide new insight into the unique ability of insect flight muscle to generate elevated power at high frequency.     

Dopamine responses comply with basic assumptions of formal learning theory.

According to contemporary learning theories, the discrepancy, or error, between the actual and predicted reward determines whether learning occurs when a stimulus is paired with a reward. The role of prediction errors is directly demonstrated by the observation that learning is blocked when the stimulus is paired with a fully predicted reward. By using this blocking procedure, we show that the responses of dopamine neurons to conditioned stimuli was governed differentially by the occurrence of reward prediction errors rather than stimulus-reward associations alone, as was the learning of behavioural reactions. Both behavioural and neuronal learning occurred predominantly when dopamine neurons registered a reward prediction error at the time of the reward. Our data indicate that the use of analytical tests derived from formal behavioural learning theory provides a powerful approach for studying the role of single neurons in learning.     

A low level of extragalactic background light as revealed by gamma-rays from blazars

The diffuse extragalactic background light consists of the sum of the starlight emitted by galaxies through the history of the Universe, and it could also have an important contribution from the 'first stars', which may have formed before galaxy formation began. Direct measurements are difficult and not yet conclusive, owing to the large uncertainties caused by the bright foreground emission associated with zodiacal light. An alternative approach is to study the absorption features imprinted on the gamma-ray spectra of distant extragalactic objects by interactions of those photons with the background light photons. Here we report the discovery of gamma-ray emission from the blazars H 2356 - 309 and 1ES 1101 - 232, at redshifts z = 0.165 and z = 0.186, respectively. Their unexpectedly hard spectra provide an upper limit on the background light at optical/near-infrared wavelengths that appears to be very close to the lower limit given by the integrated light of resolved galaxies. The background flux at these wavelengths accordingly seems to be strongly dominated by the direct starlight from galaxies, thus excluding a large contribution from other sources-in particular from the first stars formed. This result also indicates that intergalactic space is more transparent to gamma-rays than previously thought.