These data provide direct evidence that Cat S plays an important role in AAA formation and suggest that Cat S is a new therapeutic target for human AAA.

Previous studies have shown that wheat grain yield is seriously affected by drought stress, and leaf cuticular wax is reportedly associated with drought tolerance. However, most studies have focused on cuticular wax biosynthesis and model species. The effects of cuticular wax on wheat drought tolerance have rarely been studied. The aims of the current study were to study the effects of leaf cuticular wax on wheat grain yield under drought stress using the above-mentioned wheat NILs and to discuss the possible physiological mechanism of cuticular wax on high grain yield under drought stress. Compared to water-irrigated (WI) conditions, the cuticular wax content (CWC) in glaucous and non-glaucous NILs under drought-stress (DS) conditions both increased; mean increase values were 151.1 and 114.4%, respectively, which was corroborated by scanning electronic microscopy images of large wax particles loaded on the surfaces of flag leaves. The average yield of glaucous NILs was higher than that of non-glaucous NILs under DS conditions in 2014 and 2015; mean values were 7368.37 kg·ha−1 and 7103.51 kg·ha−1. This suggested that glaucous NILs were more drought-tolerant than non-glaucous NILs (P = 0.05), which was supported by the findings of drought tolerance indices TOL and SSI in both years, the relatively high water potential and relative water content, and the low ELWL. Furthermore, the photosynthesis rate (Pn) of glaucous and non-glaucous wheat NILs under DS conditions decreased by 7.5 and 9.8%, respectively; however, glaucous NILs still had higher mean values of Pn than those of non-glaucous NILs, which perhaps resulted in the higher yield of glaucous NILs. This could be explained by the fact that glaucous NILs had a smaller Fv/Fm reduction, a smaller PI reduction and a greater ABS/RC increase than non-glaucous NILs under DS conditions. This is the first report to show that wheat cuticular wax accumulation is associated with drought tolerance. Moreover, the leaf CWC can be an effective selection criterion in the development of drought-tolerant wheat cultivars.

Chili anthracnose caused by Colletotrichum spp. is an annual production concern for growers in China. Sterol C14-demethylation inhibitors (DMIs, such as tebuconazole) have been widely used to control this disease for more than three decades. In the current study, of 48 isolates collected from commercial chili farms in Jiangsu Province of China during 2018 and 2019, 8 single-spore isolates were identified as Colletotrichum gloeosporioides and the rest were identified as C. acutatum. To determine whether the DMI resistance of isolates develops in the field, mycelial growth of the 48 isolates was measured in culture medium with and without tebuconazole. In all, 6 of the 8 C. gloeosporioides isolates were resistant to tebuconazole, but all 40 of the C. acutatum isolates were sensitive to tebuconazole. The fitness cost of resistance was low based on a comparison of fitness parameters between the sensitive and resistant isolates of C. gloeosporioides. Positive cross-resistance was observed between tebuconazole and difenconazole or propiconazole, but not prochloraz. Alignment results of the CgCYP51 amino acid sequences from the sensitive and resistant isolates indicated that mutations can be divided into three genotypes. Genotype I possessed four substitutions (V18F, L58V, S175P, and P341A) at the CgCYP51A gene but no substitutions at CgCYP51B, while genotype II had five substitutions (L58V, S175P, A340S, T379A, and N476T) at CgCYP51A, concomitant with three substitutions (D121N, T132A, and F391Y) at CgCYP51B. In addition, genotype III contained two substitutions (L58V and S175P) at CgCYP51A, concomitant with one substitution (T262A) at CgCYP51B. Molecular docking models illustrated that the affinity of tebuconazole to the binding site of the CgCYP51 protein from the resistant isolates was decreased when compared with binding site affinity of the sensitive isolates. Our findings provide not only novel insights into understanding the resistance mechanism to DMIs, but also some important references for resistance management of C. gloeosporioides on chili.

Our studies suggest that Ang II stimulates Pax-2 gene expression in IRPTC via AT2R and the JAK2/signal transducers and activators of transcription (STAT) signaling transduction pathway, which may be important in renal repair following injury. Cells lacking Pax-2 gene expression appear to be prone toward apoptosis rather than proliferation.

ObjectivesTo evaluate the potential of a clinical-based model, a multiparametric ultrasound-based radiomics model, and a clinical-radiomics combined model for predicting prostate cancer (PCa).MethodsA total of 112 patients with prostate lesions were included in this retrospective study. Among them, 58 patients had no prostate cancer detected by biopsy and 54 patients had prostate cancer. Clinical risk factors related to PCa (age, prostate volume, serum PSA, etc.) were collected in all patients. Prior to surgery, patients received transrectal ultrasound (TRUS), shear-wave elastography (SWE) and TRUS-guided prostate biopsy. We used the five-fold cross-validation method to verify the results of training and validation sets of different models. The images were manually delineated and registered. All modes of ultrasound radiomics were retrieved. Machine learning used the pathology of “12+X” biopsy as a reference to draw the benign and malignant regions of interest (ROI) through the application of LASSO regression. Three models were developed to predict the PCa: a clinical model, a multiparametric ultrasound-based radiomics model and a clinical-radiomics combined model. The diagnostic performance and clinical net benefit of each model were compared by receiver operating characteristic curve (ROC) analysis and decision curve.ResultsThe multiparametric ultrasound radiomics reached area under the curve (AUC) of 0.85 for predicting PCa, meanwhile, AUC of B-mode radiomics and SWE radiomics were 0.74 and 0.80, respectively. Additionally, the clinical-radiomics combined model (AUC: 0.90) achieved greater predictive efficacy than the radiomics model (AUC: 0.85) and clinical model (AUC: 0.84). The decision curve analysis also showed that the combined model had higher net benefits in a wide range of high risk threshold than either the radiomics model or the clinical model.ConclusionsClinical-radiomics combined model can improve the accuracy of PCa predictions both in terms of diagnostic performance and clinical net benefit, compared with evaluating only clinical risk factors or radiomics score associated with PCa.