Supernovas are powerful explosions that result from gravitational collapse of a massive star. Using photometric analysis Arora et al. set out to investigate whether 2020pni (located in galaxy UGC 9684) was a supernova. They were ultimately able to identify 2020pni as a Type II-L supernova and determine it's distance from earth.

Recently, e-cigarette usage has been increasing rapidly. Previous research has found that adverse
childhood experiences (ACEs) are correlated to cigarette usage. However, there is limited data exploring if ACEs affect vaping. Therefore, in this work, we investigated the effects of ACEs on e-cigarette usage and hypothesize that witnessing vaping in the house and facing ACEs would increase e-cigarette usage while education on the dangers of vaping would decrease e-cigarette usage. We found that different types of ACEs had different correlations with e-cigarette usage and that education on the dangers of vaping had no effect on e-cigarette usage.

Using a convolution neural network, these authors show machine learning can clinically diagnose breast cancer with high accuracy.

Cellular senescence plays a key role in aging cells and is attributed to a number of disease and pathology. These authors find that genetic editing of both RPS6KB1 and PPARGC1A revitalizes a human skin fibroblast cell line.

Many cases of viral hepatitis are easily preventable if caught early; however, a lack of public awareness regarding often leads to diagnoses near the final stages of disease when it is most lethal. Thus, we wanted to understand to what extent an individual's sex, age, education and country of residence (India or Singapore) impacts disease identification. We sent out a survey and quiz to residents in India (n = 239) and Singapore (n = 130) with questions that test their knowledge and awareness of the disease. We hypothesized that older and more educated individuals would score higher because they are more experienced, but that the Indian population will not be as knowledgeable as the Singaporean population because they do not have as many resources, such as socioeconomic access to schools and accessibility to healthcare, available to them. Additionally, we predicted that there would not be any notable differences between make and females. The results revealed that the accuracy for all groups we looked at was primarily below 50%, demonstrating a severe knowledge gap. Therefore, we concluded that if more medical professionals discussed viral hepatitis during hospital visits and in schools, patients can avoid the end stages of the disease in notable cases.

Here, recognizing the vastly different opinion held regarding device usage, the authors considered the effects of technology use on middle and high school students' learning effectiveness. Using an anonymous online survey they found partial support that device use at school increases learning effectiveness, but found strong support for a negative effect of technology use at home on learning effectiveness. Based on their findings they suggest that the efficacy of technology depends on environmental context along with other important factors that need consideration.

Here, beginning from an initial interest in the possibility to use a computer to automatically solve a geometry diagram parser, the authors developed their own Fast Geometry Diagram Parser (FastGDP) that uses clustering and corner information. They compared their own methods to a more widely available, method, GeoSolver, finding their own to be an order of magnitude faster in most cases that they considered.

Staphylococcus aureus is a major pathogen in both hospitals and the community and can cause systemic infections such as pneumonia. Multi-drug resistant strains, such as Methicillin-resistant S. aureus (MRSA) are particularly worrisome. In order to reduce the development of bacterial resistance, we hypothesized that two selected traditional Chinese medicines, Shuang-Huang-Lian (SHL) and Lan-Qin, would be effective against S. aureus. The results showed that SHL had a synergistic effect with gentamicin as well as additive effects with penicillin and cefazolin against S. aureus compared with using antibiotics alone.

Pillai et al. look at whether exposure to Schistosoma mansoni, a parasitic blood fluke, has any relation to peanut allergies. They found that cockroaches exposed to an antigen found in S. mansoni eggs exhibited an allergic reaction to peanuts.

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.