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A Quantitative Assessment of Time, Frequency, and Time-frequency Algorithms for Automated Seizure Detection and Monitoring

Vangal et al. | Sep 28, 2020

A Quantitative Assessment of Time, Frequency, and Time-frequency Algorithms for Automated Seizure Detection and Monitoring

Each year, over 100,000 patients die from Sudden Unexpected Death in Epilepsy (SUDEP). A reliable seizure warning system can help patients stay safe. This work presents a comprehensive, comparative analysis of three different signal processing algorithms for automated seizure/ictal detection. The experimental results show that the proposed methods can be effective for accurate automated seizure detection and monitoring in clinical care.

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Antibiotic Residues Detected in Commercial Cow’s Milk

Memili et al. | Mar 18, 2015

Antibiotic Residues Detected in Commercial Cow’s Milk

Antibiotics are oftentimes used to treat mastitis (infection of the mammary gland) in dairy cows. Regulations require that milk from these cows be discarded until the infection has cleared and antibiotic residues are no longer detectable in the cow's milk. These regulations are in place to protect consumers and to help prevent the rise of antibiotic resistant bacteria. In this study, the authors test milk samples from 10 milk suppliers in the Greensboro, NC to see if they contain detectable levels of antibiotic residues.

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Development and Implementation of Enzymatic and Volatile Compound-based Approaches for Instantaneous Detection of Pathogenic Staphylococcus aureus

Nori et al. | Feb 20, 2021

Development and Implementation of Enzymatic and Volatile Compound-based Approaches for Instantaneous Detection of Pathogenic <i>Staphylococcus aureus</i>

Staphylococcus aureus (S. aureus) has a mortality rate of up to 30% in developing countries. The purpose of this experiment was to determine if enzymatic and volatile compound-based approaches would perform more quickly in comparison to existing S. aureus diagnostic methods and to evaluate these novel methods on accuracy. Ultimately, this device provided results in less than 30 seconds, which is much quicker than existing methods that take anywhere from 10 minutes to 48 hours based on approach. Statistical analysis of accuracy provides preliminary confirmation that the device based on enzymatic and volatile compound-based approaches can be an accurate and time-efficient tool to detect pathogenic S. aureus.

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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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DyGS: A Dynamic Gene Searching Algorithm for Cancer Detection

Wang et al. | Jun 05, 2018

DyGS: A Dynamic Gene Searching Algorithm for Cancer Detection

Wang and Gong developed a novel dynamic gene-searching algorithm called Dynamic Gene Search (DyGS) to create a gene panel for each of the 12 cancers with the highest annual incidence and death rate. The 12 gene panels the DyGS algorithm selected used only 3.5% of the original gene mutation pool, while covering every patient sample. About 40% of each gene panel is druggable, which indicates that the DyGS-generated gene panels can be used for early cancer detection as well as therapeutic targets in treatment methods.

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Machine Learning Algorithm Using Logistic Regression and an Artificial Neural Network (ANN) for Early Stage Detection of Parkinson’s Disease

Kar et al. | Oct 10, 2020

Machine Learning Algorithm Using Logistic Regression and an Artificial Neural Network (ANN) for Early Stage Detection of Parkinson’s Disease

Despite the prevalence of PD, diagnosing PD is expensive, requires specialized testing, and is often inaccurate. Moreover, diagnosis is often made late in the disease course when treatments are less effective. Using existing voice data from patients with PD and healthy controls, the authors created and trained two different algorithms: one using logistic regression and another employing an artificial neural network (ANN).

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Analysis of the Exoplanet HD 189733b to Confirm its Existence

Babaria et al. | Sep 21, 2020

Analysis of the Exoplanet HD 189733b to Confirm its Existence

In this study, the authors study features of exoplanet 189733 b. This exoplanet, or planets that orbit stars other than the Sun, is found in the HD star system. Using a DSLR camera, they constructed a high caliber exoplanet transit detection tracker to study the orbital periods, radial velocity, and photometry of 189733 b. They then compared results from their system to data collected by other high precision studies. What they found was that their system produced results supporting previously published studies. These results are exciting results from the solar system demonstrating the importance of validating radial velocity and photometry data using high-precision studies.

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Molecular Alterations in a High-Fat Mouse Model Before the Onset of Diet–Induced Nonalcoholic Fatty Liver Disease

Lee et al. | Sep 20, 2016

Molecular Alterations in a High-Fat Mouse Model Before the Onset of Diet–Induced Nonalcoholic Fatty Liver Disease

Nonalcoholic fatty liver disease (NAFLD) is one of the most prevalent chronic liver diseases worldwide, but there are few studied warning signs for early detection of the disease. Here, researchers study alterations that occur in a mouse model of NAFLD, which indicate the onset of NAFLD sooner. Earlier detection of diseases can lead to better prevention and treatment.

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The Development of a Highly Sensitive Home Diagnosis Kit for Group A Streptococcus Bacteria (GAS)

Mai et al. | Dec 05, 2018

The Development of a Highly Sensitive Home Diagnosis Kit for Group A Streptococcus Bacteria (GAS)

In this article, Mai et al. have developed a do-it-yourself kit for the detection of Strep A bacterial infections. While Strep A infections require antibiotic administration, viral infections, which can present with similar symptoms, often resolve on their own. The problem with delayed antibiotic treatment is an increasing risk of complications. Currently an accurate diagnosis requires that patients make the trip to the hospital where sensitive tests can be performed. The method described here, bundled into a commercially available kit, could help speed up the identification of such bacterial infections. When presented with symptoms of a sore throat and fever, you could just buy the kit at your local pharmacy, perform the simple yet highly accurate and sensitive test, and know whether an urgent trip to the doctor's for an antibiotic prescription is necessary. How convenient!

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