Publications by authors named "M E Wenger"

Iron deficiency (ID) is the most prevalent nutrient deficiency in the world, with a growing literature documenting the negative effects of ID on perception, attention, and memory. Animal models of ID suggest that dysregulation of dopamine is responsible for the deficits in memory. However, evidence that ID affects dopamine in humans is extremely limited.

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Pollen traps, the current gold standard to determine pollen load and thereby the allergy season, are not sufficient to determine the allergenic risk. Therefore, the establishment of highly sensitive assays for allergen measurement is of highest interest. Herein, a graphene field-effect transistor (GFET) was constructed on an interdigitated electrodes chip to develop an immersible biosensor, which was used to detect the major birch pollen allergen Bet v 1.

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Background: Despite widespread access to antiretroviral therapy (ART) in the "Treat All" era, HIV-associated Kaposi sarcoma (KS) remains among the most common malignancies in sub-Saharan Africa. Survival after KS diagnosis has historically been poor in Africa, but knowledge whether survival has changed at the population level in the contemporary era has been limited by lack of community-representative surveillance and monitoring systems.

Methods: We identified all adult persons living with HIV (PLWH) with a new diagnosis of KS made between 2016 and 2019 during outpatient or inpatient care at prototypical primary care-providing medical facilities in Kenya and Uganda using rapid case ascertainment.

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People can use their sense of hearing for discerning thermal properties, though they are for the most part unaware that they can do so. While people unequivocally claim that they cannot perceive the temperature of pouring water through the auditory properties of hearing it being poured, our research further strengthens the understanding that they can. This multimodal ability is implicitly acquired in humans, likely through perceptual learning over the lifetime of exposure to the differences in the physical attributes of pouring water.

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Background: Wearable physiological monitoring devices are promising tools for remote monitoring and early detection of potential health changes of interest. The widespread adoption of such an approach across communities and over long periods of time will require an automated data platform for collecting, processing, and analyzing relevant health information.

Objective: In this study, we explore prospective monitoring of individual health through an automated data collection, metrics extraction, and health anomaly analysis pipeline in free-living conditions over a continuous monitoring period of several months with a focus on viral respiratory infections, such as influenza or COVID-19.

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