Publications

Global estimates of high‐level brain drain and deficit

ABSTRACT Brain drain, the international migration of scientists in search of better opportunities, has been a long‐standing concern, but quantitative measurements are uncommon and limited to specific countries or disciplines. We need to understand brain drain at a global level and estimate the extent to which scientists born in countries with low opportunities never realize their potential. Data on 1523 of the most highly cited scientists for 1981–1999 are analyzed. Overall, 31.9% of these scientists did not reside in the country where they were born (range 18.1–54.6% across 21 different scientific fields). There was great variability across developed countries in the proportions of foreign‐born resident scientists and emigrating scientists. Countries without a critical mass of native scientists lost most scientists to migration. This loss occurred in both developed and developing countries. Adjusting for population and using the U.S. as reference, the number of highly cited native‐born scientists was at least 75% of the expected number in only 8 countries other than the U.S. It is estimated that ~94% of the expected top scientists worldwide have not been able to materialize themselves due to various adverse conditions. Scientific deficit is only likely to help perpetuate these adverse conditions.—Ioannidis, J. P. A. Global estimates of high‐level brain drain and deficit. FASEB J. 18, 936–939 (2004)

The Great Disruption: COVID-19 and the Global Health Crisis

The Zambakari Advisory is proud to present our Fall 2020 Special Issue: “The Great Disruption: COVID-19 and the Global Health Crisis.” To produce a quality perspective and shine a nuanced light on this health crisis, we invited prominent scholars, medical doctors, epidemiologist and social scientists to share with you the evolving pandemic as it is seen and experienced and battled around the world. Whereas much still remains unknown, untested and unpredictable, only by committing to an all-encompassing, all-inclusive, multidisciplinary approach can we begin to fight back successfully. While we encounter and try to understand new evolutions in the virus and our treatment of it, this is not the first time the world has been confronted with such a challenge. Our universality has provided the coronavirus with more rapid transmission opportunities than ever before, but we cannot turn our backs on the broad lessons we have learned from our fights against such vicious 20th-century killers as the Spanish (1918-20) and Asian (1957-58) flus, the HIV virus that causes AIDS (1981-present), the H1N1 swine flu (2009-10), the West Africa Ebola pandemic (2014-16) and the Zika virus in South and Central America (2015-present). This issue’s collection features seven articles contributed by such respected voices as Marc Lipsitch, John P. A. Ioannidis, Jonathan Fuller, Graham E. Fuller, Dirk Hansohm, Asha Abdel Rahim, Rose Jaji and Paul Gormley. In the first paper, a professor of epidemiology at Harvard University’s T. H. Chan School of Public Health, Marc Lipsitch, writes that we “should use every possible source of insight at our disposal to gain knowledge and inform decisions, which are always made under uncertainty — rarely more so than at present” when faced with the complexities of the COVID-19 pandemic. Next up, F. Rehnborg Professor in Disease Prevention in the School of Medicine, and a professor of epidemiology at Stanford University, John Ioannidis offers timely insight, noting that “failing to correct our ignorance and adapt our actions as quickly as possible is not good science. Nor is politicizing scientific disagreement or looking away from the undeniable harms of our well-intentioned actions.” The University of Pittsburgh’s Jonathan Fuller, assistant professor of history and the philosophy of science, takes his turn next, writing that epidemiology “must be split-brained, acting with one hand while collecting more information with the other. Only by borrowing from both ways of thinking will we have the right mind for a pandemic.” In the fourth paper, Graham E. Fuller, a former senior CIA official and former vice chairman of the National Intelligence Council at the CIA, contributes to our Fall Issue with a look at the COVID-19 pandemic and a warning that “It would be too bad if all we aspire to is only to return to business as usual once this particular virus has been beaten back.” Following Fuller’s thoughts, co-contributors Dirk Hansohm and Asha Abdel Rahim explore the ingredients necessary to combat COVID-19, including quality governance, interdisciplinary research, international cooperation, an EU offer of support to the countries of Africa and more. The authors admit that, at best, “the world in Europe and beyond will not return to the same state as it was before.” In the sixth paper, a senior lecturer in the Department of Sociology at the University of Zimbabwe, Rose Jaji writes, “It is time for Africa to be proactive and to actively participate in finding solutions for itself instead of waiting for richer nations to assist.” In her article, she looks at the challenges African countries face in battling the pandemic, especially in light of their limited resources. The final piece is penned by Paul Gormley, a professor of criminal justice administration and chair in social science at Lynn University in Boca Raton, Florida. Gormley contributes his thoughts on the COVD-19 pandemic and, specifically, how the correctional system and its actors are at risk. He concludes that, short of “herd immunity” or a vaccine, the system as it exists and operates today is in danger of being “crushed.”

xPF: packet filtering for low-cost network monitoring

The ever-increasing complexity in network infrastructures is making critical the demand for network monitoring tools. While the majority of network operators rely on low-cost open-source tools based on commodity hardware and operating systems, the increasing link speeds and complexity of network monitoring applications have revealed inefficiencies in the existing software organization, which may prohibit the use of such tools in high-speed networks. Although several new architectures have been proposed to address these problems, they require significant effort in re-engineering the existing body of applications. We present an alternative approach that addresses the primary sources of inefficiency without significantly altering the software structure. Specifically, we enhance the computational model of the Berkeley packet filter (BPF) to move much of the processing associated with monitoring into the kernel, thereby removing the overhead associated with context switching between kernel and applications. The resulting packet filter, called xPF, allows new tools to be more efficiently implemented and existing tools to be easily optimized for high-speed networks. We present the design and implementation of xPF as well as several example applications that demonstrate the efficiency of our approach.

Smoking Cessation, or How to Avert Half a Billion Premature Deaths — Now

An estimated 1.1 billion people currently smoke cigarettes,¹ and 50 to 70% likely will die from tobacco-related causes.² This translates to 550 to 770 million expected tobacco deaths among those who currently smoke. Many additional deaths will accrue in successive generations if the status quo continues. Of interest is the reversibility of the excess mortality risk of smoking. The meta-analysis by Cho et al.³ of four large national cohorts of nearly 1.5 million adults followed on average 14.8 years yielded 23.0 million person-years of observational data with over 120,000 deaths identified through linked death registries.

Empirical Assessment of Mandatory Stay-at-Home and Business Closure Effects on the Spread of COVID-19

Overlapping meta-analyses on the same topic: survey of published studies

While some independent replication of meta-analyses by different teams is possibly useful, the overall picture suggests that there is a waste of efforts with many topics covered by multiple overlapping meta-analyses.

Systematic reviews: guidance relevant for studies of older people

直列チップツーチップ通信のための90nm CMOSによる14mW 6.25Gb/sトランシーバ

No abstract is provided for this article.

Pancreatitis Potentially Associated Drugs as a Risk Factor for Post–Endoscopic Retrograde Cholangiopancreatography Pancreatitis

Pancreatitis potentially associated drugs used before ERCP seem to increase the risk for PEP.

A low cost laser interferometer system for machine tool applications

A compact low-cost laser interferometer system for measuring linear displacements with sub-micrometer resolution is described and first performance evaluations reported. The four-photo-diode detectors system can also provide a sensitive, simultaneous indication of straightness in two axes

Why Science Is Not Necessarily Self-Correcting

The ability to self-correct is considered a hallmark of science. However, self-correction does not always happen to scientific evidence by default. The trajectory of scientific credibility can fluctuate over time, both for defined scientific fields and for science at-large. History suggests that major catastrophes in scientific credibility are unfortunately possible and the argument that “it is obvious that progress is made” is weak. Careful evaluation of the current status of credibility of various scientific fields is important in order to understand any credibility deficits and how one could obtain and establish more trustworthy results. Efficient and unbiased replication mechanisms are essential for maintaining high levels of scientific credibility. Depending on the types of results obtained in the discovery and replication phases, there are different paradigms of research: optimal, self-correcting, false nonreplication, and perpetuated fallacy. In the absence of replication efforts, one is left with unconfirmed (genuine) discoveries and unchallenged fallacies. In several fields of investigation, including many areas of psychological science, perpetuated and unchallenged fallacies may comprise the majority of the circulating evidence. I catalogue a number of impediments to self-correction that have been empirically studied in psychological science. Finally, I discuss some proposed solutions to promote sound replication practices enhancing the credibility of scientific results as well as some potential disadvantages of each of them. Any deviation from the principle that seeking the truth has priority over any other goals may be seriously damaging to the self-correcting functions of science.

Quantifying Selective Reporting and the Proteus Phenomenon for Multiple Datasets with Similar Bias

Meta-analyses play an important role in synthesizing evidence from diverse studies and datasets that address similar questions. A major obstacle for meta-analyses arises from biases in reporting. In particular, it is speculated that findings which do not achieve formal statistical significance are less likely reported than statistically significant findings. Moreover, the patterns of bias can be complex and may also depend on the timing of the research results and their relationship with previously published work. In this paper, we present an approach that is specifically designed to analyze large-scale datasets on published results. Such datasets are currently emerging in diverse research fields, particularly in molecular medicine. We use our approach to investigate a dataset on Alzheimer's disease (AD) that covers 1167 results from case-control studies on 102 genetic markers. We observe that initial studies on a genetic marker tend to be substantially more biased than subsequent replications. The chances for initial, statistically non-significant results to be published are estimated to be about 44% (95% CI, 32% to 63%) relative to statistically significant results, while statistically non-significant replications have almost the same chance to be published as statistically significant replications (84%; 95% CI, 66% to 107%). Early replications tend to be biased against initial findings, an observation previously termed Proteus phenomenon: The chances for non-significant studies going in the same direction as the initial result are estimated to be lower than the chances for non-significant studies opposing the initial result (73%; 95% CI, 55% to 96%). Such dynamic patterns in bias are difficult to capture by conventional methods, where typically simple publication bias is assumed to operate. Our approach captures and corrects for complex dynamic patterns of bias, and thereby helps generating conclusions from published results that are more robust against the presence of different coexisting types of selective reporting.

Expectations and challenges stemming from genome-wide association studies

There are considerable expectations about the ability of genome-wide association (GWA) studies to make exciting discoveries about the role of genes in common diseases. GWA studies may allow researchers to identify causal pathways that have not been unveiled before, thus opening new avenues to disease understanding, prevention and therapy. However, there are still many open challenges. One is how to analyse these studies. The problem of false positives and false negatives provides an interesting methodological stimulus to find optimal solutions. Once main genetic effects have been concretely documented, the next question is how to proceed with the investigation of gene-gene and gene-environment interactions. It is possible that what really counts is not the main effect of genes but complex interactions. Finding and interpreting such interactions is not straightforward. Finally, continuous updated integration of all evidence, from both old studies, current GWA investigations and future replication studies, and careful interpretation of the strength of the evidence are crucial to maximize transparency and lead to informative selection of the next steps of research in this field. The present Commentary is a report of an Environmental Cancer Risk, Nutrition and Individual Susceptibility network Workshop held in Venice in October 2007 and discusses some of the problems outlined above, with examples.

GAD: A 12-GS/s CMOS 4-bit A/D converter for an equalized multi-level link

A 4-bit 12-GSample/sec A/D converter (GAD) has been fabricated in a 0.25-/spl mu/m CMOS process to investigate the design of an equalized multi-level link. Clocked differential amplifiers were used to sample the input, followed by high-speed comparators with current-summed offset cancellation. Input bandwidth was measured at 2.5 GHz. Eight 1.5-GSample/sec flash A/D converters were interleaved to achieve the aggregate sample rate.

Lifting of Embargoes to Data Sharing in Clinical Trials Published in Top Medical Journals

This study assesses data sharing status and lifting of embargoes in randomized clinical trials from top medical journals 3 to 5 years after publication.

Retrospective median power, false positive meta‐analysis and large‐scale replication

Abstract Recent, high‐profile, large‐scale, preregistered failures to replicate uncover that many highly‐regarded experiments are “false positives”; that is, statistically significant results of underlying null effects. Large surveys of research reveal that statistical power is often low and inadequate. When the research record includes selective reporting, publication bias and/or questionable research practices, conventional meta‐analyses are also likely to be falsely positive. At the core of research credibility lies the relation of statistical power to the rate of false positives. This study finds that high (>50%–60%) median retrospective power (MRP) is associated with credible meta‐analysis and large‐scale, preregistered, multi‐lab “successful” replications; that is, with replications that corroborate the effect in question. When median retrospective power is low (<50%), positive meta‐analysis findings should be interpreted with great caution or discounted altogether.

Large Trials vs Meta-analysis of Smaller Trials-Reply

In Reply. —Dr Klebanoff and colleagues bring into focus the controversy of fixed vs random effects models of combining data. 1 We think it was fair and reasonable for us to report both effects and to point out that, when diversity is present, a random effects model is probably more appropriate. It is puzzling why these authors attribute to us an a priori belief that large trials usually support the results of meta-analyses of small trials. Their second concern is imprecise. We reported that a higher event rate was associated with a greater benefit of treatment in 4 cases (not 5 cases), but with a smaller benefit in 1 case. Klebanoff et al seem to believe that de facto all treatments should work the same for all patients regardless of the underlying risk of the disease. We do not share this notion and believe that most clinicians would not either. 2,3 More

Real-world effectiveness of pharmacological treatments in schizophrenia

Most people with stroke in India have no access to organised rehabilitation services. The effectiveness of training family members to provide stroke rehabilitation is uncertain. Our primary objective was to determine whether family-led stroke rehabilitation, initiated in hospital and continued at home, would be superior to usual care in a low-resource setting.The Family-led Rehabilitation after Stroke in India (ATTEND) trial was a prospectively randomised open trial with blinded endpoint done across 14 hospitals in India. Patients aged 18 years or older who had had a stroke within the past month, had residual disability and reasonable expectation of survival, and who had an informal family-nominated caregiver were randomly assigned to intervention or usual care by site coordinators using a secure web-based system with minimisation by site and stroke severity. The family members of participants in the intervention group received additional structured rehabilitation training—including information provision, joint goal setting, carer training, and task-specific training—that was started in hospital and continued at home for up to 2 months. The primary outcome was death or dependency at 6 months, defined by scores 3–6 on the modified Rankin scale (range, 0 [no symptoms] to 6 [death]) as assessed by masked observers. Analyses were by intention to treat. This trial is registered with Clinical Trials Registry-India (CTRI/2013/04/003557), Australian New Zealand Clinical Trials Registry (ACTRN12613000078752), and Universal Trial Number (U1111-1138-6707).Between Jan 13, 2014, and Feb 12, 2016, 1250 patients were randomly assigned to intervention (n=623) or control (n=627) groups. 33 patients were lost to follow-up (14 intervention, 19 control) and five patients withdrew (two intervention, three control). At 6 months, 285 (47%) of 607 patients in the intervention group and 287 (47%) of 605 controls were dead or dependent (odds ratio 0·98, 95% CI 0·78–1·23, p=0·87). 72 (12%) patients in the intervention group and 86 (14%) in the control group died (p=0·27), and we observed no difference in rehospitalisation (89 [14%]patients in the intervention group vs 82 [13%] in the control group; p=0·56). We also found no difference in total non-fatal events (112 events in 82 [13%] intervention patients vs 110 events in 79 [13%] control patients; p=0·80).Although task shifting is an attractive solution for health-care sustainability, our results do not support investment in new stroke rehabilitation services that shift tasks to family caregivers, unless new evidence emerges. A future avenue of research should be to investigate the effects of task shifting to health-care assistants or team-based community care.The National Health and Medical Research Council of Australia.