Priming with a Recombinant Pantothenate Auxotroph of Mycobacterium bovis BCG and Boosting with MVA Elicits HIV-1 Gag Specific CD8+ T Cells

A safe and effective HIV vaccine is required to significantly reduce the number of people becoming infected with HIV each year. In this study wild type Mycobacterium bovis BCG Pasteur and an attenuated pantothenate auxotroph strain (BCGΔpanCD) that is safe in SCID mice, have been compared as vaccine vectors for HIV-1 subtype C Gag. Genetically stable vaccines BCG[pHS400] (BCG-Gag) and BCGΔpanCD[pHS400] (BCGpan-Gag) were generated using the Pasteur strain of BCG, and a panothenate auxotroph of Pasteur respectively. Stability was achieved by the use of a codon optimised gag gene and deletion of the hsp60-lysA promoter-gene cassette from the episomal vector pCB119. In this vector expression of gag is driven by the mtrA promoter and the Gag protein is fused to the Mycobacterium tuberculosis 19 kDa signal sequence. Both BCG-Gag and BCGpan-Gag primed the immune system of BALB/c mice for a boost with a recombinant modified vaccinia virus Ankara expressing Gag (MVA-Gag). After the boost high frequencies of predominantly Gag-specific CD8+ T cells were detected when BCGpan-Gag was the prime in contrast to induction of predominantly Gag-specific CD4+ T cells when priming with BCG-Gag. The differing Gag-specific T-cell phenotype elicited by the prime-boost regimens may be related to the reduced inflammation observed with the pantothenate auxotroph strain compared to the parent strain. These features make BCGpan-Gag a more desirable HIV vaccine candidate than BCG-Gag. Although no Gag-specific cells could be detected after vaccination of BALB/c mice with either recombinant BCG vaccine alone, BCGpan-Gag protected mice against a surrogate vaccinia virus challenge

Temporal Analysis of the Honey Bee Microbiome Reveals Four Novel Viruses and Seasonal Prevalence of Known Viruses, Nosema, and Crithidia

Honey bees (Apis mellifera) play a critical role in global food production as pollinators of numerous crops. Recently, honey bee populations in the United States, Canada, and Europe have suffered an unexplained increase in annual losses due to a phenomenon known as Colony Collapse Disorder (CCD). Epidemiological analysis of CCD is confounded by a relative dearth of bee pathogen field studies. To identify what constitutes an abnormal pathophysiological condition in a honey bee colony, it is critical to have characterized the spectrum of exogenous infectious agents in healthy hives over time. We conducted a prospective study of a large scale migratory bee keeping operation using high-frequency sampling paired with comprehensive molecular detection methods, including a custom microarray, qPCR, and ultra deep sequencing. We established seasonal incidence and abundance of known viruses, Nosema sp., Crithidia mellificae, and bacteria. Ultra deep sequence analysis further identified four novel RNA viruses, two of which were the most abundant observed components of the honey bee microbiome (∼1011 viruses per honey bee). Our results demonstrate episodic viral incidence and distinct pathogen patterns between summer and winter time-points. Peak infection of common honey bee viruses and Nosema occurred in the summer, whereas levels of the trypanosomatid Crithidia mellificae and Lake Sinai virus 2, a novel virus, peaked in January

Deep Phenotyping of Post-infectious Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Post-infectious myalgic encephalomyelitis/chronic fatigue syndrome (PI-ME/CFS) is a disabling disorder, yet the clinical phenotype is poorly defined, the pathophysiology is unknown, and no disease-modifying treatments are available. We used rigorous criteria to recruit PI-ME/CFS participants with matched controls to conduct deep phenotyping. Among the many physical and cognitive complaints, one defining feature of PI-ME/CFS was an alteration of effort preference, rather than physical or central fatigue, due to dysfunction of integrative brain regions potentially associated with central catechol pathway dysregulation, with consequences on autonomic functioning and physical conditioning. Immune profiling suggested chronic antigenic stimulation with increase in naïve and decrease in switched memory B-cells. Alterations in gene expression profiles of peripheral blood mononuclear cells and metabolic pathways were consistent with cellular phenotypic studies and demonstrated differences according to sex. Together these clinical abnormalities and biomarker differences provide unique insight into the underlying pathophysiology of PI-ME/CFS, which may guide future intervention

Recent Advances in Magnetic Nanoparticles and Nanocomposites for the Remediation of Water Resources

Water resources are of extreme importance for both human society and the environment. However, human activity has increasingly resulted in the contamination of these resources with a wide range of materials that can prevent their use. Nanomaterials provide a possible means to reduce this contamination, but their removal from water after use may be difficult. The addition of a magnetic character to nanomaterials makes their retrieval after use much easier. The following review comprises a short survey of the most recent reports in this field. It comprises five sections, an introduction into the theme, reports on single magnetic nanoparticles, magnetic nanocomposites containing two of more nanomaterials, magnetic nanocomposites containing material of a biologic origin and finally, observations about the reported research with a view to future developments. This review should provide a snapshot of developments in what is a vibrant and fast-moving area of research

Chiral luminescent CdS nano-tetrapods

The utilisation of chiral penicillamine stabilisers allowed the preparation of new water soluble white emitting CdS nano-tetrapods, which demonstrated circular dichroism in the band-edge region of the spectrum

Recent Advances in the Application of Magnetic Nanoparticles as a Support for Homogeneous Catalysts

Magnetic nanoparticles are a highly valuable substrate for the attachment of homogeneous inorganic and organic containing catalysts. This review deals with the very recent main advances in the development of various nanocatalytic systems by the immobilisation of homogeneous catalysts onto magnetic nanoparticles. We discuss magnetic core shell nanostructures (e.g., silica or polymer coated magnetic nanoparticles) as substrates for catalyst immobilisation. Then we consider magnetic nanoparticles bound to inorganic catalytic mesoporous structures as well as metal organic frameworks. Binding of catalytically active small organic molecules and polymers are also reviewed. After that we briefly deliberate on the binding of enzymes to magnetic nanocomposites and the corresponding enzymatic catalysis. Finally, we draw conclusions and present a future outlook for the further development of new catalytic systems which are immobilised onto magnetic nanoparticles

Machine Learning Techniques for Improving Nanosensors in Agroenvironmental Applications

Nanotechnology, nanosensors in particular, has increasingly drawn researchers’ attention in recent years since it has been shown to be a powerful tool for several fields like mining, robotics, medicine and agriculture amongst others. Challenges ahead, such as food availability, climate change and sustainability, have promoted such attention and pushed forward the use of nanosensors in agroindustry and environmental applications. However, issues with noise and confounding signals make the use of these tools a non-trivial technical challenge. Great advances in artificial intelligence, and more particularly machine learning, have provided new tools that have allowed researchers to improve the quality and functionality of nanosensor systems. This short review presents the latest work in the analysis of data from nanosensors using machine learning for agroenvironmental applications. It consists of an introduction to the topics of nanosensors and machine learning and the application of machine learning to the field of nanosensors. The rest of the paper consists of examples of the application of machine learning techniques to the utilisation of electrochemical, luminescent, SERS and colourimetric nanosensor classes. The final section consists of a short discussion and conclusion concerning the relevance of the material discussed in the review to the future of the agroenvironmental sector

Synthesis Characterization and Photocatalytic Studies of Cobalt Ferrite-Silica-Titania Nanocomposites

In this work, CoFe2O4@SiO2@TiO2 core-shell magnetic nanostructures have been prepared by coating of cobalt ferrite nanoparticles with the double SiO2/TiO2 layer using metallorganic precursors. The Transmission Electron Microscopy (TEM), Energy Dispersive X-Ray Analysis (EDX), Vibrational Sample Magnetometer (VSM) measurements and Raman spectroscopy results confirm the presence both of the silica and very thin TiO2 layers. The core-shell nanoparticles have been sintered at 600 °C and used as a catalyst in photo-oxidation reactions of methylene blue under UV light. Despite the additional non-magnetic coatings result in a lower value of the magnetic moment, the particles can still easily be retrieved from reaction mixtures by magnetic separation. This retention of magnetism was of particular importance allowing magnetic recovery and re-use of the catalyst