Electron microscopic observation of fine structural changes of Sertoli cells in the male sterility patients was made on 10 histologically proved cases. They were histologically classified to 3 groups by Nelson's classification, hypospermatogenesis, spermatogenic arrest and germinal cell aplasia. The results obtained were summarized as follows. l) The findings of ultrastructures of Sertoli cells in the normal man showed no significant differences with other author's results. 2) The ultrastructures of Sertoli cells in the male sterility revealed degenerative changes, characterized by fragmentation and dilatation of subsurface cisternae, swelling and vacuolization of mitochondria with decrease in the number of cristae and poor development of Golgi apparatus. And also observed were proliferative changes, characterized by increase in the number of sER, rER and ribosome. These morphological changes were severer in spermatogenic arrest and the severest in germinal cell aplasia. 3) The results were suggested that the most significant ultrastructural changes of Sertoli cells of male sterility were the degenerative changes of the organelles of protein synthesis and protein transport system such as rER, ribosome and Golgi apparatus.
Classification ; Dilatation ; Golgi Apparatus ; Humans* ; Infertility ; Infertility, Male* ; Male ; Male* ; Mitochondria ; Oligospermia ; Organelles ; Protein Transport ; Ribosomes ; Sertoli Cell-Only Syndrome ; Sertoli Cells*

This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first hackathon of Genomics & Informatics Annotation Hackathon (GIAH) event. Extracting text from multi-column biomedical documents such as Genomics & Informatics is known to be notoriously difficult. The hackathon was piloted as part of a coding competition of the ELTEC College of Engineering at Ewha Womans University in order to enable researchers and students to create or annotate their own versions of the Genomics & Informatics corpus, to gain and create knowledge about corpus linguistics, and simultaneously to acquire tangible and transferable skills. The proposed projects during the hackathon harness an internal database containing different versions of the corpus and annotations.

This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first hackathon of Genomics & Informatics Annotation Hackathon (GIAH) event. Extracting text from multi-column biomedical documents such as Genomics & Informatics is known to be notoriously difficult. The hackathon was piloted as part of a coding competition of the ELTEC College of Engineering at Ewha Womans University in order to enable researchers and students to create or annotate their own versions of the Genomics & Informatics corpus, to gain and create knowledge about corpus linguistics, and simultaneously to acquire tangible and transferable skills. The proposed projects during the hackathon harness an internal database containing different versions of the corpus and annotations.