Research on “post‐metallocene” polymerization catalysis ranges methodologically from fundamental mechanistic studies of polymerization reactions over catalyst design to material properties of the ...polyolefins prepared. A common goal of these studies is the creation of practically useful new polyolefin materials or polymerization processes. This Review gives a comprehensive overview of post‐metallocene polymerization catalysts that have been put into practice. The decisive properties for this success of a given catalyst structure are delineated.
“Post‐metallocene” polymerization catalysis research ranges from fundamental mechanistic studies by catalyst design to material properties of polyolefins. A common goal of these studies is the creation of practically useful new materials or processes. A comprehensive overview of post‐metallocene polymerization catalysts that have been put into practice is provided. The decisive properties for this success of a given catalyst structure are delineated.
The Society of Thoracic Surgeons (STS) uses statistical models to create risk-adjusted performance metrics for Adult Cardiac Surgery Database (ACSD) participants. Because of temporal changes in ...patient characteristics and outcomes, evolution of surgical practice, and additional risk factors available in recent ACSD versions, completely new risk models have been developed.
Using July 2011 to June 2014 ACSD data, risk models were developed for operative mortality, stroke, renal failure, prolonged ventilation, mediastinitis/deep sternal wound infection, reoperation, major morbidity or mortality composite, prolonged postoperative length of stay, and short postoperative length of stay among patients who underwent isolated coronary artery bypass grafting surgery (n = 439,092), aortic or mitral valve surgery (n = 150,150), or combined valve plus coronary artery bypass grafting surgery (n = 81,588). Separate models were developed for each procedure and endpoint except mediastinitis/deep sternal wound infection, which was analyzed in a combined model because of its infrequency. A surgeon panel selected predictors by assessing model performance and clinical face validity of full and progressively more parsimonious models. The ACSD data (July 2014 to December 2016) were used to assess model calibration and to compare discrimination with previous STS risk models.
Calibration in the validation sample was excellent for all models except mediastinitis/deep sternal wound infection, which slightly underestimated risk and will be recalibrated in feedback reports. The c-indices of new models exceeded those of the last published STS models for all populations and endpoints except stroke in valve patients.
New STS ACSD risk models have generally excellent calibration and discrimination and are well suited for risk adjustment of STS performance metrics.
The last published version of The Society of Thoracic Surgeons (STS) Adult Cardiac Surgery Database (ACSD) risk models were developed in 2008 based on patient data from 2002 to 2006 and have been ...periodically recalibrated. In response to evolving changes in patient characteristics, risk profiles, surgical practice, and outcomes, the STS has now developed a set of entirely new risk models for adult cardiac surgery.
New models were estimated for isolated coronary artery bypass grafting surgery (CABG n = 439,092), isolated aortic or mitral valve surgery (n = 150,150), and combined valve plus CABG procedures (n = 81,588). The development set was based on July 2011 to June 2014 STS ACSD data; validation was performed using July 2014 to December 2016 data. Separate models were developed for operative mortality, stroke, renal failure, prolonged ventilation, reoperation, composite major morbidity or mortality, and prolonged or short postoperative length of stay. Because of its low occurrence rate, a combined model incorporating all operative types was developed for deep sternal wound infection/mediastinitis.
Calibration was excellent except for the deep sternal wound infection/mediastinitis model, which slightly underestimated risk because of higher rates of this endpoint in the more recent validation data; this will be recalibrated in each feedback report. Discrimination (c-index) of all models was superior to that of 2008 models except for the stroke model for valve patients.
Completely new STS ACSD risk models have been developed based on contemporary patient data; their performance is superior to that of previous STS ACSD models.
In catalytic copolymerization, undesired chain transfer after incorporation of a polar vinyl monomer is a fundamental problem. We show an approach to overcome this problem by a fast consecutive ...insertion. The second double bond of acrylic anhydride rapidly inserts intramolecularly to regio- and stereoselectively form a cyclic repeat unit and a primary alkyl favorable for chain growth (>96%). This results in significantly enhanced copolymer molecular weights vs monofunctional acrylate monomers.
The aim of this study was to evaluate the diagnostic accuracy of a multipurpose image analysis software based on deep learning with artificial neural networks for the detection of breast cancer in an ...independent, dual-center mammography data set.
In this retrospective, Health Insurance Portability and Accountability Act-compliant study, all patients undergoing mammography in 2012 at our institution were reviewed (n = 3228). All of their prior and follow-up mammographies from a time span of 7 years (2008-2015) were considered as a reference for clinical diagnosis. After applying exclusion criteria (missing reference standard, prior procedures or therapies), patients with the first diagnosis of a malignoma or borderline lesion were selected (n = 143). Histology or clinical long-term follow-up served as reference standard. In a first step, a breast density-and age-matched control cohort was selected (n = 143) from the remaining patients with more than 2 years follow-up (n = 1003). The neural network was trained with this data set. From the publicly available Breast Cancer Digital Repository data set, patients with cancer and a matched control cohort were selected (n = 35 × 2). The performance of the trained neural network was also tested with this external data set. Three radiologists (3, 5, and 10 years of experience) evaluated the test data set. In a second step, the neural network was trained with all cases from January to September and tested with cases from October to December 2012 (screening-like cohort). The radiologists also evaluated this second test data set. The areas under the receiver operating characteristic curve between readers and the neural network were compared. A Bonferroni-corrected P value of less than 0.016 was considered statistically significant.
Mean age of patients with lesion was 59.6 years (range, 35-88 years) and in controls, 59.1 years (35-83 years). Breast density distribution (A/B/C/D) was 21/59/42/21 and 22/60/41/20, respectively. Histologic diagnoses were invasive ductal carcinoma in 90, ductal in situ carcinoma in 13, invasive lobular carcinoma in 13, mucinous carcinoma in 3, and borderline lesion in 12 patients. In the first step, the area under the receiver operating characteristic curve of the trained neural network was 0.81 and comparable on the test cases 0.79 (P = 0.63). One of the radiologists showed almost equal performance (0.83, P = 0.17), whereas 2 were significantly better (0.91 and 0.94, P < 0.016). In the second step, performance of the neural network (0.82) was not significantly different from the human performance (0.77-0.87, P > 0.016); however, radiologists were consistently less sensitive and more specific than the neural network.
Current state-of-the-art artificial neural networks for general image analysis are able to detect cancer in mammographies with similar accuracy to radiologists, even in a screening-like cohort with low breast cancer prevalence.
Prospective data examining the relationship between dietary protein intake and incident coronary heart disease (CHD) are inconclusive. Most evidence is derived from homogenous populations such as ...health professionals. Large community-based analyses in more diverse samples are lacking.
We studied the association of protein type and major dietary protein sources and risk for incident CHD in 12,066 middle-aged adults (aged 45-64 at baseline, 1987-1989) from four U.S. communities enrolled in the Atherosclerosis Risk in Communities (ARIC) Study who were free of diabetes mellitus and cardiovascular disease at baseline. Dietary protein intake was assessed at baseline and after 6 years of follow-up by food frequency questionnaire. Our primary outcome was adjudicated coronary heart disease events or deaths with following up through December 31, 2010. Cox proportional hazard models with multivariable adjustment were used for statistical analyses.
During a median follow-up of 22 years, there were 1,147 CHD events. In multivariable analyses total, animal and vegetable protein were not associated with an increased risk for CHD before or after adjustment. In food group analyses of major dietary protein sources, protein intake from red and processed meat, dairy products, fish, nuts, eggs, and legumes were not significantly associated with CHD risk. The hazard ratios with 95% confidence intervals for risk of CHD across quintiles of protein from poultry were 1.00 ref, 0.83 0.70-0.99, 0.93 0.75-1.15, 0.88 0.73-1.06, 0.79 0.64-0.98, P for trend = 0.16). Replacement analyses evaluating the association of substituting one source of dietary protein for another or of decreasing protein intake at the expense of carbohydrates or total fats did not show any statistically significant association with CHD risk.
Based on a large community cohort we found no overall relationship between protein type and major dietary protein sources and risk for CHD.
Increased lipoprotein(a) Lp(a) levels are associated with atherosclerotic cardiovascular disease. Studies of dietary interventions on changes in Lp(a) are sparse. We aimed to compare the effects of ...three healthy dietary interventions differing in macronutrient content on Lp(a) concentration.
Secondary analysis of a randomized, 3-period crossover feeding study including 155 (89 blacks; 66 whites) individuals. Participants were given DASH-type healthy diets rich in carbohydrates Carb, in protein Prot or in unsaturated fat Unsat Fat for 6 weeks each. Plasma Lp(a) concentration was assessed at baseline and after each diet.
Compared to baseline, all interventional diets increased mean Lp(a) by 2 to 5 mg/dl. Unsat Fat increased Lp(a) less than Prot with a difference of 1.0 mg/dl (95% CI, -0.5, 2.5; p = 0.196) in whites and 3.7 mg/dl (95% CI, 2.4, 5.0; p < 0.001) in blacks (p-value between races = 0.008); Unsat Fat increased Lp(a) less than Carb with a difference of -0.6 mg/dl, 95% CI, -2.1, 0.9; p = 0.441) in whites and -1.5 mg/dl (95% CI, -0.2, -2.8; p = 0.021) in blacks (p-value between races = 0.354). Prot increased Lp(a) more than Carb with a difference of 0.4 mg/dl (95% CI, -1.1, 1.9; p = 0.597) in whites and 2.2 mg/dl (95%CI, 0.9, 3.5; p = 0.001) in blacks (p-value between races = 0.082).
Diets high in unsaturated fat increased Lp(a) levels less than diets rich in carbohydrate or protein with greater changes in blacks than whites. Our results suggest that substitutions with dietary mono- and polyunsaturated fatty acids in healthy diets may be preferable over protein or carbohydrates with regards to Lp(a).
Clinicaltrials.gov NCT00051350.
Highly fluorescent conjugated polymer nanoparticles were prepared directly by polymerization in aqueous miniemulsion, employing Glaser coupling polymerization as a suitable step-growth reaction. A ...4,4′-dinonyl-2,2′-bipyridine-modified catalyst was found to be suited for the polymerization in the aqueous heterophase system. Nanoparticles of poly(arylene diethynylenes) (arylene = 2,5-dialkyoxy phenylenes and 9,9′-dihexyl fluorene) with molecular weights in the range of M n 104 to 105 g mol−1 and with sizes of ≤30 nm, as observed by TEM, result. N,N′-Di(4-ethynylphenyl)-1,7-di4-(1,1,3,3-tetramethylbutyl)phenoxyperylene-3,4:9,10-tetracarboxdiimide or 2,7-diethynylfluorenone was converted completely during the heterophase polymerization to afford colloidally stable nanoparticles of poly(arylene diethynylenes) with 0.1−2 mol % covalently incorporated perylene dye and 2−9 mol % of covalently incorporated fluorenone dye, respectively. Fluorescence spectroscopy of the aqueous dispersions reveals an efficient energy transfer to the dye in the nanoparticles, which enables a variation of the luminescence emission color between red (λem (max.) ca. 650 nm) and the green emission of the nanoparticles without dye.
To investigate the feasibility and accuracy of texture analysis to distinguish through objective and quantitative image information between healthy and infarcted myocardium with computed tomography ...(CT).
Twenty patients (5 females; mean age 56±10years) with proven acute myocardial infarction (MI) and 20 patients (8 females; mean age 42±15years) with no cardiac abnormalities (hereafter termed controls) underwent contrast-enhanced cardiac CT. Short axis CT images of the left ventricle (LV) were reconstructed at the slice thicknesses 1mm, 2mm, and 5mm. Two independent, blinded readers segmented the LV in controls and patients. Texture analysis was performed yielding first-level features based on the histogram (variance, skewness, kurtosis, entropy), second-level features based on the gray-level co-occurrence matrix (GLCM) (contrast, correlation, energy and homogeneity), and third-level features based on the gray-level run-length matrix (GLRLM).
Inter-and intrareader agreement was good to excellent for all histogram (intraclass correlation coefficient (ICC):0.70-0.93) and for all GLCM features (ICC:0.66-0.99), and was variable for the GLRLM features (ICC:-0.12-0.99). Univariate analysis showed significant differences between patients and controls for 2/4 histogram features, 3/4 GLCM and for 6/11 GLRLM features and all assessed slice thicknesses (all,p<0.05). In a multivariate logistic regression model, the single best variable from each level, determined by ROC analysis, was included stepwise. The best model included kurtosis (OR 0.08, 95%CI:0.01-0.65,P = 0.018) and short run high gray-level emphasis (SRHGE, OR 0.97, 95%CI:0.94-0.99,P = 0.007), with an area-under-the-curve (AUC) of 0.90 (95%CI:0.80-0.99). The best results for kurtosis and SRHGE (AUC = 0.78) were obtained at a 5mm slice thickness. A cut-off value of 14.4 for kurtosis+0.013*SRHGE predicted acute MI with a sensitivity of 95% (specificity 55%).
Our study illustrates the feasibility of texture analysis for distinguishing healthy from acutely infarcted myocardium with cardiac CT using objective, quantitative features, with most reproducible and accurate results at a short axis slice thickness of 5mm.
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