Threshold voltage control in organic thin film transistors with dielectric layer modified by a genetically engineered polypeptide

This is the published version. Copyright 2010 American Institute of PhysicsPrecise control over the threshold voltage of pentacene-based organic thin film transistors was achieved by inserting a genetically engineered quartz-binding polypeptide at the semiconductor-dielectric interface. A 30 V range was accessed with the same peptide by adjusting the pH of the solution for peptide assembly while leaving other device properties unaffected. Mobility of 0.1–0.2 cm2 V−1 s−1 and on/off current ratio of >106 could be achieved for all devices regardless of the presence of the neutral peptide or the peptide assembled in acidic or basic conditions. This shift in threshold voltages is explained by the generation of charged species and dipoles due to variation in assembling conditions. Controlling device characteristics such as threshold voltage is essential for integration of transistors into electronic circuits

Pregnane-X-receptor mediates the anti-inflammatory activities of rifaximin on detoxification pathways in intestinal epithelial cells

International audienceThe pregnane-X-receptor (PXR) is master gene overseeing detoxification of wide number of xenobiotics and is critical for maintenance of intestinal integrity. The intestinal expression of genes involved in cellular detoxification is down-regulated in patients with inflammatory bowel diseases (IBD). Rifaximin, is a non absorbable antibiotic endowed with a PXR agonistic activity. In the present study we have investigated whether rifaximin activates PXR in primary human colon epithelial cells and human colon biopsies and assessed whether this antibiotic antagonizes the effect of Tumor necrosis factor (TNF)-α on expression of PXR and PXR-related genes. Present results demonstrate that primary colon epithelial cells express PXR and that their exposure to rifaximin induces the expression of genes involved in cellular detoxification. Exposure to TNFα reduces the expression of PXR mRNA as well as expression of its target genes. This inhibitory effect was prevented by that co-treatment with rifaximin. Knocking down the expression of PXR in colon epithelial cells by an anti-PXR siRNA, abrogated the counter-regulatory effects exerted by rifaximin on cell exposed to TNFα. Finally, exposure of colon biopsies obtained from ulcerative colitis patients to rifaximin increased the expression of genes involved in xenobiotics metabolism. In aggregate, these data illustrate that rifaximin increases the expression of PXR and PXR-regulated genes involved in the metabolism and excretion of xenobiotics and antagonized the effects of TNFα in intertsinal epithelial cells and colon biopsies. These non-antibiotic effects of rifaximin could contribute to the maintenance of the intestinal barrier integrity against xenobiotics and products generated by luminal bacteria

Applications of deep learning in severity prediction of traffic accidents

This study investigates the power of deep learning in predicting the severity of injuries when accidents occur due to traffic on Malaysian highways. Three network architectures based on a simple feedforward Neural Networks (NN), Recurrent Neural Networks (RNN), and Convolutional Neural Networks (CNN) were proposed and optimized through a grid search optimization to fine tune the hyperparameters of the models that can best predict the outputs with less computational costs. The results showed that among the tested algorithms, the RNN model with an average accuracy of 73.76% outperformed the NN model (68.79%) and the CNN (70.30%) model based on a 10-fold cross-validation approach. On the other hand, the sensitivity analysis indicated that the best optimization algorithm is “Nadam” in all the three network architectures. In addition, the best batch size for the NN and RNN was determined to be 4 and 8 for CNN. The dropout with keep probability of 0.2 and 0.5 was found critical for the CNN and RNN models, respectively. This research has shown that deep learning models such as CNN and RNN provide additional information inherent in the raw data such as temporal and spatial correlations that outperform the traditional NN model in terms of both accuracy and stability

Mastitis diagnostics and performance monitoring: a practical approach

In this paper a review is given of frequently used mastitis diagnostic methods in modern dairy practice. Methods used at the quarter, cow, herd and regional or national level are discussed, including their usability for performance monitoring in udder health. Future developments, such as systems in which milk-derived parameters are combined with modern analytical techniques, are discussed. It is concluded that, although much knowledge is available and science is still developing and much knowledge is available, it is not always fully exploited in practice

Cementomimetics—constructing a cementum-like biomineralized microlayer via amelogenin-derived peptides

This is the published version. Copyright 2012 Nature Publishing GroupCementum is the outer-, mineralized-tissue covering the tooth root and an essential part of the system of periodontal tissue that anchors the tooth to the bone. Periodontal disease results from the destructive behavior of the host elicited by an infectious biofilm adhering to the tooth root and left untreated, may lead to tooth loss. We describe a novel protocol for identifying peptide sequences from native proteins with the potential to repair damaged dental tissues by controlling hydroxyapatite biomineralization. Using amelogenin as a case study and a bioinformatics scoring matrix, we identified regions within amelogenin that are shared with a set of hydroxyapatite-binding peptides (HABPs) previously selected by phage display. One 22-amino acid long peptide regions referred to as amelogenin-derived peptide 5 (ADP5) was shown to facilitate cell-free formation of a cementum-like hydroxyapatite mineral layer on demineralized human root dentin that, in turn, supported attachment of periodontal ligament cells in vitro. Our findings have several implications in peptide-assisted mineral formation that mimic biomineralization. By further elaborating the mechanism for protein control over the biomineral formed, we afford new insights into the evolution of protein–mineral interactions. By exploiting small peptide domains of native proteins, our understanding of structure–function relationships of biomineralizing proteins can be extended and these peptides can be utilized to engineer mineral formation. Finally, the cementomimetic layer formed by ADP5 has the potential clinical application to repair diseased root surfaces so as to promote the regeneration of periodontal tissues and thereby reduce the morbidity associated with tooth loss