Remodeling of Fibrous Extracellular Matrices by Contractile Cells: Predictions from Discrete Fiber Network Simulations

Contractile forces exerted on the surrounding extracellular matrix (ECM) lead to the alignment and stretching of constituent fibers within the vicinity of cells. As a consequence, the matrix reorganizes to form thick bundles of aligned fibers that enable force transmission over distances larger than the size of the cells. Contractile force-mediated remodeling of ECM fibers has bearing on a number of physiologic and pathophysiologic phenomena. In this work, we present a computational model to capture cell-mediated remodeling within fibrous matrices using finite element based discrete fiber network simulations. The model is shown to accurately capture collagen alignment, heterogeneous deformations, and long-range force transmission observed experimentally. The zone of mechanical influence surrounding a single contractile cell and the interaction between two cells are predicted from the strain-induced alignment of fibers. Through parametric studies, the effect of cell contractility and cell shape anisotropy on matrix remodeling and force transmission are quantified and summarized in a phase diagram. For highly contractile and elongated cells, we find a sensing distance that is ten times the cell size, in agreement with experimental observations.Comment: Accepted for publication in the Biophysical Journa

Indications of superconductivity in doped highly oriented pyrolytic graphite

We have observed possible superconductivity using standard resistance vs. temperature techniques in phosphorous ion implanted Highly Oriented Pyrolytic Graphite. The onset appears to be above 100 K and quenching by an applied magnetic field has been observed. The four initial boron implanted samples showed no signs of becoming superconductive whereas all four initial and eight subsequent samples that were implanted with phosphorous showed at least some sign of the existence of small amounts of the possibly superconducting phases. The observed onset temperature is dependent on both the number of electron donors present and the amount of damage done to the graphene sub-layers in the Highly Oriented Pyrolytic Graphite samples. As a result the data appears to suggest that the potential for far higher onset temperatures in un-damaged doped graphite exists.Comment: 7 pages, 1 table, 5 figures, 11 references, Acknowledgments section was correcte

Tracing the energetics and evolution of dust with Spitzer : a chapter in the history of the Eagle Nebula

Context. The Spitzer GLIMPSE and MIPSGAL surveys have revealed a wealth of details about the Galactic plane in the infrared (IR)with orders of magnitude higher sensitivity, higher resolution, and wider coverage than previous IR observations. The structure of the interstellar medium (ISM) is tightly connected to the countless star-forming regions. We use these surveys to study the energetics and dust properties of the Eagle Nebula (M16), one of the best known star-forming regions. Aims. We present MIPSGAL observations of M16 at 24 and 70 μm and combine them with previous IR data. The mid-IR image shows a shell inside the well-known molecular borders of the nebula, as in the ISO and MSX observations from 15 to 21 μm. The morphologies at 24 and 70 μm are quite different, and its color ratio is unusually warm. The far-IR image resembles the one at 8 μm that enhances the structure of the molecular cloud and the "pillars of creation". We use this set of IR data to analyze the dust energetics and properties within this template for Galactic star-forming regions. Methods. We measure IR spectral energy distributions (SEDs) across the entire nebula, both within the inner shell and the photodissociation regions (PDRs).We use the DUSTEM model to fit these SEDs and constrain the dust temperature, the dust-size distribution, and the radiation field intensity relative to that provided by the star cluster NGC 6611 (χ/χ0). Results. Within the PDRs, the inferred dust temperature (~35 K), the dust-size distribution, and the radiation field intensity (χ/χ0 < 1) are consistent with expectations. Within the inner shell, the dust is hotter (~70 K). Moreover, the radiation field required to fit the SED is larger than that provided by NGC 6611 (χ/χ0 > 1). We quantify two solutions to this problem: (1) The size distribution of the dust in the shell is not that of interstellar dust. There is a significant enhancement of the carbon dust-mass in stochastically heated very small grains. (2) The dust emission arises from a hot (~10^6 K) plasma where both UV and collisions with electrons contribute to the heating. Within this hypothesis, the shell SED may be fit for a plasma pressure p/k ~ 5 × 10^7 K cm^(−3). Conclusions. We suggest two interpretations for the M16 inner shell: (1) The shell matter is supplied by photo-evaporative flows arising from dense gas exposed to ionized radiation. The flows renew the shell matter as it is pushed out by the pressure from stellar winds. Within this scenario, we conclude that massive-star forming regions such as M16 have a major impact on the carbon dustsize distribution. The grinding of the carbon dust could result from shattering in grain-grain collisions within shocks driven by the dynamical interaction between the stellar winds and the shell. (2) We also consider a more speculative scenario where the shell is a supernova remnant. In this case, we would be witnessing a specific time in the evolution of the remnant where the plasma pressure and temperature would enable the remnant to cool through dust emission

Learning Mixtures of Polynomials of Conditional Densities from Data

Mixtures of polynomials (MoPs) are a non-parametric density estimation technique for hybrid Bayesian networks with continuous and discrete variables. We propose two methods for learning MoP approximations of conditional densities from data. Both approaches are based on learning MoP approximations of the joint density and the marginal density of the conditioning variables, but they differ as to how the MoP approximation of the quotient of the two densities is found. We illustrate the methods using data sampled from a simple Gaussian Bayesian network. We study and compare the performance of these methods with the approach for learning mixtures of truncated basis functions from data

The Thermal Evolution of Ices in the Environments of Newly Formed Stars: The CO_2 Diagnostic

Archival data from the Infrared Spectrometer of the Spitzer Space Telescope are used to study the 15 μm absorption feature of solid CO_2 toward 28 young stellar objects (YSOs) of approximately solar mass. Fits to the absorption profile using laboratory spectra enable categorization according to the degree of thermal processing of the ice matrix that contains the CO_2. The majority of YSOs in our sample (20 out of 28) are found to be consistent with a combination of polar (H_2O-rich) and nonpolar (CO-rich) ices at low temperature; the remainder exhibit profile structure consistent with partial crystallization as the result of significant heating. Ice-phase column densities of CO_2 are determined and compared with those of other species. Lines of sight with crystallization signatures in their spectra are found to be systematically deficient in solid-phase CO, as expected if CO is being sublimated in regions where the ices are heated to crystallization temperatures. Significant variation is found in the CO2 abundance with respect to both H_2O (the dominant ice constituent) and total dust column (quantified by the extinction, AV ). YSOs in our sample display typically higher CO_2 concentrations (independent of evidence for thermal processing) in comparison to quiescent regions of the prototypical cold molecular cloud. This suggests that enhanced CO_2 production is driven by photochemical reactions in proximity to some YSOs, and that photoprocessing and thermal processing may occur independently

Growth inhibition of cytosolic Salmonella by caspase-1 and caspase-11 precedes host cell death

Sensing bacterial products in the cytosol of mammalian cells by NOD-like receptors leads to the activation of caspase-1 inflammasomes, and the production of the pro-inflammatory cytokines interleukin (IL)-18 and IL-1β. In addition, mouse caspase-11 (represented in humans by its orthologs, caspase-4 and caspase-5) detects cytosolic bacterial LPS directly. Activation of caspase-1 and caspase-11 initiates pyroptotic host cell death that releases potentially harmful bacteria from the nutrient-rich host cell cytosol into the extracellular environment. Here we use single cell analysis and time-lapse microscopy to identify a subpopulation of host cells, in which growth of cytosolic Salmonella Typhimurium is inhibited independently or prior to the onset of cell death. The enzymatic activities of caspase-1 and caspase-11 are required for growth inhibition in different cell types. Our results reveal that these proteases have important functions beyond the direct induction of pyroptosis and proinflammatory cytokine secretion in the control of growth and elimination of cytosolic bacteria

Controls of dimethyl sulphide in the Bay of Bengal during BOBMEX-Pilot cruise 1998

The air-sea exchange is one of the main mechanisms maintaining the abundances of trace gases in the atmosphere. Some of these, such as carbon dioxide and dimethyl sulphide (DMS), will have a bearing on the atmospheric heat budget. While the former facilitates the trapping of radiation (greenhouse effect) the latter works in the opposite direction through reflectance of radiation back into space by sulphate aerosols that form from oxidation of DMS in atmosphere. Here we report on the first measurements made on DMS in the Bay of Bengal and the factors regulating its abundance in seawater. Phytoplankton alone does not seem to control the extent of DMS concentrations. We find that changes in salinity could effectively regulate the extent of DMSP production by marine phytoplankton. In addition, we provide the first ever evidence to the occurrence of DMS precursor, DMSP, in marine aerosols collected in the boundary layer. This suggests that the marine aerosol transport of DMSP will supplement DMS gaseous evasion in maintaining the atmospheric non-sea salt sulphur budget

From melt flow index to rheogram

A knowledge of the complete flow curve or rheogram of a polymeric melt depicting the variation of the melt viscosity over industrially relevant range of shear rate and temperature is essential in the design of polymer processing equipment, process optimization and trouble-shooting. These data are generated on sophisticated rheometers that are beyond the financial and technical means of most plastics processors. The only flow parameter available to the processor is the melt flow index of the material. In the present work, a method has been proposed to estimate the rheograms of a melt at temperatures relevant to its processing conditions with the use of a master curve, knowing the melt flow index and glass transition temperature of the material. Master curves that coalesce rheograms of different grades at various temperatures have been generated and presented for low density polyethylene, high density polyethylene, polypropylene, polystyrene and styrene-acrylonitrile copolymer