SIDEKICK: Genomic data driven analysis and decision-making framework

<p>Abstract</p> <p>Background</p> <p>Scientists striving to unlock mysteries within complex biological systems face myriad barriers in effectively integrating available information to enhance their understanding. While experimental techniques and available data sources are rapidly evolving, useful information is dispersed across a variety of sources, and sources of the same information often do not use the same format or nomenclature. To harness these expanding resources, scientists need tools that bridge nomenclature differences and allow them to integrate, organize, and evaluate the quality of information without extensive computation.</p> <p>Results</p> <p>Sidekick, a genomic data driven analysis and decision making framework, is a web-based tool that provides a user-friendly intuitive solution to the problem of information inaccessibility. Sidekick enables scientists without training in computation and data management to pursue answers to research questions like "What are the mechanisms for disease X" or "Does the set of genes associated with disease X also influence other diseases." Sidekick enables the process of combining heterogeneous data, finding and maintaining the most up-to-date data, evaluating data sources, quantifying confidence in results based on evidence, and managing the multi-step research tasks needed to answer these questions. We demonstrate Sidekick's effectiveness by showing how to accomplish a complex published analysis in a fraction of the original time with no computational effort using Sidekick.</p> <p>Conclusions</p> <p>Sidekick is an easy-to-use web-based tool that organizes and facilitates complex genomic research, allowing scientists to explore genomic relationships and formulate hypotheses without computational effort. Possible analysis steps include gene list discovery, gene-pair list discovery, various enrichments for both types of lists, and convenient list manipulation. Further, Sidekick's ability to characterize pairs of genes offers new ways to approach genomic analysis that traditional single gene lists do not, particularly in areas such as interaction discovery.</p

Cancer Risk in Diabetic Patients Treated with Metformin: A Systematic Review and Meta-analysis

BACKGROUND: A growing body of evidence has suggested that metformin potentially reduces the risk of cancer. Our objective was to enhance the precision of estimates of the effect of metformin on the risk of any-site and site-specific cancers in patients with diabetes. METHODS/PRINCIPAL FINDINGS: We performed a search of MEDLINE, EMBASE, ISI Web of Science, Cochrane Library, and ClinicalTrials.gov for pertinent articles published as of October 12, 2011, and included them in a systematic review and meta-analysis. We calculated pooled risk ratios (RRs) for overall cancer mortality and cancer incidence. Of the 21,195 diabetic patients reported in 6 studies (4 cohort studies, 2 RCTs), 991 (4.5%) cases of death from cancer were reported. A total of 11,117 (5.3%) cases of incident cancer at any site were reported among 210,892 patients in 10 studies (2 RCTs, 6 cohort studies, 2 case-control studies). The risks of cancer among metformin users were significantly lower than those among non-metformin users: the pooled RRs (95% confidence interval) were 0.66 (0.49-0.88) for cancer mortality, 0.67 (0.53-0.85) for all-cancer incidence, 0.68 (0.53-0.88) for colorectal cancer (n = 6), 0.20 (0.07-0.59) for hepatocellular cancer (n = 4), 0.67 (0.45-0.99) for lung cancer (n = 3). CONCLUSION/SIGNIFICANCE: The use of metformin in diabetic patients was associated with significantly lower risks of cancer mortality and incidence. However, this analysis is mainly based on observational studies and our findings underscore the more need for long-term RCTs to confirm this potential benefit for individuals with diabetes

Search for Higgs boson pair production in the gamma gamma b(b)over-bar final state in pp collisions at root s=13 TeV

A search is presented for the production of a pair of Higgs bosons, where one decays into two photons and the other one into a bottom quark-antiquark pair. The analysis is performed using proton-proton collision data at root s = 13 TeV recorded in 2016 by the CMS detector at the LHC, corresponding to an integrated luminosity of 35.9 fb(-1) . The results are in agreement with standard model (SM) predictions. In a search for resonant production, upper limits are set on the cross section for new spin-0 or spin-2 particles. For the SM-like nonresonant production hypothesis, the data exclude a product of cross section and branching fraction larger than 2.0 fb at 95% confidence level (CL), corresponding to about 24 times the SM prediction. Values of the effective Higgs boson self-coupling K X are constrained to be within the range -11 < K-lambda < 17 at 95% CL, assuming all other Higgs boson couplings are at their SM value. The constraints on K-lambda, are the most restrictive to date. (C) 2018 The Author(s). Published by Elsevier B.V.Peer reviewe

Search for the X(5568) State Decaying into B-s(0)pi(+/-) in Proton-Proton Collisions at root s=8 TeV

A search for resonancelike structures in the B-s(0)pi(+/-) invariant mass spectrum is performed using proton-proton collision data collected by the CMS experiment at the LHC at root s = 8 TeV, corresponding to an integrated luminosity of 19.7 fb(-1). The B-s(0) mesons are reconstructed in the decay chain B-s(0) -> J/Psi phi, with J/Psi -> mu(+) mu(-) and phi -> K+K-. The B-s(0)pi(+/-) invariant mass distribution shows no statistically significant peaks for different selection requirements on the reconstructed B-s(0) and pi(+/-) candidates. Upper limits are set on the relative production rates of the X(5568) and B-s(0) states times the branching fraction of the decay X(5568)(+/-) -> B-s(0)pi(+/-). In addition, upper limits are obtained as a function of the mass and the natural width of possible exotic states decaying into B-s(0)pi(+/-).Peer reviewe

Measurement of nuclear modification factors of ϒ(1S), ϒ(2S), and ϒ(3S) mesons in PbPb collisions at √sNN = 5.02 TeV

The cross sections for ϒ(1S), ϒ(2S), and ϒ(3S) production in lead–lead (PbPb) and proton–proton (pp) collisions at √sNN = 5.02 TeV have been measured using the CMS detector at the LHC. The nuclear modification factors, RAA, derived from the PbPb-to-pp ratio of yields for each state, are studied as functions of meson rapidity and transverse momentum, as well as PbPb collision centrality. The yields of all three states are found to be significantly suppressed, and compatible with a sequential ordering of the suppression, RAA(ϒ(1S)) > RAA(ϒ(2S)) > RAA(ϒ(3S)). The suppression of ϒ(1S) is larger than that seen at √sNN = 2.76 TeV, although the two are compatible within uncertainties. The upper limit on the RAA of ϒ(3S) integrated over pT, rapidity and centrality is 0.096 at 95% confidence level, which is the strongest suppression observed for a quarkonium state in heavy ion collisions to date

Search for excited leptons in final states in proton-proton collisions at root s=13 TeV

A search is presented for excited electrons and muons in ℓℓγ final states at the LHC. The search is based on a data sample corresponding to an integrated luminosity of 35.9 fb−1 of proton-proton collisions at a center-of-mass energy of 13 TeV, collected with the CMS detector in 2016. This is the first search for excited leptons at s√ = 13 TeV. The observation is consistent with the standard model background prediction, and the most stringent exclusion limits to date are set on the excited lepton mass and the compositeness scale, at 95% confidence level. Excited electrons and muons are excluded for masses below 3.9 and 3.8 TeV, respectively, under the assumption that the excited lepton mass equals the compositeness scale. The best observed limit on the compositeness scale is obtained with an excited lepton mass of around 1.0 TeV, excluding values below 25 TeV for both excited electrons and muons

[Measures for allogeneic blood conservation in surgery]

The aim of all efforts to reduce the need of allogeneic blood transfusions is to avoid associated risks. There should particularly be a favourable effect according to the rate of transfusion-transmitted virus infections and immunological side-effects. The acceptance of an individually adjusted lowest haematocrit level and the minimisation of intra-operative blood loss by the application of optimal surgical techniques are among the most essential strategies to reduce or even avoid allogeneic blood transfusions. In addition the following interventions are generally accepted: Preoperative autologous blood donation, where appropriate supported by erythropoietin Preoperative haemodilution, where appropriate supported by erythropoietin Intra- and postoperative blood salvage Topical or systemic pharmacologic interventions to accelerate haemostasis Controlled hypotension Efficacy and indication of the different measures always depend on the individual circumstances of the specific patient. Therefore one should develop an individual approach for every case. In this context the most important subjects are an optimal coordination and if required an appropriate combination of the discussed methods. Algorithms which preoperatively allow approximate calculation of expected transfusion need may be a meaningful tool to facilitate blood conservation planning. However, at the same time one must consider that all strategies to reduce allogeneic transfusion needs are also associated with particular risks. Therefore one has to weigh carefully the pros and cons prior to their application, including the possible alternative of allogeneic transfusion in one's decision making process