De omslag tegen het licht gehouden : wegenheffing en de kostentoedeling daarvan vanaf 2009 onder de nieuwe Waterschapswet door Hoogheemraadschap Hollands Noorderkwartier

Het Hoogheemraadschap Hollands Noorderkwartier is één van de zes waterschappen in ons land met een wegbeheerstaak. Waterschappen die belast zijn met wegbeheer zien niet al hun gemaakte kosten vergoed door algemene overheidslichamen. De niet gedekte kosten moeten worden omgeslagen over de belangencategorieën door middel van een kostentoedelingsverordening. Om deze op te kunnen stellen is door Wageningen Universiteit in 1995 een kostentoedelingsmethodiek ontwikkeld, gebaseerd op het profijt dat de verschillende categorieën hebben bij de waterschapswegen. Vanwege een fusie van waterschappen en vanwege nieuwe Waterschapswetgeving heeft thans een bijstelling van de methode plaatsgevonden

Bosjes van Poot : onderzoek bezoekers en honden

De Bosjes van Poot is een duingebied dat sinds 1990 behoort tot Natuurmonument Westduinpark. Daarmee valt het onder de Natuurbeschermingswet en in 2008 wordt de aanwijzing tot Natura 2000 gebied verwacht. In opdracht van Dienst Stadsbeheer van Den Haag is nu een onderzoek opgezet en uitgevoerd om beter zicht te krijgen op een gewenst hondenbeleid. De vraagstelling is hoeveel honden er gebruik maken van het gebied en hoe dat over het gebied verdeeld i

Prevalence of baseline polymorphisms for potential resistance to NS5A inhibitors in drug-naive individuals infected with hepatitis C genotypes 1–4

Background: The non-structural 5A (NS5A) protein of HCV is a multifunctional phosphoprotein involved in regulation of viral replication and virion assembly. NS5A inhibitors targeting domain I of NS5A protein have demonstrated high potency and pan-genotypic antiviral activity, however they possess a low genetic barrier to resistance. At present, only genotype 1, the most prevalent HCV genotype has been studied in detail for resistant variants. Methods: Utilising a panel of genotypic-specific resistance assays, population sequencing was performed on plasma derived viral RNA isolated from 138 patients infected with HCV genotypes 1-4 and not treated with directly acting anti-viral agents (DAAs). Amino acid changes in HCV NS5A domain I at codon positions 28, 30, 31, 32 and 93, reported to confer reduced susceptibility to certain NS5A inhibitors were examined. Additionally, genotypic outcome based on NS5A sequences were compared with LiPA and Abbott® real time. Results: Amino acid substitutions associated with moderate to high level resistance to NS5A inhibitors were detected in 2/42 (4.76%) HCV-1a, 3/23 (13.04%) HCV-1b, 4/26 ( 15.38% ) HCV-2, 1/24 (4.17%) HCV-3 and 1/23 (4.35%) HCV-4 infected patients who had not been treated with NS5A inhibitors. Genotype prediction based on NS5A sequences were concordant with LiPA and/or Abbott® real-time for 97.10% of cases. Conclusion: Primary resistance mutations associated with resistance to first generation NS5A inhibitors such as Daclatasvir (DCV) were observed in all genotypes, albeit at low frequencies. An excellent correlation based on NS5A genotyping and LiPA or Abbott® real-time was achieved

Development and application of a data-driven reaction classification model : comparison of an electronic lab notebook and the medicinal chemistry literature

Reaction classification has often been considered an important task for many different applications, and has traditionally been accomplished using hand-coded rule-based approaches. However, the availability of large collections of reactions enables data-driven approaches to be developed. We present the development and validation of a 336-class machine learning-based classification model integrated within a Conformal Prediction (CP) framework in order to associate reaction class predictions with confidence estimations. We also propose a data-driven approach for 'dynamic' reaction fingerprinting to maximise the effectiveness of reaction encoding, as well as developing a novel reaction classification system that organises labels in four hierarchical levels (SHREC: Sheffield Hierarchical REaction Classification). We show that the performance of the CP augmented model can be improved by defining confidence thresholds to detect predictions that are less likely to be false. For example, the external validation of the model reports 95% of predictions as correct by filtering out less than 15% of the uncertain classifications. The application of the model is demonstrated by classifying two reaction datasets: one extracted from an industrial ELN and the other from the medicinal chemistry literature. We show how confidence estimations and class compositions across different levels of information can be used to gain immediate insights on the nature of reaction collections and hidden relationship between reaction classes

Enhancing reaction-based de novo design using a multi-label reaction class recommender

Reaction-based de novo design refers to the in-silico generation of novel chemical structures by combining reagents using structural transformations derived from known reactions. The driver for using reaction-based transformations is to increase the likelihood of the designed molecules being synthetically accessible. We have previously described a reaction-based de novo design method based on reaction vectors which are transformation rules that are encoded automatically from reaction databases. A limitation of reaction vectors is that they account for structural changes that occur at the core of a reaction only, and they do not consider the presence of competing functionalities that can compromise the reaction outcome. Here, we present the development of a Reaction Class Recommender to enhance the reaction vector framework. The recommender is intended to be used as a filter on the reaction vectors that are applied during de novo design to reduce the combinatorial explosion of in-silico molecules produced while limiting the generated structures to those which are most likely to be synthesisable. The recommender has been validated using an external data set extracted from the recent medicinal chemistry literature and in two simulated de novo design experiments. Results suggest that the use of the recommender drastically reduces the number of solutions explored by the algorithm while preserving the chance of finding relevant solutions and increasing the global synthetic accessibility of the designed molecules

Identification of proteomic signatures associated with depression and psychotic depression in post-mortem brains from major depression patients

Major depressive disorder (MDD) is a leading cause of disability worldwide and results tragically in the loss of almost one million lives in Western societies every year. This is due to poor understanding of the disease pathophysiology and lack of empirical medical tests for accurate diagnosis or for guiding antidepressant treatment strategies. Here, we have used shotgun proteomics in the analysis of post-mortem dorsolateral prefrontal cortex brain tissue from 24 MDD patients and 12 matched controls. Brain proteomes were pre-fractionated by gel electrophoresis and further analyzed by shotgun data-independent label-free liquid chromatography-mass spectrometry. This led to identification of distinct proteome fingerprints between MDD and control subjects. Some of these differences were validated by Western blot or selected reaction monitoring mass spectrometry. This included proteins associated with energy metabolism and synaptic function and we also found changes in the histidine triad nucleotide-binding protein 1 (HINT1), which has been implicated recently in regulation of mood and behavior. We also found differential proteome profiles in MDD with (n=11) and without (n=12) psychosis. Interestingly, the psychosis fingerprint showed a marked overlap to changes seen in the brain proteome of schizophrenia patients. These findings suggest that it may be possible to contribute to the disease understanding by distinguishing different subtypes of MDD based on distinct brain proteomic profiles

Bruton's Tyrosine Kinase Is Required For Lipopolysaccharide-induced Tumor Necrosis Factor α Production

Lipopolysaccharide (LPS), a product of Gram-negative bacteria, is potent mediator of tumor necrosis factor (TNF)α production by myeloid/macrophage cells. Inhibitors capable of blocking the signaling events that result in TNFα production could provide useful therapeutics for treating septic shock and other inflammatory diseases. Broad spectrum tyrosine inhibitors are known to inhibit TNFα production, however, no particular family of tyrosine kinases has been shown to be essential for this process. Here we show that the Bruton's tyrosine kinase (Btk)-deficient mononuclear cells from X-linked agammaglobulinemia patients have impaired LPS-induced TNFα production and that LPS rapidly induces Btk kinase activity in normal monocytes. In addition, adenoviral overexpression of Btk in normal human monocytes enhanced TNFα production. We examined the role of Btk in TNFα production using luciferase reporter adenoviral constructs and have established that overexpression of Btk results in the stabilization of TNFα mRNA via the 3′ untranslated region. Stimulation with LPS also induced the activation of related tyrosine kinase, Tec, suggesting that the Tec family kinases are important components for LPS-induced TNFα production. This study provides the first clear evidence that tyrosine kinases of the Tec family, in particular Btk, are key elements of LPS-induced TNFα production and consequently may provide valuable therapeutic targets for intervention in inflammatory conditions

Synoptic and Mesoscale Dynamics of Cold Surges over the South China Sea and their Control on Extreme Rainfall

We investigate the synoptic and mesoscale dynamics of two wet and two dry cold surges in January 2021 using a combination of observations, reanalysis, and convective-scale model forecasts from the Met Office Unified Model (MetUM). We focus on the wet surges, and particularly the wettest days which are locally extreme over Singapore and the surrounding region (i.e., the daily mean and area-averaged rainfall over 20 years exceeds the 99th percentile). On the large scale, the wet surges are characterized by an anomalously strong anticyclone over Siberia prior to their onset. The anticyclone and resultant surge winds are stronger than those of the dry surges. There is also a relatively moist (dry) environment prior to the onset of the wet (dry) surges, with the Madden-Julian Oscillation (MJO) being in Phase 3 (Phase 6). On the mesoscale, the combination of the cold surge and a local tropical low produce strong, moist north-easterly winds and convection over the Singapore region. The equatorward advection of positive anomalies of equivalent potential temperature resembles a weak gravity-current-like structure at its head, although the spatial scale is much too large for a gravity current. There is a moist bias in the model forecasts, although the precipitation is underestimated regionally during the wet surges and particularly on the extreme rainfall days. Overall, the model forecasts perform well synoptically but not in the details of mesoscale convection

Antimicrobial mouthwashes (gargling) and nasal sprays administered to patients with suspected or confirmed COVID‐19 infection to improve patient outcomes and to protect healthcare workers treating them (Review)

A C K N O W L E D G E M E N T S: We would like to thank the peer reviewers, Professor Jeremy Bagg, Dr Karolin Hijazi, Professor Carl Philpott and Professor Claire Hopkins, fortheirinsightful comments, which helped us to improve these reviews. Thanks also to Professor Peter Tugwell, Senior Editor Cochrane MOSS Network, for acting as sign-oF editor for these projects. We are also grateful to Doug Salzwedel from the Cochrane Hypertension Group for providing search peer review comments for the draK search strategy. Professor Schilder's time for this project was supported by the National Institute for Health Research, University College London Hospitals Biomedical Research Centre, London, UK. This project was supported by the National Institute for Health Research, via Cochrane Infrastructure, Cochrane Programme Grant or Cochrane Incentive funding to Cochrane ENT and Cochrane Oral Health. The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the Systematic Reviews Programme, NIHR, NHS or the Department of Health.Peer reviewedPublisher PD

The pH of spray-dried blood meal does not influence nursery pig performance

Two studies were conducted to evaluate the effects of spray-dried blood meal and its pH on nursery pig performance. Spray-dried blood meal pH decreases as storage time increases prior to spray drying. In Exp. 1, addition of 2.5% spray-dried blood meal to the diet improved ADG and ADFI in nursery pigs (15.4 lb to 35.9 lb), but did not influence feed efficiency. In Exp. 2, the inclusion of 5% spray-dried blood meal improved feed efficiency without affecting ADG or ADFI. The pH (7.4 to 5.9 in Exp. 1 and 7.6 to 5.9 in Exp. 2) of the blood meal did not influence growth performance