Epithelial-to-mesenchymal transition (EMT) and its reversed process, mesenchymal-to-epithelial transition (MET), are fundamental processes in embryonic development and tissue repair but confer ...malignant properties to carcinoma cells, including invasive behavior, cancer stem cell activity, and greater resistance to chemotherapy and immunotherapy. Understanding the molecular and cellular basis of EMT provides fundamental insights into the etiology of cancer and may, in the long run, lead to new therapeutic strategies. Here, we discuss the regulatory mechanisms and pathological roles of epithelial-mesenchymal plasticity, with a focus on recent insights into the complexity and dynamics of this phenomenon in cancer.
Epithelial-to-mesenchymal transition and its reversed process, mesenchymal-to-epithelial transition, are fundamental in embryonic development and tissue repair but also confer malignant properties to carcinoma cells. Lu and Kang discuss recent insights into the regulation and pathological roles of epithelial-mesenchymal plasticity, with particular focus on this phenomenon in cancer.
Organic–inorganic halide perovskite (OHP) materials, for example, CH3NH3PbI3 (MAPbI3), have attracted significant interest for applications such as solar cells, photodectors, light‐emitting diodes, ...and lasers. Previous studies have shown that charged defects can migrate in perovskites under an electric field and/or light illumination, potentially preventing these devices from practical applications. Understanding and control of the defect generation and movement will not only lead to more stable devices but also new device concepts. Here, it is shown that the formation/annihilation of iodine vacancies (VI's) in MAPbI3 films, driven by electric fields and light illumination, can induce pronounced resistive switching effects. Due to a low diffusion energy barrier (≈0.17 eV), the VI's can readily drift under an electric field, and spontaneously diffuse with a concentration gradient. It is shown that the VI diffusion process can be suppressed by controlling the affinity of the contact electrode material to I− ions, or by light illumination. An electrical‐write and optical‐erase memory element is further demonstrated by coupling ion migration with electric fields and light illumination. These results provide guidance toward improved stability and performance of perovskite‐based optoelectronic systems, and can lead to the development of solid‐state devices that couple ionics, electronics, and optics.
Electric field and light illumination controlled iodine vacancy (VI) redistribution and resistive switching effects are demonstrated in organic–inorganic halide perovskite films. The diffusion energy barrier of VI is ≈0.17 eV. The VI diffusion dynamics can be modulated through engineering the anode material and controlling illumination conditions. An electrical‐write and optical‐erase memory element is demonstrated.
Covalent organic frameworks (COFs) are of great potential as adsorbents owing to their tailorable functionalities, low density and high porosity. However, their intrinsically stacked two‐dimensional ...(2D) structure limits the full use of their complete surface for sorption, especially the internal pores. The construction of ultrathin COFs could increase the exposure of active sites to the targeted molecules in a pollutant environment. Herein, an ultrathin COF with a uniform thickness of ca. 2 nm is prepared employing graphene as the surface template. The resulting hybrid aerogel with an ultralow density (7.1 mg cm−3) exhibits the ability to remove organic dye molecules of different sizes with high efficiency. The three‐dimensional (3D) macroporous structure and well‐exposed adsorption sites permit rapid diffusion of solution and efficient adsorption of organic pollutants, thereby, greatly contributing to its enhanced uptake capacity. This work highlights the effect of COF layer thickness on adsorption performance.
An ultrathin anionic covalent organic framework (COF) was constructed homogeneously on the surface of a graphene template via a facile hydrothermal method. Compared with bulk COF powder, the anionic ultrathin COF exhibited the ability to remove cationic organic dyes of different sizes with higher efficiency.
Rapid advances in the semiconductor industry, driven largely by device scaling, are now approaching fundamental physical limits and face severe power, performance, and cost constraints. ...Multifunctional materials and devices may lead to a paradigm shift toward new, intelligent, and efficient computing systems, and are being extensively studied. Herein examines how, by controlling the internal ion distribution in a solid‐state film, a material's chemical composition and physical properties can be reversibly reconfigured using an applied electric field, at room temperature and after device fabrication. Reconfigurability is observed in a wide range of materials, including commonly used dielectric films, and has led to the development of new device concepts such as resistive random‐access memory. Physical reconfigurability further allows memory and logic operations to be merged in the same device for efficient in‐memory computing and neuromorphic computing systems. By directly changing the chemical composition of the material, coupled electrical, optical, and magnetic effects can also be obtained. A survey of recent fundamental material and device studies that reveal the dynamic ionic processes is included, along with discussions on systematic modeling efforts, device and material challenges, and future research directions.
By controlling the internal ion distribution in a solid‐state film, the material's chemical composition and physical (i.e., electrical, optical, and magnetic) properties can be reversibly reconfigured, in situ, using an applied electric field. The reconfigurability is achieved in a wide range of materials, and can lead to the development of new memory, logic, and multifunctional devices and systems.
Abstract
Interfacial adhesion energy is a fundamental property of two-dimensional (2D) layered materials and van der Waals heterostructures due to their intrinsic ultrahigh surface to volume ratio, ...making adhesion forces very strong in many processes related to fabrication, integration and performance of devices incorporating 2D crystals. However, direct quantitative characterization of adhesion behavior of fresh and aged homo/heterointerfaces at nanoscale has remained elusive. Here, we use an atomic force microscopy technique to report precise adhesion measurements in ambient air through well-defined interactions of tip-attached 2D crystal nanomesas with 2D crystal and SiO
x
substrates. We quantify how different levels of short-range dispersive and long-range electrostatic interactions respond to airborne contaminants and humidity upon thermal annealing. We show that a simple but very effective precooling treatment can protect 2D crystal substrates against the airborne contaminants and thus boost the adhesion level at the interface of similar and dissimilar van der Waals heterostructures. Our combined experimental and computational analysis also reveals a distinctive interfacial behavior in transition metal dichalcogenides and graphite/SiO
x
heterostructures beyond the widely accepted van der Waals interaction.
The ability to efficiently analyze the activities of biological neural networks can significantly promote our understanding of neural communications and functionalities. However, conventional neural ...signal analysis approaches need to transmit and store large amounts of raw recording data, followed by extensive processing offline, posing significant challenges to the hardware and preventing real-time analysis and feedback. Here, we demonstrate a memristor-based reservoir computing (RC) system that can potentially analyze neural signals in real-time. We show that the perovskite halide-based memristor can be directly driven by emulated neural spikes, where the memristor state reflects temporal features in the neural spike train. The RC system is successfully used to recognize neural firing patterns, monitor the transition of the firing patterns, and identify neural synchronization states among different neurons. Advanced neuroelectronic systems with such memristor networks can enable efficient neural signal analysis with high spatiotemporal precision, and possibly closed-loop feedback control.
The blood-brain barrier (BBB), which impedes drug penetration into the central nervous system, is composed of specific structures formed by brain capillary endothelial cells and sheathed by ...astrocytic end-feet through basement membrane. Many brain drug delivery strategies have focused on adsorptive-mediated transcytosis (AMT), which is triggered by electrostatic interaction between cationic molecules and anionic microdomains on the cytoplasm membrane of the brain capillary endothelial cells. AMT-based drug delivery to the brain can be achieved by using cationic proteins and basic oligopeptides such as cell-penetrating peptides as targetors. Large therapeutic molecules such as neuropeptides and proteins or even drug-encapsulated vectors such as liposomes and nanoparticles can be allowed to access brain parenchyma through AMT when conjugated with these cationic targetors. In this review, I briefly discuss adsorptive-mediated brain delivery systems that may provide physiologic-based strategies for enhanced delivery of therapeutic substances through the BBB.
Reservoir computing systems utilize dynamic reservoirs having short-term memory to project features from the temporal inputs into a high-dimensional feature space. A readout function layer can then ...effectively analyze the projected features for tasks, such as classification and time-series analysis. The system can efficiently compute complex and temporal data with low-training cost, since only the readout function needs to be trained. Here we experimentally implement a reservoir computing system using a dynamic memristor array. We show that the internal ionic dynamic processes of memristors allow the memristor-based reservoir to directly process information in the temporal domain, and demonstrate that even a small hardware system with only 88 memristors can already be used for tasks, such as handwritten digit recognition. The system is also used to experimentally solve a second-order nonlinear task, and can successfully predict the expected output without knowing the form of the original dynamic transfer function.
With the advancements in social media and rising demand for real traffic information, the data shared in vehicular ad hoc networks (VANETs) indicate that the size and amount of requested data will ...continue increasing. Vehicles in the same area often have similar data downloading requests. If we ignore the common requests, the resource allocation efficiency of the VANET system will be quite low. Motivated by this fact, we propose an efficient and privacy-preserving data downloading scheme for VANETs, based on the edge computing concept. In the proposed scheme, a roadside unit (RSU) can find the popular data by analyzing the encrypted requests sent from nearby vehicles without having to sacrifice the privacy of their download requests. Further, the RSU caches the popular data in nearby qualified vehicles called edge computing vehicles (ECVs). If a vehicle wishes to download the popular data, it can download it directly from the nearby ECVs. This method increases the downloading efficiency of the system. The security analysis results show that the proposed scheme can resist multiple security attacks. The performance analysis results demonstrate that our scheme has reasonable computation and communication overhead. Finally, the OMNeT++ simulation results indicate that our scheme has good network performance.
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