Validation of prostate and breast cancer detection artificial intelligence algorithms for accurate histopathological diagnosis and grading: a retrospective study with a Japanese cohort.

Prostate and breast cancer incidence rates have been on the rise in Japan, emphasising the need for precise histopathological diagnosis to determine patient prognosis and guide treatment decisions. However, existing diagnostic methods face numerous challenges and are susceptible to inconsistencies between observers. To tackle these issues, artificial intelligence (AI) algorithms have been developed to aid in the diagnosis of prostate and breast cancer. This study focuses on validating the performance of two such algorithms, Galen Prostate and Galen Breast, in a Japanese cohort, with a particular focus on the grading accuracy and the ability to differentiate between invasive and non-invasive tumours. The research entailed a retrospective examination of 100 consecutive prostate and 100 consecutive breast biopsy cases obtained from a Japanese institution. Our findings demonstrated that the AI algorithms showed accurate cancer detection, with AUCs of 0.969 and 0.997 for the Galen Prostate and Galen Breast, respectively. The Galen Prostate was able to detect a higher Gleason score in four adenocarcinoma cases and detect a previously unreported cancer. The two algorithms successfully identified relevant pathological features, such as perineural invasions and lymphovascular invasions. Although further improvements are required to accurately differentiate rare cancer subtypes, these findings highlight the potential of these algorithms to enhance the precision and efficiency of prostate and breast cancer diagnosis in Japan. Furthermore, this validation paves the way for broader adoption of these algorithms as decision support tools within the Asian population.

The Escherichia coli translation-associated heat shock protein YbeY is involved in rRNA transcription antitermination.

A new group of translation-associated heat shock genes has been recently identified. One of these novel genes is ybeY which is highly conserved in bacteria. In Escherichia coli the YbeY protein is important for efficient translation at all temperatures and is essential at high temperatures. Deletion mutants of ybeY are defective in protein translation, due to impaired 30 S ribosomal subunits. Here we provide evidence which tie YbeY to the transcription antitermination process. Thus, in ybeY deletion mutants transcription is significantly inhibited when the "nut like" sequences required for transcriptional antitermination are present, while if these sequences are removed transcription is not affected by the mutation.