Background: Red meat intake is an established risk factor for developing type 2 diabetes (T2D), although the role of cooking methods in the associations of red meat intake with T2D is largely unknown. This study aimed to examine red meat cooking methods in relation to risk of T2D among U.S. women who were regular meat-consumers (≥2 servings of red meat intake per week). Methods: We prospectively followed 59,032 women in the Nurses’ Health Study through 2012, who were free of diabetes, cardiovascular disease, and cancer at baseline in 1986. Diet was assessed by validated food-frequency questionnaires. Weekly frequency of cooking methods for red meat, including roasting, broiling, barbequing, pan-frying, and stewing or boiling, were collected at baseline. Results: During 1.24 million person-years of follow-up, we documented 6,205 incident T2D cases. After multivariate adjustment for demographics, lifestyle factors, and cooking methods, comparing extreme quintiles, the HR (95% CI) of T2D was 1.18 (1.07, 1.30) for total red meat intake and 1.31 (1.20, 1.43) for processed red meat intake (both P trend<0.001). Higher frequency of broiling and barbequing for red meat were associated with greater weight gain over 8 years (all P <0.05). After multivariate adjustment including total red meat intake, and comparing with cooking red meat <1 time/month, participants cooking red meat ≥ 2 times/week had an HR (95% CI) of T2D that was 1.28 (1.18, 1.39) for broiling ( P trend<0.001), 1.22 (1.10, 1.36) for barbequing ( P trend<0.001), 1.10 (1.00, 1.22) for roasting ( P trend=0.17), 0.84 (0.76, 0.93) for pan-frying ( P trend=0.01), and 0.97 (0.85, 1.09) for stewing or boiling ( P trend=0.97). When cooking methods were further mutually adjusted, the results remained similar. Conclusion: These findings suggested that, beyond the risk of red meat intake, high-temperature open-flame cooking methods for red meat, especially broiling and barbequing, are independently associated with a higher risk of T2D.
A bstract : Single‐walled carbon nanotubes (SWNTs) are ideal systems for investigating fundamental properties in one‐dimensional electronic systems and have the potential to revolutionize many aspects of nano/molecular electronics. Scanning tunneling microscopy (STM) has been used to characterize the atomic structure and tunneling density of states of individual SWNTs. Detailed spectroscopic measurements showed one‐dimensional singularities in the SWNT density of states for both metallic and semiconducting nanotubes. The results obtained were compared to and agree well with theoretical predictions and tight‐binding calculations. SWNTs were also shortened using the STM to explore the role of finite size, which might be exploited for device applications. Segments less than 10 nm exhibited discrete peaks in their tunneling spectra, which correspond to quantized energy levels, and whose spacing scales inversely with length. Finally, the interaction between magnetic impurities and electrons confined to one dimension was studied by spatially resolving the local electronic density of states of small cobalt clusters on metallic SWNTs. Spectroscopic measurements performed on and near these clusters exhibited a narrow peak near the Fermi level that has been identified as a Kondo resonance. In addition, spectroscopic studies of ultrasmall magnetic nanostructures, consisting of small cobalt clusters on short nanotube pieces, exhibited features characteristic of the bulk Kondo resonance, but also new features due to their finite size.
In their hypothetical examples, Flegal et al.1,2 applied the weighted-sum method3 to calculate deaths attributable to obesity. Our main concern about these calculations is that they did not take into account the chronic long-term effects of obesity or its dynamic nature. One obvious logical problem is that, although most people die after 75 years of age, it is cumulative obesity exposure rather than weight at a specific older age that contributes the most to the higher mortality rates associated with obesity. Obesity is a chronic condition, and it takes years for obese individuals to develop conditions that are major causes of death, such as cardiovascular disease and cancer. Moreover, even with later weight loss, not all of the adverse effects can be reversed. Thus, the relative risks calculated from the oldest age groups do not reflect the true long-term impact of obesity on mortality. As a simple example, suppose someone was obese at age 45, had a heart attack at age 65, then lost a lot of weight and died at age 70. Most likely, obesity at age 45 rather than body mass index (BMI) at age 70 contributed to this person’s death. The essence of the population-attributable risk is to determine the number of premature deaths that could be prevented if obesity were avoided; and in the previous example, avoiding obesity at age 45 probably would have prevented the premature death at age 70. This scenario is analogous to the relationship between smoking and mortality; cumulative smoking history is more likely a better predictor of cancer and all-cause mortality than a snapshot of smoking status at a single older age (say, 75 years). Flegal et al. argued that exclusion of participants with cardiovascular disease and cancer at baseline would make the estimates of attributable deaths misleading because the resulting cohorts would not reflect the US population. However, these exclusions are necessary to obtain valid relative risks associated with obesity, because these conditions can lead to artifacts by reverse causation (i.e., a low BMI is sometimes the result, rather than the cause, of underlying illness). Similarly, in a study on cigarette smoking, if patients with cardiovascular disease and cancer at baseline were included, the effects of smoking in the general population would be seriously underestimated, as many patients would have stopped smoking because of their illness but still be at higher risk for death.
These data indicate that physical activity, including moderate-intensity exercise such as walking, is associated with substantial reduction in risk of total and ischemic stroke in a dose-response manner. JAMA. 2000.
For Abstract see ChemInform Abstract in Full Text.
article Free AccessArtifacts AvailableArtifacts Evaluated & Reusable Share on Algorithm 638: INTCOL and HERMCOL: collocation on rectangular domains with bicubic hermite polynomials Authors: E. N. Houstis Purdue Univ. and Univ. of Thessaloniki Purdue Univ. and Univ. of ThessalonikiView Profile , W. F. Mitchell Purdue Univ. Purdue Univ.View Profile , J. R. Rice Purdue Univ. Purdue Univ.View Profile Authors Info & Claims ACM Transactions on Mathematical SoftwareVolume 11Issue 4Dec. 1985 pp 416–418https://doi.org/10.1145/6187.6195Online:01 December 1985Publication History 14citation374DownloadsMetricsTotal Citations14Total Downloads374Last 12 Months10Last 6 weeks3 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
A procedure based on simulated annealing Monte Carlo (SAMC) was used to predict the crystal structures of hydrogen-bonded organic molecules that form molecular tapes. This procedure was optimized to select structures with good hydrogen-bond geometries; it allowed for deformations in molecular conformation due to packing pressures. Biasing the SAMC procedure to select structures with good hydrogen bonds improves the efficiency of generating hydrogen-bonding motifs significantly. This procedure, written in the syntax of the CHARMM molecular modeling program, correctly predicted the crystalline structures of three test molecules derived from diketopiperazine: (C5DKP = 3,6-(cyclotetramethylene)-2,5-diketopiperazine; Me4DKP = 3,6-(tetramethyl)-2,5-diketopiperazine; (Me2C6)2DKP = 3,6-(4,4-dimethylcyclohexane)-2,5-diketopiperazine). The computational and experimental results were compared using powder diffraction patterns, visualization, and values of Ck* (a measure of the crystalline packing efficiency).
A wide variety of applications ranging from microelectronics to turbines for propulsion and power generation rely on films, coatings, and multilayers to improve performance. As such, the ability to predict coating failure - such as delamination (debonding), mud-cracking, blistering, crack kinking, and the like - is critical to component design and development. This work compiles and organizes decades of research that established the theoretical foundation for predicting such failure mechanisms, and clearly outlines the methodology needed to predict performance. Detailed coverage of cracking in multilayers is provided, with an emphasis on the role of differences in thermoelastic properties between the layers. The comprehensive theoretical foundation of the book is complemented by easy-to-use analysis codes designed to empower novices with the tools needed to simulate cracking; these codes enable not only precise quantitative reproduction of results presented graphically in the literature, but also the generation of new results for more complex multilayered systems.
Background It has been suggested that there is a link between fetal growth and chronic diseases later in life. Several studies have shown a negative association between birthweight and cardiovascular diseases, as well as cardiovascular disease risk factors, such as blood pressure and type 2 diabetes. Far fewer studies have focused on the association between size at birth and blood lipid concentrations. We have conducted a qualitative assessment of the direction and consistency of the relationship between size at birth and blood lipid concentrations to see whether the suggested relationship between intrauterine growth and cardiovascular diseases is mediated by lipid metabolism.
