Patterns in metabolite profile are associated with risk of more aggressive prostate cancer: A prospective study of 3,057 matched case–control sets from EPIC

Metabolomics may reveal novel insights into the etiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3,057 matched case–control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR_1SD) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterized by higher concentrations of either phosphatidylcholines or hydroxysphingomyelins (OR_1SD = 0.77, 95% confidence interval 0.66–0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR_1SD = 0.72, 0.57–0.90), or lysophosphatidylcholines (OR_1SD = 0.81, 0.69–0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow-up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR_1SD = 0.77, 0.61–0.96). No associations were observed for prostate cancer overall or less aggressive tumor subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumors and prostate cancer death, and might be relevant to etiology of advanced stage prostate cancer.     

L’école de formation de la Ligue nationale contre le cancer

The objective of the training school of the French National League Against Cancer is to offer competent and knowledgeable volunteers and staff with a structured training strategy that is motivating and represents a guarantee for donors and government authorities. The school focuses on obtaining high quality results, tailored to the needs and expectations of the departemental committees of the French League Against Cancer. The curriculum consists of 38 training modules: two general modules mandatory for all workers — including volunteers and employees, regardless of their responsibilities — and a series of specialized modules corresponding to the different technical skills and positions within the League. From its creation in September 2002 until November 2006, the school organized many sessions and trained a large number of trainees: 315 training sessions were organized and 4084 trainees participated. The instructors are selected based on their skills, knowledge and teaching abilities. When possible, the school makes every effort to decentralize the training sessions; 144 of 345 were held in different regions. The school’s ambition is to produce highly skilled personnel who will take their place among those dedicated to the fight against cancer.     

Using Bayesian networks in the construction of a bi-level multi-classifier. A case study using intensive care unit patients data

Combining the predictions of a set of classifiers has shown to be an effective way to create composite classifiers that are more accurate than any of the component classifiers. There are many methods for combining the predictions given by component classifiers. We introduce a new method that combine a number of component classifiers using a Bayesian network as a classifier system given the component classifiers predictions. Component classifiers are standard machine learning classification algorithms, and the Bayesian network structure is learned using a genetic algorithm that searches for the structure that maximises the classification accuracy given the predictions of the component classifiers. Experimental results have been obtained on a datafile of cases containing information about ICU patients at Canary Islands University Hospital. The accuracy obtained using the presented new approach statistically improve those obtained using standard machine learning methods.     

Rehabilitación multimodal en cirugía de urgencias: ¿utopía o realidad?

Enhanced Recovery After Surgery (ERAS) constitutes the application of a series of perioperative measures based on the evidence, in order to achieve a better recovery of the patient and a decrease of the complications and the mortality. These ERAS programs initially proved their advantages in the field of colorectal surgery being progressively adopted by other surgical areas within the general surgery and other surgical specialties. The main excluding factor for the application of such programs has been the urgent clinical presentation, which has caused that despite the large volume of existing literature on ERAS in elective surgery, there are few studies that have investigated the effectiveness of these programs in surgical patients in emergencies. The aim of this article is to show ERAS measures currently available according to the existing evidence for emergency surgery.     

Evaluation of the automated fluorescent analysis of the H-ras minisatellite after optimized PCR amplification in comparison with a standardized Southern blot technique

Determination of allele sizes? loss of heterozygosity or genetic instability at minisatellite VNTR loci, are routinely performed by the conventional Southern technique. We have investigated the potential use of automated DNA sequencer for the analysis of the H-ras minisatellite. We report the modifications of amplification parameters and electrophoresis conditions on the sequencer. Seventy-one colorectal carcinomas and the corresponding normal tissues were amplified with fluorescent-labeled primers, analyzed on sequencer, and concurrently controlled by Southern blotting. The results on sequencer showed that a Hydrolink matrix used in non-denaturing conditions and a specific analysis software facilitate a more accurate fragment size calculation.     

Mediterranean Alcohol-Drinking Pattern and the Incidence of Cardiovascular Disease and Cardiovascular Mortality: The SUN Project

Background: We assessed the still unclear effect of the overall alcohol-drinking pattern, beyond the amount of alcohol consumed, on the incidence of cardiovascular clinical disease (CVD). Methods: We followed 14,651 participants during up to 14 years. We built a score assessing simultaneously seven dimensions of alcohol consumption to capture the conformity to a traditional Mediterranean alcohol-drinking pattern (MADP). It positively scored moderate alcohol intake, alcohol intake spread out over the week, low spirit consumption, preference for wine, red wine consumption, wine consumed during meals and avoidance of binge drinking. Results: During 142,177 person-years of follow-up, 127 incident cases of CVD (myocardial infarction, stroke or cardiovascular mortality) were identified. Compared with the category of better conformity with the MADP, the low-adherence group exhibited a non-significantly higher risk (HR) of total CVD ((95% CI) = 1.55 (0.58–4.16)). This direct association with a departure from the traditional MADP was even stronger for cardiovascular mortality (HR (95% CI) = 3.35 (0.77–14.5)). Nevertheless, all these associations were statistically non-significant. Conclusion: Better conformity with the MADP seemed to be associated with lower cardiovascular risk in most point estimates; however, no significant results were found and more powered studies are needed to clarify the role of the MADP on CVD.     

Better Adherence to the Mediterranean Diet Could Mitigate the Adverse Consequences of Obesity on Cardiovascular Disease: The SUN Prospective Cohort

Strong observational evidence supports the association between obesity and cardiovascular events. In elderly high-risk subjects, the Mediterranean diet (MedDiet) was reported to counteract the adverse cardiovascular effects of adiposity. Whether this same attenuation is also present in younger subjects is not known. We prospectively examined the association between obesity and cardiovascular clinical events (myocardial infarction, stroke or cardiovascular death) after 10.9 years follow-up in 19,065 middle-aged men and women (average age 38 year) according to their adherence to the MedDiet (<6 points or ≥6 points in the Trichopoulou’s Mediterranean Diet Score). We observed 152 incident cases of cardiovascular disease (CVD). An increased risk of CVD across categories of body mass index (BMI) was apparent if adherence to the MedDiet was low, with multivariable-adjusted hazard ratios (HRs): 1.44 (95% confidence interval: 0.93–2.25) for ≥25 – <30 kg/m² of BMI and 2.00 (1.04–3.83) for ≥30 kg/m² of BMI, compared to a BMI < 25 kg/m². In contrast, these estimates were 0.77 (0.35–1.67) and 1.15 (0.39–3.43) with good adherence to MedDiet. Better adherence to the MedDiet was associated with reduced CVD events (p for trend = 0.029). Our results suggest that the MedDiet could mitigate the harmful cardiovascular effect of overweight/obesity.