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POC-MON: A Novel and Cost-Effective Pocket Lemon Sniff Test (PLST) for Early Detection of Major Depressive Disorder

Cruz et al. | Jul 07, 2020

POC-MON: A Novel and Cost-Effective Pocket Lemon Sniff Test (PLST) for Early Detection of Major Depressive Disorder

Effective treatment of depression requires early detection. Depressive symptoms overlap with olfactory regions, which led to several studies of the correlation between sense of smell and depression. The alarming rise of depression, its related crimes, suicides, and lack of inexpensive, quick tools in detecting early depression — this study aims in demonstrating decreased olfaction and depression correlation. Forty-two subjects (ages 13-83) underwent POC-MON (Pocket Lemon) assessment — an oven-dried lemon peel sniff test, subjected to distance measurement when odor first detected (threshold) and completed Patient Health Questionnaires (PHQ-9). POC-MON and PHQ-9 scores yielded a correlation of 20% and 18% for the right and left nostrils, respectively. Among male (n=17) subjects, the average distance of POC-MON and PHQ-9 scores produced a correlation of 14% and 16% for the right and left nostrils, respectively. Females (n=25) demonstrated a correlation of 28% and 21% for the right and left nostrils, respectively. These results suggest the correlation between olfaction and depression in diagnosing its early-stage, using a quick, inexpensive, and patient-friendly tool — POC-MON.

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A Retrospective Study of Research Data on End Stage Renal Disease

Ponnaluri et al. | Mar 09, 2016

A Retrospective Study of Research Data on End Stage Renal Disease

End Stage Renal Disease (ESRD) is a growing health concern in the United States. The authors of this study present a study of ESRD incidence over a 32-year period, providing an in-depth look at the contributions of age, race, gender, and underlying medical factors to this disease.

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Creating a drought prediction model using convolutional neural networks

Bora et al. | Oct 08, 2024

Creating a drought prediction model using convolutional neural networks
Image credit: The authors

Droughts kill over 45,000 people yearly and affect the livelihoods of 55 million others worldwide, with climate change likely to worsen these effects. However, unlike other natural disasters (hurricanes, etc.), there is no early detection system that can predict droughts far enough in advance to be useful. Bora, Caulkins, and Joycutty tackle this issue by creating a drought prediction model.

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