14 research outputs found

    AI is a viable alternative to high throughput screening: a 318-target study

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    : High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

    Parent smoker role conflict and planning to quit smoking: a cross-sectional study

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    Abstract Background Role conflict can motivate behavior change. No prior studies have explored the association between parent/smoker role conflict and readiness to quit. The objective of the study is to assess the association of a measure of parent/smoker role conflict with other parent and child characteristics and to test the hypothesis that parent/smoker role conflict is associated with a parent’s intention to quit smoking in the next 30 days. As part of a cluster randomized controlled trial to address parental smoking (Clinical Effort Against Secondhand Smoke Exposure—CEASE), research assistants completed exit interviews with 1980 parents whose children had been seen in 20 Pediatric Research in Office Settings (PROS) practices and asked a novel identity-conflict question about “how strongly you agree or disagree” with the statement, “My being a smoker gets in the way of my being a parent.” Response choices were dichotomized as “Strongly Agree” or “Agree” versus “Disagree” or “Strongly Disagree” for the analysis. Parents were also asked whether they were “seriously planning to quit smoking in 30 days.” Chi-square and logistic regression were performed to assess the association between role conflict and other parent/children characteristics. A similar strategy was used to determine whether role conflict was independently associated with intention to quit in the next 30 days. Methods As part of a RTC in 20 pediatric practices, exit interviews were held with smoking parents after their child’s exam. Parents who smoked were asked questions about smoking behavior, smoke-free home and car rules, and role conflict. Role conflict was assessed with the question, “Please tell me how strongly you agree or disagree with the statement: ‘My being a smoker gets in the way of my being a parent.’ (Answer choices were: “Strongly agree, Agree, Disagree, Strongly Disagree.”) Results Of 1980 eligible smokers identified, 1935 (97%) responded to the role-conflict question, and of those, 563 (29%) reported experiencing conflict. Factors that were significantly associated with parent/smoker role conflict in the multivariable model included: being non-Hispanic white, allowing home smoking, the child being seen that day for a sick visit, parents receiving any assistance for their smoking, and planning to quit in the next 30 days. In a separate multivariable logistic regression model, parent/smoker role conflict was independently associated with intention to quit in the next 30 days [AOR 2.25 (95% CI 1.80-2.18)]. Conclusion This study demonstrated an association between parent/smoker role conflict and readiness to quit. Interventions that increase parent/smoker role conflict might act to increase readiness to quit among parents who smoke. Trial registration Clinical trial registration number: NCT00664261

    Innate immune mediators in cancer: between defense and resistance

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    Development of a neonatal adverse event severity scale through a Delphi consensus approach

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    BACKGROUND: Assessment of the seriousness, expectedness and causality are necessary for any adverse event (AE) in a clinical trial. In addition, assessing AE severity helps determine the importance of the AE in the clinical setting. Standardisation of AE severity criteria could make safety information more reliable and comparable across trials. Although standardised AE severity scales have been developed in other research fields, they are not suitable for use in neonates. The development of an AE severity scale to facilitate the conduct and interpretation of neonatal clinical trials is therefore urgently needed. METHODS: A stepwise consensus process was undertaken within the International Neonatal Consortium (INC) with input from all relevant stakeholders. The consensus process included several rounds of surveys (based on a Delphi approach), face-to-face meetings and a pilot validation. RESULTS: Neonatal AE severity was classified by five grades (mild, moderate, severe, life threatening or death). AE severity in neonates was defined by the effect of the AE on age appropriate behaviour, basal physiological functions and care changes in response to the AE. Pilot validation of the generic criteria revealed κ=0.23 and guided further refinement. This generic scale was applied to 35 typical and common neonatal AEs resulting in the INC neonatal AE severity scale (NAESS) V.1.0, which is now publicly available. DISCUSSION: The INC NAESS is an ongoing effort that will be continuously updated. Future perspectives include further validation and the development of a training module for users.status: publishe
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