Endogenous sex steroids and risk of cervical carcinoma : results from the EPIC study

Background: Epidemiologic data and animal models suggest that, despite the predominant role of human papillomavirus infection, sex steroid hormones are also involved in the etiology of invasive cervical carcinoma (ICC). Methods: Ninety-nine ICC cases, 121 cervical intraepithelial neoplasia grade 3 (CIN3) cases and 2 control women matched with each case for center, age, menopausal status and blood collection-related variables, were identified in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Circulating levels of testosterone (T) and estradiol (E(2)); dehydroepiandrosterone sulfate (DHEAS); progesterone (premenopausal women); and sex hormone-binding globulin (SHBG) were measured using immunoassays. Levels of free (f) T and E(2) were calculated from absolute concentrations of T, E(2), and SHBG. Odds ratios (ORs) and 95% confidence intervals (CI) were computed using regularized conditional logistic regression. Results: Among premenopausal women, associations with ICC were observed for fT (OR for highest vs. lowest tertile 5.16, 95% CI, 1.50-20.1). SHBG level was associated with a significant downward trend in ICC risk. T, E(2), fE(2), and DHEAS showed nonsignificant positive association with ICC. Progesterone was uninfluential. Among postmenopausal women, associations with ICC were found for T (OR 3.14; 95% CI, 1.21-9.37), whereas E(2) and fT showed nonsignificant positive association. SHBG level was unrelated to ICC risk in postmenopausal women. No associations between any hormone and CIN3 were detected in either pre- or postmenopausal women. Conclusions: Our findings suggest for the first time that T and possibly E(2) may be involved in the etiology of ICC. Impact: The responsiveness of cervical tumors to hormone modulators is worth exploring. Cancer Epidemiol Biomarkers Prev; 20(12); 2532-40. (C) 2011 AACR

Combining traditional dietary assessment methods with novel metabolomics techniques: present efforts by the Food Biomarker Alliance

FFQ, food diaries and 24 h recall methods represent the most commonly used dietary assessment tools in human studies on nutrition and health, but food intake biomarkers are assumed to provide a more objective reflection of intake. Unfortunately, very few of these biomarkers are sufficiently validated. This review provides an overview of food intake biomarker research and highlights present research efforts of the Joint Programming Initiative 'A Healthy Diet for a Healthy Life' (JPI-HDHL) Food Biomarkers Alliance (FoodBAll). In order to identify novel food intake biomarkers, the focus is on new food metabolomics techniques that allow the quantification of up to thousands of metabolites simultaneously, which may be applied in intervention and observational studies. As biomarkers are often influenced by various other factors than the food under investigation, FoodBAll developed a food intake biomarker quality and validity score aiming to assist the systematic evaluation of novel biomarkers. Moreover, to evaluate the applicability of nutritional biomarkers, studies are presently also focusing on associations between food intake biomarkers and diet-related disease risk. In order to be successful in these metabolomics studies, knowledge about available electronic metabolomics resources is necessary and further developments of these resources are essential. Ultimately, present efforts in this research area aim to advance quality control of traditional dietary assessment methods, advance compliance evaluation in nutritional intervention studies, and increase the significance of observational studies by investigating associations between nutrition and health. Keywords: Dietary assessment; Food intake biomarkers; Food metabolome; Metabolomics

p53 mutations in human cutaneous melanoma correlate with sun exposure but are not always involved in melanomagenesis

In melanoma, the relationship between sun exposure and the origin of mutations in either the N-ras oncogene or the p53 tumour-suppressor gene is not as clear as in other types of skin cancer. We have previously shown that mutations in the N-ras gene occur more frequently in melanomas originating from sun-exposed body sites, indicating that these mutations are UV induced. To investigate whether sun exposure also affects p53 in melanoma, we analysed 81 melanoma specimens for mutations in the p53 gene. The mutation frequency is higher than thus far reported: 17 specimens (21%) harbour one or more p53 mutations. Strikingly, 17 out of 22 mutations in p53 are of the C:G to T:A or CC:GG to TT:AA transitional type, strongly suggesting an aetiology involving UV exposure. Interestingly, the p53 mutation frequency in metastases was much lower than in primary tumours. In the case of metastases, a role for sun exposure was indicated by the finding that the mutations are present exclusively in skin metastases and not in internal metastases. Together with a relatively frequent occurrence of silent third-base pair mutations in primary melanomas, this indicates that the p53 mutations, at least in these tumours, have not contributed to melanomagenesis and may have originated after establishment of the primary tumour. 1999 Cancer Research Campaig

Data Stream Clustering for Real-Time Anomaly Detection: An Application to Insider Threats

Insider threat detection is an emergent concern for academia, industries, and governments due to the growing number of insider incidents in recent years. The continuous streaming of unbounded data coming from various sources in an organisation, typically in a high velocity, leads to a typical Big Data computational problem. The malicious insider threat refers to anomalous behaviour(s) (outliers) that deviate from the normal baseline of a data stream. The absence of previously logged activities executed by users shapes the insider threat detection mechanism into an unsupervised anomaly detection approach over a data stream. A common shortcoming in the existing data mining approaches to detect insider threats is the high number of false alarms/positives (FPs). To handle the Big Data issue and to address the shortcoming, we propose a streaming anomaly detection approach, namely Ensemble of Random subspace Anomaly detectors In Data Streams (E-RAIDS), for insider threat detection. E-RAIDS learns an ensemble of p established outlier detection techniques [Micro-cluster-based Continuous Outlier Detection (MCOD) or Anytime Outlier Detection (AnyOut)] which employ clustering over continuous data streams. Each model of the p models learns from a random feature subspace to detect local outliers, which might not be detected over the whole feature space. E-RAIDS introduces an aggregate component that combines the results from the p feature subspaces, in order to confirm whether to generate an alarm at each window iteration. The merit of E-RAIDS is that it defines a survival factor and a vote factor to address the shortcoming of high number of FPs. Experiments on E-RAIDS-MCOD and E-RAIDS-AnyOut are carried out, on synthetic data sets including malicious insider threat scenarios generated at Carnegie Mellon University, to test the effectiveness of voting feature subspaces, and the capability to detect (more than one)-behaviour-all-threat in real-time. The results show that E-RAIDS-MCOD reports the highest F1 measure and less number of false alarm = 0 compared to E-RAIDS-AnyOut, as well as it attains to detect approximately all the insider threats in real-time

Nephrolithiasis related to inborn metabolic diseases

Nephrolithiasis associated with inborn metabolic diseases is a very rare condition with some common characteristics: early onset of symptoms, family history, associated tubular impairment, bilateral, multiple and recurrent stones, and association with nephrocalcinosis. The prognosis of such diseases may lead to life threatening conditions, not only because of unabated kidney damage but also because of progressive extra-renal involvement, either in a systemic form (e.g. primary hyperoxaluria type 1, requiring combined liver and kidney transplantation), or in a neurological form (Lesch–Nyhan syndrome leading to auto-mutilation and disability, phosphoribosyl pyrophosphate synthetase superactivity, which is associated with mental retardation). Patients with other inborn metabolic diseases present only with recurrent stone formation, such as cystinuria, adenine phosphoribosyl-transferase deficiency, xanthine deficiency. Finally, nephrolithiasis may be secondarily part of some other metabolic diseases, such as glycogen storage disease type 1 or inborn errors of metabolism leading to Fanconi syndrome (nephropathic cystinosis, tyrosinaemia type 1, fructose intolerance, Wilson disease, respiratory chain disorders, etc.). The diagnosis is based on highly specific investigations, including crystal identification, biochemical analyses and DNA study. The treatment of nephrolithiasis requires hydration as well as specific measures. Compliance is a major issue regarding the progression of renal damage, but the overall outcome mainly depends on extra-renal involvement in relation to the metabolic defect