ß2-microglobulin triggers NLRP3 inflammasome activation in tumor-associated macrophages to promote multiple myeloma progression.

As substantial constituents of the multiple myeloma (MM) microenvironment, pro-inflammatory macrophages have emerged as key promoters of disease progression, bone destruction, and immune impairment. We identify beta-2-microglobulin (ß2m) as a driver in initiating inflammation in myeloma-associated macrophages (MAMs). Lysosomal accumulation of phagocytosed ß2m promotes ß2m amyloid aggregation in MAMs, resulting in lysosomal rupture and ultimately production of active interleukin-1ß (IL-1ß) and IL-18. This process depends on activation of the NLRP3 inflammasome after ß2m accumulation, as macrophages from NLRP3-deficient mice lack efficient ß2m-induced IL-1ß production. Moreover, depletion or silencing of ß2m in MM cells abrogates inflammasome activation in a murine MM model. Finally, we demonstrate that disruption of NLRP3 or IL-18 diminishes tumor growth and osteolytic bone destruction normally promoted by ß2m-induced inflammasome signaling. Our results provide mechanistic evidence for ß2m's role as an NLRP3 inflammasome activator during MM pathogenesis. Moreover, inhibition of NLRP3 represents a potential therapeutic approach in MM.

CD20-bispecific antibodies improve response to CD19-CAR T cells in lymphoma in vitro and CLL in vivo models.

ABSTRACT: Relapse after anti-CD19 chimeric antigen receptor (CD19-CAR) occurs in a substantial proportion of patients with lymphoid malignancies. We assessed the potential benefits of co-administering CD20-targeting bispecific antibodies (CD20-BsAbs) with CD19-CAR T cells with the aim of enhancing immunotherapeutic efficacy. Addition of CD20-BsAbs to cocultures of CD19-CARs and primary samples of B-cell malignancies, comprising malignant B cells and endogenous T cells, significantly improved killing of malignant cells and enhanced the expansion of both endogenous T cells and CD19-CAR T cells. In an immunocompetent mouse model of chronic lymphocytic leukemia, relapse after initial treatment response frequently occurred after CD19-CAR T-cell monotherapy. Additional treatment with CD20-BsAbs significantly enhanced the treatment response and led to improved eradication of malignant cells. Higher efficacy was accompanied by improved T-cell expansion with CD20-BsAb administration and led to longer survival with 80% of the mice being cured with no detectable malignant cell population within 8 weeks of therapy initiation. Collectively, our in vitro and in vivo data demonstrate enhanced therapeutic efficacy of CD19-CAR T cells when combined with CD20-BsAbs in B-cell malignancies. Activation and proliferation of both infused CAR T cells and endogenous T cells may contribute to improved disease control.

CD16+ as predictive marker for early relapse in aggressive B-NHL/DLBCL patients.

Assessing the prognosis of patients with aggressive non-Hodgkin B cell lymphoma mainly relies on a clinical risk score (IPI). Standard first-line therapies are based on a chemo-immunotherapy with rituximab, which mediates CD16-dependent antibody-dependent cellular cytotoxicity (ADCC). We phenotypically and functionally analyzed blood samples from 46 patients focusing on CD16+ NK cells, CD16+ T cells and CD16+ monocytes. Kaplan-Meier survival curves show a superior progression-free survival (PFS) for patients having more than 1.6% CD16+ T cells (p = 0.02; HR = 0.13 (0.007-0.67)) but an inferior PFS having more than 10.0% CD16+ monocytes (p = 0.0003; HR = 16.0 (3.1-291.9)) at diagnosis. Surprisingly, no correlation with NK cells was found. The increased risk of relapse in the presence of > 10.0% CD16+ monocytes is reversed by the simultaneous occurrence of > 1.6% CD16+ T cells. The unexpectedly strong protective function of CD16+ T cells could be explained by their high antibody-dependent cellular cytotoxicity as quantified by real-time killing assays and single-cell imaging. The combined analysis of CD16+ monocytes (> 10%) and CD16+ T cells (< 1.6%) provided a strong model with a Harrell's C index of 0.80 and a very strong power of 0.996 even with our sample size of 46 patients. CD16 assessment in the initial blood analysis is thus a precise marker for early relapse prediction.

Optimizing Monotone Chance-Constrained Submodular Functions Using Evolutionary Multi-Objective Algorithms.

Many real-world optimization problems can be stated in terms of submodular functions. Furthermore, these real-world problems often involve uncertainties which may lead to the violation of given constraints. A lot of evolutionary multi-objective algorithms following the Pareto optimization approach have recently been analyzed and applied to submodular problems with different types of constraints. We present a first runtime analysis of evolutionary multi-objective algorithms based on Pareto optimization for chance-constrained submodular functions. Here the constraint involves stochastic components and the constraint can only be violated with a small probability of α. We investigate the classical GSEMO algorithm for two different bi-objective formulations using tail bounds to determine the feasibility of solutions. We show that the algorithm GSEMO obtains the same worst case performance guarantees for monotone submodular functions as recently analyzed greedy algorithms for the case of uniform IID weights and uniformly distributed weights with the same dispersion when using the appropriate bi-objective formulation. As part of our investigations, we also point out situations where the use of tail bounds in the first bi-objective formulation can prevent GSEMO from obtaining good solutions in the case of uniformly distributed weights with the same dispersion if the objective function is submodular but non-monotone due to a single element impacting monotonicity. Furthermore, we investigate the behavior of the evolutionary multi-objective algorithms GSEMO, NSGA-II and SPEA2 on different submodular chance-constrained network problems. Our experimental results show that the use of evolutionary multi-objective algorithms leads to significant performance improvements compared to state-of-the-art greedy algorithms for submodular optimization.

Runtime Analysis of Single- and Multi-Objective Evolutionary Algorithms for Chance Constrained Optimization Problems with Normally Distributed Random Variables.

Chance constrained optimization problems allow to model problems where constraints involving stochastic components should only be violated with a small probability. Evolutionary algorithms have been applied to this scenario and shown to achieve high quality results. With this paper, we contribute to the theoretical understanding of evolutionary algorithms for chance constrained optimization. We study the scenario of stochastic components that are independent and normally distributed. Considering the simple single-objective (1+1) EA, we show that imposing an additional uniform constraint already leads to local optima for very restricted scenarios and an exponential optimization time. We therefore introduce a multi-objective formulation of the problem which trades off the expected cost and its variance. We show that multi-objective evolutionary algorithms are highly effective when using this formulation and obtain a set of solutions that contains an optimal solution for any possible confidence level imposed on the constraint. Furthermore, we prove that this approach can also be used to compute a set of optimal solutions for the chance constrained minimum spanning tree problem. In order to deal with potentially exponentially many trade-offs in the multi-objective formulation, we propose and analyze improved convex multi-objective approaches. Experimental investigations on instances of the NP-hard stochastic minimum weight dominating set problem confirm the benefit of the multi-objective and the improved convex multi-objective approach in practice.

B-cell receptor reactivity against Rothia mucilaginosa in nodular lymphocyte-predominant Hodgkin lymphoma.

Nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) is a Hodgkin lymphoma expressing functional B-cell receptors (BCR). Recently, we described a dual stimulation model of IgD+ lymphocyte-predominant cells by Moraxella catarrhalis antigen RpoC and its superantigen MID/hag, associated with extralong CDR3 and HLA-DRB1*04 or HLADRB1* 07 haplotype. The aim of the present study was to extend the antigen screening to further bacteria and viruses. The fragment antibody-binding (Fab) regions of seven new and 15 previously reported cases were analyzed. The reactivity of non-Moraxella spp.-reactive Fab regions against lysates of Rothia mucilaginosa was observed in 5/22 (22.7%) cases. Galactofuranosyl transferase (Gltf) and 2,3-butanediol dehydrogenase (Bdh) of R. mucilaginosa were identified by comparative silver- and immuno-staining in two-dimensional gels, with subsequent mass spectrometry and validation by western blots and enzyme-linked immunosorbent assay. Both R. mucilaginosa Gltf and Bdh induced BCR pathway activation and proliferation in vitro. Apoptosis was induced by recombinant Gltf/ETA'-immunotoxin conjugates in DEV cells expressing recombinant R. mucilaginosa-reactive BCR. Reactivity against M. catarrhalis RpoC was confirmed in 3/7 newly expressed BCR (total 10/22 reactive to Moraxella spp.), resulting in 15/22 (68.2%) cases with BCR reactivity against defined bacterial antigens. These findings strengthen the hypothesis of bacterial trigger contributing to subsets of NLPHL.

Increased B-cell activity with consumption of activated monocytes in severe COVID-19 patients.

The pathogenesis of autoimmune complications triggered by SARS-CoV2 has not been completely elucidated. Here, we performed an analysis of the cellular immune status, cell ratios, and monocyte populations of patients with COVID-19 treated in the intensive care unit (ICU) (cohort 1, N = 23) and normal care unit (NCU) (cohort 2, n = 10) compared with control groups: patients treated in ICU for noninfectious reasons (cohort 3, n = 30) and patients treated in NCU for infections other than COVID-19 (cohort 4, n = 21). Patients in cohort 1 presented significant differences in comparison with the other cohorts, including reduced frequencies of lymphocytes, reduced CD8+T-cell count, reduced percentage of activated and intermediate monocytes and an increased B/T8 cell ratio. Over time, patients in cohort 1 who died presented with lower counts of B, T, CD4+ T, CD8+ T-lymphocytes, NK cells, and activated monocytes. The B/T8 ratio was significantly lower in the group of survivors. In cohort 1, significantly higher levels of IgG1 and IgG3 were found, whereas cohort 3 presented higher levels of IgG3 compared to controls. Among many immune changes, an elevated B/T8-cell ratio and a reduced rate of activated monocytes were mainly observed in patients with severe COVID-19. Both parameters were associated with death in cohort 1.

Bee flowers drive macroevolutionary diversification in long-horned bees.

The role of plant-pollinator interactions in the rapid radiation of the angiosperms have long fascinated evolutionary biologists. Studies have brought evidence for pollinator-driven diversification of various plant lineages, particularly plants with specialized flowers and concealed rewards. By contrast, little is known about how this crucial interaction has shaped macroevolutionary patterns of floral visitors. In particular, there is currently no empirical evidence that floral host association has increased diversification in bees, the most prominent group of floral visitors that essentially rely on angiosperm pollen. In this study, we examine how floral host preference influenced diversification in eucerine bees (Apidae, Eucerini), which exhibit large variations in their floral associations. We combine quantitative pollen analyses with a recently proposed phylogenetic hypothesis, and use a state speciation and extinction probabilistic approach. Using this framework, we provide the first evidence that multiple evolutionary transitions from host plants with accessible pollen to restricted pollen from 'bee-flowers' have significantly increased the diversification of a bee clade. We suggest that exploiting host plants with restricted pollen has allowed the exploitation of a new ecological niche for eucerine bees and contributed both to their colonization of vast regions of the world and their rapid diversification.

Identification of the atypically modified autoantigen Ars2 as the target of B-cell receptors from activated B-cell-type diffuse large B-cell lymphoma.

It has been suggested that B-cell receptor (BCRs) stimulation by specific antigens plays a pathogenic role in diffuse large B-cell lymphoma (DLBCL). Here, it was the aim to screen for specific reactivities of DLBCL-BCRs in the spectrum of autoantigens and antigens of infectious origin. Arsenite resistance protein 2 (Ars2) was identified as the BCR target of 3/5 ABC-type DLBCL cell lines and 2/11 primary DLBCL cases. Compared to controls, Ars2 was hypo-phosphorylated exclusively in cases and cell lines with Ars2-specific BCRs. In a validation cohort, hypo-phosphorylated Ars2 was found in 8/31 ABC-type, but only 1/20 germinal center B cell (GBC)-like type DLBCL. Incubation with Ars2 induced BCR-pathway activation and increased proliferation, while an Ars2/ETA-toxin conjugate induced killing of cell lines with Ars2-reactive BCRs. Ars2 appears to play a role in a subgroup of ABC-type DLBCLs. Moreover, transformed DLBCL lines with Ars2-reactive BCRs still show growth advantage after incubation with Ars2. These results provide knowledge about the pathogenic role of a specific antigen stimulating the BCR pathway in DLCBL.

Feature-Based Diversity Optimization for Problem Instance Classification.

Understanding the behaviour of heuristic search methods is a challenge. This even holds for simple local search methods such as 2-OPT for the Travelling Salesperson Problem (TSP). In this article, we present a general framework that is able to construct a diverse set of instances which are hard or easy for a given search heuristic. Such a diverse set is obtained by using an evolutionary algorithm for constructing hard or easy instances which are diverse with respect to different features of the underlying problem. Examining the constructed instance sets, we show that many combinations of two or three features give a good classification of the TSP instances in terms of whether they are hard to be solved by 2-OPT.

Characterization of an HLA-restricted and human cytomegalovirus-specific antibody repertoire with therapeutic potential.

With an infection rate of 60-90%, the human cytomegalovirus (HCMV) is very common among adults but normally causes no symptoms. When T cell-mediated immunity is compromised, HCMV reactivation can lead to increased morbidity and mortality. HCMV antigens are processed and presented as peptides on the cell surface via HLA I complexes to the T cell receptor (TCR) of T cells. The generation of antibodies against HCMV peptides presented on HLA complexes (TCR-like antibodies) has been described, but is without therapeutic applications to date due to the polygenic and polymorphic nature of HLA genes. We set out to obtain antibodies specific for HLA/HCMV-peptides, covering the majority of HLA alleles present in European populations. Using phage display technology, we selected 10 Fabs, able to bind to HCMV-peptides presented in the 6 different HLA class I alleles A*0101, A*0201, A*2402, B*0702, B*0801 and B*3501. We demonstrate specific binding of all selected Fabs to HLA-typed lymphoblastoid cell lines (EBV-transformed B cells) and lymphocytes loaded with HCMV-peptides. After infection with HCMV, 4/10 tetramerized Fabs restricted to the alleles HLA-A*0101, HLA-A*0201 and HLA-B*0702 showed binding to infected primary fibroblasts. When linked to the pseudomonas exotoxin A, these Fab antibodies induce highly specific cytotoxicity in HLA matched cell lines loaded with HCMV peptides. TCR-like antibody repertoires therefore represent a promising new treatment modality for viral infections and may also have applications in the treatment of cancers.

A systematic genomic screen implicates nucleocytoplasmic transport and membrane growth in nuclear size control.

How cells control the overall size and growth of membrane-bound organelles is an important unanswered question of cell biology. Fission yeast cells maintain a nuclear size proportional to cellular size, resulting in a constant ratio between nuclear and cellular volumes (N/C ratio). We have conducted a genome-wide visual screen of a fission yeast gene deletion collection for viable mutants altered in their N/C ratio, and have found that defects in both nucleocytoplasmic mRNA transport and lipid synthesis alter the N/C ratio. Perturbing nuclear mRNA export results in accumulation of both mRNA and protein within the nucleus, and leads to an increase in the N/C ratio which is dependent on new membrane synthesis. Disruption of lipid synthesis dysregulates nuclear membrane growth and results in an enlarged N/C ratio. We propose that both properly regulated nucleocytoplasmic transport and nuclear membrane growth are central to the control of nuclear growth and size.

Differential effects of endurance, interval, and resistance training on telomerase activity and telomere length in a randomized, controlled study.

Aims: It is unknown whether different training modalities exert differential cellular effects. Telomeres and telomere-associated proteins play a major role in cellular aging with implications for global health. This prospective training study examines the effects of endurance training, interval training (IT), and resistance training (RT) on telomerase activity and telomere length (TL). Methods and results: One hundred and twenty-four healthy previously inactive individuals completed the 6 months study. Participants were randomized to three different interventions or the control condition (no change in lifestyle): aerobic endurance training (AET, continuous running), high-intensive IT (4 × 4 method), or RT (circle training on 8 devices), each intervention consisting of three 45 min training sessions per week. Maximum oxygen uptake (VO2max) was increased by all three training modalities. Telomerase activity in blood mononuclear cells was up-regulated by two- to three-fold in both endurance exercise groups (AET, IT), but not with RT. In parallel, lymphocyte, granulocyte, and leucocyte TL increased in the endurance-trained groups but not in the RT group. Magnet-activated cell sorting with telomerase repeat-ampliflication protocol (MACS-TRAP) assays revealed that a single bout of endurance training-but not RT-acutely increased telomerase activity in CD14+ and in CD34+ leucocytes. Conclusion: This randomized controlled trial shows that endurance training, IT, and RT protocols induce specific cellular pathways in circulating leucocytes. Endurance training and IT, but not RT, increased telomerase activity and TL which are important for cellular senescence, regenerative capacity, and thus, healthy aging.

Targeted INO80 enhances subnuclear chromatin movement and ectopic homologous recombination.

Chromatin in the interphase nucleus moves in a constrained random walk. Despite extensive study, the molecular causes of such movement and its impact on DNA-based reactions are unclear. Using high-precision live fluorescence microscopy in budding yeast, we quantified the movement of tagged chromosomal loci to which transcriptional activators or nucleosome remodeling complexes were targeted. We found that local binding of the transcriptional activator VP16, but not of the Gal4 acidic domain, enhances chromatin mobility. The increase in movement did not correlate strictly with RNA polymerase II (PolII) elongation, but could be phenocopied by targeting the INO80 remodeler to the locus. Enhanced chromatin mobility required Ino80's ATPase activity. Consistently, the INO80-dependent remodeling of nucleosomes upon transcriptional activation of the endogenous PHO5 promoter enhanced chromatin movement locally. Finally, increased mobility at a double-strand break was also shown to depend in part on the INO80 complex. This correlated with increased rates of spontaneous gene conversion. We propose that local chromatin remodeling and nucleosome eviction increase large-scale chromatin movements by enhancing the flexibility of the chromatin fiber.

Evolutionary Image Transition and Painting Using Random Walks.

We present a study demonstrating how random walk algorithms can be used for evolutionary image transition. We design different mutation operators based on uniform and biased random walks and study how their combination with a baseline mutation operator can lead to interesting image transition processes in terms of visual effects and artistic features. Using feature-based analysis we investigate the evolutionary image transition behaviour with respect to different features and evaluate the images constructed during the image transition process. Afterwards, we investigate how modifications of our biased random walk approaches can be used for evolutionary image painting. We introduce an evolutionary image painting approach whose underlying biased random walk can be controlled by a parameter influencing the bias of the random walk and thereby creating different artistic painting effects.

Origin and divergence of Afro-Indian Picrodendraceae: linking pollen morphology, dispersal modes, fossil records, molecular dating and paleogeography.

The pantropical Picrodendraceae produce mostly spheroidal to slightly oblate, echinate pollen grains equipped with narrow circular to elliptic pori that can be hard to identify to family level in both extant and fossil material using light microscopy only. Fossil pollen of the family have been described from the Paleogene of America, Antarctica, Australia, New Zealand, and Europe, but until now none have been reported from Afro-India. Extant pollen described here include representatives from all recent Picrodendraceae genera naturally occurring in Africa and/or Madagascar and south India and selected closely related tropical American taxa. Our analyses, using combined light microscopy and scanning electron microscopy, show that pollen of the Afro-Indian genera encompass three morphological types: Type 1, comprising only Hyaenanche; Type 2, including Aristogeitonia, Mischodon, Oldfieldia and Voatamalo; Type 3, comprising the remaining two genera, Androstachys and Stachyandra. Based on the pollen morphology presented here it is evident that some previous light microscopic accounts of spherical and echinate fossil pollen affiliated with Arecaceae, Asteraceae, Malvaceae, and Myristicaceae from the African continent could belong to Picrodendraceae. The pollen morphology of Picrodendraceae, fossil pollen records, a dated intra-familial phylogeny, seed dispersal modes, and the regional Late Cretaceous to early Cenozoic paleogeography, together suggest the family originated in the Americas and dispersed from southern America across Antarctica and into Australasia. A second dispersal route is believed to have occurred from the Americas into continental Africa via the North Atlantic Land Bridge and Europe.

Theoretical Analysis of Local Search and Simple Evolutionary Algorithms for the Generalized Travelling Salesperson Problem.

The generalized travelling salesperson problem is an important NP-hard combinatorial optimization problem for which metaheuristics, such as local search and evolutionary algorithms, have been used very successfully. Two hierarchical approaches with different neighbourhood structures, namely a cluster-based approach and a node-based approach, have been proposed by Hu and Raidl (2008) for solving this problem. In this article, local search algorithms and simple evolutionary algorithms based on these approaches are investigated from a theoretical perspective. For local search algorithms, we point out the complementary abilities of the two approaches by presenting instances where they mutually outperform each other. Afterwards, we introduce an instance which is hard for both approaches when initialized on a particular point of the search space, but where a variable neighbourhood search combining them finds the optimal solution in polynomial time. Then we turn our attention to analysing the behaviour of simple evolutionary algorithms that use these approaches. We show that the node-based approach solves the hard instance of the cluster-based approach presented in Corus et al. (2016) in polynomial time. Furthermore, we prove an exponential lower bound on the optimization time of the node-based approach for a class of Euclidean instances.

Parameterized Analysis of Multiobjective Evolutionary Algorithms and the Weighted Vertex Cover Problem.

Evolutionary multiobjective optimization for the classical vertex cover problem has been analysed in Kratsch and Neumann (2013) in the context of parameterized complexity analysis. This article extends the analysis to the weighted vertex cover problem in which integer weights are assigned to the vertices and the goal is to find a vertex cover of minimum weight. Using an alternative mutation operator introduced in Kratsch and Neumann (2013), we provide a fixed parameter evolutionary algorithm with respect to OPT, the cost of an optimal solution for the problem. Moreover, we present a multiobjective evolutionary algorithm with standard mutation operator that keeps the population size in a polynomial order by means of a proper diversity mechanism, and therefore, manages to find a 2-approximation in expected polynomial time. We also introduce a population-based evolutionary algorithm which finds a (1+ɛ)-approximation in expected time O(n·2min{n,2(1-ɛ)OPT}+n3).

Automated Algorithm Selection: Survey and Perspectives.

It has long been observed that for practically any computational problem that has been intensely studied, different instances are best solved using different algorithms. This is particularly pronounced for computationally hard problems, where in most cases, no single algorithm defines the state of the art; instead, there is a set of algorithms with complementary strengths. This performance complementarity can be exploited in various ways, one of which is based on the idea of selecting, from a set of given algorithms, for each problem instance to be solved the one expected to perform best. The task of automatically selecting an algorithm from a given set is known as the per-instance algorithm selection problem and has been intensely studied over the past 15 years, leading to major improvements in the state of the art in solving a growing number of discrete combinatorial problems, including propositional satisfiability and AI planning. Per-instance algorithm selection also shows much promise for boosting performance in solving continuous and mixed discrete/continuous optimisation problems. This survey provides an overview of research in automated algorithm selection, ranging from early and seminal works to recent and promising application areas. Different from earlier work, it covers applications to discrete and continuous problems, and discusses algorithm selection in context with conceptually related approaches, such as algorithm configuration, scheduling, or portfolio selection. Since informative and cheaply computable problem instance features provide the basis for effective per-instance algorithm selection systems, we also provide an overview of such features for discrete and continuous problems. Finally, we provide perspectives on future work in the area and discuss a number of open research challenges.

Determination of optimum vitamin D3 levels for NK cell-mediated rituximab- and obinutuzumab-dependent cellular cytotoxicity.

Vitamin D3 (25-OH-D3) deficiency impairs rituximab-dependent cellular cytotoxicity and the outcome of patients with diffuse large B-cell and follicular lymphomas (DLBCL). Since the optimum 25-OH-D3 serum levels for NK cell-mediated antibody-dependent cellular cytotoxicity (ADCC) are unknown, we determined the 25-OH-D3 serum levels associated with maximum NK cell-mediated ADCC. CD20 antibody-loaded CD20+ B-cell lymphoma cell lines were cultured with NK cells and ADCC activity was determined by lactate dehydrogenase release assays. Using a newly developed formula, pre-defined 25-OH-D3 serum levels were achieved with high individual precision over a wide range. NK cells from 20 healthy individuals killed antibody-treated CD20+ lymphoma cells in a concentration- and E:T ratio-dependent manner with obinutuzumab displaying a stronger ADCC activity than rituximab. Maximum NK-cell activity and ADCC were observed at 65 ng/ml 25-OH-D3, the middle of the normal range (30-100 ng/ml). 25-OH-D3 serum levels around this range should be the target in interventional trials aiming at improving NK cell-mediated ADCC by 25-OH-D3 substitution. Lower levels do not provide significant ADCC improvements in individuals with 25-OH-D3 deficiency or insufficiency and might result in the failure of interventions with 25-OH-D3.