The authors explore how diversity in data sets contributes to bias in artificial intelligence.
Read More...Addressing and Resolving Biases in Artificial Intelligence
The authors explore how diversity in data sets contributes to bias in artificial intelligence.
Read More...Computational analysis and drug repositioning: Targeting the TDP-43 RRM using FDA-approved drugs
Molecules which bind to proteins that aggregate abnormally in neurodegenerative diseases could be promising drugs for these diseases. In this study, Zhang, Wu, Zhang, and Dang simulate the binding behavior of various molecules to screen for candidates which could be promising candidates for drug development.
Read More...Indole-3 carbinol on lipid accumulation in Caenorhabditis elegans as a novel therapeutic for Type II Diabetes
In this study the authors look at the use of Indole 3 Carbinol as a treatment for Type II Diabetes finding that it may be an effective treatment.
Read More...siRNA-dependent KCNMB2 silencing inhibits lung cancer cell proliferation and promotes cell death
Here, seeking to better understand the genetic associations underlying non-small cell lung cancer, the authors screened hundreds of genes, identifying that KCNMB2 upregulation was significantly correlated with poor prognoses in lung cancer patients. Based on this, they used small interfering RNA to decrease the expression of KCNMB2 in A549 lung cancer cells, finding decreased cell proliferation and increased lung cancer cell death. They suggest this could lead to a new potential target for lung cancer therapies.
Read More...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.
Read More...Understanding the movement of professional and high school soccer players
In this article, the authors use datasets of professional and youth soccer players' movements to map and statistically compare them. Analysis compared movements that led to goals or no-goals and differences between pros and youth.
Read More...A Statistical Comparison of the Simultaneous Attack/ Persistent Pursuit Theory Against Current Methods in Counterterrorism Using a Stochastic Model
Though current strategies in counterterrorism are somewhat effective, the Simultaneous Attack/Persistent Pursuit (SAPP) Theory may be superior alternative to current methods. The authors simulated five attack strategies (1 SAPP and 4 non-SAPP), and concluded that the SAPP model was significantly more effective in reducing the final number of terrorist attacks. This demonstrates the comparative advantage of utilizing the SAPP model, which may prove to be critical in future efforts in counterterrorism.
Read More...Rethinking the electric vehicle tax policy: prioritizing affordable solutions for environmental impact
Car emissions harm both the environment and human health, and current U.S. EV tax credits mainly benefit high-income households because EVs are expensive. This study evaluates U.S. vehicle emissions policies by analyzing 2022 national vehicle data to compare the fuel economy and greenhouse gas impacts of the current EV tax credit with a proposed policy that incentivizes hybrid vehicle purchases.
Read More...Recombinant preparation and characterization of ADH1C and ALDH2 in alcohol metabolism
The authors test the activity of two purified human alcohol detoxification enzymes, alcohol dehydrogenase and aldehyde dehydrogenase.
Read More...Evaluating the clinical applicability of neural networks for meningioma tumor segmentation on 3D MRI
Authors emphasize the challenges of manual tumor segmentation and the potential of deep learning models to enhance accuracy by automatically analyzing MRI scans.
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