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Are alkaline spices the future of antibiotics?

Jani et al. | Jan 23, 2022

Are alkaline spices the future of antibiotics?

The authors experimented with several commonly available alkaline spices (turmeric, cayenne pepper, and cinnamon) to study their antimicrobial properties, hypothesizing that alkaline spices would have antimicrobial activity. Results showed a zone of inhibition of bacterial growth, with the largest zone of inhibition being around turmeric, followed by cayenne pepper, and the smallest around cinnamon. These results are impactful, as common alkaline spices generally do show antibacterial properties and both bacteriostatic and bactericidal effects correlated with degree of alkalinity.

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Correlation of socioeconomic status and lead concentration in tap water in Missouri

Rabbani et al. | Feb 03, 2022

Correlation of socioeconomic status and lead concentration in tap water in Missouri

Organic and non-organic contaminants in tap water have been linked to adverse health effects. Tap water is a major source of lead, which is neurotoxic and poses a major health risk, particularly to children and pregnant women. Using publicly available annual water quality reports data for the state of Missouri, the authors show that communities with lower median household income and lower per capita incomes had significantly higher lead levels in their tap water.

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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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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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