A robust high-sensitivity algorithm for automated detection of proteins in two-dimensional electrophoresis gels

The automated interpretation of two-dimensional gel electrophoresis images used in protein separation and analysis presents a formidable problem in the detection and characterization of ill-defined spatial objects. We describe in this paper a hierarchical algorithm that provides a robust, high-sensitivity solution to this problem, which can be easily adapted to a variety of experimental situations. The software implementation of this algorithm functions as part of a complete package designed for general protein gel analysis applications

Effects of radiative and microphysical processes on simulated warm and transition season Arctic stratus

October 17, 1997.Also issued as author's dissertation (Ph.D.) -- Colorado State University, 1997.Includes bibliographical references.A cloud-resolving model (CRM) version of RAMS, coupled to explicit bin resolving microphysics and a new two-stream radiative transfer code is used to study various aspects of Arctic stratus clouds (ASC). The two-stream radiative transfer model is coupled in a consistent fashion to the bulk microphysical parameterization of Walko et al. (1995), an explicit liquid bin microphysical model (e.g., Feingold et al. 1996a) and a mixed-phase rnicrophysical model (Reisin et al., 1996). These models are used to study both warm (summer) season and transition (fall and spring) season ASC. Equations are developed for the inclusion of the radiative term in the drop growth equation and the effect is studied in a trajectory parcel model (TPM) and the CRM. Arctic stratus simulated with the new CRM framework compared well with the observations of Curry (1986). Along with CCN concentrations, it is shown that drop distribution shape and optical property methods strongly impact cloud evolution through their effect on the radiative properties. Broader cloud top distributions lead to clouds with more shallow depths and circulation strengths as more shortwave radiation is absorbed while the opposite occurs for narrow distribution functions. Radiative-cloud interactions using mean effective radii are shown to be problematic, while conserving re and N of the distribution function (as per Hu and Stamnes, 1993) produces similar cloud evolution as compared to detailed computations. Radiative effects on drop vapor deopsition growth can produce drizzle about 30 minutes earlier and is strongly dependent upon cloud top residence time of the parcels. The same set of trajectories assists drizzle production in the radiation and no-radiation cases. Not only is the growth of larger drops enhanced by the radiative effect, but drops with r < 10µm are caused to evaporate; the effects together constitute a method of spectral broadening at cloud top. Simulations with the CRM show a smaller impact of the radiative influence; this is attributed to the spurious production of cloud top supersaturations by Eulerian models (Stevens et al., 1996a). Simulations of transition season ASC shows that boundary layer stability is strongly dependent upon ice processes, illustrating that the rapid reduction in fall stratus cloud cover may be forced, in part, by microphysical processes. Cloud stability is shown to be strongly dependent upon the cloud temperature, ice concentration, precipitation rate and the indirect effects of ice crystals on cloud top radiative cooling while ice aggregation has a weak effect. Transitions from predominately mixed to stable boundary layers occur and are a function of ice sublimation and precipitation; ice habit strongly constrains the effect. Frequently observed autumnal stable layers may be formed in this fashion. A new method of multiple cloud layer formation is discussed and occurs through the rapid loss of ice from the upper cloud layer, which moistens and cools (sublimation and radiation) the lower layers causing droplet activation.Sponsored by the Awards for Science and Engineering Research Training under contract F49620-95-1-0386; NOAA/FAA under contract NA37RJ020-ITEM14; AFOSR under grant F49620-95-1-0132; and DOES-ARM under grant DE-FG03-95ER61958

Ice Supersaturation Variability in Cirrus Clouds: Role of Vertical Wind Speeds and Deposition Coefficients

Aircraft measurements reveal ice supersaturation statistics in cirrus (ISSs) with broad maxima around ice saturation and pronounced variance. In this study, processes shaping ISSs in midlatitude and tropical upper tropospheric conditions are systematically investigated. Water vapor deposition and sublimation of size-resolved ice crystal populations are simulated in an air parcel framework. Mesoscale temperature fluctuations (MTFs) due to gravity waves force the temporal evolution of supersaturation. Various levels of background wave forcing and cirrus thickness are distinguished in stochastic ensemble simulations. Kinetic limitations to ice mass growth are brought about by supersaturation-dependent deposition coefficients that represent efficient and inefficient growth modes as a function of ice crystal size. The simulations identify a wide range of deposition coefficients in cirrus, but most values stay above 0.01 such that kinetic limitations to water uptake remain moderate. Supersaturation quenching times are long, typically 0.5–2 hr. The wave forcing thus causes a remarkably large variability in ISSs and cirrus microphysical properties except in the thickest cirrus, producing ensemble-mean ISSs in line with in-situ measurements. ISS variance is controlled by MTFs and increases with decreasing cirrus integral radii. In comparison, the impact of ice crystal growth rates on ISSs is small. These results contribute to efforts directed at identifying and solving issues associated with ice-supersaturated areas and non-equilibrium cirrus physics in global models

Characterisation of Non-Autoinducing Tropodithietic Acid (TDA) Production from Marine Sponge Pseudovibrio Species.

The search for new antimicrobial compounds has gained added momentum in recent years, paralleled by the exponential rise in resistance to most known classes of current antibiotics. While modifications of existing drugs have brought some limited clinical success, there remains a critical need for new classes of antimicrobial compound to which key clinical pathogens will be naive. This has provided the context and impetus to marine biodiscovery programmes that seek to isolate and characterize new activities from the aquatic ecosystem. One new antibiotic to emerge from these initiatives is the antibacterial compound tropodithietic acid (TDA). The aim of this study was to provide insight into the bioactivity of and the factors governing the production of TDA in marine Pseudovibrio isolates from a collection of marine sponges. The TDA produced by these Pseudovibrio isolates exhibited potent antimicrobial activity against a broad spectrum of clinical pathogens, while TDA tolerance was frequent in non-TDA producing marine isolates. Comparative genomics analysis suggested a high degree of conservation among the tda biosynthetic clusters while expression studies revealed coordinated regulation of TDA synthesis upon transition from log to stationary phase growth, which was not induced by TDA itself or by the presence of the C10-acyl homoserine lactone quorum sensing signal molecule

Disentangling Changes in the Spectral Shape of Chlorophyll Fluorescence : Implications for Remote Sensing of Photosynthesis

Novel satellite measurements of solar-induced chlorophyll fluorescence (SIF) can improve our understanding of global photosynthesis; however, little is known about how to interpret the controls on its spectral variability. To address this, we disentangle simultaneous drivers of fluorescence spectra by coupling active and passive fluorescence measurements with photosynthesis. We show empirical and mechanistic evidence for where, why, and to what extent leaf fluorescence spectra change. Three distinct components explain more than 95% of the variance in leaf fluorescence spectra under both steady-state and changing illumination conditions. A single spectral shape of fluorescence explains 84% of the variance across a wide range of species. The magnitude of this shape responds to absorbed light and photosynthetic up/down regulation; meanwhile, chlorophyll concentration and nonphotochemical quenching control 9% and 3% of the remaining spectral variance, respectively. The spectral shape of fluorescence is remarkably stable where most current satellite retrievals occur (far-red, >740nm), and dynamic downregulation of photosynthesis reduces fluorescence magnitude similarly across the 670- to 850-nm range. We conduct an exploratory analysis of hourly red and far-red canopy SIF in soybean, which shows a subtle change in red:far-red fluorescence coincident with photosynthetic downregulation but is overshadowed by longer-term changes in canopy chlorophyll and structure. Based on our leaf and canopy analysis, caution should be taken when attributing large changes in the spectral shape of remotely sensed SIF to plant stress, particularly if data acquisition is temporally sparse. Ultimately, changes in SIF magnitude at wavelengths greater than 740 nm alone may prove sufficient for tracking photosynthetic dynamics. Plain Language Summary Satellite remote sensing provides a global picture of photosynthetic activity-allowing us to see when, where, and how much CO2 plants are assimilating. To do this, satellites measure a small emission of energy from the plants called chlorophyll fluorescence. However, this measurement is typically made across a narrow wavelength range, while the emission spectrum (650-850 nm) is quite dynamic. We show where, why, and to what extent leaf fluorescence spectra change across a diverse range of species and conditions, ultimately informing canopy remote sensing measurements. Results suggest that wavelengths currently used by satellites are stable enough to track the downregulation of photosynthesis resulting from stress, while spectral shape changes respond more strongly to dynamics in canopy structure and chlorophyll concentration.Peer reviewe

Intercomparison of Large-Eddy Simulations of Arctic Mixed-Phase Clouds: Importance of Ice Size Distribution Assumptions

Large-eddy simulations of mixed-phase Arctic clouds by 11 different models are analyzed with the goal of improving understanding and model representation of processes controlling the evolution of these clouds. In a case based on observations from the Indirect and Semi-Direct Aerosol Campaign (ISDAC), it is found that ice number concentration, Ni, exerts significant influence on the cloud structure. Increasing Ni leads to a substantial reduction in liquid water path (LWP), in agreement with earlier studies. In contrast to previous intercomparison studies, all models here use the same ice particle properties (i.e., mass-size, mass-fall speed, and mass-capacitance relationships) and a common radiation parameterization. The constrained setup exposes the importance of ice particle size distributions (PSDs) in influencing cloud evolution. A clear separation in LWP and IWP predicted by models with bin and bulk microphysical treatments is documented and attributed primarily to the assumed shape of ice PSD used in bulk schemes. Compared to the bin schemes that explicitly predict the PSD, schemes assuming exponential ice PSD underestimate ice growth by vapor deposition and overestimate mass-weighted fall speed leading to an underprediction of IWP by a factor of two in the considered case. Sensitivity tests indicate LWP and IWP are much closer to the bin model simulations when a modified shape factor which is similar to that predicted by bin model simulation is used in bulk scheme. These results demonstrate the importance of representation of ice PSD in determining the partitioning of liquid and ice and the longevity of mixed-phase clouds

Intercomparison of cloud model simulations of Arctic mixed‐phase boundary layer clouds observed during SHEBA/FIRE‐ACE

An intercomparison of six cloud‐resolving and large‐eddy simulation models is presented. This case study is based on observations of a persistent mixed‐phase boundary layer cloud gathered on 7 May, 1998 from the Surface Heat Budget of Arctic Ocean (SHEBA) and First ISCCP Regional Experiment ‐ Arctic Cloud Experiment (FIRE‐ACE). Ice nucleation is constrained in the simulations in a way that holds the ice crystal concentration approximately fixed, with two sets of sensitivity runs in addition to the baseline simulations utilizing different specified ice nucleus (IN) concentrations. All of the baseline and sensitivity simulations group into two distinct quasi‐steady states associated with either persistent mixed‐phase clouds or all‐ice clouds after the first few hours of integration, implying the existence of multiple states for this case. These two states are associated with distinctly different microphysical, thermodynamic, and radiative characteristics. Most but not all of the models produce a persistent mixed‐phase cloud qualitatively similar to observations using the baseline IN/crystal concentration, while small increases in the IN/crystal concentration generally lead to rapid glaciation and conversion to the all‐ice state. Budget analysis indicates that larger ice deposition rates associated with increased IN/crystal concentrations have a limited direct impact on dissipation of liquid in these simulations. However, the impact of increased ice deposition is greatly enhanced by several interaction pathways that lead to an increased surface precipitation flux, weaker cloud top radiative cooling and cloud dynamics, and reduced vertical mixing, promoting rapid glaciation of the mixed‐phase cloud for deposition rates in the cloud layer greater than about 1 − 2 × 10−5 g kg−1 s−1 for this case. These results indicate the critical importance of precipitation‐radiative‐dynamical interactions in simulating cloud phase, which have been neglected in previous fixed‐dynamical parcel studies of the cloud phase parameter space. Large sensitivity to the IN/crystal concentration also suggests the need for improved understanding of ice nucleation and its parameterization in models