Venetoclax alone or in combination with other regimens treatment achieve deep and sustained remission of relapsed/refractory chronic lymphocytic leukemia: a meta-analysis

Clinical and Experimental Medicine - Recently, the use of novel targeted drugs significantly improved the overall response rate (ORR) and survival of patients with relapsed/refractory chronic...     

Uncertainty evaluation at three spatial scales for the NDVI-based VWC estimation method used in the SMAP algorithm

Vegetation water content (VWC) is the key input parameter for a soil moisture retrieval algorithm based on microwave remote sensing, and VWC uncertainty can limit the estimated accuracy of soil moisture. There has been little research on VWC algorithm development and validation in China, and the uncertainty of the VWC estimation method has not been well evaluated. Therefore, the aim of this study is to evaluate the uncertainty of the VWC estimation method used in the SMAP (Soil Moisture Active Passive) algorithm on three spatial scales (the point-scale, 30 m scale, and 1 km scale) for maize in northeast China. Results from three ground experimental datasets showed that the SMAP VWC estimation method was strongly biased with an average overestimation of 1.16 kg m^?2,1.04 kg m^?2, and 1.13 kg m^?2 for the point-scale, 30 m scale, and 1 km scale respectively, and maximum bias occurred in the mid-stage of maize. Also, a new power relationship between NDVI (Normalized Difference Vegetation Index) and VWC was proposed for the 30 m scale based on Sentinel 2 NDVI and field VWC values from 2017 experiment, with respective R² (coefficient of determination) and Root Mean Squared Error (RMSE) values of 0.80 and 0.67 kg m^?2. The results confirmed that this power relationship was still suitable for VWC estimation at the 1 km scale, and it has smaller bias than the original SMAP VWC method. Future work will be carried out to evaluate the applicability of this VWC estimation method over a lager region. It is expected that it can improve the accuracy of soil moisture by providing high precision VWC input parameters.     

Outcomes and risk management in type B aortic dissection patients with acute kidney injury: a concise review

PurposeType B aortic dissection is a rare but life-threatening disease. Thoracic endovascular aortic repair (TEVAR) was widely used for Type B aortic dissection patients in the last decade due to the lower mortality and morbidity compared with open chest surgical repair (OCSR). AKI in type B aortic dissection is a well-recognized complication and indicates poor short-term and long-term outcome. The objective of this concise review was to identify the risk factors and the impact of AKI on type B aortic dissection patients.Methods and resultsA literature search was performed using PubMed, Embase, MEDLINE, and Cochrane Library with the search terms ‘type B aortic dissection’ and ‘acute kidney injury’ (AKI), and all English-language literatures published in print or available online from inception through August 2020 were thoroughly reviewed. Studies that reported relative AKI risks and outcomes in type B aortic dissection patient were included. Major mechanisms of AKI in type B aortic dissection included renal hypoperfusion, inflammation response, and the use of contrast medium. Type B aortic dissection patients with AKI significantly had increased hospital stay duration, need of renal replacement therapy, and 30-d and 1-year mortality.ConclusionsAKI in type B aortic dissection is a well-recognized complication and associated with poor short-term and long-term outcome. Early identification of high-risk patients, early diagnosis of AKI, stabilization of the hemodynamic parameters, avoidance of nephrotoxic drugs, and optimization of the use of contrast agents are the major strategies for the reduction of AKI in type B aortic dissection patients.