With the advent of tyrosine kinase inhibitors (TKIs), the treatment prospects of chronic myeloid leukemia (CML) have changed markedly. This innovation can lengthen the long-term survival of patients suffering from CML. However, long-term exposure to TKIs is accompanied by various adverse events (AEs). The latter affect the quality of life and compliance of patients with CML, and may lead to serious disease progression (and even death). Recently, increasing numbers of patients with CML have begun to pursue a dose optimization strategy. Dose optimization may be considered at all stages of the entire treatment, which includes dose reduction and discontinuation of TKIs therapy. In general, reduction of the TKI dose is considered to be an important measure to reduce AEs and improve quality of life on the premise of maintaining molecular responses. Furthermore, discontinuation of TKIs therapy has been demonstrated to be feasible and safe for about half of patients with a stable optimal response and a longer duration of TKI treatment. This review focuses mainly on the latest research of dose optimization of imatinib, dasatinib, and nilotinib in CML clinical trials and real-life settings. We consider dose reduction in newly diagnosed patients, or in optimal response, or for improving AEs, either as a prelude to treatment-free remission (TFR) or as maintenance therapy in those patients unable to discontinue TKIs therapy. In addition, we also focus on discontinuation of TKIs therapy and second attempts to achieve TFR.
Hyper-parameter tuning (HPT) is crucial for many machine learning (ML) algorithms. But due to the large searching space, HPT is usually time-consuming and resource-intensive. Nowadays, many researchers use public cloud resources to train machine learning models, convenient yet expensive. How to speed up the HPT process while at the same time reduce cost is very important for cloud ML users. In this paper, we propose SpotTune, an approach that exploits transient revocable resources in the public cloud with some tailored strategies to do HPT in a parallel and cost-efficient manner. Orchestrating the HPT process upon transient servers, SpotTune uses two main techniques, fine-grained cost-aware resource provisioning, and ML training trend predicting, to reduce the monetary cost and runtime of HPT processes. Our evaluations show that SpotTune can reduce the cost by up to 90% and achieve a 16.61x performance-cost rate improvement.
In the biological system, there are various gas molecules, which play key roles in the system. Specially, NO, CO and H2S are recognized as gasotransmitters, involving in the signal transduction and related biological events. Even though remarkable advance in the field has been made these years, the roles of gasotransmitters in the biological systems are not fully understood. For further exploration of the functions of gasotransmitters, fast, high selective and high sensitive analysis and imaging methods are highly required. Development on these methods has become an important cross discipline among chemical biology, bioinorganic chemistry, pharmacy and medicine. The current review focuses on the development of the small molecule fluorescent probes for gasotransmitters in recent years, and hopefully this work would attract the interest of the field.
Stored procedure has occurred independently in database application systems. How to test the stored procedure effectively becomes an urgent problem in automated testing. Test data generation is a vital part in automated test of stored procedure. However, the current approaches of test data generation for stored procedure needs manual intervention and the solution of the constraint system which limits test data can not effectively cover all the situations. Existing approaches can not solve constraint system with character string and strict inequality. This paper improved the approach to generate test data, perfected existing approach to solve constraint system and reduced the limitation on solving the constraint system.
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