Quantum jumps and spin dynamics of interacting atoms in a strongly coupled atom-cavity system

We experimentally investigate the spin dynamics of one and two neutral atoms strongly coupled to a high finesse optical cavity. We observe quantum jumps between hyperfine ground states of a single atom. The interaction-induced normal mode splitting of the atom-cavity system is measured via the atomic excitation. Moreover, we observe evidence for conditional dynamics of two atoms simultaneously coupled to the cavity mode. Our results point towards the realization of measurement-induced entanglement schemes for neutral atoms in optical cavities.Comment: 4 pages, 4 figures, published versio

Hyperammonemic Coma—Barking Up the Wrong Tree

Hepatic encephalopathy and myxedema coma share clinical features: coma, ascites, anemia, impaired liver functions, and a “metabolic” electroencephalogram (EEG). Hyperammonemia, a hallmark of hepatic encephalopathy, has also been described in hypothyroidism. Differentiation between the 2 conditions, recognition of their possible coexistence, and the consequent therapeutic implications are of utmost importance. We describe a case of an 82-year-old woman with a history of mild chronic liver disease who presented with hyperammonemic coma unresponsive to conventional therapy. Further investigation disclosed severe hypothyroidism. Thyroid hormone replacement resulted in gain of consciousness and normalization of hyperammonemia. In patients with an elevated ammonia level, altered mental status, and liver disease, who do not have a clear inciting event for liver disease decompensation, overwhelming evidence of hepatic decompensation, or who do not respond to appropriate therapy for hepatic encephalopathy, hypothyroidism should be considered and evaluated

Inferring causal molecular networks: empirical assessment through a community-based effort

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks

Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

Complement component C5a mediates hemorrhage-induced intestinal damage

Background: Complement has been implicated in the pathogenesis of intestinal damage and inflammation in multiple animal models. Although the exact mechanism is unknown, inhibition of complement prevents hemodynamic alterations in hemorrhage. Materials/Methods: C57Bl/6, complement 5 deficient (C5-/-) and sufficient (C5+/+) mice were subjected to 25% blood loss. In some cases, C57Bl/6 mice were treated with C5a receptor antagonist (C5aRa) post-hemorrhage. Intestinal injury, leukotriene B4, and myeloperoxidase production were assessed for each treatment group of mice. Results: Mice subjected to significant blood loss without major trauma develop intestinal inflammation and tissue damage within two hours. We report here that complement 5 (C5) deficient mice are protected from intestinal tissue damage when subjected to hemorrhage (Injury score = 0.36 compared to wildtype hemorrhaged animal injury score = 2.89; p<0.05). We present evidence that C5a represents the effector molecule because C57Bl/6 mice treated with a C5a receptor antagonist displayed limited intestinal injury (Injury score = 0.88), leukotriene B4 (13.16 pg/mg tissue) and myeloperoxidase (115.6 pg/mg tissue) production compared to hemorrhaged C57Bl/6 mice (p<0.05). Conclusion: Complement activation is important in the development of hemorrhage-induced tissue injury and C5a generation is critical for tissue inflammation and damage. Thus, therapeutics targeting C5a may be useful therapeutics for hemorrhage-associated injury