Browse Articles

Combating Insulin Resistance Using Medicinal Plants as a Supplementary Therapy to Metformin in 3T3-L1 Adipocytes: Improving Early Intervention-Based Diabetes Treatment

Jayram et al. | Apr 08, 2019

Combating Insulin Resistance Using Medicinal Plants as a Supplementary Therapy to Metformin in 3T3-L1 Adipocytes: Improving Early Intervention-Based Diabetes Treatment

A primary cause of diabetes is insulin resistance, which is caused by disruption of insulin signal transduction. The objective of this study was to maximize insulin sensitivity by creating a more effective, early intervention-based treatment to avert severe T2D. This treatment combined metformin, “the insulin sensitizer”, and medicinal plants, curcumin, fenugreek, and nettle.

Read More...

Antibacterial Effects of Copper Surfaces

Mulukutla et al. | May 19, 2020

Antibacterial Effects of Copper Surfaces

This study examined the ability of copper and copper alloy surfaces to inhibit bacterial growth, which may be help prevent healthcare-associated infections. The authors exposed two non-pathogenic strains of bacteria to different metal plates for varying degrees of time and measured bacterial growth.

Read More...

Trust in the use of artificial intelligence technology for treatment planning

Srivastava et al. | Sep 18, 2024

Trust in the use of artificial intelligence technology for treatment planning

As AI becomes more integrated into healthcare, public trust in AI-developed treatment plans remains a concern, especially for emotionally charged health decisions. In a study of 81 community college students, AI-created treatment plans received lower trust ratings compared to physician-developed plans, supporting the hypothesis. The study found no significant differences in AI trust levels across demographic factors, suggesting overall skepticism toward AI-driven healthcare.

Read More...

Breast cancer mammographic screening by different guidelines among women of different races/ethnicities

Wang et al. | Aug 27, 2023

Breast cancer mammographic screening by different guidelines among women of different races/ethnicities

Mammographic screening is a common diagnostic tool for breast cancer among average-risk women. The authors hypothesized that adherence rates for mammographic screening may be lower among minorities (non-Hispanic black (NHB) and Hispanic/Latino) than among non-Hispanic whites (NHW) regardless of the guideline applied. The findings support other studies’ results that different racial/ethnic and socio-demographic factors can affect screening adherence. Therefore, healthcare providers should promote breast cancer screening especially among NHW/Hispanic women and women lacking insurance coverage.

Read More...

Country-level relationship of OTC medicine consumption and frequency of GP consultation

Hirai et al. | Dec 09, 2024

Country-level relationship of OTC medicine consumption and frequency of GP consultation

The discussion surrounding self-medication with non-prescription medicines has gained significance in healthcare and public health, particularly given the global increase in consumption of non-prescription drugs. This study aimed to examine the association between the frequency of general practitioner (GP) consultations and the proportion of economic resources spent on OTC medicine.

Read More...

Risk factors contributing to Pennsylvania childhood asthma

Li et al. | Oct 30, 2024

Risk factors contributing to Pennsylvania childhood asthma
Image credit: The authors

Asthma is one of the most prevalent chronic conditions in the United States. But not all people experience asthma equally, with factors like healthcare access and environmental pollution impacting whether children are likely to be hospitalized for asthma's effects. Li, Li, and Ruffolo investigate what demographic and environmental factors are predictive of childhood asthma hospitalization rates across Pennsylvania.

Read More...

A five-year retrospective analysis of Tuberculosis risk factors and their variability in the United States

Kini et al. | Mar 14, 2026

A five-year retrospective analysis of Tuberculosis risk factors and their variability in the United States
Image credit: Kini, Diaz Gaviria, Diaz, and Kini

The main goal of this study is to determine what demographics are related to tuberculosis incidence in the United States populations, particularly if changing demographics are related to differences in tuberculosis risk over two discrete time periods. The major finding is that in the two studied time periods, tuberculosis risk factors were somewhat consistent and may be influenced by things such as immigration, healthcare access, and race or ethnicity, although the top predictor did change.

Read More...

Advancing pediatric cancer predictions through generative artificial intelligence and machine learning

Yadav et al. | Dec 21, 2024

Advancing pediatric cancer predictions through generative artificial intelligence and machine learning

Pediatric cancers pose unique challenges due to their rarity and distinct biological factors, emphasizing the need for accurate survival prediction to guide treatment. This study integrated generative AI and machine learning, including synthetic data, to analyze 9,184 pediatric cancer patients, identifying age at diagnosis, cancer types, and anatomical sites as significant survival predictors. The findings highlight the potential of AI-driven approaches to improve survival prediction and inform personalized treatment strategies, with broader implications for innovative healthcare applications.

Read More...