45 research outputs found

    Learning Credible Models

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    In many settings, it is important that a model be capable of providing reasons for its predictions (i.e., the model must be interpretable). However, the model's reasoning may not conform with well-established knowledge. In such cases, while interpretable, the model lacks \textit{credibility}. In this work, we formally define credibility in the linear setting and focus on techniques for learning models that are both accurate and credible. In particular, we propose a regularization penalty, expert yielded estimates (EYE), that incorporates expert knowledge about well-known relationships among covariates and the outcome of interest. We give both theoretical and empirical results comparing our proposed method to several other regularization techniques. Across a range of settings, experiments on both synthetic and real data show that models learned using the EYE penalty are significantly more credible than those learned using other penalties. Applied to a large-scale patient risk stratification task, our proposed technique results in a model whose top features overlap significantly with known clinical risk factors, while still achieving good predictive performance

    Putative histidine kinase inhibitors with antibacterial effect against multi-drug resistant clinical isolates identified by in vitro and in silico screens

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    Novel antibacterials are urgently needed to address the growing problem of bacterial resistance to conventional antibiotics. Two-component systems (TCS) are widely used by bacteria to regulate gene expression in response to various environmental stimuli and physiological stress and have been previously proposed as promising antibacterial targets. TCS consist of a sensor histidine kinase (HK) and an effector response regulator. The HK component contains a highly conserved ATP-binding site that is considered to be a promising target for broad-spectrum antibacterial drugs. Here, we describe the identification of putative HK autophosphorylation inhibitors following two independent experimental approaches: in vitro fragment-based screen via differential scanning fluorimetry and in silico structure-based screening, each followed up by the exploration of analogue compounds as identified by ligand-based similarity searches. Nine of the tested compounds showed antibacterial effect against multi-drug resistant clinical isolates of bacterial pathogens and include three novel scaffolds, which have not been explored so far in other antibacterial compounds. Overall, putative HK autophosphorylation inhibitors were found that together provide a promising starting point for further optimization as antibacterials

    Broadening the antibacterial spectrum of histidine kinase autophosphorylation inhibitors via the use of epsilon-poly-L-lysine capped mesoporous silica-based nanoparticles

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    [EN] Two-component systems (TCS) regulate diverse processes such as virulence, stress responses, metabolism and antibiotic resistance in bacteria but are absent in humans, making them promising targets for novel antibacterials. By incorporating recently described TCS histidine kinase autophosphorylation inhibitors (HKAIs) into epsilon-poly-L-lysine capped nanoparticles (NPs) we could overcome the Gram negative (Gr(-)) permeability barrier for the HKAIs. The observed bactericidal activity against Gr(-) bacteria was shown to be due to the enhanced delivery and internalization of the HKAIs and not an inhibitory or synergistic effect of the NPs. The NPs had no adverse effects on mammalian cell viability or the immune function of macrophages in vitro and showed no signs of toxicity to zebrafish larvae in vivo. These results show that HKAIs are promising antibacterials for both Gr(-) and Gr + pathogens and that NPs are a safe drug delivery technology that can enhance the selectivity and efficacy of HKAIs against bacteria. (C) 2016 Elsevier Inc. All rights reserved.This work was funded by FP7 ITN STARS-Scientific Training in Antimicrobial Research Strategies (Contract No. PITN-GA-2009-238490, J.M.W., A.M.), H2020 MSCA IF (AND-659121, N.V.), grant BIO2013-42619-P from the Ministerio de Economia y Competitividad (A.M.), grant from the Spanish Government (Project MAT2015-64139-C4-1-R,N. M., J.R.M, R.M.M.), and a grant from Generalitat Valenciana (Project PROMETEOII/2014/047, N.M.). and Prometeo II/2014/029, A.M.).Velikova, N.; Mas Font, N.; Miguel-Romero, L.; Polo, L.; Stolte, E.; Zaccaria, E.; Cao, R.... (2017). Broadening the antibacterial spectrum of histidine kinase autophosphorylation inhibitors via the use of epsilon-poly-L-lysine capped mesoporous silica-based nanoparticles. Nanomedicine Nanotechnology Biology and Medicine. 13(2):569-581. https://doi.org/10.1016/j.nano.2016.09.011S56958113

    Repurposing Hsp90 inhibitors as antimicrobials targeting two-component systems identifies compounds leading to loss of bacterial membrane integrity

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    19 páginas, 7 figuras, 2 tablasThe discovery of antimicrobials with novel mechanisms of action is crucial to tackle the foreseen global health crisis due to antimicrobial resistance. Bacterial two-component signaling systems (TCSs) are attractive targets for the discovery of novel antibacterial agents. TCS-encoding genes are found in all bacterial genomes and typically consist of a sensor histidine kinase (HK) and a response regulator. Due to the conserved Bergerat fold in the ATP-binding domain of the TCS HK and the human chaperone Hsp90, there has been much interest in repurposing inhibitors of Hsp90 as antibacterial compounds. In this study, we explore the chemical space of the known Hsp90 inhibitor scaffold 3,4-diphenylpyrazole (DPP), building on previous literature to further understand their potential for HK inhibition. Six DPP analogs inhibited HK autophosphorylation in vitro and had good antimicrobial activity against Gram-positive bacteria. However, mechanistic studies showed that their antimicrobial activity was related to damage of bacterial membranes. In addition, DPP analogs were cytotoxic to human embryonic kidney cell lines and induced the cell arrest phenotype shown for other Hsp90 inhibitors. We conclude that these DPP structures can be further optimized as specific disruptors of bacterial membranes providing binding to Hsp90 and cytotoxicity are lowered. Moreover, the X-ray crystal structure of resorcinol, a substructure of the DPP derivatives, bound to the HK CheA represents a promising starting point for the fragment-based design of novel HK inhibitors. Importance: The discovery of novel antimicrobials is of paramount importance in tackling the imminent global health crisis of antimicrobial resistance. The discovery of novel antimicrobials with novel mechanisms of actions, e.g., targeting bacterial two-component signaling systems, is crucial to bypass existing resistance mechanisms and stimulate pharmaceutical innovations. Here, we explore the possible repurposing of compounds developed in cancer research as inhibitors of two-component systems and investigate their off-target effects such as bacterial membrane disruption and toxicity. These results highlight compounds that are promising for further development of novel bacterial membrane disruptors and two-component system inhibitors.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement number 765147 and grants PID2019-108541GB-I00 from the Spanish Government (Ministry of Science and Innovation) and PROMETEO/2020/012 by the Valencian Government to A.M. We also thank the Utrecht Medical Centre (UMC) group from prof. Rob Willems for providing the enterococci.Peer reviewe

    Proceedings of Patient Reported Outcome Measure’s (PROMs) Conference Oxford 2017: Advances in Patient Reported Outcomes Research

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    A33-Effects of Out-of-Pocket (OOP) Payments and Financial Distress on Quality of Life (QoL) of People with Parkinson’s (PwP) and their Carer

    Automatische borstkankerdetectie

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    Contains fulltext : 83341.pdf (publisher's version ) (Open Access

    Software speurt naar borstkanker

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    A Probabilistic Logic-based Model for Fusing Attribute Information of Objects Under Surveillance

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    Contains fulltext : 103244.pdf (publisher's version ) (Open Access)15 p
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