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A Data-Centric Analysis of “Stop and Frisk” in New York City

Bhat et al. | Apr 18, 2021

A Data-Centric Analysis of “Stop and Frisk” in New York City

The death of George Floyd has shed light on the disproportionate level of policing affecting non-Whites in the United States of America. To explore whether non-Whites were disproportionately targetted by New York City's "Stop and Frisk" policy, the authors analyze publicly available data on the practice between 2003-2019. Their results suggest African Americans were indeed more likely to be stopped by the police until 2012, after which there was some improvement.

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Testing the Effects of Salep Derived From the Tubers of Orchis mascula, Aloe vera, and Alpha-chymotrypsin on Wound Healing in Drosophila melanogaster Larvae

Halder et al. | Sep 09, 2019

Testing the Effects of Salep Derived From the Tubers of <em>Orchis mascula</em>, <em>Aloe vera</em>, and Alpha-chymotrypsin on Wound Healing in <em>Drosophila melanogaster</em> Larvae

Aloe vera and alpha-chymotrypsin have been used in are known for their various wound healing properties. Halder et al hypothesized that these treatments would enhance wound healing in Drosophila melanogaster larvae over 2 weeks by decreasing wound size more effectively compared to controls. The results of two of the treatment groups, Salep and Aloe vera, yielded wound sizes small enough to present a significant percent decrease when compared with the wound sizes of the control group. Their results show support that both Salep and Aloe vera were effective for enhancing wound healing in epithelial cells in D. melanogaster larvae.

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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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Effect of Different Growth Media on Algae’s Ability for Carbon Dioxide Biofixation

Chaudhuri et al. | Oct 12, 2020

Effect of Different Growth Media on Algae’s Ability for Carbon Dioxide Biofixation

In this study, the authors investigate the effects of different algal growth media on algae's ability to perform carbon dioxide biofixation, or utilize carbon dioxide by fixing it into fatty acids within the cells. More specifically, carbon dioxide biofixation of Chlorella vulgaris was cultured in one of four media options and carbon dioxide was measured and compared to controls. The study results demonstrated that the use of media can enhance algae's capacity for biofixation and this has important implications for developing methods to reduce carbon dioxide in the environment.

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Effects of Ocean Acidification on the Photosynthetic Ability of Chaetoceros gracilis in the Monterey Bay

Harvell et al. | Jan 16, 2020

Effects of Ocean Acidification on the Photosynthetic Ability of <i>Chaetoceros gracilis</i> in the Monterey Bay

In this article, Harvell and Nicholson hypothesized that increased ocean acidity would decrease the photosynthetic ability of Chaetoceros gracilis, a diatom prolific in Monterey Bay, because of the usually corrosive effects of carbonic acid on both seashells and cells’ internal structures. They altered pH of algae environments and measured the photosynthetic ability of diatoms over four days by spectrophotometer. Overall, their findings indicate that C. gracilis may become more abundant in Monterey Bay as the pH of the ocean continues to drop, potentially contributing to harmful algal blooms.

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Population Forecasting by Population Growth Models based on MATLAB Simulation

Li et al. | Aug 31, 2020

Population Forecasting by Population Growth Models based on MATLAB Simulation

In this work, the authors investigate the accuracy with which two different population growth models can predict population growth over time. They apply the Malthusian law or Logistic law to US population from 1951 until 2019. To assess how closely the growth model fits actual population data, a least-squared curve fit was applied and revealed that the Logistic law of population growth resulted in smaller sum of squared residuals. These findings are important for ensuring optimal population growth models are implemented to data as population forecasting affects a country's economic and social structure.

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Developing novel plant waste-based hydrogels for skin regeneration and infection detection in diabetic wounds

Mathew et al. | Aug 10, 2023

Developing novel plant waste-based hydrogels for skin regeneration and infection detection in diabetic wounds

The purpose of this investigation is to develop a hydrogel to aid skin regeneration by creating an extracellular matrix for fibroblast growth with antibacterial and infection-detection properties. Authors developed two natural hydrogels based on pectin and potato peels and characterized the gels for fibroblast compatibility through rheology, scanning electron microscopy, swelling, degradation, and cell cytotoxicity assays. Overall, this experiment fabricated various hydrogels capable of acting as skin substitutes and counteracting infections to facilitate wound healing. Following further testing and validation, these hydrogels could help alleviate the 13-billion-dollar financial burden of foot ulcer treatment.

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High-throughput virtual screening of novel dihydropyrimidine monastrol analogs reveals robust structure-activity relationship to kinesin Eg5 binding thermodynamics

Shern et al. | Jan 20, 2021

High-throughput virtual screening of novel dihydropyrimidine monastrol analogs reveals robust structure-activity relationship to kinesin Eg5 binding thermodynamics

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.

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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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