SLEEP APNEA AND THE SUDDEN INFANT DEATH SYNDROME (SIDS)

Peer Reviewe

Mathematical modeling reveals threshold mechanism in CD95-induced apoptosis

Mathematical modeling is required for understanding the complex behavior of large signal transduction networks. Previous attempts to model signal transduction pathways were often limited to small systems or based on qualitative data only. Here, we developed a mathematical modeling framework for understanding the complex signaling behavior of CD95(APO-1/Fas)-mediated apoptosis. Defects in the regulation of apoptosis result in serious diseases such as cancer, autoimmunity, and neurodegeneration. During the last decade many of the molecular mechanisms of apoptosis signaling have been examined and elucidated. A systemic understanding of apoptosis is, however, still missing. To address the complexity of apoptotic signaling we subdivided this system into subsystems of different information qualities. A new approach for sensitivity analysis within the mathematical model was key for the identification of critical system parameters and two essential system properties: modularity and robustness. Our model describes the regulation of apoptosis on a systems level and resolves the important question of a threshold mechanism for the regulation of apoptosis

Bistability in Apoptosis by Receptor Clustering

Apoptosis is a highly regulated cell death mechanism involved in many physiological processes. A key component of extrinsically activated apoptosis is the death receptor Fas, which, on binding to its cognate ligand FasL, oligomerize to form the death-inducing signaling complex. Motivated by recent experimental data, we propose a mathematical model of death ligand-receptor dynamics where FasL acts as a clustering agent for Fas, which form locally stable signaling platforms through proximity-induced receptor interactions. Significantly, the model exhibits hysteresis, providing an upstream mechanism for bistability and robustness. At low receptor concentrations, the bistability is contingent on the trimerism of FasL. Moreover, irreversible bistability, representing a committed cell death decision, emerges at high concentrations, which may be achieved through receptor pre-association or localization onto membrane lipid rafts. Thus, our model provides a novel theory for these observed biological phenomena within the unified context of bistability. Importantly, as Fas interactions initiate the extrinsic apoptotic pathway, our model also suggests a mechanism by which cells may function as bistable life/death switches independently of any such dynamics in their downstream components. Our results highlight the role of death receptors in deciding cell fate and add to the signal processing capabilities attributed to receptor clustering.Comment: Accepted by PLoS Comput Bio

An exploratory investigation of brain collateral circulation plasticity after cerebral ischemia in two experimental C57BL/6 mouse models

Brain collateral circulation is an essential compensatory mechanism in response to acute brain ischemia. To study the temporal evolution of brain macro and microcollateral recruitment and their reciprocal interactions in response to different ischemic conditions, we applied a combination of complementary techniques (T2-weighted magnetic resonance imaging [MRI], time of flight [TOF] angiography [MRA], cerebral blood flow [CBF] imaging and histology) in two different mouse models. Hypoperfusion was either induced by permanent bilateral common carotid artery stenosis (BCCAS) or 60-min transient unilateral middle cerebral artery occlusion (MCAO). In both models, collateralization is a very dynamic phenomenon with a global effect affecting both hemispheres. Patency of ipsilateral posterior communicating artery (PcomA) represents the main variable survival mechanism and the main determinant of stroke lesion volume and recovery in MCAO, whereas the promptness of external carotid artery retrograde flow recruitment together with PcomA patency, critically influence survival, brain ischemic lesion volume and retinopathy in BCCAS mice. Finally, different ischemic gradients shape microcollateral density and size

Amici Curiae Brief of New York law school professors in People v. Harris: Constitutionality of the New York Death Penalty Statute Under the State Constitution\u27s Cruel and Unusual Punishments and Antidiscrimination Clauses

Amici are teachers in New York law schools who have studied the operation of the death penalty for the purpose of teaching the subject, writing about it in scholarly journals, or representing persons accused or convicted of capital crimes. Most of us have worked in the field both as academics and as pro bono counsel for condemned inmates. Collectively, we have had first-hand experience in hundreds of death cases, in dozens of jurisdictions, extending over more than a third of a century. Our experience has convinced us that capital punishment cannot be administered with the fairness, reliability, and freedom from discrimination that a penalty so grave and irreversible requires. This is no accident or transitory condition; it is the consequence of certain innate attributes of the penalty of death. The purpose of our brief is to analyze those attributes and explain why they are fundamentally at war with the Cruel and Unusual Punishments Clause and the Antidiscrimination Clause of New York’s Bill of Rights. We hope to persuade the Court that it should not temporize with the death penalty in the face of this basic incompatibility but should hold the 1995 death penalty statute altogether unconstitutional

External Control of the GAL Network in S. cerevisiae: A View from Control Theory

While there is a vast literature on the control systems that cells utilize to regulate their own state, there is little published work on the formal application of control theory to the external regulation of cellular functions. This paper chooses the GAL network in S. cerevisiae as a well understood benchmark example to demonstrate how control theory can be employed to regulate intracellular mRNA levels via extracellular galactose. Based on a mathematical model reduced from the GAL network, we have demonstrated that a galactose dose necessary to drive and maintain the desired GAL genes' mRNA levels can be calculated in an analytic form. And thus, a proportional feedback control can be designed to precisely regulate the level of mRNA. The benefits of the proposed feedback control are extensively investigated in terms of stability and parameter sensitivity. This paper demonstrates that feedback control can both significantly accelerate the process to precisely regulate mRNA levels and enhance the robustness of the overall cellular control system

Industrial Structure and Political Outcomes: The Case of the 2016 US Presidential Election

This paper analyzes the US presidential election of 2016, examining the patterns of industrial structure and party competition in both the major party primaries and the general election. It attempts to identify the new, historically specific factors that led to the upheavals, especially the steady growth of a “dual economy” that locks more and more Americans out of the middle class. It draws extensively on a newly assembled, more comprehensive database to identify the specific political forces that coalesced around each candidate, including the various stages of the Trump campaign

Global Analysis of Dynamical Decision-Making Models through Local Computation around the Hidden Saddle

Bistable dynamical switches are frequently encountered in mathematical modeling of biological systems because binary decisions are at the core of many cellular processes. Bistable switches present two stable steady-states, each of them corresponding to a distinct decision. In response to a transient signal, the system can flip back and forth between these two stable steady-states, switching between both decisions. Understanding which parameters and states affect this switch between stable states may shed light on the mechanisms underlying the decision-making process. Yet, answering such a question involves analyzing the global dynamical (i.e., transient) behavior of a nonlinear, possibly high dimensional model. In this paper, we show how a local analysis at a particular equilibrium point of bistable systems is highly relevant to understand the global properties of the switching system. The local analysis is performed at the saddle point, an often disregarded equilibrium point of bistable models but which is shown to be a key ruler of the decision-making process. Results are illustrated on three previously published models of biological switches: two models of apoptosis, the programmed cell death and one model of long-term potentiation, a phenomenon underlying synaptic plasticity

Inferring robust gene networks from expression data by a sensitivity-based incremental evolution method

<p>Abstract</p> <p>Background</p> <p>Reconstructing gene regulatory networks (GRNs) from expression data is one of the most important challenges in systems biology research. Many computational models and methods have been proposed to automate the process of network reconstruction. Inferring robust networks with desired behaviours remains challenging, however. This problem is related to network dynamics but has yet to be investigated using network modeling.</p> <p>Results</p> <p>We propose an incremental evolution approach for inferring GRNs that takes network robustness into consideration and can deal with a large number of network parameters. Our approach includes a sensitivity analysis procedure to iteratively select the most influential network parameters, and it uses a swarm intelligence procedure to perform parameter optimization. We have conducted a series of experiments to evaluate the external behaviors and internal robustness of the networks inferred by the proposed approach. The results and analyses have verified the effectiveness of our approach.</p> <p>Conclusions</p> <p>Sensitivity analysis is crucial to identifying the most sensitive parameters that govern the network dynamics. It can further be used to derive constraints for network parameters in the network reconstruction process. The experimental results show that the proposed approach can successfully infer robust GRNs with desired system behaviors.</p