RNA molecules play fundamental roles in cellular processes. Their function and interactions with other biomolecules are dependent on the ability to form complex three-dimensional (3D) structures. However, experimental determination of RNA 3D structures is laborious and challenging, and therefore, the majority of known RNAs remain structurally uncharacterized. Here, we present SimRNA: a new method for computational RNA 3D structure prediction, which uses a coarse-grained representation, relies on the Monte Carlo method for sampling the conformational space, and employs a statistical potential to approximate the energy and identify conformations that correspond to biologically relevant structures. SimRNA can fold RNA molecules using only sequence information, and, on established test sequences, it recapitulates secondary structure with high accuracy, including correct prediction of pseudoknots. For modeling of complex 3D structures, it can use additional restraints, derived from experimental or computational analyses, including information about secondary structure and/or long-range contacts. SimRNA also can be used to analyze conformational landscapes and identify potential alternative structures.

We report the results of a first, collective, blind experiment in RNA three-dimensional (3D) structure prediction, encompassing three prediction puzzles. The goals are to assess the leading edge of RNA structure prediction techniques; compare existing methods and tools; and evaluate their relative strengths, weaknesses, and limitations in terms of sequence length and structural complexity. The results should give potential users insight into the suitability of available methods for different applications and facilitate efforts in the RNA structure prediction community in ongoing efforts to improve prediction tools. We also report the creation of an automated evaluation pipeline to facilitate the analysis of future RNA structure prediction exercises.

We present new results of timing and single-pulse measurements for 18 radio pulsars discovered in 1993-1997 by the Penn State / Naval Research Laboratory declination-strip survey conducted with the 305 m Arecibo Telescope at 430 MHz. Long-term timing measurements have led to significant improvements of the rotational and the astrometric parameters of these sources, including the millisecond pulsar, PSR J1709+2313, and the pulsar located within the supernova remnant S147, PSR J0538+2817. Single-pulse studies of the brightest objects in the sample have revealed an unusual ''bursting'' pulsar, PSR J1752+2359, two new drifting subpulse pulsars, PSR J1649+2533 and PSR J2155+2813, and another example of a pulsar with profile mode changes, PSR J1746+2540. PSR J1752+2359 is characterized by bursts of emission, which appear once every 3-5 minutes and decay exponentially on a $45 s timescale. PSR J1649+2533 spends $30% of the time in a null state with no detectable radio emission.

We study fluorescence lifetime of indocyanine green (ICG) using femtosecond laser and sensitive detection based on time-correlated single-photon counting. A time-resolved multichannel spectral system is constructed and applied for determination of the fluorescence lifetime of the ICG in different solvents. Emission properties of ICG in water, milk, and 1% intralipid solution are investigated. Fluorescence of the fluorophore of different concentrations (in a range of 1.7-160 μM) dissolved in different solutions is excited by femtosecond pulses generated with the use of Ti:Sa laser tuned within the range of 740-790 nm. It is observed that fluorescence lifetime of ICG in water is 0.166 ± 0.02 ns and does not depend on excitation and emission wavelengths. We also show that for the diffusely scattering solvents (milk and intralipid), the lifetime may depend on the dye concentration (especially for large concentrations of ICG). This effect should be taken into account when analyzing changes in the mean time of arrival of fluorescence photons excited in ICG dissolved in such optically turbid media.