Determination of glucose exchange rates and permeability of erythrocyte membrane in preeclampsia and subsequent oxidative stress-related protein damage using dynamic-19F-NMR

The cause of the pregnancy condition preeclampsia (PE) is thought to be endothelial dysfunction caused by oxidative stress. As abnormal glucose tolerance has also been associated with PE, we use a fluorinated-mimic of this metabolite to establish whether any oxidative damage to lipids and proteins in the erythrocyte membrane has increased cell membrane permeability. Data were acquired using 19F Dynamic-NMR (DNMR) to measure exchange of 3-fluoro-3-deoxyglucose (3-FDG) across the membrane of erythrocytes from 10 pregnant women (5 healthy control women, and 5 from women suffering from PE). Magnetisation transfer was measured using the 1D selective inversion and 2D EXSY pulse sequences, over a range of time delays. Integrated intensities from these experiments were used in matrix diagonalisation to estimate the values of the rate constants of exchange and membrane permeability. No significant differences were observed for the rate of exchange of 3-FDG and membrane permeability between healthy pregnant women and those suffering from PE, leading us to conclude that no oxidative damage had occurred at this carrier-protein site in the membrane

A medical device-grade T1 and ECV phantom for global T1 mapping quality assurance - the T1_1 Mapping and ECV Standardization in cardiovascular magnetic resonance (T1MES) program

$\textbf{Background:}$ T$_1$ mapping and extracellular volume (ECV) have the potential to guide patient care and serve as surrogate end-points in clinical trials, but measurements differ between cardiovascular magnetic resonance (CMR) scanners and pulse sequences. To help deliver T$_1$ mapping to global clinical care, we developed a phantom-based quality assurance (QA) system for verification of measurement stability over time at individual sites, with further aims of generalization of results across sites, vendor systems, software versions and imaging sequences. We thus created T1MES: The T1 Mapping and ECV Standardization Program. $\textbf{Methods:}$ A design collaboration consisting of a specialist MRI small-medium enterprise, clinicians, physicists and national metrology institutes was formed. A phantom was designed covering clinically relevant ranges of T$_1$ and T$_2$ in blood and myocardium, pre and post-contrast, for 1.5 T and 3 T. Reproducible mass manufacture was established. The device received regulatory clearance by the Food and Drug Administration (FDA) and Conformité Européene (CE) marking. $\textbf{Results:}$ The T1MES phantom is an agarose gel-based phantom using nickel chloride as the paramagnetic relaxation modifier. It was reproducibly specified and mass-produced with a rigorously repeatable process. Each phantom contains nine differently-doped agarose gel tubes embedded in a gel/beads matrix. Phantoms were free of air bubbles and susceptibility artifacts at both field strengths and T$_1$ maps were free from off-resonance artifacts. The incorporation of high-density polyethylene beads in the main gel fill was effective at flattening the $B_1$ field. T$_1$ and T$_2$ values measured in T1MES showed coefficients of variation of 1 % or less between repeat scans indicating good short-term reproducibility. Temperature dependency experiments confirmed that over the range 15-30 °C the short-T$_1$ tubes were more stable with temperature than the long-T$_1$ tubes. A batch of 69 phantoms was mass-produced with random sampling of ten of these showing coefficients of variations for T$_1$ of 0.64 ± 0.45 % and 0.49 ± 0.34 % at 1.5 T and 3 T respectively. $\textbf{Conclusion:}$ The T1MES program has developed a T$_1$ mapping phantom to CE/FDA manufacturing standards. An initial 69 phantoms with a multi-vendor user manual are now being scanned fortnightly in centers worldwide. Future results will explore T$_1$ mapping sequences, platform performance, stability and the potential for standardization.This project has been funded by a European Association of Cardiovascular Imaging (EACVI part of the ESC) Imaging Research Grant, a UK National Institute of Health Research (NIHR) Biomedical Research Center (BRC) Cardiometabolic Research Grant at University College London (UCL, #BRC/ 199/JM/101320), and a Barts Charity Research Grant (#1107/2356/MRC0140). G.C. is supported by the National Institute for Health Research Rare Diseases Translational Research Collaboration (NIHR RD-TRC) and by the NIHR UCL Hospitals Biomedical Research Center. J.C.M. is directly and indirectly supported by the UCL Hospitals NIHR BRC and Biomedical Research Unit at Barts Hospital respectively. This work was in part supported by an NIHR BRC award to Cambridge University Hospitals NHS Foundation Trust and NIHR Cardiovascular Biomedical Research Unit support at Royal Brompton Hospital London UK

Targeting pathogen metabolism without collateral damage to the host

The development of drugs that can inactivate disease-causing cells (e.g. cancer cells or parasites) without causing collateral damage to healthy or to host cells is complicated by the fact that many proteins are very similar between organisms. Nevertheless, due to subtle, quantitative differences between the biochemical reaction networks of target cell and host, a drug can limit the flux of the same essential process in one organism more than in another. We identified precise criteria for this â €network-based' drug selectivity, which can serve as an alternative or additive to structural differences. We combined computational and experimental approaches to compare energy metabolism in the causative agent of sleeping sickness, Trypanosoma brucei, with that of human erythrocytes, and identified glucose transport and glyceraldehyde-3-phosphate dehydrogenase as the most selective antiparasitic targets. Computational predictions were validated experimentally in a novel parasite-erythrocytes co-culture system. Glucose-transport inhibitors killed trypanosomes without killing erythrocytes, neurons or liver cells

Modelling mammalian energetics: the heterothermy problem

Global climate change is expected to have strong effects on the world’s flora and fauna. As a result, there has been a recent increase in the number of meta-analyses and mechanistic models that attempt to predict potential responses of mammals to changing climates. Many models that seek to explain the effects of environmental temperatures on mammalian energetics and survival assume a constant body temperature. However, despite generally being regarded as strict homeotherms, mammals demonstrate a large degree of daily variability in body temperature, as well as the ability to reduce metabolic costs either by entering torpor, or by increasing body temperatures at high ambient temperatures. Often, changes in body temperature variability are unpredictable, and happen in response to immediate changes in resource abundance or temperature. In this review we provide an overview of variability and unpredictability found in body temperatures of extant mammals, identify potential blind spots in the current literature, and discuss options for incorporating variability into predictive mechanistic models

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases