Complex macrocycle exploration: parallel, heuristic, and constraint-based conformer generation using ForceGen.

ForceGen is a template-free, non-stochastic approach for 2D to 3D structure generation and conformational elaboration for small molecules, including both non-macrocycles and macrocycles. For conformational search of non-macrocycles, ForceGen is both faster and more accurate than the best of all tested methods on a very large, independently curated benchmark of 2859 PDB ligands. In this study, the primary results are on macrocycles, including results for 431 unique examples from four separate benchmarks. These include complex peptide and peptide-like cases that can form networks of internal hydrogen bonds. By making use of new physical movements ("flips" of near-linear sub-cycles and explicit formation of hydrogen bonds), ForceGen exhibited statistically significantly better performance for overall RMS deviation from experimental coordinates than all other approaches. The algorithmic approach offers natural parallelization across multiple computing-cores. On a modest multi-core workstation, for all but the most complex macrocycles, median wall-clock times were generally under a minute in fast search mode and under 2 min using thorough search. On the most complex cases (roughly cyclic decapeptides and larger) explicit exploration of likely hydrogen bonding networks yielded marked improvements, but with calculation times increasing to several minutes and in some cases to roughly an hour for fast search. In complex cases, utilization of NMR data to constrain conformational search produces accurate conformational ensembles representative of solution state macrocycle behavior. On macrocycles of typical complexity (up to 21 rotatable macrocyclic and exocyclic bonds), design-focused macrocycle optimization can be practically supported by computational chemistry at interactive time-scales, with conformational ensemble accuracy equaling what is seen with non-macrocyclic ligands. For more complex macrocycles, inclusion of sparse biophysical data is a helpful adjunct to computation

Upwind MacCormack Euler solver with non-equilibrium chemistry

A computer code, designated UMPIRE, is currently under development to solve the Euler equations in two dimensions with non-equilibrium chemistry. UMPIRE employs an explicit MacCormack algorithm with dissipation introduced via Roe's flux-difference split upwind method. The code also has the capability to employ a point-implicit methodology for flows where stiffness is introduced through the chemical source term. A technique consisting of diagonal sweeps across the computational domain from each corner is presented, which is used to reduce storage and execution requirements. Results depicting one dimensional shock tube flow for both calorically perfect gas and thermally perfect, dissociating nitrogen are presented to verify current capabilities of the program. Also, computational results from a chemical reactor vessel with no fluid dynamic effects are presented to check the chemistry capability and to verify the point implicit strategy

Endothelial Injury in Scleroderma

Scleroderma, which follows rheumatoid arthritis and systemic lupus erythematosus as the third most prevalent rheumatic disorder, is poorly understood. Connective tissue abnormalities have been explored extensively (1); recently, vascular involvement has been emphasized as a unifying pathogenetic concept (2, 3). The vascular features in scleroderma include Raynaud\u27s phenomenon; an early, edematous phase of the disorder; telangiectasia; capillary abnormalities as seen by nailfold and ultrastructural microscopy; and widespread vascular pathology noted in all involved organs. The most striking histological abnormalities occur in small arteries and arterioles and consist of distinctive intimal proliferation of cells arranged concentrically in a matrix of ground substance; the cells are thought to originate from medial smooth muscle and to migrate toward the intima after injury to the endothelium (4). Evidence for endothelial injury includes: (a) the disappearance of endothelium in association with thrombosis or fibrinoid necrosis in ultrastructural studies; (b) the absence of endothelial cells within the thickened intima (4, 3) the duplication of basement membrane, a common observation in scleroderma and known to occur after endothelial perturbation in other settings. The ability to isolate, characterize, and maintain endothelial cells in vitro provides a target-cell population to study endothelial damage in scleroderma. The present report describes the effect of scleroderma serum on endothelial, smooth muscle, and fibroblast cell types. Sera from patients with scleroderma (31/52) and Raynaud\u27s syndrome (11/19) contain cytotoxic activity specific for endothelial cells which is nondialyzable, heat-stable, and elutes with albumin on gel-filtration chromatography

A Follow-Up Study of the Graduates of Urbandale High School, 1954-1958

68 leave

Merger and Acquisition Due Diligence: A Proposed Framework to Incorporate Data Privacy, Information Security, E-Discovery, and Information Governance into Due Diligence Practices

Merger and Acquisition or “M&A” deals are both figuratively and literally big business, where the stakes for the organization are often the highest. While casual observers might expect that the importance attached to these deals makes each new deal the vanguard for incorporating metrics and practices regarding every efficiency and contingency, existing research demonstrates that this is decidedly not the case

Socio-psycological aspects of stydying sharnirnay hinged pupet ( to the question of types of toys)

The material is devoted to the problems and type of games model of contemporary culture. We produce the variant of dolls types, division on the base realistic images. The popular bolt joined realistic doll isn’t the example of order games model.Статья посвящена специфике игровых моделей в современной культуре, предлагается вариант типологии игрушки, где разделение проводится по границе подвижности и степени условности. Шарнирная реалистичная кукла рассматривается как проявление нарушения основополагающих законов игры и отсутствия необходимых культурных цензов в современном социуме

Merger and Acquisition Due Diligence Part II- The Devil in the Details

Our prior scholarship examined the legal and technical challenges involved in modern Merger & Acquisition ( M&A ) due diligence practices associated with transactions ( Deals ), given recent but steady advances in technology and related increases in sophistication seen in Deal participants-primarily the organizations or assets targeted (the Targets ) as part of the Deal, and the organizations that pursued and/or resulted from the Deal (the Acquirers ). We then proposed a framework addressing five particular verticals of interest and concern: data privacy ( DP ), information security ( IS ), e-Discovery, information governance ( IG ), and the due diligence and record keeping associated with the Deal itself ( Deal Information ) (collectively, the Framework )

Forecasts for the Attainment of Major Research Milestones in Parkinson's Disease.

BACKGROUND: Projections about when research milestones will be attained are often of interest to patients and can help inform decisions about research funding and health system planning. OBJECTIVE: To collect aggregated expert forecasts on the attainment of 11 major research milestones in Parkinson's disease (PD). METHODS: Experts were asked to provide predictions about the attainment of 11 milestones in PD research in an online survey. PD experts were identified from: 1) The Michael J. Fox Foundation for Parkinson's Research data base, 2) doctors specializing in PD at top ranked neurology centers in the US and Canada, and 3) corresponding authors of articles on PD in top medical journals. Judgments were aggregated using coherence weighting. We tested the relationship between demographic variables and individual judgments using a linear regression. RESULTS: 249 PD experts completed the survey. In the aggregate, experts believed that new treatments like gene therapy for monogenic PD, immunotherapy and cell therapy had 56.1%, 59.7%, and 66.6% probability, respectively of progressing in the clinical approval process within the next 10 years. Milestones involving existing management approaches, like the approval of a deep brain stimulation device or a body worn sensor had 78.4% and 82.2% probability of occurring within the next 10 years. Demographic factors were unable to explain deviations from the aggregate forecast (R2 = 0.029). CONCLUSIONS: Aggregated expert opinion suggests that milestones for the advancement of new treatment options for PD are still many years away. However, other improvements in PD diagnosis and management are believed to be near at hand

Comparison of Patient and Expert Perceptions of the Attainment of Research Milestones in Parkinson's Disease.

BACKGROUND: Commentators suggest that patients have unrealistic expectations about the pace of research advances and that such expectations interfere with patient decision-making. OBJECTIVE: The objective of this study was to compare expert expectations about the timing of research milestone attainment with those of patients who follow Parkinson's disease (PD) research. METHODS: Patients with PD and experts were asked to provide forecasts about 11 milestones in PD research in an online survey. PD experts were identified from a Michael J. Fox Foundation database, highly ranked neurology centers in the United States and Canada, and corresponding authors of articles on PD in top medical journals. Patients with PD were recruited through the Michael J. Fox Foundation. We tested whether patient forecasts differed on average from expert forecasts. We also tested whether differences between patient forecasts and the average expert forecasts were associated with any demographic factors. RESULTS: A total of 256 patients and 249 PD experts completed the survey. For 9 of the 11 milestones, patients' forecasts were on average higher than those of experts. Only exercise therapy met our 10% difference threshold for practical significance. Education was the only demographic that predicted patient deviations from expert forecasts on milestone forecasts. Patients offered significantly higher forecasts than experts that the clinical trials used in milestone queries would report positive primary outcomes. CONCLUSIONS: Differences between patient and expert expectations about research milestones were generally minor, suggesting that there is little cause for concern that patients who follow PD research are unduly swayed by inaccurate representations of research advancement in the media or elsewhere. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q₁ = 4.9 % and q₃ = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data