Simultaneous monitoring of multiple protein–protein interactions in live cells remains a key challenge in biology and drug discovery. While multiplexed FRET enables parallel molecular readouts, existing approaches are often constrained by spectral overlap, complex instrumentation, or incompatibility with live-cell models. To overcome these limitations and increase accessibility to the broader biological community, we present multiplexed dark FRET (MDF), a genetically encoded platform that uses spectrally distinct donors (mNeonGreen, mScarlet-I3) paired with nonemissive acceptors (ShadowY, ShadowR). We first establish that MDF fluorophores exhibit minimal background FRET under co-expression, enabling clean separation of donor lifetimes under multiplexed conditions. Using fluorescence lifetime (FLT) detection, we demonstrate MDF’s versatility through three biologically and translationally relevant examples: (1) cell-type-specific biosensing in organoids, as exemplified in 3D neuro-glial spheroids; (2) target specificity for drug discovery through discrimination of TNFR1 versus TNFR2 receptor conformations and selective FLT modulation by receptor-specific small molecules; and (3) protein misfolding, as exemplified through simultaneous monitoring of alpha-synuclein oligomerization and misfolding. We further show that MDF can be applied within a single cellular environment, demonstrating the feasibility of same-cell multiplexing under optimized transient transfection conditions. MDF provides a scalable framework for real-time, live-cell biosensing across high-throughput, target-specific, and tissue-level applications in complex biological systems.

Nonlinearity, baseline drift, humidity interference, and selectivity are among the primary challenges associated with direct current measurements in semiconducting gas sensors today. This study demonstrates that integrating PtSnO2 and MXene-based sensors enables high-performance gas sensing by effectively mitigating humidity-induced interference. Impedance measurements across multiple frequencies were employed, yielding sensors with tunable gas responses, low noise, extended dynamic range, enhanced baseline stability, and minimal humidity cross-sensitivity. PtSnO2 was optimized for simultaneous NH3 and relative humidity (RH) detection, while MXene served as a dedicated RH sensor. A multilayer perceptron was trained on the impedance dataset to deconvolute and accurately predict RH and NH3 concentrations. The proposed sensor system and analytical framework were benchmarked against commercial DHT22 (humidity) and DFrobot (NH3) sensors, demonstrating superior performance and sensitivity. This methodology is extendable to other material systems, including metal oxides and transition metal dichalcogenides, for advanced gas-sensing applications. These findings advance gas-sensing technology by improving detection accuracy and robustness in industrial safety, environmental monitoring, and biomedical diagnostics, including early disease detection.

Ideally, the half-cell potential of an organic-electrolyte-based reference electrode is determined by equilibrium distribution of the organic electrolyte across the interface between an organic-electrolyte-doped membrane and the aqueous sample. The limit of applicability (LOA) of these reference electrodes is reached when sample ions transfer into the reference membrane at high concentrations. Recent insights highlight the need to evaluate the lipophilicity of the organic electrolyte's anions and cations separately; however, accurate predictions of the LOAs also require consideration of ion fluxes. LOAs are influenced not only by the concentration of interfering sample ions but also by the mobilities of the organic electrolyte and interfering ions in the sample and membrane. This was recently shown with numerical simulations and described with expressions for limiting cases in which the interfering ion enters the membrane by either ion exchange with the organic electrolyte ion of the same charge sign or co-extraction with the organic electrolyte ion of opposite charge sign. More general expressions describing LOAs that take diffusion into account and apply when ion exchange and co-extraction occur simultaneously have been missing. Here, a quasi-steady-state model is presented that describes the LOAs based on organic electrolyte partitioning, ion exchange, and diffusive mass transfer limitations. Depending on the lipophilicity of the organic electrolyte and the rate of diffusion in the membrane, four limiting cases can be identified. Above the LOA, these reference electrodes exhibit characteristic sub-Nernstian, Nernstian, or super-Nernstian responses to the sample ions. The respective LOAs can be quantitatively predicted as a function of sample composition using two straightforward equations.

Chemoresistive metal oxide gas sensors typically exhibit predictable resistance changes upon exposure to oxidizing or reducing gases, depending on their semiconductor type. However, anomalous concentration-dependent inversion of response has been reported, often attributed to intrinsic material properties. In this study, we investigate such inversion phenomena in Cr2O3-based sensors doped with Ti(IV), W(VI), and Ni(II), alongside Ag-decorated WO3 sensors. Initial observations suggested inversion of response to low concentrations of O2, consistent with prior hypotheses involving carrier-type transitions. However, systematic experiments revealed that this inversion was not intrinsic but rather caused by trace water contamination in the analyte gas stream. Only through cryogenic drying of the analyte gases was the expected sensor behavior restored. Mass spectrometry confirmed water as the sole contaminant responsible. Further tests demonstrated that water induces a rapid resistance increase in p-type Cr2O3 sensors, mimicking an n-type response. These findings highlight the critical influence of humidity on sensor behavior and suggest that some previously reported inversion phenomena may stem from undetected water interference. This work underscores the necessity of rigorous gas stream purification in low-concentration gas sensing studies.

Sweat, as a byproduct of human metabolism, can offer valuable insights for individual health monitoring and disease diagnosis. Traditional sweat detection devices face limitations including poor mechanical performance and low sensitivity. To overcome these challenges, we report a wearable surface-enhanced Raman scattering (SERS) sensor based on MXene-Au@Ag NPs core-shell structures integrated with a polyvinyl alcohol (PVA) hydrogel. The uniform deposition of Au@Ag NPs on MXene nanosheets generated high-density electromagnetic "hot spots," significantly enhancing SERS activity. The PVA hydrogel substrate not only endowed the sensor with excellent flexibility and mechanical stability but also facilitated efficient sweat collection and analyte enrichment. This sensor demonstrated ultrasensitive detection of creatinine (2.7 × 10-9 M) and uric acid (3.6 × 10-8 M), with strong linear correlations (R2 = 0.993 and 0.997), and could simultaneously monitor sweat pH. Practical trials with human volunteers confirmed the sensor's reliable, real-time quantification of biomarker concentrations and dynamic pH in sweat during exercise, validated using a portable Raman spectrometer. With its high uniformity (RSD = 7.02%), mechanical durability, and stable performance under repeated deformation, this wearable SERS sensor platform holds significant promise for point-of-care testing and continuous health monitoring.

Nitric oxide (NO), carbon monoxide (CO), and hydrogen sulfide (H2S) are endogenous gaseous signaling molecules, playing crucial roles in a wide range of biological processes. This study presents the fabrication and evaluation of a triple amperometric microsensor capable of the simultaneous and selective detection of NO, CO, and H2S for in vivo applications. The sensor integrates three platinum working electrodes into a single device. Each electrode was independently modified with specific metal deposits and selective membranes optimized to enhance specificity toward its target analyte. The sensor's excellent performance in terms of sensitivity, linearity, and selectivity was confirmed. To demonstrate in vivo applicability, the sensor was positioned on the cortical surface of a living rat brain, where it successfully monitored real-time concentration changes of NO, CO, and H2S during seizure events induced by 4-aminopyridine: NO exhibited the earliest concentration increase, followed sequentially by CO and H2S, providing the first temporally resolved evidence of in vivo gasotransmitter crosstalk during neural hyperactivity. This work establishes a powerful electrochemical platform for probing multigasotransmitter dynamics in real time.

Covalent organic frameworks (COFs), owing to their high surface area, well-defined porous structures, and abundant polar recognition sites, have shown great potential in trace gas detection. However, conventional COFs often suffer from aggregation, limited spatial distribution, and low structural utilization, which restrict their performance in gas sensors. To enhance the structural dispersity and gas sensing capability of COFs, we developed a miniaturized quartz tuning fork (MQTF) gas sensor based on a composite of EPCo-COF and pollen carbon (EPCo-COF@PC). In this hybrid sensing material, sheet-like COFs were grown in situ on a three-dimensional (3D) honeycomb-like pollen carbon scaffold, enabling effective spatial regulation of COF distribution and the formation of a stable and efficient gas transport network. The EPCo-COF@PC composite integrates abundant polar sites and 3D mass transport pathways, thereby enhancing selective adsorption of formaldehyde (HCHO), a common indoor air pollutant. Taking advantage of the high mass sensitivity of the MQTF, the adsorption-induced mass change is translated into a stable frequency shift signal. Experimental results revealed that the sensor exhibits rapid and reversible frequency responses even for ppb-level HCHO, with a broad linear detection range and excellent recovery behavior. It also shows superior selectivity against various common interfering gases and maintains 96.7% of its response after 40 days of storage at room temperature, indicating excellent long-term stability. This work provides an effective material strategy and design concept for the development of high-performance, low-cost, and integrable miniaturized gas sensors, and expands the potential applications of COF-based materials in environmental monitoring and portable sensing devices.

Hybrid microcavity systems combining optical resonatorswith responsivematerials offer a promising route toward tunable, multifunctionalphotonic devices. Here, we demonstrate a hydrogel-based microfiberlaser enhanced by plasmonic nanoparticles that enables single-modeoperation with high sensitivity. The hydrogel network acts as a disorderedscattering medium, inducing random lasing, while the microfiber geometrysupports whispering-gallery modes with strong optical feedback. Bytuning the microfiber diameter, we systematically investigate theinterplay between microcavity modes and scattering. Incorporationof Au nanoparticles further enhances the optical confinement throughlocalized surface plasmon resonances, providing single-mode lasingcontrol. The resulting device exhibits strong humidity responsivenessand operational stability, with a sensitivity of 103 pm/% RHand a rapid response time of 3.2 s. The results reported hereprovide a versatile approach for integrating smart materials and microcavities,advancing the development of ultrasensitive hydrogel-based photonicsensors.

Congo Red (CR) is the histochemical staining sensor used to diagnose amyloid tissue deposition in current clinical practice. Its characteristic aryl azo linkage is generally considered to be chemically stable. Here, we discovered by serendipity that neutral borate buffer can activate the inert azo bond in CR to covalently modify amyloid proteins at ambient temperature. Such chemistry allowed us to develop a covalent amyloid sensor to image, enrich, and proteotype amyloid deposits in Alzheimer's disease (AD) tissue. We first pinpointed the boronic acid in borate buffer triggers such amyloid bioconjugation and found that ultraviolet-light-induced azo trans-to-cis isomerization further enhanced labeling efficiency. Leveraging this boron-azo bioconjugation chemistry, we developed a covalent sensor based on CR for selective detection and microdissection of amyloid deposits from AD mouse brain tissues. By incorporating an alkyne handle into the CR scaffold, we enabled click-chemistry-assisted enrichment of amyloid aggregates, followed by proteotyping via LC-MS/MS. The covalent amyloid sensor proteotyped a complex network of protein interactors including the AD biomarkers Tau and ApoE within amyloid deposits. Overall, this work establishes a borate-activated azo-based covalent sensor for selective imaging, dissecting and proteotyping of amyloid deposits in AD tissues.