Determination of patulin in fruit juices using HPLC-DAD and GC-MSD techniques

A high performance liquid chromatography with a diode-array detector (HPLC-DAD) and a gas chromatography with a mass spectrometer (GC-MSD) are described for the determination of patulin (PAT) in apple juice. The limits of detection (DL) and quantification (QL) for the HPLC-DAD and GC-MSD method were found to be (DL = 0.23 μg kg⁻¹ QL = 1.2 μg kg⁻¹) and (DL = 5.8 μg kg⁻¹ and QL = 13.8 μg kg⁻¹), respectively. The recovery factors for HPLC-DAD and GC-MSD were found to be 99.5% (RSD% = 0.73) and 41% (RSD% = 10.03), respectively. The HPLC-DAD method was used to determine the occurrence of PAT in 90 samples of fruit juices.     

Conversational natural language understanding interfacing city event information

The article describes aspects of the development of a conversational natural language understanding (NLU) system done during the first year of the European research project CATCH-2004 (Converse in AThens Cologne and Helsinki) [http://www.catch2004.org]. The project is co-funded by the European Union in the scope of the IST programme (IST 1999-11103).

Its objectives focus on multi-modal, multi-lingual conversational natural language access to information systems. The paper emphasises on architecture, and telephony-based speech and NLU components as well as aspects of the implementation of a city event information (CEI) system in English, Finnish, German and Greek. The CEI system accesses two different databases in Athens and Helsinki using a common retrieval interface. Furthermore the paper singles out methodologies involved for acoustic and language model of the speech recognition component, parsing techniques and dialog modelling for the conversational natural language subsystem. For the implementation it outlines an incremental system refinement methodology necessary to adapt the system components to real-life data. It addresses the implementation of language specific characteristics and a common dialog design for all four languages, but also deals with aspects towards a multilingual conversational system. Finally, it presents prospects for further developments of the project.     

Design, Analysis and Performance Evaluation of Group Key Establishment in Wireless Sensor Networks

Wireless sensor networks are comprised of a vast number of ultra-small autonomous computing, communication and sensing devices, with restricted energy and computing capabilities, that co-operate to accomplish a large sensing task. Such networks can be very useful in practice, e.g. in the local monitoring of ambient conditions and reporting them to a control center. In this paper we propose a new lightweight, distributed group key establishment protocol suitable for such energy constrained networks. Our approach basically trade-offs complex message exchanges by performing some amount of additional local computations. The extra computations are simple for the devices to implement and are evenly distributed across the participants of the network leading to good energy balance. We evaluate the performance our protocol in comparison to existing group key establishment protocols both in simulated and real environments. The intractability of all protocols is based on the Diffie-Hellman problem and we used its elliptic curve analog in our experiments. Our findings basically indicate the feasibility of implementing our protocol in real sensor network devices and highlight the advantages and disadvantages of each approach given the available technology and the corresponding efficiency (energy, time) criteria.     

Simulations reveal that different responses to cell crowding determine the expansion of p53 and Notch mutant clones in squamous epithelia

During ageing, normal epithelial tissues progressively accumulate clones carrying mutations that increase mutant cell fitness above that of wild-type cells. Such mutants spread widely through the tissues, yet despite this cellular homeostasis and functional integrity of the epithelia are maintained. Two of the genes most commonly mutated in human skin and oesophagus are p53 and Notch1, both of which are also recurrently mutated in cancers of these tissues. From observations taken in human and mouse epithelia, we find that clones carrying p53 and Notch pathway mutations have different clone dynamics which can be explained by their different responses to local cell crowding. p53 mutant clone growth in mouse epidermis approximates a logistic curve, but feedbacks responding to local crowding are required to maintain tissue homeostasis. We go on to show that the observed ability of Notch pathway mutant cells to displace the wild-type population in the mouse oesophageal epithelium reflects a local density feedback that affects both mutant and wild-type cells equally. We then show how these distinct feedbacks are consistent with the distribution of mutations observed in human datasets and are suggestive of a putative mechanism to constrain these cancer-associated mutants.     

Selective methanation of CO over supported Ru catalysts

The catalytic performance of supported ruthenium catalysts for the selective methanation of CO in the presence of excess CO₂ has been investigated with respect to the loading (0.5–5.0 wt.%) and mean crystallite size (1.3–13.6 nm) of the metallic phase as well as with respect to the nature of the support (Al₂O₃, TiO₂, YSZ, CeO₂ and SiO₂). Experiments were conducted in the temperature range of 170–470 °C using a feed composition consisting of 1%CO, 50% H₂ 15% CO₂ and 0–30% H₂O (balance He). It has been found that, for all catalysts investigated, conversion of CO₂ is completely suppressed until conversion of CO reaches its maximum value. Selectivity toward methane, which is typically higher than 70%, increases with increasing temperature and becomes 100% when the CO₂ methanation reaction is initiated. Increasing metal loading results in a significant shift of the CO conversion curve toward lower temperatures, where the undesired reverse water–gas shift reaction becomes less significant. Results of kinetic measurements show that CO/CO₂ hydrogenation reactions over Ru catalysts are structure sensitive, i.e., the reaction rate per surface metal atom (turnover frequency, TOF) depends on metal crystallite size. In particular, for Ru/TiO₂ catalysts, TOFs of both CO (at 215 °C) and CO₂ (at 330 °C) increase by a factor of 40 and 25, respectively, with increasing mean crystallite size of Ru from 2.1 to 4.5 nm, which is accompanied by an increase of selectivity to methane. Qualitatively similar results were obtained from Ru catalysts supported on Al₂O₃. Experiments conducted with the use of Ru catalyst of the same metal loading (5 wt.%) and comparable crystallite size show that the nature of the metal oxide support affects significantly catalytic performance. In particular, the turnover frequency of CO is 1–2 orders of magnitude higher when Ru is supported on TiO₂, compared to YSZ or SiO₂, whereas CeO₂- and Al₂O₃-supported catalysts exhibit intermediate performance. Optimal results were obtained over the 5%Ru/TiO₂ catalyst, which is able to completely and selectively convert CO at temperatures around 230 °C. Addition of water vapor in the feed does not affect CO hydrogenation but shifts the CO₂ conversion curve toward higher temperatures, thereby further improving the performance of this catalyst for the title reaction. In addition, long-term stability tests conducted under realistic reaction conditions show that the 5%Ru/TiO₂ catalyst is very stable and, therefore, is a promising candidate for use in the selective methanation of CO for fuel cell applications.     

Detection of chromosomal and plasmid--encoded virulence determinants in Yersinia enterocolitica and other Yersinia spp. isolated from food animals in Greece

The distribution of Yersinia strains in animal reservoirs was examined in 835 food animals (pigs, chickens, sheep, cows) from different Greek departments (Attica, Fthiotida, Viotia and Evia) over a one year period. The isolated strains were characterized with respect to the presence of chromosomal (yst) and plasmid-encoded virulence determinants (virF, yadA) and their antimicrobial susceptibility was tested.In total, Yersiniaspp. were obtained from 9.94% of the 835 food animals at slaughter that were sampled in this study. There was no statistically significant seasonal distribution, nor was any significant departmental distribution observed. From the 83 isolated Yersinia strains, 76 (91,57%) belonged to Y. enterocolitica (58 were of serotype O:3/biotype 4 and 18 strains were non O:3, non O:9), 3 belonged to Y. pseudotuberculosis, 2 to Y. kristensenii and 2 to Y. intermedia. Y. enterocolitica O:3/4 was mainly isolated from the pigs, while Y. enterocolitica non O:3, non O:9 was from the chickens. The strains were grouped into 5 genotypes, with respect to the presence or absence of the virulence genes. A significant predominance of genotype V, the one carrying all the three virulence genes, was observed in the strains isolated from the pigs. Complete susceptibility to most of the 3rd and to the 4th generation cephalosporins and to ciprofloxacin, was observed among the isolates. Remarkable was the association between the presence of each virulence gene separately and resistance to some antimicrobials, a matter of further investigation.     

Potentially toxigenic fungi from selected grains and grain products

A total of 85 grain and grain product samples (including corn meal, corn muffin mix, popcorn, various types of rice, and self‐rising, all‐purpose unbleached and whole wheat flour) from U.S. retail were tested for fungal contamination levels and profiles using conventional plating as well as molecular methods. The results of this study showed that over 90% of wheat flour and corn product samples and 73% of rice samples tested carried live fungi. Popcorn carried the highest fungal levels reaching 5.45 log₁₀ colony forming units (cfu) per gram followed by corn meal (reaching 5.38 log₁₀ cfu/g). Mold and yeast counts in rice and wheat flour reached 3.30 log₁₀ and 3.28 log₁₀ cfu/g, respectively. The predominant molds in wheat flour were aspergilli and fusaria found in 50 and 46% of samples, respectively; Fusarium spp. were the most frequent contaminants of corn‐based products found in 74% of the samples followed by penicillia (present in 44% of tested samples). Rice, conversely, contained mainly Aspergillus, Fusarium, and yeasts (each found in 21% of the samples).

Practical applications

Toxigenic molds are often contaminating stored grains and grain products and under improper storage conditions could cause spoilage of these commodities accompanied with production of toxic secondary metabolites, mycotoxins. Mycotoxins are known to cause illnesses in humans and animals. Therefore, monitoring the presence and inhibiting the growth of these organisms is critical for achieving and maintaining high quality products, suitable for human and animal consumption, and free of health hazards. Establishing toxigenic mold profiles in stored grains and their derivatives can point to correct storage management and thus reduction/elimination of spoilage and mycotoxin production in these products. In this study we tested several corn, rice, and wheat flour commodities for live potentially toxigenic fungal species. Our findings can help select proper storage management techniques for these commodities.     

Outcome Prediction in Critically-Ill Patients with Venous Thromboembolism and/or Cancer Using Machine Learning Algorithms: External Validation and Comparison with Scoring Systems

Intensive care unit (ICU) patients with venous thromboembolism (VTE) and/or cancer suffer from high mortality rates. Mortality prediction in the ICU has been a major medical challenge for which several scoring systems exist but lack in specificity. This study focuses on two target groups, namely patients with thrombosis or cancer. The main goal is to develop and validate interpretable machine learning (ML) models to predict early and late mortality, while exploiting all available data stored in the medical record. To this end, retrospective data from two freely accessible databases, MIMIC-III and eICU, were used. Well-established ML algorithms were implemented utilizing automated and purposely built ML frameworks for addressing class imbalance. Prediction of early mortality showed excellent performance in both disease categories, in terms of the area under the receiver operating characteristic curve (AUC–ROC): VTE-MIMIC-III 0.93, eICU 0.87, cancer-MIMIC-III 0.94. On the other hand, late mortality prediction showed lower performance, i.e., AUC–ROC: VTE 0.82, cancer 0.74–0.88. The predictive model of early mortality developed from 1651 VTE patients (MIMIC-III) ended up with a signature of 35 features and was externally validated in 2659 patients from the eICU dataset. Our model outperformed traditional scoring systems in predicting early as well as late mortality. Novel biomarkers, such as red cell distribution width, were identified.