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The Long-Term Effect of CBD Crystals and CBD Oil on Depressive-Associated Rat Behaviors

Yang et al. | Dec 18, 2020

The Long-Term Effect of CBD Crystals and CBD Oil on Depressive-Associated Rat Behaviors

Cannabidiol (CBD) is a chemical extracted from cannabis and shown by some studies to alleviate the symptoms of many mental disorders, especially major depressive disorder. The authors hypothesized that chronic treatments with purified CBD through oral administration would relieve depression-associated behaviors in normal healthy rats under adverse conditions. A statistical analysis of the experimental data suggested that long-term consumption of CBD could elicit depression associated symptoms in normal rats without depression. The results imply that people should consume CBD-containing products with extreme caution and highlight the need to carefully monitor the use of CBD in health care products.

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Analysis of ultraviolet light as a bactericide of gram-negative bacteria in Cladophora macroalgae extracts

Newell et al. | Nov 07, 2022

Analysis of ultraviolet light as a bactericide of gram-negative bacteria in <em>Cladophora</em> macroalgae extracts

Here, the authors sought to use Cladophora macroalgae as a possible antibiotic to address the growing threat of antibiotic resistance in pathogenic bacteria. However, when they observed algae extracts to be greatly contaminated with gram-negative bacteria, they adapted to explore the ability to use ultraviolet light as a bactericide. They found that treatment with ultraviolet light had a significant effect.

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Genomic Signature Analysis for the Strategic Bioremediation of Polycyclic Aromatic Hydrocarbons in Mangrove Ecosystems in the Gulf of Tonkin

Dao et al. | Jun 27, 2021

Genomic Signature Analysis for the Strategic Bioremediation of Polycyclic Aromatic Hydrocarbons in Mangrove Ecosystems in the Gulf of Tonkin

Engineered bacteria that degrade oil are currently being considered as a safe option for the treatment of oil spills. For this approach to be successful, the bacteria must effectively express oil-degrading genes they uptake as part of an external genoming vehicle called a "plasmid". Using a computational approach, the authors investigate plasmid-bacterium compatibility to find pairs that ensure high levels of gene expression.

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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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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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Rhizosphere metagenome analysis and wet-lab approach to derive optimal strategy for lead remediation in situ

Bhat et al. | Jul 18, 2023

Rhizosphere metagenome analysis and wet-lab approach to derive optimal strategy for lead remediation <i>in situ</i>
Image credit: Karolina Grabowska

The Environmental Protection Agency (EPA) reports a significant number of heavy metal-contaminated sites across the United States. To address this public health concern, rhizoremediation using microbes has emerged as a promising solution. Here, a combination of soil microbes were inoculated in the rhizosphere in soil contaminated with 500 parts per million (ppm) of lead. Results showed rhizoremediation is an effective bioremediation strategy and may increase crop productivity by converting nonarable lands into arable lands.

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The analysis of the viral transmission and structural interactions between the HIV-1 envelope glycoprotein and the lymphocyte receptor integrin α4β7

Ganesh et al. | Apr 28, 2021

The analysis of the viral transmission and structural interactions between the HIV-1 envelope glycoprotein and the lymphocyte receptor integrin α4β7

The Human Immunodeficiency Virus (HIV) infects approximately 40 million people globally, and one million people die every year from Acquired Immune Deficiency Syndrome (AIDS)-related illnesses. This study examined the interactions between the HIV-1 envelope glycoprotein gp120 and the human lymphocyte receptor integrin α4β7, the putative first long-range receptor for the envelope glycoprotein of the virus in mucosal tissues. Presented data support the claim that the V1 loop is involved in the binding between α4β7 and the HIV-1 envelope glycoprotein through molecular dockings.

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Expressional correlations between SERPINA6 and pancreatic ductal adenocarcinoma-linked genes

Selver et al. | Oct 06, 2021

Expressional correlations between <em>SERPINA6</em> and pancreatic ductal adenocarcinoma-linked genes

Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer, with early diagnosis and treatment challenges. When any of the genes KRAS, SMAD4, TP53, and BRCA2 are heavily mutated, they correlate with PDAC progression. Cellular stress, partly regulated by the gene SERPINA6, also correlates with PDAC progression. When SERPINA6 is highly expressed, corticosteroid-binding globulin inhibits the effect of the stress hormone cortisol. In this study, the authors explored whether there is an inverse correlation between the expression of SERPINA6 and PDAC-linked genes.

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