A novel workflow for three-dimensional analysis of tumour cell migration

The limitations of two-dimensional analysis in three-dimensional (3D) cellular imaging impair the accuracy of research findings in biological studies. Here, we report a novel 3D approach to acquisition, analysis and interpretation of tumour spheroid images. Our research interest in mesenchymal–amoeboid transition led to the development of a workflow incorporating the generation and analysis of 3D data with instant structured illumination microscopy and a new ImageJ plugin

Expression analysis of the MCPH1/BRIT1 and BRCA1 tumor suppressor genes and telomerase splice variants in epithelial ovarian cancer.

Aims The aim of this study was to explore the correlation of hTERT splice variant expression with MCPH1/BRIT1 and BRCA1 expression in epithelial ovarian cancer (EOC) samples. Background Telomerase activation can contribute to the progression of tumors and the development of cancer. However, the regulation of telomerase activity remains unclear. MCPH1 (also known as BRIT1, BRCT-repeat inhibitor of hTERT expression) and BRCA1 are tumor suppressor genes that have been linked to telomerase expression. Methods qPCR was used to investigate telomerase splice variants, MCPH1/BRIT1 and BRCA1 expression in EOC tissue and primary cultures. Results The wild type α+/β+ hTERT variant was the most common splice variant in the EOC samples, followed by α+/β− hTERT, a dominant negative regulator of telomerase activity. EOC samples expressing high total hTERT demonstrated significantly lower MCPH1/BRIT1 expression in both tissue (p = 0.05) and primary cultures (p = 0.03). We identified a negative correlation between MCPH1/BRIT1 and α+/β+ hTERT (p = 0.04), and a strong positive association between MCPH1/BRIT1 and both α−/β+ hTERT and α−/β− hTERT (both p = 0.02). A positive association was observed between BRCA1 and α−/β+ hTERT and α−/β− hTERT expression (p = 0.003 and p = 0.04, respectively). Conclusions These findings support a regulatory effect of MCPH1/BRIT1 and BRCA1 on telomerase activity, particularly the negative association between MCPH1/BRIT1 and the functional form of hTERT (α+/β+)

Successful Weight Loss Surgery Improves Eating Control and Energy Metabolism: A Review of the Evidence

Eating behavior is determined by a balance of memories in terms of reward and punishment to satisfy the urge to consume food. Refilling empty energy stores and hedonistic motivation are rewarding aspects of eating. Overfeeding, associated adverse GI effects, and obesity implicate punishment. In the current review, evidence is given for the hypothesis that bariatric surgery affects control over eating behavior.Moreover, any caloric overload will reduce the feeling of satiety. Durable weight loss after bariatric surgery is probably the result of a new equilibrium between reward and punishment, together with a better signaling of satiation due to beneficial metabolic changes.We propose to introduce three main treatment goals for bariatric surgery: 1) acceptable weight loss, 2) improvement of eating control, and 3) metabolic benefit. To achieve this goal, loss of 50% to 70% of excess weight will be appropriate (i.e. 30% to 40% loss of initial weight), depending on the degree of obesity prior to operation

Cancer Risk in Diabetic Patients Treated with Metformin: A Systematic Review and Meta-analysis

BACKGROUND: A growing body of evidence has suggested that metformin potentially reduces the risk of cancer. Our objective was to enhance the precision of estimates of the effect of metformin on the risk of any-site and site-specific cancers in patients with diabetes. METHODS/PRINCIPAL FINDINGS: We performed a search of MEDLINE, EMBASE, ISI Web of Science, Cochrane Library, and ClinicalTrials.gov for pertinent articles published as of October 12, 2011, and included them in a systematic review and meta-analysis. We calculated pooled risk ratios (RRs) for overall cancer mortality and cancer incidence. Of the 21,195 diabetic patients reported in 6 studies (4 cohort studies, 2 RCTs), 991 (4.5%) cases of death from cancer were reported. A total of 11,117 (5.3%) cases of incident cancer at any site were reported among 210,892 patients in 10 studies (2 RCTs, 6 cohort studies, 2 case-control studies). The risks of cancer among metformin users were significantly lower than those among non-metformin users: the pooled RRs (95% confidence interval) were 0.66 (0.49-0.88) for cancer mortality, 0.67 (0.53-0.85) for all-cancer incidence, 0.68 (0.53-0.88) for colorectal cancer (n = 6), 0.20 (0.07-0.59) for hepatocellular cancer (n = 4), 0.67 (0.45-0.99) for lung cancer (n = 3). CONCLUSION/SIGNIFICANCE: The use of metformin in diabetic patients was associated with significantly lower risks of cancer mortality and incidence. However, this analysis is mainly based on observational studies and our findings underscore the more need for long-term RCTs to confirm this potential benefit for individuals with diabetes

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

What works in secondary schools? A systematic review of classroom-based body image programs

Governments, schools, and curriculum authorities are increasingly recognizing that body image during adolescence is a public health issue that warrants attention in the school setting. After 30 years of eating disorder prevention research, and given the current interest in this area, it seems timely to review the research on interventions to improve body image in schools. We reviewed universal-selective, classroom-based programs that have been conducted since the year 2000, among adolescents, and found 16 eligible intervention programs. Seven of these programs were effective in improving body image on at least one measure, from pre to post test, though effect sizes were small (d = 0.22–0.48). These effective programs were conducted among younger adolescents 12.33–13.62 years, and included activities focusing on media literacy, self esteem, and the influence of peers. Implications for school personnel and curriculum authorities are discussed, and we provide recommendations for a strategic approach to future research in this area

OP33 * GLYCOGEN SYNTHASE KINASE INHIBITORS REDUCE 3D MIGRATION OF PATIENT DERIVED GLIOBLASTOMA MULTIFORME STEM CELLS

INTRODUCTION: Glioblastoma multiforme (GBM) is a fast growing, highly invasive malignant brain tumour. Inhibition of tumour cell migration into normal brain tissue represents a major target for treatment. Glycogen synthase kinase (GSK-3) inhibition has been associated with reduced GBM invasion in in vitro and in vivo models. Targeting this pathway with established and/or novel drugs may elucidate more effective treatment combinations. METHOD: The effect of GSK-3 inhibitors BIO, AZD2858, AZ1293 and AZ1080 on GBM migration was assessed in patient derived GBM stem cells (GBM-1) and two established cell lines (U251 and U87) using a 3D collagen based assay. Multiple drug concentrations were investigated with up to 72 hours exposure. A migration index was determined using aggregate core size and cell migration area. Immunohistochemistry and immunocytochemistry were used to assess cell morphology and cytoskeletal changes. RESULTS: All compounds inhibit migration in this model. AZD2858 was the most potent, causing significant effects at 1 micro molar. All compounds were cytotoxic at between 10 and 20 micro molar. Cytoskeletal and nuclear abnormalities were noted following drug exposure in all cell lines. These data suggest that possible mechanisms for the anti-migratory effect of these compounds include effects on F-actin localization and microtubule polarity. Inhibition of migration and cell architecture changes occurred at non-toxic doses. CONCLUSION: Inhibition of GSK3 significantly reduced migration of this highly invasive tumour. It is evident from these data that inhibiting the complex biological mechanisms driven by GSK3 may aid treatment of GBM through a number of different mechanisms

SpheroidAnalyseR – an online platform for analysing data from 3D spheroids or organoids grown in 96-well plates

Spheroids and organoids are increasingly popular three-dimensional (3D) cell culture models. Spheroid models are more physiologically relevant to a tumor compared to two-dimensional (2D) cultures and organoids are a simplified version of an organ with similar composition. Spheroids are often only formed from a single cell type which does not represent the situation in vivo. However, despite this, both spheroids and organoids can be used in cell migration studies, disease modelling and drug discovery. A drawback of these models is, however, the lack of appropriate analytical tools for high throughput imaging and analysis over a time course. To address this, we have developed an R Shiny app called SpheroidAnalyseR: a simple, fast, effective open-source app that allows the analysis of spheroid or organoid size data generated in a 96-well format. SpheroidAnalyseR processes and analyzes datasets of image measurements that can be obtained via a bespoke software, described herein, that automates spheroid imaging and quantification using the Nikon A1R Confocal Laser Scanning Microscope. However, templates are provided to enable users to input spheroid image measurements obtained by user-preferred methods. SpheroidAnalyseR facilitates outlier identification and removal followed by graphical visualization of spheroid measurements across multiple predefined parameters such as time, cell-type and treatment(s). Spheroid imaging and analysis can, thus, be reduced from hours to minutes, removing the requirement for substantial manual data manipulation in a spreadsheet application. The combination of spheroid generation in 96-well ultra-low attachment microplates, imaging using our bespoke software, and analysis using SpheroidAnalyseR toolkit allows high throughput, longitudinal quantification of 3D spheroid growth whilst minimizing user input and significantly improving the efficiency and reproducibility of data analysis. Our bespoke imaging software is available from https://github.com/GliomaGenomics. SpheroidAnalyseR is available at https://spheroidanalyser.leeds.ac.uk, and the source code found at https://github.com/GliomaGenomics