Publications

Beyond genomics: understanding exposotypes through metabolomics

US studies may overestimate effect sizes in softer research

Many biases affect scientific research, causing a waste of resources, posing a threat to human health, and hampering scientific progress. These problems are hypothesized to be worsened by lack of consensus on theories and methods, by selective publication processes, and by career systems too heavily oriented toward productivity, such as those adopted in the United States (US). Here, we extracted 1,174 primary outcomes appearing in 82 meta-analyses published in health-related biological and behavioral research sampled from the Web of Science categories Genetics & Heredity and Psychiatry and measured how individual results deviated from the overall summary effect size within their respective meta-analysis. We found that primary studies whose outcome included behavioral parameters were generally more likely to report extreme effects, and those with a corresponding author based in the US were more likely to deviate in the direction predicted by their experimental hypotheses, particularly when their outcome did not include additional biological parameters. Nonbehavioral studies showed no such “US effect” and were subject mainly to sampling variance and small-study effects, which were stronger for non-US countries. Although this latter finding could be interpreted as a publication bias against non-US authors, the US effect observed in behavioral research is unlikely to be generated by editorial biases. Behavioral studies have lower methodological consensus and higher noise, making US researchers potentially more likely to express an underlying propensity to report strong and significant findings.

Using partitioning to help convergence in the standard-cell design automation methodology

Article Free Access Share on Using partitioning to help convergence in the standard-cell design automation methodology Authors: Hema Kapadia Computer Systems Lab, Stanford University, Stanford, CA Computer Systems Lab, Stanford University, Stanford, CAView Profile , Mark Horowitz Computer Systems Lab, Stanford University, Stanford, CA Computer Systems Lab, Stanford University, Stanford, CAView Profile Authors Info & Claims DAC '99: Proceedings of the 36th annual ACM/IEEE Design Automation ConferenceJune 1999 Pages 592–597https://doi.org/10.1145/309847.310005Online:01 June 1999Publication History 7citation215DownloadsMetricsTotal Citations7Total Downloads215Last 12 Months4Last 6 weeks2 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 Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

Bridging the gap in obesity research: A consensus statement from the European Society for Clinical Investigation

Abstract Background Most forms of obesity are associated with chronic diseases that remain a global public health challenge. Aims Despite significant advancements in understanding its pathophysiology, effective management of obesity is hindered by the persistence of knowledge gaps in epidemiology, phenotypic heterogeneity and policy implementation. Materials and Methods This consensus statement by the European Society for Clinical Investigation identifies eight critical areas requiring urgent attention. Key gaps include insufficient long‐term data on obesity trends, the inadequacy of body mass index (BMI) as a sole diagnostic measure, and insufficient recognition of phenotypic diversity in obesity‐related cardiometabolic risks. Moreover, the socio‐economic drivers of obesity and its transition across phenotypes remain poorly understood. Results The syndemic nature of obesity, exacerbated by globalization and environmental changes, necessitates a holistic approach integrating global frameworks and community‐level interventions. This statement advocates for leveraging emerging technologies, such as artificial intelligence, to refine predictive models and address phenotypic variability. It underscores the importance of collaborative efforts among scientists, policymakers, and stakeholders to create tailored interventions and enduring policies. Discussion The consensus highlights the need for harmonizing anthropometric and biochemical markers, fostering inclusive public health narratives and combating stigma associated with obesity. By addressing these gaps, this initiative aims to advance research, improve prevention strategies and optimize care delivery for people living with obesity. Conclusion This collaborative effort marks a decisive step towards mitigating the obesity epidemic and its profound impact on global health systems. Ultimately, obesity should be considered as being largely the consequence of a socio‐economic model not compatible with optimal human health.

Exploring post-replication citation patterns in psychological science

For instructions on running the analysis code please see the README.md file

A 24 Gb/s Software Programmable Analog Multi-Tone Transmitter

A 24 Gb/s transmitter employs a digital linear equalizer and a 12 GS/s 8-bit digital-to-analog converter (DAC). Implemented in a 90 nm CMOS technology, the transmitter can be programmed to support a variety of communication modes including 4-channel and 2-channel analog multi-tone (AMT), as well as various baseband (BB) modes ranging from 2 to 256 PAM. Selection of the transmission mode is enabled through software programming of the appropriate tap coefficients into the equalizer. The transmitter dissipates 510 mW of power and is fabricated over an area of 0.8 mm. Experimental results confirm clear eye diagrams at 28 Gb/s.

Prevalence and significance of race and ethnicity subgroup analyses in Cochrane intervention reviews

Supplementary Methods and Supplemental Tables 1 and 2 from Collaborative Cancer Epidemiology in the 21st Century: The Model of Cancer Consortia

<p>PDF - 121KB, Exclusion Criteria for Scoring by Scientific Area and Translational Stage, Comparison of Translational Stage of CEC versus non-CEC associated cancer genetics papers, Acknowledgement of CEC contributions in associated papers. Table 1: Scientific areas, their definitions, and examples from the literature analysis. Table 2: Acknowledgment CEC contributions in 472 papers, associated with 4 established CEC, by acknowledgement type.</p>

Mortality in persons with mental disorders is substantially overestimated using inpatient psychiatric diagnoses

Guidance to Best Tools and Practices for Systematic Reviews

» Data continue to accumulate indicating that many systematic reviews are methodologically flawed, biased, redundant, or uninformative. Some improvements have occurred in recent years based on empirical methods research and standardization of appraisal tools; however, many authors do not routinely or consistently apply these updated methods. In addition, guideline developers, peer reviewers, and journal editors often disregard current methodological standards. Although extensively acknowledged and explored in the methodological literature, most clinicians seem unaware of these issues and may automatically accept evidence syntheses (and clinical practice guidelines based on their conclusions) as trustworthy. » A plethora of methods and tools are recommended for the development and evaluation of evidence syntheses. It is important to understand what these are intended to do (and cannot do) and how they can be utilized. Our objective is to distill this sprawling information into a format that is understandable and readily accessible to authors, peer reviewers, and editors. In doing so, we aim to promote appreciation and understanding of the demanding science of evidence synthesis among stakeholders. We focus on well-documented deficiencies in key components of evidence syntheses to elucidate the rationale for current standards. The constructs underlying the tools developed to assess reporting, risk of bias, and methodological quality of evidence syntheses are distinguished from those involved in determining overall certainty of a body of evidence. Another important distinction is made between those tools used by authors to develop their syntheses as opposed to those used to ultimately judge their work. » Exemplar methods and research practices are described, complemented by novel pragmatic strategies to improve evidence syntheses. The latter include preferred terminology and a scheme to characterize types of research evidence. We organize best practice resources in a Concise Guide that can be widely adopted and adapted for routine implementation by authors and journals. Appropriate, informed use of these is encouraged, but we caution against their superficial application and emphasize their endorsement does not substitute for in-depth methodological training. By highlighting best practices with their rationale, we hope this guidance will inspire further evolution of methods and tools that can advance the field.

Outcome reporting bias in clinical trials: why monitoring matters

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Extracted data and code

Evaluation of networks of randomized trials

Randomized trials may be designed and interpreted as single experiments or they may be seen in the context of other similar or relevant evidence. The amount and complexity of available randomized evidence vary for different topics. Systematic reviews may be useful in identifying gaps in the existing randomized evidence, pointing to discrepancies between trials, and planning future trials. A new, promising, but also very much debated extension of systematic reviews, mixed treatment comparison (MTC) meta-analysis, has become increasingly popular recently. MTC meta-analysis may have value in interpreting the available randomized evidence from networks of trials and can rank many different treatments, going beyond focusing on simple pairwise-comparisons. Nevertheless, the evaluation of networks also presents special challenges and caveats. In this article, we review the statistical methodology for MTC meta-analysis. We discuss the concept of inconsistency and methods that have been proposed to evaluate it as well as the methodological gaps that remain. We introduce the concepts of network geometry and asymmetry, and propose metrics for the evaluation of the asymmetry. Finally, we discuss the implications of inconsistency, network geometry and asymmetry in informing the planning of future trials.

Architecture and circuit techniques for a reconfigurable memory block

A 2 kB reconfigurable SRAM block, using self-timed, pulse-mode circuits capable of emulating a portion of a cache or a streaming FIFO is realized in a 1.8 V 0.18 /spl mu/m CMOS process and operates at 1.1 GHz (10F04 cycle). The additional logic needed for reconfigurability consumes 26% of the total power and 32% of the total area.

Off-label treatments were not consistently better or worse than approved drug treatments in randomized trials

JAMA

An eight channel 35 GSample/s CMOS timing analyzer

While today's test systems measure inputs at a single time point each cycle, measuring when the inputs arrive is often more useful for understanding timing and jitter problems. An eight channel system is used to explore the feasibility of such a time measuring tester front-end. This system achieves 27.8 ps timing resolution in a 0.25 /spl mu/m CMOS technology using an oversampled architecture with 40 phase-shifted clocks that span a 900 MHz cycle. The chip contains two clock generators, eight input channels, on-chip memory and histogram hardware.

Fast, non-Monte-Carlo estimation of transient performance variation due to device mismatch

This paper describes a noise-based method of estimating the effects of device random mismatch on circuit's transient response, such as delay and frequency. The proposed method models DC mismatch as equivalent AC pseudo-noise and exploits the fast periodic noise analysis (PNOISE) available in RF circuit simulators to compute the resulting variation in the circuit response. While the method relies on Gaussian mismatch distributions and linear perturbation model, it can model and analyze correlations as well as identify the most sensitive design parameter to mismatches with no additional simulation cost. Three benchmarks measuring the variations in the input offset voltage of a comparator, the delay of a logic path, and the frequency of an oscillator demonstrate the speed improvement of 100--1000x compared to a 1000-point Monte-Carlo method.