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Conversion of Mesenchymal Stem Cells to Cancer-Associated Fibroblasts in a Tumor Microenvironment: An in vitro Study

Ramesh et al. | Feb 18, 2020

Conversion of Mesenchymal Stem Cells to Cancer-Associated Fibroblasts in a Tumor Microenvironment: An <em>in vitro</em> Study

Mesenchymal stem cells(MSCs) play a role in tumor formation by differentiating into cancer associated fibroblasts (CAFs) which enable metastasis of tumors. The process of conversion of MSCs into CAFs is not clear. In this study, authors tested the hypothesis that cancers cells secrete soluble factors that induce differentiation by culturing bone marrow mesenchymal stem cells in media conditioned by a breast cancer cell line.

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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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An Analysis of the Density and Patterns of the Solutions of Diophantine Equations of the Third Power

Grewal et al. | Oct 05, 2020

An Analysis of the Density and Patterns of the Solutions of Diophantine Equations of the Third Power

In this study, the authors sought to find out how many mathematical solutions there were to the Indian mathematician Ramanujan's formula, which is a3 + b3 + c3 = d3, and also quantify the densities its solutions. They wrote their own computer program to do so and kept values of a, b, and c less than 10,000. While conducting the analysis, they were also looking for perfect power taxicab numbers and their frequency. They were able to find solutions and densities for the equation. Additionally, while they found that most perfect cube taxicab numbers had a frequency of 2 or 3, they also found on number with a frequency of 42!

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Identification of a Free Radical Scavenger as an Additive for Lung Transplant Preservation Solution to Inhibit Coagulative Necrosis and Extend Organ Preservation

Ganesh et al. | Feb 12, 2015

Identification of a Free Radical Scavenger as an Additive for Lung Transplant Preservation Solution to Inhibit Coagulative Necrosis and Extend Organ Preservation

During transfer of organs from a donor to a patient, the organs deteriorate in part due to damage by free radicals. Application of antioxidant solutions could extend organ preservation times. The authors found that vitamin E and butylated hydroxytoluene seemed to be most effective in arresting cell damage of a bovine lung.

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Identifying Neural Networks that Implement a Simple Spatial Concept

Zirvi et al. | Sep 13, 2022

Identifying Neural Networks that Implement a Simple Spatial Concept

Modern artificial neural networks have been remarkably successful in various applications, from speech recognition to computer vision. However, it remains less clear whether they can implement abstract concepts, which are essential to generalization and understanding. To address this problem, the authors investigated the above vs. below task, a simple concept-based task that honeybees can solve, using a conventional neural network. They found that networks achieved 100% test accuracy when a visual target was presented below a black bar, however only 50% test accuracy when a visual target was presented below a reference shape.

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A machine learning approach for abstraction and reasoning problems without large amounts of data

Isik et al. | Jun 25, 2022

A machine learning approach for abstraction and reasoning problems without large amounts of data

While remarkable in its ability to mirror human cognition, machine learning and its associated algorithms often require extensive data to prove effective in completing tasks. However, data is not always plentiful, with unpredictable events occurring throughout our daily lives that require flexibility by artificial intelligence utilized in technology such as personal assistants and self-driving vehicles. Driven by the need for AI to complete tasks without extensive training, the researchers in this article use fluid intelligence assessments to develop an algorithm capable of generalization and abstraction. By forgoing prioritization on skill-based training, this article demonstrates the potential of focusing on a more generalized cognitive ability for artificial intelligence, proving more flexible and thus human-like in solving unique tasks than skill-focused algorithms.

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The impacts of different Al(NO3)3 concentrations on the mitotic index of Allium sativum

Jimenez Pol et al. | Jul 10, 2023

The impacts of different Al(NO<sub>3</sub>)<sub>3</sub> concentrations on the mitotic index of <i>Allium sativum</i>
Image credit: Kylie Paz

Recognizing the increasing threat of acid deposition inn soil through the reaction of NOx and SO2 pollutants with water in Spain, the authors investigates the effects of Al(NO3)3 concentrations on the health of Allium sativum. By tracking its mitotic index, they found a negative exponential correlation between Al(NO3)3 concentrations and the mitotic index of A. sativum.

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