scholarly journals Molecular Characteristics of Rickettsia in Ticks Collected along the Southern Border of Mongolia

Pathogens ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 943
Author(s):  
Michael E. von Fricken ◽  
Matthew A. Voorhees ◽  
Jeffrey W. Koehler ◽  
Carmen Asbun ◽  
Brandon Lam ◽  
...  
Keyword(s):  
Likelihood Estimation ◽  
Amplicon Sequencing ◽  
Molecular Characteristics ◽  
Ompa Gene ◽  
Rickettsia Species ◽  
Clinical Burden ◽  
High Detection ◽  
Substantial Risk ◽  
Southern Border ◽  
Risk Of Exposure

Tick-borne infections are a significant threat to public health, particularly in regions where individuals frequently enter tick habitats. Roughly 26% of the population in Mongolia practice nomadic pastoralism and are considered at high risk of exposure to ticks and the diseases they carry. This study tested ticks from Mongolia’s southern border for Rickettsia spp. to better understand the epidemiology of tick-borne diseases in the region. Dermacentor nuttalli and Hyalomma asiaticum ticks (n = 4022) were pooled and tested for Rickettsia spp. by real-time PCR. Melt-curve analyses and Sanger sequencing were used to identify Rickettsia species. Approximately 64% of the 786 tick pools tested positive for Rickettsia bacteria. Melt curve analyses identified four different Rickettsia species circulating in these tick pools. Amplicon sequencing of the ompA gene identified Rickettsia spp. that closely resembled R. raoultii and R. sibirica. Dermacentor nuttalli ticks from Govi-Altai had the highest maximum likelihood estimation infection rate 48.4% (95% CI: 41.7–56.5%), while Hyalommaasiaticum collected in Omnogovi had a rate of 7.6% (95% CI: 6.2–9.2%). The high detection of Rickettsia suggests a substantial risk of infection in southern Mongolia. Further studies are necessary to investigate the clinical burden of tick-borne diseases in Mongolia.

scholarly journals Molecular Characteristics of Rickettsia in Ticks Collected Along the Southern Border of Mongolia

2020 ◽  
Author(s):  
Michael E. von Fricken ◽  
Matthew A. Voorhees ◽  
Jeffrey W. Koehler ◽  
Carmen Asbun ◽  
Brandon Lam ◽  
...  
Keyword(s):  
Likelihood Estimation ◽  
Amplicon Sequencing ◽  
Molecular Characteristics ◽  
Ompa Gene ◽  
Detection Rates ◽  
Rickettsia Species ◽  
Clinical Burden ◽  
Southern Border ◽  
Rickettsial Diseases ◽  
Tick Genus

Abstract Introduction: Tick-borne infectious dDermacentor and iseases represent a significant threat to public health, particularly in regions where individuals frequently enter tick habitats. This is especially true in Mongolia, where 26% of the population are pastoral herders whose lifestyle results in high risk of tick-borne diseases, which include Rickettsial diseases. In this study, ticks collected along Mongolia’s southern border were tested for the presence of Rickettsia spp. DNA to better understand the risk of this bacterial infection in the region. Methods: Dermacentor and Hyalomma ticks (n = 4,022) collected across southern Mongolia (aimags Bayankhongor, Dornogovi, Govi-Altai, Khovd, and Omnogovi) were pooled and tested for Rickettsia spp. by real-time PCR. Subsequent melt-curve analyses and Sanger sequencing were used to identify specific Rickettsia species. Results: Approximately 64% of the 786 tick pools tested positive for Rickettsia bacteria. Melt curve analyses identified between four and six different Rickettsia species circulating in these tick pools. Amplicon sequencing of the ompA gene from selected positive samples identified Rickettsia spp. that closely resembled R. raoultii and R. sibirica. Detection rates varied greatly by sampling region and tick genus. Dermacentor ticks from the Govi-Altai region had the highest maximum likelihood estimation (MLE) infection rate of 48.4% (95% CI: 41.7-56.5%) while Hyalomma ticks collected in Omnogovi had an MLE rate of 7.6% (95% CI: 6.2-9.2%). Conclusions: Multiple Rickettsia species were found to circulate at high rates within native tick species in southern Mongolia. Further studies are required to investigate the clinical burden of disease associated with these Rickettsia spp. in exposed Mongolian populations.

The DQE of an electron image recording system

1978 ◽  
Vol 36 (1) ◽  
pp. 100-101
Author(s):  
K.-H. Herrmann ◽  
D. Krahl ◽  
H.-P Rust
Keyword(s):  
Primary Electron ◽  
Ideal Case ◽  
Image Recording ◽  
Main Requirement ◽  
High Detection ◽  
Electron Image ◽  
Video Amplifier ◽  
Detection Quantum Efficiency ◽  
Selection Of ◽  
The Ideal

The high detection quantum efficiency (DQE) is the main requirement for an imagerecording system used in electron microscopy of radiation-sensitive specimens. An electronic TV system of the type shown in Fig. 1 fulfills these conditions and can be used for either analog or digital image storage and processing [1], Several sources of noise may reduce the DQE, and therefore a careful selection of various elements is imperative.The noise of target and of video amplifier can be neglected when the converter stages produce sufficient target electrons per incident primary electron. The required gain depends on the type of the tube and also on the type of the signal processing chosen. For EBS tubes, for example, it exceeds 10. The ideal case, in which all impinging electrons create uniform charge peaks at the target, is not obtainable for several reasons, and these will be discussed as they relate to a system with a scintillator, fiber-optic and photo-cathode combination as the first stage.

Electron microscopy of crystalline structure in thermotropic random copolymers

1991 ◽  
Vol 49 ◽  
pp. 1054-1055
Author(s):  
Afzana Anwer ◽  
S. Eilidh Bedford ◽  
Richard J. Spontak ◽  
Alan H. Windle
Keyword(s):  
Electron Microscopy ◽  
Crystalline Structure ◽  
Liquid Crystalline ◽  
Elevated Temperatures ◽  
Random Copolymers ◽  
Molecular Characteristics ◽  
Scanning Calorimetry ◽  
X Ray ◽  
Identical Monomer ◽  
Periodic Layer

Random copolyesters composed of wholly aromatic monomers such as p-oxybenzoate (B) and 2,6-oxynaphthoate (N) are known to exhibit liquid crystalline characteristics at elevated temperatures and over a broad composition range. Previous studies employing techniques such as X-ray diffractometry (XRD) and differential scanning calorimetry (DSC) have conclusively proven that these thermotropic copolymers can possess a significant crystalline fraction, depending on molecular characteristics and processing history, despite the fact that the copolymer chains possess random intramolecular sequencing. Consequently, the nature of the crystalline structure that develops when these materials are processed in their mesophases and subsequently annealed has recently received considerable attention. A model that has been consistent with all experimental observations involves the Non-Periodic Layer (NPL) crystallite, which occurs when identical monomer sequences enter into register between adjacent chains. The objective of this work is to employ electron microscopy to identify and characterize these crystallites.

A Cautionary Note on Incremental Fit Indices Reported by LISREL

Methodology ◽  
2005 ◽  
Vol 1 (2) ◽  
pp. 81-85 ◽  
Author(s):  
Stefan C. Schmukle ◽  
Jochen Hardt
Keyword(s):  
Factor Analysis ◽  
Maximum Likelihood ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Null Model ◽  
Likelihood Estimation ◽  
Parameter Estimates ◽  
Fit Indices ◽  
Cautionary Note ◽  
Confirmatory Factor

Abstract. Incremental fit indices (IFIs) are regularly used when assessing the fit of structural equation models. IFIs are based on the comparison of the fit of a target model with that of a null model. For maximum-likelihood estimation, IFIs are usually computed by using the χ2 statistics of the maximum-likelihood fitting function (ML-χ2). However, LISREL recently changed the computation of IFIs. Since version 8.52, IFIs reported by LISREL are based on the χ2 statistics of the reweighted least squares fitting function (RLS-χ2). Although both functions lead to the same maximum-likelihood parameter estimates, the two χ2 statistics reach different values. Because these differences are especially large for null models, IFIs are affected in particular. Consequently, RLS-χ2 based IFIs in combination with conventional cut-off values explored for ML-χ2 based IFIs may lead to a wrong acceptance of models. We demonstrate this point by a confirmatory factor analysis in a sample of 2449 subjects.

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