In-line fiber optical sensor for detection of IgG aggregates in affinity chromatography.

Therapeutic monoclonal antibodies (mAbs) are critical for treatment of a wide range of diseases. Immunoglobulin G (IgG) is the most predominant form of mAb but is prone to aggregation during production. Detection and removal of IgG aggregates are time-consuming and laborious. Chromatography is central for purification of biopharmaceuticals in general and essential in the production of mAbs. Protein purification systems are usually equipped with detectors for monitoring pH, UV absorbance, and conductivity, to facilitate optimization and control of the purification process. However, specific in-line detection of the target products and contaminating species, such as aggregates, is currently not possible using convectional techniques. Here we show a novel fiber optical in-line sensor, based on localized surface plasmon resonance (LSPR), for specific detection of IgG and IgG aggregates during affinity chromatography. A flow cell with a Protein A sensor chip was connected to the outlet of the affinity column connected to three different chromatography systems operating at lab scale to pilot scale. Samples containing various IgG concentrations and aggregate contents were analyzed in-line during purification on a Protein A column using both pH gradient and isocratic elution. Because of avidity effects, IgG aggregates showed slower dissociation kinetics than monomers after binding to the sensor chips. Possibilities to detect aggregate concentrations below 1 % and difference in aggregate content smaller than 0.3 % between samples were demonstrated. In-line detection of aggregates can circumvent time-consuming off-line analysis and facilitate automation and process intensification.

Red-emitting 4-methyl coumarin fused barbituric acid as an electrochemical sensor for catechol detection and probe for latent fingerprints.

Herein, we have reported a red-emitting 4-methyl coumarin fused barbituric acid azo dye (4-MCBA) synthesized by conventional method. Density functional theory (DFT) studies of tautomer compounds were done using (B3LYP) with a basis set of 6-31G(d,p). NLO analysis has shown that tautomer has mean first-order hyperpolarisabilities (ß) value of 1.8188 × 10-30 esu and 1.0470 × 10-30 esu for azo and hydrazone forms, respectively, which is approximately nine and five times greater than the magnitude of urea. 4-MCBA exhibited two absorption peaks in the range of 290-317 and 379-394 nm, and emission spectra were observed at 536 nm. CV study demonstrated that the modified 4-MCBA/MGC electrode exhibited excellent electrochemical sensitivity towards the detection of catechol and the detection limit is 9.39 µM under optimum conditions. The 4-MCBA employed as a fluorescent probe for the visualisation of LFPs on various surfaces exhibited Level-I to level-II LFPs, with low background interference.

Synergistic Etching and Hydrogen Bonding-Induced Self-Assembly of MXene/MOF Hybrid Aerogel for Flexible Room-Temperature Gas Sensing.

Limited by insufficient active sites and restricted mechanical strength, designing reliable and wearable gas sensors with high activity and ductility remains a challenge for detecting hazardous gases. In this work, a thermally induced and solvent-assisted oxyanion etching strategy was implemented for selective pore opening in a rigid microporous Cu-based metal-organic framework (referred to as CuM). A conductive CuM/MXene aerogel was then self-assembled through cooperative hydrogen bonding interactions between the carbonyl oxygen atom in PVP grafted on the surface of defect-rich Cu-BTC and the surface functional hydroxyl group on MXene. A flexible NO2 sensing performance using the CuM/MXene aerogel hybridized sodium alginate hydrogel is finally achieved, demonstrating extraordinary sensitivity (S = 52.47 toward 50 ppm of NO2), good selectivity, and rapid response/recovery time (0.9/4.5 s) at room temperature. Compared with commercial sensors, the relative error is less than 7.7%, thereby exhibiting significant potential for application in monitoring toxic and harmful gases. This work not only provides insights for guiding rational synthesis of ideal structure models from MOF composites but also inspires the development of high-performance flexible gas sensors for potential multiscenario applications.

Molecular Origins of Long-Term Changes in a Competitive Continuous Biosensor with Single-Molecule Resolution.

Biosensing by particle motion is a biosensing technology that relies on single-molecule interactions and enables the continuous monitoring of analytes from picomolar to micromolar concentration levels. However, during sensor operation, the signals are observed to change gradually. Here, we present a comprehensive methodology to elucidate the molecular origins of long-term changes in a particle motion sensor, focusing on a competitive sensor design under conditions without flow. Experiments were performed wherein only the particles or only the surfaces were aged in order to clarify how each individual component changes over time. Furthermore, distributions of particle motion patterns and switching activity were studied to reveal how particle populations change over timespans of several days. For a cortisol sensor with anticortisol antibodies on the particles and cortisol analogues on the sensing surface, the leading hypotheses for the long-term changes are (i) that the particles lose antibodies and develop nonspecific interactions and (ii) that analogue molecules dissociate from the sensing surface. The developed methodologies and the acquired insights pave a way for realizing sensors that can operate over long timespans.

Develop Tandem Tension Sensor to Gauge Integrin-Transmitted Molecular Forces.

DNA-based tension sensors have innovated the imaging and calibration of mechanosensitive receptor-transmitted molecular forces, such as integrin tensions. However, these sensors mainly serve as binary reporters, only indicating if molecular forces exceed one predefined threshold. Here, we have developed tandem tension sensor (TTS), which comprises two consecutive force-sensing units, each with unique force detection thresholds and distinct fluorescence spectra, thereby enabling the quantification of molecular forces with dual reference levels. With TTS, we revealed that vinculin is not required for transmitting integrin tensions at approximately 10 pN (piconewtons) but is essential for elevating integrin tensions beyond 20 pN in focal adhesions (FAs). Such high tensions have emerged during the early stage of FA formation. TTS also successfully detected changes in integrin tensions in response to disrupted actin formation, inhibited myosin activity, and tuned substrate elasticity. We also applied TTS to examine integrin tensions in platelets and revealed two force regimes, with integrin tensions surpassing 20 pN at cell central regions and 13-20 pN integrin tensions at the cell edge. Overall, TTS, especially the construct consisting of a hairpin DNA (13 pN opening force) and a shearing DNA (20 pN opening force), stands as a valuable tool for the quantification of receptor-transmitted molecular forces within living cells.

Upconverting Nanoparticle-based Enhanced Luminescence Lateral-Flow Assay for Urinary Biomarker Monitoring.

Development of efficient portable sensors for accurately detecting biomarkers is crucial for early disease diagnosis, yet remains a significant challenge. To address this need, we introduce the enhanced luminescence lateral-flow assay, which leverages highly luminescent upconverting nanoparticles (UCNPs) alongside a portable reader and a smartphone app. The sensor's efficiency and versatility were shown for kidney health monitoring as a proof of concept. We engineered Er3+- and Tm3+-doped UCNPs coated with multiple layers, including an undoped inert matrix shell, a mesoporous silica shell, and an outer layer of gold (UCNP@mSiO2@Au). These coatings synergistically enhance emission by over 40-fold and facilitate biomolecule conjugation, rendering UCNP@mSiO2@Au easy to use and suitable for a broad range of bioapplications. Employing these optimized nanoparticles in lateral-flow assays, we successfully detected two acute kidney injury-related biomarkers─kidney injury molecule-1 (KIM-1) and neutrophil gelatinase-associated lipocalin (NGAL)─in urine samples. Using our sensor platform, KIM-1 and NGAL can be accurately detected and quantified within the range of 0.1 to 20 ng/mL, boasting impressively low limits of detection at 0.28 and 0.23 ng/mL, respectively. Validating our approach, we analyzed clinical urine samples, achieving biomarker concentrations that closely correlated with results obtained via ELISA. Importantly, our system enables biomarker quantification in less than 15 min, underscoring the performance of our novel UCNP-based approach and its potential as reliable, rapid, and user-friendly diagnostics.

Deep Learning Used with a Colorimetric Sensor Array to Detect Indole for Nondestructive Monitoring of Shrimp Freshness.

Intelligent colorimetric freshness indicator is a low-cost way to intuitively monitor the freshness of fresh food. A colorimetric strip sensor array was prepared by p-dimethylaminocinnamaldehyde (PDL)-doped poly(vinyl alcohol) (PVA) and chitosan (Chit) for the quantitative analysis of indole, which is an indicator of shrimp freshness. As a result of indole simulation, the array strip turned from faint yellow to pink or mulberry color with the increasing indole concentration, like a progress bar. The indicator film exhibited excellent permeability, mechanical and thermal stability, and color responsiveness to indole, which was attributed to the interactions between PDL and Chit/PVA. Furthermore, the colorimetric strip sensor array provided a good relationship between the indole concentration and the color intensity within a range of 50-350 ppb. The pathogens and spoilage bacteria of shrimp possessed the ability to produce indole, which caused the color changes of the strip sensor array. In the shrimp freshness monitoring experiment, the color-changing progress of the strip sensor array was in agreement with the simulation and could distinguish the shrimp freshness levels. The image classification system based on deep learning were developed, the accuracies of four DCNN algorithms are above 90%, with VGG16 achieving the highest accuracy at 97.89%. Consequently, a "progress bar" strip sensor array has the potential to realize nondestructive, more precise, and commercially available food freshness monitoring using simple visual inspection and intelligent equipment identification.

Pt Loading of Phosphorus-Doped Carbon Nanotube Aerogels in Fuel Cell-Type Gas Sensors for Ultrasensitive H2 Detection.

A phosphorus-doped carbon nanotube (CNT) aerogel as the support material was loaded with Pt nanoparticles in fuel cell-type gas sensors for ultrasensitive H2 detection. The high surface area of the CNT scaffold is favorable to providing abundant active sites, and the high electrical conductivity facilitates the transport of carriers generated by electrochemical reactions. In addition, the CNT aerogel was doped with phosphorus (P) to further enhance the conductivity and electrochemical catalytic activity. As a result, the fuel cell-type gas sensor using the Pt/CNT aerogel doped with the optimal P content as the sensing material shows considerable performance for H2 detection at room temperature. The sensor exhibits an ultrahigh response of -921.9 µA to 15,000 ppm of H2. The sensitivity is -0.063 µA/ppm, which is 21 times higher than that of the conventional Pt/CF counterpart. The sensor also exhibits excellent repeatability and humidity resistance, as well as fast response/recovery; the response/recovery times are 31 and 4 s to 3000 ppm of H2, respectively. The modulation of the structure and catalytic properties of the support material is responsible for the improvement of the sensor performance, thus providing a feasible solution for optimizing the performance of fuel cell-type gas sensors.

Smart Cushions with Machine Learning-Enhanced Force Sensors for Pressure Injury Risk Assessment.

Prolonged sitting can easily result in pressure injury (PI) for certain people who have had strokes or spinal cord injuries. There are not many methods available for tracking contact surface pressure and shear force to evaluate the PI risk. Here, we propose a smart cushion that uses two-dimensional force sensors (2D-FSs) to measure the pressure and shear force in the buttocks. A machine learning algorithm is then used to compute the shear stresses in the gluteal muscles, which helps to determine the PI risk. The 2D-FS consists of a ferroelectret coaxial sensor (FCS) unit placed atop a ferroelectret film sensor (FFS) unit, allowing it to detect both vertical and horizontal forces simultaneously. To characterize and calibrate, two experimental approaches are applied: one involves simultaneously applying two perpendicular forces, and one involves applying a single force. To separate the two forces, the 2D-FS is decoupled using a deep neural network technique. Multiple FCSs are embedded to form a smart cushion, and a genetic algorithm-optimized backpropagation neural network is proposed and trained to predict the shear strain in the buttocks to prevent PI. By tracking the danger of PI, the smart cushion based on 2D-FSs may be further connected with home-based intelligent care platforms to increase patient equality for spinal cord injury patients and lower the expense of nursing or rehabilitation care.

Visible Light-Activated Room Temperature NO2 Gas Sensing Based on the In2O3@ZnO Heterostructure with a Hollow Microtube Structure.

The persistent challenge of poor recovery characteristics of NO2 sensors operated at room temperature remains significant. However, the development of In2O3-based gas sensing materials provides a promising approach to accelerate response and recovery for sub-ppm of NO2 detection at room temperature. Herein, we propose a simple two-step method to synthesize a one-dimensional (1D) In2O3@ZnO heterostructure material with hollow microtubes, by coupling metal-organic frameworks (MOFs) (MIL-68 (In)) and zinc ions. Meanwhile, the In2O3@ZnO composite-based gas sensor exhibits superior sensitivity performance to NO2 under visible light activation. The response value to 5 ppm of NO2 at room temperature is as high as 1800, which is 35 times higher than that of the pure In2O3-based sensor. Additionally, the gas sensor based on the In2O3@ZnO heterostructure demonstrates a significantly reduced response/recovery time of 30 s/67 s compared to the sensor based on pure In2O3 (74 s/235 s). The outstanding gas sensing properties of the In2O3@ZnO heterostructure-based sensors can be attributed to the enhanced photogenerated charge separation efficiency resulting from the heterostructure effect, and the improved receptor function toward NO2, which can increase the reactive sites and gas adsorption capacity. In summary, this work proposes a low-cost and efficient method to synthesize a 1D heterostructure material with microtube structures, which can serve as a fundamental technique for developing high-performance room-temperature gas sensors.

Facile Fabrication of Lilac-Like Multiple Self-Supporting WO3 Nanoneedle Arrays with Cubic/Hexagonal Phase Junctions for Highly Sensitive Ethylene Glycol Gas Sensors.

Metal oxides with nanoarray structures have been demonstrated to be prospective materials for the design of gas sensors with high sensitivity. In this work, the WO3 nanoneedle array structures were synthesized by a one-step hydrothermal method and subsequent calcination. It was demonstrated that the calcination of the sample at 400 °C facilitated the construction of lilac-like multiple self-supporting WO3 arrays, with appropriate c/h-WO3 heterophase junction and highly oriented nanoneedles. Sensors with this structure exhibited the highest sensitivity (2305) to 100 ppm ethylene glycol at 160 °C and outstanding selectivity. The enhanced ethylene glycol gas sensing can be attributed to the abundant transport channels and active sites provided by this unique structure. In addition, the more oxygen adsorption caused by the heterophase junction and the aggregation of reaction medium induced by tip effect are both in favor of the improvement on the gas sensing performance.

Conformal sulfidation of HKUST-1 for constructing porous Cu2S/CuO octahedrons realizing highly sensitive non-enzymatic glucose detection.

Metal-organic frameworks (MOFs) are believed to be promising precursors for constructing novel and efficient catalysts for glucose sensing. Herein, HKUST-1 precursors are first fabricated using a one-pot hydrothermal approach, and then HKUST-1 is converted into porous Cu2S/CuO octahedrons through conformal sulfidation with the help of OH-ions. The as-obtained Cu2S/CuO composite can provide rich electrochemical active sites and promoted electric transfer kinetics. Benefiting from these combined merits, the as-fabricated Cu2S/CuO composite is confirmed to be a high-performance catalyst, with high sensitivities of 8269.45 and 4140.82µA mM-1cm-2in the corresponding ranges of 0.05 ∼ 0.6 mM and 0.6 ∼ 1.2 mM, respectively. Moreover, the as-prepared electrode materials possess good anti-interference ability, reproducibility and long-term stability. This work opens up new avenues for the design and preparation of transition metal sulfide composites.

The Identification of Oral Cariogenic Bacteria through Colorimetric Sensor Array Based on Single-Atom Nanozymes.

Effective identification of multiple cariogenic bacteria in saliva samples is important for oral disease prevention and treatment. Here, a simple colorimetric sensor array is developed for the identification of cariogenic bacteria using single-atom nanozymes (SANs) assisted by machine learning. Interestingly, cariogenic bacteria can increase oxidase-like activity of iron (Fe)─nitrogen (N)─carbon (C) SANs by accelerating electron transfer, and inversely reduce the activity of Fe─N─C further reconstruction with urea. Through machine-learning-assisted sensor array, colorimetric responses are developed as "fingerprints" of cariogenic bacteria. Multiple cariogenic bacteria can be well distinguished by linear discriminant analysis and bacteria at different genera can also be distinguished by hierarchical cluster analysis. Furthermore, colorimetric sensor array has demonstrated excellent performance for the identification of mixed cariogenic bacteria in artificial saliva samples. In view of convenience, precise, and high-throughput discrimination, the developed colorimetric sensor array based on SANs assisted by machine learning, has great potential for the identification of oral cariogenic bacteria so as to serve for oral disease prevention and treatment.

Charge-Transfer Complexes: Fundamentals and Advances in Catalysis, Sensing, and Optoelectronic Applications.

Supramolecular assemblies, formed through electronic charge transfer between two or more entities, represent a rich class of compounds dubbed as charge-transfer complexes (CTCs). Their distinctive formation pathway, rooted in charge-transfer processes at the interface of CTC-forming components, results in the delocalization of electronic charge along molecular stacks, rendering CTCs intrinsic molecular conductors. Since the discovery of CTCs, intensive research has explored their unique properties including magnetism, conductivity, and superconductivity. Their more recently recognized semiconducting functionality has inspired recent developments in applications requiring organic semiconductors. In this context, CTCs offer a tuneable energy gap, unique charge-transport properties, tailorable physicochemical interactions, photoresponsiveness, and the potential for scalable manufacturing. Here, an updated viewpoint on CTCs is provided, presenting them as emerging organic semiconductors. To this end, their electronic and chemical properties alongside their synthesis methods are reviewed. The unique properties of CTCs that benefit various related applications in the realms of organic optoelectronics, catalysts, and gas sensors are discussed. Insights for future developments and existing limitations are described.

Improving urinary incontinence management and sleep quality with wetness sensing technology in absorbent products.

Using absorbent products to manage the urinary incontinence (UI) of dependent residents in care facilities (such as nursing homes, and hospitals) requires frequent routine checks throughout the day and night to see if products need changing. Timely changes of saturated products are necessary to avoid long-lasting skin exposure to wet absorbent products, unpleasant odor, leaking of such products and embarrassing moments for the users. Limited staffing, high workload, and peaks on the demand for caregiving are challenges that hamper swift support for the care dependent population. This paper describes novel sensing technology that has been developed for monitoring the wet state of absorbent products remotely. The Orizon system by Ontex enables caregivers to prioritize care routines, avoid sleep disturbance at night and achieve effective leakage prevention. Moreover, the monitoring data can be used to understand the individual product usage and incontinence pattern of individuals, helping incontinence specialists to choose the optimal product and implement appropriate toilet training for each user.

Polyoxometalate-based iron-organic complex nanozymes with peroxidase-like activities for colorimetric detection of hydrogen peroxide and ascorbic acid.

As a new type of artificial enzyme, a nanozyme is an ideal substitute for natural enzymes and has been successfully applied in many fields. However, in the application of biomolecular detection, most nanozymes have the disadvantages of long reaction times or high detection limits, prompting researchers to search for new efficient nanozymes. In this work, the enzyme-like activities of three polyoxometalate-based iron-organic complexes ([Fe(bpp)2](Mo6O19), [Fe(bpp)2]2(Mo8O26)·2CH3OH, and [Fe(bpp)2]4H[Na(Mo8O26)]3), namely, FeMo6, Fe2Mo8, and Fe4Mo8Na, were analyzed. All three polyoxometalate-based iron-organic complexes were found to be capable of catalyzing hydrogen peroxide (H2O2) to oxidize 3,3',5,5'-tetramethylbenzidine and o-phenylenediamine, resulting in visible color changes, further exhibiting peroxidase-like activity. Results showed that Fe4Mo8Na had more active sites due to its long chain structure, endowing more prominent peroxidase-like activity compared with Fe2Mo8 and FeMo6. A colorimetric sensing platform for H2O2 and ascorbic acid detection based on Fe4Mo8Na was established. The linear response range for H2O2 detection was 0.5-100 µM, and the detection limit was 0.143 µM. The linear response for ascorbic acid detection ranges from 0 to 750 µM with a detection limit of 1.07 µM. This study provides a new perspective for developing new nanozymes and expanding the sensing and detection application of nanozymes.

A comprehensive review of 5G NR RF-EMF exposure assessment technologies: fundamentals, advancements, challenges, niches, and implications.

This review offers a detailed examination of the current landscape of radio frequency (RF) electromagnetic field (EMF) assessment tools, ranging from spectrum analyzers and broadband field meters to area monitors and custom-built devices. The discussion encompasses both standardized and non-standardized measurement protocols, shedding light on the various methods employed in this domain. Furthermore, the review highlights the prevalent use of mobile apps for characterizing 5G NR radio network data. A growing need for low-cost measurement devices is observed, commonly referred to as "sensors" or "sensor nodes", that are capable of enduring diverse environmental conditions. These sensors play a crucial role in both microenvironmental surveys and individual exposures, enabling stationary, mobile, and personal exposure assessments based on body-worn sensors, across wider geographical areas. This review revealed a notable need for cost-effective and long-lasting sensors, whether for individual exposure assessments, mobile (vehicle-integrated) measurements, or incorporation into distributed sensor networks. However, there is a lack of comprehensive information on existing custom-developed RF-EMF measurement tools, especially in terms of measuring uncertainty. Additionally, there is a need for real-time, fast-sampling solutions to understand the highly irregular temporal variations EMF distribution in next-generation networks. Given the diversity of tools and methods, a comprehensive comparison is crucial to determine the necessary statistical tools for aggregating the available measurement data.

Nucleobase-modulated copper nanomaterials with laccase-like activity for high-performance degradation and detection of phenolic pollutants.

Laccases are the most commonly used agents for the treatment of phenolic pollutants. To address the instability and high cost of natural laccases, we investigated nucleobase-modulated copper nanomaterial with laccase-like activity. Various nucleobases, including adenine, guanine, cytosine, and thymine, were investigated as templates for Cu2+ reduction and copper nanomaterials formation due to their coordination capacity. By comparing structure and catalytic activity, the cytosine-mediated copper nanomaterial (C-Cu) had the best laccase-like activity and other nucleobase-templated copper nanomaterials exhibited low catalytic activity under the same conditions. The mechanism of nucleobase regulation of the catalytic activity of copper nanomaterials was further analyzed using X-ray photoelectron spectroscopy and density functional theory. The possible catalytic mechanisms of C-Cu, including substrate adsorption, substrate oxidation, oxygen binding, and oxygen reduction, were proposed. Remarkably, nucleobase-modulated copper nanozymes showed high stability and catalytic oxidation performance at various pH values, temperatures, long-term storage, and high salinity. In combination with electrochemical techniques, a portable electrochemical sensor for measuring phenolic pollutants was developed. This novel sensor exhibited a good linear response to catechol (10-1000 µM) with a limit of detection of 1.8 µM and excellent selectivity and anti-interference ability. This study provides not only a new strategy for the regulation of the laccase-like activity of copper nanomaterials but also a novel tool for the effective removal and low-cost detection of phenolic pollutants.

Highly selective Zn2+ near-infrared fluorescent probe and its application in biological imaging.

Zn2+ plays a vital role in regulating various life processes, such as gene expression, cell signaling, and brain function. In this study, a near-infrared fluorescent probe AXS was synthesized to detect Zn2+ with good fluorescence specificity, high selectivity, and high sensitivity; the detection limit of Zn2+ was 6.924 × 10-11 M. The mechanism of Zn2+ recognition by the AXS probe was investigated by 1H nuclear magnetic resonance titrations, UV-visible spectroscopy, fluorescence spectroscopy, Fourier-transform infrared spectroscopy, and high-resolution mass spectrometry. Test paper experiments showed that the AXS probe could detect Zn2+ in real samples. In addition, quantitative and qualitative detection of Zn2+ in common foodstuffs was achieved. For portable Zn2+ detection, a smartphone detection platform was also developed based on the AXS probe. Importantly, the AXS probe showed good bioimaging capabilities in Caenorhabditis elegans and mice.

Point-of-care testing of Pseudomonas aeruginosa using PCN-222(Pt) prepared by nanoconfinement-guided protocol to catalyze gas generation reaction.

BACKGROUND: Pathogenic bacteria are keeping threatening global public health since they can cause many infectious diseases. The traditional microorganism identification and molecular diagnostic techniques are insufficiently sensitive, time-consuming, or expensive. Thus it is of great interest to establish pressure signal-based sensing platforms for point-of-care testing of pathogenic bacteria to achieve timely diagnosis of infectious diseases. Rational design and synthesis of nano-sized probes with high peroxidase-mimicking activity have been a long-term cherished goal for improving the sensitivity of pressure signal-based sensing methods. RESULTS: Guided by nanoconfinement effect, PCN-222(Pt) was prepared by confining Pt clusters within the channels of a zirconium porphyrin MOFs material termed as PCN-222. In comparison to regular platinum nanoparticles, palladium@platinum core-shell nanodendrites, and platinum-coated gold nanoparticles, the prepared PCN-222(Pt) displayed superior peroxidase-mimicking activity with outstanding efficiency for catalyzing the decay of H2O2 to produce O2. Thus it was used as a pressure signal probe to establish a sensitive method on a hydrogel pellets platform for analyzing Pseudomonas aeruginosa (P. aeruginosa), for which polymyxin B and a phage termed as JZ1 were used as recognition agents for the target pathogen. P. aeruginosa was quantified with a handheld pressure meter within a broad range of 2.2 × 102-2.2 × 107 cfu mL-1. This method was used to quantify P. aeruginosa in various biological and food samples with acceptable accuracy and reliability. SIGNIFICANCE: The proposed nanoconfinement-guided protocol provides a novel approach for rational design and preparation of nano-sized probes with high peroxidase-mimicking activity for catalyzing gas-generation reaction. Thus this study opens an avenue for establishment of sensitive pressure signal-based sensing methods for pathogenic bacteria, which shows broad application prospects in medical diagnosis of infectious diseases.