The pseudo GTPase CENP-M drives human kinetochore assembly

Basilico, Federica et al.Kinetochores, multi-subunit complexes that assemble at the interface with centromeres, bind spindle microtubules to ensure faithful delivery of chromosomes during cell division. The configuration and function of the kinetochore–centromere interface is poorly understood. We report that a protein at this interface, CENP-M, is structurally and evolutionarily related to small GTPases but is incapable of GTP-binding and conformational switching. We show that CENP-M is crucially required for the assembly and stability of a tetramer also comprising CENP-I, CENP-H, and CENP-K, the HIKM complex, which we extensively characterize through a combination of structural, biochemical, and cell biological approaches. A point mutant affecting the CENP-M/CENP-I interaction hampers kinetochore assembly and chromosome alignment and prevents kinetochore recruitment of the CENP-T/W complex, questioning a role of CENP-T/W as founder of an independent axis of kinetochore assembly. Our studies identify a single pathway having CENP-C as founder, and CENP-H/I/K/M and CENP-T/W as CENP-C-dependent followers.AM acknowledges funding by the European Union's 7th Framework Program ERC agreement KINCON and the Integrated Project MitoSys. FH is supported by the Bavarian Research Center of Molecular Biosystems and by a LMU excellent junior grant.Peer reviewe

COMET: A Recipe for Learning and Using Large Ensembles on Massive Data

COMET is a single-pass MapReduce algorithm for learning on large-scale data. It builds multiple random forest ensembles on distributed blocks of data and merges them into a mega-ensemble. This approach is appropriate when learning from massive-scale data that is too large to fit on a single machine. To get the best accuracy, IVoting should be used instead of bagging to generate the training subset for each decision tree in the random forest. Experiments with two large datasets (5GB and 50GB compressed) show that COMET compares favorably (in both accuracy and training time) to learning on a subsample of data using a serial algorithm. Finally, we propose a new Gaussian approach for lazy ensemble evaluation which dynamically decides how many ensemble members to evaluate per data point; this can reduce evaluation cost by 100X or more

Security Games for Node Localization through Verifiable Multilateration

Most applications of wireless sensor networks (WSNs) rely on data about the positions of sensor nodes, which are not necessarily known beforehand. Several localization approaches have been proposed but most of them omit to consider that WSNs could be deployed in adversarial settings, where hostile nodes under the control of an attacker coexist with faithful ones. Verifiable multilateration (VM) was proposed to cope with this problem by leveraging on a set of trusted landmark nodes that act as verifiers. Although VM is able to recognize reliable localization measures, it allows for regions of undecided positions that can amount to the 40 percent of the monitored area. We studied the properties of VM as a noncooperative two-player game where the first player employs a number of verifiers to do VM computations and the second player controls a malicious node. The verifiers aim at securely localizing malicious nodes, while malicious nodes strive to masquerade as unknown and to pretend false positions. Thanks to game theory, the potentialities of VM are analyzed with the aim of improving the defender's strategy. We found that the best placement for verifiers is an equilateral triangle with edge equal to the power range R, and maximum deception in the undecided region is approximately 0.27R. Moreover, we characterized-in terms of the probability of choosing an unknown node to examine further-the strategies of the players

Workshop on Learning and Evaluating Recommendations with Impressions (LERI)

Recommender systems typically rely on past user interactions as the primary source of information for making predictions. However, although highly informative, past user interactions are strongly biased. Impressions, on the other hand, are a new source of information that indicate the items displayed on screen when the user interacted (or not) with them, and have the potential to impact the field of recommender systems in several ways. Early research on impressions was constrained by the limited availability of public datasets, but this is rapidly changing and, as a consequence, interest in impressions has increased. Impressions present new research questions and opportunities, but also bring new challenges. Several works propose to use impressions as part of recommender models in various ways and discuss their information content. Others explore their potential in off-policy-estimation and reinforcement learning. Overall, the interest of the community is growing, but efforts in this direction remain disconnected. Therefore, we believe that a workshop would be useful in bringing the community together

Targeting the MET oncogene by concomitant inhibition of receptor and ligand via an antibody-“decoy” strategy

MET, a master gene sustaining "invasive growth," is a relevant target for cancer precision therapy. In the vast majority of tumors, wild-type MET behaves as a "stress-response" gene and relies on the ligand (HGF) to sustain cell "scattering," invasive growth and apoptosis protection (oncogene "expedience"). In this context, concomitant targeting of MET and HGF could be crucial to reach effective inhibition. To test this hypothesis, we combined an anti-MET antibody (MvDN30) inducing "shedding" (i.e., removal of MET from the cell surface), with a "decoy" (i.e., the soluble extracellular domain of the MET receptor) endowed with HGF-sequestering ability. To avoid antibody/decoy interaction-and subsequent neutralization-we identified a single aminoacid in the extracellular domain of MET-lysine 842-that is critical for MvDN30 binding and engineered the corresponding recombinant decoyMET (K842E). DecoyMET(K842E) retains the ability to bind HGF with high affinity and inhibits HGF-induced MET phosphorylation. In HGF-dependent cellular models, MvDN30 antibody and decoyMET(K842E) used in combination cooperate in restraining invasive growth, and synergize in blocking cancer cell "scattering." The antibody and the decoy unbridle apoptosis of colon cancer stem cells grown in vitro as spheroids. In a preclinical model, built by orthotopic transplantation of a human pancreatic carcinoma in SCID mice engineered to express human HGF, concomitant treatment with antibody and decoy significantly reduces metastatic spread. The data reported indicate that vertical targeting of the MET/HGF axis results in powerful inhibition of ligand-dependent MET activation, providing proof of concept in favor of combined target therapy of MET "expedience.

Effect of hypoxia on gene expression in cell populations involved in wound healing

Wound healing is a complex process regulated by multiple signals and consisting of several phases known as haemostasis, inflammation, proliferation, and remodelling. Keratinocytes, endothelial cells, macrophages, and fibroblasts are the major cell populations involved in wound healing process. Hypoxia plays a critical role in this process since cells sense and respond to hypoxic conditions by changing gene expression. This study assessed the in vitro expression of 77 genes involved in angiogenesis, metabolism, cell growth, proliferation and apoptosis in human keratinocytes (HaCaT), microvascular endothelial cells (HMEC-1), differentiated macrophages (THP-1), and dermal fibroblasts (HDF). Results indicated that the gene expression profiles induced by hypoxia were cell-type specific. In HMEC-1 and differentiated THP-1, most of the genes modulated by hypoxia encode proteins involved in angiogenesis or belonging to cytokines and growth factors. In HaCaT and HDF, hypoxia mainly affected the expression of genes encoding proteins involved in cell metabolism. This work can help to enlarge the current knowledge about the mechanisms through which a hypoxic environment influences wound healing processes at the molecular level

From pre-and probiotics to post-biotics: A narrative review

Background and aims: Gut microbiota (GM) is a complex ecosystem containing bacteria, viruses, fungi, and yeasts. It has several functions in the human body ranging from immunomodulation to metabolic. GM derangement is called dysbiosis and is involved in several host diseases. Pre-, probiotics, and symbiotics (PRE-PRO-SYMB) have been extensively developed and studied for GM re-modulation. Herein, we review the literature data regarding the new concept of postbiotics, starting from PRE-PRO-SYMB. Methods: We conducted a search on the main medical databases for original articles, reviews, meta-analyses, randomized clinical trials, and case series using the following keywords and acronyms and their associations: Gut microbiota, prebiotics, probiotics, symbiotic, and postbiotics. Results: Postbiotics account for PRO components and metabolic products able to beneficially affect host health and GM. The deeper the knowledge about them, the greater their possible uses: The prevention and treatment of atopic, respiratory tract, and inflammatory bowel diseases. Conclusions: Better knowledge about postbiotics can be useful for the prevention and treatment of several human body diseases, alone or as an add-on to PRE-PRO-SYMB

Supplementary data for the article: Konstantinović, J.; Videnović, M.; Orsini, S.; Bogojević, K.; D’Alessandro, S.; Scaccabarozzi, D.; Terzić Jovanović, N.; Gradoni, L.; Basilico, N.; Šolaja, B. A. Novel Aminoquinoline Derivatives Significantly Reduce Parasite Load in Leishmania Infantum Infected Mice. ACS Medicinal Chemistry Letters 2018, 9 (7), 629–634. https://doi.org/10.1021/acsmedchemlett.8b00053

Supplementary material for: [https://pubs.acs.org/doi/10.1021/acsmedchemlett.8b00053]Related to published version: [http://cherry.chem.bg.ac.rs/handle/123456789/2209]Related to accepted version: [http://cherry.chem.bg.ac.rs/handle/123456789/2948