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In epidemiology, gerontology, human development and the social sciences, age-period-cohort (APC) models are used to study the variability in trajectories of change over time. A well-known issue exists in simultaneously identifying age, period and birth cohort effects, namely that the three characteristics comprise a perfectly collinear system. That is, since age = period−cohort, only two of these effects are estimable at a time. In this paper, we introduce an alternative framework for considering effects relating to age, period and birth cohort. In particular, instead of directly modeling age in the presence of period and cohort effects, we propose a risk modeling approach to characterize age-related risk (i.e., a hybrid of multiple biological and sociological influences to evaluate phenomena associated with growing older). The properties of this approach, termed risk-period-cohort (RPC), are described in this paper and studied by simulations. We show that, except for pathological circumstances where risk is uniquely determined by age, using such risk indices obviates the problem of collinearity. We also show that the size of the chronological age effect in the risk prediction model associates with the correlation between a risk index and chronological age and that the RPC approach can satisfactorily recover cohort and period effects in most cases. We illustrate the advantages of RPC compared to traditional APC analysis on 27496 individuals from NHANES survey data (2005–2016) to study the longitudinal variability in depression screening over time. Our RPC method has broad implications for examining processes of change over time in longitudinal studies. [ABSTRACT FROM AUTHOR]

Dendritic cells (DCs) are the most effective professional antigen-presenting cell. They ferry antigen from the extremities to T cells and are essential for the initiation of an adaptive immune response. Despite interest in how DCs respond to chemical stimuli, there have been few attempts to model DC migration. In this paper, we simulate the motility of DCs by modeling the generation of forces by filopodia and a force balance on the cell. The direction of fliopodial extension is coupled to differential occupancy of cognate chemokine receptors across the cell. Our model simulates chemokinesis and chemotaxis in a variety of chemical and mechanical environments. Simulated DCs undergoing chemokinesis were measured to have a speed of 5.1 ± 0.07 μm·min-1 and a persistence time of 3.2 ± 0.46 min, consistent with experiment. Cells undergoing chemotaxis exhibited a stronger chemotactic response when exposed to lower average chemokine concentrations, also consistent with experiment. We predicted that when placed in two opposing gradients, cells will cluster in a line, which we call the “line of equistimulation;” this clustering has also been observed. We calculated the effect of varying gradient steepness on the line of equistimulation, with steeper gradients resulting in tighter clustering. Moreover, gradients are found to be most potent when cells are in a gradient of chemokine whose mean concentration is close to the binding of the Kd to the receptor, and least potent when the mean concentration is 0.1Kd. Comparing our simulations to experiment, we can give a quantitative measure of the strength of certain chemokines relative to others. Assigning the signal of CCL19 binding CCR7 a baseline strength of 1, we found CCL21 binding CCR7 had a strength of 0.28, and CXCL12 binding CXCR4 had a strength of 0.30. These differences emerge despite both chemokines having virtually the same Kd, suggesting a mechanism of signal amplification in DCs requiring further study. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this paper was to describe the time trends in the prevalence of multimorbidity and polypharmacy in Flanders (Belgium) between 2000 and 2015, while controlling for age and sex. Methods: Data were available from Intego, a Flemish-Belgian general practice-based morbidity registration network. The practice population between 2000 and 2015 was used as the denominator, representing a mean of 159,946 people per year. Age and gender-standardised prevalence rates were used for the trends of multimorbidity and polypharmacy in the total population and for subgroups. Joinpoint regression analyses were used to analyse the time trends and breaks in trends, for the entire population as well as for specific age and sex groups. Results: Overall, in 2015, 22.7% of the population had multimorbidity, while the overall prevalence of polypharmacy was 20%. Throughout the study period the standardised prevalence rate of multimorbidity rose for both sexes and in all age groups. The largest relative increase in multimorbidity was observed in the younger age groups (up to the age of 50 years). The prevalence of polypharmacy showed a significant increase between 2000 and 2015 for all age groups except the youngest (0–25 years). Conclusion: For all adult age groups multimorbidity and polypharmacy are frequent, dynamic over time and increasing. This asks for both epidemiological and interventional studies to improve the management of the resulting complex care. [ABSTRACT FROM AUTHOR]

Oncolytic virus (OV) is a replication competent virus that selectively invades cancer cells; as these cells die under the viral burden, the released virus particles proceed to infect other cancer cells. Oncolytic viruses are designed to also be able to stimulate the anticancer immune response. Thus, one may represent an OV by two parameters: its replication potential and its immunogenicity. In this paper we consider a combination therapy with OV and a checkpoint inhibitor, anti-PD-1. We evaluate the efficacy of the combination therapy in terms of the tumor volume at some later time, for example, 6 months from initial treatment. Since T cells kill not only virus-free cancer cells but also virus-infected cancer cells, the following question arises: Does increasing the amount of the checkpoint inhibitor always improve the efficacy? We address this question, by a mathematical model consisting of a system of partial differential equations. We use the model to construct, by simulations, an efficacy map in terms of the doses of the checkpoint inhibitor and the OV injection. We show that there are regions in the map where an increase in the checkpoint inhibitor actually decreases the efficacy of the treatment. We also construct efficacy maps with checkpoint inhibitor vs. the replication potential of the virus that show the same antagonism, namely, an increase in the checkpoint inhibitor may actually decrease the efficacy. These results have implications for clinical trials. [ABSTRACT FROM AUTHOR]

Cross-presentation of apoptotic cell associated antigens by immature dendritic cells prevents the activation of self reactive CD8 T cells. Tolerized self reactive CD8 T cells down-regulate IL-7R expression on their surface. Whether over-expression of IL-7R can reverse their fate and function has not been examined. In this paper, we showed forced expression of IL-7R in OT-I T cells by a transgene enhanced CD8 T cell mediated diabetes in the RIP-mOVA model. Although IL-7R Tg (transgenic) did not completely reverse the deletion of OT-I T cells, it provided a significant survival advantage over w.t OT-I T cells. Furthermore, IL7R Tg OT-I T cells isolated from diabetic pancreata displayed increased production of IFN-γ, higher expression of T-bet, and increased externalization of CD107a. We also found that immature DCs containing apoptotic cells expressed high levels of PDL-1 on their surface. Although IL-7R Tg did not change PD1 expression on activated OT-I cells in vivo, the transgene enabled a significantly lower number of OT-I T cells to induce diabetes in the absence of PDL-1. Our results demonstrated that forced expression of IL-7R not only improved the functionality of tolerized CD8 T cells, it also acted in synergy with PDL-1 deficiency to further promote CD8 T cell cytotoxicity to self antigens. [ABSTRACT FROM AUTHOR]

T-cells and antigen presenting cells are an essential part of the adaptive immune response system and how they interact is crucial in how the body effectively fights infection or responds to vaccines. Much of the experimental work studying interaction forces between cells has looked at the average properties of bulk samples of cells or applied microscopy to image the dynamic contact between these cells. In this paper we present a novel optical trapping technique for interrogating the force of this interaction and measuring relative interaction forces at the single-cell level. A triple-spot optical trap is used to directly manipulate the cells of interest without introducing foreign bodies such as beads to the system. The optical trap is used to directly control the initiation of cell-cell contact and, subsequently to terminate the interaction at a defined time point. The laser beam power required to separate immune cell pairs is determined and correlates with the force applied by the optical trap. As proof of concept, the antigen-specific increase in interaction force between a dendritic cell and a specific T-cell is demonstrated. Furthermore, it is demonstrated that this interaction force is completely abrogated when T-cell signalling is blocked. As a result the potential of using optical trapping to interrogate cellular interactions at the single cell level without the need to introduce foreign bodies such as beads is clearly demonstrated. [ABSTRACT FROM AUTHOR]

Robot swarms are large-scale multirobot systems with decentralized control which means that each robot acts based only on local perception and on local coordination with neighboring robots. The decentralized approach to control confers number of potential benefits. In particular, inherent scalability and robustness are often highlighted as key distinguishing features of robot swarms compared with systems that rely on traditional approaches to multirobot coordination. It has, however, been shown that swarm robotics systems are not always fault tolerant. To realize the robustness potential of robot swarms, it is thus essential to give systems the capacity to actively detect and accommodate faults. In this paper, we present a generic fault-detection system for robot swarms. We show how robots with limited and imperfect sensing capabilities are able to observe and classify the behavior of one another. In order to achieve this, the underlying classifier is an immune system-inspired algorithm that learns to distinguish between normal behavior and abnormal behavior online. Through a series of experiments, we systematically assess the performance of our approach in a detailed simulation environment. In particular, we analyze our system’s capacity to correctly detect robots with faults, false positive rates, performance in a foraging task in which each robot exhibits a composite behavior, and performance under perturbations of the task environment. Results show that our generic fault-detection system is robust, that it is able to detect faults in a timely manner, and that it achieves a low false positive rate. The developed fault-detection system has the potential to enable long-term autonomy for robust multirobot systems, thus increasing the usefulness of robots for a diverse repertoire of upcoming applications in the area of distributed intelligent automation. [ABSTRACT FROM AUTHOR]

This paper distinguishes a rare subset of myeloid dendritic-like cells found in mouse spleen from conventional (c) dendritic cells (DC) in terms of phenotype, function and gene expression. These cells are tentatively named “L-DC” since they resemble dendritic-like cells produced in longterm cultures of spleen. L-DC can be distinguished on the basis of their unique phenotype as CD11bhiCD11cloMHCII-CD43+Ly6C-Ly6G-Siglec-F- cells. They demonstrate similar ability as cDC to uptake and retain complex antigens like mannan via mannose receptors, but much lower ability to endocytose and retain soluble antigen. While L-DC differ from cDC by their inability to activate CD4+ T cells, they are capable of antigen cross-presentation for activation of CD8+ T cells, although less effectively so than the cDC subsets. In terms of gene expression, CD8- cDC and CD8+ cDC are quite distinct from L-DC. CD8+ cDC are distinguishable from the other two subsets by expression of CD24a, Clec9a, Xcr1 and Tlr11, while CD8- cDC are distinguished by expression of Ccnd1 and H-2Eb2. L-DC are distinct from the two cDC subsets through upregulated expression of Clec4a3, Emr4, Itgam, Csf1r and CD300ld. The L-DC gene profile is quite distinct from that of cDC, confirming a myeloid cell type with distinct antigen presenting properties. [ABSTRACT FROM AUTHOR]

Cellular signalling pathways consolidate multiple molecular interactions into working models of signal propagation, amplification, and modulation. They are described and visualized as networks. Adjusting network topologies to experimental data is a key goal of systems biology. While network reconstruction algorithms like nested effects models are well established tools of computational biology, their data requirements can be prohibitive for their practical use. In this paper we suggest focussing on well defined aspects of a pathway and develop the computational tools to do so. We adapt the framework of nested effect models to focus on a specific aspect of activated Wnt signalling in HCT116 colon cancer cells: Does the activation of Wnt target genes depend on the secretion of Wnt ligands or do mutations in the signalling molecule β-catenin make this activation independent from them? We framed this question into two competing classes of models: Models that depend on Wnt ligands secretion versus those that do not. The model classes translate into restrictions of the pathways in the network topology. Wnt dependent models are more flexible than Wnt independent models. Bayes factors are the standard Bayesian tool to compare different models fairly on the data evidence. In our analysis, the Bayes factors depend on the number of potential Wnt signalling target genes included in the models. Stability analysis with respect to this number showed that the data strongly favours Wnt ligands dependent models for all realistic numbers of target genes. [ABSTRACT FROM AUTHOR]

• In this paper, by reviewing MC phagocytic function, activated MC expression of APC surface markers, and MC participation in the inflammatory response and local renal immune response, we confirm that activated MCs can act as APCs in renal disease. • This review introduces MC function through a developmental perspective and summarizes the important role of MC as antigen-presenting cells in renal local immune response. • This review mentions the uniqueness of MC and also points out the limitations of MC research at this stage. Mesangial cells (MCs), as resident cells of the kidneys, play an important role in maintaining glomerular function. MCs are located between the capillary loops of the glomeruli and mainly support the capillary plexus, constrict blood vessels, extracellular matrix components, produce cytokines, and perform phagocytosis and clearance of macromolecular substances. When the glomerular environment changes, MCs are often affected, which can lead to functional transformation. The immune response is involved in the occurrence and development of various kidney diseases, in these diseases, antigen-presenting cells (APCs) play an important role. APCs can present antigens to T lymphocytes, causing them to become activated and proliferate. Studies have shown that MCs have phagocytic function and express APC markers on the cell surface. Additionally, MCs are stimulated by or produce various inflammatory factors to participate in the renal inflammatory response. Therefore, MCs have potential antigen presentation function and participate in the pathological changes of various kidney diseases as APCs upon activation. In this paper, by reviewing MC phagocytic function, activated MC expression of APC surface markers, and MC participation in the inflammatory response and local renal immune response, we confirm that activated MCs can act as APCs in renal disease. [ABSTRACT FROM AUTHOR]

Mitoxantrone is an antineoplastic agent approved for clinical use in the secondary progressive phase of multiple sclerosis (MS). Several scientific reports indicate that mitoxantrone acts through the induction of short-term cell lysis at high concentrations and long-term induction of programmed cell death at lower concentrations of antigen-presenting cells. In this paper, we present the potential cytotoxic effects of mitoxantrone on the cells of the immune system, whose activity is associated with their degenerative effects on axonal myelin sheaths. The article also evaluates the results from the hospital treatment of patients diagnosed with MS. The presented data indicate that, apart from the cytostatic properties, mitoxantrone also exhibits side effects of its clinical application. This drug has high cardiotoxicity, and is associated with decreased left ventricular ejection fraction and increased risk of congestive heart failure. Therefore researchers are currently looking for new substances that can reduce the toxic effects of mitoxantrone in healthy tissues, resulting in the generation of reactive oxygen species during its metabolism. [ABSTRACT FROM AUTHOR]

Abstract: The adaptive immune system of a vertebrate may attack its own body, causing autoimmune diseases. Regulatory T cells suppress the activity of the autoreactive effector T cells, but they also interrupt normal immune reactions against foreign antigens. In this paper, we discuss the optimal number of regulatory T cells that should be produced. We make the assumptions that some self-reactive immature T cells may fail to interact with their target antigens during the limited training period and later become effector T cells causing autoimmunity, and that regulatory T cells exist that recognize self-antigens. When a regulatory T cell is stimulated by its target self-antigen on an antigen-presenting cell (APC), it stays there and suppresses the activation of other naive T cells on the same APC. Analysis of the benefit and the harm of having regulatory T cells suggests that the optimal number of regulatory T cells depends on the number of self-antigens, the severity of the autoimmunity, the abundance of pathogenic foreign antigens, and the spatial distribution of self-antigens in the body. For multiple types of self-antigen, we discuss the optimal number of regulatory T cells when the self-antigens are localized in different parts of the body and when they are co-localized. We also examine the separate regulation of the abundances of regulatory T cells for different self-antigens, comparing it with the situation in which they are constrained to be equal. [Copyright &y& Elsevier]

Cathepsin E (CatE) and D (CatD) are the major aspartic proteinases in the endolysosomal pathway. They have similar specificity and therefore it is difficult to distinguish between them, as known substrates are not exclusively specific for one or the other. In this paper we present a substrate-based assay, which is highly relevant for immunological investigations because it detects both CatE and CatD in antigen-processing organelles. Therefore it could be used to study the involvement of these proteinases in protein degradation and the processing of invariant chain. An assay combining a new monospecific CatE antibody and the substrate, MOCAc-Gly-Lys-Pro-Ile-Leu-Phe-Phe-Arg-Leu-Lys(Dnp)-d-Arg-NH2[where MOCAc is (7-methoxycoumarin-4-yl)acetyl and Dnp is dinitrophenyl], is presented. This substrate is digested by both proteinases and therefore can be used to detect total aspartic proteinase activity in biological samples. After depletion of CatE by immunoprecipitation, the remaining activity is due to CatD, and the decrease in activity can be assigned to CatE. The activity of CatE and CatD in cytosolic, endosomal and lysosomal fractions of B cells, dendritic cells and human keratinocytes was determined. The data clearly indicate that CatE activity is mainly located in endosomal compartments, and that of CatD in lysosomal compartments. Hence this assay can also be used to characterize subcellular fractions using CatE as an endosomal marker, whereas CatD is a well-known lysosomal marker. The highest total aspartic proteinase activity was detected in dendritic cells, and the lowest in B cells. The assay presented exhibits a lower detection limit than common antibody-based methods without lacking the specificity. [ABSTRACT FROM AUTHOR]