Dr.Emb Appyter: A web platform for drug discovery using embedding vectors.

Using embedding methods, compounds with similar properties will be closely located in latent space, and these embedding vectors can be used to find other compounds with similar properties based on the distance between compounds. However, they often require computational resources and programming skills. Here we develop Dr.Emb Appyter, a user-friendly web-based chemical compound search platform for drug discovery without any technical barriers. It uses embedding vectors to identify compounds similar to a given query in the embedding space. Dr.Emb Appyter provides various types of embedding methods, such as fingerprinting, SMILES, and transcriptional response-based methods, and embeds numerous compounds using them. The Faiss-based search system efficiently finds the closest compounds of query in the library. Additionally, Dr.Emb Appyter offers information on the top compounds; visualizes the results with 3D scatter plots, heatmaps, and UpSet plots; and analyses the results using a drug-set enrichment analysis. Dr.Emb Appyter is freely available at https://dremb.korea.ac.kr.

Clinical characteristics and risk factors for septic shock in patients with pyometra: A retrospective multicenter cohort study.

BACKGROUND: Pyometra is a disease characterized by the collection of pus in the uterus. The clinical characteristics and etiology of pyometra have not been sufficiently described. In this study, we investigated the clinical characteristics, epidemiology, outcomes, and risk factors of septic shock in patients with pyometra. METHODS: Patients with pyometra admitted to one of four university-affiliated hospitals between January 2010 to August 2022 were enrolled. Pyometra cases associated with peripartum infection and surgical site infection were excluded. Clinical characteristics and outcomes of pyometra were described, and pyometra patients with or without septic shock were compared. RESULTS: A total of 192 patients was included. Twenty-eight-day all-cause mortality was 5.0%, and the 1-year recurrence rate was 6.3%. Median patient age was 77.5 years. The two most common symptoms were abdominal pain (49.0%) and vaginal discharge (47.9%). Escherichia coli (40.1%), Klebsiella pneumoniae (16.7%), and Streptococcus spp.(16.0%) were the pathogens most frequently isolated by conventional culture; those isolated from polymerase chain reaction were Mycoplasma hominis (48.0%), and Ureaplasma spp. (32.0%). In multivariable analysis, fever, uterine perforation, and dementia were associated with increased incidence of septic shock, while vaginal discharge was associated with a lower incidence of septic shock. CONCLUSIONS: Our findings suggest that pyometra is a unique gynecological infectious syndrome in post-menopausal individuals. The most common associated pathogens are similar to those involved in urinary tract infections rather than those of sexually transmitted diseases. Decreased cognitive function could delay early diagnosis of pyometra and lead to septic shock and higher mortality.

Erratum: Publisher Correction: Systems immunology-based drug repurposing framework to target inflammation in atherosclerosis.

[This corrects the article DOI: 10.1038/s44161-023-00278-y.].