Trending Papers in biological physics

Hybrid approach catches lightPlant chloroplasts enclose two major photosynthetic processes: light reactions, which generate the energy carriers adenosine triphosphate and reduced nicotinamide dinucleotide phosphate (NADPH), and dark reactions, which use these molecules to fix carbon dioxide and build biomass. Miller et al. appropriated natural components, thylakoid membranes from spinach, for the light reactions and showed that these could be coupled to a synthetic enzymatic cycle that fixes carbon dioxide within water-in-oil droplets. The composition of the droplets could be tuned and optimized and the metabolic activity monitored in real time by NADPH fluorescence (see the Perspective by Gaut and Adamala). These chloroplast-mimicking droplets bring together natural and synthetic components in a small space and are amenable to further functionalization to perform complex biosynthetic tasks.Science, this issue p. 649; see also p. 587Nature integrates complex biosynthetic and energy-converting tasks within compartments such as chloroplasts and mitochondria. Chloroplasts convert light into chemical energy, driving carbon dioxide fixation. We used microfluidics to develop a chloroplast mimic by encapsulating and operating photosynthetic membranes in cell-sized droplets. These droplets can be energized by light to power enzymes or enzyme cascades and analyzed for their catalytic properties in multiplex and real time. We demonstrate how these microdroplets can be programmed and controlled by adjusting internal compositions and by using light as an external trigger. We showcase the capability of our platform by integrating the crotonyl–coenzyme A (CoA)/ethylmalonyl-CoA/hydroxybutyryl-CoA (CETCH) cycle, a synthetic network for carbon dioxide conversion, to create an artificial photosynthetic system that interfaces the natural and the synthetic biological worlds.Natural photosynthetic components power a synthetic CO2 fixation pathway in picoliter droplets.Natural photosynthetic components power a synthetic CO2 fixation pathway in picoliter droplets.

The spatial distribution of neuronal cells is an important requirement forachieving proper neuronal function in several parts of the nervous system ofmost animals. For instance, specific distribution of photoreceptors and relatedneuronal cells, particularly the ganglion cells, in mammal's retina is requiredin order to properly sample the projected scene. This work presents how twoconcepts from the areas of statistical mechanics and complex systems, namelythe \emph{lacunarity} and the \emph{multiscale entropy} (i.e. the entropycalculated over progressively diffused representations of the cell mosaic),have allowed effective characterization of the spatial distribution of retinalcells.

The emerging diffusive dynamics in many complex systems shows acharacteristic crossover behaviour from anomalous to normal diffusion which isotherwise fitted by two independent power-laws. A prominent example for asubdiffusive-diffusive crossover are viscoelastic systems such as lipid bilayermembranes, while superdiffusive-diffusive crossovers occur in systems ofactively moving biological cells. We here consider the general dynamics of astochastic particle driven by so-called tempered fractional Gaussian noise,that is noise with Gaussian amplitude and power-law correlations, which are cutoff at some mesoscopic time scale. Concretely we consider such noise withbuilt-in exponential or power-law tempering, driving an overdamped Langevinequation (fractional Brownian motion) and fractional Langevin equation motion.We derive explicit expressions for the mean squared displacement andcorrelation functions, including different shapes of the crossover behaviourdepending on the concrete tempering, and discuss the physical meaning of thetempering. In the case of power-law tempering we also find a crossoverbehaviour from faster to slower superdiffusion and slower to fastersubdiffusion. As a direct application of our model we demonstrate that theobtained dynamics quantitatively described the subdiffusion-diffusion andsubdiffusion-subdiffusion crossover in lipid bilayer systems. We also show thata model of tempered fractional Brownian motion recently proposed by Sabzikarand Meerschaert leads to physically very different behaviour with a seeminglyparadoxical ballistic long time scaling.

Machine learning method is being applied in cancer research. In this work, wepropose a method to classify the small patch of triple-negative breast cancer(TNBC) tumor and use the overall percentage of "good" patches as a marker topredict the prognosis, which is an automatic method of prognosis and could alsobe used for other cancers.

Stability of running on rough terrain depends on the propagation ofperturbations due to the ground. We consider stability within the sagittalplane and model the dynamics of running as a two-dimensional body with analternating aerial and stance phase. Stance is modeled as a passive, impulsivecollision followed by an active, impulsive push-off that compensates forcollisional losses. Such a runner has infinitely many strategies to maintainperiodic gaits on flat ground. However, these strategies differ in howperturbations due to terrain unevenness are propagated. Instabilities manifestas tumbling (orientational instability) or failing to maintain a steady speed(translational instability). We find that open-loop strategies that avoidsensory feedback are sufficient to maintain stability on step-like terrainswith piecewise flat surfaces that randomly vary in height. However, theseopen-loop runners lose orientational stability on rough terrains whose slopeand height vary randomly. Only by avoiding tangential collisions isorientational stability recovered. Tangential collisions may be avoided throughleg-retraction to match foot and ground speed at touch down. By analyzing thepropagation of perturbations, we derive a single dimensionless parameter thatgoverns stability and guides the design and control of both biological androbotic runners.

In this work, single particle dispersion was analyzed for a bacterialturbulence by retrieving the virtual Lagrangian trajectory via numericalintegration of the Lagrangian equation. High-order displacement functions werecalculated for cases with and without mean velocity effect. Two-regimepower-law behavior for short and long time evolutions were identifiedexperimentally, which were separated by the Lagrangian integral time. For thecase with the mean velocity effect, the experimental Hurst numbers weredetermined to be $0.94$ and $0.97$ for short and long times evolutions,respectively. For the case without the mean velocity effect, the values were$0.88$ and $0.58$. Moreover, very weak intermittency correction was detected.All measured Hurst number were above $1/2$, the value of the normal diffusion,which verifies the super-diffusion behavior of living fluid. This behaviorincreases the efficiency of bacteria to obtain food.

The impact of nanomaterials on lung fluids or on the plasma membrane ofliving cells has prompted researchers to examine the interactions betweennanoparticles and lipid vesicles. Recent studies have shown thatnanoparticle-lipid interaction leads to a broad range of structures includingsupported lipid bilayers (SLB), particles adsorbed at the surface orinternalized inside vesicles, and mixed aggregates. Today, there is a need tohave simple protocols that can readily assess the nature of structures obtainedfrom particles and vesicles. Here we apply the method of continuous variationfor measuring Job scattering plots and provide analytical expressions for thescattering intensity in various scenarios. The result that emerges from thecomparison between modeling and experimental measurements is thatelectrostatics plays a key role in the association, but it is not sufficient toinduce the formation of supported lipid bilayers.

Mammalian ultrasonic vocalization (USV) has been a subject of interest fordecades. This interest has mainly been driven by the intelligence of dolphinsand other odontocetes. However the semantic content of odontocete USV and itsmechanism of production remain poorly understood. Serendipitously however manyrodent species have convergently evolved the ability to produce USVs in asimilar manner. In this paper we use rodent USV as a model process to help usgain insight into the production mechanism for mammalian USV as a whole. Wederive a model that describes the production of rodent USVs by considering theinteraction of an unstable jet, emerging from the vocal folds, with the passiveresonance modes of the upper vocal tract. Thus our model is also a solution toa special case of the jet susceptibility problem. The derived model takes theform of a set of coupled nonlinear time domain ODEs, whose solutions arecontrolled by biologically relevant parameters such as subglottal pressure andvocal fold radius. In our analysis of the model we find the existence of asubglottal blowing pressure threshold ($p \approx 710$ Pa), above which steadyacoustic oscillations occur. Furthermore we also reproduce the $22$ kHz ratalarm call at realistic blowing pressures ($p \approx 1500$ Pa)

We describe the photochemical dissipative structuring of fatty acids from COand CO2 saturated water under the solar UVC and UVA photon potential prevalentat Earth's surface during the Archean. Their association into vesicles andtheir subsequent association with other fundamental molecules of life such asRNA, DNA and carotenoids to form the first protocells is also suggested tooccur through photochemical dissipative structuring. In particular, it ispostulated that the first vesicles were formed from conjugated linolenic(C18:3n-3) and parinaric (C18:4n-3) acids which would form vesicles stable atthe high temperatures (~85 {\deg}C) and the somewhat acidic pH values (6.0-6.5)of the Archean ocean surface, resistant to divalent cation salt flocculation,permeable to ions and small charged molecules, but impermeable to short DNA andRNA, and, most importantly, highly dissipative in the prevailing UVC+UVAregions.

The emergence of electrical fields across biological membranes is central toour present understanding of biomembrane function. The most prominent exampleis the textbook model for the action potential that relies on transmembranevoltage and membrane permeability. In a recent article by Tamagawa & Ikeda , animportant underlying concept, the Goldman-Hodgkin-Katz equation, has beenchallenged (Tamagawa & Ikeda. 2018, Eur. Biophys. J. doi:10.1007/s00249-018-1332-0}. This will be discussed below.