(E)-2-(1,3-Diphenyl­allyl­idene)malononitrile

The title compound, C18H12N2, adopts an E conformation with the benzyl­idenemalononitrile and phenyl groups located on opposite sides of the C=C bond. The two phenyl rings are oriented at a dihedral angle of 62.49 (7)°

(2R,3R)-3-(2-Chloro­phen­yl)-N-phenyl­oxirane-2-carboxamide

In the title compound, C15H12ClNO2, the two benzene rings adopt a syn configuration with respect to the ep­oxy ring; the dihedral angles between the ep­oxy ring and the two benzene rings are 59.71 (16) and 67.58 (15)°. There is a weak intra­molecular N—H⋯O bond, which may help to establish the conformation. In the crystal, the mol­ecules are linked into a chain parallel to the b axis through inter­molecular N—H⋯O hydrogen bonds

2-(7-Methyl-3-oxo-1-phenyl­perhydro­naphthalen-4a-yl)malononitrile

In the title compound, C20H22N2O, both cyclo­hexane rings adopt chair conformations. Weak C—H⋯N and C—H⋯O hydrogen bonding is present in the crystal structure

(E)-N-Benzyl-2-cyano-3-phenyl­acryl­amide

In the title compound, C17H14N2O, the N-benzyl­formamide and phenyl groups are located on the opposite sides of the C=C bond, showing an E configuration; the terminal phenyl rings are twisted to each other at a dihedral angle of 63.61 (7)°. Inter­molecular classical N—H⋯N and weak C—H⋯O hydrogen bonds occur in the crystal structure

2-[(E)-1-(4-Meth­oxy­phen­yl)pent-1-en-3-yl­idene]malononitrile

In the title compound, C15H14N2O, the mol­ecule skeleton displays an approximately planar structure except for the ethyl group [maximum deviation = 0.042 (1) Å]. The meth­oxy­phenyl ring and butanylidenemalononitrile groups are located on opposite sides of the C=C bond, showing an E configuration. Weak inter­molecular C—H⋯N hydrogen bonding is present in the crystal structure

Malignant and Nonmalignant Gene Signatures in Squamous Head and Neck Cancer

Genetic events specific to the pathogenesis of malignancy can offer clues to the tumorigenesis process. The objective of this study was to identify gene alterations that differentiate tumor and nontumor lesions in squamous head and neck cancer (HNSCC). DNA from 220 primary HNSCC with concurrently present tumor and nontumor lesions from the same patient was interrogated for genomic alterations of loss or gain of copy. Conditional logistic regression dealt with tumor and non-tumor records within a patient. Of 113 genes, 53 had univariate effects (P < 0.01), of which 16 genes remained in the multivariable model with P < 0.01. The model had a C-index (ROC) of 0.93. Loss of CDKN2B and gain of BCL6, FGF3, and PTP4A3 predicted tumor. Loss of BAK1 and CCND1 and gain of STCH predicted nontumor. This highly powered model assigned alterations in 16 genes specific for malignant versus nonmalignant lesions, supporting their contribution to the pathogenesis of HNSCC as well as their potential utility as relevant targets for further evaluation as markers of early detection and progression

NADPH oxidase 4 mediates insulin-stimulated HIF-1α and VEGF expression, and angiogenesis in vitro

Acute intensive insulin therapy causes a transient worsening of diabetic retinopathy in type 1 diabetes patients and is related to VEGF expression. Reactive oxygen species (ROS) have been shown to be involved in HIF-1α and VEGF expression induced by insulin, but the role of specific ROS sources has not been fully elucidated. In this study we examined the role of NADPH oxidase subunit 4 (Nox4) in insulin-stimulated HIF-1α and VEGF expression, and angiogenic responses in human microvascular endothelial cells (HMVECs). Here we demonstrate that knockdown of Nox4 by siRNA reduced insulin-stimulated ROS generation, the tyrosine phosphorylation of IR-β and IRS-1, but did not change the serine phosphorylation of IRS-1. Nox4 gene silencing had a much greater inhibitory effect on insulin-induced AKT activation than ERK1/2 activation, whereas it had little effect on the expression of the phosphatases such as MKP-1 and SHIP. Inhibition of Nox4 expression inhibited the transcriptional activity of VEGF through HIF-1. Overexpression of wild-type Nox4 was sufficient to increase VEGF transcriptional activity, and further enhanced insulin-stimulated the activation of VEGF. Downregulation of Nox4 expression decreased insulin-stimulated mRNA and protein expression of HIF-1α, but did not change the rate of HIF-1α degradation. Inhibition of Nox4 impaired insulin-stimulated VEGF expression, cell migration, cell proliferation, and tube formation in HMVECs. Our data indicate that Nox4-derived ROS are essential for HIF-1α-dependent VEGF expression, and angiogenesis in vitro induced by insulin. Nox4 may be an attractive therapeutic target for diabetic retinopathy caused by intensive insulin treatment

Ag-Decorated Fe 3

Well-dispersed Ag nanoparticles (NPs) are successfully decorated on Fe3O4@SiO2 nanorods (NRs) via a facile step-by-step strategy. This method involves coating α-Fe2O3 NRs with uniform silica layer, reduction in 10% H2/Ar atmosphere at 450°C to obtain Fe3O4@SiO2 NRs, and then depositing Ag NPs on the surface of Fe3O4@SiO2 NRs through a sonochemical step. It was found that the as-prepared Ag-decorated magnetic Fe3O4@SiO2 NRs (Ag-MNRs) exhibited a higher catalytic efficiency than bare Ag NPs in the degradation of organic dye and could be easily recovered by convenient magnetic separation, which show great application potential for environmental protection applications

Federated Meta-Learning for Few-Shot Fault Diagnosis with Representation Encoding

Deep learning-based fault diagnosis (FD) approaches require a large amount of training data, which are difficult to obtain since they are located across different entities. Federated learning (FL) enables multiple clients to collaboratively train a shared model with data privacy guaranteed. However, the domain discrepancy and data scarcity problems among clients deteriorate the performance of the global FL model. To tackle these issues, we propose a novel framework called representation encoding-based federated meta-learning (REFML) for few-shot FD. First, a novel training strategy based on representation encoding and meta-learning is developed. It harnesses the inherent heterogeneity among training clients, effectively transforming it into an advantage for out-of-distribution generalization on unseen working conditions or equipment types. Additionally, an adaptive interpolation method that calculates the optimal combination of local and global models as the initialization of local training is proposed. This helps to further utilize local information to mitigate the negative effects of domain discrepancy. As a result, high diagnostic accuracy can be achieved on unseen working conditions or equipment types with limited training data. Compared with the state-of-the-art methods, such as FedProx, the proposed REFML framework achieves an increase in accuracy by 2.17%-6.50% when tested on unseen working conditions of the same equipment type and 13.44%-18.33% when tested on totally unseen equipment types, respectively