Φ-score: A cell-to-cell phenotypic scoring method for sensitive and selective hit discovery in cell-based assays.

Phenotypic screening monitors phenotypic changes induced by perturbations, including those generated by drugs or RNA interference. Currently-used methods for scoring screen hits have proven to be problematic, particularly when applied to physiologically relevant conditions such as low cell numbers or inefficient transfection. Here, we describe the Φ-score, which is a novel scoring method for the identification of phenotypic modifiers or hits in cell-based screens. Φ-score performance was assessed with simulations, a validation experiment and its application to gene identification in a large-scale RNAi screen. Using robust statistics and a variance model, we demonstrated that the Φ-score showed better sensitivity, selectivity and reproducibility compared to classical approaches. The improved performance of the Φ-score paves the way for cell-based screening of primary cells, which are often difficult to obtain from patients in sufficient numbers. We also describe a dedicated merging procedure to pool scores from small interfering RNAs targeting the same gene so as to provide improved visualization and hit selection.

Alcohol and atherosclerotic vascular disease risk factors in French men: relationships are linear, J-shaped, and U-shaped.

BACKGROUND: Although it is well admitted that alcohol displays a U-shaped relationship with atherosclerotic vascular disease, individual relationships between alcohol and atherosclerosis risk factors may be different and have not been determined precisely for several of them. METHODS: A cross-sectional study within the SU.VI.MAX French cohort study was performed to assess the curve of potential relationships between alcohol and atherosclerosis risk factors in 2126 healthy men. Mean daily alcohol intake was derived from 37 alcoholic beverages in twelve 24-hr dietary recalls. Logistic models were adjusted for age. RESULTS: Apolipoprotein B (ApoB), fasting glucose, body mass index, waist-to-hip ratio, and waist circumference displayed a linear relationship with alcohol. The odds ratios and 95% confidence intervals associated with abnormal values of the markers for the highest quintile of alcohol intake were 1.45 (1.06-1.97) for ApoB, 1.98 (1.40-2.80) for fasting glucose, and 1.74 (1.30-2.34) for body mass index. An inverse J-shaped relationship was assumed for ApoA1 and ApoB/ApoA1 ratio, whereas a U-shaped relationship was observed for serum triglycerides and mixed hyperlipidemia. Only the highest quintile of alcohol was associated with hypertension, although the test for linearity was also significant. No association was observed for Lp(a) or homocysteine. Associations were unmodified by further adjustment for carbohydrates, fiber, lipids, tobacco, or exercise. CONCLUSIONS: The aggregate of the disparate alcohol risk factor relationships suggests probable net benefit at 15 to 25 g of alcohol/day.

Drinking patterns in French adult men--a cluster analysis of alcoholic beverages and relationship with lifestyle.

BACKGROUND: Establishing patterns of alcohol consumption may be useful for investigating the relationship between alcohol and diseases. METHODS: We used a hierarchical agglomerative clustering method to describe the intake of eight types of alcoholic beverages and to determine drinking patterns in a cohort of 1797 men enrolled in a French 8-year intervention study involving nutritional doses of vitamins and minerals, the SU.VI.MAX study. RESULTS: Cluster 1, referred to as 'abstainers', was defined a priori and included 329 men who drank less than 5 g of alcohol per day. Six drinking patterns were defined in alcohol drinkers, with increasing mean alcohol intake: cluster 2, 'low drinkers', included 670 subjects, who drank little of any type of alcoholic beverage; cluster 3, 'high quality wines', included 584 men with a high intake of champagne, high quality wines, and high-alcohol aperitifs; cluster 4, 'beer and cider', included 190 subjects with a high intake of beer and cider; cluster 5, 'digestives', included 54 men with a specifically high consumption of digestive beverages; cluster 6, 'local wines', included 238 subjects with a high intake of local wines and low-alcohol aperitifs; cluster 7, 'table wines', included 61 men with a high intake of table wines and high-alcohol aperitifs. These clusters were significantly associated with socioeconomic and lifestyle variables such as place of residence, occupation, mean caloric intake and distribution of energy intake throughout the day, body mass index, and smoking habits. CONCLUSIONS: They will be useful in future studies of the relationship between alcohol intake and medical conditions or risk factors.