Background The angiotensin‐receptor neprilysin inhibitor (ARNI) sacubitril/valsartan was shown to be superior to the angiotensin‐converting enzyme inhibitor enalapril in terms of reducing cardiovascular mortality in the PARADIGM‐HF (Prospective Comparison of ARNI with angiotensin‐converting enzyme inhibitor to Determine Impact on Global Mortality and Morbidity in Heart Failure) study. However, the impact of ARNI on cardiac reverse remodeling (CRR) has not been established. Methods and Results We conducted a meta‐analysis to compare the effects of ARNI versus angiotensin‐converting enzyme inhibitors or angiotensin receptor blockers on CRR indices. We searched databases for studies published between 2010 and 2019 that reported CRR indices following ARNI administration. Effect size was expressed as mean difference (MD) with 95% CIs. Twenty studies enrolling 10 175 patients were included. ARNI improved functional capacity in patients with heart failure (HF) and a reduced ejection fraction (EF), including increasing New York Heart Association functional class (MD −0.79, 95% CI −0.86, −0.71) and 6‐minute walking distance (MD 27.62 m, 95% CI 15.76, 39.48). ARNI outperformed angiotensin‐converting enzyme inhibitors/angiotensin receptor blockers in terms of CRR indices, with striking changes in left ventricular EF, diameter, and volume. However, there were no significant improvements in indices except left ventricular mass index (MD −3.25 g/m 2 , 95% CI −3.78, −2.72) and left atrial volume (MD −7.20 mL, 95% CI −14.11, −0.29) in HF patients with preserved EF treated with ARNI. Improvements in CRR indices were observed at 3 months and became more significant with longer follow‐up to 12 months. The regression equation for the relationship between left ventricular EF and end‐diastolic dimension was y=0.041+0.071x+0.045x 2 +0.006x 3 . Conclusions ARNI distinctly improved left ventricular size and hypertrophy compared with angiotensin‐converting enzyme inhibitors/angiotensin receptor blockers in HF with reduced EF patients, even after short‐term follow‐up. Patients appeared to benefit more in terms of CRR treated with ARNI as early as possible and for at least 3 months. Further large sample trials are required to determine the effects of ARNI on CRR in HF with preserved EF patients.

In the cytoplasm of virtually all clear-cell renal cell carcinoma (ccRCC), speckle-type POZ protein (SPOP) is overexpressed and misallocated, which may induce proliferation and promote kidney tumorigenesis. In normal cells, however, SPOP is located in the nucleus and induces apoptosis. Here we show that a structure-based design and subsequent hit optimization yield small molecules that can inhibit the SPOP-substrate protein interaction and can suppress oncogenic SPOP-signaling pathways. These inhibitors kill human ccRCC cells that are dependent on oncogenic cytoplasmic SPOP. Notably, these inhibitors minimally affect the viability of other cells in which SPOP is not accumulated in the cytoplasm. Our findings validate the SPOP-substrate protein interaction as an attractive target specific to ccRCC that may yield novel drug discovery efforts.

PurposeQuantification of carotid plaques has been shown to be important for assessing as well as monitoring the progression and regression of carotid atherosclerosis. Various metrics have been proposed and methods of measurements ranging from manual tracing to automated segmentations have also been investigated. Of those metrics, quantification of carotid plaques by measuring vessel‐wall‐volume (VWV) using the segmented media‐adventitia (MAB) and lumen‐intima (LIB) boundaries has been shown to be sensitive to temporal changes in carotid plaque burden. Thus, semi‐automatic MAB and LIB segmentation methods are required to help generate VWV measurements with high accuracy and less user interaction.MethodsIn this paper, we propose a semiautomatic segmentation method based on deep learning to segment the MAB and LIB from carotid three‐dimensional ultrasound (3DUS) images. For the MAB segmentation, we convert the segmentation problem to a pixel‐by‐pixel classification problem. A dynamic convolutional neural network (Dynamic CNN) is proposed to classify the patches generated by sliding a window along the norm line of the initial contour where the CNN model is fine‐tuned dynamically in each test task. The LIB is segmented by applying a region‐of‐interest of carotid images to a U‐Net model, which allows the network to be trained end‐to‐end for pixel‐wise classification.ResultsA total of 144 3DUS images were used in this development, and a threefold cross‐validation technique was used for evaluation of the proposed algorithm. The proposed algorithm‐generated accuracy was significantly higher than the previous methods but with less user interactions. Comparing the algorithm segmentation results with manual segmentations by an expert showed that the average Dice similarity coefficients (DSC) were 96.46 ± 2.22% and 92.84 ± 4.46% for the MAB and LIB, respectively, while only an average of 34 s (vs 1.13, 2.8 and 4.4 min in previous methods) was required to segment a 3DUS image. The interobserver experiment indicated that the DSC was 96.14 ± 1.87% between algorithm‐generated MAB contours of two observers' initialization.ConclusionsOur results showed that the proposed carotid plaque segmentation method obtains high accuracy and repeatability with less user interactions, suggesting that the method could be used in clinical practice to measure VWV and monitor the progression and regression of carotid plaques.

In HL-2A and J-TEXT ohmic confinement regimes, an electrostatic turbulence with quasi-coherent characteristics in spectra of density fluctuations was observed by multi-channel microwave reflectometers. These quasi-coherent modes (QCMs) were detectable in a large plasma region (r/a∼0.3−0.8). The characteristic frequencies of QCMs were in the range of 30–140 kHz. The mode is rotated in the electron diamagnetic direction. In the plasmas with QCMs, trapped electron mode (TEM) was predicted to be unstable by gyrokinetic simulations. The combined experimental results show that the TEM is survived in the linear ohmic confinement regime of plasmas. The quasi-coherent TEM was replaced by broad-band fluctuations when the plasma transits from linear to saturated ohmic confinement regime. The observation was strongly related to the turbulence transition from TEM to ion temperature gradient mode. A critical gradient threshold for TEM excitation in electron temperature gradient was directly found. The effect of TEM on density profile peaking was presented.