A Dual Tracer 18F-FCH/18F-FDG PET Imaging of an Orthotopic Brain Tumor Xenograft Model

Early diagnosis of low grade glioma has been a challenge to clinicians. Positron Emission Tomography (PET) using ¹⁸F-FDG as a radio-tracer has limited utility in this area because of the high background in normal brain tissue. Other radiotracers such as ¹⁸F-Fluorocholine (¹⁸F-FCH) could provide better contrast between tumor and normal brain tissue but with high incidence of false positives. In this study, the potential application of a dual tracer ¹⁸F-FCH/¹⁸F-FDG-PET is investigated in order to improve the sensitivity of PET imaging for low grade glioma diagnosis based on a mouse orthotopic xenograft model. BALB/c nude mice with and without orthotopic glioma xenografts from U87 MG-luc2 glioma cell line are used for the study. The animals are subjected to ¹⁸F-FCH and ¹⁸F-FDG PET imaging, and images acquired from two separate scans are superimposed for analysis. The ¹⁸F-FCH counts are subtracted from the merged images to identify the tumor. Micro-CT, bioluminescence imaging (BLI), histology and measurement of the tumor diameter are also conducted for comparison. Results show that there is a significant contrast in ¹⁸F-FCH uptake between tumor and normal brain tissue (2.65 ± 0.98), but with a high false positive rate of 28.6%. The difficulty of identifying the tumor by ¹⁸F-FDG only is also proved in this study. All the tumors can be detected based on the dual tracer technique of ¹⁸F-FCH/ ¹⁸F-FDG-PET imaging in this study, while the false-positive caused by ¹⁸F-FCH can be eliminated. Dual tracer ¹⁸F-FCH/¹⁸F-FDG PET imaging has the potential to improve the visualization of low grade glioma. ¹⁸F-FCH delineates tumor areas and the tumor can be identified by subtracting the ¹⁸F-FCH counts. The sensitivity was over 95%. Further studies are required to evaluate the possibility of applying this technique in clinical trials.     

High-Density Lipoprotein-Associated miR-223 Is Altered after Diet-Induced Weight Loss in Overweight and Obese Males

Background and Aims

microRNAs (miRNAs) are small, endogenous non-coding RNAs that regulate metabolic processes, including obesity. The levels of circulating miRNAs are affected by metabolic changes in obesity, as well as in diet-induced weight loss. Circulating miRNAs are transported by high-density lipoproteins (HDL) but the regulation of HDL-associated miRNAs after diet-induced weight loss has not been studied. We aim to determine if HDL-associated miR-16, miR-17, miR-126, miR-222 and miR-223 levels are altered by diet-induced weight loss in overweight and obese males.

Methods

HDL were isolated from 47 subjects following 12 weeks weight loss comparing a high protein diet (HP, 30% of energy) with a normal protein diet (NP, 20% of energy). HDL-associated miRNAs (miR-16, miR-17, miR-126, miR-222 and miR-223) at baseline and after 12 weeks of weight loss were quantified by TaqMan miRNA assays. HDL particle sizes were determined by non-denaturing polyacrylamide gradient gel electrophoresis. Serum concentrations of human HDL constituents were measured immunoturbidometrically or enzymatically.

Results

miR-16, miR-17, miR-126, miR-222 and miR-223 were present on HDL from overweight and obese subjects at baseline and after 12 weeks of the HP and NP weight loss diets. The HP diet induced a significant decrease in HDL-associated miR-223 levels (p = 0.015), which positively correlated with changes in body weight (r = 0.488, p = 0.032). Changes in miR-223 levels were not associated to changes in HDL composition or size.

Conclusion

HDL-associated miR-223 levels are significantly decreased after HP diet-induced weight loss in overweight and obese males. This is the first study reporting changes in HDL-associated miRNA levels with diet-induced weight loss.     

A step through the looking glass

正Despite our many advances in deconstructing and understanding cellular and biomolecular machineries,the homochirality of life remains an enigma.Since our earliest ancestors,the central dogma has operated solely on D-DNA     

Reduced O-GlcNAcase expression promotes mitotic errors and spindle defects

Alterations in O-GlcNAc cycling, the addition and removal of O-GlcNAc, lead to mitotic defects and increased aneuploidy. Herein, we generated stable O-GlcNAcase (OGA, the enzyme that removes O-GlcNAc) knockdown HeLa cell lines and characterized the effect of the reduction in OGA activity on cell cycle progression. After release from G₁/S, the OGA knockdown cells progressed normally through S phase but demonstrated mitotic exit defects. Cyclin A was increased in the knockdown cells while Cyclin B and D expression was reduced. Retinoblastoma protein (RB) phosphorylation was also increased in the knockdown compared to control. At M phase, the knockdown cells showed more compact spindle chromatids than control cells and had a greater percentage of cells with multipolar spindles. Furthermore, the timing of the inhibitory tyrosine phosphorylation of Cyclin Dependent Kinase 1 (CDK1) was altered in the OGA knockdown cells. Although expression and localization of the chromosomal passenger protein complex (CPC) was unchanged, histone H3 threonine 3 phosphorylation was decreased in one of the OGA knockdown cell lines. The Ewing Sarcoma Breakpoint Region 1 Protein (EWS) participates in organizing the CPC at the spindle and is a known substrate for O-GlcNAc transferase (OGT, the enzyme that adds O-GlcNAc). EWS O-GlcNAcylation was significantly increased in the OGA knockdown cells promoting uneven localization of the mitotic midzone. Our data suggests that O-GlcNAc cycling is an essential mechanism for proper mitotic signaling and spindle formation, and alterations in the rate of O-GlcNAc cycling produces aberrant spindles and promotes aneuploidy.     

Dynamical systems for discovering protein complexes and functional modules from biological networks

Recent advances in high throughput experiments and annotations via published literature have provided a wealth of interaction maps of several biomolecular networks, including metabolic, protein-protein, and protein-DNA interaction networks. The architecture of these molecular networks reveals important principles of cellular organization and molecular functions. Analyzing such networks, i.e., discovering dense regions in the network, is an important way to identify protein complexes and functional modules. This task has been formulated as the problem of finding heavy subgraphs, the heaviest k-subgraph problem (k-HSP), which itself is NP-hard. However, any method based on the k-HSP requires the parameter k and an exact solution of k-HSP may still end up as a "spurious" heavy subgraph, thus reducing its practicability in analyzing large scale biological networks. We proposed a new formulation, called the rank-HSP, and two dynamical systems to approximate its results. In addition, a novel metric, called the standard deviation and mean ratio (SMR), is proposed for use in "spurious" heavy subgraphs to automate the discovery by setting a fixed threshold. Empirical results on both the simulated graphs and biological networks have demonstrated the efficiency and effectiveness of our proposal     

An integrated fluid–structure interaction and thrombosis model for type B aortic dissection

False lumen thrombosis (FLT) in type B aortic dissection has been associated with the progression of dissection and treatment outcome. Existing computational models mostly assume rigid wall behavior which ignores the effect of flap motion on flow and thrombus formation within the FL. In this study, we have combined a fully coupled fluid–structure interaction (FSI) approach with a shear-driven thrombosis model described by a series of convection–diffusion reaction equations. The integrated FSI-thrombosis model has been applied to an idealized dissection geometry to investigate the interaction between vessel wall motion and growing thrombus. Our simulation results show that wall compliance and flap motion can influence the progression of FLT. The main difference between the rigid and FSI models is the continuous development of vortices near the tears caused by drastic flap motion up to 4.45 mm. Flap-induced high shear stress and shear rates around tears help to transport activated platelets further to the neighboring region, thus speeding up thrombus formation during the accelerated phase in the FSI models. Reducing flap mobility by increasing the Young’s modulus of the flap slows down the thrombus growth. Compared to the rigid model, the predicted thrombus volume is 25% larger using the FSI-thrombosis model with a relatively mobile flap. Furthermore, our FSI-thrombosis model can capture the gradual effect of thrombus growth on the flow field, leading to flow obstruction in the FL, increased blood viscosity and reduced flap motion. This model is a step closer toward simulating realistic thrombus growth in aortic dissection, by taking into account the effect of intimal flap and vessel wall motion.

     

Coupled Single-Cell CRISPR Screening and Epigenomic Profiling Reveals Causal Gene Regulatory Networks

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