3,729 research outputs found
Developing a Molecular Roadmap of Drug-Food Interactions
Recent research has demonstrated that consumption of food -especially fruits and vegetables- can alter the effects of drugs by interfering either with their pharmacokinetic or pharmacodynamic processes. Despite the recognition of such drug-food associations as an important element for successful therapeutic interventions, a systematic approach for identifying, predicting and preventing potential interactions between food and marketed or novel drugs is not yet available. The overall objective of this work was to sketch a comprehensive picture of the interference of ∼ 4,000 dietary components present in ∼1800 plant-based foods with the pharmacokinetics and pharmacodynamics processes of medicine, with the purpose of elucidating the molecular mechanisms involved. By employing a systems chemical biology approach that integrates data from the scientific literature and online databases, we gained a global view of the associations between diet and dietary molecules with drug targets, metabolic enzymes, drug transporters and carriers currently deposited in DrugBank. Moreover, we identified disease areas and drug targets that are most prone to the negative effects of drug-food interactions, showcasing a platform for making recommendations in relation to foods that should be avoided under certain medications. Lastly, by investigating the correlation of gene expression signatures of foods and drugs we were able to generate a completely novel drug-diet interactome map.published_or_final_versio
Prognostic value of prehospital single measurement of N-terminal pro-brain natriuretic peptide and troponin T after acute ischemic stroke
Ballistic nanofriction
Sliding parts in nanosystems such as Nano ElectroMechanical Systems (NEMS)
and nanomotors, increasingly involve large speeds, and rotations as well as
translations of the moving surfaces; yet, the physics of high speed nanoscale
friction is so far unexplored. Here, by simulating the motion of drifting and
of kicked Au clusters on graphite - a workhorse system of experimental
relevance -- we demonstrate and characterize a novel "ballistic" friction
regime at high speed, separate from drift at low speed. The temperature
dependence of the cluster slip distance and time, measuring friction, is
opposite in these two regimes, consistent with theory. Crucial to both regimes
is the interplay of rotations and translations, shown to be correlated in slow
drift but anticorrelated in fast sliding. Despite these differences, we find
the velocity dependence of ballistic friction to be, like drift, viscous
A comparison of three clustering methods for finding subgroups in MRI, SMS or clinical data: SPSS TwoStep Cluster analysis, Latent Gold and SNOB
Background: There are various methodological approaches to identifying clinically important subgroups and one method is to identify clusters of characteristics that differentiate people in cross-sectional and/or longitudinal data using Cluster Analysis (CA) or Latent Class Analysis (LCA). There is a scarcity of head-to-head comparisons that can inform the choice of which clustering method might be suitable for particular clinical datasets and research questions. Therefore, the aim of this study was to perform a head-to-head comparison of three commonly available methods (SPSS TwoStep CA, Latent Gold LCA and SNOB LCA). Methods. The performance of these three methods was compared: (i) quantitatively using the number of subgroups detected, the classification probability of individuals into subgroups, the reproducibility of results, and (ii) qualitatively using subjective judgments about each program's ease of use and interpretability of the presentation of results.We analysed five real datasets of varying complexity in a secondary analysis of data from other research projects. Three datasets contained only MRI findings (n = 2,060 to 20,810 vertebral disc levels), one dataset contained only pain intensity data collected for 52 weeks by text (SMS) messaging (n = 1,121 people), and the last dataset contained a range of clinical variables measured in low back pain patients (n = 543 people). Four artificial datasets (n = 1,000 each) containing subgroups of varying complexity were also analysed testing the ability of these clustering methods to detect subgroups and correctly classify individuals when subgroup membership was known. Results: The results from the real clinical datasets indicated that the number of subgroups detected varied, the certainty of classifying individuals into those subgroups varied, the findings had perfect reproducibility, some programs were easier to use and the interpretability of the presentation of their findings also varied. The results from the artificial datasets indicated that all three clustering methods showed a near-perfect ability to detect known subgroups and correctly classify individuals into those subgroups. Conclusions: Our subjective judgement was that Latent Gold offered the best balance of sensitivity to subgroups, ease of use and presentation of results with these datasets but we recognise that different clustering methods may suit other types of data and clinical research questions
Site-specific incorporation of phosphotyrosine using an expanded genetic code.
Access to phosphoproteins with stoichiometric and site-specific phosphorylation status is key to understanding the role of protein phosphorylation. Here we report an efficient method to generate pure, active phosphotyrosine-containing proteins by genetically encoding a stable phosphotyrosine analog that is convertible to native phosphotyrosine. We demonstrate its general compatibility with proteins of various sizes, phosphotyrosine sites and functions, and reveal a possible role of tyrosine phosphorylation in negative regulation of ubiquitination
Inverse magnetic catalysis in dense holographic matter
We study the chiral phase transition in a magnetic field at finite
temperature and chemical potential within the Sakai-Sugimoto model, a
holographic top-down approach to (large-N_c) QCD. We consider the limit of a
small separation of the flavor D8-branes, which corresponds to a dual field
theory comparable to a Nambu-Jona Lasinio (NJL) model. Mapping out the surface
of the chiral phase transition in the parameter space of magnetic field
strength, quark chemical potential, and temperature, we find that for small
temperatures the addition of a magnetic field decreases the critical chemical
potential for chiral symmetry restoration - in contrast to the case of
vanishing chemical potential where, in accordance with the familiar phenomenon
of magnetic catalysis, the magnetic field favors the chirally broken phase.
This "inverse magnetic catalysis" (IMC) appears to be associated with a
previously found magnetic phase transition within the chirally symmetric phase
that shows an intriguing similarity to a transition into the lowest Landau
level. We estimate IMC to persist up to 10^{19} G at low temperatures.Comment: 42 pages, 11 figures, v3: extended discussion; new appendix D;
references added; version to appear in JHE
Genome-wide association studies and prediction of 17 traits related to phenology, biomass and cell wall composition in the energy grass Miscanthus sinensis
Increasing demands for food and energy require a step change in the effectiveness, speed and flexibility of crop breeding. Therefore, the aim of this study was to assess the potential of genome-wide association studies (GWASs) and genomic selection (i.e. phenotype prediction from a genome-wide set of markers) to guide fundamental plant science and to accelerate breeding in the energy grass Miscanthus. We generated over 100 000 single-nucleotide variants (SNVs) by sequencing restriction site-associated DNA (RAD) tags in 138 Micanthus sinensis genotypes, and related SNVs to phenotypic data for 17 traits measured in a field trial. Confounding by population structure and relatedness was severe in naïve GWAS analyses, but mixed-linear models robustly controlled for these effects and allowed us to detect multiple associations that reached genome-wide significance. Genome-wide prediction accuracies tended to be moderate to high (average of 0.57), but varied dramatically across traits. As expected, predictive abilities increased linearly with the size of the mapping population, but reached a plateau when the number of markers used for prediction exceeded 10 000–20 000, and tended to decline, but remain significant, when cross-validations were performed across subpopulations. Our results suggest that the immediate implementation of genomic selection in Miscanthus breeding programs may be feasible
Is Workstyle a Mediating Factor for Pain in the Upper Extremity Over Time?
Introduction Upper extremity musculoskeletal disorders influence workers’ quality of life. Workstyle may be one factor to deal with in workers with pain in the upper extremity. The objective of this study was to determine if workstyle is a mediating factor for upper extremity pain in a changing work environment of office workers over time. Methods Office workers with upper extremity pain filled out a Workstyle questionnaire (WSF) at baseline (n = 110). After 8 and 12 months follow-up assessment took place. Participants were divided into a good and an adverse workstyle group at baseline. The presence of upper extremity pain in both groups was calculated and relative risks were determined. Chi-square tests were used. Results Eight months after baseline, 80% of the adverse and 45% of the good workstyle group reported pain. The relative risk (RR) of having upper extremity pain for the adverse compared to the good workstyle group was 1.8 (95% CI 1.08–2.86) (P = 0.055). Twelve months after baseline, upper extremity pain was more often presented in the adverse workstyle compared to the good workstyle group (RR = 3.0, (95% CI 1.76–5.11), P = 0.003). Twelve months after baseline, 100% of the adverse workstyle group and 33% of the good workstyle group reported pain in the upper extremity. Conclusion Workstyle seems to be a mediating factor for upper extremity pain in office workers in a changing work environment. It is recommended to assess workstyle among office workers with upper extremity pain, and to include workstyle behaviour in treatments
Wavelet packets based denoising method for measurement domain repeat-time multipath filtering in GPS static high-precision positioning
Repeatable satellite orbits can be used for multipath mitigation in GPS-based deformation monitoring and other high-precision GPS applications that involve continuous observation with static antennas. Multipath signals at a static station repeat when the GPS constellation repeats given the same site environment. Repeat-time multipath filtering techniques need noise reduction methods to remove the white noise in carrier phase measurement residuals in order to retrieve the carrier phase multipath corrections for the next day. We propose a generic and robust three-level wavelet packets based denoising method for repeat-time-based carrier phase multipath filtering in relative positioning; the method does not need tuning to work with different data sets. The proposed denoising method is tested rigorously and compared with two other denoising methods. Three rooftop data sets collected at the University of Nottingham Ningbo China and two data sets collected at three Southern California Integrated GPS Network high-rate stations are used in the performance assessment. Test results of the wavelet packets denoising method are compared with the results of the resistor–capacitor (RC) low-pass filter and the single-level discrete wavelet transform (DWT) denoising method. Multipath mitigation efficiency in carrier phase measurement domain is shown by spectrum analysis of two selected satellites in two data sets. The positioning performance of the repeat-time-based multipath filtering techniques is assessed. The results show that the performance of the three noise reduction techniques is about 1–46 % improvement on positioning accuracy when compared with no multipath filtering. The statistical results show that the wavelet packets based denoising method is always better than the RC filter by 2–4 %, and better than the DWT method by 6–15 %. These results suggest that the proposed wavelet packets based denoising method is better than both the DWT method and the relatively simple RC low-pass filter for noise reduction in multipath filtering. However, the wavelet packets based denoising method is not significantly better than the RC filter
Calibration of myocardial T2 and T1 against iron concentration.
BACKGROUND: The assessment of myocardial iron using T2* cardiovascular magnetic resonance (CMR) has been validated and calibrated, and is in clinical use. However, there is very limited data assessing the relaxation parameters T1 and T2 for measurement of human myocardial iron.
METHODS: Twelve hearts were examined from transfusion-dependent patients: 11 with end-stage heart failure, either following death (n=7) or cardiac transplantation (n=4), and 1 heart from a patient who died from a stroke with no cardiac iron loading. Ex-vivo R1 and R2 measurements (R1=1/T1 and R2=1/T2) at 1.5 Tesla were compared with myocardial iron concentration measured using inductively coupled plasma atomic emission spectroscopy.
RESULTS: From a single myocardial slice in formalin which was repeatedly examined, a modest decrease in T2 was observed with time, from mean (± SD) 23.7 ± 0.93 ms at baseline (13 days after death and formalin fixation) to 18.5 ± 1.41 ms at day 566 (p<0.001). Raw T2 values were therefore adjusted to correct for this fall over time. Myocardial R2 was correlated with iron concentration [Fe] (R2 0.566, p<0.001), but the correlation was stronger between LnR2 and Ln[Fe] (R2 0.790, p<0.001). The relation was [Fe] = 5081•(T2)-2.22 between T2 (ms) and myocardial iron (mg/g dry weight). Analysis of T1 proved challenging with a dichotomous distribution of T1, with very short T1 (mean 72.3 ± 25.8 ms) that was independent of iron concentration in all hearts stored in formalin for greater than 12 months. In the remaining hearts stored for <10 weeks prior to scanning, LnR1 and iron concentration were correlated but with marked scatter (R2 0.517, p<0.001). A linear relationship was present between T1 and T2 in the hearts stored for a short period (R2 0.657, p<0.001).
CONCLUSION: Myocardial T2 correlates well with myocardial iron concentration, which raises the possibility that T2 may provide additive information to T2* for patients with myocardial siderosis. However, ex-vivo T1 measurements are less reliable due to the severe chemical effects of formalin on T1 shortening, and therefore T1 calibration may only be practical from in-vivo human studies
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