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Aggression of Carcharhinus leucas and Carcharhinus amblyrhynchos towards humans

Mignone et al. | May 11, 2021

Aggression of <i>Carcharhinus leucas</i> and <i>Carcharhinus amblyrhynchos</i> towards humans

This paper presents findings on Carcharhinus leucas (bull shark) and Carcharhinus amblyrhynchos (grey reef shark) aggression towards humans at Beqa Adventure Divers in Shark Reef Marine Reserve, Fiji. We hypothesized that grey reef sharks would receive more prods than bull sharks because grey reef sharks are typically more aggressive than bull sharks. The results supported our hypothesis, as an individual grey reef shark received 2.44 prods on average per feed, while a bull shark had an average of 0.61. These findings are meaningful not only to the world’s general understanding of shark aggression, but also to human protection against grey reef sharks as well as public education on bull sharks and the conservation of the species.

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Contrasting role of ASCC3 and ALKBH3 in determining genomic alterations in Glioblastoma Multiforme

Sriram et al. | Sep 27, 2022

Contrasting role of <i>ASCC3</i> and <i>ALKBH3</i> in determining genomic alterations in Glioblastoma Multiforme

Glioblastoma Multiforme (GBM) is the most malignant brain tumor with the highest fraction of genome alterations (FGA), manifesting poor disease-free status (DFS) and overall survival (OS). We explored The Cancer Genome Atlas (TCGA) and cBioportal public dataset- Firehose legacy GBM to study DNA repair genes Activating Signal Cointegrator 1 Complex Subunit 3 (ASCC3) and Alpha-Ketoglutarate-Dependent Dioxygenase AlkB Homolog 3 (ALKBH3). To test our hypothesis that these genes have correlations with FGA and can better determine prognosis and survival, we sorted the dataset to arrive at 254 patients. Analyzing using RStudio, both ASCC3 and ALKBH3 demonstrated hypomethylation in 82.3% and 61.8% of patients, respectively. Interestingly, low mRNA expression was observed in both these genes. We further conducted correlation tests between both methylation and mRNA expression of these genes with FGA. ASCC3 was found to be negatively correlated, while ALKBH3 was found to be positively correlated, potentially indicating contrasting dysregulation of these two genes. Prognostic analysis showed the following: ASCC3 hypomethylation is significant with DFS and high ASCC3 mRNA expression to be significant with OS, demonstrating ASCC3’s potential as disease prediction marker.

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Exploring Unconventional Growing Methods to Promote Healthy Growth in Common Household Plants: Tagetes patula L. and Lepidium sativum

Nguyen et al. | Feb 25, 2021

Exploring Unconventional Growing Methods to Promote Healthy Growth in Common Household Plants: <i>Tagetes patula</i> L. and <i>Lepidium sativum</i>

This study focused on finding more sustainable growing methods that reduce chemical fertilizer or water usage and can be used at the household level for garden plants. Metrics for healthy plant growth were height at first bloom, growing time, and survival rate. The Deep Water Culture (DWC) treatment for garden cress plants significantly increased the height at first bloom compared to the control group. For rates of surviving plants, the treatments had little effect on garden cress, but the Eggshell Grounds, Wick System, and DWC system groups outperformed the control group for marigolds.

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The Effect of the Stomatal Index on the Net Rate of Photosynthesis in the Leaves of Spinacia oleracea, Vinca minor, Rhododendron spp, Epipremnum aureum, and Hedera spp

Segev et al. | Nov 15, 2015

The Effect of the Stomatal Index on the Net Rate of Photosynthesis in the Leaves of <i>Spinacia oleracea</i>, <i>Vinca minor</i>, <i>Rhododendron spp</i>, <i>Epipremnum aureum</i>, and <i>Hedera spp</i>

The density of stomata, or stomatal index, in plant leaves is correlated with the plant's rate of photosynthesis, and affected by the plant's climate. In this paper, authors measure the stomatal index of five plant species to derive their rates of photosynthesis. These results could help track changes in plants' photosynthetic rates with changing climate.

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Ramifications of natural and artificial sweeteners on the gastrointestinal system

Cowen et al. | Jun 19, 2023

Ramifications of natural and artificial sweeteners on the gastrointestinal system

This study aimed to determine whether artificial sweeteners are harmful to the human microbiome by investigating two different bacteria found to be advantageous to the human gut, Escherichia coli and Bacillus coagulans. Results showed dramatic reduction in bacterial growth for agar plates containing two artificial sweeteners in comparison to two natural sweeteners. This led to the conclusion that both artificial sweeteners inhibit the growth of the two bacteria and warrants further study to determine if zero-sugar sweeteners may be worse for the human gut than natural sugar itself.

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Isolation of Microbes From Common Household Surfaces

Gajanan et al. | Jan 27, 2013

Isolation of Microbes From Common Household Surfaces

Microorganisms such as bacteria and fungi live everywhere in the world around us. The authors here demonstrate that these predominantly harmless microbes can be isolated from many household locations that appear "clean." Further, they test the cleaning power of 70% ethanol and suggest that many "clean" surfaces are not in fact "sterile."

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Pichia kudriavzevii Yeast Exposure Increases the Asthmatic Behavior of Alveolar Epithelial Cells In Vitro

Ortega et al. | Jun 07, 2019

<em>Pichia kudriavzevii</em> Yeast Exposure Increases the Asthmatic Behavior of Alveolar Epithelial Cells <em>In Vitro</em>

Asthma affects over 334 million people worldwide and is triggered by inhalation of environmental stimuli. The authors of this study characterized the effect of exposure to common spoilage yeast, Pichia kidriavzevii on alveolar epithelial cells. A direct correlation between infection duration and asthmatic status of these cells was found, indicating the potential for this yeast to be an environmental stimulus of asthma and warranting further study.

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Machine Learning Algorithm Using Logistic Regression and an Artificial Neural Network (ANN) for Early Stage Detection of Parkinson’s Disease

Kar et al. | Oct 10, 2020

Machine Learning Algorithm Using Logistic Regression and an Artificial Neural Network (ANN) for Early Stage Detection of Parkinson’s Disease

Despite the prevalence of PD, diagnosing PD is expensive, requires specialized testing, and is often inaccurate. Moreover, diagnosis is often made late in the disease course when treatments are less effective. Using existing voice data from patients with PD and healthy controls, the authors created and trained two different algorithms: one using logistic regression and another employing an artificial neural network (ANN).

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