Comparing ion conductance recordings of synthetic lipid bilayers with cell membranes containing TRP channels

In this article we compare electrical conductance events from single channel recordings of three TRP channel proteins (TRPA1, TRPM2 and TRPM8) expressed in human embryonic kidney cells with channel events recorded on synthetic lipid membranes close to melting transitions. Ion channels from the TRP family are involved in a variety of sensory processes including thermo- and mechano-reception. Synthetic lipid membranes close to phase transitions display channel-like events that respond to stimuli related to changes in intensive thermodynamic variables such as pressure and temperature. TRP channel activity is characterized by typical patterns of current events dependent on the type of protein expressed. Synthetic lipid bilayers show a wide spectrum of electrical phenomena that are considered typical for the activity of protein ion channels. We find unitary currents, burst behavior, flickering, multistep-conductances, and spikes behavior in both preparations. Moreover, we report conductances and lifetimes for lipid channels as described for protein channels. Non-linear and asymmetric current-voltage relationships are seen in both systems. Without further knowledge of the recording conditions, no easy decision can be made whether short current traces originate from a channel protein or from a pure lipid membraneComment: 13 pages, 9 Figure

The influence of anesthetics, neurotransmitters and antibiotics on the relaxation processes in lipid membranes

In the proximity of melting transitions of artificial and biological membranes fluctuations in enthalpy, area, volume and concentration are enhanced. This results in domain formation, changes of the elastic constants, changes in permeability and slowing down of relaxation processes. In this study we used pressure perturbation calorimetry to investigate the relaxation time scale after a jump into the melting transition regime of artificial lipid membranes. This time corresponds to the characteristic rate of domain growth. The studies were performed on single-component large unilamellar and multilamellar vesicle systems with and without the addition of small molecules such as general anesthetics, neurotransmitters and antibiotics. These drugs interact with membranes and affect melting points and profiles. In all systems we found that heat capacity and relaxation times are related to each other in a simple manner. The maximum relaxation time depends on the cooperativity of the heat capacity profile and decreases with a broadening of the transition. For this reason the influence of a drug on the time scale of domain formation processes can be understood on the basis of their influence on the heat capacity profile. This allows estimations of the time scale of domain formation processes in biological membranes.Comment: 12 pages, 6 figure

Flux-Induced Vortex in Mesoscopic Superconducting Loops

We predict the existence of a quantum vortex for an unusual situation. We study the order parameter in doubly connected superconducting samples embedded in a uniform magnetic field. For samples with perfect cylindrical symmetry, the order parameter has been known for long and no vortices are present in the linear regime. However, if the sample is not symmetric, there exist ranges of the field for which the order parameter vanishes along a line, parallel to the field. In many respects, the behavior of this line is qualitatively different from that of the vortices encountered in type II superconductivity. For samples with mirror symmetry, this flux-induced vortex appears at the thin side for small fluxes and at the opposite side for large fluxes. We propose direct and indirect experimental methods which could test our predictions.Comment: 6 pages, Latex, 4 figs., uses RevTex, extended to situations far from cylindrical symmetr

Phase transitions in biological membranes

Native membranes of biological cells display melting transitions of their lipids at a temperature of 10-20 degrees below body temperature. Such transitions can be observed in various bacterial cells, in nerves, in cancer cells, but also in lung surfactant. It seems as if the presence of transitions slightly below physiological temperature is a generic property of most cells. They are important because they influence many physical properties of the membranes. At the transition temperature, membranes display a larger permeability that is accompanied by ion-channel-like phenomena even in the complete absence of proteins. Membranes are softer, which implies that phenomena such as endocytosis and exocytosis are facilitated. Mechanical signal propagation phenomena related to nerve pulses are strongly enhanced. The position of transitions can be affected by changes in temperature, pressure, pH and salt concentration or by the presence of anesthetics. Thus, even at physiological temperature, these transitions are of relevance. There position and thereby the physical properties of the membrane can be controlled by changes in the intensive thermodynamic variables. Here, we review some of the experimental findings and the thermodynamics that describes the control of the membrane function.Comment: 23 pages, 15 figure

Theory of superconductor with kappa close to 1/sqrt{2}

As was firstly shown by E. Bogomolny, the critical Ginzburg-Landay (GL) parameter kappa =1/sqrt{2} at which a superconductor changes its behavior from type-I to type-II, is the special highly degenerate point where Abrikosov vortices do not interact and therefore all vortex states have the same energy. Developing a secular perturbation theory we studied how this degeneracy is lifted when kappa is slightly different from 1\sqrt{2} or when the GL theory is extended to the higher in T-Tc terms. We constructed a simple secular functional, that depends only on few experimentally measurable phenomenological parameters and therefore is quite efficient to study the vortex state of superconductor in this transitional region of kappa. Basing on this, we calculated such vortex state properties as: critical fields, energy of the normal-superconductor interface, energy of the vortex lattice, vortex interaction energy etc. and compared them with previous results that were based on bulky solutions of GL equations.Comment: Revtex, 14 pages, 4 postscript pictures embedded in the tex

Action anticipation based on an agent's epistemic state in toddlers and adults

Do toddlers and adults engage in spontaneous Theory of Mind (ToM)? Evidence from anticipatory looking (AL) studies suggests that they do. But a growing body of failed replication studies raised questions about the paradigm’s suitability. In this multi-lab collaboration, we test the robustness of spontaneous ToM measures. We examine whether 18- to 27-month-olds’ and adults’ anticipatory looks distinguish between two basic forms of an agent’s epistemic states: knowledge and ignorance. In toddlers [ANTICIPATED n = 520 50% FEMALE] and adults [ANTICIPATED n = 408, 50% FEMALE] from diverse ethnic backgrounds, we found [SUPPORT/NO SUPPORT] for epistemic state-based action anticipation. Future research can probe whether this conclusion extends to more complex kinds of epistemic states, such as true and false beliefs

The spin label amino acid TOAC and its uses in studies of peptides: chemical, physicochemical, spectroscopic, and conformational aspects

We review work on the paramagnetic amino acid 2,2,6,6-tetramethyl-N-oxyl-4-amino-4-carboxylic acid, TOAC, and its applications in studies of peptides and peptide synthesis. TOAC was the first spin label probe incorporated in peptides by means of a peptide bond. In view of the rigid character of this cyclic molecule and its attachment to the peptide backbone via a peptide bond, TOAC incorporation has been very useful to analyze backbone dynamics and peptide secondary structure. Many of these studies were performed making use of EPR spectroscopy, but other physical techniques, such as X-ray crystallography, CD, fluorescence, NMR, and FT-IR, have been employed. The use of double-labeled synthetic peptides has allowed the investigation of their secondary structure. A large number of studies have focused on the interaction of peptides, both synthetic and biologically active, with membranes. In the latter case, work has been reported on ligands and fragments of GPCR, host defense peptides, phospholamban, and β-amyloid. EPR studies of macroscopically aligned samples have provided information on the orientation of peptides in membranes. More recent studies have focused on peptide–protein and peptide–nucleic acid interactions. Moreover, TOAC has been shown to be a valuable probe for paramagnetic relaxation enhancement NMR studies of the interaction of labeled peptides with proteins. The growth of the number of TOAC-related publications suggests that this unnatural amino acid will find increasing applications in the future

Show me the world: Object categorization and socially guided object learning in infancy

How infants acquire knowledge about animate beings and physical objects has been of interest to developmental psychologists for many years. In this article, we provide evidence suggesting that by 7 months, infants have formed a global animate-inanimate distinction that seems to be based on previously acquired knowledge. This knowledge may allow infants to analyze triadic social interactions involving another animate being and a physical object in more complex ways. Whereas 3- to 4-month-olds respond to object-directed social cues such as eye gaze or facial expressions more or less automatically, 9- to 12-month-olds seem to integrate social and object knowledge to allocate their attentional resources. Twelve-month-olds can even detect person-specific preferences for an entire category of objects. Based on this evidence, we conclude that infants’ learning about social beings and physical objects is closely related, but changes substantially in preverbal children

Backward-Compatible Prediction Updates: A Probabilistic Approach

When machine learning systems meet real world applications, accuracy is only one of several requirements. In this paper, we assay a complementary perspective originating from the increasing availability of pre-trained and regularly improving state-of-the-art models. While new improved models develop at a fast pace, downstream tasks vary more slowly or stay constant. Assume that we have a large unlabelled data set for which we want to maintain accurate predictions. Whenever a new and presumably better ML models becomes available, we encounter two problems: (i) given a limited budget, which data points should be re-evaluated using the new model?; and (ii) if the new predictions differ from the current ones, should we update? Problem (i) is about compute cost, which matters for very large data sets and models. Problem (ii) is about maintaining consistency of the predictions, which can be highly relevant for downstream applications; our demand is to avoid negative flips, i.e., changing correct to incorrect predictions. In this paper, we formalize the Prediction Update Problem and present an efficient probabilistic approach as answer to the above questions. In extensive experiments on standard classification benchmark data sets, we show that our method outperforms alternative strategies along key metrics for backward-compatible prediction updates