Chemical electron microscopy (CEM), a toolbox that comprises imaging and spectroscopy techniques, provides dynamic morphological, structural, chemical, and electronic information about an object in chemical environment under conditions of observable performance. CEM has experienced a revolutionary improvement in the past years and is becoming an effective characterization method for revealing the mechanism of chemical reactions, such as catalysis. Here, we mainly address the concept of CEM for heterogeneous catalysis in the gas phase and what CEM could uniquely contribute to catalysis, and illustrate what we can know better with CEM and the challenges and future development of CEM.

Hydrogen bonds are non-covalent interactions and essential for assembling supermolecules into ordered structures in biological systems, endowing crystals with fascinating physical properties, and inspiring the construction of eco-friendly electromechanical devices. However, the interplay between hydrogen bonding and the physical properties is not fully understood at the molecular level. Herein, we demonstrate that the physical property of biological crystals with double-layer structures could be enhanced by rationally controlling hydrogen bonding interactions between amino and carboxyl groups. Different hydrogen bonding interactions result in various thermal, mechanical, electronic, and piezoelectric properties. In particular, the weak interaction between O and H atoms contributes to low mechanical strength that permits important ion displacement under stress, giving rise to a strong piezoelectric response. This study not only reveals the correlation between the hydrogen bonding and physical properties in double-layer structures of biological crystals but also demonstrates the potential of these crystals as functional biomaterials for high-performance energy-harvesting devices. Theoretical calculations and experimental verifications in this work provide new insights into the rational design of biomaterials with desirable physical properties for bioelectrical devices by modulating intermolecular interactions.

This research aims to demonstrate a novel vortex ultrasound enabled endovascular thrombolysis method designed for treating cerebral venous sinus thrombosis (CVST). This is a topic of substantial importance since current treatment modalities for CVST still fail in as many as 20% to 40% of the cases, and the incidence of CVST has increased since the outbreak of the coronavirus disease 2019 pandemic. Compared with conventional anticoagulant or thrombolytic drugs, sonothrombolysis has the potential to remarkably shorten the required treatment time owing to the direct clot targeting with acoustic waves. However, previously reported strategies for sonothrombolysis have not demonstrated clinically meaningful outcomes (e.g., recanalization within 30 min) in treating large, completely occluded veins or arteries. Here, we demonstrated a new vortex ultrasound technique for endovascular sonothrombolysis utilizing wave-matter interaction-induced shear stress to enhance the lytic rate substantially. Our in vitro experiment showed that the lytic rate was increased by at least 64.3% compared with the nonvortex endovascular ultrasound treatment. A 3.1-g, 7.5-cm-long, completely occluded in vitro 3-dimensional model of acute CVST was fully recanalized within 8 min with a record-high lytic rate of 237.5 mg/min for acute bovine clot in vitro. Furthermore, we confirmed that the vortex ultrasound causes no vessel wall damage over ex vivo canine veins. This vortex ultrasound thrombolysis technique potentially presents a new life-saving tool for severe CVST cases that cannot be efficaciously treated using existing therapies.

The role of the human intestinal tract in host–microbe interactions has been highlighted in recent years. Several 3-dimensional (3D) models have been developed to reproduce the physiological characteristics of the human gut and to investigate the function of the gut microbiota. One challenge for 3D models is to recapitulate the low oxygen concentrations in the intestinal lumen. Moreover, most earlier 3D culture systems used a membrane to physically separate bacteria from the intestinal epithelium, which has sometimes made the studies of bacteria adhering to or invading cells less feasible. We report the establishment of a 3D gut epithelium model and cultured it at high cell viability under an anaerobic condition. We further cocultured intestinal bacteria including both commensal and pathogen directly with epithelial cells in the established 3D model under the anaerobic condition. We subsequently compared the gene expression differences of aerobic and anaerobic conditions for cell and bacterial growth via dual RNA sequencing. Our study provides a physiologically relevant 3D gut epithelium model that mimics the anaerobic condition in the intestinal lumen and supplies a powerful system for future in-depth gut–microbe interactional investigations.

Heptamethine cyanines (Cy7) are one of the most important dyes in bioimaging and phototherapy, but they often suffer from poor photostability or limited photothermal conversion efficiency. Here, a facile molecular engineering approach to regulating the photophysical properties of Cy7 by metal ions is demonstrated. By innovatively modifying the nitrogen with functional groups, a novel terpyridine-grafted nitrogen-terminated Cy7 scaffold (denoted as CydtPy) was synthesized and exhibited tunable photophysical properties when chelating with various metal ions (Mn²⁺, Fe²⁺, etc.). In comparison with metal-ion-free PEGylated CydtPy (LET-11), Mn²⁺-chelated LET-11 (namely, LET-11-Mn) exhibited the increased fluorescence emission intensity, and Fe²⁺-chelated LET-11 (namely, LET-11-Fe) showed the enhanced photostability with ~2-fold increase in photothermal conversion efficiency. By simply switching the chelated metal ion species, LET-11-Mn or LET-11-Fe could be used for near-infrared fluorescence imaging, magnetic resonance imaging, or photoacoustic imaging. Furthermore, LET-11-Fe displayed superior synergistic efficacy of photothermal therapy and chemodynamic therapy both in vitro and in vivo. This work not only provides a new strategy for regulating the photophysical properties of cyanine dyes but also establishes a versatile nanoplatform for cancer theranostics.

The growth of underwater robotic applications in ocean exploration and research has created an urgent need for effective tactile sensing. Here, we propose an underwater 3-dimensional tactile tensegrity (U3DTT) based on soft self-powered triboelectric nanogenerators and deep-learning-assisted data analytics. This device can measure and distinguish the magnitude, location, and orientation of perturbations in real time from both flow field and interaction with obstacles and provide collision protection for underwater vehicles operation. It is enabled by the structure that mimics terrestrial animals’ musculoskeletal systems composed of both stiff bones and stretchable muscles. Moreover, when successfully integrated with underwater vehicles, the U3DTT shows advantages of multiple degrees of freedom in its shape modes, an ultrahigh sensitivity, and fast response times with a low cost and conformability. The real-time 3-dimensional pose of the U3DTT has been predicted with an average root-mean-square error of 0.76 in a water pool, indicating that this developed U3DTT is a promising technology in vehicles with tactile feedback.

Multimode fibers hold great promise to advance data rates in optical communications but come with the challenge to compensate for modal crosstalk and mode-dependent losses, resulting in strong distortions. The holographic measurement of the transmission matrix enables not only correcting distortions but also harnessing these effects for creating a confidential data connection between legitimate communication parties, Alice and Bob. The feasibility of this physical-layer-security-based approach is demonstrated experimentally for the first time on a multimode fiber link to which the eavesdropper Eve is physically coupled. Once the proper structured light field is launched at Alice’s side, the message can be delivered to Bob, and, simultaneously, the decipherment for an illegitimate wiretapper Eve is destroyed. Within a real communication scenario, we implement wiretap codes and demonstrate confidentiality by quantifying the level of secrecy. Compared to an uncoded data transmission, the amount of securely exchanged data is enhanced by a factor of 538. The complex light transportation phenomena that have long been considered limiting and have restricted the widespread use of multimode fiber are exploited for opening new perspectives on information security in spatial multiplexing communication systems.

Tomato yellow leaf curl virus (TYLCV) dispersed across different countries, specifically to subtropical regions, associated with more severe symptoms. Since TYLCV was first isolated in 1931, it has been a menace to tomato industrial production worldwide over the past century. Three groups were newly isolated from TYLCV-resistant tomatoes in 2022; however, their functions are unknown. The development of machine learning (ML)-based models using characterized sequences and evaluating blind predictions is one of the major challenges in interdisciplinary research. The purpose of this study was to develop an integrated computational framework for the accurate identification of symptoms (mild or severe) based on TYLCV sequences (isolated in Korea). For the development of the framework, we first extracted 11 different feature encodings and hybrid features from the training data and then explored 8 different classifiers and developed their respective prediction models by using randomized 10-fold cross-validation. Subsequently, we carried out a systematic evaluation of these 96 developed models and selected the top 90 models, whose predicted class labels were combined and considered as reduced features. On the basis of these features, a multilayer perceptron was applied and developed the final prediction model (IML-TYLCVs). We conducted blind prediction on 3 groups using IML-TYLCVs, and the results indicated that 2 groups were severe and 1 group was mild. Furthermore, we confirmed the prediction with virus-challenging experiments of tomato plant phenotypes using infectious clones from 3 groups. Plant virologists and plant breeding professionals can access the user-friendly online IML-TYLCVs web server at https://balalab-skku.org/IML-TYLCVs, which can guide them in developing new protection strategies for newly emerging viruses.

Heart failure (HF), leading as one of the main causes of mortality, has become a serious public health issue with high prevalence around the world. Single cardiomyocyte (CM) metabolomics promises to revolutionize the understanding of HF pathogenesis since the metabolic remodeling in the human hearts plays a vital role in the disease progression. Unfortunately, current metabolic analysis is often limited by the dynamic features of metabolites and the critical needs for high-quality isolated CMs. Here, high-quality CMs were directly isolated from transgenic HF mice biopsies and further employed in the cellular metabolic analysis. The lipids landscape in individual CMs was profiled with a delayed extraction mode in time-of-flight secondary ion mass spectrometry. Specific metabolic signatures were identified to distinguish HF CMs from the control subjects, presenting as possible single-cell biomarkers. The spatial distributions of these signatures were imaged in single cells, and those were further found to be strongly associated with lipoprotein metabolism, transmembrane transport, and signal transduction. Taken together, we systematically studied the lipid metabolism of single CMs with a mass spectrometry imaging method, which directly benefited the identification of HF-associated signatures and a deeper understanding of HF-related metabolic pathways.

Active particles have been regarded as the key models to mimic and understand the complex systems of nature. Although chemical and field-powered active particles have received wide attentions, light-programmed actuation with long-range interaction and high throughput remains elusive. Here, we utilize photothermal active plasmonic substrate made of porous anodic aluminum oxide filled with Au nanoparticles and poly(N-isopropylacrylamide) (PNIPAM) to optically oscillate silica beads with robust reversibility. The thermal gradient generated by the laser beam incurs the phase change of PNIPAM, producing gradient of surface forces and large volume changes within the complex system. The dynamic evolution of phase change and water diffusion in PNIPAM films result in bistate locomotion of silica beads, which can be programmed by modulating the laser beam. This light-programmed bistate colloidal actuation provides promising opportunity to control and mimic the natural complex systems.