The role of cholinesterases in chagas disease.

Acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) hydrolyze acetylcholine (ACh) in neural synaptic clefts and are primarily found in erythrocytes and blood plasma, respectively. Besides inactivating ACh, cholinesterases may play a non-classical role in inflammation and in immune response. In a previous study, we reported that BChE levels were decreased in chronic Chagas disease patients presenting the mega syndromes. In this series, we reported that: i) the activity of AChE did not differ between patients and controls, irrespective of the presence or not of the 1057C > A ACHE polymorphism, and ii) the increased BChE levels modestly influenced the AChE activity in Chagas disease.

Dynamics of data availability in disease modeling: An example evaluating the trade-offs of ultra-fine-scale factors applied to human West Nile virus disease models in the Chicago area, USA.

BACKGROUND: Since 1999, West Nile virus (WNV) has moved rapidly across the United States, resulting in tens of thousands of human cases. Both the number of human cases and the minimum infection rate (MIR) in vector mosquitoes vary across time and space and are driven by numerous abiotic and biotic forces, ranging from differences in microclimates to socio-demographic factors. Because the interactions among these multiple factors affect the locally variable risk of WNV illness, it has been especially difficult to model human disease risk across varying spatial and temporal scales. Cook and DuPage Counties, comprising the city of Chicago and surrounding suburbs, experience some of the highest numbers of human neuroinvasive cases of WNV in the United States. Despite active mosquito control efforts, there is consistent annual WNV presence, resulting in more than 285 confirmed WNV human cases and 20 deaths from the years 2014-2018 in Cook County alone. METHODS: A previous Chicago-area WNV model identified the fifty-five most high and low risk locations in the Northwest Mosquito Abatement District (NWMAD), an enclave » the size of the combined Cook and DuPage county area. In these locations, human WNV risk was stratified by model performance, as indicated by differences in studentized residuals. Within these areas, an additional two-years of field collections and data processing was added to a 12-year WNV dataset that includes human cases, MIR, vector abundance, and land-use, historical climate, and socio-economic and demographic variables, and was assessed by an ultra-fine-scale (1 km spatial x 1 week temporal resolution) multivariate logistic regression model. RESULTS: Multivariate statistical methods applied to the ultra-fine-scale model identified fewer explanatory variables while improving upon the fit of the previous model. Beyond MIR and climatic factors, efforts to acquire additional covariates only slightly improved model predictive performance. CONCLUSIONS: These results suggest human WNV illness in the Chicago area may be associated with fewer, but increasingly critical, key variables at finer scales. Given limited resources, these findings suggest large variations in model performance occur, depending on covariate availability, and provide guidance in variable selection for optimal WNV human illness modeling.

Historical Expansion of Kyasanur Forest Disease in India From 1957 to 2017: A Retrospective Analysis.

A highly infectious tick-borne virus causes Kyasanur Forest disease (KFD), which has been expanding in recent decades in India. Current studies do not provide an updated understanding of the disease trends and its expansion in India. We address this gap in the literature through a detailed review to reveal the annual historic expansion of KFD cases across the span of years from 1957 to 2017. In addition, we explore the factors that may have led to the geographic expansion of KFD. The annual numbers of cases of KFD among humans are estimated using peer-reviewed journal articles, Pro-MED database, historical and archived newspapers, and government reports, technical reports, publications, and medical websites. From 1957 to 2017, there were an estimated 9,594 cases of KFD within 16 districts in India. The most significant human outbreaks of the disease were in the years 1957-1958 (681 cases), 1983-1984 (2,589 cases), 2002-2003 (1,562 cases), and 2016-2017 (809 cases). In 2015, KFD appeared in Goa. In 2016, new cases emerged in Belgaum, a district in Karnataka state, and in the Sindhudurg district in Maharashtra state. The processes by which KFD persists and spreads are not clear, but demographic, socioeconomic, political, and environmental factors seem to play a role.

A novel anaerobic filter membrane bioreactor: prototype start-up and filtration assays.

Anaerobic digestion allows efficient treatment of high loaded wastewater, and membrane technology allows obtaining high quality effluents with complete biomass retention. However, high biomass concentration interferes with membrane fouling. In the present work, a new bioreactor that integrates an attached biomass anaerobic culture on a fixed bed and a submerged membrane has been started up. The recirculation between the digestion and filtration chambers is coupled to the gas-lift effect of the bubbling employed for the scouring of the membranes, avoiding the use or electromechanical pumps that damage the suspended biomass. The support material retains the biomass in the digestion tank despite the downwards flow, avoiding the submerged membrane contacting with a high concentrated suspension. This novel system, called an anaerobic filter membrane bioreactor was immediately started up, achieving chemical oxygen demand (COD) removal efficiencies of 96% at an organic loading rate (OLR) of 7 kg COD/m3·d. In order to select filtration flux, specific gas demand and filtration cycle duration, the results of 15 short term assays, eight hours for each one, is presented for fluxes between 15.7 and 17.7 L/m2·h, cycle duration between 10 and 30 minutes, and three levels of scouring. It was checked that reversible and irreversible fouling were directly related when dTMP/dt > 2.5 mbar/min.

Assessing human risk of illness with West Nile virus mosquito surveillance data to improve public health preparedness.

Surveillance for West Nile virus (WNV) and other mosquito-borne pathogens involves costly and time-consuming collection and testing of mosquito samples. One difficulty faced by public health personnel is how to interpret mosquito data relative to human risk, thus leading to a failure to fully exploit the information from mosquito testing. The objective of our study was to use the information gained from historic West Nile virus mosquito testing to determine human risk relative to mosquito infection and to assess the usefulness of our mosquito infection forecasting models to give advance warning. We compared weekly mosquito infection rates from 2004 to 2013 to WNV case numbers in Illinois. We then developed a weather-based forecasting model to estimate the WNV mosquito infection rate one to 3 weeks ahead of mosquito testing both statewide and for nine regions of Illinois. We further evaluated human illness risk relative to both the measured and the model-estimated infection rates to provide guidelines for public health messages. We determined that across 10 years, over half of human WNV cases occurred following the 29 (of 210) weeks with the highest mosquito infection rates. The values forecasted by the models can identify those time periods, but model results and data availability varied by region with much stronger results obtained from regions with more mosquito data. The differences among the regions may be related to the amount of surveillance or may be due to diverse landscape characteristics across Illinois. We set the stage for better use of all surveillance options available for WNV and described an approach to modelling that can be expanded to other mosquito-borne illnesses.

Predicting West Nile Virus Infection Risk From the Synergistic Effects of Rainfall and Temperature.

Mosquito-based surveillance is a practical way to estimate the risk of transmission of West Nile virus (WNV) to people. Variations in temperature and precipitation play a role in driving mosquito infection rates and transmission of WNV, motivating efforts to predict infection rates based on prior weather conditions. Weather conditions and sequential patterns of meteorological events can have particularly important, but regionally distinctive, consequences for WNV transmission, with high temperatures and low precipitation often increasing WNV mosquito infection. Predictive models that incorporate weather can thus be used to provide early indications of the risk of WNV infection. The purpose of this study was first, to assess the ability of a previously published model of WNV mosquito infection to predict infection for an area within the region for which it was developed, and second, to improve the predictive ability of this model by incorporating new weather factors that may affect mosquito development. The legacy model captured the primary trends in mosquito infection, but it was improved considerably when calibrated with local mosquito infection rates. The use of interaction terms between precipitation and temperature improved model performance. Specifically, temperature had a stronger influence than rainfall, so that lower than average temperature greatly reduced the effect of low rainfall on increased infection rates. When rainfall was lower, high temperature had an even stronger positive impact on infection rates. The final model is practical, stable, and operationally valid for predicting West Nile virus infection rates in future weeks when calibrated with local data.

The PTPN22 1858T allele but not variants in the proximal promoter region of IL-21 gene is associated with the susceptibility to type 1 diabetes and the presence of autoantibodies in a Brazilian cohort.

Interleukin (IL)-21 and protein tyrosine phosphatase non-receptor 22 (PTPN22) regulate lymphocyte function and have been implicated in the pathogenesis of autoimmune diabetes. We sequenced the proximal promoter of the IL-21 gene for the first time and analysed the PTPN22 1858T polymorphism in type 1A diabetes (T1AD) patients and healthy controls (HC). We correlated the frequencies of islet and extra-pancreatic autoantibodies with genotypes from both loci. The case series comprised 612 T1AD patients and 792 HC. Genotyping of PTPN22 C1858T was performed on 434 T1AD patients and 689 HC. The -448 to +83 base pairs (bp) region of the IL-21 gene was sequenced in 309 Brazilian T1AD and 189 HC subjects. We also evaluated human leucocyte antigen (HLA) DR3/DR4 alleles. The frequencies of glutamic acid decarboxylase (GAD65), tyrosine phosphatase-like protein (IA)-2, anti-nuclear antibody (ANA), thyroid peroxidase (TPO), thyroglobulin (TG), thyrotrophin receptor autoantibody (TRAb), anti-smooth muscle (ASM) and 21-hydroxylase (21-OH) autoantibodies were higher in T1AD patients than in HC. The PTPN22 1858T allele was associated with an increased risk for developing T1AD [odds ratio (OR) = 1·94; P < 0·001], particularly in patients of European ancestry, and with a higher frequency of GAD65 and TG autoantibodies. HLA-DR3/DR4 alleles predominated in T1AD patients. A heterozygous allelic IL-21 gene variant (g.-241 T > A) was found in only one patient. In conclusion, only PTPN22 C1858T polymorphism and HLA-DR3 and/or DR4 alleles, but not allelic variants in the 5'-proximal region of the IL-21 gene were associated with T1AD risk. Patients with T1AD had increased frequencies of anti-islet-cell, anti-thyroid, anti-nuclear, anti-smooth muscle and anti-21-OH autoantibodies. The C1858T PTPN22 polymorphism was also associated with a higher frequency of GAD65 and TG autoantibodies.

Haplotype frequencies of the PowerPlex Y system in a Mexican-Mestizo population sample from Mexico City.

The PowerPlex Y system including 11 Y-STRs (DYS19, DYS389I/II, DYS390, DYS391, DYS392, DYS393, DYS385, DYS437, DYS438 and DYS439) was analyzed by capillary electrophoresis in 357 males from Mexico City. Haplotype frequency for this system was reported. The haplotype diversity was 99.56+/-0.04%, and gene diversity ranged from 51.4% for DYS393 to 92.5% for DYS385. AMOVA tests including previous reports from Mexico (Chihuahua and Jalisco States), demonstrated significant genetic heterogeneity between north and western populations regarding Mexico City, justifying the establishment of local databases in this country for male-identification purposes.

Population data for 15 loci (Identifiler Kit) in a sample from the Valley of Mexico.

We analyzed 242 individuals from the Valley of Mexico, including the larger and more cosmopolitan city of this country. They were PCR-typed for 15 STR loci with the AmpFlSTR Identifiler PCR Amplification Kit (Applied Biosystems). Allele frequencies for each STR were estimated and compared to previous reports. Genotype distribution by locus and by two-loci combination was in agreement with Hardy-Weinberg expectations for all fifteen STRs. This STR system in Mexican-mestizos presented a combined probability of exclusion (PE) and discrimination (PD) longer than 99.999%, respectively.