Use of machine learning algorithms to classify binary protein sequences as highly-designable or poorly-designable

<p>Abstract</p> <p>Background</p> <p>By using a standard Support Vector Machine (SVM) with a Sequential Minimal Optimization (SMO) method of training, Naïve Bayes and other machine learning algorithms we are able to distinguish between two classes of protein sequences: those folding to highly-designable conformations, or those folding to poorly- or non-designable conformations.</p> <p>Results</p> <p>First, we generate all possible compact lattice conformations for the specified shape (a hexagon or a triangle) on the 2D triangular lattice. Then we generate all possible binary hydrophobic/polar (H/P) sequences and by using a specified energy function, thread them through all of these compact conformations. If for a given sequence the lowest energy is obtained for a particular lattice conformation we assume that this sequence folds to that conformation. Highly-designable conformations have many H/P sequences folding to them, while poorly-designable conformations have few or no H/P sequences. We classify sequences as folding to either highly – or poorly-designable conformations. We have randomly selected subsets of the sequences belonging to highly-designable and poorly-designable conformations and used them to train several different standard machine learning algorithms.</p> <p>Conclusion</p> <p>By using these machine learning algorithms with ten-fold cross-validation we are able to classify the two classes of sequences with high accuracy – in some cases exceeding 95%.</p

Challenges in multidisciplinary cancer care among general surgeons in Canada

<p>Abstract</p> <p>Background</p> <p>While many factors can influence the way that cancer care is delivered, including the way that evidence is packaged and disseminated, little research has evaluated how health care professionals who manage cancer patients seek and use this information to identify whether and how this could be supported. Through interviews we identified that general surgeons experience challenges in coordinating care for complex cancer patients whose management is not easily addressed by guidelines, and conducted a population-based survey of general surgeon information needs and information seeking practices to extend these findings.</p> <p>Methods</p> <p>General surgeons with privileges at acute care hospitals in Ontario, Canada were mailed a questionnaire to solicit information needs (task, importance), information seeking (source, frequency of and reasons for use), key challenges and suggested solutions. Non-responders received up to three reminder packages. Significant differences among sub-groups (age, setting) were examined statistically (Kruskal Wallis, Mann Whitney, Chi Square). Standard qualitative methods were used to thematically analyze open-ended responses.</p> <p>Results</p> <p>The response rate was 44.2% (170/385) representing all 14 health regions. System resource constraints (60.4%), comorbidities (56.4%) and physiologic factors (51.8%) were top-ranked issues creating information needs. Local surgical colleagues (84.6%), other local colleagues (82.2%) and the Internet (81.1%) were top-ranked sources of information, primarily due to familiarity and speed of access. No resources were considered to be highly applicable to patient care. Challenges were related to limitations in diagnostics and staging, operative resources, and systems to support multidisciplinary care, together accounting for 76.0% of all reported issues. Findings did not differ significantly by surgeon age or setting of care.</p> <p>Conclusion</p> <p>General surgeons appear to use a wide range of information resources but they may not address the complex needs of many cancer patients. Decision-making is challenged by informational and logistical issues related to the coordination of multidisciplinary care. This suggests that limitations in system capacity may, in part, contribute to variable guideline compliance. Further research is required to evaluate the appropriateness of information seeking, and both concurrent and consecutive mechanisms by which to achieve multidisciplinary care.</p

Information transfer: what do decision makers want and need from researchers?

<p>Abstract</p> <p>Purpose</p> <p>The purpose of this study was to undertake a systematic assessment of the need for research-based information by decision-makers working in community-based organizations. It is part of a more comprehensive knowledge transfer and exchange strategy that seeks to understand both the content required and the format/methods by which such information should be presented.</p> <p>Methods</p> <p>This was a cross-sectional telephone survey. Questions covered current practices, research use, and demographic information, as well as preferences for receiving research information. Three types of organizations participated: Children's Treatment Centres of Ontario (CTCs); Ontario Community Care Access Centres (CCACs); and District Health Councils (DHCs). The analysis used descriptive statistics and analyses of variance (ANOVA) to describe and explore variations across organizations.</p> <p>Results</p> <p>The participation rate was 70%. The highest perception of barriers to the use of research information was reported by the CCAC respondents, followed by CTCs and DHCs. The CTCs and DHCs reported greater use of research evidence in planning decisions as compared to the CCACs. Four sources of information transfer were consistently identified. These were websites, health-related research journals, electronic mail, and conferences and workshops. Preferred formats for receiving information were executive summaries, abstracts, and original articles.</p> <p>Conclusion</p> <p>There were a number of similarities across organization type with respect to perceived barriers to research transfer, as well as the types of activities the organizations engaged in to promote research use in decision-making. These findings support the importance of developing interactive, collaborative knowledge transfer strategies, as well as the need to foster relationships with health care decision-makers, practitioners and policymakers.</p

Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.