Leveraging Artificial Intelligence as a Safety Net for Incidentally Identified Lung Nodules at a Tertiary Center.

Background: Artificial intelligence (AI)-powered platforms may be used to ensure that clinically significant lung nodules receive appropriate management. We studied the impact of a commercially available AI natural language processing tool on detection of clinically significant indeterminate pulmonary nodules (IPNs) based on radiology reports and provision of guideline-consistent care.

Study Design: All computed tomography (CT) scans performed at a single tertiary care center in the outpatient or emergency room setting between 20-Feb-2024 and 20-March-2024 were processed by the AI natural language processing algorithm.

Transcriptomics profiling of the non-small cell lung cancer microenvironment across disease stages reveals dual immune cell-type behaviors.

Background: Lung cancer is the leading cause of cancer death worldwide, with poor survival despite recent therapeutic advances. A better understanding of the complexity of the tumor microenvironment is needed to improve patients' outcome.

Methods: We applied a computational immunology approach (involving immune cell proportion estimation by deconvolution, transcription factor activity inference, pathways and immune scores estimations) in order to characterize bulk transcriptomics of 62 primary lung adenocarcinoma (LUAD) samples from patients across disease stages.

Keeping Up With Technological Innovation: The Moral Imperative for Pragmatic Clinical Trials in Interventional Pulmonology.

The advances in minimally invasive lung cancer diagnostics of the last decade have transformed patient care but have also raised important concerns about the regulatory processes used to approve new devices and the best way to generate data to support their use. Disruptive technologies, such as robotic bronchoscopy, have been widely adopted by interventional pulmonologists in the absence of robust data demonstrating improved patient outcomes. Comparative research is needed to inform patient care, but traditional methods of conducting clinical trials in which research teams operate separately from clinical teams are ill-suited to testing the safety and effectiveness of technologies being introduced on the market at unprecedented speed.

Sensory artificial cilia for in situ monitoring of airway physiological properties.

Continuously monitoring human airway conditions is crucial for timely interventions, especially when airway stents are implanted to alleviate central airway obstruction in lung cancer and other diseases. Mucus conditions, in particular, are important biomarkers for indicating inflammation and stent patency but remain challenging to monitor. Current methods, reliant on computational tomography imaging and bronchoscope inspection, pose risks due to radiation and lack the ability to provide continuous real-time feedback outside of hospitals.

Building Resilience in Medical Students: "Strengthening You to Strengthen Them".

Medical students, like many health professional students, are at risk for burnout and other negative well-being outcomes. Research suggests that building resilience may help to mitigate these risks. A multi-disciplinary team developed, delivered, and evaluated a training on building resilience for medical students entitled, "Resilience for Health Providers - Strengthening You to Strengthen Them.