Background The prognosis of recurrent low-grade endometrial stromal sarcoma (LGESS) is little known. This study was to investigate the survival outcomes of a cohort of patients with recurrent LGESS. Methods Patients with primary LGESS diagnosed and treated for first recurrence confirmed by histology in the study center from February 2012 to June 2019 were retrospectively included. The progression-free interval (PFI) after the last treatment for first recurrence and overall survival (OS) since the diagnosis of first recurrence, which were followed up to June 1, 2020, were compared between groups of various therapy modalities. Results Fifty-six patients were included, and 43 patients (76.8%) had definite follow-up outcomes. The 5-year PFI and OS rates were 30.0% (95% confidence interval [95% CI] 29.2–30.8) and 75.0% (68.0–82.0), respectively. In univariate analysis, only fertility-sparing treatment, ovarian preservation and surgical treatment had a significant impact on the PFI (hazard ratio [HR] 4.5, 3.1, and 0.2; 95% CI 1.5–13.1, 1.3–7.3, and 0.1–0.7; and p = 0.006, 0.009 and 0.006, respectively), but no factor was found to be associated with increased mortality risk. After adjusted with hormone treatment or chemotherapy, surgical treatment had significant effectiveness on OS (HR 0.3 and 0.3, 95% CI 0.1–1.0 and 0.1–1.0, p = 0.045 and 0.049, respectively). None of the patients with fertility-sparing treatment had successful conception, and all experienced repeated relapse. Conclusion For patients with recurrent LGESS, fertility-sparing treatment or ovarian preservation should not be provided. Surgery is the treatment of choice, and hormone treatment and/or chemotherapy was effective for the survival benefits of surgical treatment.

The oracle bone character (OBC) from ancient China is the most famous ancient writing systems around the world. Identifying and deciphering OBCs is one of the most important topics in oracle bone study. In research, one of the challenges is that the literature review usually leads to a huge cost of time and manpower. Therefore, the digitazation of OBC literature through the automatic recognition is the inevitable trend of future development. However, the OBCs in the literature are usually writing characters while the database of handwriting OBC has not yet been presented. In this paper, we establish a handwriting oracle bone character database called HWOBC, containing 83,245 character-level samples which are grouped into 3881-character categories. We also present the performance of several baseline DCNN-based methods, in which Melnyk-Net exhibits the best accuracy of 97.64%. It is anticipated that the publication of this database will facilitate the development of OBC research.