Synthesis and biological evaluation of arylpiperazine derivatives as potential anti-prostate cancer agents.

A novel scaffold of arylpiperazine derivatives was discovered as potent androgen receptor (AR) antagonist through rational drug designation based on our pre-work, leading to the discovery of a series of new antiproliferative compounds. Compounds 10, 16, 27, 29 and 31 exhibited relatively strong antagonistic potency against AR and exhibited potent AR binding affinities, while compounds 5, 6, 10, 14, 16, 19, 21, 27 and 31 exhibited strong cytotoxic activities against LNCaP cells (AR-rich) as well as also displayed the higher activities than finasteride toward PC-3 (AR-deficient) and DU145 (AR-deficient). Docking study suggested that the most potent antagonist 16 mainly bind to AR ligand binding pocket (LBP) site through hydrogen bonding interactions. The structure-activity relationship (SAR) of these designed arylpiperazine derivatives was rationally explored and discussed. These results indicated that the novel scaffold compounds demonstrated a step towards the development of novel and improved AR antagonists, and promising candidates for future development were identified.

Cancer risk assessment in modern radiotherapy workflow with medical big data.

Modern radiotherapy (RT) is being enriched by big digital data and intensive technology. Multimodality image registration, intelligence-guided planning, real-time tracking, image-guided RT (IGRT), and automatic follow-up surveys are the products of the digital era. Enormous digital data are created in the process of treatment, including benefits and risks. Generally, decision making in RT tries to balance these two aspects, which is based on the archival and retrieving of data from various platforms. However, modern risk-based analysis shows that many errors that occur in radiation oncology are due to failures in workflow. These errors can lead to imbalance between benefits and risks. In addition, the exact mechanism and dose-response relationship for radiation-induced malignancy are not well understood. The cancer risk in modern RT workflow continues to be a problem. Therefore, in this review, we develop risk assessments based on our current knowledge of IGRT and provide strategies for cancer risk reduction. Artificial intelligence (AI) such as machine learning is also discussed because big data are transforming RT via AI.

Synthesis, biological evaluation and SAR of naftopidil-based arylpiperazine derivatives.

For the development of potential anti-prostate cancer agents, 24 kinds of novel naftopidil-based arylpiperazine derivatives have been synthesized and characterized by spectroscopic methods. Their antitumor activities were evaluated against several classical prostate cancer cell lines including PC-3, LNCaP, and DU145. Among all the compounds, 9, 13, 17, 21 and 27 showed strong cytotoxic activities against DU145 cells (IC50 < 1 µM). Further testing confirmed that compound 17 inhibited the growth of DU145 cells by inducing cell cycle arrest at G0/G1 phase. Besides, antagonistic activities of compounds (9, 13, 17, 21 and 27) towards a1-ARs (α1A, α1B, and α1D) were further evaluated using dual-luciferase reporter assays, and the compounds 13 and 17 exhibited better a1-ARs subtype selectivity. The structure-activity relationship (SAR) of these developed arylpiperazine derivatives was rationally discussed. Taken together, these results suggested that further development of such compounds may be of great interest.

[Influence of projection data correction on digital breast tomosynthesis imaging].

OBJECTIVE: To investigate the effect of detector performance during digital breast tomography (DBT) projection data acquisition on reconstructed image quality. METHODS: With reference to the traditional detector data correction method and the specific data acquisition pattern in DBT imaging, we utilized dark field correction, light field and its gain correction for processing the projection data collected by the detector. The reconstructed images were evaluated using iterative reconstruction method based on total generalized variation (TGV). RESULTS: In physical breast phantom experiment, the proposed method resulted in a reduced Heel effect caused by nonuniform photon number. The reconstructed DBT images after correction showed obviously improved image quality especially in the details with a low contrast. CONCLUSION: The dark field correction, light field and its gain correction process for DBT image reconstruction can improve the image quality.