Uncovering distinct protein-network topologies in heterogeneous cell populations

Background: Cell biology research is fundamentally limited by the number of intracellular components, particularly proteins, that can be co-measured in the same cell. Therefore, cell-to-cell heterogeneity in unmeasured proteins can lead to completely different observed relations between the same measured proteins. Attempts to infer such relations in a heterogeneous cell population can yield uninformative average relations if only one underlying biochemical network is assumed. To address this, we developed a method that recursively couples an iterative unmixing process with a Bayesian analysis of each unmixed subpopulation. Results: Our approach enables to identify the number of distinct cell subpopulations, unmix their corresponding observations and resolve the network structure of each subpopulation. Using simulations of the MAPK pathway upon EGF and NGF stimulations we assess the performance of the method. We demonstrate that the presented method can identify better than clustering approaches the number of subpopulations within a mixture of observations, thus resolving correctly the statistical relations between the proteins. Conclusions: Coupling the unmixing of multiplexed observations with the inference of statistical relations between the measured parameters is essential for the success of both of these processes. Here we present a conceptual and algorithmic solution to achieve such coupling and hence to analyze data obtained from a natural mixture of cell populations. As the technologies and necessity for multiplexed measurements are rising in the systems biology era, this work addresses an important current challenge in the analysis of the derived data.Fil: Wieczorek, Jakob. Universitat Dortmund; AlemaniaFil: Malik Sheriff, Rahuman S.. Institut Max Planck fur Molekulare Physiologie; Alemania. Imperial College London; Reino Unido. European Bioinformatics Institute. European Molecular Biology Laboratory; Reino UnidoFil: Fermin, Yessica. Universitat Dortmund; AlemaniaFil: Grecco, Hernan Edgardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Institut Max Planck fur Molekulare Physiologie; AlemaniaFil: Zamir, Eli. Institut Max Planck fur Molekulare Physiologie; AlemaniaFil: Ickstadt, Katja. Universitat Dortmund; Alemani

Optomechanical cooling with coherent and squeezed light: the thermodynamic cost of opening the heat valve

Ground-state cooling of mechanical motion by coupling to a driven optical cavity has been demonstrated in various optomechanical systems. In our work, we provide a so far missing thermodynamic performance analysis of optomechanical sideband cooling in terms of a heat valve. As performance quantifiers, we examine not only the lowest reachable effective temperature (phonon number) but also the evacuated-heat flow as an equivalent to the cooling power of a standard refrigerator, as well as appropriate thermodynamic efficiencies, which all can be experimentally inferred from measurements of the cavity output light field. Importantly, in addition to the standard optomechanical setup fed by coherent light, we investigate two recent alternative setups for achieving ground-state cooling: replacing the coherent laser drive by squeezed light or using a cavity with a frequency-dependent (Fano) mirror. We study the dynamics of these setups within and beyond the weak-coupling limit and give concrete examples based on parameters of existing experimental systems. By applying our thermodynamic framework, we gain detailed insights into these three different optomechanical cooling setups, allowing a comprehensive understanding of the thermodynamic mechanisms at play.Comment: 28 pages, 14 figures, 2 tables Small revision of the main text, corrected typos in the appendices, added study of the stability of the systems and comparison with absorption refrigerators in appendi

Locating Pleistocene Refugia: Comparing Phylogeographic and Ecological Niche Model Predictions

Ecological niche models (ENMs) provide a means of characterizing the spatial distribution of suitable conditions for species, and have recently been applied to the challenge of locating potential distributional areas at the Last Glacial Maximum (LGM) when unfavorable climate conditions led to range contractions and fragmentation. Here, we compare and contrast ENM-based reconstructions of LGM refugial locations with those resulting from the more traditional molecular genetic and phylogeographic predictions. We examined 20 North American terrestrial vertebrate species from different regions and with different range sizes for which refugia have been identified based on phylogeographic analyses, using ENM tools to make parallel predictions. We then assessed the correspondence between the two approaches based on spatial overlap and areal extent of the predicted refugia. In 14 of the 20 species, the predictions from ENM and predictions based on phylogeographic studies were significantly spatially correlated, suggesting that the two approaches to development of refugial maps are converging on a similar result. Our results confirm that ENM scenario exploration can provide a useful complement to molecular studies, offering a less subjective, spatially explicit hypothesis of past geographic patterns of distribution

New insights in the relation between climate and slope failures at high-elevation sites

Climate change is now unequivocal; however, the type and extent of terrestrial impacts are still widely debated. Among these, the effects on slope stability are receiving a growing attention in recent years, both as terrestrial indicators of climate change and implications for hazard assessment. High-elevation areas are particularly suitable for these studies, because of the presence of the cryosphere, which is particularly sensitive to climate. In this paper, we analyze 358 slope failures which occurred in the Italian Alps in the period 2000–2016, at an elevation above 1500 m a.s.l. We use a statistical-based method to detect climate anomalies associated with the occurrence of slope failures, with the aim to catch an eventual climate signal in the preparation and/or triggering of the considered case studies. We first analyze the probability values assumed by 25 climate variables on the occasion of a slope-failure occurrence. We then perform a dimensionality reduction procedure and come out with a set of four most significant and representative climate variables, in particular heavy precipitation and short-term high temperature. Our study highlights that slope failures occur in association with one or more climate anomalies in almost 92% of our case studies. One or more temperature anomalies are detected in association with most case studies, in combination or not with precipitation (47% and 38%, respectively). Summer events prevail, and an increasing role of positive temperature anomalies from spring to winter, and with elevation and failure size, emerges. While not providing a final evidence of the role of climate warming on slope instability increase at high elevation in recent years, the results of our study strengthen this hypothesis, calling for more extensive and in-depth studies on the subject

Nurses' perceptions of aids and obstacles to the provision of optimal end of life care in ICU

Contains fulltext : 172380.pdf (publisher's version ) (Open Access

Highly Multiplexed Imaging Uncovers Changes in Compositional Noise within Assembling Focal Adhesions.

Integrin adhesome proteins bind each other in alternative manners, forming within the cell diverse cell-matrix adhesion sites with distinct properties. An intriguing question is how such modular assembly of adhesion sites is achieved correctly solely by self-organization of their components. Here we address this question using high-throughput multiplexed imaging of eight proteins and two phosphorylation sites in a large number of single focal adhesions. We found that during the assembly of focal adhesions the variances of protein densities decrease while the correlations between them increase, suggesting reduction in the noise levels within these structures. These changes correlate independently with the area and internal density of focal adhesions, but not with their age or shape. Artificial neural network analysis indicates that a joint consideration of multiple components improves the predictability of paxillin and zyxin levels in internally dense focal adhesions. This suggests that paxillin and zyxin densities in focal adhesions are fine-tuned by integrating the levels of multiple other components, thus averaging-out stochastic fluctuations. Based on these results we propose that increase in internal protein densities facilitates noise suppression in focal adhesions, while noise suppression enables their stable growth and further density increase-hence forming a feedback loop giving rise to a quality-controlled assembly