Patient- and clinician-based evaluation of large language models for patient education in prostate cancer radiotherapy.

Background: This study aims to evaluate the capabilities and limitations of large language models (LLMs) for providing patient education for men undergoing radiotherapy for localized prostate cancer, incorporating assessments from both clinicians and patients.

Methods: Six questions about definitive radiotherapy for prostate cancer were designed based on common patient inquiries. These questions were presented to different LLMs [ChatGPT‑4, ChatGPT-4o (both OpenAI Inc.

Optimal Setup and Parameters of Diffusion-Weighted Magnetic Resonance Imaging for Translational Evaluation of a Tumor Progression Model for Soft Tissue Sarcomas.

Purpose: Defining a microscopic tumor infiltration boundary is critical to the success of radiation therapy. Currently, radiation oncologists use margins to geometrically expand the visible tumor for radiation treatment planning in soft tissue sarcomas (STS). Image-based models of tumor progression would be critical to personalize the treatment radiation field to the pattern of sarcoma spread.

Engraft: A Collaborative Learning Health Network for Enhanced Transplant and Cellular Therapy Outcomes.

The Engraft Learning Health Network (LHN) aims to improve outcomes for patients undergoing transplant and cellular therapy (TCT) through a collaborative, data-driven approach. Engraft brings together diverse stakeholders, including clinicians, patients, caregivers, and institutions, to standardize best practices and accelerate the dissemination of innovations in TCT care. By establishing a multicenter, real-world clinical registry focused on rapid-cycle quality improvement (QI) and implementation research, Engraft seeks to reduce variability in clinical practice to improve TCT outcomes across centers.

Target trial emulation to evaluate the effect of immune-related adverse events on outcomes in metastatic urothelial cancer.

Background: Immune checkpoint inhibitors (ICIs) are an important therapeutic pillar in metastatic urothelial carcinoma (mUC). The occurrence of immune-related adverse events (irAEs) appears to be associated with improved outcomes in observational studies. However, these associations are likely affected by immortal time bias and do not represent causal effects.

Ultrathin BIC Metasurfaces Based on Ultra-Low-Loss SbSe Phase-Change Material.

Ultrathin and low-loss phase-change materials (PCMs) are highly valued for their fast and effective phase transitions and applications in reconfigurable photonic chips, metasurfaces, optical modulators, sensors, photonic memories, and neuromorphic computing. However, conventional PCMs mostly suffer from high intrinsic losses in the near-infrared (NIR) region, limiting their potential for high quality factor (-factor) resonant metasurfaces. Here we present the design and fabrication of tunable bound states in the continuum (BIC) metasurfaces using the ultra-low-loss PCM SbSe.