CNN-based automatic segmentations and radiomics feature reliability on contrast-enhanced ultrasound images for renal tumors

ObjectiveTo investigate the feasibility and efficiency of automatic segmentation of contrast-enhanced ultrasound (CEUS) images in renal tumors by convolutional neural network (CNN) based models and their further application in radiomic analysis.Materials and methodsFrom 94 pathologically confirmed renal tumor cases, 3355 CEUS images were extracted and randomly divided into training set (3020 images) and test set (335 images). According to the histological subtypes of renal cell carcinoma, the test set was further split into clear cell renal cell carcinoma (ccRCC) set (225 images), renal angiomyolipoma (AML) set (77 images) and set of other subtypes (33 images). Manual segmentation was the gold standard and serves as ground truth. Seven CNN-based models including DeepLabV3+, UNet, UNet++, UNet3+, SegNet, MultilResUNet and Attention UNet were used for automatic segmentation. Python 3.7.0 and Pyradiomics package 3.0.1 were used for radiomic feature extraction. Performance of all approaches was evaluated by the metrics of mean intersection over union (mIOU), dice similarity coefficient (DSC), precision, and recall. Reliability and reproducibility of radiomics features were evaluated by the Pearson coefficient and the intraclass correlation coefficient (ICC).ResultsAll seven CNN-based models achieved good performance with the mIOU, DSC, precision and recall ranging between 81.97%-93.04%, 78.67%-92.70%, 93.92%-97.56%, and 85.29%-95.17%, respectively. The average Pearson coefficients ranged from 0.81 to 0.95, and the average ICCs ranged from 0.77 to 0.92. The UNet++ model showed the best performance with the mIOU, DSC, precision and recall of 93.04%, 92.70%, 97.43% and 95.17%, respectively. For ccRCC, AML and other subtypes, the reliability and reproducibility of radiomic analysis derived from automatically segmented CEUS images were excellent, with the average Pearson coefficients of 0.95, 0.96 and 0.96, and the average ICCs for different subtypes were 0.91, 0.93 and 0.94, respectively.ConclusionThis retrospective single-center study showed that the CNN-based models had good performance on automatic segmentation of CEUS images for renal tumors, especially the UNet++ model. The radiomics features extracted from automatically segmented CEUS images were feasible and reliable, and further validation by multi-center research is necessary

Calcium-sensing receptor regulates stomatal closure through hydrogen peroxide and nitric oxide in response to extracellular calcium in Arabidopsis

The Arabidopsis calcium-sensing receptor CAS is a crucial regulator of extracellular calcium-induced stomatal closure. Free cytosolic Ca2+ (Ca2+i) increases in response to a high extracellular calcium (Ca2+o) level through a CAS signalling pathway and finally leads to stomatal closure. Multidisciplinary approaches including histochemical, pharmacological, fluorescent, electrochemical, and molecular biological methods were used to discuss the relationship of hydrogen peroxide (H2O2) and nitric oxide (NO) signalling in the CAS signalling pathway in guard cells in response to Ca2+o. Here it is shown that Ca2+o could induce H2O2 and NO production from guard cells but only H2O2 from chloroplasts, leading to stomatal closure. In addition, the CASas mutant, the atrbohD/F double mutant, and the Atnoa1 mutant were all insensitive to Ca2+o-stimulated stomatal closure, as well as H2O2 and NO elevation in the case of CASas. Furthermore, it was found that the antioxidant system might function as a mediator in Ca2+o and H2O2 signalling in guard cells. The results suggest a hypothetical model whereby Ca2+o induces H2O2 and NO accumulation in guard cells through the CAS signalling pathway, which further triggers Ca2+i transients and finally stomatal closure. The possible cross-talk of Ca2+o and abscisic acid signalling as well as the antioxidant system are discussed

A facile space-confined solid-phase sulfurization strategy for growth of high-quality ultrathin molybdenum disulfide single crystals

Single-crystal transition metal dichalcogenides (TMDs) and TMD-based heterojunctions have recently attracted significant research and industrial interest owing to their intriguing optical and electrical properties. However, the lack of a simple, low-cost, environmentally friendly, synthetic method and a poor understanding of the growth mechanism post a huge challenge to implementing TMDs in practical applications. In this work, we developed a novel approach for direct formation of high-quality, monolayer and few-layer MoS2 single crystal domains via a single-step rapid thermal processing of a sandwiched reactor with sulfur and molybdenum (Mo) film in a confined reaction space. An all-solid-phase growth mechanism was proposed and experimentally/theoretically evidenced by analyzing the surface potential and morphology mapping. Compared with the conventional chemical vapor deposition approaches, our method involves no complicated gas-phase reactant transfer or reactions and requires very small amount of solid precursors [e.g., Mo (∼3 μg)], no carrier gas, no pretreatment of the precursor, no complex equipment design, thereby facilitating a simple, low-cost, and environmentally friendly growth. Moreover, we examined the symmetry, defects, and stacking phase in as-grown MoS2 samples using simultaneous second-harmonic-/sum-frequency-generation (SHG/SFG) imaging. For the first time, we observed that the SFG (peak intensity/position) polarization can be used as a sensitive probe to identify the orientation of TMDs’ crystallographic axes. Furthermore, we fabricated ferroelectric programmable Schottky junction devices via local domain patterning using the as-grown, single-crystal monolayer MoS2, revealing their great potential in logic and optoelectronic applications. Our strategy thus provides a simple, low-cost, and scalable path toward a wide variety of TMD single crystal growth and novel functional device design

RA-inducible gene-I induction augments STAT1 activation to inhibit leukemia cell proliferation

RA-inducible gene I (RIG-I/DDX58) has been shown to activate IFN-β promoter stimulator 1 (IPS-1) on recognizing cytoplasmic viral RNAs. It is unclear how RIG-I functions within the IFN and/or RA signaling process in acute myeloid leukemia (AML) cells, however, where obvious RIG-I induction is observed. Here, we show that the RIG-I induction functionally contributes to IFN-α plus RA-triggered growth inhibition of AML cells. Interestingly, although RIG-I induction itself is under the regulation of STAT1, a major IFN intracellular signal mediator, under circumstances in which it does not stimulate IPS-1, it conversely augments STAT1 activation to induce IFN-stimulatory gene expression and inhibit leukemia cell proliferation. Thus, our results unveil a previously undescribed RIG-I activity in regulating the cellular proliferation of leukemia cells via STAT1, which is independent of its classic role of sensing viral invasion to trigger type I IFN transcription