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Managing stress is essential for mental and physical health, yet current methods rely on subjective self-assessments or indirect physiological measurements, often lacking accuracy. Existing wearable sensors primarily target a single stress hormone, cortisol, using single-point measurements that fail to capture real-time changes and distinguish between acute and chronic stress. To address this, we present Stressomic, a wearable multiplexed microfluidic biosensor for noninvasive monitoring of cortisol, epinephrine, and norepinephrine in sweat. Stressomic integrates iontophoresis-driven sweat extraction with bursting valve-regulated microfluidic channels for continuous sampling and analysis. Gold nanodendrite–decorated laser-engraved graphene electrodes achieve picomolar-level sensitivity, enabling simultaneous detection of multiple stress hormones. Electrochemical assays and human studies demonstrate that Stressomic reliably tracks hormone fluctuations in response to physical, psychological, and pharmacological stressors. Distinct temporal patterns reveal the dynamic interplay between the hypothalamic-pituitary-adrenal axis and the sympathetic nervous system. This platform enables continuous, multiplexed stress profiling, offering opportunities for early detection of maladaptive responses, personalized stress management, and deeper insights into stress biology. 

Abstract Recent advancements in wearable sensor technologies have enabled real-time monitoring of physiological and biochemical signals, opening new opportunities for personalized healthcare applications. However, conventional wearable devices often depend on rigid electronics components for signal transduction, processing, and wireless communications, leading to compromised signal quality due to the mechanical mismatches with the soft, flexible nature of human skin. Additionally, current computing technologies face substantial challenges in efficiently processing these vast datasets, with limitations in scalability, high power consumption, and a heavy reliance on external internet resources, which also poses security risks. To address these challenges, we have developed a miniaturized, standalone, chip-less wearable neuromorphic system capable of simultaneously monitoring, processing, and analyzing multimodal physicochemical biomarker data (i.e., metabolites, cardiac activities, and core body temperature). By leveraging scalable printing technology, we fabricated artificial synapses that function as both sensors and analog processing units, integrating them alongside printed synaptic nodes into a compact wearable system embedded with a medical diagnostic algorithm for multimodal data processing and decision making. The feasibility of this flexible wearable neuromorphic system was demonstrated in sepsis diagnosis and patient data classification, highlighting the potential of this wearable technology for real-time medical diagnostics. 

Abstract A synaptic memristor using 2D ferroelectric junctions is a promising candidate for future neuromorphic computing with ultra‐low power consumption, parallel computing, and adaptive scalable computing technologies. However, its utilization is restricted due to the limited operational voltage memory window and low on/off current (I_ON/OFF) ratio of the memristor devices. Here, it is demonstrated that synaptic operations of 2D In₂Se₃ferroelectric junctions in a planar memristor architecture can reach a voltage memory window as high as 16 V (±8 V) and I_ON/OFFratio of 10⁸, significantly higher than the current literature values. The power consumption is 10⁻⁵ W at the on state, demonstrating low power usage while maintaining a large I_ON/OFFratio of 10⁸compared to other ferroelectric devices. Moreover, the developed ferroelectric junction mimicked synaptic plasticity through pulses in the pre‐synapse. The nonlinearity factors are obtained 1.25 for LTP, −0.25 for LTD, respectively. The single‐layer perceptron (SLP) and convolutional neural network (CNN) on‐chip training results in an accuracy of up to 90%, compared to the 91% in an ideal synapse device. Furthermore, the incorporation of a 3 nm thick SiO₂interface between the α‐In₂Se₃and the Au electrode resulted in ultrahigh performance among other 2D ferroelectric junction devices to date. 

Abstract Glucosinolates (GSLs) are defensive secondary metabolites produced by Brassicaceae species in response to abiotic and biotic stresses. The biosynthesis of GSL compounds and the expression of GSL-related genes are highly modulated by endogenous signals (i.e. circadian clocks) and environmental cues, such as temperature, light, and pathogens. However, the detailed mechanism by which light signaling influences GSL metabolism remains poorly understood. In this study, we found that a light-signaling factor, ELONGATED HYPOCOTYL 5 (HY5), was involved in the regulation of GSL content under light conditions in Arabidopsis (Arabidopsis thaliana). In hy5-215 mutants, the transcript levels of GSL pathway genes were substantially upregulated compared with those in wild-type (WT) plants. The content of GSL compounds was also substantially increased in hy5-215 mutants, whereas 35S::HY5-GFP/hy5-215 transgenic lines exhibited comparable levels of GSL-related transcripts and GSL content to those in WT plants. HY5 physically interacts with HISTONE DEACETYLASE9 and binds to the proximal promoter region of MYB29 and IMD1 to suppress aliphatic GSL biosynthetic processes. These results demonstrate that HY5 suppresses GSL accumulation during the daytime, thus properly modulating GSL content daily in Arabidopsis plants. 

The concept of remote epitaxy involves a two-dimensional van der Waals layer covering the substrate surface, which still enable adatoms to follow the atomic motif of the underlying substrate. The mode of growth must be carefully defined as defects, e.g., pinholes, in two-dimensional materials can allow direct epitaxy from the substrate, which, in combination with lateral epitaxial overgrowth, could also form an epilayer. Here, we show several unique cases that can only be observed for remote epitaxy, distinguishable from other two-dimensional material-based epitaxy mechanisms. We first grow BaTiO₃on patterned graphene to establish a condition for minimizing epitaxial lateral overgrowth. By observing entire nanometer-scale nuclei grown aligned to the substrate on pinhole-free graphene confirmed by high-resolution scanning transmission electron microscopy, we visually confirm that remote epitaxy is operative at the atomic scale. Macroscopically, we also show variations in the density of GaN microcrystal arrays that depend on the ionicity of substrates and the number of graphene layers. 

Electrostatic capacitors are foundational components of advanced electronics and high-power electrical systems owing to their ultrafast charging-discharging capability. Ferroelectric materials offer high maximum polarization, but high remnant polarization has hindered their effective deployment in energy storage applications. Previous methodologies have encountered problems because of the deteriorated crystallinity of the ferroelectric materials. We introduce an approach to control the relaxation time using two-dimensional (2D) materials while minimizing energy loss by using 2D/3D/2D heterostructures and preserving the crystallinity of ferroelectric 3D materials. Using this approach, we were able to achieve an energy density of 191.7 joules per cubic centimeter with an efficiency greater than 90%. This precise control over relaxation time holds promise for a wide array of applications and has the potential to accelerate the development of highly efficient energy storage systems.