Uterine Environment and Pregnancy Rate of Heiferswith High Blood Urea Concentrations

Reports demonstrate that excess dietary protein significantly alters the ionic composition of uterine fluid during the luteal phase ultimately decreasing fertility. Since the early bovine embryo cannot adapt to changes in the uterine environment, changes in the concentrations of ions (pH) in the uterus can be unfavorable to embryo development and survival therefore having negative effects on fertility. In this study, heifers fed a high protein diet had elevated systemic concentrations of plasma urea nitrogen (PUN) compared to heifers fed a control diet. However, there was no deleterious effect on uterine pH or reproductive success. In summary, excess protein in a diet did increase PUNs to a concentration that has previously been reported to be detrimental to pregnancy success; however, there was no negative effect on uterine pH or pregnancy success

First imaging results from the Iapetus B/C flyby of the Cassini spacecraft

Cassini had a relatively close flyby at Iapetus on New Year's Eve 2005. The 288 ISS images set various constraints on the origin theories of the dark/bright dichotomy, as revealed multiple surface structures at up to 740 m/pxl size

Palaeoproterozoic magnesite: lithological and isotopic evidence for playa/sabkha environments

Magnesite forms a series of 1- to 15-m-thick beds within the approximate to2.0 Ga (Palaeoproterozoic) Tulomozerskaya Formation, NW Fennoscandian Shield, Russia. Drillcore material together with natural exposures reveal that the 680-m-thick formation is composed of a stromatolite-dolomite-'red bed' sequence formed in a complex combination of shallow-marine and non-marine, evaporitic environments. Dolomite-collapse breccia, stromatolitic and micritic dolostones and sparry allochemical dolostones are the principal rocks hosting the magnesite beds. All dolomite lithologies are marked by delta C-13 values from +7.1 parts per thousand to +11.6 parts per thousand (V-PDB) and delta O-18 ranging from 17.4 parts per thousand to 26.3 parts per thousand (V-SMOW). Magnesite occurs in different forms: finely laminated micritic; stromatolitic magnesite; and structureless micritic, crystalline and coarsely crystalline magnesite. All varieties exhibit anomalously high delta C-13 values ranging from +9.0 parts per thousand to +11.6 parts per thousand and delta O-18 values of 20.0-25.7 parts per thousand. Laminated and structureless micritic magnesite forms as a secondary phase replacing dolomite during early diagenesis, and replaced dolomite before the major phase of burial. Crystalline and coarsely crystalline magnesite replacing micritic magnesite formed late in the diagenetic/metamorphic history. Magnesite apparently precipitated from sea water-derived brine, diluted by meteoric fluids. Magnesitization was accomplished under evaporitic conditions (sabkha to playa lake environment) proposed to be similar to the Coorong or Lake Walyungup coastal playa magnesite. Magnesite and host dolostones formed in evaporative and partly restricted environments; consequently, extremely high delta C-13 values reflect a combined contribution from both global and local carbon reservoirs. A C- 13-rich global carbon reservoir (delta C-13 at around +5 parts per thousand) is related to the perturbation of the carbon cycle at 2.0 Ga, whereas the local enhancement in C-13 (up to +12 parts per thousand) is associated with evaporative and restricted environments with high bioproductivity

Controlled human malaria infection with graded numbers of Plasmodium falciparum NF135.C10- or NF166.C8-infected mosquitoes

Controlled human malaria infections (CHMIs) with Plasmodium falciparum (Pf) parasites are well established. Exposure to five Pf (NF54)-infected Anopheles mosquitoes results in 100% infection rates in malaria-näive volunteers. Recently Pf clones NF135.C10 and NF166.C8 were generated for application in CHMIs. Here, we tested the clinical infection rates of these clones, using graded numbers of Pf-infected mosquitoes. In a double-blind randomized trial, we exposed 24 malaria-näive volunteers to bites from one, two, or five mosquitoes infected with NF135.C10 or NF166.C8. The primary endpoint was parasitemia by quantitative polymerase chain reaction. For both strains, bites by five infected mosquitoes resulted in parasitemiain4/4 volunteers; 3/4 volunteers developed parasitemia after exposure to one or two infected mosquitoes infected with either clone. The prepatent period was 7.25 ± 4.0 days (median ± range). There were no serious adverse events and comparable clinical symptoms between all groups. These data confirm the eligibility of NF135.C10 and NF166.C8 for use in CHMI studies

A simple model to quantitatively account for periodic outbreaks of the measles in the Dutch Bible Belt

In the Netherlands there has been nationwide vaccination against the measles since 1976. However, in small clustered communities of orthodox Protestants there is widespread refusal of the vaccine. After 1976, three large outbreaks with about 3000 reported cases of the measles have occurred among these orthodox Protestants. The outbreaks appear to occur about every twelve years. We show how a simple Kermack-McKendrick-like model can quantitatively account for the periodic outbreaks. Approximate analytic formulae to connect the period, size, and outbreak duration are derived. With an enhanced model we take the latency period in account. We also expand the model to follow how different age groups are affected. Like other researchers using other methods, we conclude that large scale underreporting of the disease must occur

High-resolution SMA imaging of bright submillimetre sources from the SCUBA-2 Cosmology Legacy Survey

Large scale structure and cosmolog

The influence of racial factors on psychiatric diagnosis: A review and suggestions for research

Research on race and diagnosis initially focused on black-white differences in depression and schizophrenia. Statistics showing a higher treated prevalence of schizophrenia and a lower prevalence of depression for blacks seemed to support the claim that blacks did not suffer from depression. Others argued, however, that clinicians were misdiagnosing depression in blacks. This article reviews empirical studies of racial differences in individual symptoms and summarizes the evidence on misdiagnosis. It argues that more attention must be paid to resolving two contradictory assumptions made by researchers working in the area of race and diagnostic inference: (1) blacks and whites exhibit symptomatology similarly but diagnosticians mistakenly assume that they are different; (2) blacks and whites display psychopathology in different ways but diagnosticians are unaware of or insensitive to such cultural differences. The article concludes with suggested research directions and a discussion of critical research issues.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44303/1/10597_2004_Article_BF00755677.pd

Interdisciplinary-driven hypotheses on spatial associations of mixtures of industrial air pollutants with adverse birth outcomes

Background: Adverse birth outcomes (ABO) such as prematurity and small for gestational age confer a high risk of mortality and morbidity. ABO have been linked to air pollution; however, relationships with mixtures of industrial emissions are poorly understood. The exploration of relationships between ABO and mixtures is complex when hundreds of chemicals are analyzed simultaneously, requiring the use of novel approaches. Objective: We aimed to generate robust hypotheses spatially linking mixtures and the occurrence of ABO using a spatial data mining algorithm and subsequent geographical and statistical analysis. The spatial data mining approach aimed to reduce data dimensionality and efficiently identify spatial associations between multiple chemicals and ABO. Methods: We discovered co-location patterns of mixtures and ABO in Alberta, Canada (2006–2012). An ad-hoc spatial data mining algorithm allowed the extraction of primary co-location patterns of 136 chemicals released into the air by 6279 industrial facilities (National Pollutant Release Inventory), wind-patterns from 182 stations, and 333,247 singleton live births at the maternal postal code at delivery (Alberta Perinatal Health Program), from which we identified cases of preterm birth, small for gestational age, and low birth weight at term. We selected secondary patterns using a lift ratio metric from ABO and non-ABO impacted by the same mixture. The relevance of the secondary patterns was estimated using logistic models (adjusted by socioeconomic status and ABO-related maternal factors) and a geographic-based assignment of maternal exposure to the mixtures as calculated by kernel density. Results: From 136 chemicals and three ABO, spatial data mining identified 1700 primary patterns from which five secondary patterns of three-chemical mixtures, including particulate matter, methyl-ethyl-ketone, xylene, carbon monoxide, 2-butoxyethanol, and n-butyl alcohol, were subsequently analyzed. The significance of the associations (odds ratio > 1) between the five mixtures and ABO provided statistical support for a new set of hypotheses. Conclusion: This study demonstrated that, in complex research settings, spatial data mining followed by pattern selection and geographic and statistical analyses can catalyze future research on associations between air pollutant mixtures and adverse birth outcomes

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)