Composition of the fecal, vaginal and colostrum microbiotas of dams at parturition and their relationship with neonatal outcomes in dogs.

Background: Microbial seeding in early life is critical for the host's short- and long-term health, and the mother is the first source of bacteria for the newborn. The objective of this study was to characterize the maternal fecal, vaginal, and colostral microbiotas in the canine species one day after parturition and to evaluate the relationship between the microbial profiles of 36 dams and the neonatal outcomes of 284 newborns.

Results: The first part of the study revealed the presence of 2 fecal, 3 vaginal, and 2 colostral microbial clusters on the basis of the core microbiota of the dams.

A machine learning approach for the rapid identification of measurable residual disease in acute myeloid leukemia.

Not available.

Deep-learning-ready RGB-depth images of seedling development.

In the era of machine learning-driven plant imaging, the production of annotated datasets is a very important contribution. In this data paper, a unique annotated dataset of seedling emergence kinetics is proposed. It is composed of almost 70,000 RGB-depth frames and more than 700,000 plant annotations.

Development and Validation of a Synoptic Operative Report as a Quality Indicator for Thyroid Surgery: A Canadian Study.

Background: Narrative operative reports (NORs) often lack key information that can guide postoperative management of thyroid disease. We aimed to develop and validate a nationally standardized synoptic operative report (SOR) for thyroid surgery.

Materials And Methods: Surgeons were surveyed for their opinions of current operative reporting practices.