Neutrophil adhesion to vessel walls impairs pulmonary circulation in COVID-19 pathology.

Microthrombus formation is associated with COVID-19 severity; however, the detailed mechanism remains unclear. In this study, we investigated mouse models with severe pneumonia caused by SARS-CoV-2 infection by using our in vivo two-photon imaging system. In the lungs of SARS-CoV-2-infected mice, increased expression of adhesion molecules in intravascular neutrophils prolonged adhesion time to the vessel wall, resulting in platelet aggregation and impaired lung perfusion.

Highly pathogenic avian H5N1 influenza A virus replication in ex vivo cultures of bovine mammary gland and teat tissues.

Since early 2024, highly pathogenic avian influenza H5N1 viruses have been causing outbreaks in dairy cattle in the United States. Here, we compared the replicative capacity of A/dairy cattle/Texas/24-008749-001/2024 (H5N1; Cow-H5N1) isolated from a dairy cow, A/chicken/Ghana/AVL-76321VIR7050-39/2021 (H5N1; Chicken-H5N1) isolated from a chicken, and a human H1N1 2009 pandemic virus in ex vivo explant cultures of mammary gland and teat from lactating cows. We also examined the expression of influenza virus receptors in these organs.

Utility of Machine Learning Models to Predict Lymph Node Metastasis of Japanese Localized Prostate Cancer.

Background/objectives: Extended pelvic lymph node dissection is a crucial surgical technique for managing intermediate to high-risk prostate cancer. Accurately predicting lymph node metastasis before surgery can minimize unnecessary lymph node dissections and their associated complications. This study assessed the efficacy of various machine learning models for predicting lymph node metastasis in a cohort of Japanese patients who underwent robot-assisted laparoscopic radical prostatectomy.