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Mechanistic deconvolution of autoreduction in tetrazolium-based cell viability assays

Tran et al. | Jul 12, 2024

Mechanistic deconvolution of autoreduction in tetrazolium-based cell viability assays

Optical reporters like tetrazolium dyes, exemplified by 5-diphenyl tetrazolium bromide (MTT), are effective tools for quantifying cellular responses under experimental conditions. These dyes assess cell viability by producing brightly-colored formazan dyes when reduced inside active cells. However, certain small molecules, including reducing agents like ascorbic acid, cysteine, and glutathione (GSH), can interfere with MTT assays, potentially compromising accuracy.

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Intra and interspecies control of bacterial growth through extracellular extracts

Howe et al. | Jun 07, 2024

Intra and interspecies control of bacterial growth through extracellular extracts

The study discusses the relationship between bacterial species and the human gut microbiome, emphasizing the role of quorum sensing molecules in bacterial communication and its implications for health. Authors investigated the impact of bacterial supernatants from Escherichia coli (E. coli) on the growth of new E. coli and Enterobacter aerogenes (E. aerogenes) cultures.

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A Novel Alzheimer's Disease Therapeutic Model: Attenuating Hyperphosphorylated Tau and Amyloid β (Aβ) Aggregates by Characterizing Antioxidative, Anti-Inflammatory, and Neuroprotective Properties of Natural Extracts

Pokkunuri et al. | Jul 25, 2022

A Novel Alzheimer's Disease Therapeutic Model: Attenuating Hyperphosphorylated Tau and Amyloid β (Aβ) Aggregates by Characterizing Antioxidative, Anti-Inflammatory, and Neuroprotective Properties of Natural Extracts

Oxidative damage and neuro-inflammation were the key pathways implicated in the pathogenesis of Alzheimer’s disease. In this study, 30 natural extracts from plant roots and leaves with extensive anti-inflammatory and anti-oxidative properties were consumed by Drosophila melanogaster. Several assays were performed to evaluate the efficacy of these combinational extracts on delaying the progression of Alzheimer’s disease. The experimental group showed increased motor activity, improved associative memory, and decreased lifespan decline relative to the control group.

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Effects of caffeine on muscle signals measured with sEMG signals

Park et al. | Jun 20, 2022

Effects of caffeine on muscle signals measured with sEMG signals

Here, the authors used surface electromyography to measure the effects of caffeine intake on the resting activity of muscles. They found a significant increase in the measured amplitude suggesting that caffeine intake increased the number of activated muscle fibers during rest. While previous research has focused on caffeine's effect on the contraction signals of muscles, this research suggests that its effects extend to even when a muscle is at rest.

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Using data science along with machine learning to determine the ARIMA model’s ability to adjust to irregularities in the dataset

Choudhary et al. | Jul 26, 2021

Using data science along with machine learning to determine the ARIMA model’s ability to adjust to irregularities in the dataset

Auto-Regressive Integrated Moving Average (ARIMA) models are known for their influence and application on time series data. This statistical analysis model uses time series data to depict future trends or values: a key contributor to crime mapping algorithms. However, the models may not function to their true potential when analyzing data with many different patterns. In order to determine the potential of ARIMA models, our research will test the model on irregularities in the data. Our team hypothesizes that the ARIMA model will be able to adapt to the different irregularities in the data that do not correspond to a certain trend or pattern. Using crime theft data and an ARIMA model, we determined the results of the ARIMA model’s forecast and how the accuracy differed on different days with irregularities in crime.

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