Reversed-phase liquid chromatography coupled on-line to estrogen receptor bioaffinity detection based on fluorescence polarization

We describe the development and validation of a high-resolution screening (HRS) platform which couples gradient reversed-phase high-performance liquid chromatography (RP-HPLC) on-line to estrogen receptor α (ERα) affinity detection using fluorescence polarization (FP). FP, which allows detection at high wavelengths, limits the occurrence of interference from the autofluorescence of test compounds in the bioassay. A fluorescein-labeled estradiol derivative (E2-F) was synthesized and a binding assay was optimized in platereader format. After subsequent optimization in flow-injection analysis (FIA) mode, the optimized parameters were translated to the on-line HRS bioassay. Proof of principle was demonstrated by separating a mixture of five compounds known to be estrogenic (17β-estradiol, 17α-ethinylestradiol and the phytoestrogens coumestrol, coumarol and zearalenone), followed by post-column bioaffinity screening of the individual affinities for ERα. Using the HRS-based FP setup, we were able to screen affinities of off-line-generated metabolites of zearalenone for ERα. It is concluded that the on-line FP-based bioassay can be used to screen for the affinity of compounds without the disturbing occurrence of autofluorescence

Macroscopic superposition states of ultracold bosons in a double-well potential

We present a thorough description of the physical regimes for ultracold bosons in double wells, with special attention paid to macroscopic superpositions (MSs). We use a generalization of the Lipkin-Meshkov-Glick Hamiltonian of up to eight single particle modes to study these MSs, solving the Hamiltonian with a combination of numerical exact diagonalization and high-order perturbation theory. The MS is between left and right potential wells; the extreme case with all atoms simultaneously located in both wells and in only two modes is the famous NOON state, but our approach encompasses much more general MSs. Use of more single particle modes brings dimensionality into the problem, allows us to set hard limits on the use of the original two-mode LMG model commonly treated in the literature, and also introduces a new mixed Josephson-Fock regime. Higher modes introduce angular degrees of freedom and MS states with different angular properties.Comment: 15 pages, 8 figures, 1 table. Mini-review prepared for the special issue of Frontiers of Physics "Recent Progresses on Quantum Dynamics of Ultracold Atoms and Future Quantum Technologies", edited by Profs. Lee, Ueda, and Drummon

High-Throughput Screening for Modulators of CFTR Activity Based on Genetically Engineered Cystic Fibrosis Disease-Specific iPSCs

Organotypic culture systems from disease-specific induced pluripotent stem cells (iPSCs) exhibit obvious advantages compared with immortalized cell lines and primary cell cultures, but implementation of iPSC-based high-throughput (HT) assays is still technically challenging. Here, we demonstrate the development and conduction of an organotypic HT Cl/I exchange assay using cystic fibrosis (CF) disease-specific iPSCs. The introduction of a halide-sensitive YFP variant enabled automated quantitative measurement of Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) function in iPSC-derived intestinal epithelia. CFTR function was partially rescued by treatment with VX-770 and VX-809, and seamless gene correction of the p.Phe508del mutation resulted in full restoration of CFTR function. The identification of a series of validated primary hits that improve the function of p.Phe508del CFTR from a library of 42,500 chemical compounds demonstrates that the advantages of complex iPSC-derived culture systems for disease modeling can also be utilized for drug screening in a true HT format

A technical framework for costing health workforce retention schemes in remote and rural areas

<p>Abstract</p> <p>Background</p> <p>Increasing the availability of health workers in remote and rural areas through improved health workforce recruitment and retention is crucial to population health. However, information about the costs of such policy interventions often appears incomplete, fragmented or missing, despite its importance for the sound selection, planning, implementation and evaluation of these policies. This lack of a systematic approach to costing poses a serious challenge for strong health policy decisions.</p> <p>Methods</p> <p>This paper proposes a framework for carrying out a costing analysis of interventions to increase the availability of health workers in rural and remote areas with the aim to help policy decision makers. It also underlines the importance of identifying key sources of financing and of assessing financial sustainability.</p> <p>The paper reviews the evidence on costing interventions to improve health workforce recruitment and retention in remote and rural areas, provides guidance to undertake a costing evaluation of such interventions and investigates the role and importance of costing to inform the broader assessment of how to improve health workforce planning and management.</p> <p>Results</p> <p>We show that while the debate on the effectiveness of policies and strategies to improve health workforce retention is gaining impetus and attention, there is still a significant lack of knowledge and evidence about the associated costs. To address the concerns stemming from this situation, key elements of a framework to undertake a cost analysis are proposed and discussed.</p> <p>Conclusions</p> <p>These key elements should help policy makers gain insight into the costs of policy interventions, to clearly identify and understand their financing sources and mechanisms, and to ensure their sustainability.</p

Jellyfish Support High Energy Intake of Leatherback Sea Turtles (Dermochelys coriacea): Video Evidence from Animal-Borne Cameras

The endangered leatherback turtle is a large, highly migratory marine predator that inexplicably relies upon a diet of low-energy gelatinous zooplankton. The location of these prey may be predictable at large oceanographic scales, given that leatherback turtles perform long distance migrations (1000s of km) from nesting beaches to high latitude foraging grounds. However, little is known about the profitability of this migration and foraging strategy. We used GPS location data and video from animal-borne cameras to examine how prey characteristics (i.e., prey size, prey type, prey encounter rate) correlate with the daytime foraging behavior of leatherbacks (n = 19) in shelf waters off Cape Breton Island, NS, Canada, during August and September. Video was recorded continuously, averaged 1:53 h per turtle (range 0:08–3:38 h), and documented a total of 601 prey captures. Lion's mane jellyfish (Cyanea capillata) was the dominant prey (83–100%), but moon jellyfish (Aurelia aurita) were also consumed. Turtles approached and attacked most jellyfish within the camera's field of view and appeared to consume prey completely. There was no significant relationship between encounter rate and dive duration (p = 0.74, linear mixed-effects models). Handling time increased with prey size regardless of prey species (p = 0.0001). Estimates of energy intake averaged 66,018 kJ•d−1 but were as high as 167,797 kJ•d−1 corresponding to turtles consuming an average of 330 kg wet mass•d−1 (up to 840 kg•d−1) or approximately 261 (up to 664) jellyfish•d-1. Assuming our turtles averaged 455 kg body mass, they consumed an average of 73% of their body mass•d−1 equating to an average energy intake of 3–7 times their daily metabolic requirements, depending on estimates used. This study provides evidence that feeding tactics used by leatherbacks in Atlantic Canadian waters are highly profitable and our results are consistent with estimates of mass gain prior to southward migration

DNA damage by lipid peroxidation products: implications in cancer, inflammation and autoimmunity

Oxidative stress and lipid peroxidation (LPO) induced by inflammation, excess metal storage and excess caloric intake cause generalized DNA damage, producing genotoxic and mutagenic effects. The consequent deregulation of cell homeostasis is implicated in the pathogenesis of a number of malignancies and degenerative diseases. Reactive aldehydes produced by LPO, such as malondialdehyde, acrolein, crotonaldehyde and 4-hydroxy-2-nonenal, react with DNA bases, generating promutagenic exocyclic DNA adducts, which likely contribute to the mutagenic and carcinogenic effects associated with oxidative stress-induced LPO. However, reactive aldehydes, when added to tumor cells, can exert an anticancerous effect. They act, analogously to other chemotherapeutic drugs, by forming DNA adducts and, in this way, they drive the tumor cells toward apoptosis. The aldehyde-DNA adducts, which can be observed during inflammation, play an important role by inducing epigenetic changes which, in turn, can modulate the inflammatory process. The pathogenic role of the adducts formed by the products of LPO with biological macromolecules in the breaking of immunological tolerance to self antigens and in the development of autoimmunity has been supported by a wealth of evidence. The instrumental role of the adducts of reactive LPO products with self protein antigens in the sensitization of autoreactive cells to the respective unmodified proteins and in the intermolecular spreading of the autoimmune responses to aldehyde-modified and native DNA is well documented. In contrast, further investigation is required in order to establish whether the formation of adducts of LPO products with DNA might incite substantial immune responsivity and might be instrumental for the spreading of the immunological responses from aldehyde-modified DNA to native DNA and similarly modified, unmodified and/or structurally analogous self protein antigens, thus leading to autoimmunity

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)

Applying polygenic risk scoring for psychiatric disorders to a large family with bipolar disorder and major depressive disorder

Psychiatric disorders are thought to have a complex genetic pathology consisting of interplay of common and rare variation. Traditionally, pedigrees are used to shed light on the latter only, while here we discuss the application of polygenic risk scores to also highlight patterns of common genetic risk. We analyze polygenic risk scores for psychiatric disorders in a large pedigree (n similar to 260) in which 30% of family members suffer from major depressive disorder or bipolar disorder. Studying patterns of assortative mating and anticipation, it appears increased polygenic risk is contributed by affected individuals who married into the family, resulting in an increasing genetic risk over generations. This may explain the observation of anticipation in mood disorders, whereby onset is earlier and the severity increases over the generations of a family. Joint analyses of rare and common variation may be a powerful way to understand the familial genetics of psychiatric disorders