Browse Articles

Can the nucleotide content of a DNA sequence predict the sequence accessibility?

Balachandran et al. | Mar 10, 2023

Can the nucleotide content of a DNA sequence predict the sequence accessibility?
Image credit: Warren Umoh

Sequence accessibility is an important factor affecting gene expression. Sequence accessibility or openness impacts the likelihood that a gene is transcribed and translated into a protein and performs functions and manifests traits. There are many potential factors that affect the accessibility of a gene. In this study, our hypothesis was that the content of nucleotides in a genetic sequence predicts its accessibility. Using a machine learning linear regression model, we studied the relationship between nucleotide content and accessibility.

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Toxicity of aminomethylphosphonic acid via the Wnt signaling pathway as a novel mechanism

Zhuang et al. | Mar 08, 2023

Toxicity of aminomethylphosphonic acid via the Wnt signaling pathway as a novel mechanism
Image credit: Image credit: Dapur Melodi

The Wnt signaling pathway, known to coordinate important aspects of cellular homeostasis ranging from differentiation, proliferation, migration, and much more, is dysregulated in many human diseases. This study demonstrates that aminomethylphosphonic acid, which is the main metabolite found in the common herbicide Glyphosate, is toxic to planaria and capable of binding to canonical Wnt proteins.

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Tomato disease identification with shallow convolutional neural networks

Trinh et al. | Mar 03, 2023

Tomato disease identification with shallow convolutional neural networks

Plant diseases can cause up to 50% crop yield loss for the popular tomato plant. A mobile device-based method to identify diseases from photos of symptomatic leaves via computer vision can be more effective due to its convenience and accessibility. To enable a practical mobile solution, a “shallow” convolutional neural networks (CNNs) with few layers, and thus low computational requirement but with high accuracy similar to the deep CNNs is needed. In this work, we explored if such a model was possible.

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Different volumes of acetic acid affect the oxygen production of spinach leaves during photosynthesis

Wang et al. | Feb 24, 2023

Different volumes of acetic acid affect the oxygen production of spinach leaves during photosynthesis

The burning of fossil fuels, leading to an increased amount of carbon emissions, is the main cause of acid rain. Acid rain affects the process of photosynthesis, which makes the topic valuable to investigate. Our group utilizes plants to further investigate the relationship between pH value and photosynthesis. In this experiment, our group hypothesized that rain with a lower pH will decrease the rate of photosynthesis, causing less oxygen to be produced in the reaction.

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The novel function of PMS2 mutation on ovarian cancer proliferation

Cho et al. | Dec 18, 2022

The novel function of <em>PMS2</em> mutation on ovarian cancer proliferation

With disruption of DNA repair pathways pertinent to the timeline of cancer, thorough evaluation of mutations relevant to DNA repair proteins is crucial within cancer research. One such mutation includes S815L PMS2 - a mutation that results in significant decrease of DNA repair function by PMS2 protein. While mutation of PMS2 is associated with significantly increased colorectal and endometrial cancer risk, much work is left to do to establish the functional effects of the S815L PMS2 mutation in ovarian cancer progression. In this article, researchers contribute to this essential area of research by uncovering the tumor-progressive effects of the S815L PMS2 mutation in the context of ovarian cancer cell lines.

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Prediction of preclinical Aβ deposit in Alzheimer’s disease mice using EEG and machine learning

Igarashi et al. | Nov 29, 2022

Prediction of preclinical Aβ deposit in Alzheimer’s disease mice using EEG and machine learning

Alzheimer’s disease (AD) is a common disease affecting 6 million people in the U.S., but no cure exists. To create therapy for AD, it is critical to detect amyloid-β protein in the brain at the early stage of AD because the accumulation of amyloid-β over 20 years is believed to cause memory impairment. However, it is difficult to examine amyloid-β in patients’ brains. In this study, we hypothesized that we could accurately predict the presence of amyloid-β using EEG data and machine learning.

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Effect of heme vs. non-heme iron supplements on gut microbiome fitness

Dogra et al. | Nov 07, 2022

Effect of heme vs. non-heme iron supplements on gut microbiome fitness

Here, based on identification of iron deficiencies of a majority of people around the world, the authors sought to understand how the two main forms of dietary iron, heme and non-heme, affect the bacteria found in the human gut. by using a cell plate study, they found that bacterial growth increased with increasing concentration os either form of iron, up until the point where the high iron content resulted in cytotoxicity. They suggest this evidence points to the potential dangers of overconsumption of iron.

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A novel deep learning model for visibility correction of environmental factors in autonomous vehicles

Dey et al. | Oct 31, 2022

A novel deep learning model for visibility correction of environmental factors in autonomous vehicles

Intelligent vehicles utilize a combination of video-enabled object detection and radar data to traverse safely through surrounding environments. However, since the most momentary missteps in these systems can cause devastating collisions, the margin of error in the software for these systems is small. In this paper, we hypothesized that a novel object detection system that improves detection accuracy and speed of detection during adverse weather conditions would outperform industry alternatives in an average comparison.

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Effect of environment factors on the expression of soluble PDE8A1 in E. coli

Jiang et al. | Oct 25, 2022

Effect of environment factors on the expression of soluble PDE8A1 in <em>E. coli</em>

PDE8, a type of phosphodiesterase (PDE), is proven to be crucial in various cellular activities and physiological activities by influencing second messenger systems. It is involved in a wide range of diseases, including Alzheimer’s disease and various heart diseases. However, there is limited information about PDE8 selective inhibitors. This work aimed to improve the solubility and yield of PDE8 in the supernatant by exploring suitable culture conditions, including temperatures and different additives.

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Refinement of Single Nucleotide Polymorphisms of Atopic Dermatitis related Filaggrin through R packages

Naravane et al. | Oct 12, 2022

Refinement of Single Nucleotide Polymorphisms of Atopic Dermatitis related Filaggrin through R packages

In the United States, there are currently 17.8 million affected by atopic dermatitis (AD), commonly known as eczema. It is characterized by itching and skin inflammation. AD patients are at higher risk for infections, depression, cancer, and suicide. Genetics, environment, and stress are some of the causes of the disease. With the rise of personalized medicine and the acceptance of gene-editing technologies, AD-related variations need to be identified for treatment. Genome-wide association studies (GWAS) have associated the Filaggrin (FLG) gene with AD but have not identified specific problematic single nucleotide polymorphisms (SNPs). This research aimed to refine known SNPs of FLG for gene editing technologies to establish a causal link between specific SNPs and the diseases and to target the polymorphisms. The research utilized R and its Bioconductor packages to refine data from the National Center for Biotechnology Information's (NCBI's) Variation Viewer. The algorithm filtered the dataset by coding regions and conserved domains. The algorithm also removed synonymous variations and treated non-synonymous, frameshift, and nonsense separately. The non-synonymous variations were refined and ordered by the BLOSUM62 substitution matrix. Overall, the analysis removed 96.65% of data, which was redundant or not the focus of the research and ordered the remaining relevant data by impact. The code for the project can also be repurposed as a tool for other diseases. The research can help solve GWAS's imprecise identification challenge. This research is the first step in providing the refined databases required for gene-editing treatment.

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