Acoustic Wave-Induced Stroboscopic Optical Mechanotyping of Adherent Cells.

In this study, a novel, high content technique using a cylindrical acoustic transducer, stroboscopic fast imaging, and homodyne detection to recover the mechanical properties (dynamic shear modulus) of living adherent cells at low ultrasonic frequencies is presented. By analyzing the micro-oscillations of cells, whole populations are simultaneously mechanotyped with sub-cellular resolution. The technique can be combined with standard fluorescence imaging allowing to further cross-correlate biological and mechanical information. The potential of the technique is demonstrated by mechanotyping co-cultures of different cell types with significantly different mechanical properties.

Coherently remapping toroidal cells but not Grid cells are responsible for path integration in virtual agents.

It is widely believed that grid cells provide cues for path integration, with place cells encoding an animal's location and environmental identity. When entering a new environment, these cells remap concurrently, sparking debates about their causal relationship. Using a continuous attractor recurrent neural network, we study spatial cell dynamics in multiple environments. We investigate grid cell remapping as a function of global remapping in place-like units through random resampling of place cell centers. Dimensionality reduction techniques reveal that a subset of cells manifest a persistent torus across environments. Unexpectedly, these toroidal cells resemble band-like cells rather than high grid score units. Subsequent pruning studies reveal that toroidal cells are crucial for path integration while grid cells are not. As we extend the model to operate across many environments, we delineate its generalization boundaries, revealing challenges with modeling many environments in current models.

Perineuronal nets restrict transport near the neuron surface: A coarse-grained molecular dynamics study.

Perineuronal nets (PNNs) are mesh-like extracellular matrix structures that wrap around certain neurons in the central nervous system. They are hypothesized to stabilize memories in the brain and act as a barrier between cell and extracellular space. As a means to study the impact of PNNs on diffusion, the nets were approximated by negatively charged polymer brushes and simulated by coarse-grained molecular dynamics. Diffusion constants of single neutral and single charged particles were obtained in directions parallel and perpendicular to the brush substrate. The results for the neutral particle were compared to different theories of diffusion in a heuristic manner. Diffusion was found to be considerably reduced for brush spacings smaller than 10 nm, with a pronounced anisotropy for dense brushes. The exact dynamics of the chains was found to have a negligible impact on particle diffusion. The resistance of the brush proved small compared to typical values of the membrane resistance of a neuron, indicating that PNNs likely contribute little to the total resistance of an enwrapped neuron.

Modeling V̇o2 on-kinetics based on intensity-dependent delayed adjustment and loss of efficiency (DALE).

This study presents and evaluates a new mathematical model of V̇o2 on-kinetics, with the following properties: 1) a progressively slower primary phase following the size-principle of motor unit recruitment, explaining the delayed V̇o2 steady state seen in the heavy exercise intensity domain, and 2) a severe-domain slow component modeled as a time-dependent decrease in efficiency. Breath-by-breath V̇o2 measurements from eight subjects performing step cycling transitions, in the moderate, heavy, and severe exercise domains, were fitted to the conventional three-phase model and the new model. Model performance was evaluated with a residual analysis and by comparing Bayesian (BIC) and corrected Akaike (AICc) information criteria. The residual analysis showed no systematic deviations, except perhaps for the initial part of the primary phase. BIC favored the new model, being 9.3 (SD 7.1) lower than the conventional model whereas AICc was similar between models. Compared with the conventional three-phase model, the proposed model distinguishes between the kinetic adaptations in the heavy and severe domains by predicting a delayed steady-state V̇o2 in the heavy and no steady-state V̇o2 in the severe domain. This allows to determine when stable oxygen costs of exercise are attainable and it also represents a first step in defining time-dependent oxygen costs when stable energy conversion efficiency is not attainable.NEW & NOTEWORTHY We propose and assess a new minimalistic integrated model for the V̇o2 on-kinetics, inspired by the currently available best evidence of the underlying mechanisms. We show that the model provides a similar fit as the conventionally used three-phase model, even though a stricter data fitting method is used for the proposed model. The proposed model clarifies misconceptions related to the V̇o2 slow component's behavior, by clearly predicting that steady-state V̇o2 is attainable in the moderate and heavy exercise intensity domains. Furthermore, the model opens new possibilities for assessing oxygen cost during severe intensity exercise without the fallible assumption of time-constant energy-conversion efficiency.

Myonuclear content regulates cell size with similar scaling properties in mice and humans.

Muscle fibers are the largest cells in the body, and one of its few syncytia. Individual cell sizes are variable and adaptable, but what governs cell size has been unclear. We find that muscle fibers are DNA scarce compared to other cells, and that the nuclear number (N) adheres to the relationship N = aVb where V is the cytoplasmic volume. N invariably scales sublinearly to V (b < 1), making larger cells even more DNA scarce. N scales linearly to cell surface in adult humans, in adult and developing mice, and in mice with genetically reduced N, but in the latter the relationship eventually fails when they reach adulthood with extremely large myonuclear domains. Another exception is denervation-atrophy where nuclei are not eliminated. In conclusion, scaling exponents are remarkably similar across species, developmental stages and experimental conditions, suggesting an underlying scaling law where DNA-content functions as a limiter of muscle cell size.

Experimental Pipeline (Expipe): A Lightweight Data Management Platform to Simplify the Steps From Experiment to Data Analysis.

As experimental neuroscience is moving toward more integrative approaches, with a variety of acquisition techniques covering multiple spatiotemporal scales, data management is becoming increasingly challenging for neuroscience laboratories. Often, datasets are too large to practically be stored on a laptop or a workstation. The ability to query metadata collections without retrieving complete datasets is therefore critical to efficiently perform new analyses and explore the data. At the same time, new experimental paradigms lead to constantly changing specifications for the metadata to be stored. Despite this, there is currently a serious lack of agile software tools for data management in neuroscience laboratories. To meet this need, we have developed Expipe, a lightweight data management framework that simplifies the steps from experiment to data analysis. Expipe provides the functionality to store and organize experimental data and metadata for easy retrieval in exploration and analysis throughout the experimental pipeline. It is flexible in terms of defining the metadata to store and aims to solve the storage and retrieval challenges of data/metadata due to ever changing experimental pipelines. Due to its simplicity and lightweight design, we envision Expipe as an easy-to-use data management solution for experimental laboratories, that can improve provenance, reproducibility, and sharing of scientific projects.

Oxygen Demand, Uptake, and Deficits in Elite Cross-Country Skiers during a 15-km Race.

PURPOSE: This study aimed to quantify the repeated oxygen deficits attained during intermittent endurance exercise by measuring oxygen consumption (V˙O2) and oxygen demand (V˙O2) throughout a simulated roller ski race. METHODS: Eight male elite cross-country skiers (V˙O2peak, 77.4 ± 4.4 mL·kg⋅min) raced a 13.5-km roller ski time trial on a World Cup course. On two additional days, athletes completed (i) six submaximal loads (~5 min) and ~4-min maximal trial to establish athlete-specific estimates of skiing economy, V˙O2peak, and maximal ΣO2 (MAOD); and (ii) a simulation of the time trial on a roller skiing treadmill. During the simulation, external work rate (Pprop) and skiing speed (v) were adjusted to match the Pprop and v measured during the time trial, and pulmonary V˙O2 was measured breath by breath. V˙O2 and ΣO2 were calculated using an athlete-specific model for skiing economy throughout the treadmill simulation. RESULTS: During the treadmill simulation, V˙O2 was on average 0.77 V˙O2peak, and active V˙O2 (i.e., excluding the time in simulated downhill) was on average 1.01 V˙O2peak. The athletes repeatedly attained substantial oxygen deficits in individual uphill sections of the treadmill simulation, but the deficits were typically small compared with their MAOD (average 14%, range ~0%-50%). However, the ΣO2 summed over all periods of active propulsion was on average 3.8 MAOD. CONCLUSION: Athletes repeatedly attain substantial oxygen deficits in the uphill segments of a distance cross-country ski race. Furthermore, the total accumulated oxygen deficit of all these segments is several times higher than the athletes' MAOD. This suggests that the rapid recovery of the energy stores represented by the oxygen deficit is necessary during downhill sections, and that this might be an important determinant of distance skiing performance.

Minimal model for slow, sub-Rayleigh, supershear, and unsteady rupture propagation along homogeneously loaded frictional interfaces.

In nature and experiments, a large variety of rupture speeds and front modes along frictional interfaces are observed. Here, we introduce a minimal model for the rupture of homogeneously loaded interfaces with velocity strengthening dynamic friction, containing only two dimensionless parameters; τ[over ¯], which governs the prestress, and α[over ¯], which is set by the interfacial viscosity. This model contains a large variety of front types, including slow fronts, sub-Rayleigh fronts, supershear fronts, slip pulses, cracks, arresting fronts, and fronts that alternate between arresting and propagating phases. Our results indicate that this wide range of front types is an inherent property of frictional systems with velocity strengthening branches.

Molecular-scale thermally activated fractures in methane hydrates: a molecular dynamics study.

We perform multiple large molecular dynamics simulations to study the fracture behaviour of monocrystalline methane hydrates under tension. We examine the fracture initiation phase and find that the fracture process can be divided into two phases: slow crack growth and rapid crack propagation. The time of the slow crack growth phase can be predicted by a thermal activation model [L. Vanel et al., J. Phys. D: Appl. Phys., 2009, 42, 214007] where an energy barrier has to be overcome in order for the crack to propagate. Our simulations predict that the slow growth phase vanishes when the stress intensity factor approaches .

Rate-and-state friction explains glacier surge propagation.

The incomplete understanding of glacier dynamics is a major source of uncertainty in assessments of sea-level rise from land-based ice. Through increased ice discharge into the oceans, accelerating glacier flow has the potential to considerably enhance expected sea-level change, well ahead of scenarios considered by the IPCC. Central in our incomplete understanding is the motion at the glacier bed, responsible for flow transients and instabilities involving switches from slow to fast flow. We introduce a rate-and-state framework for the transient evolution of basal shear stress, which we incorporate in glacier simulations. We demonstrate that a velocity-strengthening-weakening transition combined with a characteristic length scale for the opening of subglacial cavities is sufficient to reproduce several previously unexplained features of glacier surges. The rate-and-state framework opens for new ways to analyze, understand and predict transient glacier dynamics as well as to assess the stability of glaciers and ice caps.

Statistics of the separation between sliding rigid rough surfaces: Simulations and extreme value theory approach.

When a rigid rough solid slides on a rigid rough surface, it experiences a random motion in the direction normal to the average contact plane. Here, through simulations of the separation at single-point contact between self-affine topographies, we characterize the statistical and spectral properties of this normal motion. In particular, its rms amplitude is much smaller than that of the equivalent roughness of the two topographies and depends on the ratio of the slider's lateral size over a characteristic wavelength of the topography. In addition, due to the nonlinearity of the sliding contact process, the normal motion's spectrum contains wavelengths smaller than the smallest wavelength present in the underlying topographies. We show that the statistical properties of the normal motion's amplitude are well captured by a simple analytic model based on the extreme value theory framework, extending its applicability to sliding-contact-related topics.

Propulsive Power in Cross-Country Skiing: Application and Limitations of a Novel Wearable Sensor-Based Method During Roller Skiing.

Cross-country skiing is an endurance sport that requires extremely high maximal aerobic power. Due to downhill sections where the athletes can recover, skiers must also have the ability to perform repeated efforts where metabolic power substantially exceeds maximal aerobic power. Since the duration of these supra-aerobic efforts is often in the order of seconds, heart rate, and pulmonary VO2 do not adequately reflect instantaneous metabolic power. Propulsive power (P prop) is an alternative parameter that can be used to estimate metabolic power, but the validity of such calculations during cross-country skiing has rarely been addressed. The aim of this study was therefore twofold: to develop a procedure using small non-intrusive sensors attached to the athlete for estimating P prop during roller-skiing and to evaluate its limits; and (2) to utilize this procedure to determine the P prop generated by high-level skiers during a simulated distance race. Eight elite male cross-country skiers simulated a 15 km individual distance race on roller skis using ski skating techniques on a course (13.5 km) similar to World Cup skiing courses. P prop was calculated using a combination of standalone and differential GNSS measurements and inertial measurement units. The method's measurement error was assessed using a Monte Carlo simulation, sampling from the most relevant sources of error. P prop decreased approximately linearly with skiing speed and acceleration, and was approximated by the equation P prop ( v , v ˙ ) = -0.54·v -0.71 · v ˙ + 7.26 W·kg-1. P prop was typically zero for skiing speeds >9 m·s-1, because the athletes transitioned to the tuck position. Peak P prop was 8.35 ± 0.63 W·kg-1 and was typically attained during the final lap in the last major ascent, while average P prop throughout the race was 3.35 ± 0.23 W·kg-1. The measurement error of P prop increased with skiing speed, from 0.09 W·kg-1 at 2.0 m·s-1 to 0.58 W·kg-1 at 9.0 m·s-1. In summary, this study is the first to provide continuous measurements of P prop for distance skiing, as well as the first to quantify the measurement error during roller skiing using the power balance principle. Therefore, these results provide novel insight into the pacing strategies employed by high-level skiers.

A Kirchhoff-Nernst-Planck framework for modeling large scale extracellular electrodiffusion surrounding morphologically detailed neurons.

Many pathological conditions, such as seizures, stroke, and spreading depression, are associated with substantial changes in ion concentrations in the extracellular space (ECS) of the brain. An understanding of the mechanisms that govern ECS concentration dynamics may be a prerequisite for understanding such pathologies. To estimate the transport of ions due to electrodiffusive effects, one must keep track of both the ion concentrations and the electric potential simultaneously in the relevant regions of the brain. Although this is currently unfeasible experimentally, it is in principle achievable with computational models based on biophysical principles and constraints. Previous computational models of extracellular ion-concentration dynamics have required extensive computing power, and therefore have been limited to either phenomena on very small spatiotemporal scales (micrometers and milliseconds), or simplified and idealized 1-dimensional (1-D) transport processes on a larger scale. Here, we present the 3-D Kirchhoff-Nernst-Planck (KNP) framework, tailored to explore electrodiffusive effects on large spatiotemporal scales. By assuming electroneutrality, the KNP-framework circumvents charge-relaxation processes on the spatiotemporal scales of nanometers and nanoseconds, and makes it feasible to run simulations on the spatiotemporal scales of millimeters and seconds on a standard desktop computer. In the present work, we use the 3-D KNP framework to simulate the dynamics of ion concentrations and the electrical potential surrounding a morphologically detailed pyramidal cell. In addition to elucidating the single neuron contribution to electrodiffusive effects in the ECS, the simulation demonstrates the efficiency of the 3-D KNP framework. We envision that future applications of the framework to more complex and biologically realistic systems will be useful in exploring pathological conditions associated with large concentration variations in the ECS.

Experimental Directory Structure (Exdir): An Alternative to HDF5 Without Introducing a New File Format.

Natural sciences generate an increasing amount of data in a wide range of formats developed by different research groups and commercial companies. At the same time there is a growing desire to share data along with publications in order to enable reproducible research. Open formats have publicly available specifications which facilitate data sharing and reproducible research. Hierarchical Data Format 5 (HDF5) is a popular open format widely used in neuroscience, often as a foundation for other, more specialized formats. However, drawbacks related to HDF5's complex specification have initiated a discussion for an improved replacement. We propose a novel alternative, the Experimental Directory Structure (Exdir), an open specification for data storage in experimental pipelines which amends drawbacks associated with HDF5 while retaining its advantages. HDF5 stores data and metadata in a hierarchy within a complex binary file which, among other things, is not human-readable, not optimal for version control systems, and lacks support for easy access to raw data from external applications. Exdir, on the other hand, uses file system directories to represent the hierarchy, with metadata stored in human-readable YAML files, datasets stored in binary NumPy files, and raw data stored directly in subdirectories. Furthermore, storing data in multiple files makes it easier to track for version control systems. Exdir is not a file format in itself, but a specification for organizing files in a directory structure. Exdir uses the same abstractions as HDF5 and is compatible with the HDF5 Abstract Data Model. Several research groups are already using data stored in a directory hierarchy as an alternative to HDF5, but no common standard exists. This complicates and limits the opportunity for data sharing and development of common tools for reading, writing, and analyzing data. Exdir facilitates improved data storage, data sharing, reproducible research, and novel insight from interdisciplinary collaboration. With the publication of Exdir, we invite the scientific community to join the development to create an open specification that will serve as many needs as possible and as a foundation for open access to and exchange of data.

Removal of perineuronal nets disrupts recall of a remote fear memory.

Throughout life animals learn to recognize cues that signal danger and instantaneously initiate an adequate threat response. Memories of such associations may last a lifetime and far outlast the intracellular molecules currently found to be important for memory processing. The memory engram may be supported by other more stable molecular components, such as the extracellular matrix structure of perineuronal nets (PNNs). Here, we show that recall of remote, but not recent, visual fear memories in rats depend on intact PNNs in the secondary visual cortex (V2L). Supporting our behavioral findings, increased synchronized theta oscillations between V2L and basolateral amygdala, a physiological correlate of successful recall, was absent in rats with degraded PNNs in V2L. Together, our findings suggest a role for PNNs in remote memory processing by stabilizing the neural network of the engram.

Fluid-driven metamorphism of the continental crust governed by nanoscale fluid flow.

The transport of fluids through the Earth's crust controls the redistribution of elements to form mineral and hydrocarbon deposits, the release and sequestration of greenhouse gases, and facilitates metamorphic reactions that influence lithospheric rheology. In permeable systems with a well-connected porosity, fluid transport is largely driven by fluid pressure gradients. In less permeable rocks, deformation may induce permeability by creating interconnected heterogeneities, but without these perturbations, mass transport is limited along grain boundaries or relies on transformation processes that self-generate transient fluid pathways. The latter can facilitate large-scale fluid and mass transport in nominally impermeable rocks without large-scale fluid transport pathways. Here, we show that pervasive, fluid-driven metamorphism of crustal igneous rocks is directly coupled to the production of nanoscale porosity. Using multi-dimensional nano-imaging and molecular dynamics simulations, we demonstrate that in feldspar, the most abundant mineral family in the Earth's crust, electrokinetic transport through reaction-induced nanopores (10-100 nm) can potentially be significant. This suggests that metamorphic fluid flow and fluid-mediated mineral transformation reactions can be considerably influenced by nanofluidic transport phenomena.

Neuronify: An Educational Simulator for Neural Circuits.

Educational software (apps) can improve science education by providing an interactive way of learning about complicated topics that are hard to explain with text and static illustrations. However, few educational apps are available for simulation of neural networks. Here, we describe an educational app, Neuronify, allowing the user to easily create and explore neural networks in a plug-and-play simulation environment. The user can pick network elements with adjustable parameters from a menu, i.e., synaptically connected neurons modelled as integrate-and-fire neurons and various stimulators (current sources, spike generators, visual, and touch) and recording devices (voltmeter, spike detector, and loudspeaker). We aim to provide a low entry point to simulation-based neuroscience by allowing students with no programming experience to create and simulate neural networks. To facilitate the use of Neuronify in teaching, a set of premade common network motifs is provided, performing functions such as input summation, gain control by inhibition, and detection of direction of stimulus movement. Neuronify is developed in C++ and QML using the cross-platform application framework Qt and runs on smart phones (Android, iOS) and tablet computers as well personal computers (Windows, Mac, Linux).

Transient cluster formation in sheared non-Brownian suspensions.

We perform numerical simulations of non-Brownian suspensions in the laminar flow regime to study the scaling behavior of particle clusters and collisions under shear. As the particle fraction approaches the maximum packing fraction, large transient clusters appear in the system. We use methods from percolation theory to discuss the cluster size distribution. We also give a scaling relation for the percolation threshold as well as system size effects through time-dependent fluctuations of this threshold and relate them to system size. System size effects are important close to the maximum packing fraction due to the divergence of the cluster length scale. We then investigate the transient nature of the clusters through characterization of particle collisions and show that collision times exhibit scale-invariant properties. Finally, we show that particle collision times can be modeled as first-passage processes.

Steady-state propagation speed of rupture fronts along one-dimensional frictional interfaces.

The rupture of dry frictional interfaces occurs through the propagation of fronts breaking the contacts at the interface. Recent experiments have shown that the velocities of these rupture fronts range from quasistatic velocities proportional to the external loading rate to velocities larger than the shear wave speed. The way system parameters influence front speed is still poorly understood. Here we study steady-state rupture propagation in a one-dimensional (1D) spring-block model of an extended frictional interface for various friction laws. With the classical Amontons-Coulomb friction law, we derive a closed-form expression for the steady-state rupture velocity as a function of the interfacial shear stress just prior to rupture. We then consider an additional shear stiffness of the interface and show that the softer the interface, the slower the rupture fronts. We provide an approximate closed form expression for this effect. We finally show that adding a bulk viscosity on the relative motion of blocks accelerates steady-state rupture fronts and we give an approximate expression for this effect. We demonstrate that the 1D results are qualitatively valid in 2D. Our results provide insights into the qualitative role of various key parameters of a frictional interface on its rupture dynamics. They will be useful to better understand the many systems in which spring-block models have proved adequate, from friction to granular matter and earthquake dynamics.

Speed of fast and slow rupture fronts along frictional interfaces.

The transition from stick to slip at a dry frictional interface occurs through the breaking of microjunctions between the two contacting surfaces. Typically, interactions between junctions through the bulk lead to rupture fronts propagating from weak and/or highly stressed regions, whose junctions break first. Experiments find rupture fronts ranging from quasistatic fronts, via fronts much slower than elastic wave speeds, to fronts faster than the shear wave speed. The mechanisms behind and selection between these fronts are still imperfectly understood. Here we perform simulations in an elastic two-dimensional spring-block model where the frictional interaction between each interfacial block and the substrate arises from a set of junctions modeled explicitly. We find that material slip speed and rupture front speed are proportional across the full range of front speeds we observe. We revisit a mechanism for slow slip in the model and demonstrate that fast slip and fast fronts have a different, inertial origin. We highlight the long transients in front speed even along homogeneous interfaces, and we study how both the local shear to normal stress ratio and the local strength are involved in the selection of front type and front speed. Last, we introduce an experimentally accessible integrated measure of block slip history, the Gini coefficient, and demonstrate that in the model it is a good predictor of the history-dependent local static friction coefficient of the interface. These results will contribute both to building a physically based classification of the various types of fronts and to identifying the important mechanisms involved in the selection of their propagation speed.