Remodeling tumor-associated macrophage for anti-cancer effects by rational design of irreversible inhibition of mitogen-activated protein kinase-activated protein kinase 2.

Mitogen-activated protein kinase-activated protein kinase 2 (MK2) emerges as a pivotal target in developing anti-cancer therapies. The limitations of ATP-competitive inhibitors, due to insufficient potency and selectivity, underscore the urgent need for a covalent irreversible MK2 inhibitor. Our initial analyses of The Cancer Genome Atlas database revealed MK2's overexpression across various cancer types, especially those characterized by inflammation, linking it to poor prognosis and highlighting its significance. Investigating MK2's kinase domain led to the identification of a unique cysteine residue, enabling the creation of targeted covalent inhibitors. Compound 11 was developed, demonstrating robust MK2 inhibition (IC50 = 2.3 nM) and high selectivity. It binds irreversibly to MK2, achieving prolonged signal suppression and reducing pathological inflammatory cytokines in macrophages. Furthermore, compound 11 or MK2 knockdown can inhibit the tumor-promoting macrophage M2 phenotype in vitro and in vivo. In macrophage-rich tumor model, compound 11 notably slowed growth in a dose-dependent manner. These findings support MK2 as a promising anticancer target, especially relevant in cancers fueled by inflammation or dominated by macrophages, and provide compound 11 serving as an invaluable chemical tool for exploring MK2's functions.

A Long Life Moisture-Enabled Electric Generator Based on Ionic Diode Rectification and Electrode Chemistry Regulation.

Considerable efforts have recently been made to augment the power density of moisture-enabled electric generators. However, due to the unsustainable ion/water molecule concentration gradients, the ion-directed transport gradually diminishes, which largely affects the operating lifetime and energy efficiency of generators. This work introduces an electrode chemistry regulation strategy into the ionic diode-type energy conversion structure, which demonstrates 1240 h power generation in ambient humidity. The electrode chemical regulation can be achieved by adding Cl-. The purpose is to destroy the passivation film on the electrode interface and provide a continuous path for ion-electron coupling conduction. Moreover, this device simultaneously satisfies the requirements of fast trapping of moisture molecules, high rectification ratio transport of ions, and sustained ion-to-electron current conversion. A single device can deliver an open-circuit voltage of about 1 V and a peak short-circuit current density of 350 µA cm-2. Finally, the first-principle calculations are carried out to reveal the mechanism by which the electrode surface chemistry affects the power generation performance.

Bioinspired ion channel receptor based on hygroelectricity for precontact sensing of living organism.

Tactile sensors play an important role in human-machine interaction (HMI). Compared to contact tactile sensing, which leaves physical hardware vulnerable to wear and tear, proximity sensing is better at reacting to remote events before physical contact. The apteronotus albifrons possess ion channel receptors for remote surroundings perception. Inspired by the relevant ion channel structure and self-powered operation mode, we designed a new proximity sensor with ion rectification characteristics and self-powered capability. This bio-inspired ion channel receptor exploits the hygroelectric effect to convert the humidity information into a series of current signals when the living organism approaches, and it is insensitive to non-aquatic non-organisms. The sensor offers high sensitivity (2.3 mm-1), a suitable range (0-10 mm) for close object detection, fast response (0.3 s), and fast recovery (2.5 s). The unique combination of bio-sensitivity, non-contact detection characteristics, and humidity-based power generation capabilities enriches the functionality of future HMI electronics. As a proof of concept, the sensor has been successfully applied in different scenarios such as human health management, early warning systems, non-contact switches to prevent virus transmission, object recognition, and finger trajectory detection.

Sustainable power generation for at least one month from ambient humidity using unique nanofluidic diode.

The continuous energy-harvesting in moisture environment is attractive for the development of clean energy source. Controlling the transport of ionized mobile charge in intelligent nanoporous membrane systems is a promising strategy to develop the moisture-enabled electric generator. However, existing designs still suffer from low output power density. Moreover, these devices can only produce short-term (mostly a few seconds or a few hours, rarely for a few days) voltage and current output in the ambient environment. Here, we show an ionic diode-type hybrid membrane capable of continuously generating energy in the ambient environment. The built-in electric field of the nanofluidic diode-type PN junction helps the selective ions separation and the steady-state one-way ion charge transfer. This directional ion migration is further converted to electron transportation at the surface of electrodes via oxidation-reduction reaction and charge adsorption, thus resulting in a continuous voltage and current with high energy conversion efficiency.

Structural superlubricity in graphite flakes assembled under ambient conditions.

To date, structural superlubricity in microscale contacts is mostly observed in intrinsic graphite flakes that are cleaved by shearing from HOPG mesas in situ or friction pairs assembled in vacuum due to the high requirement of ultra clean interface for superlubricity, which severely limits their practical applications. Herein, we report observations on microscale structural superlubricity in graphite flake pairs assembled under ambient conditions, where contaminants are inevitably present at the interfaces. For such friction pairs, we find a novel running-in phenomenon, where the friction decreases with reciprocating motions, but no morphological or chemical changes can be observed. The underlying mechanism for the new running-in process is revealed to be the removal of third bodies confined between the surfaces. Our results improve the understanding of microscale superlubricity and may help extend the practical applications of superlubricity.

Evaluation of driver fatigue on two channels of EEG data.

Electroencephalogram (EEG) data is an effective indicator to evaluate driver fatigue. The 16 channels of EEG data are collected and transformed into three bands (θ, α, and ß) in the current paper. First, 12 types of energy parameters are computed based on the EEG data. Then, Grey Relational Analysis (GRA) is introduced to identify the optimal indicator of driver fatigue, after which, the number of significant electrodes is reduced using Kernel Principle Component Analysis (KPCA). Finally, the evaluation model for driver fatigue is established with the regression equation based on the EEG data from two significant electrodes (Fp1 and O1). The experimental results verify that the model is effective in evaluating driver fatigue.