Phase Synchronization in Railway Timetables

Timetable construction belongs to the most important optimization problems in public transport. Finding optimal or near-optimal timetables under the subsidiary conditions of minimizing travel times and other criteria is a targeted contribution to the functioning of public transport. In addition to efficiency (given, e.g., by minimal average travel times), a significant feature of a timetable is its robustness against delay propagation. Here we study the balance of efficiency and robustness in long-distance railway timetables (in particular the current long-distance railway timetable in Germany) from the perspective of synchronization, exploiting the fact that a major part of the trains run nearly periodically. We find that synchronization is highest at intermediate-sized stations. We argue that this synchronization perspective opens a new avenue towards an understanding of railway timetables by representing them as spatio-temporal phase patterns. Robustness and efficiency can then be viewed as properties of this phase pattern

Teaching for the transition: The Canadian PGY-1 neurosurgery \u27rookie camp\u27

Background: Transitioning from medical school to residency is difficult and stressful, necessitating innovation in easing this transition. In response, a Canadian neurosurgical Rookie Camp was designed and implemented to foster acquisition of technical, cognitive and behavioral skills among incoming Canadian post graduate year one (PGY-1) neurosurgery residents. Methods: The inaugural Rookie Camp was held in July 2012 in Halifax. The curriculum was developed based on a national needs-assessment and consisted of a pre-course manual, 7 case-based stations, 4 procedural skills stations and 2 group discussions. The content was clinically focused, used a variety of teaching methods, and addressed multiple CanMEDS competencies. Evaluation included participant and faculty surveys and a pre-course, post-course, and 3-month retention knowledge test. Results: 17 of 23 PGY-1 Canadian neurosurgical residents participated in the Camp. All agreed the course content was relevant for PGY-1 training and the experience prepared them for residency. All participants would recommend the course to future neurosurgical residents. A statistically significant improvement was observed in knowledge related to course content (F(2,32) = 7.572, p\u3c0.002). There were no significant differences between post-test and retention-test scores at three months. Conclusion: The inaugural Canadian Neurosurgery Rookie Camp for PGY-1 residents was successfully delivered, with engagement from participants, training programs, the Canadian Neurosurgical Society, and the Royal College. In addition to providing fundamental knowledge, which was shown to be retained, the course eased junior residents\u27 transition to residency by fostering camaraderie and socialization within the specialty

Unraveling the Design Principle for Motif Organization in Signaling Networks

Cellular signaling networks display complex architecture. Defining the design principle of this architecture is crucial for our understanding of various biological processes. Using a mathematical model for three-node feed-forward loops, we identify that the organization of motifs in specific manner within the network serves as an important regulator of signal processing. Further, incorporating a systemic stochastic perturbation to the model we could propose a possible design principle, for higher-order organization of motifs into larger networks in order to achieve specific biological output. The design principle was then verified in a large, complex human cancer signaling network. Further analysis permitted us to classify signaling nodes of the network into robust and vulnerable nodes as a result of higher order motif organization. We show that distribution of these nodes within the network at strategic locations then provides for the range of features displayed by the signaling network

Chemotaxis: a feedback-based computational model robustly predicts multiple aspects of real cell behaviour

The mechanism of eukaryotic chemotaxis remains unclear despite intensive study. The most frequently described mechanism acts through attractants causing actin polymerization, in turn leading to pseudopod formation and cell movement. We recently proposed an alternative mechanism, supported by several lines of data, in which pseudopods are made by a self-generated cycle. If chemoattractants are present, they modulate the cycle rather than directly causing actin polymerization. The aim of this work is to test the explanatory and predictive powers of such pseudopod-based models to predict the complex behaviour of cells in chemotaxis. We have now tested the effectiveness of this mechanism using a computational model of cell movement and chemotaxis based on pseudopod autocatalysis. The model reproduces a surprisingly wide range of existing data about cell movement and chemotaxis. It simulates cell polarization and persistence without stimuli and selection of accurate pseudopods when chemoattractant gradients are present. It predicts both bias of pseudopod position in low chemoattractant gradients and-unexpectedly-lateral pseudopod initiation in high gradients. To test the predictive ability of the model, we looked for untested and novel predictions. One prediction from the model is that the angle between successive pseudopods at the front of the cell will increase in proportion to the difference between the cell's direction and the direction of the gradient. We measured the angles between pseudopods in chemotaxing Dictyostelium cells under different conditions and found the results agreed with the model extremely well. Our model and data together suggest that in rapidly moving cells like Dictyostelium and neutrophils an intrinsic pseudopod cycle lies at the heart of cell motility. This implies that the mechanism behind chemotaxis relies on modification of intrinsic pseudopod behaviour, more than generation of new pseudopods or actin polymerization by chemoattractant

Dose-Response Aligned Circuits in Signaling Systems

Cells use biological signal transduction pathways to respond to environmental stimuli and the behavior of many cell types depends on precise sensing and transmission of external information. A notable property of signal transduction that was characterized in the Saccharomyces cerevisiae yeast cell and many mammalian cells is the alignment of dose-response curves. It was found that the dose response of the receptor matches closely the dose responses of the downstream. This dose-response alignment (DoRA) renders equal sensitivities and concordant responses in different parts of signaling system and guarantees a faithful information transmission. The experimental observations raise interesting questions about the nature of the information transmission through DoRA signaling networks and design principles of signaling systems with this function. Here, we performed an exhaustive computational analysis on network architectures that underlie the DoRA function in simple regulatory networks composed of two and three enzymes. The minimal circuits capable of DoRA were examined with Michaelis-Menten kinetics. Several motifs that are essential for the dynamical function of DoRA were identified. Systematic analysis of the topology space of robust DoRA circuits revealed that, rather than fine-tuning the network's parameters, the function is primarily realized by enzymatic regulations on the controlled node that are constrained in limiting regions of saturation or linearity

Robust Signal Processing in Living Cells

Cellular signaling networks have evolved an astonishing ability to function reliably and with high fidelity in uncertain environments. A crucial prerequisite for the high precision exhibited by many signaling circuits is their ability to keep the concentrations of active signaling compounds within tightly defined bounds, despite strong stochastic fluctuations in copy numbers and other detrimental influences. Based on a simple mathematical formalism, we identify topological organizing principles that facilitate such robust control of intracellular concentrations in the face of multifarious perturbations. Our framework allows us to judge whether a multiple-input-multiple-output reaction network is robust against large perturbations of network parameters and enables the predictive design of perfectly robust synthetic network architectures. Utilizing the Escherichia coli chemotaxis pathway as a hallmark example, we provide experimental evidence that our framework indeed allows us to unravel the topological organization of robust signaling. We demonstrate that the specific organization of the pathway allows the system to maintain global concentration robustness of the diffusible response regulator CheY with respect to several dominant perturbations. Our framework provides a counterpoint to the hypothesis that cellular function relies on an extensive machinery to fine-tune or control intracellular parameters. Rather, we suggest that for a large class of perturbations, there exists an appropriate topology that renders the network output invariant to the respective perturbations

Vms1 and ANKZF1 peptidyl-tRNA hydrolases release nascent chains from stalled ribosomes

Ribosomal surveillance pathways scan for ribosomes that are transiently paused or terminally stalled owing to structural elements in mRNAs or nascent chain sequences. Some stalls in budding yeast are sensed by the GTPase Hbs1, which loads Dom34, a catalytically inactive member of the archaeo-eukaryotic release factor 1 superfamily. Hbs1–Dom34 and the ATPase Rli1 dissociate stalled ribosomes into 40S and 60S subunits. However, the 60S subunits retain the peptidyl-tRNA nascent chains, which recruit the ribosome quality control complex that consists of Rqc1–Rqc2–Ltn1–Cdc48–Ufd1–Npl4. Nascent chains ubiquitylated by the E3 ubiquitin ligase Ltn1 are extracted from the 60S subunit by the ATPase Cdc48–Ufd1–Npl4 and presented to the 26S proteasome for degradation. Failure to degrade the nascent chains leads to protein aggregation and proteotoxic stress in yeast and neurodegeneration in mice. Despite intensive investigations on the ribosome quality control pathway, it is not known how the tRNA is hydrolysed from the ubiquitylated nascent chain before its degradation. Here we show that the Cdc48 adaptor Vms1 is a peptidyl-tRNA hydrolase. Similar to classical eukaryotic release factor 1, Vms1 activity is dependent on a conserved catalytic glutamine. Evolutionary analysis indicates that yeast Vms1 is the founding member of a clade of eukaryotic release factor 1 homologues that we designate the Vms1-like release factor 1 clade

Fluid flow and interlinked feedback loops establish left-right asymmetric decay of Cerl2 mRNA

Breaking of left-right symmetry in mouse embryos requires fluid flow at the node, but the precise action of the flow has remained unknown. Here we show that the left-right asymmetry of Cerl2 expression around the node, a target of the flow, is determined post-transcriptionally by decay of Cerl2 mRNA in a manner dependent on its 3' untranslated region. Cerl2 mRNA is absent specifically from the apical region of crown cells on the left side of the node. Preferential decay of Cerl2 mRNA on the left is initiated by the leftward flow and further enhanced by the operation of Wnt-Cerl2 interlinked feedback loops, in which Wnt3 upregulates Wnt3 expression and promotes Cerl2 mRNA decay, whereas Cerl2 promotes Wnt degradation. Mathematical modelling and experimental data suggest that these feedback loops behave as a bistable switch that can amplify in a noise-resistant manner a small bias conferred by fluid flow.Ministry of Education, Culture, Sports, Science, and Technology of Japan; Core Research for Evolutional Science and Technology (CREST) of the Japan Science and Technology Corporation (JST); GCOE of Osaka University; FCTinfo:eu-repo/semantics/publishedVersio

Modeling Robustness Tradeoffs in Yeast Cell Polarization Induced by Spatial Gradients

Cells localize (polarize) internal components to specific locations in response to external signals such as spatial gradients. For example, yeast cells form a mating projection toward the source of mating pheromone. There are specific challenges associated with cell polarization including amplification of shallow external gradients of ligand to produce steep internal gradients of protein components (e.g. localized distribution), response over a broad range of ligand concentrations, and tracking of moving signal sources. In this work, we investigated the tradeoffs among these performance objectives using a generic model that captures the basic spatial dynamics of polarization in yeast cells, which are small. We varied the positive feedback, cooperativity, and diffusion coefficients in the model to explore the nature of this tradeoff. Increasing the positive feedback gain resulted in better amplification, but also produced multiple steady-states and hysteresis that prevented the tracking of directional changes of the gradient. Feedforward/feedback coincidence detection in the positive feedback loop and multi-stage amplification both improved tracking with only a modest loss of amplification. Surprisingly, we found that introducing lateral surface diffusion increased the robustness of polarization and collapsed the multiple steady-states to a single steady-state at the cost of a reduction in polarization. Finally, in a more mechanistic model of yeast cell polarization, a surface diffusion coefficient between 0.01 and 0.001 µm2/s produced the best polarization performance, and this range is close to the measured value. The model also showed good gradient-sensitivity and dynamic range. This research is significant because it provides an in-depth analysis of the performance tradeoffs that confront biological systems that sense and respond to chemical spatial gradients, proposes strategies for balancing this tradeoff, highlights the critical role of lateral diffusion of proteins in the membrane on the robustness of polarization, and furnishes a framework for future spatial models of yeast cell polarization

A Comparison of Mathematical Models for Polarization of Single Eukaryotic Cells in Response to Guided Cues

Polarization, a primary step in the response of an individual eukaryotic cell to a spatial stimulus, has attracted numerous theoretical treatments complementing experimental studies in a variety of cell types. While the phenomenon itself is universal, details differ across cell types, and across classes of models that have been proposed. Most models address how symmetry breaking leads to polarization, some in abstract settings, others based on specific biochemistry. Here, we compare polarization in response to a stimulus (e.g., a chemoattractant) in cells typically used in experiments (yeast, amoebae, leukocytes, keratocytes, fibroblasts, and neurons), and, in parallel, responses of several prototypical models to typical stimulation protocols. We find that the diversity of cell behaviors is reflected by a diversity of models, and that some, but not all models, can account for amplification of stimulus, maintenance of polarity, adaptation, sensitivity to new signals, and robustness