Management of KPC-Producing Klebsiella pneumoniae Infections

Klebsiella pneumoniae carbapenemase (KPC)-producing K. pneumoniae (KPC-KP) has become one of the most important contemporary pathogens, especially in endemic areas

Method-dependent epidemiological cutoff values (ECVs) for detection of triazole resistance in Candida and Aspergillus species for the SYO colorimetric broth and Etest agar diffusion methods

Although the Sensitrite Yeast-One (SYO) and Etest methods are widely utilized, interpretive criteria are not available for triazole susceptibility testing of Candida or Aspergillus species. We collected fluconazole, itraconazole, posaconazole and voriconazole SYO and Etest MICs from 39 laboratories representing all continents for (method-agent-dependent): 11,171 Candida albicans, 215 C. dubliniensis, 4,418 C. glabrata species complex (SC), 157 C. (Meyerozyma) guilliermondii, 676 C. krusei (Pichia kudriavzevii), 298 C (Clavispora) lusitaniae, 911 and 3,691 C. parapsilosissensu stricto (SS) and C. parapsilosisSC, respectively, 36 C. metapsilosis, 110 C. orthopsilosis, 1,854 C. tropicalis, 244 Saccharomyces cerevisiae, 1,409 Aspergillus fumigatus, 389 A. flavus, 130 A. nidulans, 233 A. niger, and 302 A. terreus complexes. SYO/Etest MICs for 282 confirmed non-WT isolates were included: ERG11 (C. albicans), ERG11 and MRR1 (C. parapsilosis), cyp51A (A. fumigatus), and CDR2, CDR1 overexpression (C. albicans and C. glabrata, respectively). Interlaboratory modal agreement was superior by SYO for yeast spp., and by the Etest for Aspergillus spp. Distributions fulfilling CLSI criteria for ECV definition were pooled and we proposed SYO ECVs for S. cerevisiae, 9 yeast and 3 Aspergillus species, and Etest ECVs for 5 yeast and 4 Aspergillus species. The posaconazole SYO ECV of 0.06 \ub5g/ml for C. albicans and the Etest itraconazole ECV of 2 \ub5g/ml for A. fumigatus were the best predictors of non-WT isolates. These findings support the need for method-dependent ECVs, as overall, the SYO appears to perform better for susceptibility testing of yeast spp. and the Etest for Aspergillus spp. Further evaluations should be conducted with more Candida mutants

Meta-analysis of type 2 Diabetes in African Americans Consortium

Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15 × 10(-94)<P<5 × 10(-8), odds ratio (OR)  = 1.09 to 1.36). Fine-mapping revealed that 88 of 158 previously identified T2D or glucose homeostasis loci demonstrated nominal to highly significant association (2.2 × 10(-23) < locus-wide P<0.05). These novel and previously identified loci yielded a sibling relative risk of 1.19, explaining 17.5% of the phenotypic variance of T2D on the liability scale in African Americans. Overall, this study identified two novel susceptibility loci for T2D in African Americans. A substantial number of previously reported loci are transferable to African Americans after accounting for linkage disequilibrium, enabling fine mapping of causal variants in trans-ethnic meta-analysis studies.Peer reviewe

Track D Social Science, Human Rights and Political Science

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138414/1/jia218442.pd

Helium identification with LHCb

The identification of helium nuclei at LHCb is achieved using a method based on measurements of ionisation losses in the silicon sensors and timing measurements in the Outer Tracker drift tubes. The background from photon conversions is reduced using the RICH detectors and an isolation requirement. The method is developed using pp collision data at √(s) = 13 TeV recorded by the LHCb experiment in the years 2016 to 2018, corresponding to an integrated luminosity of 5.5 fb-1. A total of around 105 helium and antihelium candidates are identified with negligible background contamination. The helium identification efficiency is estimated to be approximately 50% with a corresponding background rejection rate of up to O(10^12). These results demonstrate the feasibility of a rich programme of measurements of QCD and astrophysics interest involving light nuclei

Curvature-bias corrections using a pseudomass method

Momentum measurements for very high momentum charged particles, such as muons from electroweak vector boson decays, are particularly susceptible to charge-dependent curvature biases that arise from misalignments of tracking detectors. Low momentum charged particles used in alignment procedures have limited sensitivity to coherent displacements of such detectors, and therefore are unable to fully constrain these misalignments to the precision necessary for studies of electroweak physics. Additional approaches are therefore required to understand and correct for these effects. In this paper the curvature biases present at the LHCb detector are studied using the pseudomass method in proton-proton collision data recorded at centre of mass energy √(s)=13 TeV during 2016, 2017 and 2018. The biases are determined using Z→μ + μ - decays in intervals defined by the data-taking period, magnet polarity and muon direction. Correcting for these biases, which are typically at the 10-4 GeV-1 level, improves the Z→μ + μ - mass resolution by roughly 18% and eliminates several pathological trends in the kinematic-dependence of the mean dimuon invariant mass