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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6
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Publication Open Access Virulence determinants of colistin-resistant K. pneumoniae high-risk clones(Multidisciplinary Digital Publishing Institute (MDPI), 2021) Department of Industrial Engineering; Ergönül, Önder; Gönen, Mehmet; Can, Füsun; Doğan, Özlem; Vatansever, Cansel; Ataç, Nazlı; Albayrak, Özgür; Karahüseyinoğlu, Serçin; Şahin, Özgün Ekin; Kılıçoğlu, Bilge Kaan; Demiray, Atalay; Faculty Member; Faculty Member; Faculty Member; Faculty Member; Undergraduate Student; Researcher; Faculty Member; Master Student; Department of Industrial Engineering; School of Medicine; Graduate School of Health Sciences; College of Engineering; 110398; 237468; 103165; 170418; N/A; N/A; N/A; 110772; N/A; N/A; N/AWe proposed the hypothesis that high-risk clones of colistin-resistant K. pneumoniae (ColR-Kp) possesses a high number of virulence factors and has enhanced survival capacity against the neutrophil activity. We studied virulence genes of ColR-Kp isolates and neutrophil response in 142 patients with invasive ColR-Kp infections. The ST101 and ST395 ColR-Kp infections had higher 30-day mortality (58%, p = 0.005 and 75%, p = 0.003). The presence of yersiniabactin biosynthesis gene (ybtS) and ferric uptake operon associated gene (kfu) were significantly higher in ST101 (99%, p <= 0.001) and ST395 (94%, p < 0.012). Being in ICU (OR: 7.9; CI: 1.43-55.98; p = 0.024), kfu (OR:27.0; CI: 5.67-179.65; p < 0.001) and ST101 (OR: 17.2; CI: 2.45-350.40; p = 0.01) were found to be predictors of 30-day mortality. Even the neutrophil uptake of kfu+-ybtS+ ColR-Kp was significantly higher than kfu--ybtS- ColR-Kp (phagocytosis rate: 78% vs. 65%, p < 0.001), and the kfu+-ybtS+ ColR-Kp survived more than kfu--ybtS- ColR-Kp (median survival index: 7.90 vs. 4.22; p = 0.001). The kfu+-ybtS+ ColR-Kp stimulated excessive NET formation. Iron uptake systems in high-risk clones of colistin-resistant K. pneumoniae enhance the success of survival against the neutrophil phagocytic defense and stimulate excessive NET formation. The drugs targeted to iron uptake systems would be a promising approach for the treatment of colistin-resistant high-risk clones of K. pneumoniae infections.Publication Open Access Modelling and analysis of the impact of correlated inter-event data on production control using Markovian arrival processes(Springer, 2019) Department of Business Administration; Department of Industrial Engineering; N/A; Tan, Barış; Dizbin, Nima Manafzadeh; Faculty Member; Department of Business Administration; Department of Industrial Engineering; College of Administrative Sciences and Economics; College of Engineering; Graduate School of Business; 28600; N/AEmpirical studies show that the inter-event times of a production system are correlated. However, most of the analytical studies for the analysis and control of production systems ignore correlation. In this study, we show that real-time data collected from a manufacturing system can be used to build a Markovian arrival processes (MAP) model that captures correlation in inter-event times. The obtained MAP model can then be used to control production in an effective way. We first present a comprehensive review on MAP modeling and MAP fitting methods applicable to manufacturing systems. Then we present results on the effectiveness of these fitting methods and discuss how the collected inter-event data can be used to represent the flow dynamics of a production system accurately. In order to study the impact of capturing the flow dynamics accurately on the performance of a production control system, we analyze a manufacturing system that is controlled by using a base-stock policy. We study the impact of correlation in inter-event times on the optimal base-stock level of the system numerically by employing the structural properties of the MAP. We show that ignoring correlated arrival or service process can lead to overestimation of the optimal base-stock level for negatively correlated processes, and underestimation for the positively correlated processes. We conclude that MAPs can be used to develop data-driven models and control manufacturing systems more effectively by using shop-floor inter-event data.Publication Open Access The state-dependent M/G/1 queue with orbit(Springer, 2018) Baron, Opher; Economou, Antonis; Department of Industrial Engineering; Manou, Athanasia; Faculty Member; Department of Industrial Engineering; College of EngineeringWe consider a state-dependent single-server queue with orbit. This is a versatile model for the study of service systems, where the server needs a non-negligible time to retrieve waiting customers every time he completes a service. This situation arises typically when the customers are not physically present at a system, but they have a remote access to it, as in a call center station, a communication node, etc. We introduce a probabilistic approach for the performance evaluation of this queueing system, that we refer to as the queueing and Markov chain decomposition approach. Moreover, we discuss the applicability of this approach for the performance evaluation of other non-Markovian service systems with state dependencies.Publication Open Access Discovery of a small molecule that selectively destabilizes Cryptochrome 1 and enhances life span in p53 knockout mice(Nature Portfolio, 2022) Akyel, Yasemin Kübra; Korkmaz, Tuba; Selvi, Saba; Danış, İbrahim; İpek, Özgecan Savluğ; Aygenli, Fatih; Öztürk, Nuri; Öztürk, Narin; Ünal, Durişehvar Özer; Güzel, Mustafa; Okyar, Alper; N/A; Department of Chemical and Biological Engineering; Department of Industrial Engineering; Gül, Şeref; Gül, Zeynep Melis; Işın, Şafak; Özcan, Onur; Akarlar, Büşra; Taşkın, Ali Cihan; Türkay, Metin; Kavaklı, İbrahim Halil; Researcher; Other; Faculty Member; Faculty Member; Faculty Member; Department of Chemical and Biological Engineering; Department of Industrial Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); College of Engineering; N/A; N/A; N/A; N/A; N/A; 291296; 105301; 24956; 40319Cryptochromes are negative transcriptional regulators of the circadian clock in mammals. It is not clear how reducing the level of endogenous CRY1 in mammals will affect circadian rhythm and the relation of such a decrease with apoptosis. Here, we discovered a molecule (M47) that destabilizes Cryptochrome 1 (CRY1) both in vitro and in vivo. The M47 selectively enhanced the degradation rate of CRY1 by increasing its ubiquitination and resulted in increasing the circadian period length of U2OS Bmal1-dLuc cells. In addition, subcellular fractionation studies from mice liver indicated that M47 increased degradation of the CRY1 in the nucleus. Furthermore, M47-mediated CRY1 reduction enhanced oxaliplatin-induced apoptosis in Ras-transformed p53 null fibroblast cells. Systemic repetitive administration of M47 increased the median lifespan of p53(-/-) mice by similar to 25%. Collectively our data suggest that M47 is a promising molecule to treat forms of cancer depending on the p53 mutation.Publication Open Access An efficient framework to identify key miRNA-mRNA regulatory modules in cancer(Oxford University Press (OUP), 2020) N/A; Department of Industrial Engineering; Mokhtaridoost, Milad; Gönen, Mehmet; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; School of MedicineMotivation: micro-RNAs (miRNAs) are known as the important components of RNA silencing and post-transcriptional gene regulation, and they interact with messenger RNAs (mRNAs) either by degradation or by translational repression. miRNA alterations have a significant impact on the formation and progression of human cancers. Accordingly, it is important to establish computational methods with high predictive performance to identify cancer-specific miRNA-mRNA regulatory modules. Results: we presented a two-step framework to model miRNA-mRNA relationships and identify cancer-specific modules between miRNAs and mRNAs from their matched expression profiles of more than 9000 primary tumors. We first estimated the regulatory matrix between miRNA and mRNA expression profiles by solving multiple linear programming problems. We then formulated a unified regularized factor regression (RFR) model that simultaneously estimates the effective number of modules (i.e. latent factors) and extracts modules by decomposing regulatory matrix into two low-rank matrices. Our RFR model groups correlated miRNAs together and correlated mRNAs together, and also controls sparsity levels of both matrices. These attributes lead to interpretable results with high predictive performance. We applied our method on a very comprehensive data collection by including 32 TCGA cancer types. To find the biological relevance of our approach, we performed functional gene set enrichment and survival analyses. A large portion of the identified modules are significantly enriched in Hallmark, PID and KEGG pathways/gene sets. To validate the identified modules, we also performed literature validation as well as validation using experimentally supportedmiRTarBase database.Publication Open Access Modeling and analysis of an auction-based logistics market(Elsevier, 2008) Ağralı, Semra; Department of Business Administration; Department of Industrial Engineering; Tan, Barış; Karaesmen, Fikri; Faculty Member; Faculty Member; Department of Business Administration; Department of Industrial Engineering; College of Administrative Sciences and Economics; College of Engineering; 28600; 3579We consider a logistics spot market where the transportation orders from a number of firms are matched with two types of carriers through a reverse auction. In the spot market, local carriers compete with in-transit carriers that have lower costs. In order to analyze the effects of implementing a logistics spot market on these three parties: firms, local carriers, and in-transit carriers and also the effects of various system parameters, we develop a two-stage stochastic model. We first model the auction in a static setting and determine the expected auction price based on the number of carriers engaging in the auction and their cost distributions. We then develop a continuous-time Markov chain model to evaluate the performance of the system in a dynamic setting with random arrivals and possible abandonment of orders and carriers. By combining these two models, we evaluate the performance measures such as the expected auction price, price paid to the carriers, distribution of orders between local and in-transit carriers, and expected number of carriers and orders waiting at the logistics center in the long run. We present analytical and computational results related to the performance of the system and discuss operation of such a logistics spot market in Turkey.Publication Open Access Rapid molecular detection of gastrointestinal pathogens and its role in antimicrobial stewardship(American Society for Microbiology, 2018) Keske, Şiran; Palaoğlu, Erhan; N/A; Department of Industrial Engineering; Zabun, Burak; Aksoy, Kahraman; Can, Füsun; Ergönül, Önder; Faculty Member; Faculty Member; Department of Industrial Engineering; School of Medicine; N/A; N/A; N/A; 110398We aimed to detect the etiological agents of acute diarrhea by a molecular gastrointestinal pathogen test (MGPT) and to assess the impact of MGPT on antimicrobial stewardship programs (ASP). This is a prospective observational study and was conducted between 1 January 2015 and 30 June 2017. We included consequent patients who had acute diarrhea. At the end of 2015, we implemented ASP in acute diarrhea cases and compared the outcomes in the pre-ASP and post-ASP periods. An FDA-cleared multiplexed gastrointestinal PCR panel system, the BioFire FilmArray (Idaho Technology, Salt Lake City, UT), which detects 20 pathogens in stool, was used. In 499 out of 699 patients (71%), at least one pathogen was detected. Among 314 adults with positive MGPT, 101 (32%) enteropathogenic Escherichia coli (EPEC), 71 (23%) enteroaggregative E. coli (EAEC), 68 (22%) enterotoxigenic E. coli (ETEC), 55 (18%) Shiga toxin-producing E. coli (STEC) (17%) Norovirus, 48 (15%) Campylobacter, 21 (7%) Salmonella, and 20 (6%) Clostridium difficile strains were detected. Among 185 children, 55 (30%) EPEC, 37 (20%) C. difficile, 32 (17%) Norovirus, 29 (16%) EAEC, 22 (12%) STEC, 21 (11%) ETEC, 21 (11%) Campylobacter, 20 (11%) Salmonella, and 16 (5%) Rotavirus strains were detected. Inappropriate antibiotic use decreased in the post-ASP period compared with the pre-ASP period among inpatients (42.9% and 25.8%, respectively; P = 0.023). Using MGPT in clinical practice significantly decreased the unnecessary use of antibiotics. Detection of high rates of C. difficile in children and Salmonella spp., as well as relatively high rates of Campylobacter spp., which were hard to isolate by routine stool culture, were remarkable.Publication Open Access A hierarchical solution approach for a multicommodity distribution problem under a special cost structure(Elsevier, 2012) Koca, Esra; Department of Industrial Engineering; Yıldırım, Emre Alper; Faculty Member; Department of Industrial Engineering; College of EngineeringMotivated by the spare parts distribution system of a major automotive manufacturer in Turkey, we consider a multicommodity distribution problem from a central depot to a number of geographically dispersed demand points. The distribution of the items is carried out by a set of identical vehicles. The demand of each demand point can be satisfied by several vehicles and a single vehicle is allowed to serve multiple demand points. For a given vehicle, the cost structure is dictated by the farthest demand point from the depot among all demand points served by that vehicle. The objective is to satisfy the demand of each demand point with the minimum total distribution cost. We present a novel integer linear programming formulation of the problem as a variant of the network design problem. The resulting optimization problem becomes computationally infeasible for real-life problems due to the large number of integer variables. In an attempt to circumvent this disadvantage of using the direct formulation especially for larger problems, we propose a Hierarchical Approach that is aimed at solving the problem in two stages using partial demand aggregation followed by a disaggregation scheme. We study the properties of the solution returned by the Hierarchical Approach. We perform computational studies on a data set adapted from a major automotive manufacturer in Turkey. Our results reveal that the Hierarchical Approach significantly outperforms the direct formulation approach in terms of both the running time and the quality of the resulting solution especially on large instances.Publication Open Access AUC maximization in Bayesian hierarchical models(IOS Press, 2016) Department of Industrial Engineering; Gönen, Mehmet; Faculty Member; Department of Industrial Engineering; College of Engineering; 237468The area under the curve (AUC) measures such as the area under the receiver operating characteristics curve (AUROC) and the area under the precision-recall curve (AUPR) are known to be more appropriate than the error rate, especially, for imbalanced data sets. There are several algorithms to optimize AUC measures instead of minimizing the error rate. However, this idea has not been fully exploited in Bayesian hierarchical models owing to the difficulties in inference. Here, we formulate a general Bayesian inference framework, called Bayesian AUC Maximization (BAM), to integrate AUC maximization into Bayesian hierarchical models by borrowing the pairwise and listwise ranking ideas from the information retrieval literature. To showcase our BAM framework, we develop two Bayesian linear classifier variants for two ranking approaches and derive their variational inference procedures. We perform validation experiments on four biomedical data sets to demonstrate the better predictive performance of our framework over its error-minimizing counterpart in terms of average AUROC and AUPR values.Publication Open Access Structural properties of a class of robust inventory and queueing control problems(Wiley, 2018) Department of Industrial Engineering; N/A; Örmeci, Lerzan; Karaesmen, Fikri; Faculty Member; Faculty Member; Department of Industrial Engineering; College of Engineering; Graduate School of Sciences and Engineering; 32863; 3579; N/AIn standard stochastic dynamic programming, the transition probability distributions of the underlying Markov Chains are assumed to be known with certainty. We focus on the case where the transition probabilities or other input data are uncertain. Robust dynamic programming addresses this problem by defining a min-max game between Nature and the controller. Considering examples from inventory and queueing control, we examine the structure of the optimal policy in such robust dynamic programs when event probabilities are uncertain. We identify the cases where certain monotonicity results still hold and the form of the optimal policy is determined by a threshold. We also investigate the marginal value of time and the case of uncertain rewards.