Stomata, microscopic pores in leaf surfaces through which water loss and carbon dioxide uptake occur, are closed in response to drought by the phytohormone abscisic acid (ABA). This process is vital for drought tolerance and has been the topic of extensive experimental investigation in the last decades. Although a core signaling chain has been elucidated consisting of ABA binding to receptors, which alleviates negative regulation by protein phosphatases 2C (PP2Cs) of the protein kinase OPEN STOMATA 1 (OST1) and ultimately results in activation of anion channels, osmotic water loss, and stomatal closure, over 70 additional components have been identified, yet their relationships with each other and the core components are poorly elucidated. We integrated and processed hundreds of disparate observations regarding ABA signal transduction responses underlying stomatal closure into a network of 84 nodes and 156 edges and, as a result, established those relationships, including identification of a 36-node, strongly connected (feedback-rich) component as well as its in- and out-components. The network’s domination by a feedback-rich component may reflect a general feature of rapid signaling events. We developed a discrete dynamic model of this network and elucidated the effects of ABA plus knockout or constitutive activity of 79 nodes on both the outcome of the system (closure) and the status of all internal nodes. The model, with more than 1024 system states, is far from fully determined by the available data, yet model results agree with existing experiments in 82 cases and disagree in only 17 cases, a validation rate of 75%. Our results reveal nodes that could be engineered to impact stomatal closure in a controlled fashion and also provide over 140 novel predictions for which experimental data are currently lacking. Noting the paucity of wet-bench data regarding combinatorial effects of ABA and internal node activation, we experimentally confirmed several predictions of the model with regard to reactive oxygen species, cytosolic Ca2+ (Ca2+c), and heterotrimeric G-protein signaling. We analyzed dynamics-determining positive and negative feedback loops, thereby elucidating the attractor (dynamic behavior) repertoire of the system and the groups of nodes that determine each attractor. Based on this analysis, we predict the likely presence of a previously unrecognized feedback mechanism dependent on Ca2+c. This mechanism would provide model agreement with 10 additional experimental observations, for a validation rate of 85%. Our research underscores the importance of feedback regulation in generating robust and adaptable biological responses. The high validation rate of our model illustrates the advantages of discrete dynamic modeling for complex, nonlinear systems common in biology.

Nitinol self-expanding stents undergo both axial and bending deformation when implanted into the superficial femoral and popliteal arteries. Commercially available stents exhibit a variable ability to withstand chronic deformation in vitro, and their response is highly dependent on the type of deformation applied.

Goals: We aimed to describe the diagnostic and prognostic performance of transient elastography (TE) and magnetic resonance elastography (MRE) in patients with primary biliary cholangitis (PBC). Background: The diagnostic performance of TE and MRE in detecting advanced fibrosis in PBC and in predicting outcomes independent of existing serologic prognostic markers is incompletely understood. Materials and Methods: Five hundred thirty-eight consecutive patients with PBC at 3 centers with liver stiffness (LS) measurements by TE (n=286) or MRE (n=332) were reviewed. LS cutoffs for predicting fibrosis stages were determined by receiver operating characteristic curves among those with a liver biopsy (TE, n=63; MRE, n=98). Cox proportional hazard regression modeling was used to identify associations between covariates and hepatic decompensation. Results: The optimal LS thresholds for predicting histologic stage F4 were 14.40 kPa (area under the curve=0.94) for TE and 4.60 kPa (area under the curve=0.82) for MRE. Both TE and MRE outperformed biochemical markers for the prediction of histologic advanced fibrosis. Optimal LS thresholds to predict hepatic decompensation were 10.20 kPa on TE and 4.30 kPa on MRE. LS by TE and MRE (respectively) remained predictors of hepatic decompensation after adjusting for ursodeoxycholic acid responsiveness [hazard ratio (HR), 1.14; 95% confidence interval (CI), 1.05-1.24 and HR, 1.68; 95% CI, 1.28-2.19] and the GLOBE score (HR, 1.13; 95% CI, 1.07-1.19 and HR, 2.09; 95% CI, 1.57-2.78). Conclusion: LS measurement with either TE or MRE can accurately detect advanced fibrosis and offers additional prognostic value beyond existing serologic predictive tools.

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