Unveiling thermal transitions of polymers in subnanometre pores

The thermal transitions of confined polymers are important for the application of polymers in molecular scale devices and advanced nanotechnology. However, thermal transitions of ultrathin polymer assemblies confined in subnanometre spaces are poorly understood. In this study, we show that incorporation of polyethylene glycol (PEG) into nanochannels of porous coordination polymers (PCPs) enabled observation of thermal transitions of the chain assemblies by differential scanning calorimetry. The pore size and surface functionality of PCPs can be tailored to study the transition behaviour of confined polymers. The transition temperature of PEG in PCPs was determined by manipulating the pore size and the pore–polymer interactions. It is also striking that the transition temperature of the confined PEG decreased as the molecular weight of PEG increased

Working Memory Cells' Behavior May Be Explained by Cross-Regional Networks with Synaptic Facilitation

Neurons in the cortex exhibit a number of patterns that correlate with working memory. Specifically, averaged across trials of working memory tasks, neurons exhibit different firing rate patterns during the delay of those tasks. These patterns include: 1) persistent fixed-frequency elevated rates above baseline, 2) elevated rates that decay throughout the tasks memory period, 3) rates that accelerate throughout the delay, and 4) patterns of inhibited firing (below baseline) analogous to each of the preceding excitatory patterns. Persistent elevated rate patterns are believed to be the neural correlate of working memory retention and preparation for execution of behavioral/motor responses as required in working memory tasks. Models have proposed that such activity corresponds to stable attractors in cortical neural networks with fixed synaptic weights. However, the variability in patterned behavior and the firing statistics of real neurons across the entire range of those behaviors across and within trials of working memory tasks are typical not reproduced. Here we examine the effect of dynamic synapses and network architectures with multiple cortical areas on the states and dynamics of working memory networks. The analysis indicates that the multiple pattern types exhibited by cells in working memory networks are inherent in networks with dynamic synapses, and that the variability and firing statistics in such networks with distributed architectures agree with that observed in the cortex

Epstein-Barr Virus-Encoded LMP1 Interacts with FGD4 to Activate Cdc42 and Thereby Promote Migration of Nasopharyngeal Carcinoma Cells

Epstein-Barr virus (EBV) is closely associated with nasopharyngeal carcinoma (NPC), a human malignancy notorious for its highly metastatic nature. Among EBV-encoded genes, latent membrane protein 1 (LMP1) is expressed in most NPC tissues and exerts oncogenicity by engaging multiple signaling pathways in a ligand-independent manner. LMP1 expression also results in actin cytoskeleton reorganization, which modulates cell morphology and cell motility— cellular process regulated by RhoGTPases, such as Cdc42. Despite the prominent association of Cdc42 activation with tumorigenesis, the molecular basis of Cdc42 activation by LMP1 in NPC cells remains to be elucidated. Here using GST-CBD (active Cdc42-binding domain) as bait in GST pull-down assays to precipitate active Cdc42 from cell lysates, we demonstrated that LMP1 acts through its transmembrane domains to preferentially induce Cdc42 activation in various types of epithelial cells, including NPC cells. Using RNA interference combined with re-introduction experiments, we identified FGD4 (FYVE, RhoGEF and PH domain containing 4) as the GEF (guanine nucleotide exchange factor) responsible for the activation of Cdc42 by LMP1. Serial deletion experiments and co-immunoprecipitation assays further revealed that ectopically expressed FGD4 modulated LMP1-mediated Cdc42 activation by interacting with LMP1. Moreover, LMP1, through its transmembrane domains, directly bound FGD4 and enhanced FGD4 activity toward Cdc42, leading to actin cytoskeleton rearrangement and increased motility of NPC cells. Depletion of FGD4 or Cdc42 significantly reduced (∼50%) the LMP1-stimulated cell motility, an effect that was partially reversed by expression of a constitutively active mutant of Cdc42. Finally, quantitative RT-PCR and immunohistochemistry analyses showed that FGD4 and LMP1 were expressed in NPC tissues, supporting the potential physiologically relevance of this mechanism in NPC. Collectively, our results not only uncover a novel mechanism underlying LMP1-mediated Cdc42 activation, namely LMP1 interaction with FGD4, but also functionally link FGD4 to NPC tumorigenesis

History-Dependent Excitability as a Single-Cell Substrate of Transient Memory for Information Discrimination

Neurons react differently to incoming stimuli depending upon their previous history of stimulation. This property can be considered as a single-cell substrate for transient memory, or context-dependent information processing: depending upon the current context that the neuron “sees” through the subset of the network impinging on it in the immediate past, the same synaptic event can evoke a postsynaptic spike or just a subthreshold depolarization. We propose a formal definition of History-Dependent Excitability (HDE) as a measure of the propensity to firing in any moment in time, linking the subthreshold history-dependent dynamics with spike generation. This definition allows the quantitative assessment of the intrinsic memory for different single-neuron dynamics and input statistics. We illustrate the concept of HDE by considering two general dynamical mechanisms: the passive behavior of an Integrate and Fire (IF) neuron, and the inductive behavior of a Generalized Integrate and Fire (GIF) neuron with subthreshold damped oscillations. This framework allows us to characterize the sensitivity of different model neurons to the detailed temporal structure of incoming stimuli. While a neuron with intrinsic oscillations discriminates equally well between input trains with the same or different frequency, a passive neuron discriminates better between inputs with different frequencies. This suggests that passive neurons are better suited to rate-based computation, while neurons with subthreshold oscillations are advantageous in a temporal coding scheme. We also address the influence of intrinsic properties in single-cell processing as a function of input statistics, and show that intrinsic oscillations enhance discrimination sensitivity at high input rates. Finally, we discuss how the recognition of these cell-specific discrimination properties might further our understanding of neuronal network computations and their relationships to the distribution and functional connectivity of different neuronal types

Towards Understanding the Origin of Cosmic-Ray Positrons

Precision measurements of cosmic ray positrons are presented up to 1 TeV based on 1.9 million positrons collected by the Alpha Magnetic Spectrometer on the International Space Station. The positron flux exhibits complex energy dependence. Its distinctive properties are (a) a significant excess starting from 25.2 +/- 1.8 GeV compared to the lower-energy, power-law trend, (b) a sharp dropoff above 284(-64)(+91) GeV, (c) in the entire energy range the positron flux is well described by the sum of a term associated with the positrons produced in the collision of cosmic rays, which dominates at low energies, and a new source term of positrons, which dominates at high energies, and (d) a finite energy cutoff of the source term of E-s = 810(-180)(+310) GeV is established with a significance of more than 4 sigma. These experimental data on cosmic ray positrons show that, at high energies, they predominantly originate either from dark matter annihilation or from other astrophysical sources

Properties of Neon, Magnesium, and Silicon Primary Cosmic Rays Results from the Alpha Magnetic Spectrometer

We report the observation of new properties of primary cosmic rays, neon (Ne), magnesium (Mg), and silicon (Si), measured in the rigidity range 2.15 GV to 3.0 TV with 1.8 x 10(6) Ne, 2.2 x 10(6) Mg, and 1.6 x 10(6) Si nuclei collected by the Alpha Magnetic Spectrometer experiment on the International Space Station. The Ne and Mg spectra have identical rigidity dependence above 3.65 GV. The three spectra have identical rigidity dependence above 86.5 GV, deviate from a single power law above 200 GV, and harden in an identical way. Unexpectedly, above 86.5 GV the rigidity dependence of primary cosmic rays Ne, Mg, and Si spectra is different from the rigidity dependence of primary cosmic rays He, C, and O. This shows that the Ne, Mg, and Si and He, C, and O are two different classes of primary cosmic rays

Properties of Cosmic Helium Isotopes Measured by the Alpha Magnetic Spectrometer

Precision measurements by the Alpha Magnetic Spectrometer (AMS) on the International Space Station of He-3 and He-4 fluxes are presented. The measurements are based on 100 million He-4 nuclei in the rigidity range from 2.1 to 21 GV and 18 million He-3 from 1.9 to 15 GV collected from May 2011 to November 2017. We observed that the He-3 and He-4 fluxes exhibit nearly identical variations with time. The relative magnitude of the variations decreases with increasing rigidity. The rigidity dependence of the He-3/He-4 flux ratio is measured for the first time. Below 4 GV, the He-3/He-4 flux ratio was found to have a significant long-term time dependence. Above 4 GV, the He-3/He-4 flux ratio was found to be time independent, and its rigidity dependence is well described by a single power law proportional to R-Delta with Delta = 0.294 0.004. Unexpectedly, this value is in agreement with the B/O and B/C spectral indices at high energies

Towards Understanding the Origin of Cosmic-Ray Electrons

Precision results on cosmic-ray electrons are presented in the energy range from 0.5 GeV to 1.4 TeV based on 28.1 x 10(6) electrons collected by the Alpha Magnetic Spectrometer on the International Space Station. In the entire energy range the electron and positron spectra have distinctly different magnitudes and energy dependences. The electron flux exhibits a significant excess starting from 42.1(-5.2)(+5.4) GeV compared to the lower energy trends, but the nature of this excess is different from the positron flux excess above 25.2 +/- 1.8 GeV. Contrary to the positron flux, which has an exponential energy cutoff of 810(-180)(+310) GeV, at the 5 sigma level the electron flux does not have an energy cutoff below 1.9 TeV. In the entire energy range the electron flux is well described by the sum of two power law components. The different behavior of the cosmic-ray electrons and positrons measured by the Alpha Magnetic Spectrometer is clear evidence that most high energy electrons originate from different sources than high energy positrons