Breast cancer has been reported as the most common cancer in women globally, with 2.26 million new cases in 2020. While anthracyclines are the first-line drug for breast cancer, they cause a variety of adverse reactions and drug resistance, especially for triple-negative breast cancer, which can lead to poor prognosis, high relapse, and mortality rate. MicroRNAs (miRNAs) have been shown to be important in the initiation, development and metastasis of malignancies and their abnormal transcription levels may influence the efficacy of anthracyclines by participating in the pathologic mechanisms of breast cancer. Therefore, it is essential to understand the exact role of miRNAs in the treatment of breast cancer with anthracyclines. In this review, we outline the mechanisms and signaling pathways involved in miRNAs in the treatment of breast cancer using anthracyclines. The role of miRNA in the diagnosis, prognosis and treatment of breast cancer patients is discussed, along with the involvement of miRNAs in chemotherapy for breast cancer.

Aim: The aim of the research is to establish a population pharmacokinetic (PPK) model of Clindamycin hydrochloride capsules in Chinese health subjects and investigate the factors affecting the pharmacokinetic parameters to provide guidance for the individualized treatment of Clindamycin. Methods: Clindamycin concentrations were measured in 48 selective health subjects (30 males and 18 females aged 18-45 years). The subjects were assigned to two groups randomly. 150mg Clindamycin oral administration were given at fasting or postprandial, respectively. Blood samples were collected at specified time. A total of 1344 blood drug concentration data were analyzed using NONMEM. The Non-linear mixed effect model was conducted to establish the population pharmacokinetic model of Clindamycin in Chinese healthy patients. The model was verified and evaluated by Visual Prediction Test (VPC) and Bootstrap method. Results: This study established a one-compartment pharmacokinetic model of Clindamycin hydrochloride capsules in Chinese healthy subjects. The final population pharmacokinetic parameters were oral absorption coefficient (Ka=2.69 h-1), apparent volume of distribution (V/F=76.74 L) and apparent clearance (CL/F= 30.10 L·h-1). And the food was the only significant covariate in the model. The final model was stable and predictable, verified by VPC and Bootstrap. Conclusion: A robust and predictable population pharmacokinetic model of Clindamycin in Chinese healthy subjects was constructed successfully. The dietary state had a significant effect on the pharmacokinetics of Clindamycin which gave an important steer for dose adjustment or changing medication in clinical practice. Moreover, the model had great potential to guide the individualized medication of Clindamycin.

China is aggressively pursuing digital transformation, and data, alike labor, technology, capital, and knowledge, has become as a crucial factor of production. Digital transformation is accelerating the emergence of a data-intensive society, and the ensuing difficulties of balancing freedom and responsibility, openness and security, as well as free sharing and legal regulation are posing new challenges to national and social governance. Among these challenges, defining data ownership, the social disorder and anomie brought about by the unclear definition of data ownership, and data ownership regulatory path are new propositions that need to be urgently addressed in this data-intensive society. This paper systematically explains the theoretical meaning and practical value of data ownership through a literature review on the analysis of domestic and foreign scholars as well as research think tanks, compares the differences and inherent conflicts between the definition of data ownership by the government, enterprises, and society in China, thoroughly compares the definition standards of the European Union, the United States, and Japan, and on this basis, discusses the formation of a definition of data ownership that meets the requirements of China’s digital transformation.