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Creating a Phenology Trail Around Central Park Pond

Flynn et al. | Jul 16, 2020

Creating a Phenology Trail Around Central Park Pond

This study aimed to determine whether the life cycle stages, or phenophases, of some plants in the urban environment of Central Park, New York, differ from the typical phenophases of the same plant species. The authors hypothesized that the phenophases of the thirteen plants we studied would differ from their typical phenophases due to the urban heat island effect. Although the phenophases of five plants matched up with typical trends, there were distinct changes in the phenophases of the other eight, possibly resulting from the urban heat island effect.

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The presence of Wolbachia in Brood X cicadas

Hasan et al. | Oct 15, 2022

The presence of <em>Wolbachia</em> in Brood X cicadas

Here, seeking to understand a possible cause of the declining popluations of Brood X cicadas in Ohio and Indiana, the authors investigated the presence of Wolbachia, an inherited bacterial symbiont that lives in the reproductive cells of approximately 60% of insect species in these cicadas. Following their screening of one-hundred 17-year periodical cicadas, they only identified the presence of Wolbachia infection in less than 2%, suggesting that while Wolbachia can infect cicadas it appears uncommon in the Brood X cicadas they surveyed.

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The influence of working memory on auditory category learning in the presence of visual stimuli

Vishag et al. | Sep 18, 2022

The influence of working memory on auditory category learning in the presence of visual stimuli

Here in an effort to better understand how our brains process and remember different categories of information, the authors assessed working memory capacity using an operation span task. They found that individuals with higher working memory capacity had higher overall higher task accuracy regardless of the type of category or the type of visual distractors they had to process. They suggest this may play a role in how some students may be less affected by distracting stimuli compared to others.

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Do Attractants Bias the Results of Malaise Trap Research?

Martinez et al. | Jan 22, 2020

Do Attractants Bias the Results of Malaise Trap Research?

Malaise traps are commonly used to collect flying insects for a variety of research. In this study, researchers hypothesized the attractants used in these traps may create bias in insect studies that could lead to misinterpreted data. To test this hypothesis two different kinds of attractant were used in malaise traps, and insect diversity was assessed. Attractants were found to alter the dispersion of insects caught in traps. These findings can inform future malaise traps studies on insect diversity.

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Investigating the Role of the Novel ESCRT-III Recruitment Factor CCDC11 in HIV Budding: A Potential Target for Antiviral Therapy

Takemaru et al. | Feb 24, 2020

Investigating the Role of the Novel ESCRT-III Recruitment Factor CCDC11 in HIV Budding: A Potential Target for Antiviral Therapy

Acquired immunodeficiency syndrome (AIDS) is a life-threatening condition caused by the human immunodeficiency virus (HIV). In this work, Takemaru et al explored the role of Coiled-Coil Domain-Containing 11 (CCDC11) in HIV-1 budding. Their results suggest that CCDC11 is critical for efficient HIV-1 budding, potentially indicating CCDC11 a viable target for antiviral therapeutics without major side effects.

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The Cohesiveness of the Oscillating Belousov-Zhabotinsky Reaction

Gottlieb et al. | Dec 18, 2018

The Cohesiveness of the Oscillating Belousov-Zhabotinsky Reaction

In this study the author undertakes a careful characterization of a special type of chemical reaction, called an oscillating Belousov-Zhabotinsky (or B-Z) reaction, which has a number of existing applications in biomedical engineering as well as the potential to be useful in future developments in other fields of science and engineering. Specifically, she uses experimental measurements in combination with computational analysis to investigate whether the reaction is cohesive – that is, whether the oscillations between chemical states will remain consistent or change over time as the reaction progresses. Her results indicate that the reaction is not cohesive, providing an important foundation for the development of future technologies using B-Z reactions.

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Using explainable artificial intelligence to identify patient-specific breast cancer subtypes

Suresh et al. | Jan 12, 2024

Using explainable artificial intelligence to identify patient-specific breast cancer subtypes

Breast cancer is the most common cancer in women, with approximately 300,000 diagnosed with breast cancer in 2023. It ranks second in cancer-related deaths for women, after lung cancer with nearly 50,000 deaths. Scientists have identified important genetic mutations in genes like BRCA1 and BRCA2 that lead to the development of breast cancer, but previous studies were limited as they focused on specific populations. To overcome limitations, diverse populations and powerful statistical methods like genome-wide association studies and whole-genome sequencing are needed. Explainable artificial intelligence (XAI) can be used in oncology and breast cancer research to overcome these limitations of specificity as it can analyze datasets of diagnosed patients by providing interpretable explanations for identified patterns and predictions. This project aims to achieve technological and medicinal goals by using advanced algorithms to identify breast cancer subtypes for faster diagnoses. Multiple methods were utilized to develop an efficient algorithm. We hypothesized that an XAI approach would be best as it can assign scores to genes, specifically with a 90% success rate. To test that, we ran multiple trials utilizing XAI methods through the identification of class-specific and patient-specific key genes. We found that the study demonstrated a pipeline that combines multiple XAI techniques to identify potential biomarker genes for breast cancer with a 95% success rate.

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Strain-selective in vitro and in silico structure activity relationship (SAR) of N-acyl β-lactam broad spectrum antibiotics

Poosarla et al. | Oct 19, 2021

Strain-selective <i>in vitro</i> and <i>in silico</i> structure activity relationship (SAR) of N-acyl β-lactam broad spectrum antibiotics

In this study, the authors investigate the antibacterial efficacy of penicillin G and its analogs amoxicillin, carbenicillin, piperacillin, cloxacillin, and ampicillin, against four species of bacteria. Results showed that all six penicillin-type antibiotics inhibit Staphylococcus epidermidis, Escherichia coli, and Neisseria sicca with varying degrees of efficacy but exhibited no inhibition against Bacillus cereus. Penicillin G had the greatest broad-spectrum antibacterial activity with a high radius of inhibition against S. epidermidis, E. coli, and N. sicca.

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