Effect of Solution pH on the Dual Role of Dissolved Organic Matter in Sensitized Pollutant Photooxidation

[Image: see text] Dissolved organic matter (DOM) has a dual role in indirect phototransformations of aquatic contaminants by acting both as a photosensitizer and an inhibitor. Herein, the pH dependence of the inhibitory effect of DOM and the underlying mechanisms were studied in more than 400 kinetic irradiation experiments over the pH range of 6–11. Experiments employed various combinations of one of three DOM isolates, one of two model photosensitizers, the model antioxidant phenol, and one of nine target compounds (TCs), comprising several aromatic amines, in particular anilines and sulfonamides, and 4-cyanophenol. Using model photosensitizers without antioxidants, the phototransformation of most TCs increased with increasing pH, even for TCs for which pH did not affect speciation. This trend was attributed to pH-dependent formation yields of TC-derived radicals and their re-formation to the parent TC. Analogous trends were observed with DOM as a photosensitizer. Comparison of model and DOM photosensitizer data sets showed increasing inhibitory effects of DOM on TC phototransformation kinetics with increasing pH. In systems with anilines as a TC and phenol as a model antioxidant, pH trends of the inhibitory effect could be rationalized based on the reduction potential difference (ΔE(red)) of phenoxyl/phenol and anilinyl/aniline couples. Our results indicate that the light-induced transformation of aromatic amines in the aquatic environment is governed by the pH-dependent inhibitory effects of antioxidant phenolic moieties of DOM and pH-dependent processes related to the formation of amine oxidation intermediates

Charge transport in a single molecule transistor probed by scanning tunneling microscopy

We report on the scanning tunneling microscopy/spectroscopy (STM/STS) study of cobalt phthalocyanine (CoPc) molecules deposited onto a back-gated graphene device. We observe a clear gate voltage ( V g ) dependence of the energy position of the features originating from the molecular states. Based on the analysis of the energy shifts of the molecular features upon tuning  V g , we are able to determine the nature of the electronic states that lead to a gapped differential conductance. Our measurements show that capacitive couplings of comparable strengths exist between the CoPc molecule and the STM tip as well as between CoPc and graphene, thus facilitating electronic transport involving only unoccupied molecular states for both tunneling bias polarities. These findings provide novel information on the interaction between graphene and organic molecules and are of importance for further studies, which envisage the realization of single molecule transistors with non-metallic electrodes

Development of a species-specific RNA polymerase I-based shRNA expression vector

RNA interference (RNAi) can be induced in vitro either by application of synthetic short interfering RNAs (siRNAs), or by intracellular expression of siRNAs or short hairpin RNAs (shRNAs) from transfected vectors. The most widely used promoters for siRNA/shRNA expression are based on polymerase III (Pol III)-dependent transcription. We developed an alternative vector for siRNA/shRNA expression, using a mouse RNA polymerase I (Pol I) promoter. Pol I-dependent transcription serves in cells for production of ribosomal RNA (rRNA), and as such, is ubiquitously and stably active in different cell types. As Pol I-dependent transcription is highly species-specific, Pol I-based system provides an important biosafety advantage with respect to silencing of genes with unknown functions

Deducing corticotropin-releasing hormone receptor type 1 signaling networks from gene expression data by usage of genetic algorithms and graphical Gaussian models

<p>Abstract</p> <p>Background</p> <p>Dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis is a hallmark of complex and multifactorial psychiatric diseases such as anxiety and mood disorders. About 50-60% of patients with major depression show HPA axis dysfunction, i.e. hyperactivity and impaired negative feedback regulation. The neuropeptide corticotropin-releasing hormone (CRH) and its receptor type 1 (CRHR1) are key regulators of this neuroendocrine stress axis. Therefore, we analyzed CRH/CRHR1-dependent gene expression data obtained from the pituitary corticotrope cell line AtT-20, a well-established <it>in vitro </it>model for CRHR1-mediated signal transduction. To extract significantly regulated genes from a genome-wide microarray data set and to deduce underlying CRHR1-dependent signaling networks, we combined supervised and unsupervised algorithms.</p> <p>Results</p> <p>We present an efficient variable selection strategy by consecutively applying univariate as well as multivariate methods followed by graphical models. First, feature preselection was used to exclude genes not differentially regulated over time from the dataset. For multivariate variable selection a maximum likelihood (MLHD) discriminant function within GALGO, an R package based on a genetic algorithm (GA), was chosen. The topmost genes representing major nodes in the expression network were ranked to find highly separating candidate genes. By using groups of five genes (chromosome size) in the discriminant function and repeating the genetic algorithm separately four times we found eleven genes occurring at least in three of the top ranked result lists of the four repetitions. In addition, we compared the results of GA/MLHD with the alternative optimization algorithms greedy selection and simulated annealing as well as with the state-of-the-art method random forest. In every case we obtained a clear overlap of the selected genes independently confirming the results of MLHD in combination with a genetic algorithm.</p> <p>With two unsupervised algorithms, principal component analysis and graphical Gaussian models, putative interactions of the candidate genes were determined and reconstructed by literature mining. Differential regulation of six candidate genes was validated by qRT-PCR.</p> <p>Conclusions</p> <p>The combination of supervised and unsupervised algorithms in this study allowed extracting a small subset of meaningful candidate genes from the genome-wide expression data set. Thereby, variable selection using different optimization algorithms based on linear classifiers as well as the nonlinear random forest method resulted in congruent candidate genes. The calculated interacting network connecting these new target genes was bioinformatically mapped to known CRHR1-dependent signaling pathways. Additionally, the differential expression of the identified target genes was confirmed experimentally.</p

p-BioSPRE-an information and communication technology framework for transnational biomaterial sharing and access

Biobanks represent key resources for clinico-genomic research and are needed to pave the way to personalised medicine. To achieve this goal, it is crucial that scientists can securely access and share high-quality biomaterial and related data. Therefore, there is a growing interest in integrating biobanks into larger biomedical information and communication technology (ICT) infrastructures. The European project p-medicine is currently building an innovative ICT infrastructure to meet this need. This platform provides tools and services for conducting research and clinical trials in personalised medicine. In this paper, we describe one of its main components, the biobank access framework p-BioSPRE (p-medicine Biospecimen Search and Project Request Engine). This generic framework enables and simplifies access to existing biobanks, but also to offer own biomaterial collections to research communities, and to manage biobank specimens and related clinical data over the ObTiMA Trial Biomaterial Manager. p-BioSPRE takes into consideration all relevant ethical and legal standards, e.g., safeguarding donors’ personal rights and enabling biobanks to keep control over the donated material and related data. The framework thus enables secure sharing of biomaterial within open and closed research communities, while flexibly integrating related clinical and omics data. Although the development of the framework is mainly driven by user scenarios from the cancer domain, in this case, acute lymphoblastic leukaemia and Wilms tumour, it can be extended to further disease entities.FP7/2007-2013/27008

Anthropometric and blood parameters for the prediction of NAFLD among overweight and obese adults

Backround: Non-alcoholic fatty liver disease (NAFLD) comprises non-progressive steatosis and non-alcoholic steatohepatitis (NASH), the latter of which may cause cirrhosis and hepatocellular carcinoma (HCC). As NAFLD detection is imperative for the prevention of its complications, we evaluated whether a combination of blood-based biomarkers and anthropometric parameters can be used to predict NAFLD among overweight and obese adults. Methods: 143 overweight or obese non-smokers free of diabetes (50% women, age: 35–65 years) were recruited. Anthropometric indices and routine biomarkers of metabolism and liver function were measured to predict magnetic resonance (MR) - derived NAFLD by multivariable logistic regression models. In addition, we evaluated to which degree the use of more novel biomarkers (adiponectin, leptin, resistin, C-reactive protein, TNF-α, IL-6, IL-8 and interferon-γ) could improve prediction models. Results: NAFLD was best predicted by a combination of age, sex, waist circumference, ALT, HbA1c, and HOMA-IR at an area under the receiver operating characteristic curve (AUROC) of 0.87 (95% CI: 0.81, 0.93) before and 0.85 (95% CI: 0.78, 0.91) after internal bootstrap validation. The use of additional biomarkers of inflammation and metabolism did not improve NAFLD prediction. Previously published indices predicted NAFLD at AUROCs between 0.71 and 0.82. Conclusions: The AUROC of &gt; 0.8 obtained by our regression model suggests the feasibility of a non-invasive detection of NAFLD by anthropometry and circulating biomarkers, even though further increments in the capacity of prediction models may be needed before NAFLD indices can be applied in routine clinical practice

Implementation in nursing and midwifery. A scoping review

Hintergrund: Evidenzbasiertes Wissen steht im Pflege- und Hebammenbereich zunehmend zur Verfügung, wird aber nicht automatisch in die Praxis umgesetzt. Implementationsforschung gewinnt daher immer grössere Bedeutung. Die international verfügbaren Forschungsergebnisse zu den Faktoren, die zum Gelingen einer Implementation beitragen, sind bislang noch nicht genügend aufbereitet worden. Gegenstand des Artikels: Im vorliegenden Scoping Review wird der Frage nachgegangen, welche Arbeiten zur gelungenen Vorbereitung, Durchführung und Aufrechterhaltung von Interventionen im Bereich der Pflege- und Hebammenarbeit vorliegen. Methode: In der für Scoping Reviews vorgesehenen, systematischen Vorgehensweise wurden einschlägige Datenbanken durchsucht, um Reviews und Studien zur Implementationsforschung im Bereich Pflege und Hebammenarbeit aufzufinden. Der Auswahlprozess, der zur Trefferliste führte, und die Charakteristika der eingeschlossenen Studien werden in Abbildungen und Tabellen strukturiert aufbereitet. Ergebnis: In vier Reviews und 38 Studien, die den Einschlusskriterien entsprechen, werden verschiedene Faktoren mit gelungener Implementation verbunden. Für die eingeschlossenen Studien werden folgende vier Kategorien aufgestellt: (1) Arbeitsplatzkultur mit 16 Nennungen, (2) Leitungskultur: 28 Nennungen, (3) Ressourcen: 4 Nennungen und (4) Training mit 22 Nennungen. Je nach Phase der Implementation (Vorbereitung, Durchführung oder Aufrechterhaltung) kommt ihnen eine etwas andere Bedeutung zu. Zusammenfassung: Das Review bietet eine Orientierung im Feld der Implementationsforschung und zeigt Design, Thema und Ergebnis der eingeschlossenen Studien auf. Nur wenige Studien berücksichtigen relevante Theorien und zeigen den Einfluss sowohl der Forschenden als auch der Zielgruppe auf den Implementationsprozess oder die genaue Beschreibung der Umstände, in denen die Implementation stattfindet, auf. Background: Evidence-based expertise in nursing and midwifery is growing but is not automatically turned into practice. The importance of implementation research is therefore increasing. International research results on factors facilitating implementation have not yet been sufficiently presented. Objective: This scoping review will explore the findings on successful preparation, realisation and maintenance of interventions in nursing and midwifery. Method: Based on an existing systematic approach, relevant data bases were accessed to identify original studies relating to implementation research in nursing and midwifery. The process of study selection and the characteristics of the included studies were charted. Findings: In the four reviews and 38 studies which met the inclusion criteria, various factors leading to successful implementation are identified. Based on the included studies, four facilitating factors can be pinpointed: (1) workplace culture (16 entries), (2) leadership culture (28 entries), (3) resources (4 entries), and (4) training (22 entries). Depending on the specific phase of the implementation process (preparation, realisation, or maintenance), these factors will vary in importance. Conclusion: This scoping review provides an orientation for the field of implementation research and it maps the design, themes and results of the studies included. It should be noted that few studies take into consideration the relevant theories, as well as the influence that the researchers and the target group may have on the implementation process, or provide an exact description of the setting in which the implementation takes place

A Hypomorphic Vasopressin Allele Prevents Anxiety-Related Behavior

To investigate neurobiological correlates of trait anxiety, CD1 mice were selectively bred for extremes in anxiety-related behavior, with high (HAB) and low (LAB) anxiety-related behavior mice additionally differing in behavioral tests reflecting depression-like behavior. promoter deletion to anxiety-related behavior. gene promoter explains gene expression differences in association with the observed phenotype, thus further strengthening the concept of the critical involvement of centrally released AVP in trait anxiety

A hypomorphic vasopressin allele prevents anxiety-related behavior

In this study, microarray analysis, in situ hybridization, quantitative real-time PCR and immunohistochemistry revealed decreased expression of the vasopressin gene (Avp) in the hypothalamic paraventricular (PVN) and supraoptic (SON) nuclei of adult LAB mice compared to HAB, NAB (normal anxiety-related behavior) and HABxLAB F1 intercross controls, without detecting differences in receptor expression or density. By sequencing the regions 2.5 kbp up- and downstream of the Avp gene locus, we could identify several polymorphic loci, differing between the HAB and LAB lines. In the gene promoter, a deletion of twelve bp Δ(−2180–2191) is particularly likely to contribute to the reduced Avp expression detected in LAB animals under basal conditions. Indeed, allele-specific transcription analysis of F1 animals revealed a hypomorphic LAB-specific Avp allele with a reduced transcription rate by 75% compared to the HAB-specific allele, thus explaining line-specific Avp expression profiles and phenotypic features. Accordingly, intra-PVN Avp mRNA levels were found to correlate with anxiety-related and depression-like behaviors. In addition to this correlative evidence, a significant, though moderate, genotype/phenotype association was demonstrated in 258 male mice of a freely-segregating F2 panel, suggesting a causal contribution of the Avp promoter deletion to anxiety-related behavior

Profiling Trait Anxiety: Transcriptome Analysis Reveals Cathepsin B (Ctsb) as a Novel Candidate Gene for Emotionality in Mice

Behavioral endophenotypes are determined by a multitude of counteracting but precisely balanced molecular and physiological mechanisms. In this study, we aim to identify potential novel molecular targets that contribute to the multigenic trait “anxiety”. We used microarrays to investigate the gene expression profiles of different brain regions within the limbic system of mice which were selectively bred for either high (HAB) or low (LAB) anxiety-related behavior, and also show signs of comorbid depression-like behavior