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FadA antigen of Fusobacterium nucleatum: implications for ceRNA network in colorectal cancer and adenomatous polyps progression.
Discov Oncol
January 2025
Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Introduction: Colorectal cancer (CRC) is the second most common cause of cancer-related deaths globally. The gut microbiota, along with adenomatous polyps (AP), has emerged as a plausible contributor to CRC progression. This study aimed to scrutinize the impact of the FadA antigen derived from Fusobacterium nucleatum on the expression levels of the ANXA2 ceRNA network and assess its relevance to CRC advancement.
View Article and Find Full Text PDFA contentious intervention to support the medical workforce: a case study of the policy of introducing physician associates in the United Kingdom.
Hum Resour Health
January 2025
Wolfson Institute of Population Health, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
Background: Health systems across Europe are facing a workforce crisis, with some experiencing severe shortages of doctors. In response, many are exploring greater task-sharing, across established professions, such as doctors, nurses, and pharmacists, with patients and carers, and with new occupational groups, in particular ones that can assist doctors and relieve their workload.
Case Presentation: In the early 2000s the United Kingdom created a new occupational role, that of physician assistant.
Spatial-Structural Mechanisms of Racialized Disparities in Overdose Mortality: A Spatiotemporal Analysis.
J Racial Ethn Health Disparities
January 2025
Department of Pharmacology & Toxicology, Medical College of Wisconsin, Milwaukee, WI, USA.
Efforts to understand and respond to the opioid crisis have focused on overdose fatalities. Overdose mortality rates (ratios of overdoses resulting in death) are rarely examined though they are important indicators of harm reduction effectiveness. Factors that vary across urban communities likely determine which community members are receiving the resources needed to reduce fatal overdose risk.
View Article and Find Full Text PDFArtificial Intelligence Scribe and Large Language Model Technology in Healthcare Documentation: Advantages, Limitations, and Recommendations.
Plast Reconstr Surg Glob Open
January 2025
Department of Computer Science, Johns Hopkins University, Baltimore, MD.
Artificial intelligence (AI) scribe applications in the healthcare community are in the early adoption phase and offer unprecedented efficiency for medical documentation. They typically use an application programming interface with a large language model (LLM), for example, generative pretrained transformer 4. They use automatic speech recognition on the physician-patient interaction, generating a full medical note for the encounter, together with a draft follow-up e-mail for the patient and, often, recommendations, all within seconds or minutes.
View Article and Find Full Text PDFAssessing the Current Limitations of Large Language Models in Advancing Health Care Education.
JMIR Form Res
January 2025
Department of Physician Assistant Studies, Massachusetts College of Pharmacy and Health Sciences, 179 Longwood Avenue, Boston, MA, 02115, United States, 1 6177322961.
The integration of large language models (LLMs), as seen with the generative pretrained transformers series, into health care education and clinical management represents a transformative potential. The practical use of current LLMs in health care sparks great anticipation for new avenues, yet its embracement also elicits considerable concerns that necessitate careful deliberation. This study aims to evaluate the application of state-of-the-art LLMs in health care education, highlighting the following shortcomings as areas requiring significant and urgent improvements: (1) threats to academic integrity, (2) dissemination of misinformation and risks of automation bias, (3) challenges with information completeness and consistency, (4) inequity of access, (5) risks of algorithmic bias, (6) exhibition of moral instability, (7) technological limitations in plugin tools, and (8) lack of regulatory oversight in addressing legal and ethical challenges.
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