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Objective:
Over the past decade, myocardial triglyceride content has become an accepted biomarker for chronic metabolic and cardiac disease. The purpose of this study was to use proton (hydrogen 1)-magnetic resonance spectroscopy (\(^{1}\)H-MRS) at 3Tesla (3 T) field strength to assess potential gender-related differences in myocardial triglyceride content in healthy individuals.
Methods:
Cardiac MR imaging was performed to enable accurate voxel placement and obtain functional and morphological information. Double triggered (i.e., ECG and respiratory motion gating) \(^{1}\)H-MRS was used to quantify myocardial triglyceride levels for each gender. Two-sample t-test and Mann-Whitney U-test were used for statistical analyses.
Results:
In total, 40 healthy volunteers (22 male, 18 female; aged >18 years and age matched) were included in the study. Median myocardial triglyceride content was 0.28% (interquartile range [IQR] 0.17–0.42%) in male and 0.24% (IQR 0.14–0.45%) in female participants, and no statistically significant difference was observed between the genders. Furthermore, no gender-specific difference in ejection fraction was observed, although on average, male participants presented with a higher mean ± SD left ventricular mass (136.3 ± 25.2 g) than female participants (103.9 ± 16.1 g).
Conclusions:
The study showed that \(^{1}\)H-MRS is a capable, noninvasive tool for acquisition of myocardial triglyceride metabolites. Myocardial triglyceride concentration was shown to be unrelated to gender in this group of healthy volunteers.
Nuclear Magnetic Resonance (NMR) provides a highly flexible platform for non invasive analysis and imaging biological samples, since the manipulation of nuclear spin allows the tailoring of experiments to maximize the informativeness of the data. MRI is capable of visualizing a holistic picture of the lipid storage in living plant/seed. This review has sought to explain how the technology can be used to acquire functional and physiological data from plant samples, and how to exploit it to characterize lipid deposition in vivo. At the same time, we have referred to the current limitations of NMR technology as applied to plants, and in particular of the difficulty of transferring methodologies optimized for animal/medical subjects to plant ones. A forward look into likely developments in the field is included, anticipating its key future role in the study of living plant.
New antimycotic drugs are challenging to find, as potential target proteins may have close human orthologs. We here focus on identifying metabolic targets that are critical for fungal growth and have minimal similarity to targets among human proteins. We compare and combine here: (I) direct metabolic network modeling using elementary mode analysis and flux estimates approximations using expression data, (II) targeting metabolic genes by transcriptome analysis of condition-specific highly expressed enzymes, and (III) analysis of enzyme structure, enzyme interconnectedness (“hubs”), and identification of pathogen-specific enzymes using orthology relations. We have identified 64 targets including metabolic enzymes involved in vitamin synthesis, lipid, and amino acid biosynthesis including 18 targets validated from the literature, two validated and five currently examined in own genetic experiments, and 38 further promising novel target proteins which are non-orthologous to human proteins, involved in metabolism and are highly ranked drug targets from these pipelines.