Facile Synthesis of 2-(1,3-Benzoxazol/benzothiazol-2-yl)- 3H-benzo[f]chromen-3-one as Blue Fluorescent Brighteners

A novel synthetic method was developed to prepare new fluorescent 2-(1,3-benzoxazol/benzothiazol-2-yl)-3H-benzo [ƒ]chromen-3-one derivatives 3a-p by the Knoevenagel condensation between 2-hydroxy-1-naphthaldehyde and benzothiazole-2-yl-aceatates or N-methyl benzoxazole-2-yl-acetates using choline chloride/urea ionic liquid as a green catalyst. The results of fluorescence studies revealed that all the compounds show moderate to low emission intensities and are expressed in the form of quantum yields.Keywords: Benzooxazolyl-3H-benzo[ƒ]chromen-3-one, benzothiazolyl-3H-benzo[ƒ]chromen-3-one, choline chloride/urea, fluorescent brightener

Synthesis of New Benzocoumaryl Oxadiazolyls as Strong Blue-Green Fluorescent Brighteners

The benzocoumarin-3-ethylcarboxylate 2 on treatment with hydrazine hydrate at room temperature afforded benzocoumarin-3-carbohydrazide 3. The compound 3 served as key intermediate in the synthesis of the title compounds. Thus, benzocoumarin-1,3,4-oxadiazolyls 6a–e were obtained in two ways, i.e. one by direct cyclization of benzocoumarin-3- carbohydrazide 3 with substituted benzoic acids in POCl3 and the other by cyclization of Schiff bases of compounds 5a–e in the presence of bromine/ acetic acid. The structures of the novel benzocoumaryl oxadiazolyls 6a–e were confirmed by spectral analysis. The benzocoumarin-1,3,4-oxadiazolyls 6a–e exhibited strong blue and green fluorescent properties. The Stoke’s shifts range from 43 to 165 nm. The absorption and fluorescence maxima of the benzocoumaryl oxadiazolyls showed good bathochromic shifts.Keywords: Benzocoumarin-3-ethylcarboxylate, benzocoumaryl oxadiazolyls, fluorescent brightener

Controlling Curie temperature in (Ga,Ms)As through location of the Fermi level within the impurity band

The ferromagnetic semiconductor (Ga,Mn)As has emerged as the most studied material for prototype applications in semiconductor spintronics. Because ferromagnetism in (Ga,Mn)As is hole-mediated, the nature of the hole states has direct and crucial bearing on its Curie temperature TC. It is vigorously debated, however, whether holes in (Ga,Mn)As reside in the valence band or in an impurity band. In this paper we combine results of channeling experiments, which measure the concentrations both of Mn ions and of holes relevant to the ferromagnetic order, with magnetization, transport, and magneto-optical data to address this issue. Taken together, these measurements provide strong evidence that it is the location of the Fermi level within the impurity band that determines TC through determining the degree of hole localization. This finding differs drastically from the often accepted view that TC is controlled by valence band holes, thus opening new avenues for achieving higher values of TC.Comment: 5 figures, supplementary material include

Ferromagnetic Semiconductors: Moving Beyond (Ga,Mn)As

The recent development of MBE techniques for growth of III-V ferromagnetic semiconductors has created materials with exceptional promise in spintronics, i.e. electronics that exploit carrier spin polarization. Among the most carefully studied of these materials is (Ga,Mn)As, in which meticulous optimization of growth techniques has led to reproducible materials properties and ferromagnetic transition temperatures well above 150 K. We review progress in the understanding of this particular material and efforts to address ferromagnetic semiconductors as a class. We then discuss proposals for how these materials might find applications in spintronics. Finally, we propose criteria that can be used to judge the potential utility of newly discovered ferromagnetic semiconductors, and we suggest guidelines that may be helpful in shaping the search for the ideal material.Comment: 37 pages, 4 figure

How to identify essential genes from molecular networks?

<p>Abstract</p> <p>Background</p> <p>The prediction of essential genes from molecular networks is a way to test the understanding of essentiality in the context of what is known about the network. However, the current knowledge on molecular network structures is incomplete yet, and consequently the strategies aimed to predict essential genes are prone to uncertain predictions. We propose that simultaneously evaluating different network structures and different algorithms representing gene essentiality (centrality measures) may identify essential genes in networks in a reliable fashion.</p> <p>Results</p> <p>By simultaneously analyzing 16 different centrality measures on 18 different reconstructed metabolic networks for <it>Saccharomyces cerevisiae</it>, we show that no single centrality measure identifies essential genes from these networks in a statistically significant way; however, the combination of at least 2 centrality measures achieves a reliable prediction of most but not all of the essential genes. No improvement is achieved in the prediction of essential genes when 3 or 4 centrality measures were combined.</p> <p>Conclusion</p> <p>The method reported here describes a reliable procedure to predict essential genes from molecular networks. Our results show that essential genes may be predicted only by combining centrality measures, revealing the complex nature of the function of essential genes.</p

ERK1/2 signalling protects against apoptosis following endoplasmic reticulum stress but cannot provide long-term protection against BAX/BAK-independent cell death

Disruption of protein folding in the endoplasmic reticulum (ER) causes ER stress. Activation of the unfolded protein response (UPR) acts to restore protein homeostasis or, if ER stress is severe or persistent, drive apoptosis, which is thought to proceed through the cell intrinsic, mitochondrial pathway. Indeed, cells that lack the key executioner proteins BAX and BAK are protected from ER stress-induced apoptosis. Here we show that chronic ER stress causes the progressive inhibition of the extracellular signal-regulated kinase (ERK1/2) signalling pathway. This is causally related to ER stress since reactivation of ERK1/2 can protect cells from ER stress-induced apoptosis whilst ERK1/2 pathway inhibition sensitises cells to ER stress. Furthermore, cancer cell lines harbouring constitutively active BRAFV600E are addicted to ERK1/2 signalling for protection against ER stress-induced cell death. ERK1/2 signalling normally represses the pro-death proteins BIM, BMF and PUMA and it has been proposed that ER stress induces BIM-dependent cell death. We found no evidence that ER stress increased the expression of these proteins; furthermore, BIM was not required for ER stress-induced death. Rather, ER stress caused the PERK-dependent inhibition of cap-dependent mRNA translation and the progressive loss of pro-survival proteins including BCL2, BCLXL and MCL1. Despite these observations, neither ERK1/2 activation nor loss of BAX/BAK could confer long-term clonogenic survival to cells exposed to ER stress. Thus, ER stress induces cell death by at least two biochemically and genetically distinct pathways: a classical BAX/BAK-dependent apoptotic response that can be inhibited by ERK1/2 signalling and an alternative ERK1/2- and BAX/BAK-independent cell death pathway

Genetic and pharmacological inhibition of CDK9 drives neutrophil apoptosis to resolve inflammation in zebrafish in vivo

Neutrophilic inflammation is tightly regulated and subsequently resolves to limit tissue damage and promote repair. When the timely resolution of inflammation is dysregulated, tissue damage and disease results. One key control mechanism is neutrophil apoptosis, followed by apoptotic cell clearance by phagocytes such as macrophages. Cyclin-dependent kinase (CDK) inhibitor drugs induce neutrophil apoptosis in vitro and promote resolution of inflammation in rodent models. Here we present the first in vivo evidence, using pharmacological and genetic approaches, that CDK9 is involved in the resolution of neutrophil-dependent inflammation. Using live cell imaging in zebrafish with labelled neutrophils and macrophages, we show that pharmacological inhibition, morpholino-mediated knockdown and CRISPR/cas9-mediated knockout of CDK9 enhances inflammation resolution by reducing neutrophil numbers via induction of apoptosis after tailfin injury. Importantly, knockdown of the negative regulator La-related protein 7 (LaRP7) increased neutrophilic inflammation. Our data show that CDK9 is a possible target for controlling resolution of inflammation

An Automated Phenotype-Driven Approach (GeneForce) for Refining Metabolic and Regulatory Models

Integrated constraint-based metabolic and regulatory models can accurately predict cellular growth phenotypes arising from genetic and environmental perturbations. Challenges in constructing such models involve the limited availability of information about transcription factor—gene target interactions and computational methods to quickly refine models based on additional datasets. In this study, we developed an algorithm, GeneForce, to identify incorrect regulatory rules and gene-protein-reaction associations in integrated metabolic and regulatory models. We applied the algorithm to refine integrated models of Escherichia coli and Salmonella typhimurium, and experimentally validated some of the algorithm's suggested refinements. The adjusted E. coli model showed improved accuracy (∼80.0%) for predicting growth phenotypes for 50,557 cases (knockout mutants tested for growth in different environmental conditions). In addition to identifying needed model corrections, the algorithm was used to identify native E. coli genes that, if over-expressed, would allow E. coli to grow in new environments. We envision that this approach will enable the rapid development and assessment of genome-scale metabolic and regulatory network models for less characterized organisms, as such models can be constructed from genome annotations and cis-regulatory network predictions

Metabolomic Analysis in Severe Childhood Pneumonia in The Gambia, West Africa: Findings from a Pilot Study

Pneumonia remains the leading cause of death in young children globally and improved diagnostics are needed to better identify cases and reduce case fatality. Metabolomics, a rapidly evolving field aimed at characterizing metabolites in biofluids, has the potential to improve diagnostics in a range of diseases. The objective of this pilot study is to apply metabolomic analysis to childhood pneumonia to explore its potential to improve pneumonia diagnosis in a high-burden setting. and Random Forests (RF). ‘Unsupervised’ (blinded) data were analyzed by Principal Component Analysis (PCA), while ‘supervised’ (unblinded) analysis was by Partial Least Squares-Discriminant Analysis (PLS-DA) and Orthogonal Projection to Latent Structures (OPLS). Potential markers were extracted from S-plots constructed following analysis with OPLS, and markers were chosen based on their contribution to the variation and correlation within the data set. The dataset was additionally analyzed with the machine-learning algorithm RF in order to address issues of model overfitting and markers were selected based on their variable importance ranking. Unsupervised PCA analysis revealed good separation of pneumonia and control groups, with even clearer separation of the groups with PLS-DA and OPLS analysis. Statistically significant differences (p<0.05) between groups were seen with the following metabolites: uric acid, hypoxanthine and glutamic acid were higher in plasma from cases, while L-tryptophan and adenosine-5′-diphosphate (ADP) were lower; uric acid and L-histidine were lower in urine from cases. The key limitation of this study is its small size.Metabolomic analysis clearly distinguished severe pneumonia patients from community controls. The metabolites identified are important for the host response to infection through antioxidant, inflammatory and antimicrobial pathways, and energy metabolism. Larger studies are needed to determine whether these findings are pneumonia-specific and to distinguish organism-specific responses. Metabolomics has considerable potential to improve diagnostics for childhood pneumonia