Liquid metal (LM) droplets show the superiority in coalescing into integral liquid conductors applicable in flexible and deformable electronics. However, the large surface tension, oxide shells and poor compatibility with most other materials may prevent spontaneous coalescence of LM droplets and/or hybridisation into composites, unless external interventions (e.g., shear and laser) are applied. Here, we show that biological nanofibrils (NFs; including cellulose, silk fibroin and amyloid) enable evaporation-induced sintering of LM droplets under ambient conditions into conductive coating on diverse substrates and free-standing films. The resultants possess an insulating NFs-rich layer and a conductive LM-rich layer, offering flexibility, high reflectivity, stretchable conductivity, electromagnetic shielding, degradability and rapid actuating behaviours. Thus this sintering approach not only extends fundamental knowledge about sintering LM droplets, but also starts a new scenario of producing flexible coating and free-standing composites with flexibility, conductivity, sustainability and degradability, and applicable in microcircuits, wearable electronics and soft robotics.

No abstract

No abstract

Social bots are referred to as the automated accounts on social networks that make attempts to behave like human. While Graph Neural Networks (GNNs) has been massively applied to the field of social bot detection, a huge amount of domain expertise and prior knowledge is heavily engaged in the state-of-the art approaches to design a dedicated neural network architecture for a specific classification task. Involving oversized nodes and network layers in the model design, however, usually causes the over-smoothing problem and the lack of embedding discrimination. In this paper, we propose RoSGAS , a novel R einf o rced and S elf-supervised G NN A rchitecture S earch framework to adaptively pinpoint the most suitable multi-hop neighborhood and the number of layers in the GNN architecture. More specifically, we consider the social bot detection problem as a user-centric subgraph embedding and classification task. We exploit heterogeneous information network to present the user connectivity by leveraging account metadata, relationships, behavioral features and content features. RoSGAS uses a multi-agent deep reinforcement learning (RL) mechanism for navigating the search of optimal neighborhood and network layers to learn individually the subgraph embedding for each target user. A nearest neighbor mechanism is developed for accelerating the RL training process, and RoSGAS can learn more discriminative subgraph embedding with the aid of self-supervised learning. Experiments on 5 Twitter datasets show that RoSGAS outperforms the state-of-the-art approaches in terms of accuracy, training efficiency and stability, and has better generalization when handling unseen samples.

Chemotherapy remains one of the most important adjuvant treatments for bladder cancer (BC). However, similar to other malignancies, BC is prone to chemotherapy resistance and only approximately half of muscle-invasive patients with BC respond to chemotherapy. The present study aimed to reveal the mechanisms underlying chemoresistance in BC cells. Cell viabilities were assessed by CCK-8 assay. The differentiated expression of genes in chemoresistant and their parental BC cells were examined by RNA sequencing. Cell death was determined by flow cytometry. Different cell death inhibitors were used to determine the types of cell death. Levels of reactive oxygen species, iron, glutathione and malondialdehyde were assessed using the corresponding commercial kits. ChIP and dual luciferase activity assays were performed to investigate the interaction between staphylococcal nuclease and tumour domain containing 1 (SND1) and glutathione peroxidase 4 (GPX4) mRNA. RNAi was used to knockdown SND1 or GPX4. The results revealed that SND1 in BC cells were insensitive to cisplatin, and inhibition of SND1 overcame this resistance. Silencing of SND1 enhanced cell death induced by cisplatin by promoting ferroptosis in BC cells. Mechanistically, SND1 was revealed to bind to the 3'UTR region of GPX4 mRNA and stabilise it. Knockdown of GPX4 could also overcome chemoresistance, and overexpressing GPX4 reversed the effects of silencing of GPX4 on the chemosensitivity of BC cells. Thus, targeting the SND1-GPX4 axis may be a potential strategy to overcome chemoresistance in BC cells.