Positron emission tomography imaging of tumor cell metabolism and application to therapy response monitoring

Cancer cells do reprogram their energy metabolism to enable several functions, such as generation of biomass including membrane biosynthesis, and overcoming bioenergetic and redox stress. In this article, we review both established and evolving radioprobes developed in association with positron emission tomography (PET) to detect tumor cell metabolism and effect of treatment. Measurement of enhanced tumor cell glycolysis using 2-deoxy-2-[(18)F]fluoro-D-glucose is well established in the clinic. Analogs of choline, including [(11)C]choline and various fluorinated derivatives are being tested in several cancer types clinically with PET. In addition to these, there is an evolving array of metabolic tracers for measuring intracellular transport of glutamine and other amino acids or for measuring glycogenesis, as well as probes used as surrogates for fatty acid synthesis or precursors for fatty acid oxidation. In addition to providing us with opportunities for examining the complex regulation of reprogramed energy metabolism in living subjects, the PET methods open up opportunities for monitoring pharmacological activity of new therapies that directly or indirectly inhibit tumor cell metabolism

Predictors of improved biochemical progression free survival for salvage prostate bed radiotherapy after radical prostatectomy

Predictors of improved biochemical progression free survival for salvage prostate bed radiotherapy after radical prostatectom

Upfront docetaxel with androgen deprivation therapy in the elderly patient with metastatic hormone-naïve prostate cancer: Single institution experience

Upfront docetaxel with androgen deprivation therapy in the elderly patient with metastatic hormone-naïve prostate cancer: Single institution experienc

Two-dimensional electrophoretic comparison of metastatic and non-metastatic human breast tumors using in vitro cultured epithelial cells derived from the cancer tissues

<p>Abstract</p> <p>Background</p> <p>Breast carcinomas represent a heterogeneous group of tumors diverse in behavior, outcome, and response to therapy. Identification of proteins resembling the tumor biology can improve the diagnosis, prediction, treatment selection, and targeting of therapy. Since the beginning of the post-genomic era, the focus of molecular biology gradually moved from genomes to proteins and proteomes and to their functionality. Proteomics can potentially capture dynamic changes in protein expression integrating both genetic and epigenetic influences.</p> <p>Methods</p> <p>We prepared primary cultures of epithelial cells from 23 breast cancer tissue samples and performed comparative proteomic analysis. Seven patients developed distant metastases within three-year follow-up. These samples were included into a metastase-positive group, the others formed a metastase-negative group. Two-dimensional electrophoretical (2-DE) gels in pH range 4–7 were prepared. Spot densities in 2-DE protein maps were subjected to statistical analyses (R/maanova package) and data-mining analysis (GUHA). For identification of proteins in selected spots, liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed.</p> <p>Results</p> <p>Three protein spots were significantly altered between the metastatic and non-metastatic groups. The correlations were proven at the 0.05 significance level. Nucleophosmin was increased in the group with metastases. The levels of 2,3-trans-enoyl-CoA isomerase and glutathione peroxidase 1 were decreased.</p> <p>Conclusion</p> <p>We have performed an extensive proteomic study of mammary epithelial cells from breast cancer patients. We have found differentially expressed proteins between the samples from metastase-positive and metastase-negative patient groups.</p

Effect of blood glucose level on standardized uptake value (SUV) in F-18- FDG PET-scan : a systematic review and meta-analysis of 20,807 individual SUV measurements

Objectives To evaluate the effect of pre-scan blood glucose levels (BGL) on standardized uptake value (SUV) in F-18-FDG-PET scan. Methods A literature review was performed in the MEDLINE, Embase, and Cochrane library databases. Multivariate regression analysis was performed on individual datum to investigate the correlation of BGL with SUVmax and SUVmean adjusting for sex, age, body mass index (BMI), diabetes mellitus diagnosis, F-18-FDG injected dose, and time interval. The ANOVA test was done to evaluate differences in SUVmax or SUVmean among five different BGL groups (200 mg/dl). Results Individual data for a total of 20,807 SUVmax and SUVmean measurements from 29 studies with 8380 patients was included in the analysis. Increased BGL is significantly correlated with decreased SUVmax and SUVmean in brain (p <0.001, p <0.001,) and muscle (p <0.001, p <0.001) and increased SUVmax and SUVmean in liver (p = 0.001, p = 0004) and blood pool (p=0.008, p200 mg/dl had significantly lower SUVmax. Conclusion If BGL is lower than 200mg/dl no interventions are needed for lowering BGL, unless the liver is the organ of interest. Future studies are needed to evaluate sensitivity and specificity of FDG-PET scan in diagnosis of malignant lesions in hyperglycemia.Peer reviewe

Machine learning assisted design of new lattice core for sandwich structures with superior load carrying capacity

Herein new lattice unit cells with buckling load 261–308% higher than the classical octet unit cell were reported. Lattice structures have been widely used in sandwich structures as lightweight core. While stretching dominated and bending dominated cells such as octahedron, tetrahedron and octet have been designed for lightweight structures, it is plausible that other cells exist which might perform better than the existing counterparts. Machine learning technique was used to discover new optimal unit cells. An 8-node cube containing a maximum of 27 elements, which extended into an eightfold unit cell, was taken as representative volume element (RVE). Numerous possible unit cells within the RVE were generated using permutations and combinations through MATLAB coding. Uniaxial compression tests using ANSYS were performed to form a dataset, which was used to train machine learning algorithms and form predictive model. The model was then used to further optimize the unit cells. A total of 20 optimal symmetric unit cells were predicted which showed 51–57% higher capacity than octet cell. Particularly, if the solid rods were replaced by porous biomimetic rods, an additional 130–160% increase in buckling resistance was achieved. Sandwich structures made of these 3D printed optimal symmetric unit cells showed 13–35% higher flexural strength than octet cell cored counterpart. This study opens up new opportunities to design high-performance sandwich structures

CONCEPTUAL LABORATORIES OF OPERATIVE EXPLORATION (CLOE) TO BUILD FORMAL THINKING IN BASIC SCHOOL: THE CASE OF SOUND

The design of innovative didactic sequence on a specific topic requires, in the Model of Educational Reconstruction perspective, besides the conceptual contents reconstruction, knowledge of students' conceptions about the topic focused. Conceptual Laboratories of Operative Exploration (CLOE) were designed with the goal of gaining direct knowledge on how students, particularly younger children (kinder-garden, primary, middle school), approach to specific topics and to the operative proposals, through which the innovative educational proposals are developed. CLOE lab involves pupils to discuss everyday life scenarios, recover their everyday and sensorial knowledge, explore experimental situations by means of Inquiry-Based Learning strategies. The informal learning environment of a CLOE session is an ideal format also for research focused on students\u2019 ideas and reasoning patterns, how they build formal thinking, develop interpretative representations, construct models on phenomena, reinterpret everyday knowledge. The research design characteristics of the CLOE labs are presented, exemplifying it, in the case of sound in primar