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Concepts used in the scientific study of complex systems have become so widespread that their use and abuse has led to ambiguity and confusion in their meaning. In this article, we use information theory to provide and concise measures of complexity, emergence, self‐organization, and homeostasis. The purpose is to clarify the meaning of these concepts with the aid of the proposed formal measures. In a simplified version of the measures (focusing on the information produced by a system), emergence becomes the opposite of self‐organization, while complexity represents their balance. Homeostasis can be seen as a measure of the stability of the system. We use computational experiments on random Boolean networks and elementary cellular automata to illustrate our measures at multiple scales. © 2012 Wiley Periodicals, Inc. Complexity, 2012

Classification is a ubiquitous and fundamental problem in artificial intelligence and machine learning, with extensive efforts dedicated to developing more powerful classifiers and larger datasets. However, the classification task is ultimately constrained by the intrinsic properties of datasets, independently of computational power or model complexity. In this work, we introduce a formal entropy-based measure of classifiability, which quantifies the inherent difficulty of a classification problem by assessing the uncertainty in class assignments given feature representations. This measure captures the degree of class overlap and aligns with human intuition, serving as an upper bound on classification performance for classification problems. Our results establish a theoretical limit beyond which no classifier can improve the classification accuracy, regardless of the architecture or amount of data, in a given problem. Our approach provides a principled framework for understanding when classification is inherently fallible and fundamentally ambiguous.

Sertoli cells, can function as non-professional tolerogenic antigen-presenting cells and sustain the blood-testis barrier formed by their tight junctions. The NOD-like receptor family members and the NALP3 inflammasome play a key role in pro-inflammatory innate immunity signalling pathways. Limited data exist on NOD1 and NOD2 expression in human and mouse Sertoli cells. Currently, there is no data on inflammasome expression or function in Sertoli cells. We found that in primary pre-pubertal Sertoli cells and in adult Sertoli line, TLR4\\NOD1 and NOD2 crosstalk converged in NFκB activation and elicited a NALP3 activation, leading to de novo synthesis and inflammasome priming. This led to caspase-1 activation and IL-1β secretion. We demonstrated this process was controlled by mechanisms linked to autophagy. NOD1 promoted pro-IL-1β restriction and autophagosome maturation arrest, while NOD2 promoted caspase-1 activation, IL-1β secretion and autophagy maturation. NALP3 modulated NOD1 and pro-IL-1β expression, while NOD2 inversely promoted IL-1β. This study is proof of concept that Sertoli cells, upon specific stimulation, could participate in male infertility pathogenesis via inflammatory cytokine induction.

We apply measures of complexity, emergence, and self-organization to an urban traffic model for comparing a traditional traffic-light coordination method with a self-organizing method in two scenarios: cyclic boundaries and non-orientable boundaries. We show that the measures are useful to identify and characterize different dynamical phases. It becomes clear that different operation regimes are required for different traffic demands. Thus, not only is traffic a non-stationary problem, requiring controllers to adapt constantly; controllers must also change drastically the complexity of their behavior depending on the demand. Based on our measures and extending Ashby’s law of requisite variety, we can say that the self-organizing method achieves an adaptability level comparable to that of a living system.

The development of effective vaccines against neglected diseases, especially those associated with poverty and social deprivation, is urgently needed. Modern vaccine technologies and a better understanding of the immune response have provided scientists with the tools for rational and safer design of subunit vaccines. Often, however, subunit vaccines do not elicit strong immune responses, highlighting the need to incorporate better adjuvants; this step therefore becomes a key factor for vaccine development. In this review we outline some key features of modern vaccinology that are linked with the development of better adjuvants. In line with the increased desire to obtain novel adjuvants for future vaccines, the Finlay Adjuvant Platform offers a novel approach for the development of new and effective adjuvants. The Finlay Adjuvants (AFs), AFPL (proteoliposome), and AFCo (cochleate), were initially designed for parenteral and mucosal applications, and constitute potent adjuvants for the induction of Th1 responses against several antigens. This review summarizes the status of the Finlay technology in producing promising adjuvants for unsolved-vaccine diseases including mucosal approaches and therapeutic vaccines. Ideas related to adjuvant classification, adjuvant selection, and their possible influence on innate recognition via multiple toll-like receptors are also discussed.

We extend previously proposed measures of complexity, emergence, and self-organization to continuous distributions using differential entropy. Given that the measures were based on Shannon’s information, the novel continuous complexity measures describe how a system’s predictability changes in terms of the probability distribution parameters. This allows us to calculate the complexity of phenomena for which distributions are known. We find that a broad range of common parameters found in Gaussian and scale-free distributions present high complexity values. We also explore the relationship between our measure of complexity and information adaptation.

In this work, the extraction of phenolic compounds from orange waste (OW) obtained after the industrial extraction of neohesperidin from bitter oranges (Seville oranges) was assayed by microwave-assisted extraction (MAE) and Soxhlet extraction (SE). The extraction agents were ethanol and acetone. For SE, aqueous solutions of both extraction agents were used at 50%, 75%, and 100% (v/v). For MAE, a design of experiments was applied to determine the conditions that maximize the extraction yield. The independent variables were temperature (from 20 to 75 °C), process time (between 10 and 20 min), and percentage of extraction agent (v/v) in the extraction solution (50%, 75%, and 100%). Following that, the extracts were analyzed by ultra-high-performance liquid chromatography to identify the main phenolic compounds extracted. Results showed that 50% (v/v) ethanol or acetone was the extraction agent concentration that maximized the extraction yield for both SE and MAE, with the yields of MAE being higher than those of SE. Thus, the highest extraction yields on a dry basis achieved for MAE were 16.7 g/100 OW for 50% acetone, 75 °C, and 15 min, and 20.2 g/100 OW for 50% ethanol, 75 °C, and 10.8 min, respectively. Finally, the main phenolic compounds found in the orange waste were naringin, hesperidin, neohesperidin, and naringenin (i.e., flavonoids).

Implantation of mammalian embryos into their mother’s uterus ensures optimal nourishment and protection throughout development. Complex molecular interactions characterize the implantation process, and an optimal synchronization of the components of this embryo-maternal dialogue is crucial for a successful reproductive outcome. In the present study, we investigated the role of dendritic cells (DC) during implantation process using a transgenic mouse system (DTRtg) that allows transient depletion of CD11c + cells in vivo through administration of diphtheria toxin. We observed that DC depletion impairs the implantation process, resulting in a reduced breeding efficiency. Furthermore, the maturity of uterine natural killer cells at dendritic cell knockout (DCKO) implantation sites was affected as well; as demonstrated by decreased perforin expression and reduced numbers of periodic-acid-Schiff (PAS)-positive cells. This was accompanied by disarrangements in decidual vascular development. In the present study, we were also able to identify a novel DC-dependent protein, phosphatidylinositol transfer protein β (PITPβ), involved in implantation and trophoblast development using a proteomic approach. Indeed, DCKO mice exhibited substantial anomalies in placental development, including hypocellularity of the spongiotrophoblast and labyrinthine layers and reduced numbers of trophoblast giant cells. Giant cells also down-regulated their expression of two characteristic markers of trophoblast differentiation, placental lactogen 1 and proliferin. In view of these findings, dendritic cells emerge as possible modulators in the orchestration of events leading to the establishment and maintenance of pregnancy.

Single-particle tracking (SPT) was used to determine the mobility characteristics of MHC (major histocompatibility complex) class I molecules at the surface of HeLa cells at 22°C and on different time scales. MHC class I was labeled using the Fab fragment of a monoclonal antibody (W6/32), covalently bound to either R-phycoerythrin or fluorescent microspheres, and the particles were tracked using high-sensitivity fluorescence imaging. Analysis of the data for a fixed time interval suggests a reasonable fit to a random diffusion model. The best fit values of the diffusion coefficient D decreased markedly, however, with increasing time interval, demonstrating the existence of anomalous diffusion. Further analysis of the data shows that the diffusion is anomalous over the complete time range investigated, 4–300 s. Fitting the results obtained with the R-phycoerythrin probe to D = D 0 t α−1 , where D o is a constant and t is the time, gave D 0 = (6.7 ± 4.5) × 10 −11 cm 2 s −1 and α = 0.49 ± 0.16. Experiments with fluorescent microspheres were less reproducible and gave slower anomalous diffusion. The R-phycoerythrin probe is considered more reliable for fluorescent SPT because it is small (11 × 8 nm) and monovalent. The type of motion exhibited by the class I molecules will greatly affect their ability to migrate in the plane of the membrane. Anomalous diffusion, in particular, greatly reduces the distance a class I molecule can travel on the time scale of minutes. The present data are discussed in relation to the possible role of diffusion and clustering in T-cell activation.

A complex regulation of innate and adaptive immune responses at the maternal fetal interface promotes tolerance of trophoblast cells carrying paternally derived antigens. Such regulatory functions involve uterine dendritic cells (uDC) and natural killer (uNK) cells. The existence of a NK and DC “cross talk” has been revealed in various experimental settings; its biological significance ranging from cooperative stimulation to cell lysis. Little is known about the presence or role of NK and DC cross talk at the maternal fetal interface. The present study shows that mouse NK and DC interactions are subject to modulation by trophoblast cells in vitro. This interaction promotes a tolerogenic microenvironment characterized by downregulation of the expression of activation markers on uNK cells and uDC and dominance of Th2 cytokines. NK and DC interactions would also influence uterine cell proliferation and this process would be strongly modulated by trophoblast-derived signals. Indeed; while low proliferation rates were observed upon regular coculture allowing direct contact between uterine cells and trophoblasts, incubation in a transwell culture system markedly increased uterine cell proliferation suggesting that soluble factors are key mediators in the molecular “dialog” between the mother and the conceptus during the establishment of mouse pregnancy. Our data further reveal that the regulatory functions of trophoblast cells associated with tolerance induction are impaired in high abortion murine matings. Interestingly, we observed that secretion of interleukin-12p70 by uDC is dramatically abrogated in the presence of uNK cells. Taken together, our results provide the first evidence that a delicate balance of interactions involving NK cells, DC, and trophoblasts at the mouse maternal fetal interface supports a successful pregnancy outcome.