On groundwater fluctuations, evapotranspiration, and understory removal in riparian corridors

This study utilizes 7 years of continuously monitored groundwater-level data from four sites along the Río Grande riparian corridor in central New Mexico to calculate evapotranspiration from groundwater and assess impacts of understory vegetation removal during a restoration project. Diurnal groundwater fluctuation measurements were used to compare the well-known White method for estimating evapotranspiration from groundwater (ETg) to colocated measurements of total riparian evapotranspiration (ET) measured using the eddy covariance method. On average, the two methods were linearly correlated and had similar variability, but groundwater hydrograph estimates of ET g tended to be larger than tower ET estimates. Average ETg estimates for two wells at one site ranged from 91.45% to 164.77% of measured tower ET estimates, but were also shown to range from 57.35% to 254.34% at another site. Comparisons between the methods improved with deeper water tables, reduced groundwater and river connectivity, and where soil profiles were dominated by coarse-sized particles. Using a range of texture-based estimates of specific yield (Sy) with water table position improves the field application of the White method. River-induced fluctuations in groundwater increased the variability of ETg measurements. Removal of understory vegetation at one site resulted in a small but significant reduction in diel groundwater fluctuation amplitude of 19-21%. Caution is required when understory vegetation removal is used as a means to decrease overall riparian ET. Diel groundwater fluctuation amplitudes can be useful in gauging the hydrological effects of vegetation removal. Riparian groundwater hydrographs are critical to investigating the hydrologic connectivity between river and shallow groundwater, the temporal patterns of vegetative consumption, and monitoring changes to the vegetation community. Copyright 2009 by the American Geophysical Union

Effect of a 14-day course of systemic corticosteroids on the hypothalamic-pituitary-adrenal-axis in patients with acute exacerbation of chronic obstructive pulmonary disease

<p/> <p>Background</p> <p>As supra-physiological intake of corticosteroids is a well known risk factor for the development of adrenal insufficiency, we investigated the function of the hypothalamic-pituitary-adrenal (HPA) axis during a 14-day course of systemic corticosteroids in patients with acute exacerbation of chronic obstructive pulmonary disease using clinical and laboratory measures.</p> <p>Methods</p> <p>A systematic clinical and laboratory assessment including measurement of basal cortisol levels and the response to low dose (1 μg) ACTH stimulation was performed in nine patients before, on the first and the last day of treatment, as well as 2, 7 and 21 days after corticosteroid withdrawal.</p> <p>Results</p> <p>At baseline, all nine patients had normal responses to 1 μg ACTH. On the first day of steroid treatment, 78% had a blunted peak cortisol response. This percentage increased to 89% after 14 days of steroid treatment. 78%, 33% and 33% of the patients had a blunted cortisol response to ACTH 2, 7, and 21 days after corticosteroid withdrawal, respectively. ROC curve analysis revealed that only basal cortisol concentrations (AUC 0.89), but not ACTH concentrations (AUC 0.49) or clinical signs (AUC 0.47) were predictive of an impaired function of the HPA axis. Basal cortisol levels of > 400 and < 150 nmol/l were 96% and 100% sensitive for a normal or pathological response to the ACTH stimulation test, respectively.</p> <p>Conclusion</p> <p>Immediate and prolonged suppression of the HPA axis is a common finding in otherwise asymptomatic patients undergoing systemic steroid treatment for acute exacerbation of chronic obstructive pulmonary disease and can reliably be assessed with the low-dose ACTH test.</p

Role of biomarkers in early infectious complications after lung transplantation

Background Infections and primary graft dysfunction are devastating complications in the immediate postoperative period following lung transplantation. Nowadays, reliable diagnostic tools are not available. Biomarkers could improve early infection diagnosis. Methods Multicentre prospective observational study that included all centres authorized to perform lung transplantation in Spain. Lung infection and/or primary graft dysfunction presentation during study period (first postoperative week) was determined. Biomarkers were measured on ICU admission and daily till ICU discharge or for the following 6 consecutive postoperative days. Results We included 233 patients. Median PCT levels were significantly lower in patients with no infection than in patients with Infection on all follow up days. PCT levels were similar for PGD grades 1 and 2 and increased significantly in grade 3. CRP levels were similar in all groups, and no significant differences were observed at any study time point. In the absence of PGD grade 3, PCT levels above median (0.50 ng/ml on admission or 1.17 ng/ml on day 1) were significantly associated with more than two- and three-fold increase in the risk of infection (adjusted Odds Ratio 2.37, 95% confidence interval 1.06 to 5.30 and 3.44, 95% confidence interval 1.52 to 7.78, respectively). Conclusions In the absence of severe primary graft dysfunction, procalcitonin can be useful in detecting infections during the first postoperative week. PGD grade 3 significantly increases PCT levels and interferes with the capacity of PCT as a marker of infection. PCT was superior to CRP in the diagnosis of infection during the study period

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Achieving Optimal Growth through Product Feedback Inhibition in Metabolism

Recent evidence suggests that the metabolism of some organisms, such as Escherichia coli, is remarkably efficient, producing close to the maximum amount of biomass per unit of nutrient consumed. This observation raises the question of what regulatory mechanisms enable such efficiency. Here, we propose that simple product-feedback inhibition by itself is capable of leading to such optimality. We analyze several representative metabolic modules—starting from a linear pathway and advancing to a bidirectional pathway and metabolic cycle, and finally to integration of two different nutrient inputs. In each case, our mathematical analysis shows that product-feedback inhibition is not only homeostatic but also, with appropriate feedback connections, can minimize futile cycling and optimize fluxes. However, the effectiveness of simple product-feedback inhibition comes at the cost of high levels of some metabolite pools, potentially associated with toxicity and osmotic imbalance. These large metabolite pool sizes can be restricted if feedback inhibition is ultrasensitive. Indeed, the multi-layer regulation of metabolism by control of enzyme expression, enzyme covalent modification, and allostery is expected to result in such ultrasensitive feedbacks. To experimentally test whether the qualitative predictions from our analysis of feedback inhibition apply to metabolic modules beyond linear pathways, we examine the case of nitrogen assimilation in E. coli, which involves both nutrient integration and a metabolic cycle. We find that the feedback regulation scheme suggested by our mathematical analysis closely aligns with the actual regulation of the network and is sufficient to explain much of the dynamical behavior of relevant metabolite pool sizes in nutrient-switching experiments

Heterogeneity of mammary lesions represent molecular differences

BACKGROUND: Human breast cancer is a heterogeneous disease, histopathologically, molecularly and phenotypically. The molecular basis of this heterogeneity is not well understood. We have used a mouse model of DCIS that consists of unique lines of mammary intraepithelial neoplasia (MIN) outgrowths, the premalignant lesion in the mouse that progress to invasive carcinoma, to understand the molecular changes that are characteristic to certain phenotypes. Each MIN-O line has distinguishable morphologies, metastatic potentials and estrogen dependencies. METHODS: We utilized oligonucleotide expression arrays and high resolution array comparative genomic hybridization (aCGH) to investigate whole genome expression patterns and whole genome aberrations in both the MIN-O and tumor from four different MIN-O lines that each have different phenotypes. From the whole genome analysis at 35 kb resolution, we found that chromosome 1, 2, 10, and 11 were frequently associated with whole chromosome gains in the MIN-Os. In particular, two MIN-O lines had the majority of the chromosome gains. Although we did not find any whole chromosome loss, we identified 3 recurring chromosome losses (2F1-2, 3E4, 17E2) and two chromosome copy number gains on chromosome 11. These interstitial deletions and duplications were verified with a custom made array designed to interrogate the specific regions at approximately 550 bp resolution. RESULTS: We demonstrated that expression and genomic changes are present in the early premalignant lesions and that these molecular profiles can be correlated to phenotype (metastasis and estrogen responsiveness). We also identified expression changes associated with genomic instability. Progression to invasive carcinoma was associated with few additional changes in gene expression and genomic organization. Therefore, in the MIN-O mice, early premalignant lesions have the major molecular and genetic changes required and these changes have important phenotypic significance. In contrast, the changes that occur in the transition to invasive carcinoma are subtle, with few consistent changes and no association with phenotype. CONCLUSION: We propose that the early lesions carry the important genetic changes that reflect the major phenotypic information, while additional genetic changes that accumulate in the invasive carcinoma are less associated with the overall phenotype

Structural Heterogeneity and Quantitative FRET Efficiency Distributions of Polyprolines through a Hybrid Atomistic Simulation and Monte Carlo Approach

Förster Resonance Energy Transfer (FRET) experiments probe molecular distances via distance dependent energy transfer from an excited donor dye to an acceptor dye. Single molecule experiments not only probe average distances, but also distance distributions or even fluctuations, and thus provide a powerful tool to study biomolecular structure and dynamics. However, the measured energy transfer efficiency depends not only on the distance between the dyes, but also on their mutual orientation, which is typically inaccessible to experiments. Thus, assumptions on the orientation distributions and averages are usually made, limiting the accuracy of the distance distributions extracted from FRET experiments. Here, we demonstrate that by combining single molecule FRET experiments with the mutual dye orientation statistics obtained from Molecular Dynamics (MD) simulations, improved estimates of distances and distributions are obtained. From the simulated time-dependent mutual orientations, FRET efficiencies are calculated and the full statistics of individual photon absorption, energy transfer, and photon emission events is obtained from subsequent Monte Carlo (MC) simulations of the FRET kinetics. All recorded emission events are collected to bursts from which efficiency distributions are calculated in close resemblance to the actual FRET experiment, taking shot noise fully into account. Using polyproline chains with attached Alexa 488 and Alexa 594 dyes as a test system, we demonstrate the feasibility of this approach by direct comparison to experimental data. We identified cis-isomers and different static local environments as sources of the experimentally observed heterogeneity. Reconstructions of distance distributions from experimental data at different levels of theory demonstrate how the respective underlying assumptions and approximations affect the obtained accuracy. Our results show that dye fluctuations obtained from MD simulations, combined with MC single photon kinetics, provide a versatile tool to improve the accuracy of distance distributions that can be extracted from measured single molecule FRET efficiencies

Identification, Replication, and Functional Fine-Mapping of Expression Quantitative Trait Loci in Primary Human Liver Tissue

The discovery of expression quantitative trait loci (“eQTLs”) can help to unravel genetic contributions to complex traits. We identified genetic determinants of human liver gene expression variation using two independent collections of primary tissue profiled with Agilent (n = 206) and Illumina (n = 60) expression arrays and Illumina SNP genotyping (550K), and we also incorporated data from a published study (n = 266). We found that ∼30% of SNP-expression correlations in one study failed to replicate in either of the others, even at thresholds yielding high reproducibility in simulations, and we quantified numerous factors affecting reproducibility. Our data suggest that drug exposure, clinical descriptors, and unknown factors associated with tissue ascertainment and analysis have substantial effects on gene expression and that controlling for hidden confounding variables significantly increases replication rate. Furthermore, we found that reproducible eQTL SNPs were heavily enriched near gene starts and ends, and subsequently resequenced the promoters and 3′UTRs for 14 genes and tested the identified haplotypes using luciferase assays. For three genes, significant haplotype-specific in vitro functional differences correlated directly with expression levels, suggesting that many bona fide eQTLs result from functional variants that can be mechanistically isolated in a high-throughput fashion. Finally, given our study design, we were able to discover and validate hundreds of liver eQTLs. Many of these relate directly to complex traits for which liver-specific analyses are likely to be relevant, and we identified dozens of potential connections with disease-associated loci. These included previously characterized eQTL contributors to diabetes, drug response, and lipid levels, and they suggest novel candidates such as a role for NOD2 expression in leprosy risk and C2orf43 in prostate cancer. In general, the work presented here will be valuable for future efforts to precisely identify and functionally characterize genetic contributions to a variety of complex traits

Interaction of SET domains with histones and nucleic acid structures in active chromatin

Changes in the normal program of gene expression are the basis for a number of human diseases. Epigenetic control of gene expression is programmed by chromatin modifications—the inheritable “histone code”—the major component of which is histone methylation. This chromatin methylation code of gene activity is created upon cell differentiation and is further controlled by the “SET” (methyltransferase) domain proteins which maintain this histone methylation pattern and preserve it through rounds of cell division. The molecular principles of epigenetic gene maintenance are essential for proper treatment and prevention of disorders and their complications. However, the principles of epigenetic gene programming are not resolved. Here we discuss some evidence of how the SET proteins determine the required states of target genes and maintain the required levels of their activity. We suggest that, along with other recognition pathways, SET domains can directly recognize the nucleosome and nucleic acids intermediates that are specific for active chromatin regions

The impact of diabetes on the pathogenesis of sepsis

Diabetes is associated with an increased susceptibility to infection and sepsis. Conflicting data exist on whether the mortality of patients with sepsis is influenced by the presence of diabetes, fuelling the ongoing debate on the benefit of tight glucose regulation in patients with sepsis. The main reason for which diabetes predisposes to infection appears to be abnormalities of the host response, particularly in neutrophil chemotaxis, adhesion and intracellular killing, defects that have been attributed to the effect of hyperglycaemia. There is also evidence for defects in humoral immunity, and this may play a larger role than previously recognised. We review the literature on the immune response in diabetes and its potential contribution to the pathogenesis of sepsis. In addition, the effect of diabetes treatment on the immune response is discussed, with specific reference to insulin, metformin, sulphonylureas and thiazolidinediones