The quality of tracheal intubation contributes to laryngeal morbidity, and excellent conditions are less frequently associated with postoperative hoarseness and vocal cord sequelae. Adding atracurium to a propofol-fentanyl induction regimen significantly improved the quality of tracheal intubation and decreased postoperative hoarseness and vocal cord sequelae.

Large bioacoustic archives of wild animals are an important source to identify reappearing communication patterns, which can then be related to recurring behavioral patterns to advance the current understanding of intra-specific communication of non-human animals. A main challenge remains that most large-scale bioacoustic archives contain only a small percentage of animal vocalizations and a large amount of environmental noise, which makes it extremely difficult to manually retrieve sufficient vocalizations for further analysis – particularly important for species with advanced social systems and complex vocalizations. In this study deep neural networks were trained on 11,509 killer whale ( Orcinus orca ) signals and 34,848 noise segments. The resulting toolkit ORCA-SPOT was tested on a large-scale bioacoustic repository – the Orchive – comprising roughly 19,000 hours of killer whale underwater recordings. An automated segmentation of the entire Orchive recordings (about 2.2 years) took approximately 8 days. It achieved a time-based precision or positive-predictive-value (PPV) of 93.2% and an area-under-the-curve (AUC) of 0.9523. This approach enables an automated annotation procedure of large bioacoustics databases to extract killer whale sounds, which are essential for subsequent identification of significant communication patterns. The code will be publicly available in October 2019 to support the application of deep learning to bioaoucstic research. ORCA-SPOT can be adapted to other animal species.

In 147 cases of mammary carcinoma, 388 serial mammographies were performed before final treatment. The average retrospective observation time was 27 months with a range of two months to 11 years. The number of serial mammographies per case ranged between two and 11. The tumor volume doubling times (TV); obtained by measuring the growth of the tumor nucleus shadow in the mammographies, ranged from 44 to 1869 days with an average of 212 days. No correlation between volume doubling time and histologic differentiation could be found. One hundred of these cancer patients were found in a screening population of 22,000 women receiving serial mammographies in a time period ranging from two to 16 years. An additional 40 cancer patients surfaced in this group without roentgenologic but with foregoing clinical or thermographic abnormalities before final diagnosis. An additional 21 cancer patients surfaced without any foregoing abnormalities. The follow-up tumor ranged between three months and two years with a mean time of one year and nine months. Not considering tumor size, pathologic-thermographic signs appeared with greater frequency the faster the tumor grew. Theoretically, an average of more than 16 years should elapse before an initial tumor cell develops into a 10-mm primary mammary carcinoma (30 doubling times). Therefore the length of time necessary for a 2-mm tumor to grow to a size of 10-mm is, on the average, four years.