In the wake of the ongoing nationwide antiracist movement, the academy at large has been reflecting on its role in society and the pursuit of social justice. Here, we examine the state of diversity, equity, and inclusion (DEI) in chemistry education research and practice through a literature review and offer suggestions for future directions. Through a keyword search in four leading journals in chemistry and science education, we chose to review 73 articles with DEI-relevant research foci. Through quantitative analysis, we noticed that there has been a recent increase in DEI-focused studies and that most studies have been conducted at precollege and college levels. We also performed qualitative analysis in order to identify common themes across reviewed articles. On the basis of this analysis, we organized our findings into four sections: the rationale for advancing DEI, the current state of DEI, prevalent explanations of existing inequities, and strategies for advancing DEI. The literature indicates that the state of DEI has improved considerably over the years, particularly in terms of the numbers and achievements of women and historically minoritized groups. These improvements may be driven by widespread research in and embracement of novel pedagogical approaches that enhance students' academic outcomes and classroom culture. However, we also noticed areas with scope for improvement. We make suggestions to continue this hard-won progress: expanding research in less studied contexts, holistic reform approaches across institutional levels, and justice-and relevance-oriented curricular reforms. We also urge the Chemistry Education Research (CER) community to reconceptualize frameworks for equity and diversity to move beyond increasing the numbers of people from minoritized groups.
Author ContributionsYRC supervised the project. YRC, IG, and PM conceived the experimental method. RB and PM performed the experiments. YRC and RB developed the analysis. RB performed the analysis and numerical simulations. YRC derived the analytical model with IG. RB and YRC wrote the manuscript with inputs from IG. AbstractBiochemical signaling networks allow living cells to adapt to a changing environment, but these networks must cope with unavoidable number fluctuations ("noise") in their molecular constituents. Escherichia coli chemotaxis, by which bacteria modulate their random run/tumble swimming pattern to navigate their environment, is a paradigm for the role of noise in cell signaling. The key signaling protein, CheY, when activated by (reversible) phosphorylation, causes a switch in the rotational direction of the flagellar motors propelling the cell, leading to tumbling. CheY-P concentration, [CheY-P], is thus a measure of the chemotaxis network's output, and temporal fluctuations in [CheY-P] provide a proxy for network noise. However, measuring these fluctuations in the single cell, at the relevant timescale of individual run and tumble events, remains a challenge. Here we quantify the short-timescale (0.5-5 s) fluctuations in [CheY-P] from the switching dynamics of individual flagella, observed using time-resolved fluorescence microscopy of optically trapped E. coli cells. This approach reveals large [CheY-P] fluctuations at steady state, which may play a critical role in driving flagellar switching and cell tumbling. A stochastic theoretical model, inspired by work on gene expression noise, points to CheY activation occurring in bursts, driving the large [CheY-P] fluctuations. When the network is stimulated chemically to higher activity, we observe a dramatic decrease in [CheY-P] fluctuations.Our stochastic model shows that an intrinsic kinetic ceiling on network activity places an upper limit on [CheY-P], which when encountered suppresses its fluctuations. This limit may also prevent cells from tumbling unproductively in steep gradients.3 Significance StatementBacteria use intracellular signaling networks to navigate and adapt to their changing environment. These networks must cope with fluctuations in their molecular constituents, but the role this noise plays in cell behavior is not well understood. Here, we present a novel approach to quantify network noise in individual Escherichia coli cells. Our measurements show that the network exhibits larger-than-expected fluctuations when operating at a steady state; these fluctuations decrease dramatically when the network is activated by a chemical stimulus.A model inspired by gene expression noise studies recapitulates our findings and suggests that large fluctuations are driven by 'bursts' in signaling, drawing a parallel between the operating principles of gene regulatory and protein signaling networks.
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