Optical control of neuronal activities with photoswitchable nanovesicles.

Precise modulation of neuronal activity by neuroactive molecules is essential for understanding brain circuits and behavior. However, tools for highly controllable molecular release are lacking. Here, we developed a photoswitchable nanovesicle with azobenzene-containing phosphatidylcholine (azo-PC), coined 'azosome', for neuromodulation. Irradiation with 365 nm light triggers the trans-to-cis isomerization of azo-PC, resulting in a disordered lipid bilayer with decreased thickness and cargo release. Irradiation with 455 nm light induces reverse isomerization and switches the release off. Real-time fluorescence imaging shows controllable and repeatable cargo release within seconds (< 3 s). Importantly, we demonstrate that SKF-81297, a dopamine D1-receptor agonist, can be repeatedly released from the azosome to activate cultures of primary striatal neurons. Azosome shows promise for precise optical control over the molecular release and can be a valuable tool for molecular neuroscience studies.

Efficient d-dimensional molecular dynamics simulations for studies of the glass-jamming transition.

We develop an algorithm suitable for parallel molecular dynamics simulations in d spatial dimensions and describe its implementation in C++. All routines work in arbitrary d; the maximum simulated d is limited only by available computing resources. These routines include several that are particularly useful for studies of the glass-jamming transition, such as SWAP Monte Carlo and FIRE energy minimization. The scalings of simulation runtimes with the number of particles N and number of simulation threads n_{threads} are comparable to popular molecular dynamics codes such as LAMMPS. The efficient parallel implementation allows simulation of systems that are much larger than those employed in previous high-dimensional glass-transition studies. As a demonstration of the code's capabilities, we show that supercooled d=6 liquids can possess dynamics that are substantially more heterogeneous and experience a breakdown of the Stokes-Einstein relation that is substantially stronger than previously reported, owing at least in part to the much smaller system sizes employed in earlier simulations.

Biophysical and in silico characterization of NrtA: a protein-based host for aqueous nitrate and nitrite recognition.

Nitrate and nitrite are key components of the global nitrogen cycle. As such, Nature has evolved proteins as biological supramolecular hosts for the recognition, translocation, and transformation of both nitrate and nitrite. To understand the supramolecular principles that govern these anion-protein interactions, here, we employ a hybrid biophysical and in silico approach to characterize the thermodynamic properties and protein dynamics of NrtA from the cyanobacterium Synechocystis sp. PCC 6803 for the recognition of nitrate and nitrite.

Unipolar stroke, electroosmotic pump carbon nanotube yarn muscles.

Success in making artificial muscles that are faster and more powerful and that provide larger strokes would expand their applications. Electrochemical carbon nanotube yarn muscles are of special interest because of their relatively high energy conversion efficiencies. However, they are bipolar, meaning that they do not monotonically expand or contract over the available potential range. This limits muscle stroke and work capacity. Here, we describe unipolar stroke carbon nanotube yarn muscles in which muscle stroke changes between extreme potentials are additive and muscle stroke substantially increases with increasing potential scan rate. The normal decrease in stroke with increasing scan rate is overwhelmed by a notable increase in effective ion size. Enhanced muscle strokes, contractile work-per-cycle, contractile power densities, and energy conversion efficiencies are obtained for unipolar muscles.