The Antibacterial Drug Candidate SBC3 is a Potent Inhibitor of Bacterial Thioredoxin Reductase

Antibiotic resistance is a growing problem for public health and associated with increasing economic costs and mortality rates. Silver and silver-related compounds have been used for centuries due to their antimicrobial properties. In this work, we show that 1,3-dibenzyl-4,5-diphenyl-imidazol-2-ylidene silver(I) acetate/NHC*-Ag-OAc (SBC3) is a reversible, high affinity inhibitor of E. coli thioredoxin reductase (TrxR; K_i=10.8±1.2 nM). Minimal inhibition concentration (MIC) tests with different E. coli and P. aeruginosa strains demonstrated that SBC3 can efficiently inhibit bacterial cell growth, especially in combination with established antibiotics like gentamicin. Our results show that SBC3 is a promising antibiotic drug candidate targeting bacterial TrxR.     

Neurological complications of radiotherapy and chemotherapy

Neurological complications of radiotherapy and chemotherapy can affect the central or peripheral nervous system. Most are dose-dependent and constitute a limiting factor in the administration of treatments. Radiation-induced neurological complications are classified as acute, early-delayed or delayed. The most important are radionecrosis and cognitive dysfunction/leukoencephalopathy. Neurotoxicity of chemotherapy is frequent and depends upon dose, type of drugs (especially cisplatin and methotrexate) and their combination with radiotherapy.     

Estimation of fouling in a plate heat exchanger through the application of neural networks

Pasteurization is an important, if not the most important, process step in the packaging of milk. It is subject to alterations stemming from the variation in the temperature, pH and raw milk quality. The variability may manifest itself in changes in the formation of the deposit (fouling) in the pasteurization unit, such that there is a need for tools, both instrumentation and computational, to help in monitoring the process and keeping it on the desired course. In this paper we describe a practical procedure based on artificial neural networks (ANN) that allows prediction of the deposit thickness, the overall heat transfer coefficient and the critical time (the time that the unit has to be stopped for cleaning) for reducing the impact of fouling on such processes. The procedure determines when the cleaning operation is required once the system is under critical conditions of operations. A combination of fundamental studies and plant measurements were used for study of the operating conditions and thus evaluation of the trades‐offs between operating conditions and longer operating life span. The results are encouraging, enough to validate current operating industrial techniques. Copyright © 2005 Society of Chemical Industry     

New-onset psychogenic seizures after surgery for epilepsy

BACKGROUND: The emergence of psychogenic seizures after surgery for epilepsy is not well recognized. OBJECTIVES: To identify the frequency of psychogenic seizures in an 11-year surgical experience and to characterize the patients with this complication. METHODS: Ninety-six patients underwent surgery for epilepsy between 1985 and 1996. The surgical database was reviewed and all patients who experienced postoperative psychogenic seizures were identified. Patients were characterized by sex, age, psychopathologic conditions, full-scale IQ, duration of epilepsy, surgical procedure, and operative complications. Patients were compared with the surgical group as a whole for these variables. SETTING: A comprehensive epilepsy center. RESULTS: Five patients were identified: 3 men and 2 women. Mean full-scale IQ was 73 (range, 66-82). Mean age was 29.8 years (range, 22-36 years). Three patients were diagnosed as having psychosis, 1 with borderline personality disorder and 1 with generalized anxiety. Operations included 4 anterior temporal lobectomies and 1 occipital lobectomy. Two patients experienced operative complications. Compared with the surgical cohort, patients had a higher frequency of preoperative psychopathologic conditions, lower mean full-scale IQ, and a greater occurrence of operative complications. CONCLUSIONS: (1) Patients can develop new-onset psychogenic seizures after surgery for epilepsy. (2) Low full-scale IQ, serious preoperative psychopathologic conditions, and major surgical complications may be risk factors. (3) Atypical postoperative seizures should be evaluated with video electroencephalographic monitoring before concluding that they are epileptic.     

A Survey of Optical Flow Techniques for Robotics Navigation Applications

Optical flow has been widely used by insects and birds to support navigation functions. Such information has appealing capabilities for application to ground and aerial robots, especially for navigation and collision avoidance in urban or indoor areas. The purpose of this paper is to provide a survey of existing optical flow techniques for robotics navigation applications. Detailed comparisons are made among different optical-flow-aided navigation solutions with emphasis on the sensor hardware as well as optical flow motion models. A summary of current research status and future research directions are further discussed.     

A comparative study of iterative and non-iterative feature selection techniques for software defect prediction

Two important problems which can affect the performance of classification models are high-dimensionality (an overabundance of independent features in the dataset) and imbalanced data (a skewed class distribution which creates at least one class with many fewer instances than other classes). To resolve these problems concurrently, we propose an iterative feature selection approach, which repeated applies data sampling (in order to address class imbalance) followed by feature selection (in order to address high-dimensionality), and finally we perform an aggregation step which combines the ranked feature lists from the separate iterations of sampling. This approach is designed to find a ranked feature list which is particularly effective on the more balanced dataset resulting from sampling while minimizing the risk of losing data through the sampling step and missing important features. To demonstrate this technique, we employ 18 different feature selection algorithms and Random Undersampling with two post-sampling class distributions. We also investigate the use of sampling and feature selection without the iterative step (e.g., using the ranked list from a single iteration, rather than combining the lists from multiple iterations), and compare these results from the version which uses iteration. Our study is carried out using three groups of datasets with different levels of class balance, all of which were collected from a real-world software system. All of our experiments use four different learners and one feature subset size. We find that our proposed iterative feature selection approach outperforms the non-iterative approach.     

Experiences with large-scale operational trials of ALTO-enhanced P2P filesharing in an intra-ISP scenario

Application Layer Traffic Optimization (ALTO) has recently gained attention in the research and standardisation community as a way for a network operator to guide the peer selection process of distributed applications by providing network layer topology information. In particular P2P applications are expected to gain from ALTO, due to the many connections peers form among each other, often without taking network layer topology information into account. In this paper, we present results of an extensive intra-ISP trial with an ALTO-enhanced P2P filesharing software. In summary, our results show that—depending on the concrete setting and on the distribution of upload capacity in the network—ALTO enables an ISP to save operational costs significantly while not degrading application layer performance noticeably. In addition, based on our experience we are able to give advice to operators on how to save costs with ALTO while not sacrificing application layer performance at all.