https://www.selleckchem.com/products/tefinostat.html The gram-negative Coxiella burnetii bacterium is the pathogen that causes Q fever. The bacterium is transmitted to animals via ticks, and manure, air, dead infected animals, etc. and can cause infection in domestic animals, wild animals, and humans. Xinjiang, the provincial-level administrative region with the largest land area in China, has many endemic tick species. The infection rate of C. burnetii in ticks in Xinjiang border areas has not been studied in detail. For the current study, 1507 ticks were collected from livestock at 22 sampling sites in ten border regions of the Xinjiang Uygur Autonomous region from 2018 to 2019. C. burnetii was detected in 205/348 (58.91%) Dermacentor nuttalli; in 110/146 (75.34%) D. pavlovskyi; in 66/80 (82.50%) D. silvarum; in 15/32 (46.90%) D. niveus; in 28/132 (21.21%) Hyalomma rufipes; in 24/25 (96.00%) H. anatolicum; in 219/312 (70.19%) H. asiaticum; in 252/338 (74.56%) Rhipicephalus sanguineus; and in 54/92 (58.70%) Haemaphysalis punctata. Among these samples, C. b rate of C. burnetii detected in the ticks found in domestic animals may indicate a high likelihood of Q fever infection in both domestic animals and humans. Knowledge discovery from breast cancer treatment records has promoted downstream clinical studies such as careflow mining and therapy analysis. However, the clinical treatment text from electronic health data might be recorded by different doctors under their hospital guidelines, making the final data rich in author- and domain-specific idiosyncrasies. Therefore, breast cancer treatment entity normalization becomes an essential task for the above downstream clinical studies. The latest studies have demonstrated the superiority of deep learning methods in named entity normalization tasks. Fundamentally, most existing approaches adopt pipeline implementations that treat it as an independent process after named entity recognition, which can propagate errors to l