Emergence of skew distributions in controlled growth processes

Starting from a master equation, we derive the evolution equation for the size distribution of elements in an evolving system, where each element can grow, divide into two, and produce new elements. We then probe general solutions of the evolution quation, to obtain such skew distributions as power-law, log-normal, and Weibull distributions, depending on the growth or division and production. Specifically, repeated production of elements of uniform size leads to power-law distributions, whereas production of elements with the size distributed according to the current distribution as well as no production of new elements results in log-normal distributions. Finally, division into two, or binary fission, bears Weibull distributions. Numerical simulations are also carried out, confirming the validity of the obtained solutions.Comment: 9 pages, 3 figure

Functional analysis of the fructooligosaccharide utilization operon in \u3ci\u3eLactobacillus paracasei\u3c/i\u3e 1195

The fosABCDXE operon encodes components of a putative fructose/mannose phosphoenolpyruvate-dependent phosphotransferase system (PTS) and a β- fructosidase precursor (FosE) that are involved in the fructooligosaccharide (FOS) utilization pathway of Lactobacillus paracasei 1195. The presence of an N-terminal signal peptide sequence and a LPQAG cell wall anchor motif at the C-terminal region of the deduced FosE precursor amino acid sequence predicted that the enzyme is cell wall-associated, indicating that FOS may be hydrolyzed extracellularly. In this study, cell fractionation experiments demonstrated that the FOS hydrolysis activity was contained exclusively in the cell wall extract of L. paracasei previously grown on FOS. In contrast, no measurable FOS hydrolysis activity was detected in the cell wall extract from the isogenic fosE mutant. Induction of β-fructosidase activity was observed when cells were grown on FOS, inulin, sucrose, or fructose, but not glucose. A diauxic growth pattern was observed when cells were grown on FOS in the presence of limiting glucose (0.1%). Analysis of the culture supernatant revealed that glucose was consumed first, followed by the longer chain FOS species. Transcription analysis further showed that the fos operon was expressed only after glucose was depleted in the medium. Expression of fosE in a non-FOS-fermenting strain, Lactobacillus rhamnosus GG, enabled the recombinant strain to metabolize FOS, inulin, sucrose, and levan

IL11 stimulates IL33 expression and proinflammatory fibroblast activation across tissues

Interleukin 11 (IL11) is upregulated in inflammatory conditions, where it is mostly believed to have anti-inflammatory activity. However, recent studies suggest instead that IL11 promotes inflammation by activating fibroblasts. Here, we assessed whether IL11 is pro- or anti-inflammatory in fibroblasts. Primary cultures of human kidney, lung or skin fibroblasts were stimulated with IL11 that resulted in the transient phosphorylation of signal transducer and activator of transcription 3 (STAT3) and the sustained activation of extracellular signal-regulated protein kinases (ERK). RNA sequencing over a time course of IL11 stimulation revealed a robust but short-lived transcriptional response that was enriched for gene set hallmarks of inflammation and characterized by the upregulation of SERPINB2, TNFRSF18, Interleukin 33 (IL33), CCL20, IL1RL1, CXCL3/5/8, ICAM1 and IL11 itself. IL33 was the most upregulated signaling factor (38-fold, p = 9.8 × 10-5), and IL1RL1, its cognate receptor, was similarly increased (18-fold, p = 1.1 × 10-34). In proteomic studies, IL11 triggered a proinflammatory secretome with the notable upregulation of IL8, IL6, MCP1, CCL20 and CXCL1/5/6, which are important chemotaxins for neutrophils, monocytes, and lymphocytes. IL11 induced IL33 expression across fibroblast types, and the inhibition of STAT3 but not of MEK/ERK prevented this. These data establish IL11 as pro-inflammatory with specific importance for priming the IL33 alarmin response in inflammatory fibroblasts across tissues

Optimal Control of SOAs with Artificial Intelligence for Sub-Nanosecond Optical Switching

Novel approaches to switching ultra-fast semiconductor optical amplifiers using artificial intelligence algorithms (particle swarm optimisation, ant colony optimisation, and a genetic algorithm) are developed and applied both in simulation and experiment. Effective off-on switching (settling) times of 542 ps are demonstrated with just 4.8% overshoot, achieving an order of magnitude improvement over previous attempts described in the literature and standard dampening techniques from control theory.Comment: This manuscript was accepted for publication in the IEEE/OSA Journal of Lightwave Technology on 21st June 2020. Open access code: https://github.com/cwfparsonson/soa_driving Open access data: https://doi.org/10.5522/04/12356696.v

Correlated multiplexity and connectivity of multiplex random networks

Nodes in a complex networked system often engage in more than one type of interactions among them; they form a multiplex network with multiple types of links. In real-world complex systems, a node's degree for one type of links and that for the other are not randomly distributed but correlated, which we term correlated multiplexity. In this paper we study a simple model of multiplex random networks and demonstrate that the correlated multiplexity can drastically affect the properties of giant component in the network. Specifically, when the degrees of a node for different interactions in a duplex Erdos-Renyi network are maximally correlated, the network contains the giant component for any nonzero link densities. In contrast, when the degrees of a node are maximally anti-correlated, the emergence of giant component is significantly delayed, yet the entire network becomes connected into a single component at a finite link density. We also discuss the mixing patterns and the cases with imperfect correlated multiplexity.Comment: Revised version, 12 pages, 6 figure