Human HKU1-reactive CD4 T cells are enriched for cytolytic potential that persists in older adults.

The emergence of SARS-CoV-2 increased interest in cellular immunity established by infections with human coronaviruses (HCoVs). Using PBMC from a cohort of human subjects collected prior to 2019, we assessed the abundance and phenotype of these CD4 T cells using cytokine Elispot assays. Unexpectedly, cytotoxic potential was uniquely enriched amongst HKU1-reactive CD4 T cells, as measured by quantification of granzyme producing cells.

Unilateral Versus Bilateral Endoscopic Resection of Olfactory Neuroblastoma: Pooled Analysis From Prospective and Retrospective Multicenter Data.

Background: Olfactory neuroblastoma (ONB) is a rare sinonasal malignancy primarily treated with surgery. For tumors arising from the olfactory area, traditional treatment involves transcribriform resection of the anterior cranial fossa. Surgery can be performed with unilateral or bilateral resection depending on extent of involvement; however, there are currently no studies comparing outcomes between the two.

Comparing Efficacy of Steroid Irrigation + Steroid-eluting Sinus Stent Versus Steroid Irrigation Alone for Maintaining Frontal Sinus Patency After Sinus Surgery: A Randomized Controlled Trial.

Background: Steroid rinses and steroid-eluting stents are both options for preventing postoperative stenosis after frontal sinus surgery. This study aimed to assess whether steroid-eluting stents offer added benefit over steroid rinses alone in postoperative healing and long-term frontal sinus patency.

Methods: A randomized controlled trial enrolled patients with CRS with nasal polyps (CRSwNP) who underwent surgery for bilateral and equal frontal sinusitis after failing prior medical therapy.

Utilization of ChatGPT for Rhinology Patient Education: Limitations in a Surgical Sub-Specialty.

Objective: To analyze the accuracy of ChatGPT-generated responses to common rhinologic patient questions.

Methods: Ten common questions from rhinology patients were compiled by a panel of 4 rhinology fellowship-trained surgeons based on clinical patient experience. This panel (Panel 1) developed consensus "expert" responses to each question.

Machine learning of endoscopy images to identify, classify, and segment sinonasal masses.

Background: We developed and assessed the performance of a machine learning model (MLM) to identify, classify, and segment sinonasal masses based on endoscopic appearance.

Methods: A convolutional neural network-based model was constructed from nasal endoscopy images from patients evaluated at an otolaryngology center between 2013 and 2024. Images were classified into four groups: normal endoscopy, nasal polyps, benign, and malignant tumors.