Droplet manipulation technology plays a crucial role in academic research and engineering applications. However, current manipulation technology requires integrated circuits and electrode configurations, which introduce the risk of short circuits and droplet cross-contamination during operation. Herein, we developed an omnidirectional wireless electro-droplet manipulation system (WEDMS) without using electrode/circuit control that obviates droplet cross-contamination to precisely manipulate droplet movement in separated or isolated space. This system innovatively generates localized electric fields through the synergistic effects of dielectric polarization and air discharge, achieving a noncontact, electrode-free droplet charging and driving strategy. It achieves synchronous movement of the slider and droplets via hand movement, enhancing droplet operation flexibility and human–droplet interaction on triboelectric nanogenerators. Moreover, WEDMS is capable of manipulation droplets with high speed across a wide range of volumes (10 to 2,000 μl) and effective control of droplets in both gas and oil phases, achieving a series of manipulations such as droplet positioning, chemical reactions, flexible steering, and droplet climbing, showcasing an innovative, efficient, portable, and comprehensive droplet manipulation strategy. Based on the prominent advantages of WEDMS in structural simplicity and high-efficiency control, its adaptability in multidisciplinary microfluidic applications can be further enhanced, demonstrating tremendous potential in drug delivery, green chemical synthesis, and environmental monitoring.

tRNA-derived small RNAs (tsRNAs) or tRNA-derived fragments (tRFs) are an important class of regulatory molecules whose role in cardiac hypertrophy remains largely unknown. Here, we identified a novel tRF contributing to the regulation of cardiac hypertrophy that we termed CHAtRF (cardiac hypertrophy-associated tRF). The CHAtRF level was increased in mice and in patients with cardiac hypertrophy. CHAtRF deficiency attenuated angiotensin II (AngII)-induced cardiac hypertrophy and restored the heart function, while CHAtRF overexpression enhanced hypertrophic responses. Mechanistically, CHAtRF directly interacts with SRSF5 and blocks SRSF5 to bind with Psmg4 pre-mRNA, which mediates alternative splicing of Psmg4 pre-mRNA and promotes exon 2 skipping of Psmg4. CHAtRF-dependent alternative splicing of Psmg4 inhibits the expression of Psmg4 full-length isoform, resulting in progression of pathological hypertrophy. The ability of CHAtRF to regulate hypertrophy was confirmed in hiPSC-CMs, and CHAtRF serum levels are higher in individuals with myocardial hypertrophy or heart failure. Our findings reveal new insights into the previously unrecognized role of tsRNAs during cardiac hypertrophy, which provide potential novel therapeutic targets for pathological hypertrophy and might serve as potential biomarkers for diagnosing cardiac hypertrophy and heart failure.

Behavior plays a critical role in health and disease. Although molecular omics have advanced the understanding of biological mechanisms, they alone cannot explain the role of behavior in health, and traditional behavioral measurement technologies have struggled to capture the dynamic, multidimensional, and heterogeneous nature of real-world behaviors. With the development of digital technologies such as wearable devices, smartphone sensors, and ecological momentary assessment, behavioromics has emerged as a new research paradigm with a holistic systems perspective, integrating continuous, multimodal behavioral data with molecular, physiological, and environmental information. By organizing behavioral measurement, modeling, and interpretation within a unified analytical framework, behavioromics reveals dynamic behavioral patterns, supports mechanism-informed inference, and identifies actionable targets for early intervention. Despite ongoing challenges in data heterogeneity, causal interpretation, and ethical governance, behavioromics holds promise for reshaping disease prediction, early detection, and precision intervention, and for advancing proactive health through earlier, behavior-centered prevention.

To reduce mental disorder prevalence, the understanding of resilience to stress-related disorder and its neurobiological mechanisms has come into the focus of biomedical research to develop both biologically rooted prevention and innovative therapeutic approaches for stress-related disorder. While some resilience mechanisms have been exemplified on the molecular, cellular, and brain-regional level, evidence on the neural systems level is rather sparse. We present the first translational evidence of adaptive plasticity in visual microcircuits and top-down modulation onto the visual system as a neurobiological resilience mechanism at the neural systems level in both humans and mice. In humans, we demonstrate that this adaptive microcircuit plasticity is linked to interactions between neurocognitive domains—executive and perceptual—and between brain regions—frontal and occipital—in specific oscillatory frequencies (β band in frontal inferior frontal gyrus and γ band in occipital V2). Additionally, expanding upon prior resilience research, our findings offer further evidence that phenotypic resilience is associated not only with macro- and microcircuit plasticity but also with better performance in neurocognitive functions central to resilience, i.e., perceptual discrimination in mice and cognitive control in humans. In mice, using awake 2-photon calcium imaging, we observed distinct resilient and susceptible network phenotypes in mouse visual cortex. Resilient animals surpassed both susceptible animals and nonstressed controls in their ability to encode visual afferents. This suggests an improved performance supporting the concepts of posttraumatic growth and stress inoculation on a neurobiological level. Resilience at the neural systems level involves active, dynamic processes rather than being merely passive responses to stress and constitutes a first example that neural network states of resilience are metastable, self-stabilizing, and noncontinuous entities that could serve as a target for new neural network interventions for fostering resilience.

Parity–time and anti-parity–time symmetries, originally formulated in the context of non-Hermitian quantum mechanics, have now been experimentally realized across diverse physical platforms, including photonic, wave-guiding, acoustic, and mechanical systems, as well as systems operating near exceptional points. While the active manipulation of these symmetries has been well explored in wave-based systems, their implementations in diffusive physics have long remained predominantly confined to static phases, where systems are locked in a fixed symmetric or symmetry-broken configuration due to their invariant structural parameters. Bridging this gap, recent work has introduced and verified the concept of temporal anti-parity–time symmetry, demonstrating that energy transport in diffusive media can be actively programmed in the time domain.

Evaluating chemical toxicity and its potential hazards to human health and the environment is essential in diverse fields, including medicine, industry, and agriculture. Multi-species acute toxicity prediction (MSATP) is critical in toxicity assessment. Traditional methods rely on exposing animals to a single high dose of a compound and observing its toxicity. However, with growing ethical concerns regarding animal testing, advancements in computational technology have positioned the artificial intelligence-based MSATP as an efficient alternative. Current research on MSATP commonly employs multi-task deep neural networks for modeling. However, the small size, high dimensionality, and sparsity of MSATP tabular data render them unsuitable for neural network approaches. To address this, we proposed a multi-task cascade forest framework for MSATP. This framework integrated feature enhancement through knowledge transfer, sample enhancement using a greedy search strategy with the covariance distance measure. The framework accommodated tasks of varying sizes in multi-task learning and was specifically designed for tabular data, achieving a 12% improvement in performance compared to current state-of-the-art methods (R2 equals to 0.64, root mean square error equals to 0.57). In a single-view context, we conducted ablation experiments to validate the effectiveness of the data enhancement strategy and introduced external dataset experiments to assess the generalization capability of the proposed method for cross-species prediction. In a multi-view context, the feature fusion method and consensus ensemble were demonstrated to further enhance the model performance. Additionally, we analyzed feature importance vectors to provide interpretable insights into species toxicity correlations. Overall, this framework effectively addressed MSATP tasks and exhibited substantial potential for application in various toxicity prediction domains.

Aqueous ammonium-ion (NH4+) batteries/capacitors, recognized for inherent high safety and fast diffusion kinetics, are a promising alternative for sustainable energy storage. However, the development of ammonium-ion energy storage devices has been hindered by the poor compatibility between the distinctive solvation structure of NH4+ ions and conventional organic electrode materials, especially under low-temperature conditions. Here, a redox-active conjugated polymer with self-selective coordination mechanism is designed for achieving high-rate and low-temperature performance. The electron delocalization induced by the conjugated backbone facilitates rapid electronic transport in electrodes, delivering an ultrahigh-rate capacity of 107 mAh g−1 at 20 A g−1 under 25 °C and stable cycling performance with 99% capacity retention under −50 °C. Theoretical calculations and experimental investigations reveal that the inherent structural self-selectivity renders symmetrically arranged carbonyl groups as active binding sites for NH4+ storage, leading to a reversible 4-electron coordination process. Hence, the assembled all-organic hybrid ammonium-ion capacitor enables a long cycle life for over 3,000 cycles at −50 °C, which surpasses the lowest operating temperature reported for ammonium-ion devices, thus propelling the advancement of ammonium-ion energy storage technologies at low temperatures.

The maintenance and regulation of cancer stem cell (CSC) stemness are crucial for tumor progression; however, the mechanisms underlying tumor stemness regulation remain poorly understood. Herein, we discovered that the enhanced hypoxia-induced transforming growth factor beta induced protein (TGFBI) in bladder cancer (BLCA) promotes the establishment of a stemness loop in the tumor microenvironment, facilitating the maintenance of CSC stemness and malignant proliferation. Clinically, the upregulation of hypoxic TGFBI in BLCA correlates with malignant BLCA features and poor prognosis. Mechanically, TGFBI can stabilize the structural integrity of disulfide bonds in Cys48 and Cys77 of growth differentiation factor 15 (GDF15), leading to aberrant function activity of GDF15 and secretion. Interestingly, secreted GDF15 consequently not only further upregulates CSC-related gene expression but also induces the activation of cancer-associated fibroblasts through the transforming growth factor beta receptor type 2 (TGFBR2)–transforming growth factor β (TGFβ)–TGFBI self-regulatory feedback loop to promote stemness in BLCA. TGFBI knockdown or GDF15 inhibition results in a decrease in functional proteins associated with stemness maintenance, which suppresses bladder CSCs’ self-renewal and effectively improves the efficacy of chemotherapy. Together, these findings demonstrate the pivotal role of TGFBI in BLCA’s stemness maintenance and BLCA progression, highlighting that the inhibition of the TGFBI/GDF15 axis is a potential therapeutic strategy for the amelioration of cancer chemotherapy.