Bell-LaPadula model of computer security

The exact description is given of Bell and La Padula security model with use of modern notation. The document is intended serve as a basis for more precise formal and academic discussion model. The Bell-La Padula security model created conceptual tools for the analysis and design of safe computer systems. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/2882

Incorporating Baseline Outcome Data in Individual Participant Data Meta-Analysis of Non-randomized Studies.

Background In non-randomized studies (NRSs) where a continuous outcome variable (e.g., depressive symptoms) is assessed at baseline and follow-up, it is common to observe imbalance of the baseline values between the treatment/exposure group and control group. This may bias the study and consequently a meta-analysis (MA) estimate. These estimates may differ across statistical methods used to deal with this issue. Analysis of individual participant data (IPD) allows standardization of methods across studies. We aimed to identify methods used in published IPD-MAs of NRSs for continuous outcomes, and to compare different methods to account for baseline values of outcome variables in IPD-MA of NRSs using two empirical examples from the Thyroid Studies Collaboration (TSC). Methods For the first aim we systematically searched in MEDLINE, EMBASE, and Cochrane from inception to February 2021 to identify published IPD-MAs of NRSs that adjusted for baseline outcome measures in the analysis of continuous outcomes. For the second aim, we applied analysis of covariance (ANCOVA), change score, propensity score and the naïve approach (ignores the baseline outcome data) in IPD-MA from NRSs on the association between subclinical hyperthyroidism and depressive symptoms and renal function. We estimated the study and meta-analytic mean difference (MD) and relative standard error (SE). We used both fixed- and random-effects MA. Results Ten of 18 (56%) of the included studies used the change score method, seven (39%) studies used ANCOVA and one the propensity score (5%). The study estimates were similar across the methods in studies in which groups were balanced at baseline with regard to outcome variables but differed in studies with baseline imbalance. In our empirical examples, ANCOVA and change score showed study results on the same direction, not the propensity score. In our applications, ANCOVA provided more precise estimates, both at study and meta-analytical level, in comparison to other methods. Heterogeneity was higher when change score was used as outcome, moderate for ANCOVA and null with the propensity score. Conclusion ANCOVA provided the most precise estimates at both study and meta-analytic level and thus seems preferable in the meta-analysis of IPD from non-randomized studies. For the studies that were well-balanced between groups, change score, and ANCOVA performed similarly

Spectral Line Selection for HMI: A Comparison of Fe I 6173 and Ni I 6768

We present a study of two spectral lines, Fe I 6173 Angstroms and Ni I 6768 Angstroms, that were candidates to be used in the Helioseismic and Magnetic Imager (HMI) for observing Doppler velocity and the vector magnetic field. The line profiles were studied using the Mt. Wilson Observatory, the Advanced Stokes Polarimeter and the Kitt Peak McMath telescope and one meter Fourier transform spectrometer atlas. Both Fe I and Ni I profiles have clean continua and no blends that threaten instrument performance. The Fe I line is 2% deeper, 15% narrower and has a 6% smaller equivalent width than the Ni I line. The potential of each spectral line to recover pre-assigned solar conditions is tested using a least-squares minimization technique to fit Milne-Eddington models to tens of thousands of line profiles that have been sampled at five spectral positions across the line. Overall, the Fe I line has a better performance than the Ni I line for vector magnetic field retrieval. We selected the Fe I spectral line for use in HMI due to its better performance for magnetic diagnostics while not sacrificing velocity information

Drug-gene interactions of antihypertensive medications and risk of incident cardiovascular disease: A pharmacogenomics study from the CHARGE consortium

Background Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals. Methods Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk ofmajor cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regressionmodels to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases). Results Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0×10-8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genom

Chronology of age-related disease definitions:Osteoporosis and sarcopenia

Low muscle mass at older age has been associated with functional impairments, cognitive decline and mortality. The term sarcopenia, coined in 1988, has been used interchangeably to describe low muscle mass, strength, and function. Without a well defined definition, results of studies using the term sarcopenia cannot be compared. Difficulties in defining sarcopenia parallel the history of defining osteoporosis. To understand critical steps that are needed to reach consensus in defining age-related diseases, we have identified milestones in the history of defining osteoporosis and compared these to sarcopenia. As a result, the main missing steps in the process of defining sarcopenia are: specific treatment options, pharmaceutical interest, and public awareness. Similar to osteoporosis being defined as 'low bone mineral density', the term sarcopenia should be reserved for 'low muscle mass'. Consensus must be reached regarding the diagnostic criteria to quantify muscle mass, correction factors, and reference populations used to define cut-off values of muscle mass

Determinanten van ziekte en gezondheid op hoge leeftijd: Nieuwe inzichten uit de Leidse verouderingsstudies

The clinical research of the Department of Gerontology and Geriatrics of the Leiden University Medical Center focuses on the causes of health and disease in old age. We examine, amongst others, the genetic mechanisms of longevity by comparing children of long-living parents with their partners. At a mean age of 60 years, the children of the longliving parents have a lower prevalence of several cardiometabolic diseases, among which are myocardial infarction, diabetes, and hypertension. The children of the long-living parents also have a more favourable cardiometabolic risk profile, with lower values of glucose, insulin, triglycerides, and thyroid hormone, and a better insulin sensitivity. Moreover, over the past years we have shown that traditional cardiovascular risk factors, such as an increased cholesterol and hypertension, do not automatically apply to the very old. For the very old it must be taken into account that risk profiles for various diseases differ from those of younger populations. The choice of treatment must therefore be based on the 'best available evidence'. In absence of randomized clinical trials this is currently the knowledge on the pathofysiology of health and disease in old age