Checking the Polarity of Superconducting Multipole LHC Magnets

This paper describes the design and operation of the âﾜPolarity Checkerâ, a scanning probe designed to check multipole field order, type and polarity of superconducting LHC magnets. First we introduce the measurement method, based on the harmonic analysis of the radial field component picked up by a rotating Hall sensor at different current levels. Then we describe the hardware and the software of the system, which features automatic powering, data acquisition and treatment, discussing the achieved sensitivity and performance. Finally we provide a summary of the test results on the first 505 cryoassemblies, showing how the system was usefully employed to detect some potentially harmful connection errors

CD32+CD4+memory T cells are enriched for total HIV-1 DNA in tissues from humanized mice

CD32 has raised conflicting results as a putative marker of the HIV-1 reservoir. We measured CD32 expression in tissues from viremic and virally suppressed humanized mice treated relatively early or late after HIV-1 infection with combined antiretroviral therapy. CD32 was expressed in a small fraction of the memory CD4(+) T-cell subsets from different tissues in viremic and aviremic mice, regardless of treatment initiation time. CD32(+) memory CD4(+) T cells were enriched in cell associated (CA) HIV-1 DNA but not in CA HIV-1 RNA as compared to the CD32(-) CD4(+) fraction. Using multidimensional reduction analysis, several memory CD4(+)CD32(+) T-cell clusters were identified expressing HLA-DR, TIGIT, or PD-1. Importantly, although tissue-resident CD32(+)CD4(+) memory cells were enriched with translation-competent reservoirs, most of it was detected in memory CD32-CD4(+) T cells. Our findings support that CD32 labels highly activated/exhausted memory CD4(+) T-cell subsets that contain only a small proportion of the translation-competent reservoir

Plant viruses.

Clover viruses, 82ES38, 82AL47, 82MA19, 82BR19, 82BY29; 82BU5, 82HA9. Lupin virus, diseases. Barley yellow dwarf virus, 82AL46, 82AL51, 82B10, 82BA33, 82BR16, 82BR18, 82C29, 82E27, 82ES37, 82ES40, 82JE19, 82JE20, 82KA33, 82KA34, 82ABI3, 82MA18, 82MN22, 82MT34, 82NA32, 82WH28,82B8, 82MN17, 82E24, 82MT30, 82E25, 82MN18, 82MT31, 82B9, 82ABI2, 82BA31, 82C26, 82JE17, 82WH27, 82AL45, 82BR17, 82ES39, 82MA1, 82MA117, 82MT33

Biohydrogenation of 22:6n-3 by Butyrivibrio proteoclasticus P18

Background: Rumen microbes metabolize 22:6n-3. However, pathways of 22:6n-3 biohydrogenation and ruminal microbes involved in this process are not known. In this study, we examine the ability of the well-known rumen biohydrogenating bacteria, Butyrivibrio fibrisolvens D1 and Butyrivibrio proteoclasticus P18, to hydrogenate 22:6n-3. Results: Butyrivibrio fibrisolvens D1 failed to hydrogenate 22:6n-3 (0.5 to 32 mu g/mL) in growth medium containing autoclaved ruminal fluid that either had or had not been centrifuged. Growth of B. fibrisolvens was delayed at the higher 22:6n-3 concentrations; however, total volatile fatty acid production was not affected. Butyrivibrio proteoclasticus P18 hydrogenated 22:6n-3 in growth medium containing autoclaved ruminal fluid that either had or had not been centrifuged. Biohydrogenation only started when volatile fatty acid production or growth of B. proteoclasticus P18 had been initiated, which might suggest that growth or metabolic activity is a prerequisite for the metabolism of 22:6n-3. The amount of 22:6n-3 hydrogenated was quantitatively recovered in several intermediate products eluting on the gas chromatogram between 22:6n-3 and 22:0. Formation of neither 22:0 nor 22:6 conjugated fatty acids was observed during 22:6n-3 metabolism. Extensive metabolism was observed at lower initial concentrations of 22:6n-3 (5, 10 and 20 mu g/mL) whereas increasing concentrations of 22:6n-3 (40 and 80 mu g/mL) inhibited its metabolism. Stearic acid formation (18:0) from 18:2n-6 by B. proteoclasticus P18 was retarded, but not completely inhibited, in the presence of 22:6n-3 and this effect was dependent on 22:6n-3 concentration. Conclusions: For the first time, our study identified ruminal bacteria with the ability to hydrogenate 22:6n-3. The gradual appearance of intermediates indicates that biohydrogenation of 22:6n-3 by B. proteoclasticus P18 occurs by pathways of isomerization and hydrogenation resulting in a variety of unsaturated 22 carbon fatty acids. During the simultaneous presence of 18:2n-6 and 22:6n-3, B. proteoclasticus P18 initiated 22:6n-3 metabolism before converting 18:1 isomers into 18:0

Prediction of first test day milk yield using historical records in dairy cows

The transition between two lactations remains one of the most critical periods during the productive life of dairy cows. In this study, we aimed to develop a model that predicts the milk yield of dairy cows from test day milk yield data collected in the previous lactation. In the past, data routinely collected in the context of herd improvement programmes on dairy farms have been used to provide insights in the health status of animals or for genetic evaluations. Typically, only data from the current lactation is used, comparing expected (i.e., unperturbed) with realised milk yields. This approach cannot be used to monitor the transition period due to the lack of unperturbed milk yields at the start of a lactation. For multiparous cows, an opportunity lies in the use of data from the previous lactation to predict the expected production of the next one. We developed a methodology to predict the first test day milk yield after calving using information from the previous lactation. To this end, three random forest models (nextMILKFULL, nextMILKPH, and nextMILKP) were trained with three different feature sets to forecast the milk yield on the first test day of the next lactation. To evaluate the added value of using a machine-learning approach against simple models based on contemporary animals or production in the previous lactation, we compared the nextMILK models with four benchmark models. The nextMILK models had an RMSE ranging from 6.08 to 6.24 kg of milk. In conclusion, the nextMILK models had a better prediction performance compared to the benchmark models. Application-wise, the proposed methodology could be part of a monitoring tool tailored towards the transition period. Future research should focus on validation of the developed methodology within such tool

Comparative Lipidomics in Clinical Isolates of Candida albicans Reveal Crosstalk between Mitochondria, Cell Wall Integrity and Azole Resistance

Prolonged usage of antifungal azoles which target enzymes involved in lipid biosynthesis invariably leads to the development of multi-drug resistance (MDR) in Candida albicans. We had earlier shown that membrane lipids and their fluidity are closely linked to the MDR phenomenon. In one of our recent studies involving comparative lipidomics between azole susceptible (AS) and azole resistant (AR) matched pair clinical isolates of C. albicans, we could not see consistent differences in the lipid profiles of AS and AR strains because they came from different patients and so in this study, we have used genetically related variant recovered from the same patient collected over a period of 2-years. During this time, the levels of fluconazole (FLC) resistance of the strain increased by over 200-fold. By comparing the lipid profiles of select isolates, we were able to observe gradual and statistically significant changes in several lipid classes, particularly in plasma membrane microdomain specific lipids such as mannosylinositolphosphorylceramides and ergosterol, and in a mitochondrial specific phosphoglyceride, phosphatidyl glycerol. Superimposed with these quantitative and qualitative changes in the lipid profiles, were simultaneous changes at the molecular lipid species levels which again coincided with the development of resistance to FLC. Reverse transcriptase-PCR of the key genes of the lipid metabolism validated lipidomic picture. Taken together, this study illustrates how the gradual corrective changes in Candida lipidome correspond to the development of FLC tolerance. Our study also shows a first instance of the mitochondrial membrane dysfunction and defective cell wall (CW) in clinical AR isolates of C. albicans, and provides evidence of a cross-talk between mitochondrial lipid homeostasis, CW integrity and azole tolerance

Synthetic Nanoparticles for Vaccines and Immunotherapy

The immune system plays a critical role in our health. No other component of human physiology plays a decisive role in as diverse an array of maladies, from deadly diseases with which we are all familiar to equally terrible esoteric conditions: HIV, malaria, pneumococcal and influenza infections; cancer; atherosclerosis; autoimmune diseases such as lupus, diabetes, and multiple sclerosis. The importance of understanding the function of the immune system and learning how to modulate immunity to protect against or treat disease thus cannot be overstated. Fortunately, we are entering an exciting era where the science of immunology is defining pathways for the rational manipulation of the immune system at the cellular and molecular level, and this understanding is leading to dramatic advances in the clinic that are transforming the future of medicine.1,2 These initial advances are being made primarily through biologic drugs– recombinant proteins (especially antibodies) or patient-derived cell therapies– but exciting data from preclinical studies suggest that a marriage of approaches based in biotechnology with the materials science and chemistry of nanomaterials, especially nanoparticles, could enable more effective and safer immune engineering strategies. This review will examine these nanoparticle-based strategies to immune modulation in detail, and discuss the promise and outstanding challenges facing the field of immune engineering from a chemical biology/materials engineering perspectiveNational Institutes of Health (U.S.) (Grants AI111860, CA174795, CA172164, AI091693, and AI095109)United States. Department of Defense (W911NF-13-D-0001 and Awards W911NF-07-D-0004