Occurrence of pharmaceuticals in river water and their elimination in a pilot-scale drinking water treatment plant

The occurrence of four beta blockers, one antiepileptic drug, one lipid regulator, four anti-inflammatories, and three fluoroquinolones was studied in a river receiving sewage effluents. All compounds but two of the fluoroquinolones were observed in the water above their limit of quantification concentrations. The highest concentrations (up to 107 ng L(-1)) of the compounds were measured during the winter months. The river water was passed to a pilot-scale drinking water treatment plant, and the elimination of the pharmaceuticals was followed during the treatment. The processes applied by the plant consisted of ferric salt coagulation, rapid sand filtration, ozonation, two-stage granular activated carbon filtration (GAC), and UV disinfection. Following the coagulation, sedimentation, and rapid sand filtration, the studied pharmaceuticals were found to be eliminated only by an average of 13%. An efficient elimination was found to take place during ozonation at an ozone dose of about 1 mg L(-1) (i.e., 0.2-0.4 mg of O3/ mg of TOC). Following this treatment, the concentrations of the pharmaceuticals dropped to below the quantification limits with the exception of ciprofloxacin. Atenolol, sotalol, and ciprofloxacin, the most hydrophilic of the studied pharmaceuticals, were not fully eliminated during the GAC filtrations. All in all, the treatment train was found to very effectively eliminate the pharmaceuticals from the rawwater. The only compound that was found to pass almost unaffected through all the treatment steps was ciprofloxacin.     

CLONING OF A YEAST GENE WHICH CAUSES PHENOLIC OFF-FLAVOURS IN BEER

A gene (POF1) has been cloned, which confers upon yeast (Saccharomyces cerevisiae) the ability to decarboxylate phenolic acids such as ferulic and trans-cinnamic acid. This property was previously shown to be a cause of phenolic off-flavour production in wort fermentations. The identity of the cloned gene was confirmed as POF1 by gene disruption techniques. Southern blotting of total genomic DNA revealed that sequences homologous to POF1 are conserved in Pof^? brewing strains of Sacch. cerevisiae. The transformation of a Pof^? lager strain with the cloned POF1 gene led to the production of an aroma characteristic of a phenolic off-flavour, when the transformed strain was used in wort fermentations. This latter observation suggests that the Pof^? phenotype of brewers' yeast is specifically due to the absence of a functional POF1 gene.     

Algorithms for unimodal segmentation with applications to unimodality detection

We study the problem of segmenting a sequence into k pieces so that the resulting segmentation satisfies monotonicity or unimodality constraints. Unimodal functions can be used to model phenomena in which a measured variable first increases to a certain level and then decreases. We combine a well-known unimodal regression algorithm with a simple dynamic-programming approach to obtain an optimal quadratic-time algorithm for the problem of unimodal k-segmentation. In addition, we describe a more efficient greedy-merging heuristic that is experimentally shown to give solutions very close to the optimal. As a concrete application of our algorithms, we describe methods for testing if a sequence behaves unimodally or not. The methods include segmentation error comparisons, permutation testing, and a BIC-based scoring scheme. Our experimental evaluation shows that our algorithms and the proposed unimodality tests give very intuitive results, for both real-valued and binary data. Niina Haiminen received the M.Sc. degree from the University of Helsinki in 2004. She is currently a Graduate Student at the Department of Computer Science of University of Helsinki, and a Researcher at the Basic Research Unit of Helsinki Institute for Information Technology. Her research interests include algorithms, bioinformatics, and data mining. Aristides Gionis received the Ph.D. degree from Stanford University in 2003, and he is currently a Senior Researcher at the Basic Research Unit of Helsinki Institute for Information Technology. His research experience includes summer internship positions at Bell Labs, AT&T Labs, and Microsoft Research. His research areas are data mining, algorithms, and databases. Kari Laasonen received the M.Sc. degree in Theoretical Physics in 1995 from the University of Helsinki. He is currently a Graduate Student in Computer Science at the University of Helsinki and a Researcher at the Basic Research Unit of Helsinki Institute for Information Technology. His research is focused on algorithms and data analysis methods for pervasive computing.     

Reduction of the off-state current of polysilicon thin-filmtransistors by means of a polysilicon buffer layer

The off state current for polysilicon thin-film transistors for pixels in LCDs has been successfully reduced by introducing a polysilicon buffer layer between a polysilicon active layer fabricated by solid-phase-crystallisation (SPC) and a fused quartz substrate. Off-slate current of less than 1 pA under V_gs=-25 V at V_ds=3 V was obtained for n-channel single-gate coplanar transistors using the buffer layer (400 Å)     

Clonal change of HTLV-1 infected lymphocytes before onset of adult T-cell leukemia/lymphoma

A 73-year-old HTLV-1 infected male developed overt ATL following 3-years observation, and the clonality of HTLV-1 infected cells changed before overt ATL onset. 10 micrograms of DNA, extracted from mononuclear cells was digested with PstI, and the clonal proliferation of HTLV-1 infected cells was examined by Southern blotting with LTR probe. 4 bands were observed 3 years prior to ATL onset, and 2 different bands were detected 2 years and 6 months later. This suggests that in some ATL cases, the clonality of monoclonally proliferated HTLV-1 infected cells may be changeable before overt ATL onset.     

Development and validation of a near-infrared method for the quantitation of caffeine in intact single tablets

A near-infrared spectroscopic method was developed and validated for determining the caffeine concentration of single and intact tablets in a Finnish pharmaceutical product containing 58.82% (m/m) caffeine.The spectral region of interest contained a total of 474 data points. The second derivative of Savitsky-Golay, a standard normal variate, and mean centering were used as spectral preprocessing options. The feasibility study showed nonuniformity of caffeine repartition within each tablet. Thus, spectra were recorded from both faces of the tablets, and the analysis result for a single tablet was reported as the average of both face determinations. Precision of the method was validated because the relative standard deviations from repeatability and intermediate precision tests were below 0.75% (m/m). Accuracy validation proved that the NIR results were not significantly different (P = 0.09, n = 12) from the results obtained with the reference HPLC method. The limit of quantification for caffeine was 13.7% (m/m) in the tablets. The method was found to be unaffected by NIR source replacement, but the repeatability of the results was affected if the sample holder was not placed in the correct position in the light beam. Routine NIR analysis of caffeine in tablet form was found to be more flexible and much faster than that performed with the HPLC method.     

Mixed methods in international business research: A value-added perspective

The paper considers the use of mixed methods in international business research by reviewing empirical studies in four major journals. A total of 484 articles were reviewed, 68 of which had applied a mixed method strategy. In our analysis we categorize mixed methods according to their use in different stages of the research process and provide a range of alternative designs for mixing qualitative and quantitative methods.     

Systematic Exploration of Natural and Synthetic Flavonoids for the Inhibition of Staphylococcus aureus Biofilms

When single-cell (or suspended) bacteria switch into the biofilm lifestyle, they become less susceptible to antimicrobials, imposing the need for anti-biofilms research. Flavonoids are among the most extensively studied natural compounds with an unprecedented amount of bioactivity claims. Most studies focus on the antibacterial effects against suspended cells; fewer reports have researched their anti-biofilm properties. Here, a high throughput phenotypic platform was utilized to screen for the inhibitory activity of 500 flavonoids, including natural and synthetic derivatives, against Staphylococcus aureus biofilms. Since discrepancies among results from earlier antibacterial studies on flavonoids had been noted, the current study aimed to minimize sources of variations. After the first screen, flavonoids were classified as inactive (443), moderately active (47) or highly active (10). Further, exclusion criteria combining bioactivity and selectivity identified two synthetic flavans as the most promising. The body of data reported here serves three main purposes. First, it offers an improved methodological workflow for anti-biofilm screens of chemical libraries taking into account the (many times ignored) connections between anti-biofilm and antibacterial properties. This is particularly relevant for the study of flavonoids and other natural products. Second, it provides a large and freely available anti-biofilm bioactivity dataset that expands the knowledge on flavonoids and paves the way for future structure-activity relationship studies and structural optimizations. Finally, it identifies two new flavans that can successfully act on biofilms, as well as on suspended bacteria and represent more feasible antibacterial candidates.