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The Effect of Caffeine on the Regeneration of Brown Planaria (Dugesia tigrina)

Lazorik et al. | May 10, 2019

The Effect of Caffeine on the Regeneration of Brown Planaria (<em>Dugesia tigrina</em>)

The degeneration of nerve cells in the brain can lead to pathologies such as Parkinson’s disease. It has been suggested that neurons in humans may regenerate. In this study, the effect of different doses of caffeine on regeneration was explored in the planeria model. Caffeine has been shown to enhance dopamine production, and dopamine is found in high concentrations in regenerating planeria tissues. Higher doses of caffeine accelerated planeria regeneration following decapitation, indicating a potential role for caffeine as a treatment to stimulate regeneration.

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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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The Potential of Fibroblast Growth Factors to Stimulate Hair Growth In Vitro

Cheng et al. | Nov 07, 2021

The Potential of Fibroblast Growth Factors to Stimulate Hair Growth In Vitro

Identifying treatments that can stimulate hair growth use could help those struggling with undesirable hair loss. Here, the authors show that Fibroblast Growth Factors can stimulate the division of cells isolated from the mouse hair follicle. Their results suggest that this family of growth factors might be helpful in stimulating hair growth in living animals as well.

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Effects of vascular normalizing agents on immune marker expression in T cells, dendritic cells, and melanoma cells

Yaskolko et al. | Nov 03, 2021

Effects of vascular normalizing agents on immune marker expression in T cells, dendritic cells, and melanoma cells

Tertiary lymphoid structures (TLS) are lymph node-like structures that form at sites of inflammation, and their presence in cancer patients is predictive of a better clinical outcome. One significant obstacle to TLS formation is reduced immune cell infiltration into the tumor microenvironment (TME). Recent studies have shown that vasculature normalizing (VN) agents may override this defect to improve tissue perfusion and increased immune cell entry into the TME. However, their effects on immune cell and tumor cell phenotype remain understudied. Here the authors investigate whether treating tumor cells with VN would reduce their immunosuppressive phenotype and promote production of chemokine that recruit immune cells and foster TLS formation.

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Combined Progestin-Estrogenic Contraceptive Pills May Promote Growth in Crop-Plants

Saha et al. | Feb 21, 2020

Combined Progestin-Estrogenic Contraceptive Pills May Promote Growth in Crop-Plants

Ethinyl estradiol and progestin norgestrel are commonly present in contraceptive tablets and it is unknown how they affect the environment. In this study, the authors investigate the role that ethinyl estradiol and progestin norgestrel have on the growth of flowering plants. The percentage germination, embryonic and adventitious tissue proliferation, root length, and shoot length were measured in V. radiata and T. aestivum treated with each compound and results demonstrate that ethinyl estradiol and progestin norgestrel can induce growth in both plants at certain concentrations. These findings have important implications as societal use of chemicals increases and more make their way into the environment.

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Transfer Learning for Small and Different Datasets: Fine-Tuning A Pre-Trained Model Affects Performance

Gupta et al. | Oct 18, 2020

Transfer Learning for Small and Different Datasets: Fine-Tuning A Pre-Trained Model Affects Performance

In this study, the authors seek to improve a machine learning algorithm used for image classification: identifying male and female images. In addition to fine-tuning the classification model, they investigate how accuracy is affected by their changes (an important task when developing and updating algorithms). To determine accuracy, a set of images is used to train the model and then a separate set of images is used for validation. They found that the validation accuracy was close to the training accuracy. This study contributes to the expanding areas of machine learning and its applications to image identification.

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Effect of Collagen Gel Structure on Fibroblast Phenotype

Grace et al. | Nov 28, 2012

Effect of Collagen Gel Structure on Fibroblast Phenotype

Environment affects the progression of life, especially at the cellular level. This study investigates multiple 3-dimensional growth environments, also known as scaffolds or hydrogels, and their effect on the growth of a type of cells called fibroblasts. These results suggest that a scaffold made of collagen and polyethylene glycol are favorable for cell growth. This research is useful for developing implantable devices to aid wound healing.

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Comparing the Effectiveness of Popular Treatments for Swelling and Scarring

Benavides et al. | Jul 08, 2020

Comparing the Effectiveness of Popular Treatments for Swelling and Scarring

Numerous specialty treatments claim to reduce swelling and scarring; however, it is unknown if these treatments are more effective than less expensive treatments. In an attempt to determine if one outperforms the other, treatments were applied to the same subject following bilateral orthopedic foot surgery. No difference was found the specialty treatments compared to more cost-effective treatments.

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Similarity Graph-Based Semi-supervised Methods for Multiclass Data Classification

Balaji et al. | Sep 11, 2021

Similarity Graph-Based Semi-supervised Methods for Multiclass Data Classification

The purpose of the study was to determine whether graph-based machine learning techniques, which have increased prevalence in the last few years, can accurately classify data into one of many clusters, while requiring less labeled training data and parameter tuning as opposed to traditional machine learning algorithms. The results determined that the accuracy of graph-based and traditional classification algorithms depends directly upon the number of features of each dataset, the number of classes in each dataset, and the amount of labeled training data used.

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