2,497 publications from this institution
This paper describes a half-swing pulse-mode gate family that uses reduced input signal swing without sacrificing performance. These gates are well suited for decreasing the power in SRAM decoders and write circuits by reducing the signal swing on high-capacitance predecode lines, write bus lines, and bit lines. Charge recycling between positive and negative half-swing pulses further reduces the power dissipation. These techniques are demonstrated in a 2-K/spl times/16-b SRAM fabricated in a 0.25-/spl mu/m dual-V/sub t/ CMOS technology that dissipates 0.9 mW operating at 1 V, 100 MHz, and room temperature. On-chip voltage samplers were used to probe internal nodes.
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Routinely collected data (RCD) are increasingly used for biomedical research. Extensive resources have been invested in this field: they include the set-up of disease registries and clinical databases at regional, national or international levels; the promotion of the use of electronic health
Objective The Great Barrington Declaration (GBD) and the John Snow Memorandum (JSM), each signed by numerous scientists, have proposed hotly debated strategies for handling the COVID-19 pandemic. The current analysis aimed to examine whether the prevailing narrative that GBD is a minority view among experts is true. Methods The citation impact and social media presence of the key GBD and JSM signatories was assessed. Citation data were obtained from Scopus using a previously validated composite citation indicator that incorporated also coauthorship and author order and ranking was against all authors in the same Science-Metrix scientific field with at least five full papers. Random samples of scientists from the longer lists of signatories were also assessed. The number of Twitter followers for all key signatories was also tracked. Results Among the 47 key GBD signatories, 20, 19 and 21, respectively, were top-cited authors for career impact, recent single-year (2019) impact or either. For comparison, among the 34 key JSM signatories, 11, 14 and 15, respectively, were top cited. Key signatories represented 30 different scientific fields (9 represented in both documents, 17 only in GBD and 4 only in JSM). In a random sample of n=30 scientists among the longer lists of signatories, five in GBD and three in JSM were top cited. By April 2021, only 19/47 key GBD signatories had personal Twitter accounts versus 34/34 of key JSM signatories; 3 key GBD signatories versus 10 key JSM signatories had >50 000 Twitter followers and extraordinary Kardashian K-indices (363–2569). By November 2021, four key GBD signatories versus 13 key JSM signatories had >50 000 Twitter followers. Conclusions Both GBD and JSM include many stellar scientists, but JSM has far more powerful social media presence and this may have shaped the impression that it is the dominant narrative.
We assessed whether the most highly cited studies in emotion research reported larger effect sizes compared with meta-analyses and the largest studies on the same question. We screened all reports with at least 1,000 citations and identified matching meta-analyses for 40 highly cited observational studies and 25 highly cited experimental studies. Highly cited observational studies had effects greater on average by 1.42-fold (95% confidence interval [CI] = [1.09, 1.87]) compared with meta-analyses and 1.99-fold (95% CI = [1.33, 2.99]) compared with largest studies on the same questions. Highly cited experimental studies had increases of 1.29-fold (95% CI = [1.01, 1.63]) compared with meta-analyses and 2.02-fold (95% CI = [1.60, 2.57]) compared with the largest studies. There was substantial between-topics heterogeneity, more prominently for observational studies. Highly cited studies often did not have the largest weight in meta-analyses (12 of 65 topics, 18%) but were frequently the earliest ones published on the topic (31 of 65 topics, 48%). Highly cited studies may offer, on average, exaggerated estimates of effects in both observational and experimental designs.
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Reclassification studies would benefit from more rigorous methodological standards; otherwise claims for improved reclassification may remain spurious.
A T-to-C polymorphism in the 5' promoter region of the CYP17 gene that encodes the cytochrome P450c17alpha has been implicated as a risk factor for prostate cancer, but individual studies have been inconclusive or controversial. Therefore we performed a meta-analysis of 10 studies (12 comparisons) with CYP17 genotyping on 2404 patients with prostate cancer and 2755 controls. Overall, the random effects odds ratio (OR) for the A2 (C) versus A1 (T) allele was 1.08 [95% confidence interval (CI), 0.95-1.22], with some between-study heterogeneity (P = 0.04). There was no suggestion of an overall effect either in recessive or dominant modeling of A2 effects, and the comparison of A2/A2 versus A1/A1 also showed no differential susceptibility to prostate cancer (OR, 1.15; 95% CI, 0.91-1.46). No effect of A2 was seen in subjects of European descent (7 comparisons, OR, 1.04; 95% CI, 0.92-1.18, no significant between-study heterogeneity) or Asian descent (2 comparisons, OR, 1.06; 95% CI, 0.66-1.71; P = 0.02 for heterogeneity), whereas A2 increased susceptibility to prostate cancer in subjects of African descent (3 comparisons, OR, 1.56; 95% CI, 1.07-2.28; no between-study heterogeneity). Smaller studies unilaterally showed more prominent genetic effects for A2 than larger studies (P = 0.038). The meta-analysis suggests that the CYP17 polymorphism is unlikely to increase considerably the risk of sporadic prostate cancer on a wide population basis, especially in subjects of European descent. Previously reported associations may reflect publication bias, although it is also possible that the polymorphism may be important in subjects of African descent.
Abstract The objective of this meta‐epidemiological study was to explore the impact of attrition rates on treatment effect estimates in randomised trials of chronic inflammatory diseases (CID) treated with biological and targeted synthetic disease‐modifying drugs. We sampled trials from Cochrane reviews. Attrition rates and primary endpoint results were retrieved from trial publications; Odds ratios (ORs) were calculated from the odds of withdrawing in the experimental intervention compared to the control comparison groups (i.e., differential attrition), as well as the odds of achieving a clinical response (i.e., the trial outcome). Trials were combined using random effects restricted maximum likelihood meta‐regression models and associations between estimates of treatment effects and attrition rates were analysed. From 37 meta‐analyses, 179 trials were included, and 163 were analysed (301 randomised comparisons; n = 62,220 patients). Overall, the odds of withdrawal were lower in the experimental compared to control groups (random effects summary OR = 0.45, 95% CI, 0.41–0.50). The corresponding overall treatment effects were large (random effects summary OR = 4.43, 95% CI 3.92–4.99) with considerable heterogeneity across interventions and clinical specialties ( I 2 = 85.7%). The ORs estimating treatment effect showed larger treatment benefits when the differential attrition was more prominent with more attrition in the control group (OR = 0.73, 95% CI 0.55–0.96). Higher attrition rates from the control arm are associated with larger estimated benefits of treatments with biological or targeted synthetic disease‐modifying drugs in CID trials; differential attrition may affect estimates of treatment benefit in randomised trials.
