Sildenafil attenuates pulmonary arterial pressure but does not improve oxygenation during ARDS

OBJECTIVE: Pulmonary hypertension is a characteristic feature of acute respiratory distress syndrome (ARDS) and contributes to mortality. Administration of sildenafil in ambulatory patients with pulmonary hypertension improves oxygenation and ameliorates pulmonary hypertension. Our aim was to determine whether sildenafil is beneficial for patients with ARDS. DESIGN: Prospective, open-label, multicenter, interventional cohort study. SETTING: Medical-surgical ICU of two university hospitals. PATIENTS: Ten consecutive patients meeting the NAECC criteria for ARDS. INTERVENTIONS: A single dose of 50 mg sildenafil citrate administered via a nasogastric tube. MAIN RESULTS: Administration of sildenafil in patients with ARDS decreased mean pulmonary arterial pressure from 25 to 22 mmHg (P = 0.022) and pulmonary artery occlusion pressure from 16 to 13 mmHg (P = 0.049). Systemic mean arterial pressures were markedly decreased from 81 to 75 mmHg (P = 0.005). Sildenafil did not improve pulmonary arterial oxygen tension, but resulted in a further increase in the shunt fraction. CONCLUSION: Although sildenafil reduced pulmonary arterial pressures during ARDS, the increased shunt fraction and decreased arterial oxygenation render it unsuitable for the treatment of patients with ARD

Integration of Global Signaling Pathways, cAMP-PKA, MAPK and TOR in the Regulation of FLO11

The budding yeast, Saccharomyces cerevisiae, responds to various environmental cues by invoking specific adaptive mechanisms for their survival. Under nitrogen limitation, S. cerevisiae undergoes a dimorphic filamentous transition called pseudohyphae, which helps the cell to forage for nutrients and reach an environment conducive for growth. This transition is governed by a complex network of signaling pathways, namely cAMP-PKA, MAPK and TOR, which controls the transcriptional activation of FLO11, a flocculin gene that encodes a cell wall protein. However, little is known about how these pathways co-ordinate to govern the conversion of nutritional availability into gene expression. Here, we have analyzed an integrative network comprised of cAMP-PKA, MAPK and TOR pathways with respect to the availability of nitrogen source using experimental and steady state modeling approach. Our experiments demonstrate that the steady state expression of FLO11 was bistable over a range of inducing ammonium sulphate concentration based on the preculturing condition. We also show that yeast switched from FLO11 expression to accumulation of trehalose, a STRE response controlled by a transcriptional activator Msn2/4, with decrease in the inducing concentration to complete starvation. Steady state analysis of the integrative network revealed the relationship between the environment, signaling cascades and the expression of FLO11. We demonstrate that the double negative feedback loop in TOR pathway can elicit a bistable response, to differentiate between vegetative growth, filamentous growth and STRE response. Negative feedback on TOR pathway function to restrict the expression of FLO11 under nitrogen starved condition and also with re-addition of nitrogen to starved cells. In general, we show that these global signaling pathways respond with specific sensitivity to regulate the expression of FLO11 under nitrogen limitation. The holistic steady state modeling approach of the integrative network revealed how the global signaling pathways could differentiate between multiple phenotypes

A Topological Criterion for Filtering Information in Complex Brain Networks.

In many biological systems, the network of interactions between the elements can only be inferred from experimental measurements. In neuroscience, non-invasive imaging tools are extensively used to derive either structural or functional brain networks in-vivo. As a result of the inference process, we obtain a matrix of values corresponding to a fully connected and weighted network. To turn this into a useful sparse network, thresholding is typically adopted to cancel a percentage of the weakest connections. The structural properties of the resulting network depend on how much of the inferred connectivity is eventually retained. However, how to objectively fix this threshold is still an open issue. We introduce a criterion, the efficiency cost optimization (ECO), to select a threshold based on the optimization of the trade-off between the efficiency of a network and its wiring cost. We prove analytically and we confirm through numerical simulations that the connection density maximizing this trade-off emphasizes the intrinsic properties of a given network, while preserving its sparsity. Moreover, this density threshold can be determined a-priori, since the number of connections to filter only depends on the network size according to a power-law. We validate this result on several brain networks, from micro- to macro-scales, obtained with different imaging modalities. Finally, we test the potential of ECO in discriminating brain states with respect to alternative filtering methods. ECO advances our ability to analyze and compare biological networks, inferred from experimental data, in a fast and principled way.VL and MC acknowledge support by the European Commission Project LASAGNE Grant 318132; VL acknowledges support from EPSRC project GALE Grant EP/K020633/1; FDVF and MC acknowledge support by French program “Investissements d’avenir” ANR-10-IAIHU-06; FDVF acknowledges support by the “Agence Nationale de la Recherche” through contract number ANR-15-NEUC-0006-02. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Massive stars and their supernovae

Stars more massive than about 8-10 solar masses evolve differently from their lower-mass counterparts: nuclear energy liberation is possible at higher temperatures and densities, due to gravitational contraction caused by such high masses, until forming an iron core that ends this stellar evolution. The star collapses thereafter, as insufficient pressure support exists when energy release stops due to Fe/Ni possessing the highest nuclear binding per nucleon, and this implosion turns into either a supernova explosion or a compact black hole remnant object. Neutron stars are the likely compact-star remnants after supernova explosions for a certain stellar mass range. In this chapter, we discuss this late-phase evolution of massive stars and their core collapse, including the nuclear reactions and nucleosynthesis products. We also include in this discussion more exotic outcomes, such as magnetic jet supernovae, hypernovae, gamma-ray bursts and neutron star mergers. In all cases we emphasize the viewpoint with respect to the role of radioactivities