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Background In vivo Braak staging stratifies patients across the AD spectrum and has the potential to harmonize tau PET tracer staging. This study aims to compare and test harmonization procedures for Braak staging individuals using MK6240 and Flortaucipir tau PET tracers. Methods We assessed 437 participants across the AD spectrum (245 cognitively unimpaired (CU) and 192 cognitively impaired; mean age 68.5 ± 8.6) using head‐to‐head MK6240 and Flortaucipir scans. We computed SUVRs in Braak regions of interest (ROIs) and assessed four cut‐off methods for Braak positivity: (a) mean + 2.5 SD of young controls (age <28 years), (b) mean + 2.5 SD of elderly CU Aβ−, (c) Gaussian mixture modeling (GMM), and (d) the Youden index. Braak stages were assigned using seven (0 to VI) or four (0, I–II, III–IV, V–VI) categories. We evaluated inter‐ and intra‐tracer concordance (intra‐tracer, i.e., whether it follows the sequential Braak pattern). Results The intra‐tracer seven‐class Braak staging concordance ranged from 63% to 94%. With the highest intra‐tracer Braak concordance being achieved when using GMM cutoffs: 94% (MK6240) and 89% (Flortaucipir; Figure 1). Inter‐tracer agreement concordance ranged from 56% to 76%. The highest concordance emerged from the CU Elderly Aβ– cutoff optimizing the Braak II region for spill‐off (Figure 2). Using the Braak staging simplified version improved intra‐tracer concordance in both tracers (MK6240as well as inter‐tracer agreement (86.5%). Most inter‐tracer discrepancies were observed at Braak stages II–IV. Despite showing staging discordances, the distribution of cognitive status across the Braak stages is similar for both tracers (Figure 3). Conclusion These preliminary findings reveal some discrepancies in Braak staging when comparing MK6240 and Flortaucipir. Our results also suggest that adjustments in cutoffs and regions of interest can partially mitigate both inter‐ and intra‐tracer divergences. Finally, our analysis suggests robust concordance after adjustment and using 4 classes (0, I‐II, III‐IV, V‐VI).

Background In vivo Braak staging stratifies patients across the AD spectrum and has the potential to harmonize tau PET tracer staging. This study aims to compare and test harmonization procedures for Braak staging individuals using MK6240 and Flortaucipir tau PET tracers. Methods We assessed 437 participants across the AD spectrum (245 cognitively unimpaired (CU) and 192 cognitively impaired; mean age 68.5 ± 8.6) using head‐to‐head MK6240 and Flortaucipir scans. We computed SUVRs in Braak regions of interest (ROIs) and assessed four cut‐off methods for Braak positivity: (a) mean + 2.5 SD of young controls (age <28 years), (b) mean + 2.5 SD of elderly CU Aβ−, (c) Gaussian mixture modeling (GMM), and (d) the Youden index. Braak stages were assigned using seven (0 to VI) or four (0, I–II, III–IV, V–VI) categories. We evaluated inter‐ and intra‐tracer concordance (intra‐tracer, i.e., whether it follows the sequential Braak pattern). Results The intra‐tracer seven‐class Braak staging concordance ranged from 63% to 94%. With the highest intra‐tracer Braak concordance being achieved when using GMM cutoffs: 94% (MK6240) and 89% (Flortaucipir; Figure 1). Inter‐tracer agreement concordance ranged from 56% to 76%. The highest concordance emerged from the CU Elderly Aβ– cutoff optimizing the Braak II region for spill‐off (Figure 2). Using the Braak staging simplified version improved intra‐tracer concordance in both tracers (MK6240as well as inter‐tracer agreement (86.5%). Most inter‐tracer discrepancies were observed at Braak stages II–IV. Despite showing staging discordances, the distribution of cognitive status across the Braak stages is similar for both tracers (Figure 3). Conclusion These preliminary findings reveal some discrepancies in Braak staging when comparing MK6240 and Flortaucipir. Our results also suggest that adjustments in cutoffs and regions of interest can partially mitigate both inter‐ and intra‐tracer divergences. Finally, our analysis suggests robust concordance after adjustment and using 4 classes (0, I‐II, III‐IV, V‐VI).

As the number of single‐cell transcriptomics datasets grows, the natural next step is to integrate the accumulating data to achieve a common ontology of cell types and states. However, it is not straightforward to compare gene expression levels across datasets and to automatically assign cell type labels in a new dataset based on existing annotations. In this manuscript, we demonstrate that our previously developed method, scVI, provides an effective and fully probabilistic approach for joint representation and analysis of scRNA‐seq data, while accounting for uncertainty caused by biological and measurement noise. We also introduce single‐cell ANnotation using Variational Inference (scANVI), a semi‐supervised variant of scVI designed to leverage existing cell state annotations. We demonstrate that scVI and scANVI compare favorably to state‐of‐the‐art methods for data integration and cell state annotation in terms of accuracy, scalability, and adaptability to challenging settings. In contrast to existing methods, scVI and scANVI integrate multiple datasets with a single generative model that can be directly used for downstream tasks, such as differential expression. Both methods are easily accessible through scvi‐tools. SYNOPSIS This study demonstrates the ability of scVI to integrate single‐cell RNA‐seq datasets in a variety of settings and presents scANVI, a new development based on scVI for automated annotation of cell types and states. In scVI, datasets from different labs and technologies are integrated in a joint latent space. In scANVI, cell type annotations are transferred between datasets and across different scenarios. Uncertainties of differential gene expression in multiple samples are quantified. The performance of scVI and scANVI in data integration and cell state annotation is superior to other related methods. Graphical Abstract This study demonstrates the ability of scVI to integrate single‐cell RNA‐seq datasets in a variety of settings and presents scANVI, a new development based on scVI for automated annotation of cell types and states.

To understand how people cultivate and sustain authenticity in multiple, often shifting, work roles, we analyze qualitative data gathered over five years from a sample of 48 plural careerists—people who choose to simultaneously hold and identify with multiple jobs. We find that people with multiple work identities struggle with being, feeling, and seeming authentic both to their contextualized work roles and to their broader work selves. Further, practices developed to cope with these struggles change over time, suggesting a two-phase emergent process of authentication in which people first synchronize their individual work role identities and then progress toward harmonizing a more general work self. This study challenges the notion that consistency is the core of authenticity, demonstrating that for people with multiple valued identities, authenticity is not about being true to one identity across time and contexts, but instead involves creating and holding cognitive and social space for several true versions of oneself that may change over time. It suggests that authentication is the emergent, socially constructed process of both determining who one is and helping others see who one is.

Products derived from agricultural biotechnology is fast becoming one of the biggest agricultural trade commodities globally, clothing us, feeding our livestock, and fueling our eco-friendly cars. This exponential growth occurs despite asynchronous regulatory schemes around the world, ranging from moratoriums and prohibitions on genetically modified (GM) organisms, to regulations that treat both conventional and biotech novel plant products under the same regulatory framework. Given the enormous surface area being cultivated, there is no longer a question of acceptance or outright need for biotech crop varieties. Recent recognition of the researchers for the development of a genome editing technique using CRISPR/Cas9 by the Nobel Prize committee is another step closer to developing and cultivating new varieties of agricultural crops. By employing precise, efficient, yet affordable genome editing techniques, new genome edited crops are entering country regulatory schemes for commercialization. Countries which currently dominate in cultivating and exporting GM crops are quickly recognizing different types of gene-edited products by comparing the products to conventionally bred varieties. This nuanced legislative development, first implemented in Argentina, and soon followed by many, shows considerable shifts in the landscape of agricultural biotechnology products. The evolution of the law on gene edited crops demonstrates that the law is not static and must adjust to the mores of society, informed by the experiences of 25 years of cultivation and regulation of GM crops. The crux of this review is a consolidation of the global legislative landscape on GM crops, as it stands, building on earlier works by specifically addressing how gene edited crops will fit into the existing frameworks. This work is the first of its kind to synthesize the applicable regulatory documents across the globe, with a focus on GM crop cultivation, and provides links to original legislation on GM and gene edited crops.

The impacts of autonomous vehicles, coupled with greater inter-vehicle and system connectivity, may be far-reaching on several levels. They entail changes to (1) the demand and behavior side, (2) the supply of mobility services, and (3) network and facility operational performance. We focus here on their impact on traffic flow and operations, especially in mixed traffic situations in which autonomous vehicles share the road with regular, human-driven vehicles, along with connected vehicles that may also have some automated functions. These mixed traffic situations correspond to likely deployment scenarios of the technologies, especially in the long transition towards 100% deployment. We explain using elementary traffic science concepts how autonomous vehicles and connected vehicles are expected to increase the throughput of highway facilities, as well as improve the stability of the traffic stream. A microsimulation framework featuring varying behavioral mechanisms for the three classes of vehicles is introduced. The framework is used to examine the throughput and stability questions through a series of experiments under varying market penetration rates of autonomous and/or connected vehicles; at low market shares, the impacts are relatively minor on either throughput or stability. However, as market shares increase, autonomous vehicles exert a greater influence on both dimensions compared to the same shares of connected vehicles. Applications of the framework to examine the effectiveness of selected traffic management approaches are discussed, including dedicated lanes for autonomous vehicles (good only if its use is optional and when the market share of autonomous vehicles is greater than the percentage of nominal capacity represented by that lane), and speed harmonization.

•We demonstrate a flexible deep-learning-based harmonisation framework.•Applied to age prediction and segmentation tasks in a range of datasets.•Scanner information is removed, maintaining performance and improving generalisability.•The framework can be used with any feedforward network architecture.•It successfully removes additional confounds and works with varied distributions. Increasingly large MRI neuroimaging datasets are becoming available, including many highly multi-site multi-scanner datasets. Combining the data from the different scanners is vital for increased statistical power; however, this leads to an increase in variance due to nonbiological factors such as the differences in acquisition protocols and hardware, which can mask signals of interest. We propose a deep learning based training scheme, inspired by domain adaptation techniques, which uses an iterative update approach to aim to create scanner-invariant features while simultaneously maintaining performance on the main task of interest, thus reducing the influence of scanner on network predictions. We demonstrate the framework for regression, classification and segmentation tasks with two different network architectures. We show that not only can the framework harmonise many-site datasets but it can also adapt to many data scenarios, including biased datasets and limited training labels. Finally, we show that the framework can be extended for the removal of other known confounds in addition to scanner. The overall framework is therefore flexible and should be applicable to a wide range of neuroimaging studies.

With the proliferation of multi-site neuroimaging studies, there is a greater need for handling non-biological variance introduced by differences in MRI scanners and acquisition protocols. Such unwanted sources of variation, which we refer to as “scanner effects”, can hinder the detection of imaging features associated with clinical covariates of interest and cause spurious findings. In this paper, we investigate scanner effects in two large multi-site studies on cortical thickness measurements across a total of 11 scanners. We propose a set of tools for visualizing and identifying scanner effects that are generalizable to other modalities. We then propose to use ComBat, a technique adopted from the genomics literature and recently applied to diffusion tensor imaging data, to combine and harmonize cortical thickness values across scanners. We show that ComBat removes unwanted sources of scan variability while simultaneously increasing the power and reproducibility of subsequent statistical analyses. We also show that ComBat is useful for combining imaging data with the goal of studying life-span trajectories in the brain. •Cortical thickness (CT) measurements are highly scanner specific.•Identifying scanner effects is crucial for inference and biomarker development.•We propose to use ComBat to harmonize cortical thickness values across scanners.

Meta-analysis is a method that combines estimates from studies conducted on different samples, in different contexts, or at different times. Social scientists increasingly use meta-analyses to aggregate evidence and learn about general substantive phenomena. We develop a framework to examine the theoretical foundations of meta-analysis, with emphasis on clarifying the role of external validity. We identify the conditions under which multiple studies are target-equivalent, meaning they identify the same empirical target. Our main result shows that external validity and harmonization, in comparisons made and how outcomes are measured, are necessary and sufficient for target-equivalence. We examine common formulations of meta-analysis—fixed-and random-effects models—developing the theoretical assumptions that underpin them and providing design-based identification results for these models. We then provide practical guidance based on our framework and results. Our results reveal limits to agnostic approaches to the combination of causal evidence from multiple studies.

Objective A consensual definition of occupational burnout is currently lacking. We aimed to harmonize the definition of occupational burnout as a health outcome in medical research and reach a consensus on this definition within the Network on the Coordination and Harmonisation of European Occupational Cohorts (OMEGA-NET). Methods First, we performed a systematic review in MEDLINE, PsycINFO and Embase (January 1990 to August 2018) and a semantic analysis of the available definitions. We used the definitions of burnout and burnout-related concepts from the Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT) to formulate a consistent harmonized definition of the concept. Second, we sought to obtain the Delphi consensus on the proposed definition. Results We identified 88 unique definitions of burnout and assigned each of them to 1 of the 11 original definitions. The semantic analysis yielded a first proposal, further reformulated according to SNOMED-CT and the panelists` comments as follows: \"In a worker, occupational burnout or occupational physical AND emotional exhaustion state is an exhaustion due to prolonged exposure to work-related problems\". A panel of 50 experts (researchers and healthcare professionals with an interest for occupational burnout) reached consensus on this proposal at the second round of the Delphi, with 82% of experts agreeing on it. Conclusion This study resulted in a harmonized definition of occupational burnout approved by experts from 29 countries within OMEGA-NET. Future research should address the reproducibility of the Delphi consensus in a larger panel of experts, representing more countries, and examine the practicability of the definition.