A method for the automated classification of benign and malignant masses on digital breast tomosynthesis images using machine learning and radiomic features.

In digital mammography, which is used for the early detection of breast tumors, oversight may occur due to overlap between normal tissues and lesions. However, since digital breast tomosynthesis can acquire three-dimensional images, tissue overlapping is reduced, and, therefore, the shape and distribution of the lesions can be easily identified. However, it is often difficult to distinguish between benign and malignant breast lesions on images, and the diagnostic accuracy can be reduced due to complications from radiological interpretations, owing to acquisition of a higher number of images.

Physical performance reflects cognitive function, fall risk, and quality of life in community-dwelling older people.

This report searched for relationships between physical performance and other health indices through a detailed investigation of a randomly sampled cohort from a basic town resident registry. Residents between the age of 50 and 89 years were randomly sampled from the basic resident registry of a cooperating town for construction of a 415-participant cohort that minimized selection bias. Cognitive function measures, annual fall frequency, and SF-8 as an HRQOL measure were the outcomes of interest.

Cell‑to‑cell communication via extracellular vesicles among human pancreatic cancer cells derived from the same patient.

Despite existing multimodal therapies, pancreatic cancer exhibits high metastatic capability and poor prognosis. Extracellular vesicles (EVs) are nanoparticles comprising lipid bilayers and various other components, such as protein and nucleic acids, derived from secreted cells. Recent research has demonstrated the involvement of EVs released from cancer cells in the metastasis of cancer cells to distant organs.