Publications by authors named "M Virginia Jernigan"

Background: Diaphorina citri is an insect vector of "Candidatus Liberibacter asiaticus" (CLas), the gram-negative bacterial pathogen associated with citrus greening disease. Control measures rely on pesticides with negative impacts on the environment, natural ecosystems, and human and animal health. In contrast, gene-targeting methods have the potential to specifically target the vector species and/or reduce pathogen transmission.

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In 2021, the American Psychological Association offered an apology to people of color for harms, actions, and inactions and accepted responsibility for contributing to systemic inequities. The field of psychology has a complicated and long history of contributing to American racism and the belief in human hierarchy. This article illustrates the strategy the American Psychological Association followed to issue an apology at a scale that incorporated the voices and perspectives of the association's senior leaders and racial equity experts.

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Dr. Janet E. Helms's use of psychological science to engage the field of psychology in radical progressive debates about race and identity is unprecedented.

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Citrus greening disease is caused by the pathogen Liberibacter asiaticus and transmitted by the Asian citrus psyllid, . No curative treatment or significant prevention mechanism exists for this disease, which causes economic losses from reduced citrus production. A high-quality genome of is being manually annotated to provide accurate gene models to identify novel control targets and increase understanding of this pest.

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Introduction: The population of American Indians and Alaska Natives (AI/ANs) aged 65 and older is growing rapidly, raising concerns about Alzheimer's disease (AD) in their communities.

Methods: We distributed a survey incorporating the Alzheimer's Disease Knowledge Scale to 341 AI/AN community members attending cultural events. We computed average adjusted predictions and 95% confidence intervals from a linear regression model, used joint F tests to examine differences in scores according to demographic variables, calculated the percentage of correct items for each participant, and computed domain-specific averages across the sample.

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