Breast cancer risk perception: what do we know and understand?

Women's perceptions of breast cancer risk are largely inaccurate and are often associated with high levels of anxiety about cancer. There are interesting cultural differences that are not well researched. Genetic risk counselling significantly improves accuracy of women's perceptions of risk, but not necessarily to the correct level. Reasons for this are unclear, but may relate to personal beliefs about susceptibility and to problems or variations in risk communication. Research into the impact of demographic and psychological factors on risk perception has been inconclusive. An understanding of the process of developing a perception of risk would help to inform risk counselling strategies. This is important, because knowledge of risk is needed both for appropriate health care decision making and to reassure women who are not at increased risk

Explorative visual analytics on interval-based genomic data and their metadata

Background: With the wide-spreading of public repositories of NGS processed data, the availability of user-friendly and effective tools for data exploration, analysis and visualization is becoming very relevant. These tools enable interactive analytics, an exploratory approach for the seamless "sense-making" of data through on-the-fly integration of analysis and visualization phases, suggested not only for evaluating processing results, but also for designing and adapting NGS data analysis pipelines. Results: This paper presents abstractions for supporting the early analysis of NGS processed data and their implementation in an associated tool, named GenoMetric Space Explorer (GeMSE). This tool serves the needs of the GenoMetric Query Language, an innovative cloud-based system for computing complex queries over heterogeneous processed data. It can also be used starting from any text files in standard BED, BroadPeak, NarrowPeak, GTF, or general tab-delimited format, containing numerical features of genomic regions; metadata can be provided as text files in tab-delimited attribute-value format. GeMSE allows interactive analytics, consisting of on-the-fly cycling among steps of data exploration, analysis and visualization that help biologists and bioinformaticians in making sense of heterogeneous genomic datasets. By means of an explorative interaction support, users can trace past activities and quickly recover their results, seamlessly going backward and forward in the analysis steps and comparative visualizations of heatmaps. Conclusions: GeMSE effective application and practical usefulness is demonstrated through significant use cases of biological interest. GeMSE is available at http://www.bioinformatics.deib.polimi.it/GeMSE/ , and its source code is available at https://github.com/Genometric/GeMSEunder GPLv3 open-source license

Phase I/II study of oral etoposide plus GM-CSF as second-line chemotherapy in platinum-pretreated patients with advanced ovarian cancer

The aim of this phase I/II study was to determine the maximum tolerated dose (MTD) and the dose-limiting toxicities of chronic oral etoposide given on days 1–10 followed by rescue with subcutaneous (s.c.) granulocyte-macrophage colony-stimulating factor (GM-CSF) on days 12–19 as second-line chemotherapy in platinum-pretreated patients (pts) with advanced ovarian carcinoma. Cohorts of three to six pts were treated with doses of oral etoposide from 750 mg m−2 cycle−1 escalated to 1250 mg m−2 cycle−1 over 10 days, every 3 weeks. Subcutanous GM-CSF, 400 μg once daily, days 12–19, was added if dose-limiting granulocytopenia was encountered. In total, 18 pts with a median Karnofsky index of 80% (range, 70–100%) and a median time elapsed since the last platinum dose of 10 months (range, 1–24 months), 30% of whom showed visceral metastases, were treated at four dose levels (DLs) of oral etoposide on days 1–10 of each cycle as follows: DL 1, 750 mg m−2 cycle−1, without GM-CSF, three pts; DL 2, 1000 mg m−2 cycle−1, without GM-CSF, three pts; DL 3, 1000 mg m−2 cycle−1, with GM-CSF, six pts; and DL 4, 1250 mg m−2 cycle−1, with GM-CSF, six pts. All pts were assessable for toxicity and 16 pts for response. Dose-limiting toxicity (DLT) was reached at DL 4 by three of six pts, showing World Health Organization (WHO) toxicity grade 4. One patient died from gram-negative sepsis associated with granulocytopenia grade 4. Two more pts developed uncomplicated granulocytopenia grade 4. Thus, we recommend that DL 3 can be used for further phase II evaluation (i.e. oral etoposide 1000 mg m−2 cycle−1, days 1–10, followed by s.c. GM-CSF 400 μg, days 12–19). The clinical complete or partial responses in each patient cohort were: DL 1, one of three pts; DL 2, one of three pts; DL 3, three of five pts; and DL 4, two of five pts. In conclusion, in this phase I/II study, we defined the MTD and the dose recommended for the therapy with oral etoposide given over 10 days followed by s.c. GM-CSF in platinum-pretreated patients with advanced ovarian cancer. Our data demonstrate encouraging activity of this regimen and strongly support its further investigation in a phase II study

Bad news from Fallujah

This study uses the thematic analysis developed by the Glasgow University Media Group to explore how the US, UK and German national press covered the US/Coalition assault on the Iraqi city of Fallujah in November 2004. The study relies on quantitative and qualitative full text content analyses to assess 428 news, editorial and commentary items. The article suggests that, while government and military officials of the US/Coalition had argued the military ‘operation’ was necessary to secure Iraq and defeat an ‘insurgency’, organisations and actors from Iraqi society refer to the ‘operation’ as ‘collective punishment’ and a ‘massacre’ that targeted the Iraqi population. The article investigates how the press represented each of these perspectives. The findings suggest that the press overemphasised the US/Coalition perspective despite striking counter evidence. Critical aspects of coverage largely focused on tactical elements of the military dimension of the event. The article concludes that such findings are in accord with hegemonic models of media performance

Utilisation of Mucin Glycans by the Human Gut Symbiont Ruminococcus gnavus Is Strain-Dependent

Commensal bacteria often have an especially rich source of glycan-degrading enzymes which allow them to utilize undigested carbohydrates from the food or the host. The species Ruminococcus gnavus is present in the digestive tract of ≥90% of humans and has been implicated in gut-related diseases such as inflammatory bowel diseases (IBD). Here we analysed the ability of two R. gnavus human strains, E1 and ATCC 29149, to utilize host glycans. We showed that although both strains could assimilate mucin monosaccharides, only R. gnavus ATCC 29149 was able to grow on mucin as a sole carbon source. Comparative genomic analysis of the two R. gnavus strains highlighted potential clusters and glycoside hydrolases (GHs) responsible for the breakdown and utilization of mucin-derived glycans. Transcriptomic and functional activity assays confirmed the importance of specific GH33 sialidase, and GH29 and GH95 fucosidases in the mucin utilisation pathway. Notably, we uncovered a novel pathway by which R. gnavus ATCC 29149 utilises sialic acid from sialylated substrates. Our results also demonstrated the ability of R. gnavus ATCC 29149 to produce propanol and propionate as the end products of metabolism when grown on mucin and fucosylated glycans. These new findings provide molecular insights into the strain-specificity of R. gnavus adaptation to the gut environment advancing our understanding of the role of gut commensals in health and disease

Competitive Repair by Naturally Dispersed Repetitive DNA during Non-Allelic Homologous Recombination

Genome rearrangements often result from non-allelic homologous recombination (NAHR) between repetitive DNA elements dispersed throughout the genome. Here we systematically analyze NAHR between Ty retrotransposons using a genome-wide approach that exploits unique features of Saccharomyces cerevisiae purebred and Saccharomyces cerevisiae/Saccharomyces bayanus hybrid diploids. We find that DNA double-strand breaks (DSBs) induce NAHR–dependent rearrangements using Ty elements located 12 to 48 kilobases distal to the break site. This break-distal recombination (BDR) occurs frequently, even when allelic recombination can repair the break using the homolog. Robust BDR–dependent NAHR demonstrates that sequences very distal to DSBs can effectively compete with proximal sequences for repair of the break. In addition, our analysis of NAHR partner choice between Ty repeats shows that intrachromosomal Ty partners are preferred despite the abundance of potential interchromosomal Ty partners that share higher sequence identity. This competitive advantage of intrachromosomal Tys results from the relative efficiencies of different NAHR repair pathways. Finally, NAHR generates deleterious rearrangements more frequently when DSBs occur outside rather than within a Ty repeat. These findings yield insights into mechanisms of repeat-mediated genome rearrangements associated with evolution and cancer

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Accuracy comparison of machine learning algorithms for predictive analytics in higher education

In this research, we compared the accuracy of machine learning algorithms that could be used for predictive analytics in higher education. The proposed experiment is based on a combination of classic machine learning algorithms such as Naive Bayes and Random Forest with various ensemble methods such as Stochastic, Linear Discriminant Analysis (LDA), Tree model (C5.0), Bagged CART (treebag) and K Nearest Neighbors (KNN). We applied traditional classification methods to classify the students’ performance and to determine the independent variables that offer the highest accuracy. Our results depict that the data with the 11 features using random forest generated the best accuracy value of 0.7333. However, we revised the experiment with ensemble algorithms to reduce the variance (bagging), bias (boosting) and to improve the prediction accuracy (stacking). Consequently, the bagging random forest outperformed other methods with the accuracy value of 0.7959