The chemopreventive polyphenol Curcumin prevents hematogenous breast cancer metastases in immunodeficient mice

Dissemination of metastatic cells probably occurs long before diagnosis of the primary tumor. Metastasis during early phases of carcinogenesis in high risk patients is therefore a potential prevention target. The plant polyphenol Curcumin has been proposed for dietary prevention of cancer. We therefore examined its effects on the human breast cancer cell line MDA-MB-231 in vitro and in a mouse metastasis model. Curcumin strongly induces apoptosis in MDA- MB- 231 cells in correlation with reduced activation of the survival pathway NF kappa B, as a consequence of diminished I kappa B and p65 phosphorylation. Curcumin also reduces the expression of major matrix metalloproteinases (MMPs) due to reduced NF kappa B activity and transcriptional downregulation of AP-1. NF kappa B/p65 silencing is sufficient to downregulate c-jun and MMP expression. Reduced NF kappa B/AP-1 activity and MMP expression lead to diminished invasion through a reconstituted basement membrane and to a significantly lower number of lung metastases in immunodeficient mice after intercardiac injection of 231 cells (p=0.0035). 68% of Curcumin treated but only 17% of untreated animals showed no or very few lung metastases, most likely as a consequence of down-regulation of NF kappa B/AP-1 dependent MMP expression and direct apoptotic effects on circulating tumor cells but not on established metastases. Dietary chemoprevention of metastases appears therefore feasible. Copyright (c) 2007 S. Karger AG, Basel

Root trenching: a useful tool to estimate autotrophic soil respiration? A case study in an Austrian mountain forest

We conducted a trenching experiment in a mountain forest in order to assess the contribution of theautotrophic respiration to total soil respiration and evaluate trenching as a technique to achieve it. We hypothesised that the trenching experiment would alter both microbial biomass and microbial community structure and that Wne roots (less than 2 mm diameter) would be decomposed within one growing season. Soil CO2 eZux was measured roughlybiweekly over two growing seasons. Root presence and morphology parameters, as well as the soil microbial community were measured prior to trenching, 5 and 15 months after trenching. The trenched plots emitted about 20 and 30% less CO2 than the control plots in the Wrst and secondgrowing season, respectively. Roots died in trenched plots, but root decay was slow. After 5 and 15 months, Wne root biomass was decreased by 9% (not statistically diferent)and 30%, (statistically diVerent) respectively. When wecorrected for the additional trenched-plot CO2 eZux due to Wne root decomposition, the autotrophic soil respiration rose to »26% of the total soil respiration for the Wrst growing season, and to »44% for the second growing season.Soil microbial biomass and community structure was not altered by the end of the second growing season. We conclude that trenching can give accurate estimates of the autotrophic and heterotrophic components of soil respiration, ifmethodological side eVects are accounted for, only

Spatial heterogeneity of habitat suitability for Rift Valley fever occurrence in Tanzania: an ecological niche modelling approach

Despite the long history of Rift Valley fever (RVF) in Tanzania, extent of its suitable habitat in the country remains unclear. In this study we investigated potential effects of temperature, precipitation, elevation, soil type, livestock density, rainfall pattern, proximity to wild animals, protected areas and forest on the habitat suitability for RVF occurrence in Tanzania. Presence-only records of 193 RVF outbreak locations from 1930 to 2007 together with potential predictor variables were used to model and map the suitable habitats for RVF occurrence using ecological niche modelling. Ground-truthing of the model outputs was conducted by comparing the levels of RVF virus specific antibodies in cattle, sheep and goats sampled from locations in Tanzania that presented different predicted habitat suitability values. Habitat suitability values for RVF occurrence were higher in the northern and central-eastern regions of Tanzania than the rest of the regions in the country. Soil type and precipitation of the wettest quarter contributed equally to habitat suitability (32.4% each), followed by livestock density (25.9%) and rainfall pattern (9.3%). Ground-truthing of model outputs revealed that the odds of an animal being seropositive for RVFV when sampled from areas predicted to be most suitable for RVF occurrence were twice the odds of an animal sampled from areas least suitable for RVF occurrence (95% CI: 1.43, 2.76, p < 0.001). The regions in the northern and central-eastern Tanzania were more suitable for RVF occurrence than the rest of the regions in the country. The modelled suitable habitat is characterised by impermeable soils, moderate precipitation in the wettest quarter, high livestock density and a bimodal rainfall pattern. The findings of this study should provide guidance for the design of appropriate RVF surveillance, prevention and control strategies which target areas with these characteristics

Probabilistic machine learning and artificial intelligence.

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.The author acknowledges an EPSRC grant EP/I036575/1, the DARPA PPAML programme, a Google Focused Research Award for the Automatic Statistician and support from Microsoft Research.This is the author accepted manuscript. The final version is available from NPG at http://www.nature.com/nature/journal/v521/n7553/full/nature14541.html#abstract

Action planning and the timescale of evidence accumulation

Perceptual decisions are based on the temporal integration of sensory evidence for different states of the outside world. The timescale of this integration process varies widely across behavioral contexts and individuals, and it is diagnostic for the underlying neural mechanisms. In many situations, the decision-maker knows the required mapping between perceptual evidence and motor response (henceforth termed “sensory-motor contingency”) before decision formation. Here, the integrated evidence can be directly translated into a motor plan and, indeed, neural signatures of the integration process are evident as build-up activity in premotor brain regions. In other situations, however, the sensory-motor contingencies are unknown at the time of decision formation. We used behavioral psychophysics and computational modeling to test if knowledge about sensory-motor contingencies affects the timescale of perceptual evidence integration. We asked human observers to perform the same motion discrimination task, with or without trial-to-trial variations of the mapping between perceptual choice and motor response. When the mapping varied, it was either instructed before or after the stimulus presentation. We quantified the timescale of evidence integration under these different sensory-motor mapping conditions by means of two approaches. First, we analyzed subjects’ discrimination threshold as a function of stimulus duration. Second, we fitted a dynamical decision-making model to subjects’ choice behavior. The results from both approaches indicated that observers (i) integrated motion information for several hundred ms, (ii) used a shorter than optimal integration timescale, and (iii) used the same integration timescale under all sensory-motor mappings. We conclude that the mechanisms limiting the timescale of perceptual decisions are largely independent from long-term learning (under fixed mapping) or rapid acquisition (under variable mapping) of sensory-motor contingencies. This conclusion has implications for neurophysiological and neuroimaging studies of perceptual decision-making

Recycling Attitudes and Behavior among a Clinic-Based Sample of Low-Income Hispanic Women in Southeast Texas

We examined attitudes and behavior surrounding voluntary recycling in a population of low-income Hispanic women. Participants (N = 1,512) 18–55 years of age completed a self-report survey and responded to questions regarding household recycling behavior, recycling knowledge, recycling beliefs, potential barriers to recycling (transportation mode, time), acculturation, demographic characteristics (age, income, employment, marital status, education, number of children, birth country), and social desirability. Forty-six percent of participants (n = 810) indicated that they or someone else in their household recycled. In a logistic regression model controlling for social desirability, recycling behavior was related to increased age (P<0.05), lower acculturation (P<0.01), knowing what to recycle (P<0.01), knowing that recycling saves landfill space (P<0.05), and disagreeing that recycling takes too much time (P<0.001). A Sobel test revealed that acculturation mediated the relationship between recycling knowledge and recycling behavior (P<0.05). We offer new information on recycling behavior among Hispanic women and highlight the need for educational outreach and intervention strategies to increase recycling behavior within this understudied population

MIQuant – Semi-Automation of Infarct Size Assessment in Models of Cardiac Ischemic Injury

BACKGROUND: The cardiac regenerative potential of newly developed therapies is traditionally evaluated in rodent models of surgically induced myocardial ischemia. A generally accepted key parameter for determining the success of the applied therapy is the infarct size. Although regarded as a gold standard method for infarct size estimation in heart ischemia, histological planimetry is time-consuming and highly variable amongst studies. The purpose of this work is to contribute towards the standardization and simplification of infarct size assessment by providing free access to a novel semi-automated software tool. The acronym MIQuant was attributed to this application. METHODOLOGY/PRINCIPAL FINDINGS: Mice were subject to permanent coronary artery ligation and the size of chronic infarcts was estimated by area and midline-length methods using manual planimetry and with MIQuant. Repeatability and reproducibility of MIQuant scores were verified. The validation showed high correlation (r(midline length) = 0.981; r(area) = 0.970 ) and agreement (Bland-Altman analysis), free from bias for midline length and negligible bias of 1.21% to 3.72% for area quantification. Further analysis demonstrated that MIQuant reduced by 4.5-fold the time spent on the analysis and, importantly, MIQuant effectiveness is independent of user proficiency. The results indicate that MIQuant can be regarded as a better alternative to manual measurement. CONCLUSIONS: We conclude that MIQuant is a reliable and an easy-to-use software for infarct size quantification. The widespread use of MIQuant will contribute towards the standardization of infarct size assessment across studies and, therefore, to the systematization of the evaluation of cardiac regenerative potential of emerging therapies

Association between high-dose erythropoiesis-stimulating agents, inflammatory biomarkers, and soluble erythropoietin receptors

<p>Abstract</p> <p>Background</p> <p>High-dose erythropoiesis-stimulating agents (ESA) for anemia of chronic kidney disease (CKD) have been associated with adverse clinical outcomes and do not always improve erythropoiesis. We hypothesized that high-dose ESA requirement would be associated with elevated inflammatory biomarkers, decreased adipokines, and increased circulating, endogenous soluble erythropoietin receptors (sEpoR).</p> <p>Methods</p> <p>A cross-sectional cohort of anemic 32 CKD participants receiving ESA were enrolled at a single center and cytokine profiles, adipokines, and sEpoR were compared between participants stratified by ESA dose requirement (usual-dose darbepoetin-α (< 1 μg/kg/week) and high-dose (≥1 μg/kg/week)).</p> <p>Results</p> <p>Baseline characteristics were similar between groups; however, hemoglobin was lower among participants on high-dose (1.4 μg/kg/week) vs usual-dose (0.5 μg/kg/week) ESA.</p> <p>In adjusted analyses, high-dose ESA was associated with an increased odds for elevations in c-reactive protein and interleukin-6 (p < 0.05 for both). There was no correlation between high-dose ESA and adipokines. Higher ESA dose correlated with higher levels of sEpoR (r_s= 0.39, p = 0.03). In adjusted analyses, higher ESA dose (per μcg/kg/week) was associated with a 53% greater odds of sEpoR being above the median (p < 0.05).</p> <p>Conclusion</p> <p>High-dose ESA requirement among anemic CKD participants was associated with elevated inflammatory biomarkers and higher levels of circulating sEpoR, an inhibitor of erythropoiesis. Further research confirming these findings is warranted.</p> <p>Trial registration</p> <p>Clinicaltrials.gov <a href="http://www.clinicaltrials.gov/ct2/show/NCT00526747">NCT00526747</a></p

Development of Resistance towards Artesunate in MDA-MB-231 Human Breast Cancer Cells

Breast cancer is the most common cancer and the second leading cause of cancer death in industrialized countries. Systemic treatment of breast cancer is effective at the beginning of therapy. However, after a variable period of time, progression occurs due to therapy resistance. Artesunate, clinically used as anti-malarial agent, has recently revealed remarkable anti-tumor activity offering a role as novel candidate for cancer chemotherapy. We analyzed the anti-tumor effects of artesunate in metastasizing breast carcinoma in vitro and in vivo. Unlike as expected, artesunate induced resistance in highly metastatic human breast cancer cells MDA-MB-231. Likewise acquired resistance led to abolishment of apoptosis and cytotoxicity in pre-treated MDA-MB-231 cells. In contrast, artesunate was more cytotoxic towards the less tumorigenic MDA-MB-468 cells without showing resistance. Unraveling the underlying molecular mechanisms, we found that resistance was induced due to activation of the tumor progression related transcription factors NFκB and AP-1. Thereby transcription, expression and activity of the matrix-degrading enzyme MMP-1, whose function is correlated with increased invasion and metastasis, was up-regulated upon acquisition of resistance. Additionally, activation of the apoptosis-related factor NFκB lead to increased expression of ant-apoptotic bcl2 and reduced expression of pro-apoptotic bax. Application of artesunate in vivo in a model of xenografted breast cancer showed, that tumors growth was not efficiently abolished as compared to the control drug doxorubicin. Taken together our in vitro and in vivo results correlate well showing for the first time that artesunate induces resistance in highly metastatic breast tumors

Identification and analysis of miRNAs in human breast cancer and teratoma samples using deep sequencing

<p>Abstract</p> <p>Background</p> <p>MiRNAs play important roles in cellular control and in various disease states such as cancers, where they may serve as markers or possibly even therapeutics. Identifying the whole repertoire of miRNAs and understanding their expression patterns is therefore an important goal.</p> <p>Methods</p> <p>Here we describe the analysis of 454 pyrosequencing of small RNA from four different tissues: Breast cancer, normal adjacent breast, and two teratoma cell lines. We developed a pipeline for identifying new miRNAs, emphasizing extracting and retaining as much data as possible from even noisy sequencing data. We investigated differential expression of miRNAs in the breast cancer and normal adjacent breast samples, and systematically examined the mature sequence end variability of miRNA compared to non-miRNA loci.</p> <p>Results</p> <p>We identified five novel miRNAs, as well as two putative alternative precursors for known miRNAs. Several miRNAs were differentially expressed between the breast cancer and normal breast samples. The end variability was shown to be significantly different between miRNA and non-miRNA loci.</p> <p>Conclusion</p> <p>Pyrosequencing of small RNAs, together with a computational pipeline, can be used to identify miRNAs in tumor and other tissues. Measures of miRNA end variability may in the future be incorporated into the discovery pipeline as a discriminatory feature. Breast cancer samples show a distinct miRNA expression profile compared to normal adjacent breast.</p