Cell segmentation is the task of identifying cell nuclei instances in fluorescence microscopy images. The goal of this paper is to benchmark the performance of representative deep learning techniques for cell nuclei segmentation using standard datasets and common evaluation criteria. This research establishes an important baseline for cell nuclei segmentation, enabling researchers to continually refine and deploy neural models for real-world clinical applications.
Every year, around 40% of undergraduate students in the United States discontinue their studies, resulting in a loss of valuable education for students and a loss of money for colleges. Even so, colleges across the nation struggle to discover the underlying causes of these high dropout rates. In this paper, the authors discuss the use of machine learning to find correlations between the built environment factors and the retention rates of colleges. They hypothesized that one way for colleges to improve their retention rates could be to improve the physical characteristics of their campus to be more pleasing. The authors used image classification techniques to look at images of colleges and correlate certain features like colors, cars, and people to higher or lower retention rates. With three possible options of high, medium, and low retention rates, the probability that their models reached the right conclusion if they simply chose randomly was 33%. After finding that this 33%, or 0.33 mark, always fell outside of the 99% confidence intervals built around their models’ accuracies, the authors concluded that their machine learning techniques can be used to find correlations between certain environmental factors and retention rates.
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.
Here, seeking to identify an optimal method to classify tree species through remote sensing, the authors used a few machine learning algorithms to classify forest tree species through multispectral satellite imagery. They found the Random Forest algorithm to most accurately classify tree species, with the potential to improve model training and inference based on the inclusion of other tree properties.
While some believe that ride-hailing services offer reduced CO2 emissions compared to individual driving, studies have found that driving without passengers on ride-hailing trips or "deadheading" prevents this. Here, with a mathematical model, the authors investigated if the use of electric vehicles as ride-hailing vehicles could offer reduced CO2 emissions. They found that the improved vehicle efficiency and cleaner generation could in fact lower emissions compared to the use of personal gas vehicles.
As cancer continues to take millions of lives worldwide, the need to create effective therapeutics for the disease persists. The kinesin Eg5 assembly motor protein is a promising target for cancer therapeutics as inhibition of this protein leads to cell cycle arrest. Monastrol, a small dihydropyrimidine-based molecule capable of inhibiting the kinesin Eg5 function, has attracted the attention of medicinal chemists with its potency, affinity, and specificity to the highly targeted loop5/α2/α3 allosteric binding pocket. In this work, we employed high-throughput virtual screening (HTVS) to identify potential small molecule Eg5 inhibitors from a designed set of novel dihydropyrimidine analogs structurally similar to monastrol.
According to the World Health Organization, cancer is a leading cause of death globally. The disease’s prevalence is rapidly increasing in association with factors including the increased use of pesticides and herbicides, such as glyphosate, which is one of the most widely used herbicide ingredients. Natural antioxidants and phytochemicals are being tested as anti-cancer agents due to their antiproliferative, antioxidative, and pro-apoptotic properties. Thus, we aimed to investigate the potential role of S. amara extract as a therapeutic agent against glyphosate-induced toxicity and tumor-like morphologies in regenerating and homeostatic planaria (Dugesia dorotocephala).
Alcohol use disorder is a chronic, relapsing disease that affects millions of Americans every day. There are limited treatment options for alcohol dependence and alcohol withdrawal symptoms, including depression and anxiety. Previous studies have shown that probiotics can decrease depression in rodents during maternal separation and anxiety in humans. Therefore, we hypothesized that the ethanol-withdrawn planaria who consumed probiotics would have decreased withdrawal symptoms as measured by increased motility compared to the ethanol-withdrawn planaria that were not fed probiotics. The ethanol-withdrawn planaria had a statistically significant decrease in motility compared to the control group, while the planaria that consumed probiotics had no statistically significant change in motility compared to the control group.
Ultraviolet (UV) radiation is known to alter DNA structure and impair cellular function in all living organisms. In this study, Lateef et al examine the effects of UV radiation to determine whether antioxidant-enriched nutrition can combat the potential deleterious effects of UV radiation on Drosophila melanogaster. They found that UVB (320nm) radiation caused a 59% decrease in the Drosophila lifespan and mutagenic effects on flies' physical appearance, but did not significantly affect fertility. Curcumin significantly prolonged lifespan and enhanced fertility for both UV- and non-UV-exposed flies. The research demonstrates the positive potential of natural antioxidants as weapons against radiation-induced diseases including cancer.
This study uses a fruit fly model of type 1 diabetes (T1D) to determine whether strengthening intestinal tight junctions to reduce intestinal permeability would improve T1D symptoms.