Sternstorgaard7714

Bistability is a common mechanism to ensure robust and irreversible cell cycle transitions. Whenever biological parameters or external conditions change such that a threshold is crossed, the system abruptly switches between different cell cycle states. Experimental studies have uncovered mechanisms that can make the shape of the bistable response curve change dynamically in time. Here, we show how such a dynamically changing bistable switch can provide a cell with better control over the timing of cell cycle transitions. Moreover, cell cycle oscillations built on bistable switches are more robust when the bistability is modulated in time. Our results are not specific to cell cycle models and may apply to other bistable systems in which the bistable response curve is time-dependent.Galectin-1 (gal-1) is a carbohydrate-binding lectin with important functions in angiogenesis, immune response, hemostasis and inflammation. Comparable functions are exerted by platelet factor 4 (CXCL4), a chemokine stored in the α-granules of platelets. Previously, gal-1 was found to activate platelets through integrin αIIbβ3. Both gal-1 and CXCL4 have high affinities for polysaccharides, and thus may mutually influence their functions. The aim of this study was to investigate a possible synergism of gal-1 and CXCL4 in platelet activation. Platelets were treated with increasing concentrations of gal-1, CXCL4 or both, and aggregation, integrin activation, P-selectin and phosphatidyl serine (PS) exposure were determined by light transmission aggregometry and by flow cytometry. To investigate the influence of cell surface sialic acid, platelets were treated with neuraminidase prior to stimulation. Gal-1 and CXCL4 were found to colocalize on the platelet surface. Stimulation with gal-1 led to integrin αIIbβ3 activation and to robust platelet aggregation, while CXCL4 weakly triggered aggregation and primarily induced P-selectin expression. Co-incubation of gal-1 and CXCL4 potentiated platelet aggregation compared with gal-1 alone. Whereas neither gal-1 and CXCL4 induced PS-exposure on platelets, prior removal of surface sialic acid strongly potentiated PS exposure. In addition, neuraminidase treatment increased the binding of gal-1 to platelets and lowered the activation threshold for gal-1. However, CXCL4 did not affect binding of gal-1 to platelets. Taken together, stimulation of platelets with gal-1 and CXCL4 led to distinct and complementary activation profiles, with additive rather than synergistic effects.Phenomenological relations such as Ohm's or Fourier's law have a venerable history in physics but are still scarce in biology. This situation restrains predictive theory. Here, we build on bacterial "growth laws," which capture physiological feedback between translation and cell growth, to construct a minimal biophysical model for the combined action of ribosome-targeting antibiotics. Our model predicts drug interactions like antagonism or synergy solely from responses to individual drugs. We provide analytical results for limiting cases, which agree well with numerical results. We systematically refine the model by including direct physical interactions of different antibiotics on the ribosome. In a limiting case, our model provides a mechanistic underpinning for recent predictions of higher-order interactions that were derived using entropy maximization. We further refine the model to include the effects of antibiotics that mimic starvation and the presence of resistance genes. We describe the impact of a starvation-mimicking antibiotic on drug interactions analytically and verify it experimentally. Our extended model suggests a change in the type of drug interaction that depends on the strength of resistance, which challenges established rescaling paradigms. We experimentally show that the presence of unregulated resistance genes can lead to altered drug interaction, which agrees with the prediction of the model. While minimal, the model is readily adaptable and opens the door to predicting interactions of second and higher-order in a broad range of biological systems.A new algorithmic approach to personality prototyping based on Big Five traits was applied to a large representative and longitudinal German dataset (N = 22,820) including behavior, personality and health correlates. GC376 3C-Like Protease inhibitor We applied three different clustering techniques, latent profile analysis, the k-means method and spectral clustering algorithms. The resulting cluster centers, i.e. the personality prototypes, were evaluated using a large number of internal and external validity criteria including health, locus of control, self-esteem, impulsivity, risk-taking and wellbeing. The best-fitting prototypical personality profiles were labeled according to their Euclidean distances to averaged personality type profiles identified in a review of previous studies on personality types. This procedure yielded a five-cluster solution resilient, overcontroller, undercontroller, reserved and vulnerable-resilient. Reliability and construct validity could be confirmed. We discuss wether personality types could comprise a bridge between personality and clinical psychology as well as between developmental psychology and resilience research.To tackle China's rapidly aging population, a policy was framed by using overlapping generations (OLG) model and computable general equilibrium (CGE) model; the main objective was to successfully implement "second-child policy" and "delayed retirement age" for female or male workers. The 2012 census data was obtained from National Bureau of Statistics of China. Our research findings suggest that the economy can be improved in the short-term by delaying retirement age; however, Chinese economy would improve tremendously in the long run by implementing second-child policy. Compared to delayed retirement age, second-child policy would be more effective in improving the economy in China. In terms of industrial output, the three policies have a greater influence on labor-intensive industries, such as agriculture, light industry, finance, and service sector; the impact is less significant on construction and heavy industry. In terms of industrial import and export, these three policies have greatly influenced following industries finance, electric power, and fossil energy.