Other Chemicals and Drugs Commons^™

Identification Of Novel Biosynthetic Gene Clusters Encoding For Polyketide/Nrps-Producing Chemotherapeutic Compounds From Marine-Derived Streptomyces Hygroscopicus From A Marine Sanctuary, Hannah Ruth Flaherty

Honors Theses and Capstones

Nearly one out of six deaths in 2020, around ten million people, were caused by cancer, making it a leading cause of death worldwide (WHO, 2022). This major public health issue, in addition to the rise of multidrug-resistant (MDR) pathogens, provides a high demand for the discovery of new pharmaceutical drugs to be used clinically to treat these conditions. The Streptomyces genus accounts to produce 39% of all microbial metabolites currently approved for human health, indicating its potential as an important species to study for antimicrobial and anticancer agents. The long linear genome of Streptomyces contains specialized sequences known as …

Prescription Opioid Misuse And Addiction: Healthcare’S Contribution To The Opioid Epidemic And What Can Be Done About It, Emily Larsen, Katrina Ecke

Nursing | Senior Theses

Up to one in four patients undergoing prolonged opioid therapy in a primary care setting battle opioid addiction. In 2020, the CDC found that more than 16,000 deaths involving prescription opioids (limited to natural and semi-synthetic opioids and methadone) had occurred, which is equivalent to about 45 deaths per day. Opioid overdose death can be identified through three distinct waves; increased prescribing of opioids in the 1990’s began the first wave, the beginning of the second wave came in 2010 with a rapid increase in heroin related overdose deaths, and in 2013 the third wave began with a significant increase …

Nicotine And E-Cigarette Effect On Maximal Metabolic Rate (Mmr) In Procambarus Clarkii, Nathan Cuttica

Williams Honors College, Honors Research Projects

The use of electronic cigarettes, commonly referred to as e-cigarettes or vapes, has increased exponentially in recent years despite the lack of research into potentially negative physiological effects. The rise in e-cigarette use is likely due to the overwhelming evidence regarding the addictive properties of nicotine and the damage caused by traditional tobacco cigarettes. Most e-cigarettes, however, still contain nicotine and are associated with a rise in nicotine-related intoxications (Belkoniene et al., 2019). There are nicotine-free e-cigarette options, which are gaining popularity, but it is unknown if they carry similar or other negative physiological effects. Studies involving e-cigarettes containing nicotine …

Electronic Cigarettes And Young Adults: Use Of Screening Tools And Provider Knowledge, Kayla Erin Chelf

DNP Projects

Background: Electronic Cigarette (e-cigarette) use is now more common than traditional cigarette use in adolescents and young adults (Dinardo & Rome, 2019). There is concern that the lack of screening for use and knowledge about the health consequences of e-cigarette use is driving this growth.

Objective: The purposes of this project were to (1) assess baseline e-cigarette knowledge and screening practices from healthcare professionals, and (2) evaluate changes in knowledge after delivery of an educational intervention about e-cigarettes.

Methods: In this quasi-experimental study a seven-question survey on screening practice and knowledge concerning e-cigarettes in young adults was posted on the …

Msdrp: A Deep Learning Model Based On Multisource Data For Predicting Drug Response, Haochen Zhao, Xiaoyu Zhang, Qichang Zhao, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Motivation: Cancer heterogeneity drastically affects cancer therapeutic outcomes. Predicting drug response in vitro is expected to help formulate personalized therapy regimens. In recent years, several computational models based on machine learning and deep learning have been proposed to predict drug response in vitro. However, most of these methods capture drug features based on a single drug description (e.g. drug structure), without considering the relationships between drugs and biological entities (e.g. target, diseases, and side effects). Moreover, most of these methods collect features separately for drugs and cell lines but fail to consider the pairwise interactions between drugs and cell …