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Don’t Waste the Medical Waste: Reducing Improperly Classified Hazardous Waste in a Medical Facility

Hemani et al. | Jun 20, 2018

Don’t Waste the Medical Waste: Reducing Improperly Classified Hazardous Waste in a Medical Facility

Hemani et al. tackled the problem of rampant hospital waste by implementing staff training to help inform hospital workers about proper waste disposal. The authors observed a significant increase in proper waste disposal after the training, showing that simple strategies, such as in-person classroom training and posters, can have a profound effect on limiting improper waste handling.

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Decolorization of textile dyes by edible white rot fungi

Lin et al. | Apr 29, 2022

Decolorization of textile dyes by edible white rot fungi

As fast fashion explodes in popularity, the fashion industry remains one of the most prominent industries responsible for pollution. This pollution includes a lack of treatment for textile dyes that remain toxic or carcinogenic as they persist in wastewater. To resolve this, the authors of this study set out to determine the efficacy of using edible white rot fungi for cell-based biodegradation of textile dyes into harmless chemicals. This method takes advantage of fungi found in excess from the fungi industry, decreasing food waste while addressing textile waste in tandem.

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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.

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Mendelian randomization reveals shared genetic landscape in autism spectrum disorder and Alzheimer's disease

Lee et al. | Nov 04, 2024

Mendelian randomization reveals shared genetic landscape in autism spectrum disorder and Alzheimer's disease

Autism Spectrum Disorder (ASD) and Alzheimer's Disease (AD) are distinct conditions, but research suggests a link, as individuals with ASD are 2.5 times more likely to develop AD. A study employing genome-wide association studies and Mendelian randomization revealed shared genetic factors, particularly in synaptic regulation pathways, that may increase the risk of AD in those with ASD. These findings provide insights into the genetic underpinnings connecting the two disorders.

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A novel approach for predicting Alzheimer’s disease using machine learning on DNA methylation in blood

Adami et al. | Sep 20, 2023

A novel approach for predicting Alzheimer’s disease using machine learning on DNA methylation in blood
Image credit: National Cancer Institute

Here, recognizing the difficulty associated with tracking the progression of dementia, the authors used machine learning models to predict between the presence of cognitive normalcy, mild cognitive impairment, and Alzheimer's Disease, based on blood DNA methylation levels, sex, and age. With four machine learning models and two dataset dimensionality reduction methods they achieved an accuracy of 53.33%.

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