Motif-pattern dependence of biomolecular phase separation driven by specific interactions.

Eukaryotic cells partition a wide variety of important materials and processes into biomolecular condensates-phase-separated droplets that lack a membrane. In addition to nonspecific electrostatic or hydrophobic interactions, phase separation also depends on specific binding motifs that link together constituent molecules. Nevertheless, few rules have been established for how these ubiquitous specific, saturating, motif-motif interactions drive phase separation. By integrating Monte Carlo simulations of lattice-polymers with mean-field theory, we show that the sequence of heterotypic binding motifs strongly affects a polymer's ability to phase separate, influencing both phase boundaries and condensate properties (e.g. viscosity and polymer diffusion). We find that sequences with large blocks of single motifs typically form more inter-polymer bonds, which promotes phase separation. Notably, the sequence of binding motifs influences phase separation primarily by determining the conformational entropy of self-bonding by single polymers. This contrasts with systems where the molecular architecture primarily affects the energy of the dense phase, providing a new entropy-based mechanism for the biological control of phase separation.

Noise-Robust Modes of the Retinal Population Code Have the Geometry of "Ridges" and Correspond to Neuronal Communities.

An appealing new principle for neural population codes is that correlations among neurons organize neural activity patterns into a discrete set of clusters, which can each be viewed as a noise-robust population codeword. Previous studies assumed that these codewords corresponded geometrically with local peaks in the probability landscape of neural population responses. Here, we analyze multiple data sets of the responses of approximately 150 retinal ganglion cells and show that local probability peaks are absent under broad, nonrepeated stimulus ensembles, which are characteristic of natural behavior. However, we find that neural activity still forms noise-robust clusters in this regime, albeit clusters with a different geometry. We start by defining a soft local maximum, which is a local probability maximum when constrained to a fixed spike count. Next, we show that soft local maxima are robustly present and can, moreover, be linked across different spike count levels in the probability landscape to form a ridge. We found that these ridges comprise combinations of spiking and silence in the neural population such that all of the spiking neurons are members of the same neuronal community, a notion from network theory. We argue that a neuronal community shares many of the properties of Donald Hebb's classic cell assembly and show that a simple, biologically plausible decoding algorithm can recognize the presence of a specific neuronal community.

Evaluation and Minimization of Uncertainty in ITC Binding Measurements: Heat Error, Concentration Error, Saturation, and Stoichiometry.

BACKGROUND: Isothermal titration calorimetry (ITC) is uniquely useful for characterizing binding thermodynamics, because it straightforwardly provides both the binding enthalpy and free energy. However, the precision of the results depends on the experimental setup and how thermodynamic results are obtained from the raw data. METHODS: Experiments and Monte Carlo analysis are used to study how uncertainties in injection heat and concentration propagate to binding enthalpies in various scenarios. We identify regimes in which it is preferable to fix the stoichiometry parameter, N, and evaluate the reliability of uncertainties provided by the least squares method. RESULTS: The noise in the injection heat is mainly proportional in character, with ~1% and ~3% uncertainty at 27C and 65C, respectively; concentration errors are ~1%. Simulations of experiments based on these uncertainties delineate how experimental design and curve fitting methods influence the uncertainty in the final results. CONCLUSIONS: In most cases, experimental uncertainty is minimized by using more injections and by fixing N at its known value. With appropriate technique, the uncertainty in measured binding enthalpies can be kept below ~2% under many conditions, including low C values. GENERAL SIGNIFICANCE: We quantify uncertainties in ITC data due to heat and concentration error, and identify practices to minimize these uncertainties. The resulting guidelines are important when ITC data are used quantitatively, such as to test computer simulations of binding. Reproducibility and further study are supported by free distribution of the new software developed here.

Assessment of quadriceps muscle inactivation with a new electrical stimulation paradigm.

INTRODUCTION: In this study we evaluated the validity of garment-based quadriceps stimulation (GQS) for assessment of muscle inactivation in comparison with femoral nerve stimulation (FNS). METHODS: Inactivation estimates (superimposed doublet torque), self-reported discomfort, and twitch and doublet contractile properties were compared between GQS and FNS in 15 healthy subjects. RESULTS: Superimposed doublet torque was significantly lower for GQS than for FNS at 20% and 40% maximum voluntary contraction (MVC) (P < 0.01), but not at 60%, 80%, and 100% MVC. Discomfort scores were systematically lower for GQS than for FNS (P < 0.05). Resting twitch and doublet peak torque were lower for GQS, and time to peak torque was shorter for GQS than for FNS (P < 0.01). CONCLUSIONS: GQS can be used with confidence for straightforward evaluation of quadriceps muscle inactivation, whereas its validity for assessment of contractile properties remains to be determined.

A syntactic two-component encoding model for the trajectories of human actions.

Human actions have been widely studied for their potential application in various areas such as sports, pervasive patient monitoring, and rehabilitation. However, challenges still persist pertaining to determining the most useful ways to describe human actions at the sensor, then limb and complete action levels of representation and deriving important relations between these levels each involving their own atomic components. In this paper, we report on a motion encoder developed for the sensor level based on the need to distinguish between the shape of the sensor's trajectory and its temporal characteristics during execution. This distinction is critical as it provides a different encoding scheme than the usual velocity and acceleration measures which confound these two attributes of any motion. At the same time, we eliminate noise from sensors by comparing temporal and spatial indexing schemes and a number of optimal filtering models for robust encoding. Results demonstrate the benefits of spatial indexing and separating the shape and dynamics of a motion, as well as its ability to decompose complex motions into several atomic ones. Finally, we discuss how this specific type of sensor encoder bears on the derivation of limb and complete action descriptions.

Transient sodium current at subthreshold voltages: activation by EPSP waveforms.

Tetrodotoxin (TTX)-sensitive sodium channels carry large transient currents during action potentials and also "persistent" sodium current, a noninactivating TTX-sensitive current present at subthreshold voltages. We examined gating of subthreshold sodium current in dissociated cerebellar Purkinje neurons and hippocampal CA1 neurons, studied at 37°C with near-physiological ionic conditions. Unexpectedly, in both cell types small voltage steps at subthreshold voltages activated a substantial component of transient sodium current as well as persistent current. Subthreshold EPSP-like waveforms also activated a large component of transient sodium current, but IPSP-like waveforms engaged primarily persistent sodium current with only a small additional transient component. Activation of transient as well as persistent sodium current at subthreshold voltages produces amplification of EPSPs that is sensitive to the rate of depolarization and can help account for the dependence of spike threshold on depolarization rate, as previously observed in vivo.

Aquatic-treadmill walking: quantifying drag force and energy expenditure.

CONTEXT: Quantification of the magnitudes of fluid resistance provided by water jets (currents) and their effect on energy expenditure during aquatic-treadmill walking is lacking in the scientific literature. OBJECTIVE: To quantify the effect of water-jet intensity on jet velocity, drag force, and oxygen uptake (VO2) during aquatic-treadmill walking. DESIGN: Descriptive and repeated measures. SETTING: Athletic training facility. PARTICIPANTS, INTERVENTION, AND MEASURES: Water-jet velocities were measured using an electromagnetic flow meter at 9 different jet intensities (0-80% maximum). Drag forces on 3 healthy subjects with a range of frontal areas (600, 880, and 1250 cm2) were measured at each jet intensity with a force transducer and line attached to the subject, who was suspended in water. Five healthy participants (age 37.2 ± 11.3 y, weight 611 ± 96 N) subsequently walked (~1.03 m/s or 2.3 miles/h) on an aquatic treadmill at the 9 different jet intensities while expired gases were collected to estimate VO2. RESULTS: For the range of jet intensities, water-jet velocities and drag forces were 0-1.2 m/s and 0-47 N, respectively. VO2 increased nonlinearly, with values ranging from 11.4 ± 1.0 to 22.2 ± 3.8 mL · kg-1 · min-1 for 0-80% of jet maximum, respectively. CONCLUSIONS: This study presented methodology for quantifying water-jet flow velocities and drag forces in an aquatic-treadmill environment and examined how different jet intensities influenced VO2 during walking. Quantification of these variables provides a fundamental understanding of aquatic-jet use and its effect on VO2. In practice, the results indicate that VO2 may be substantially increased on an aquatic treadmill while maintaining a relatively slow walking speed.

A sequential Monte Carlo approach to estimate biophysical neural models from spikes.

Realistic computational models of neuronal activity typically involve many variables and parameters, most of which remain unknown or poorly constrained. Moreover, experimental observations of the neuronal system are typically limited to the times of action potentials, or spikes. One important component of developing a computational model is the optimal incorporation of these sparse experimental data. Here, we use point process statistical theory to develop a procedure for estimating parameters and hidden variables in neuronal computational models given only the observed spike times. We discuss the implementation of a sequential Monte Carlo method for this procedure and apply it to three simulated examples of neuronal spiking activity. We also address the issues of model identification and misspecification, and show that accurate estimates of model parameters and hidden variables are possible given only spike time data.

Sharp Ca²âº nanodomains beneath the ribbon promote highly synchronous multivesicular release at hair cell synapses.

Hair cell ribbon synapses exhibit several distinguishing features. Structurally, a dense body, or ribbon, is anchored to the presynaptic membrane and tethers synaptic vesicles; functionally, neurotransmitter release is dominated by large EPSC events produced by seemingly synchronous multivesicular release. However, the specific role of the synaptic ribbon in promoting this form of release remains elusive. Using complete ultrastructural reconstructions and capacitance measurements of bullfrog amphibian papilla hair cells dialyzed with high concentrations of a slow Ca²âº buffer (10 mM EGTA), we found that the number of synaptic vesicles at the base of the ribbon correlated closely to those vesicles that released most rapidly and efficiently, while the rest of the ribbon-tethered vesicles correlated to a second, slower pool of vesicles. Combined with the persistence of multivesicular release in extreme Ca²âº buffering conditions (10 mM BAPTA), our data argue against the Ca²âº-dependent compound fusion of ribbon-tethered vesicles at hair cell synapses. Moreover, during hair cell depolarization, our results suggest that elevated Ca²âº levels enhance vesicle pool replenishment rates. Finally, using Ca²âº diffusion simulations, we propose that the ribbon and its vesicles define a small cytoplasmic volume where Ca²âº buffer is saturated, despite 10 mM BAPTA conditions. This local buffer saturation permits fast and large Ca²âº rises near release sites beneath the synaptic ribbon that can trigger multiquantal EPSCs. We conclude that, by restricting the available presynaptic volume, the ribbon may be creating conditions for the synchronous release of a small cohort of docked vesicles.

Aerodynamic drag in cycling: methods of assessment.

When cycling on level ground at a speed greater than 14 m/s, aerodynamic drag is the most important resistive force. About 90% of the total mechanical power output is necessary to overcome it. Aerodynamic drag is mainly affected by the effective frontal area which is the product of the projected frontal area and the coefficient of drag. The effective frontal area represents the position of the cyclist on the bicycle and the aerodynamics of the cyclist-bicycle system in this position. In order to optimise performance, estimation of these parameters is necessary. The aim of this study is to describe and comment on the methods used during the last 30 years for the evaluation of the effective frontal area and the projected frontal area in cycling, in both laboratory and actual conditions. Most of the field methods are not expensive and can be realised with few materials, providing valid results in comparison with the reference method in aerodynamics, the wind tunnel. Finally, knowledge of these parameters can be useful in practice or to create theoretical models of cycling performance.

Quantitative assessment of the distributions of membrane conductances involved in action potential backpropagation along basal dendrites.

Basal dendrites of prefrontal cortical neurons receive strong synaptic drive from recurrent excitatory synaptic inputs. Synaptic integration within basal dendrites is therefore likely to play an important role in cortical information processing. Both synaptic integration and synaptic plasticity depend crucially on dendritic membrane excitability and the backpropagation of action potentials. We carried out multisite voltage-sensitive dye imaging of membrane potential transients from thin basal branches of prefrontal cortical pyramidal neurons before and after application of channel blockers. We found that backpropagating action potentials (bAPs) are predominantly controlled by voltage-gated sodium and A-type potassium channels. In contrast, pharmacologically blocking the delayed rectifier potassium, voltage-gated calcium, or I(h) conductance had little effect on dendritic AP propagation. Optically recorded bAP waveforms were quantified and multicompartmental modeling was used to link the observed behavior with the underlying biophysical properties. The best-fit model included a nonuniform sodium channel distribution with decreasing conductance with distance from the soma, together with a nonuniform (increasing) A-type potassium conductance. AP amplitudes decline with distance in this model, but to a lesser extent than previously thought. We used this model to explore the mechanisms underlying two sets of published data involving high-frequency trains of APs and the local generation of sodium spikelets. We also explored the conditions under which I(A) down-regulation would produce branch strength potentiation in the proposed model. Finally, we discuss the hypothesis that a fraction of basal branches may have different membrane properties compared with sister branches in the same dendritic tree.

Single and repetitive paired-pulse suppression: a parametric analysis and assessment of usefulness in epilepsy research.

PURPOSE: The paired-pulse technique has been widely used as a convenient but indirect measure of "inhibition" in hippocampal circuits of normal and epileptic animals. Most investigators have used a single paired-pulse protocol, whereas others have utilized repetitive paired pulses. This study investigated which parameters influence results from paired-pulse tests, focusing on the repetitive paired-pulse technique; it aims to assess how this technique may be used in an unbiased and quantitative manner across animal preparations for comparisons of control and experimental epileptic animals. METHODS: The perforant path was stimulated while field potentials were recorded from the granule cell layer under isoflurane anesthesia. Paired-pulse suppression was analyzed as a function of stimulation intensity and interpulse interval and frequency. RESULTS: Paired-pulse suppression was greater with increased stimulus intensity and decreased interpulse interval (20-100 ms). During repetitive protocols, stimulation frequencies