281 research outputs found
Epidemiological and clinical characteristics of international travelers with enteric fever and antibiotic resistance profiles of their isolates: A GeoSentinel analysis
Copyright © 2020 American Society for Microbiology. All Rights Reserved. Enteric fever, caused by Salmonella enterica serovar Typhi (S. Typhi) and S. enterica serovar Paratyphi (S. Paratyphi), is a common travel-related illness. Limited data are available on the antimicrobial resistance (AMR) patterns of these serovars among travelers. Records of travelers with a culture-confirmed diagnosis seen during or after travel from January 2007 to December 2018 were obtained from GeoSentinel. Traveler demographics and antimicrobial susceptibility data were analyzed. Isolates were classified as nonsusceptible if intermediate or resistant or as susceptible in accordance with the participating site’s national guidelines. A total of 889 travelers (S. Typhi infections, n = 474; S. Paratyphi infections, n = 414; coinfection, n = 1) were included; 114 (13%) were children of (41%) traveled to visit friends and relatives (VFRs) and acquired the infection in South Asia (71%). Child travelers with S. Typhi infection were most frequently VFRs (77%). The median trip duration was 31 days (interquartile range, 18 to 61 days), and 448 of 691 travelers (65%) had no pretravel consultation. Of 143 S. Typhi and 75 S. Paratyphi isolates for which there were susceptibility data, nonsusceptibility to antibiotics varied (fluoroquinolones, 65% and 56%, respectively; co-trimoxazole, 13% and 0%; macrolides, 8% and 16%). Two S. Typhi isolates (1.5%) from India were nonsusceptible to third-generation cephalosporins. S. Typhi fluoroquinolone nonsusceptibility was highest when infection was acquired in South Asia (70 of 90 isolates; 78%) and sub-Saharan Africa (6 of 10 isolates; 60%). Enteric fever is an important travel-associated illness complicated by AMR. Our data contribute to a better understanding of region-specific AMR, helping to inform empirical treatment options. Prevention measures need to focus on high-risk travelers including VFRs and children
Sequential phosphorylation of SLP-76 at tyrosine 173 is required for activation of T and mast cells.
Cooperatively assembled signalling complexes, nucleated by adaptor proteins, integrate information from surface receptors to determine cellular outcomes. In T and mast cells, antigen receptor signalling is nucleated by three adaptors: SLP-76, Gads and LAT. Three well-characterized SLP-76 tyrosine phosphorylation sites recruit key components, including a Tec-family tyrosine kinase, Itk. We identified a fourth, evolutionarily conserved SLP-76 phosphorylation site, Y173, which was phosphorylated upon T-cell receptor stimulation in primary murine and Jurkat T cells. Y173 was required for antigen receptor-induced phosphorylation of phospholipase C-γ1 (PLC-γ1) in both T and mast cells, and for consequent downstream events, including activation of the IL-2 promoter in T cells, and degranulation and IL-6 production in mast cells. In intact cells, Y173 phosphorylation depended on three, ZAP-70-targeted tyrosines at the N-terminus of SLP-76 that recruit and activate Itk, a kinase that selectively phosphorylated Y173 in vitro. These data suggest a sequential mechanism whereby ZAP-70-dependent priming of SLP-76 at three N-terminal sites triggers reciprocal regulatory interactions between Itk and SLP-76, which are ultimately required to couple active Itk to its substrate, PLC-γ1
Lack of Association of Type 2 Diabetes Susceptibility Genotypes and Body Weight on the Development of Islet Autoimmunity and Type 1 Diabetes
AIM: To investigate whether type 2 diabetes susceptibility genes and body weight influence the development of islet autoantibodies and the rate of progression to type 1 diabetes. METHODS: Genotyping for single nucleotide polymorphisms (SNP) of the type 2 diabetes susceptibility genes CDKAL1, CDKN2A/2B, FTO, HHEX-IDE, HMGA2, IGF2BP2, KCNJ11, KCNQ1, MTNR1B, PPARG, SLC30A8 and TCF7L2 was obtained in 1350 children from parents with type 1 diabetes participating in the BABYDIAB study. Children were prospectively followed from birth for islet autoantibodies and type 1 diabetes. Data on weight and height were obtained at 9 months, 2, 5, 8, 11, and 14 years of age. RESULTS: None of type 2 diabetes risk alleles at the CDKAL1, CDKN2A/2B, FTO, HHEX-IDE, HMGA2, IGF2BP2, KCNJ11, KCNQ1, MTNR1B, PPARG and SLC30A8 loci were associated with the development of islet autoantibodies or diabetes. The type 2 diabetes susceptible genotype of TCF7L2 was associated with a lower risk of islet autoantibodies (7% vs. 12% by age of 10 years, P = 0.015, P(corrected) = 0.18). Overweight children at seroconversion did not progress to diabetes faster than non-overweight children (HR: 1.08; 95% CI: 0.48-2.45, P>0.05). CONCLUSIONS: These findings do not support an association of type 2 diabetes risk factors with islet autoimmunity or acceleration of diabetes in children with a family history of type 1 diabetes
Crown Lengthening Revisited
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141178/1/cap0233.pd
Atomic Routing Games on Maximum Congestion
We study atomic routing congestion games in which each player chooses a path in the network from its strategy set (a collection of paths) with the objective to minimize the maximum congestion along any edge on its selected path. The social cost is the global maximum congestion on any edge in the network. We show that for arbitrary routing games, the price of stability is 1, and the price of anarchy, PoA, is bounded by κ − 1 ≤ PoA ≤ c(κ 2 + log 2 n), where κ is the length of the longest cycle in the network, n is the size of the network and c is a constant. Further, any best response dynamic converges to a Nash equilibrium. Our bounds show that for maximum congestion games, the topology of the network, in particular the length of cycles, plays an important role in determining the quality of the Nash equilibria. A fundamental issue in the management of large scale communication networks is to route the packet traffic so as to optimize the network performance. Our measure of network performance is the worst bottleneck (most used link) in the system. The model we use for network traffic is that of finite, unsplittable packets (atomic flow), and each packet’s path is controlled independentl
Investigating the Role of T-Cell Avidity and Killing Efficacy in Relation to Type 1 Diabetes Prediction
During the progression of the clinical onset of Type 1 Diabetes (T1D), high-risk individuals exhibit multiple islet autoantibodies and high-avidity T cells which progressively destroy beta cells causing overt T1D. In particular, novel autoantibodies, such as those against IA-2 epitopes (aa1-577), had a predictive rate of 100% in a 10-year follow up (rapid progressors), unlike conventional autoantibodies that required 15 years of follow up for a 74% predictive rate (slow progressors). The discrepancy between these two groups is thought to be associated with T-cell avidity, including CD8 and/or CD4 T cells. For this purpose, we build a series of mathematical models incorporating first one clone then multiple clones of islet-specific and pathogenic CD8 and/or CD4 T cells, together with B lymphocytes, to investigate the interaction of T-cell avidity with autoantibodies in predicting disease onset. These models are instrumental in examining several experimental observations associated with T-cell avidity, including the phenomenon of avidity maturation (increased average T-cell avidity over time), based on intra- and cross-clonal competition between T cells in high-risk human subjects. The model shows that the level and persistence of autoantibodies depends not only on the avidity of T cells, but also on the killing efficacy of these cells. Quantification and modeling of autoreactive T-cell avidities can thus determine the level of risk associated with each type of autoantibodies and the timing of T1D disease onset in individuals that have been tested positive for these autoantibodies. Such studies may lead to early diagnosis of the disease in high-risk individuals and thus potentially serve as a means of staging patients for clinical trials of preventive or interventional therapies far before disease onset
Rabies post-exposure prophylaxis started during or after travel: a GeoSentinel analysis
Background
Recent studies demonstrate that rabies post-exposure prophylaxis (RPEP) in international travelers is suboptimal, with only 5–20% of travelers receiving rabies immune globulin (RIG) in the country of exposure when indicated. We hypothesized that travelers may not be receiving RIG appropriately, and practices may vary between countries. We aim to describe the characteristics of travelers who received RIG and/or RPEP during travel.
Methodology/Principal findings
We conducted a multi-center review of international travelers exposed to potentially rabid animals, collecting information on RPEP administration. Travelers who started RPEP before (Group A) and at (Group B) presentation to a GeoSentinel clinic during September 2014–July 2017 were included. We included 920 travelers who started RPEP. About two-thirds of Group A travelers with an indication for rabies immunoglobulin (RIG) did not receive it. Travelers exposed in Indonesia were less likely to receive RIG in the country of exposure (relative risk: 0.30; 95% confidence interval: 0.12–0.73; P = 0.01). Travelers exposed in Thailand [Relative risk (RR) 1.38, 95% Confidence Interval (95% CI): 1.0–1.8; P = 0.02], Sri Lanka (RR 3.99, 95% CI: 3.99–11.9; P = 0.013), and the Philippines (RR 19.95, 95% CI: 2.5–157.2; P = 0.01), were more likely to receive RIG in the country of exposure.
Conclusions/Significance
This analysis highlights gaps in early delivery of RIG to travelers and identifies specific countries where travelers may be more or less likely to receive RIG. More detailed country-level information helps inform risk education of international travelers regarding appropriate rabies prevention
Living Law, Legal Pluralism, and Corruption in Post-Soviet Uzbekistan
This paper aims to explore the multifaceted meaning, logic, and morality of informal transactions in order to better understand the social context that informs the meaning of corruption and bribery in post-Soviet Uzbekistan. It will be argued that the informal transactions in Uzbek society reflect different cultural and functional meanings from those in most of the Western world, and hence transactions that from a Western-centric perspective would be labelled as bribes can be morally accepted transactions in the Uzbek cultural context. If this is true, there may be reasons to re-evaluate the relevance of the Western-centric interpretations of corruption in the context of Uzbekistan, and possibly other Central Asian countries. These issues will be investigated with reference to observations and informal interviews from post-Soviet Uzbekistan. This study is based on three periods of ethnographic field research between 2009 and 2012 in the Ferghana Province of Uzbekistan. It draws on concepts of ‘living law’ and legal pluralism to provide a theoretical framework
Etiological Approach to Characterization of Diabetes Type: The SEARCH for Diabetes in Youth Study
OBJECTIVE To describe an etiologic approach to classification of diabetes types in youth based on the 1997 American Diabetes Association (ADA) framework, using data from the SEARCH for Diabetes in Youth Study
Urinary Proteomics to Support Diagnosis of Stroke
Accurate diagnosis in suspected ischaemic stroke can be difficult. We explored the urinary proteome in patients with stroke (n = 69), compared to controls (n = 33), and developed a biomarker model for the diagnosis of stroke. We performed capillary electrophoresis online coupled to micro-time-of-flight mass spectrometry. Potentially disease-specific peptides were identified and a classifier based on these was generated using support vector machine-based software. Candidate biomarkers were sequenced by liquid chromatography-tandem mass spectrometry. We developed two biomarker-based classifiers, employing 14 biomarkers (nominal p-value <0.004) or 35 biomarkers (nominal p-value <0.01). When tested on a blinded test set of 47 independent samples, the classification factor was significantly different between groups; for the 35 biomarker model, median value of the classifier was 0.49 (−0.30 to 1.25) in cases compared to −1.04 (IQR −1.86 to −0.09) in controls, p<0.001. The 35 biomarker classifier gave sensitivity of 56%, specificity was 93% and the AUC on ROC analysis was 0.86. This study supports the potential for urinary proteomic biomarker models to assist with the diagnosis of acute stroke in those with mild symptoms. We now plan to refine further and explore the clinical utility of such a test in large prospective clinical trials
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