A technique for designing DLLs and PLLs using CMOS buffers with a regulated supply is presented. By scaling the charge pump current and the output resistance of the regulating amplifier, the proposed loops achieve a wide bandwidth that tracks the operating frequency, a constant damping factor, large operating range and low noise sensitivity. Prototype loops designed in 0.35-/spl mu/m CMOS processes exhibit >10x operating range and less than 1% input tracking jitter.
Background— Percutaneous coronary intervention (PCI) has been shown to improve symptoms compared with conservative medical treatment in patients with stable coronary artery disease (CAD); however, there is limited evidence on the effect of PCI on the risk of death, myocardial infarction, and subsequent revascularization. Therefore, we performed a meta-analysis of 11 randomized trials comparing PCI to conservative treatment in patients with stable CAD. Methods and Results— A total of 2950 patients were included in the meta-analysis (1476 received PCI, and 1474 received conservative treatment). There was no significant difference between the 2 treatment strategies with regard to mortality, cardiac death or myocardial infarction, nonfatal myocardial infarction, CABG, or PCI during follow-up. By random effects, the risk ratios (95% CIs) for the PCI versus conservative treatment arms were 0.94 (0.72 to 1.24), 1.17 (0.88 to 1.57), 1.28 (0.94 to 1.75), 1.03 (0.80 to 1.33), and 1.23 (0.80 to 1.90) for these 5 outcomes, respectively. A possible survival benefit was seen for PCI only in trials of patients who had a relatively recent myocardial infarction (risk ratio 0.40, 95% CI 0.17 to 0.95). Except for PCI during follow-up, there was no significant between-study heterogeneity for any outcome. Conclusions— In patients with chronic stable CAD, in the absence of a recent myocardial infarction, PCI does not offer any benefit in terms of death, myocardial infarction, or the need for subsequent revascularization compared with conservative medical treatment.
This document describes functional requirements for IPsec (RFC 2401) and Internet Key Exchange (IKE) (RFC 2409) to facilitate their use in securing SCTP (RFC 2960) traffic.
Abstract Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy–Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct or analysis.
Our systematic association study has enabled us to postulate about broad environmental correlation to lipid levels. Although subject to confounding and reverse causality bias, these findings merit evaluation in additional cohorts.
Networks of randomized clinical trials can be evaluated in the context of a network meta-analysis, a procedure that permits inferences into the comparative effectiveness of interventions that may or may not have been evaluated directly against each other. This approach is quickly gaining popularity among clinicians and guideline decision makers. However, certain methodological aspects are poorly understood. Here, we explain the geometry of a network, statistical and conceptual heterogeneity and incoherence, and challenges in the application and interpretation of data synthesis. These concepts are essential to make sense of a network meta-analysis.
Abstract We introduce and evaluate three tests for publication selection bias based on excess statistical significance (ESS). The proposed tests incorporate heterogeneity explicitly in the formulas for expected and ESS. We calculate the expected proportion of statistically significant findings in the absence of selective reporting or publication bias based on each study's SE and meta‐analysis estimates of the mean and variance of the true‐effect distribution. A simple proportion of statistical significance test (PSST) compares the expected to the observed proportion of statistically significant findings. Alternatively, we propose a direct test of excess statistical significance (TESS). We also combine these two tests of excess statistical significance (TESSPSST). Simulations show that these ESS tests often outperform the conventional Egger test for publication selection bias and the three‐parameter selection model (3PSM).
ABSTRACT A healthy diet is essential to attain genetically determined peak bone mass and maintain optimal skeletal health across the adult lifespan. Despite the importance of nutrition for bone health, many of the nutritional requirements of the skeleton across the lifespan remain underexplored, poorly understood, or controversial. With increasingly aging populations, combined with rapidly changing diets and lifestyles globally, one anticipates large increases in the prevalence of osteoporosis and incidence of osteoporotic fractures. Robust, transparent, and reproducible nutrition research is a cornerstone for developing reliable public health recommendations to prevent osteoporosis and osteoporotic fractures. However, nutrition research is often criticized or ignored by healthcare professionals due to the overemphasis of weak science, conflicting, confusing or implausible findings, industry interests, common misconceptions, and strong opinions. Conversely, spurious research findings are often overemphasized or misconstrued by the media or prominent figures especially via social media, potentially leading to confusion and a lack of trust by the general public. Recently, reforms of the broader discipline of nutrition science have been suggested and promoted, leading to new tools and recommendations to attempt to address these issues. In this perspective, we provide a brief overview of what has been achieved in the field on nutrition and bone health, focusing on osteoporosis and osteoporotic fractures. We discuss what we view as some of the challenges, including inherent difficulties in assessing diet and its change, disentangling complex interactions between dietary components and between diet and other factors, selection of bone-related outcomes for nutrition studies, obtaining evidence with more unbiased designs, and perhaps most importantly, ensuring the trust of the public and healthcare professionals. This perspective also provides specific recommendations and highlights new developments and future opportunities for scientists studying nutrition and bone health. © 2021 American Society for Bone and Mineral Research (ASBMR).
Genetic and molecular epidemiology covers a vast area of research. Given the rapid changes in this field, discussing a research agenda is a precarious and ambitious task. A representative set of high-priority concepts will be presented here, each of which alone could be the topic of a long series of essays. The wish list includes issues of full transparency and integration of information, dealing efficiently with complex multidimensional biology, juxtaposing the genome and environmental exposures, and using robust randomised trials to advance our knowledge and its application in this field.
Retractions are becoming increasingly common but still account for a small minority of published papers. It would be useful to generate databases where the presence of retractions can be linked to impact metrics of each scientist. We have thus incorporated retraction data in an updated Scopus-based database of highly cited scientists (top 2% in each scientific subfield according to a composite citation indicator). Using data from the Retraction Watch database (RWDB), retraction records were linked to Scopus citation data. Of 55,237 items in RWDB as of August 15, 2024, we excluded non-retractions, retractions clearly not due to any author error, retractions where the paper had been republished, and items not linkable to Scopus records. Eventually, 39,468 eligible retractions were linked to Scopus. Among 217,097 top-cited scientists in career-long impact and 223,152 in single recent year (2023) impact, 7,083 (3.3%) and 8,747 (4.0%), respectively, had at least 1 retraction. Scientists with retracted publications had younger publication age, higher self-citation rates, and larger publication volume than those without any retracted publications. Retractions were more common in the life sciences and rare or nonexistent in several other disciplines. In several developing countries, very high proportions of top-cited scientists had retractions (highest in Senegal (66.7%), Ecuador (28.6%), and Pakistan (27.8%) in career-long citation impact lists). Variability in retraction rates across fields and countries suggests differences in research practices, scrutiny, and ease of retraction. Addition of retraction data enhances the granularity of top-cited scientists’ profiles, aiding in responsible research evaluation. However, caution is needed when interpreting retractions, as they do not always signify misconduct; further analysis on a case-by-case basis is essential. The database should hopefully provide a resource for meta-research and deeper insights into scientific practices.
This paper summarizes the proceedings of an NIAID-sponsored workshop on statistical issues for HIV surrogate endpoints. The workshop brought together statisticians and clinicians in an attempt to shed light on some unresolved issues in the use of HIV laboratory markers (such as HIV RNA and CD4+ cell counts) in the design and analysis of clinical studies and in patient management. Utilizing a debate format, the workshop explored a series of specific questions dealing with the relationship between markers and clinical endpoints, and the choice of endpoints and methods of analysis in clinical studies. This paper provides the position statements from the two debaters on each issue. Consensus conclusions, based on the presentations and discussion, are outlined. While not providing final answers, we hope that these discussions have helped clarify a number of issues, and will stimulate further consideration of some of the highlighted problems. These issues will be critical in the proper assessment and use of future therapies for HIV disease.
