Intrinsic regulation of FIC-domain AMP-transferases by oligomerization and automodification

Filamentation induced by cyclic AMP (FIC)-domain enzymes catalyze adenylylation or other posttranslational modifications of target proteins to control their function. Recently, we have shown that Fic enzymes are autoinhibited by an α-helix (αinh) that partly obstructs the active site. For the single-domain class III Fic proteins, the αinh is located at the C terminus and its deletion relieves autoinhibition. However, it has remained unclear how activation occurs naturally. Here, we show by structural, biophysical, and enzymatic analyses combined with in vivo data that the class III Fic protein NmFic from Neisseria meningitidis gets autoadenylylated in cis, thereby autonomously relieving autoinhibition and thus allowing subsequent adenylylation of its target, the DNA gyrase subunit GyrB. Furthermore, we show that NmFic activation is antagonized by tetramerization. The combination of autoadenylylation and tetramerization results in nonmonotonic concentration dependence of NmFic activity and a pronounced lag phase in the progress of target adenylylation. Bioinformatic analyses indicate that this elaborate dual-control mechanism is conserved throughout class III Fic proteins

Swimmer-tracer scattering at low Reynolds number

Understanding the stochastic dynamics of tracer particles in active fluids is important for identifying the physical properties of flow generating objects such as colloids, bacteria or algae. Here, we study both analytically and numerically the scattering of a tracer particle in different types of time-dependent, hydrodynamic flow fields. Specifically, we compare the tracer motion induced by an externally driven colloid with the one generated by various self-motile, multi-sphere swimmers. Our results suggest that force-free swimmers generically induce loop-shaped tracer trajectories. The specific topological structure of these loops is determined by the hydrodynamic properties of the microswimmer. Quantitative estimates for typical experimental conditions imply that the loops survive on average even if Brownian motion effects are taken into account.Comment: 14 pages, to appear in Soft Matte

Langevin Equation for the Rayleigh model with finite-ranged interactions

Both linear and nonlinear Langevin equations are derived directly from the Liouville equation for an exactly solvable model consisting of a Brownian particle of mass $M$ interacting with ideal gas molecules of mass $m$ via a quadratic repulsive potential. Explicit microscopic expressions for all kinetic coefficients appearing in these equations are presented. It is shown that the range of applicability of the Langevin equation, as well as statistical properties of random force, may depend not only on the mass ratio $m/M$ but also by the parameter $Nm/M$, involving the average number $N$ of molecules in the interaction zone around the particle. For the case of a short-ranged potential, when $N\ll 1$, analysis of the Langevin equations yields previously obtained results for a hard-wall potential in which only binary collisions are considered. For the finite-ranged potential, when multiple collisions are important ($N\gg 1$), the model describes nontrivial dynamics on time scales that are on the order of the collision time, a regime that is usually beyond the scope of more phenomenological models.Comment: 21 pages, 1 figure. To appear in Phys. Rev.

Continuum extrapolation of the gradient-flowed color-magnetic correlator at 1.5 Tc1.5\,T_c

In a recently published work we employ gradient flow on the lattice to extract the leading contribution of the heavy quark momentum diffusion coefficient in the heavy quark limit from calculations of a well-known two-point function of color-electric field operators. In this article we want to report the progress of calculating the recently derived color-magnetic correlator that encodes a finite mass correction to this transport coefficient. The calculations we present here are based on the same ensemble of quenched gauge configurations at $1.5\, T_c$ that we previously used for the color-electric correlator.Comment: 7 pages, 4 figures, presented at the 38th International Symposium on Lattice Field Theor

Low Reynolds number hydrodynamics of asymmetric, oscillating dumbbell pairs

Active dumbbell suspensions constitute one of the simplest model system for collective swimming at low Reynolds number. Generalizing recent work, we derive and analyze stroke-averaged equations of motion that capture the effective hydrodynamic far-field interaction between two oscillating, asymmetric dumbbells in three space dimensions. Time-averaged equations of motion, as those presented in this paper, not only yield a considerable speed-up in numerical simulations, they may also serve as a starting point when deriving continuum equations for the macroscopic dynamics of multi-swimmer suspensions. The specific model discussed here appears to be particularly useful in this context, since it allows one to investigate how the collective macroscopic behavior is affected by changes in the microscopic symmetry of individual swimmers.Comment: 10 pages, to appear in EPJ Special Topic

Lattice QCD noise reduction for bosonic correlators through blocking

We propose a method to substantially improve the signal-to-noise ratio of lattice correlation functions for bosonic operators or other operator combinations with disconnected contributions. The technique is applicable for correlations between operators on two planes (zero momentum correlators) when the dimension of the plane is larger than the separation between the two planes which are correlated. In this case, the correlation arises primarily from points whose in-plane coordinates are close, but noise arises from all pairs of points. By breaking each plane into bins and computing bin-bin correlations, it is possible to capture these short-distance correlators exactly while replacing (small) correlators at large spatial extent with a fit, with smaller uncertainty than the data. The cost is only marginally larger than averaging each plane before correlating, but the improvement in signal-to-noise can be substantial. We test the method on correlators of the gradient-flowed topological charge density and squared field strength, finding noise reductions by a factor of ∼3–7 compared to the conventional approach on the same ensemble of configurations

Indexed left ventricular mass to QRS voltage ratio is associated with heart failure hospitalizations in patients with cardiac amyloidosis

In cardiac amyloidosis (CA), amyloid infiltration results in increased left ventricular (LV) mass disproportionate to electrocardiographic (EKG) voltage. We assessed the relationship between LV mass-voltage ratio with subsequent heart failure hospitalization (HHF) and mortality in CA. Patients with confirmed CA and comprehensive cardiovascular magnetic resonance (CMR) and EKG exams were included. CMR-derived LV mass was indexed to body surface area. EKG voltage was assessed using Sokolow, Cornell, and Limb-voltage criteria. The optimal LV mass-voltage ratio for predicting outcomes was determined using receiver operating characteristic curve analysis. The relationship between LV mass-voltage ratio and HHF was assessed using Cox proportional hazards analysis adjusting for significant covariates. A total of 85 patients (mean 69 ± 11 years, 22% female) were included, 42 with transthyretin and 43 with light chain CA. At a median of 3.4-year follow-up, 49% of patients experienced HHF and 60% had died. In unadjusted analysis, Cornell LV mass-voltage ratio was significantly associated with HHF (HR, 1.05; 95% CI 1.02-1.09, p = 0.001) and mortality (HR, 1.05; 95% CI 1.02-1.07, p = 0.001). Using ROC curve analysis, the optimal cutoff value for Cornell LV mass-voltage ratio to predict HHF was 6.7 gm/m2/mV. After adjusting for age, NYHA class, BNP, ECV, and LVEF, a Cornell LV mass-voltage ratio > 6.7 gm/m2/mV was significantly associated with HHF (HR 2.25, 95% CI 1.09-4.61; p = 0.03) but not mortality. Indexed LV mass-voltage ratio is associated with subsequent HHF and may be a useful prognostic marker in cardiac amyloidosis

Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models

Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions