A chromosome conformation capture ordered sequence of the barley genome

201

Gene expression analysis of cell death induction by Taurolidine in different malignant cell lines

<p>Abstract</p> <p>Background</p> <p>The anti-infective agent Taurolidine (TRD) has been shown to have cell death inducing properties, but the mechanism of its action is largely unknown. The aim of this study was to identify potential common target genes modulated at the transcriptional level following TRD treatment in tumour cell lines originating from different cancer types.</p> <p>Methods</p> <p>Five different malignant cell lines (HT29, Chang Liver, HT1080, AsPC-1 and BxPC-3) were incubated with TRD (100 μM, 250 μM and 1000 μM). Proliferation after 8 h and cell viability after 24 h were analyzed by BrdU assay and FACS analysis, respectively. Gene expression analyses were carried out using the <it>Agilent </it>-microarray platform to indentify genes which displayed conjoint regulation following the addition of TRD in all cell lines. Candidate genes were subjected to <it>Ingenuity Pathways Analysis </it>and selected genes were validated by qRT-PCR and Western Blot.</p> <p>Results</p> <p>TRD 250 μM caused a significant inhibition of proliferation as well as apoptotic cell death in all cell lines. Among cell death associated genes with the strongest regulation in gene expression, we identified pro-apoptotic transcription factors (EGR1, ATF3) as well as genes involved in the ER stress response (PPP1R15A), in ubiquitination (TRAF6) and mitochondrial apoptotic pathways (PMAIP1).</p> <p>Conclusions</p> <p>This is the first conjoint analysis of potential target genes of TRD which was performed simultaneously in different malignant cell lines. The results indicate that TRD might be involved in different signal transduction pathways leading to apoptosis.</p

Automated macrophage counting in DLBCL tissue samples: a ROF filter based approach

BackgroundFor analysis of the tumor microenvironment in diffuse large B-cell lymphoma (DLBCL) tissue samples, it is desirable to obtain information about counts and distribution of different macrophage subtypes. Until now, macrophage counts are mostly inferred from gene expression analysis of whole tissue sections, providing only indirect information. Direct analysis of immunohistochemically (IHC) fluorescence stained tissue samples is confronted with several difficulties, e.g. high variability of shape and size of target macrophages and strongly inhomogeneous intensity of staining. Consequently, application of commercial software is largely restricted to very rough analysis modes, and most macrophage counts are still obtained by manual counting in microarrays or high power fields, thus failing to represent the heterogeneity of tumor microenvironment adequately.MethodsWe describe a Rudin-Osher-Fatemi (ROF) filter based segmentation approach for whole tissue samples, combining floating intensity thresholding and rule-based feature detection. Method is validated against manual counts and compared with two commercial software kits (Tissue Studio 64, Definiens AG, and Halo, Indica Labs) and a straightforward machine-learning approach in a set of 50 test images. Further, the novel method and both commercial packages are applied to a set of 44 whole tissue sections. Outputs are compared with gene expression data available for the same tissue samples. Finally, the ROF based method is applied to 44 expert-specified tumor subregions for testing selection and subsampling strategies.ResultsAmong all tested methods, the novel approach is best correlated with manual count (0.9297). Automated detection of evaluation subregions proved to be fully reliable. Comparison with gene expression data obtained for the same tissue samples reveals only moderate to low correlation levels. Subsampling within tumor subregions is possible with results almost identical to full sampling. Mean macrophage size in tumor subregions is 152.5111.3 m(2).ConclusionsROF based approach is successfully applied to detection of IHC stained macrophages in DLBCL tissue samples. The method competes well with existing commercial software kits. In difference to them, it is fully automated, externally repeatable, independent on training data and completely documented. Comparison with gene expression data indicates that image morphometry constitutes an independent source of information about antibody-polarized macrophage occurence and distribution

Solving the random diffusion model in an infinite medium: A mean square approach

[EN] This paper deals with the construction of an analytic-numerical mean square solution of the random diffusion model in an infinite medium. The well-known Fourier transform method, which is used to solve this problem in the deterministic case, is extended to the random framework. Mean square operational rules to the Fourier transform of a stochastic process are developed and stated. The main statistical moments of the stochastic process solution are also computed. Finally, some illustrative numerical examples are included.This work has been partially supported by the Ministerio de Economia y Competitividad grant: DPI2010-20891-c0-01, and Universitat Politecnica de Valencia grant: PAID06-11-2070.Casabán, M.; Company Rossi, R.; Cortés, J.; Jódar Sánchez, LA. (2014). Solving the random diffusion model in an infinite medium: A mean square approach. Applied Mathematical Modelling. 38(24):5922-5933. https://doi.org/10.1016/j.apm.2014.04.063S59225933382

Innovative substance 2250 as a highly promising anti-neoplastic agent in malignant pancreatic carcinoma - in vitro and in vivo

BACKGROUND: Former studies already revealed the anti-neoplastic properties of the anti-infective agent Taurolidine (TRD) against many tumor species in vitro and in vivo. Its anti-proliferative and cell death inducing capacity is largely due to its main derivative Taurultam (TRLT). In this study it could be demonstrated, that substance 2250 - a newly defined innovative structural analogue of TRLT - exhibits an anti-neoplastic effect on malignant pancreatic carcinoma in vitro and in vivo. METHODS: The anti-neoplastic potential of substance 2250 as well as its mode of action was demonstrated in extensive in vitro analysis, followed by successful and effective in vivo testings, using xenograft models derived from established pancreatic cancer cell lines as well as patient derived tissue. RESULTS: Our functional analysis regarding the role of oxidative stress (ROS) and caspase activated apoptosis showed, that ROS driven programmed cell death (PCD) is the major mechanisms induced by substance 2250 in pancreatic carcinoma. What is strongly relevant towards clinical practice is especially the observed inhibition of patient derived pancreatic cancer tumor growth in mice treated with this new substance in combination with its sharply higher metabolic stability. CONCLUSION: These encouraging results provide new therapeutical opportunities in pancreatic cancer treatment and build the basis for further functional analysis as well as first clinical studies for this promising agent

Enhanced recovery in colorectal surgery: a multicentre study

<p>Abstract</p> <p>Background</p> <p>Major colorectal surgery usually requires a hospital stay of more than 12 days. Inadequate pain management, intestinal dysfunction and immobilisation are the main factors associated with delay in recovery. The present work assesses the short and medium term results achieved by an enhanced recovery program based on previously published protocols.</p> <p>Methods</p> <p>This prospective study, performed at 12 Spanish hospitals in 2008 and 2009, involved 300 patients. All patients underwent elective colorectal resection for cancer following an enhanced recovery program. The main elements of this program were: preoperative advice, no colon preparation, provision of carbohydrate-rich drinks one day prior and on the morning of surgery, goal directed fluid administration, body temperature control during surgery, avoiding drainages and nasogastric tubes, early mobilisation, and the taking of oral fluids in the early postoperative period. Perioperative morbidity and mortality data were collected and the length of hospital stay and protocol compliance recorded.</p> <p>Results</p> <p>The median age of the patients was 68 years. Fifty-two % of the patients were women. The distribution of patients by ASA class was: I 10%, II 50% and III 40%. Sixty-four % of interventions were laparoscopic; 15% required conversion to laparotomy. The majority of patients underwent sigmoidectomy or right hemicolectomy. The overall compliance to protocol was approximately 65%, but varied widely in its different components. The median length of postoperative hospital stay was 6 days. Some 3% of patients were readmitted to hospital after discharge; some 7% required repeat surgery during their initial hospitalisation or after readmission. The most common complications were surgical (24%), followed by septic (11%) or other medical complications (10%). Three patients (1%) died during follow-up. Some 31% of patients suffered symptoms that delayed their discharge, the most common being vomiting or nausea (12%), dyspnoea (7%) and fever (5%).</p> <p>Conclusion</p> <p>The following of this enhanced recovery program posed no risk to patients in terms of morbidity, mortality and shortened the length of their hospital stay. Overall compliance to protocol was 65%. The following of this program was of benefit to patients and reduces costs by shortening the length of hospital stay. The implantation of such programmes is therefore highly recommended.</p

Automated detection of regions of interest for tissue microarray experiments: an image texture analysis

BACKGROUND: Recent research with tissue microarrays led to a rapid progress toward quantifying the expressions of large sets of biomarkers in normal and diseased tissue. However, standard procedures for sampling tissue for molecular profiling have not yet been established. METHODS: This study presents a high throughput analysis of texture heterogeneity on breast tissue images for the purpose of identifying regions of interest in the tissue for molecular profiling via tissue microarray technology. Image texture of breast histology slides was described in terms of three parameters: the percentage of area occupied in an image block by chromatin (B), percentage occupied by stroma-like regions (P), and a statistical heterogeneity index H commonly used in image analysis. Texture parameters were defined and computed for each of the thousands of image blocks in our dataset using both the gray scale and color segmentation. The image blocks were then classified into three categories using the texture feature parameters in a novel statistical learning algorithm. These categories are as follows: image blocks specific to normal breast tissue, blocks specific to cancerous tissue, and those image blocks that are non-specific to normal and disease states. RESULTS: Gray scale and color segmentation techniques led to identification of same regions in histology slides as cancer-specific. Moreover the image blocks identified as cancer-specific belonged to those cell crowded regions in whole section image slides that were marked by two pathologists as regions of interest for further histological studies. CONCLUSION: These results indicate the high efficiency of our automated method for identifying pathologic regions of interest on histology slides. Automation of critical region identification will help minimize the inter-rater variability among different raters (pathologists) as hundreds of tumors that are used to develop an array have typically been evaluated (graded) by different pathologists. The region of interest information gathered from the whole section images will guide the excision of tissue for constructing tissue microarrays and for high throughput profiling of global gene expression

Health and performance challenges in the era of human enhancement: Insights from sport medicine professionals

Background: In the pursuit of sporting success, some elite athletes prioritise peak performance over long-term health, frequently resulting in significant and enduring health consequences. The Enhanced Games (TEG) position themselves as a bold experiment in transhumanism, advocating for the use of performance-enhancing drugs (PEDs), including methods banned by World Anti-Doping Agency (WADA), to push the boundaries of human athletic potential. Objectives: The aim of this study is to explore the perspectives of sport physicians, sport scientists, physiotherapists and other allied healthcare professionals on treating and supporting “enhanced athletes”, with the view of informing future guidelines. Methods: Participants were invited via email and personal contacts within sport medicine communities to complete a brief anonymous survey via QuestionPro™. Descriptive statistics were performed using Excel™ and RStudio™. Results: A total of 323 healthcare professionals responded (82% were sport physicians), among whom 74% expressed a willingness to treat acute lesions and/or chronic diseases in “enhanced athletes”. In comparison, a considerable minority (30%) expressed support for assisting athletes in their use of PEDs and methods under medically supervised conditions, with high consistency across professional roles. A relatively high readiness was observed in sport physicians treating acute (77% versus 58%; p < 0.01) and chronic (75% versus 63%; p = 0.11) diseases for “enhanced athletes”. As far as WADA rules and/or national anti-doping laws apply, this support presupposes compliance with the code and the respective national laws to protect physicians from serious professional, legal and personal consequences. Conclusion: The preliminary findings align with the broader goal of fostering a sport culture that values both peak performance and the short- and long-term health of all participants. These results emphasise the necessity of implementing professional guidelines and comprehensive support systems designed to safeguard the long-term well-being of all athletes and underscore the urgent need for further research into the impact of TEG on sport and its community

Innovative Business Approaches for the Reduction of Extreme Poverty and Marginality?

Extreme poverty is an immense political and market failure, wasting the potential of hundreds of millions of people. Investing in the creation of markets that include the extreme poor and marginalized should thus not only be considered as a charitable activity, but promises high returns on investments - in financial and humanitarian terms. However, while the potential of innovative business approaches to target the poor that live close to the poverty line is increasingly being recognised, the question remains how far these approaches can push the margin to also include those that are extremely poor. And how can those that are marginalized from development opportunities be brought into and benefit from market-based systems to improve the quality of their lives? The impressive rise of business approaches to combating poverty stems from a long history of debates on the role of businesses in society. From an initial focus on social objectives as an external add-on, leading business thinkers have increasingly been stressing the benefits for companies of integrating social considerations into their core business strategies, for instance by targeting lowincome consumers (or 'bottom of the pyramid' markets) or strengthening supply and distribution chains through the involvement of local communities as part of inclusive business strategies. Others - most notably Muhammed Yunus along with other social entrepreneurs - are taking this argument one step further, advocating the use of business strategies primarily to address social goals rather than for financial gains. Thus, in discussions on the role of business in society, profit maximisation as the primary objective of business operations is increasingly making way for business initiatives that are guided by social objectives. This trend is also being supported by growing interest among investors in financing enterprises that promote social or environmental objectives, either as their primary aim or in parallel with seeking to generate financial returns. How suitable these different approaches are to engage the poorest and marginalized depends in part on the extent to which they are able to involve the extreme poor themselves, their flexibility to direct business objectives towards the reduction of extreme poverty and marginality, and their ability to successfully operate with non-business public and civil society partners and in sectors of particular interest to the extreme poor. Further research and action is needed to identify outcome-focused indicators and measurement tools for social value creation, examine possible government measures to support business activities for the poorest, and consider complementarities between the different business approaches. While we recognise that it is unrealistic to expect businesses to be able to reach all of the extreme poor, we believe that the boundaries of innovative business operations can be pushed much further to include a far larger number of the poorest and marginalized