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Hydrogels are promising materials for constructing next-generation bioelectronics because of their excellent biocompatibility and mechanical compliance. Yet, creating robust and multifunctional hydrogel devices that conform to the surface of 3D organs remains challenging. Here, we report a biomimetic strategy for engineering ultrathin and ultrastrong hydrogel membranes as an advanced platform for organ-conformal bioelectronics. In these hydrogels, self-organized nanofiber networks confer strain-stiffening characteristics with a phenomenal combination of high mechanical strength (∼13.65 MPa), fracture toughness (∼21 573 J/m2), and low initial stiffness (∼600 kPa), which accommodates the construction of ultrathin membranes (∼10 μm thickness) reconciling mechanical robustness and 3D conformability. Theoretical simulations reveal unique strengthening mechanisms originating from the topological reconfiguration of fibrillar joints, indicating a widely applicable principle for designing soft composites involving 3D fibrillar networks. We show that various electronic components, including conducting polymers and wafer-fabricated microelectronic sensors, can be integrated on the ultrathin hydrogel membranes, providing means for multimodal physiological sensing and stimulation. These hydrogel membranes open paths to robust, functional and biocompatible interfaces with 3D soft organs and tissues, which are useful for epidermal electronics, implantable brain-machine interfaces, peripheral nerve stimulation, and many other bioelectronic applications.

Biocompatibility is the defining determinant for the clinical translation of implantable biomedical devices. As bioelectronics evolve toward softer, electroactive, and bioresorbable systems, traditional definitions of biocompatibility-largely focused on cytotoxicity and gross inflammation-are no longer sufficient. Instead, emerging bioresorbable devices demand multidimensional biocompatibility, encompassing immune modulation, mechanical and electrical matching, controlled degradation, and functional stability over clinically relevant time windows. This review offers a biocompatibility-focused overview of recent advances in bioresorbable materials and electronics, known as transient devices. Emphasis is placed on how material selection, device architecture, and degradation pathways jointly govern immune responses and tissue integration. A comparative framework is introduced to relate material classes to immune outcomes and degradation behaviors, and current biocompatibility evaluation metrics and international standards (ISO 10993) are critically discussed. Finally, we propose design guidelines and future research directions to accelerate the translation of next-generation bioresorbable electronics.

Soft electronic devices require durability to endure their inherent exposure to diverse mechanical deformations, including scratches, punctures, and repeated bending. Without intrinsic damage recovery mechanisms, such deformations inevitably compromise mechanical integrity and limit device lifetime. To address this issue, the strategic incorporation of reversible dynamic bonds enables autonomous self-healing while simultaneously achieving high mechanical toughness through energy dissipation during bond rupture. To this end, optimizing the glass transition temperature and bond exchange kinetics is essential to ensure sufficient chain mobility for rapid interfacial diffusion and autonomous mechanical recovery. Building on the reversible bond nature, this review presents emerging self-healable and tough soft electronics applications in three major areas: (1) Multimodal electronic skins capable of comprehensive physiological signal sensing; (2) modularly reconfigurable systems with adhesive-free interlayer bonding that enable user-on-demand device assembly; (3) optoelectronic devices that seamlessly integrate light-emitting and pressure-sensing capabilities. These applications demonstrate that dynamic bond engineering enables elastomeric devices to simultaneously achieve mechanical robustness, functional adaptability, and autonomous self-healing. Such advancements position them as durable platforms with extended operational lifetimes, paving the way for next-generation wearable and implantable bioelectronics in real-world applications.

This work set out to establish an easily applicable system to improve a broad range of bioelectronic devices using the SpyTag-SpyCatcher crosslinking system together with one of the model organisms for extracellular electron transport, Shewanella oneidensis. Therefore, the surface-displayed c-type cytochrome MtrC was equipped with an accessible SpyTag and coupled to SpyCatcher-functionalized surfaces. A transposon screen followed by nanopore sequencing was conducted in order to identify integration positions which facilitate MtrC functionality while the SpyTag is surface accessible. Three integration positions (W314, Y417, T603) were chosen for further characterization. Expression of the MtrC-SpyTag constructs in a S. oneidensis strain lacking all outer membrane cytochromes restored the ability to reduce an extracellular electron acceptor. Two of the three strains reached reduction rates at the wildtype MtrC level proving that the integrated SpyTag does not hamper extracellular electron transfer. In vivo, all three constructs showed significantly better binding properties to SpyCatcher functionalized magnetic beads than the wildtype MtrC control. The two most promising candidates were coupled to conductive, magnetic gold nanoparticles and directed towards a screen-printed electrode showcasing how MtrC-SpyTag expression can improve bioelectronic devices. A significantly higher charge transfer compared to the wildtype control was reached in linear sweep voltammetry and chronoamperometry experiments. Moreover, a shift towards direct electron transfer was observed which reduces the problem of redox shuttle washout in flowthrough systems. Direct binding of the cells to SpyCatcher functionalized electrodes enabled robust current production even after thorough washing of the electrodes while control cells failed to produce current under these conditions. The versatile SpyCatcher toolbox can be used together with the here reported strains to eliminate bottlenecks in bioelectronics like poor biofilm formation or the production of an insulating extracellular polymer matrix.

As one of the most classical and well-characterized enzymes in modern biochemistry, lactate dehydrogenases (LDHs) are versatile oxidoreductases with broad functional and technological relevance. They serve as central components in diagnostic kits, biosensors, bioelectronics, and biocatalytic systems. Bacterial LDHs, in particular, stand out for their intricate regulatory features and remarkable robustness, making them suitable for industrial applications and necessitating a rational framework for their redesign. This paper reviews the structural attributes and catalytic mechanisms of both D-LDHs and L-LDHs from diverse bacterial species, highlighting the molecular determinants that govern their distinct enzymatic behaviors. The functions of key amino acid residues involved in catalysis, allosteric regulation, and cofactor binding are discussed, together with recent advances in genetic engineering and immobilization strategies that enhance enzyme yield and stability. Collectively, these insights provide a conceptual framework for the rational design of LDH variants with properties tailored to specific applications. Finally, unresolved literature gaps, emerging opportunities, and prospective directions for bacterial LDHs are explored in relation to their expanding roles in biotechnology across the environmental, medical, and materials sciences.

Organic electrochemical transistors (OECTs) are promising for bioelectronics and low-power logic owing to their mixed ionic-electronic conduction and mechanical softness. However, thermoelectric gating of OECTs remains unexplored due to the incompatibility of rigid, electronically dominated thermoelectric modules with hydrated soft systems. Here, we introduce printable thermoelectric ionogels with n-p convertible thermopower, where the Seebeck coefficient is tunable from -3.61 to +9.74&#xa0;mV K- 1 through facile [EMIm][Cl] doping. These ionogels act simultaneously as thermoelectric legs and ionic dielectrics, enabling direct integration with OECTs to realize soft, complementary p-n thermoelectric modules. We demonstrate thermoelectric gating of both BBL- and p(g2T-T)-based OECTs, achieving high on/off ratios (>103) and robust transconductance under low temperature gradients (<30 K), while retaining mechanical stretchability. This strategy provides a general framework for coupling thermoelectric functionality with OECTs, opening new avenues for energy-autonomous, flexible electronics with built-in thermal sensing and adaptive control.

ConspectusEumelanin, the ubiquitous brown-black pigment, is renowned for its remarkable photoprotective properties across the natural world. Its broadband absorption across the UV-visible region enables the efficient capture of solar radiation, while its photoprotective efficiency arises primarily from the ultrafast deactivation of excited states. Multiple nonradiative decay pathways rapidly funnel electronic energy into harmless vibrational motion before reactive intermediates can accumulate. These functions are intimately connected to eumelanin's complex molecular and supramolecular organization. Unlike conventional chromophores with well-defined structures, eumelanin exists as a chemically heterogeneous ensemble of indole-derived building blocks present in multiple oxidation states, linked through diverse coupling motifs and organized through dynamic aggregation. This intrinsic chemical and electronic disorder, reinforced by supramolecular interactions such as &#x3c0;-&#x3c0; stacking and hydrogen bonding, generates layered nanostructures and hierarchical particles. Rather than being detrimental, this disorder contributes to eumelanin's featureless absorption spectrum and ultrafast excited-state deactivation, which together underpin its photoprotective function.In this Account, we describe our efforts to disentangle this complexity by examining eumelanin across multiple length scales, ranging from well-defined monomers and synthetically modified derivatives to structurally ordered multimers and supramolecular aggregates. Using steady-state and time-resolved spectroscopy in combination with electronic structure calculations, we map the pathways through which eumelanin dissipates excited-state energy. A fundamental theme that emerges is the interplay between structural disorder and excited-state dynamics. By resolving the crystal structures of the key eumelanin monomers, 5,6-dihydroxyindole (DHI) and 5,6-dihydroxyindole-2-carboxylic acid (DHICA), we establish a structural framework for probing their excited-state behavior. These crystalline assemblies reveal exciton delocalization and demonstrate how molecular packing influences photophysical properties. Extending from monomers to covalently linked oligomers and supramolecular assemblies uncovers amplified excitonic interactions that broaden electronic absorption and accelerate nonradiative decay, reflecting eumelanin's natural photoprotective function. At the same time, synthetic analogues and engineered derivatives demonstrate that eumelanin-inspired systems need not be limited to natural photoprotection. Heavy-atom substitution, for example, can enhance intersystem crossing and stabilize long-lived triplet states, enabling controllable delayed emission. Similarly, supramolecular organization determines whether delayed emission occurs through delayed fluorescence or phosphorescence, highlighting aggregation as a powerful handle for tuning excited-state dynamics. These findings suggest that eumelanin-inspired materials can be rationally engineered for applications in light harvesting, bioelectronics, photomedicine, and related technologies. By integrating synthetic design, spectroscopic investigation, and theoretical analysis across multiple structural levels, our work outlines a systematic approach for understanding and controlling the relationship between structural disorder and excited-state dynamics in eumelanin and related functional biomaterials.

Epidermal patches are multifunctional skin-interfacing platforms with applications spanning wound management, real-time biosensing, drug delivery, and tissue regeneration. Hydrogels play a central role due to their mechanical compliance, water-rich composition, and tunable physicochemical properties. Key design features flexibility, stretchability, self-healing, and self-adhesion, which ensure stable skin contact and device stability. Tailored electrical conductivity, enabled by conductive polymers, fillers, and novel fabrication strategies, allows seamless integration with bioelectronics for intelligent health monitoring. Fabrication innovations, such as 3D/4D printing, stereolithography, digital light processing, extrusion-based writing, inkjet printing, electrospinning, and microneedle-based platforms, allow precise spatial control and multifunctional integration. Emerging approaches, including AI-assisted biosensing, stimuli-responsive drug release, noninvasive skin metabolite monitoring, and biodegradable systems, further expand their potential. Applications range from infection-resistant wound dressings and minimally invasive drug delivery to acne therapy, cardiac patches, and hydrogel micropatch probes for skin metabolomics. Challenges remain in achieving scalable manufacturing, long-term durability, and material sustainability. Future development will converge intelligent hydrogel design, integrated biosensing, data-driven analytics, advanced metabolomics, and personalized transdermal therapeutic, transforming epidermal patches from passive materials into adaptive, closed-loop biointerfaces capable of sensing, decision-making, and on-demand intervention. By uniting therapeutic, diagnostic, and protective functions, hydrogel-based epidermal patches are set to revolutionize personalized healthcare.

Soft neural interfaces require encapsulation materials that simultaneously provide mechanical compliance, thermal safety, and long-term barrier reliability, yet conventional polymers suffer from poor thermal transport, while inorganic coatings compromise flexibility. Here, we present a polyisobutylene-based nanocomposite encapsulation incorporating hexagonal boron nitride (PIB-hBN) that enhances thermal conductivity while preserving the low modulus and elastic stretchability required for soft neural implants. The PIB-hBN nanocomposite exhibits increased in-plane and through-plane thermal conductivities compared to pristine PIB, resulting in improved heat dissipation during electrically driven operation. Thermal cycling measurements using surface temperatures constrained to 37 &#xb0;C show that maintaining the PIB-hBN surface allows higher heat source temperatures while remaining within safety limits during dynamic operation. Mechanical durability and moisture barrier performance are systematically evaluated, demonstrating reliability comparable to established soft encapsulation materials while offering superior thermal transport. Conformal integration with a peripheral nerve mock-up further demonstrates compatibility with implantable device architectures.

The rapid growth and accessibility of artificial intelligence (AI) and machine learning (ML) have opened many avenues to revolutionize biomedical research, particularly in oncogenesis. Oncogenesis is a hallmark process in the development of cancer, involving the amplification of proto-oncogenes and the subsequent dysregulation of molecular signaling networks. These pathways-including the RAS/RAF/MEK/ERK, PI3K-AKT, JAK-STAT, TGF-&#x3b2;/Smad, Wnt/&#x3b2;-Catenin, and Notch cascades-have been studied extensively in isolation, with major strides achieved in understanding how they drive cancer. However, there are still many considerations regarding how these networks interact. Ongoing studies show that crosstalk among these pathways occurs through feedback loops, shared intermediates, and compensatory activation, creating a complex network that enables tumor cells to adapt and metastasize. New developments in AI and ML have enabled modeling and prediction of these interactions for pathway discovery, mapping oncogenic crosstalk, predicting drug resistance and therapeutic responses, and complex data analysis. Novel technologies such as feature selection algorithms and convolutional neural networks have demonstrated immense translational potential to bridge computational predictions in cancer genomics with clinical applications. Similar models have also proven useful for learning from genomic datasets and reducing multidimensionality in heterogeneous multiomics data. As current AI/ML approaches continue to develop, it is also important to consider the limitations of batch effects, model generalizability, and potential bias in training datasets. This review aims to integrate the most recent AI and ML applications in uncovering the hidden interactions within oncogenic networks that drive tumorigenesis, heterogeneity, and resistance to therapies. Moreover, this review aims to synthesize the functionality of emerging computational methods that elucidate these insights, as well as the transformative implications of AI-guided systems biology on precision oncology and combinatorial therapies.

Studying synaptic transmission is facilitated in experimental systems that isolate individual neuronal connections. We developed an integrated platform combining polydimethylsiloxane (PDMS) microstructures with high-density microelectrode arrays to isolate, record, and manipulate neuronal pairs from human induced pluripotent stem cell (hiPSC)-derived neurons. The system maintained hundreds of parallel neuronal pairs for over 100 days, demonstrating functional synapses through pharmacological validation. We coupled this platform with a biophysical Hodgkin-Huxley model and simulation-based inference to extract mechanistic parameters from the electrophysiological data. As a proof-of-concept application, we analyzed shifts in model parameter distributions following a stimulation protocol. The biophysical model revealed &#x3b1;-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) and N-methyl-D-aspartate (NMDA) receptor-specific alterations after stimulation, providing quantitative insights into synaptic plasticity mechanisms. This integrated approach combines isolated hiPSC-derived synaptic pairs, stable parallel long-term recordings, and mechanistic modeling to enable systematic studies of human synaptic transmission.

This study introduces a robust selective on-chip DNA synthesis platform utilizing an electric field-assisted polymerase chain reaction (E-PCR) system based on a microelectrode array. We demonstrate the use of electric field manipulation for the selective immobilization of DNA and enzyme-mediated single-stranded DNA synthesis, achieving precise spatial control at the microscale. By optimizing electric field patterns, we achieved high-efficiency synthesis and addressed critical challenges in electrochemical stability and DNA integrity. The E-PCR system enables selective DNA synthesis, length-controlled synthesis, and sensitive nucleic acid detection. Our findings provide a scalable foundation for high-throughput enzymatic synthesis, offering significant potential for DNA data storage, synthetic biology, and molecular diagnostics.

To examine concurrent validity between the Bayley Scales of Infant and Toddler Development, Fourth Edition (Bayley-4) gross motor subtest and the Alberta Infant Motor Scale (AIMS), and evaluate agreement among the Bayley-4 (full test and gross motor subtest), AIMS, and Hammersmith Infant Neurological Examination (HINE) in identifying atypical development at 12&#x2009;months of age. This cross-sectional observational study included Bayley-4, AIMS, and HINE scores from 123 children (56 females, 67 males) with varied risk profiles at approximately 12&#x2009;months of age. Concurrent validity was assessed using Spearman's rank correlation of raw scores. Agreement was evaluated using Cohen's kappa (k) and evidence-based thresholds of typicality for each assessment. Additional assessment comparisons, including AIMS and HINE, were conducted for benchmarking. The Bayley-4 gross motor subtest was strongly correlated (r&#xa0;=&#xa0;0.90, p&#x2009;<&#x2009;0.01) with the AIMS. Both the Bayley-4 full test and gross motor subtest demonstrated substantial agreement with the AIMS 5th centile (k&#xa0;=&#xa0;0.72-0.73) and fair agreement (k&#xa0;=&#xa0;0.28-0.32) with the HINE. By comparison, the AIMS and HINE were moderately correlated (r&#xa0;=&#xa0;0.48), with fair agreement (k&#xa0;=&#xa0;0.34). This study provides the first evidence of concurrent validity and agreement for the Bayley-4, supporting its use as a reliable developmental assessment in clinical and home settings. The Bayley-4 aligned more closely with the motor-focused AIMS than with the neurologically focused HINE.

Cardiorespiratory coupling (CRC) reflects coordination between heart and lung function, but how it changes with increasing intensity during graded exercise remains unclear. We investigated CRC as real-time covariation between cardiac timing and breath-by-breath pulmonary oxygen uptake (VO2) to test whether coupling strengthens with workload in adolescent athletes. We conducted an observational, within-subject analysis of the ACTES cycling dataset. Eighteen adolescents cycled at 50, 110, and 140&#x2009;W. Beat-to-beat RR intervals and pulmonary VO2 time series were examined in ultra-short 60 s segments. Fluctuations were summarized using SDRR/RMSSD and SDVO2/RMSSDVO2. CRC was measured using joint symbolic dynamics (JSD; Shannon entropy, SE, and Miller-Madow-corrected entropy, CSE) and the highest normalized cross-correlation (X-Corr). Mean RR decreased and mean pulmonary VO2 increased with workload (both p&#x2009;<&#x2009;0.0001). SDRR and RMSSD were lower at 110 and 140&#x2009;W versus 50&#x2009;W; SDVO2 declined from 50 to 110/140&#x2009;W, whereas RMSSDVO2 was unchanged. X-Corr increased from 50 to 110/140&#x2009;W (p&#x2009;&#x2264;&#x2009;0.0014). JSD indices decreased as workload increased (SE: global p&#x2009;=&#x2009;0.139; CSE: global p&#x2009;=&#x2009;0.029), suggesting tighter CRC. CRC becomes more pronounced with increased workload, aligning with reduced heart rate variability and reflecting vagal withdrawal and reflex responses that improve heart-lung integration in adolescent athletes.

Charge transport underpins essential biological processes, including cellular respiration, photosynthesis, and enzymatic catalysis. Advances in molecular electronics have enabled single-molecule measurements that unequivocally establish redox-active proteins as efficient electron conductors, with their metal cofactors serving as intrinsic redox relays. By contrast, ubiquitous non-redox proteins lacking such redox centers have long been considered poor conductors. However, recent research has challenged this view, demonstrating that efficient charge transport in non-redox proteins can be mediated through polypeptide backbones, aromatic side-chain arrays, and hydrogen bond networks. This review surveys progress in understanding the single-molecule conductance of non-redox proteins. Firstly, we elucidate the fundamental transport mechanisms, highlighting the interplay between coherent tunneling and thermally activated hopping. We then provide an overview of state-of-the-art experimental techniques for single-molecule characterization. Through analysis of diverse systems spanning short peptides to large enzymes, we illustrate how aromatic amino acid networks and dynamic conformational fluctuations govern conductance, enabling emerging applications in label-free biosensing and single-molecule protein/DNA sequencing. Finally, we discuss persistent challenges and outline future opportunities for integrating protein-based conductors into bioelectronic devices. This review aims to stimulate further research and pave the way for novel applications harnessing protein conductance.

Photoacoustic configuration studies were performed to measure the water vapor permeability of the polymeric PVDF transfer membranes with a pore size of 0.45 &#xb5;m and a thickness of 117 and 119 &#xb5;m, taking advantage of the characteristic that the polyvinylidene difluoride (PVDF), once polarized by the corona poling, creates a piezoelectric polymer. Polymeric membrane measured polarized as a piezoelectric polymer and an unpolarized ferroelectric polymer. Polarized and non-polarized PVDF membranes were developed for the two experimental photoacoustic detection of permeability tests; the first one was used to measure the humidity of bi-distilled water, and the second one was characterized with artificial tears. The obtained results show that PVDF membrane has different permeability coefficient for water and artificial tears, and at the same time, pores in the tested membranes change sizes depending on the liquid used. The results of the permeability and pore size of the PVDF membranes provide insight into vapor transport mechanisms that may inform the future development of humidity sensors.