Reproducibility in modeling and simulation of the knee:Academic, industry, and regulatory perspectives

Stakeholders in the modeling and simulation (M&amp;S) community organized a workshop at the 2019 Annual Meeting of the Orthopaedic Research Society (ORS) entitled “Reproducibility in Modeling and Simulation of the Knee: Academic, Industry, and Regulatory Perspectives.” The goal was to discuss efforts among these stakeholders to address irreproducibility in M&amp;S focusing on the knee joint. An academic representative from a leading orthopedic hospital in the United States described a multi-institutional, open effort funded by the National Institutes of Health to assess model reproducibility in computational knee biomechanics. A regulatory representative from the United States Food and Drug Administration indicated the necessity of standards for reproducibility to increase utility of M&amp;S in the regulatory setting. An industry representative from a major orthopedic implant company emphasized improving reproducibility by addressing indeterminacy in personalized modeling through sensitivity analyses, thereby enhancing preclinical evaluation of joint replacement technology. Thought leaders in the M&amp;S community stressed the importance of data sharing to minimize duplication of efforts. A survey comprised 103 attendees revealed strong support for the workshop and for increasing emphasis on computational modeling at future ORS meetings. Nearly all survey respondents (97%) considered reproducibility to be an important issue. Almost half of respondents (45%) tried and failed to reproduce the work of others. Two-thirds of respondents (67%) declared that individual laboratories are most responsible for ensuring reproducible research whereas 44% thought that journals are most responsible. Thought leaders and survey respondents emphasized that computational models must be reproducible and credible to advance knee M&amp;S.</p

Design of Organocatalysts for Asymmetric Propargylations through Computational Screening

The development of asymmetric catalysts is typically driven by the experimental screening of potential catalyst designs. Herein, we demonstrate the design of asymmetric propargylation catalysts through computational screening. This was done using our computational toolkit AARON (automated alkylation reaction optimizer for <i>N</i>-oxides), which automates the prediction of enantioselectivities for bidentate Lewis base catalyzed alkylation reactions. A systematic screening of 59 potential catalysts built on 6 bipyridine <i>N</i>,<i>N</i>′-dioxide-derived scaffolds results in predicted ee values for the propargylation of benzaldehyde ranging from 45% (<i>S</i>) to 99% (<i>R</i>), with 12 ee values exceeding 95%. These data provide a broad set of experimentally testable predictions. Moreover, the associated data revealed key details regarding the role of stabilizing electrostatic interactions in asymmetric propargylations, which were harnessed in the design of a propargylation catalyst for which the predicted ee exceeds 99%

Design of Organocatalysts for Asymmetric Propargylations through Computational Screening

The development of asymmetric catalysts is typically driven by the experimental screening of potential catalyst designs. Herein, we demonstrate the design of asymmetric propargylation catalysts through computational screening. This was done using our computational toolkit AARON (automated alkylation reaction optimizer for <i>N</i>-oxides), which automates the prediction of enantioselectivities for bidentate Lewis base catalyzed alkylation reactions. A systematic screening of 59 potential catalysts built on 6 bipyridine <i>N</i>,<i>N</i>′-dioxide-derived scaffolds results in predicted ee values for the propargylation of benzaldehyde ranging from 45% (<i>S</i>) to 99% (<i>R</i>), with 12 ee values exceeding 95%. These data provide a broad set of experimentally testable predictions. Moreover, the associated data revealed key details regarding the role of stabilizing electrostatic interactions in asymmetric propargylations, which were harnessed in the design of a propargylation catalyst for which the predicted ee exceeds 99%

Prospects for the Computational Design of Bipyridine <i>N</i>,<i>N</i>′‑Dioxide Catalysts for Asymmetric Propargylation Reactions

Stereoselectivities were predicted for the allylation of benzaldehyde using allyl­trichlorosilanes catalyzed by 18 axially chiral bipyridine <i>N</i>,<i>N</i>′-dioxides. This was facilitated by the computational toolkit AARON (Automated Alkylation Reaction Optimizer for <i>N</i>-oxides), which automates the optimization of all of the required transition-state structures for such reactions. Overall, we were able to predict the sense of stereoinduction for all 18 of the catalysts, with predicted ee’s in reasonable agreement with experiment for 15 of the 18 catalysts. Curiously, we find that ee’s predicted from relative energy barriers are more reliable than those based on either relative enthalpy or free energy barriers. The ability to correctly predict the stereoselectivities for these allylation catalysts in an automated fashion portends the computational screening of potential organocatalysts for this and related reactions. By studying a large number of allylation catalysts, we were also able to gain new insight into the origin of stereoselectivity in these reactions, extending our previous model for bipyridine <i>N</i>-oxide-catalyzed alkylation reactions (<i>Organic Letters</i> <b>2012</b>, <i>14</i>, 5310). Finally, we assessed the potential performance of these bipyridine <i>N</i>,<i>N′</i>-dioxide catalysts for the propargylation of benzaldehyde using allenyl­trichlorosilanes, finding that two of these catalysts should provide reasonable stereoselectivities for this transformation. Most importantly, we show that bipyridine <i>N</i>,<i>N</i>′-dioxides constitute an ideal scaffold for the development of asymmetric propargylation catalysts and, along with AARON, should enable the rational design of such catalysts purely through computation

An Electronic Tool to Support Patient-Centered Broad Consent: A Multi-Arm Randomized Clinical Trial in Family Medicine

Patients are frequently asked to share their personal health information. The objective of this study was to compare the effects on patient experiences of 3 electronic consent (e-consent) versions asking patients to share their health records for research. A multi-arm randomized controlled trial was conducted from November 2017 through November 2018. Adult patients (n = 734) were recruited from 4 family medicine clinics in Florida. Using a tablet computer, participants were randomized to (1) a standard e-consent (standard), (2) an e-consent containing standard information plus hyperlinks to additional interactive details (interactive), or (3) an e-consent containing standard information, interactive hyperlinks, and factual messages about data protections and researcher training (trust-enhanced). Satisfaction (1 to 5), subjective understanding (0 to 100), and other outcomes were measured immediately, at 1 week, and at 6 months. A majority of participants (94%) consented to future uses of their health record information for research. No differences in study outcomes between versions were observed at immediate or 1-week follow-up. At 6-month follow-up, compared with the standard e-consent, participants who used the interactive e-consent reported greater satisfaction (B = 0.43; SE = 0.09; <.001) and subjective understanding (B = 18.04; SE = 2.58; <.001). At 6-month follow-up, compared with the interactive e-consent, participants who used the trust-enhanced e-consent reported greater satisfaction (B = 0.9; SE = 1.0; <.001) and subjective understanding (B = 32.2; SE = 2.6, <.001). Patients who used e-consents with interactive research details and trust-enhancing messages reported higher satisfaction and understanding at 6-month follow-up. Research institutions should consider developing and further validating e-consents that interactively deliver information beyond that required by federal regulations, including facts that may enhance patient trust in research

High-Frequency (>100 GHz) and High-Speed (<10 ps) Electronic Devices

Contains an introduction, reports on four research projects and a list of publications.National Aeronautics and Space Administration Grant NAGW-4691National Science Foundation Grant AST 94-23608U.S. Army Research Laboratory/Federated Laboratory Grant QK-8819National Science Foundation/MRSEC Grant DMR 94-00334U.S. Army Research Office Grant DAAH04-95-1-0610Federated Laboratory Grant QK-8819Hertz Foundation FellowshipU.S. Army Research Office/AASERT Grant DAAH04-94-G-016