The Effect of Class Noise on Continuous Test Case Selection: A Controlled Experiment on Industrial Data

Continuous integration and testing produce a large amount of data about defects in code revisions, which can be utilized for training a predictive learner to effectively select a subset of test suites. One challenge in using predictive learners lies in the noise that comes in the training data, which often leads to a decrease in classification performances. This study examines the impact of one type of noise, called class noise, on a learner’s ability for selecting test cases. Understanding the impact of class noise on the performance of a learner for test case selection would assist testers decide on the appropriateness of different noise handling strategies. For this purpose, we design and implement a controlled experiment using an industrial data-set to measure the impact of class noise at six different levels on the predictive performance of a learner. We measure the learning performance using the Precision, Recall, F-score, and Mathew Correlation Coefficient (MCC) metrics. The results show a statistically significant relationship between class noise and the learners performance for test case selection. Particularly, a significant difference between the three performance measures (Precision, F-score, and MCC)under all the six noise levels and at 0% level was found, whereas a similar relationship between recall and class noise was found at a level above30%. We conclude that higher class noise ratios lead to missing out more tests in the predicted subset of test suite and increases the rate of false alarms when the class noise ratio exceeds 30

High fat diet modifies the association of lipoprotein lipase gene polymorphism with high density lipoprotein cholesterol in an Asian Indian population

Background Single nucleotide polymorphisms (SNPs) in lipoprotein lipase gene (LPL) have been shown to influence metabolism related to lipid phenotypes. Dietary factors have been shown to modify the association between LPL SNPs and lipids; however, to date, there are no studies in South Asians. Hence, we tested for the association of four common LPL SNPs with plasma lipids and examined the interactions between the SNPs and dietary factors on lipids in 1,845 Asian Indians. Methods The analysis was performed in 788 Type 2 diabetes cases and 1,057 controls randomly chosen from the cross-sectional Chennai Urban Rural Epidemiological Study. Serum triacylglycerol (TAG), serum total cholesterol, and high-density lipoprotein cholesterol (HDL-C) were measured using a Hitachi-912 autoanalyzer (Roche Diagnostics GmbH, Mannheim, Germany). Dietary intake was assessed using a semi-quantitative food frequency questionnaire. The SNPs (rs1121923, rs328, rs4922115 and rs285) were genotyped by polymerase chain reaction followed by restriction enzyme digestion and 20% of samples were sequenced to validate the genotypes obtained. Statistical Package for Social Sciences for Windows version 22.0 (SPSS, Chicago, IL) was used for statistical analysis. Results After correction for multiple testing and adjusting for potential confounders, SNPs rs328 and rs285 showed association with HDL-C (P = 0.0004) and serum TAG (P = 1×10−5), respectively. The interaction between SNP rs1121923 and fat intake (energy %) on HDL-C (P = 0.003) was also significant, where, among those who consumed a high fat diet (28.4 ± 2.5%), the T allele carriers (TT + XT) had significantly higher HDL-C concentrations (P = 0.0002) and 30% reduced risk of low HDL-C levels compared to the CC homozygotes. None of the interactions on other lipid traits were statistically significant. Conclusion Our findings suggest that individuals carrying T allele of the SNP rs1121923 have increased HDL-C levels when consuming a high fat diet compared to CC homozygotes. Our finding warrants confirmation in prospective studies and randomized controlled trials

Statistical power considerations in genotype-based recall randomized controlled trials

Randomized controlled trials (RCT) are often underpowered for validating gene-treatment interactions. Using published data from the Diabetes Prevention Program (DPP), we examined power in conventional and genotype-based recall (GBR) trials. We calculated sample size and statistical power for genemetformin interactions (vs. placebo) using incidence rates, gene-drug interaction effect estimates and allele frequencies reported in the DPP for the rs8065082 SLC47A1 variant, a metformin transported encoding locus. We then calculated statistical power for interactions between genetic risk scores (GRS), metformin treatment and intensive lifestyle intervention (ILI) given a range of sampling frames, clinical trial sample sizes, interaction effect estimates, and allele frequencies; outcomes were type 2 diabetes incidence (time-to-event) and change in small LDL particles (continuous outcome). Thereafter, we compared two recruitment frameworks: GBR (participants recruited from the extremes of a GRS distribution) and conventional sampling (participants recruited without explicit emphasis on genetic characteristics). We further examined the influence of outcome measurement error on statistical power. Under most simulated scenarios, GBR trials have substantially higher power to observe gene-drug and gene-lifestyle interactions than same-sized conventional RCTs. GBR trials are becoming popular for validation of gene-treatment interactions; our analyses illustrate the strengths and weaknesses of this design

Dairy consumption and cardiometabolic diseases: systematic review and updated meta-analyses of prospective cohort studies

Purpose of Review Dairy products contain both beneficial and harmful nutrients in relation to cardiometabolic diseases. Here, we provide the latest scientific evidence regarding the relationship between dairy products and cardiometabolic diseases by reviewing the literature and updating meta-analyses of observational studies. Recent Findings We updated our previous meta-analyses of cohort studies on type 2 diabetes, coronary heart disease (CHD), and stroke with nine studies and confirmed previous results. Total dairy and low-fat dairy (per 200 g/d) were inversely associated with a 3–4% lower risk of diabetes. Yogurt was non-linearly inversely associatedwith diabetes (RR = 0.86, 95%CI: 0.83–0.90 at 80 g/ d). Total dairy and milk were not associated with CHD (RR~1.0). An increment of 200 g of daily milk intake was associated with an 8% lower risk of stroke. Summary The latest scientific evidence confirmed neutral or beneficial associations between dairy products and risk of cardiometabolic diseases

Association of apolipoprotein E gene polymorphisms with blood lipids and their interaction with dietary factors

Several candidate genes have been identified in relation to lipid metabolism, and among these, lipoprotein lipase (LPL) and apolipoprotein E (APOE) gene polymorphisms are major sources of genetically determined variation in lipid concentrations. This study investigated the association of two single nucleotide polymorphisms (SNPs) at LPL, seven tagging SNPs at the APOE gene, and a common APOE haplotype (two SNPs) with blood lipids, and examined the interaction of these SNPs with dietary factors. METHODS: The population studied for this investigation included 660 individuals from the Prevention of Cancer by Intervention with Selenium (PRECISE) study who supplied baseline data. The findings of the PRECISE study were further replicated using 1238 individuals from the Caerphilly Prospective cohort (CaPS). Dietary intake was assessed using a validated food-frequency questionnaire (FFQ) in PRECISE and a validated semi-quantitative FFQ in the CaPS. Interaction analyses were performed by including the interaction term in the linear regression model adjusted for age, body mass index, sex and country. RESULTS: There was no association between dietary factors and blood lipids after Bonferroni correction and adjustment for confounding factors in either cohort. In the PRECISE study, after correction for multiple testing, there was a statistically significant association of the APOE haplotype (rs7412 and rs429358; E2, E3, and E4) and APOE tagSNP rs445925 with total cholesterol (P = 4 × 10- 4 and P = 0.003, respectively). Carriers of the E2 allele had lower total cholesterol concentration (5.54 ± 0.97 mmol/L) than those with the E3 (5.98 ± 1.05 mmol/L) (P = 0.001) and E4 (6.09 ± 1.06 mmol/L) (P = 2 × 10- 4) alleles. The association of APOE haplotype (E2, E3, and E4) and APOE SNP rs445925 with total cholesterol (P = 2 × 10- 6 and P = 3 × 10- 4, respectively) was further replicated in the CaPS. Additionally, significant association was found between APOE haplotype and APOE SNP rs445925 with low density lipoprotein cholesterol in CaPS (P = 4 × 10- 4 and P = 0.001, respectively). After Bonferroni correction, none of the cohorts showed a statistically significant SNP-diet interaction on lipid outcomes. CONCLUSION: In summary, our findings from the two cohorts confirm that genetic variations at the APOE locus influence plasma total cholesterol concentrations, however, the gene-diet interactions on lipids require further investigation in larger cohorts

Whole Grain Products, Fish and Bilberries Alter Glucose and Lipid Metabolism in a Randomized, Controlled Trial: The Sysdimet Study

Due to the growing prevalence of type 2 diabetes, new dietary solutions are needed to help improve glucose and lipid metabolism in persons at high risk of developing the disease. Herein we investigated the effects of low-insulin-response grain products, fatty fish, and berries on glucose metabolism and plasma lipidomic profiles in persons with impaired glucose metabolism.Altogether 106 men and women with impaired glucose metabolism and with at least two other features of the metabolic syndrome were included in a 12-week parallel dietary intervention. The participants were randomized into three diet intervention groups: (1) whole grain and low postprandial insulin response grain products, fatty fish three times a week, and bilberries three portions per day (HealthyDiet group), (2) Whole grain enriched diet (WGED) group, which includes principally the same grain products as group (1), but with no change in fish or berry consumption, and (3) refined wheat breads (Control). Oral glucose tolerance, plasma fatty acids and lipidomic profiles were measured before and after the intervention. Self-reported compliance with the diets was good and the body weight remained constant. Within the HealthyDiet group two hour glucose concentration and area-under-the-curve for glucose decreased and plasma proportion of (n-3) long-chain PUFAs increased (False Discovery Rate p-values <0.05). Increases in eicosapentaenoic acid and docosahexaenoic acid associated curvilinearly with the improved insulin secretion and glucose disposal. Among the 364 characterized lipids, 25 changed significantly in the HealthyDiet group, including multiple triglycerides incorporating the long chain (n-3) PUFA.The results suggest that the diet rich in whole grain and low insulin response grain products, bilberries, and fatty fish improve glucose metabolism and alter the lipidomic profile. Therefore, such a diet may have a beneficial effect in the efforts to prevent type 2 diabetes in high risk persons.ClinicalTrials.gov NCT00573781

Omega-3 fatty acids in high-risk cardiovascular patients: a meta-analysis of randomized controlled trials

<p>Abstract</p> <p>Background</p> <p>Multiple randomized controlled trials (RCTs) have examined the cardiovascular effects of omega-3 fatty acids and have provided unexplained conflicting results. A meta-analysis of these RCTs to estimate efficacy and safety and potential sources of heterogeneity may be helpful.</p> <p>Methods</p> <p>The Cochrane library, MEDLINE, and EMBASE were systematically searched to identify all interventional trials of omega-3 fatty acids compared to placebo or usual diet in high-risk cardiovascular patients. The primary outcome was all-cause mortality and secondary outcomes were coronary restenosis following percutaneous coronary intervention and safety. Meta-analyses were carried out using Bayesian random-effects models, and heterogeneity was examined using meta-regression.</p> <p>Results</p> <p>A total of 29 RCTs (n = 35,144) met our inclusion criteria, with 25 reporting mortality and 14 reporting restenosis. Omega-3 fatty acids were not associated with a statistically significant decreased mortality (relative risk [RR] = 0.88, 95% Credible Interval [CrI] = 0.64, 1.03) or with restenosis prevention (RR = 0.89, 95% CrI = 0.72, 1.06), though the probability of some benefit remains high (0.93 and 0.90, respectively). However in meta-regressions, there was a >90% probability that larger studies and those with longer follow-up were associated with smaller benefits. No serious safety issues were identified.</p> <p>Conclusions</p> <p>Although not reaching conventional statistical significance, the evidence to date suggests that omega-3 fatty acids may result in a modest reduction in mortality and restenosis. However, caution must be exercised in interpreting these benefits as results were attenuated in higher quality studies, suggesting that bias may be at least partially responsible. Additional high quality studies are required to clarify the role of omega-3 fatty acid supplementation for the secondary prevention of cardiovascular disease.</p