Radiation Promotes Acute and Chronic Damage to Adipose Tissue.

Radiotherapy is commonly used for treating various types of cancer. In addition, adipose tissue is not routinely spared during typical radiation treatment. Although radiation is known to induce metabolic effects in patients, the effects of radiation therapy on adipose tissue have not been elucidated.

Associations of circulating insulin-like growth factor-1 and insulin-like growth factor binding protein-3 with the expression of stem cell markers in benign breast tissue.

Background: The insulin-like growth factor (IGF) pathway is implicated in a naturally occurring process of tissue remodeling during which cells acquire stem cell-like characteristics. We examined associations of circulating IGF-1 and IGF binding protein-3 (IGFBP-3) with expression of CD44, CD24, and ALDH1A1 stem cell markers in benign breast biopsies.

Methods: This study included 151 cancer-free women with incident biopsy-confirmed benign breast disease and blood samples within the Nurses' Health Study II.

Generative artificial intelligence and machine learning methods to screen social media content.

Background: Social media research is confronted by the expansive and constantly evolving nature of social media data. Hashtags and keywords are frequently used to identify content related to a specific topic, but these search strategies often result in large numbers of irrelevant results. Therefore, methods are needed to quickly screen social media content based on a specific research question.

Vaping, Acculturation, and Social Media Use Among Mexican American College Students: Protocol for a Mixed Methods Web-Based Cohort Study.

Background: The tobacco industry has a history of targeting minority communities, including Hispanic individuals, by promoting vaping through social media. This marketing increases the risk of vaping among Hispanic young adults, including college students. In Texas, college enrollment among Mexican Americans has significantly increased over recent years.

Identification and Classification of Images in e-Cigarette-Related Content on TikTok: Unsupervised Machine Learning Image Clustering Approach.

Background: Previous studies identified e-cigarette content on popular video and image-based social media platforms such as TikTok. While machine learning approaches have been increasingly used with text-based social media data, image-based analysis such as image-clustering has been rarely used on TikTok. Image clustering can identify underlying patterns and structures across large sets of images, enabling more streamlined distillation and analysis of visual data on TikTok.