Significance of resected stomach measurements in postoperative delayed gastric emptying following laparoscopic pylorus-preserving gastrectomy.

PURPOSE: We investigated the relationship between the resected stomach measurements, the incidence of delayed gastric emptying (DGE), and food residue 1 year after surgery in patients who underwent laparoscopic pylorus-preserving gastrectomy (PPG). MATERIALS AND METHODS: The DGE group included 10 patients fasting due to nausea, vomiting, abdominal distension, or remnant stomach distension on radiographs; the control group included 36 patients without these symptoms. We compared the size and length of lesser and greater curvatures of the resected stomach and endoscopic findings after 1 year. RESULTS: No significant differences were observed between groups in terms of sex, body mass index, gross type, histology, tumor progression, number of dissected lymph nodes, operating time, or blood loss. The DGE group was older, had a longer postoperative stay, and showed a smaller size and shorter greater curvature of the resected stomach than the control group (p < 0.01 for all). No difference was observed in the length of the lesser curvature of the resected stomach. In addition, there were no disparities in residual food, degree and extent of gastritis, or bile reflux 1 year after gastrectomy. CONCLUSIONS: Measurements of the resected stomach suggest that preventing DGE may be achievable by removing a larger area of the greater curvature and/or stomach during laparoscopic PPG. This implies potential surgical strategy improvements for better outcomes. Further multicenter trials are needed to validate and refine techniques.

Deconstructing 3D growth rates from transmission microscopy images of facetted crystals as captured in situ within supersaturated aqueous solutions.

Here, a morphologically based approach is used for the in situ characterization of 3D growth rates of facetted crystals from the solution phase. Crystal images of single crystals of the ß-form of l-glutamic acid are captured in situ during their growth at a relative supersaturation of 1.05 using transmission optical microscopy. The crystal growth rates estimated for both the {101} capping and {021} prismatic faces through image processing are consistent with those determined using reflection light mode [Jiang, Ma, Hazlehurst, Ilett, Jackson, Hogg & Roberts (2024 ▸). Cryst. Growth Des. 24, 3277-3288]. The growth rate in the {010} face is, for the first time, estimated from the shadow widths of the {021} prismatic faces and found to be typically about half that of the {021} prismatic faces. Analysis of the 3D shape during growth reveals that the initial needle-like crystal morphology develops during the growth process to become more tabular, associated with the Zingg factor evolving from 2.9 to 1.7 (>1). The change in relative solution supersaturation during the growth process is estimated from calculations of the crystal volume, offering an alternative approach to determine this dynamically from visual observations.

Development of a Topological-Insulator-Based Quantum Resistance Standard.

This paper describes the characterization of the quantum anomalous Hall (QAH) effect resistor with Chromium-doped Bismuth Antimony Telluride with the efforts in coupling directly to a programmable Josephson voltage standard (PJVS) at zero magnetic field. The precision measurement of the QAH resistance was performed under the presence of microwave signal biased to the PJVS. Understanding such effect will help to improve the experimental set-up for integrating multiple quantum electrical standards in a single system.

Accurate locomotor activity profiles of group-housed mice derived from home cage monitoring data.

Introduction: Holistic phenotyping of rodent models is increasing, with a growing awareness of the 3Rs and the fact that specialized experimental setups can also impose artificial restrictions. Activity is an important parameter for almost all basic and applied research areas involving laboratory animals. Locomotor activity, the main form of energy expenditure, influences metabolic rate, muscle mass, and body weight and is frequently investigated in metabolic disease research. Additionally, it serves as an indicator of animal welfare in therapeutic, pharmacological, and toxicological studies. Thus, accurate and effective measurement of activity is crucial. However, conventional monitoring systems often alter the housing environment and require handling, which can introduce artificial interference and lead to measurement inaccuracies. Methods: Our study focused on evaluating circadian activity profiles derived from the DVC and comparing them with conventional activity measurements to validate them statistically and assess their reproducibility. We utilized data from metabolic studies, an Alzheimer's disease model known for increased activity, and included DVC monitoring in a project investigating treatment effects on activity in a type-1-like diabetes model. Results: The DVC data yielded robust, scientifically accurate, and consistent circadian profiles from group-housed mice, which is particularly advantageous for longitudinal experiments. The activity profiles from both systems were fully comparable, providing matching profiles. Using DVC monitoring, we confirmed the hyperactivity phenotype in an AD model and reproduced a decline in activity in type-1-like diabetes model. Discussion: In our work, we derived robust circadian activity profiles from the DVC data of group-housed mice, which were scientifically accurate, reproducible and comparable to another activity measurement. This approach can not only improve animal welfare according to the 3R principles but can also be implement in high-throughput longitudinal studies. Furthermore, we discuss the advantages and limitations of DVC activity measurements to highlight its potential and avoid confounders.

Patterns and determinants of micronutrient dietary biomarkers and their associations with dietary intakes in young children.

BACKGROUND: Circulating dietary biomarkers are not direct proxies for intake, as the biomarkers reflect not only food and supplement consumption but also nutrient absorption, metabolism, and tissue distribution. Therefore, along with nutrient intake, several other upstream factors can impact dietary biomarker concentrations, including demographic, medical history, and genetic factors. OBJECTIVE: The aim of this study was to explore the dietary and nondietary determinants of circulating levels of vitamins A, C, D, and E among children aged 6 months to 4 years. METHODS: Plasma retinol, beta-carotene, ascorbic acid, 25(OH)D, alpha-tocopherol, and gamma-tocopherol were measured in 2887 samples from 1490 children enrolled in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Dietary intake was assessed with 3-day food records. Associations of genetic and environmental factors with biomarker concentrations were examined using multivariable linear regression models with random intercepts. RESULTS: All biomarkers except retinol were positively associated with intake of the same nutrient. Inverse associations were identified between recent gastrointestinal infection and ß-carotene, ascorbic acid, and α-tocopherol, while recent respiratory infection was associated inversely with plasma retinol. Several genetic determinants of biomarker status were identified, validating previously reported findings. For some genetic and environmental exposures, we found evidence of statistical interaction with same-nutrient intake, indicating that the association between intake and biomarker concentration is dependent upon the level or status of these other exposures. For example, the association between ß-carotene intake and concentration is weaker among children with a recent respiratory infection. CONCLUSIONS: Our findings suggest that non-dietary exposures including childhood infections can alter micronutrient metabolism. This summary of micronutrient determinants will facilitate improved design of future analyses exploring the role of diet in childhood chronic disease etiology through a better understanding of relevant potential confounders and mediators of the diet-outcome relationships.

Influences of Variability in Attenuation Compensation on the Estimation of Backscatter Coefficient of Median Nerves in Vivo.

OBJECTIVE: Peripheral nerves remain a challenging target for medical imaging, given their size, anatomical complexity, and structural heterogeneity. Quantitative ultrasound (QUS) applies a set of techniques to estimate tissue acoustic parameters independent of the imaging platform. Many useful medical and laboratory applications for QUS have been reported, but challenges remain for deployment in vivo, especially for heterogeneous tissues. Several phenomena introduce variability in attenuation estimates, which may influence the estimation of other QUS parameters. For example, estimating the backscatter coefficient (BSC) requires compensation for the attenuation of overlying tissues between the transducer and the underlying tissue of interest. The purpose of this study is to extend prior studies by investigating the efficacy of several analytical methods of estimating attenuation compensation on QUS outcomes in the human median nerve. METHODS: Median nerves were imaged at the volar wrist in vivo and beam-formed radiofrequency (RF) data were acquired. Six analytical approaches for attenuation compensation were compared: 1-2) attenuation estimated by applying spectral difference method (SDM) and spectral log difference method (SLDM) independently to regions of interest (ROIs) overlying the nerve and to the nerve ROI itself; 3-4) attenuation estimation by applying SDM and SLDM to ROIs overlying the nerve, and transferring these properties to the nerve ROI; and 5-6) methods that apply previously published values of tissue attenuation to the measured thickness of each overlying tissue. Mean between-subject estimates of BSC-related outcomes as well as within-subject variability of these outcomes were compared among the 6 methods. RESULTS: Compensating for attenuation using SLDM and values from the literature reduced variability in BSC-based outcomes, compared to SDM. Variability in attenuation coefficients contributes substantially to variability in backscatter measurements. CONCLUSION: This work has implications for the application of QUS to in vivo diagnostic assessments in peripheral nerves and possibly other heterogeneous tissues.

Time-resolved observation of DHR123 nano-clay radio-fluorogenic gel dosimeters by photoluminescence-detected pulse radiolysis.

The importance of real-time dose evaluation has increased for recent advanced radiotherapy. However, conventional methods for real-time dosimetry using gel dosimeters face challenges owing to the delayed dose response caused by the slow completion of radiation-induced chemical reactions. In this study, a novel technique called photoluminescence-detected pulse radiolysis (PLPR) was developed, and its potential to allow real-time dose measurements using nano-clay radio-fluorogenic gel (NC-RFG) dosimeters was investigated. PLPR is a time-resolved observation method, and enables time-resolved fluorescence measurement. NC-RFG dosimeters were prepared, typically consisting of 100 µM dihydrorhodamine 123 (DHR123) and 2.0 wt.% nano-clay, along with catalytic and dissolving additives. We successfully achieved time-resolved observation of the increase in fluorescence intensity upon irradiation of the dosimeter. Dose evaluation was possible at 1 s after irradiation. The dose-rate effect was not observed for the deoxygenated dosimeter, but was observed for the aerated dosimeter. Besides the dose-rate effect, linear dose responses were obtained for both conditions. Furthermore, we made a novel observation of a decay in the fluorescence intensity over time in the early stages which named fluorescence secondary loss (FSL) and elucidated the conditions under which this phenomenon occurs.

TENSOR REGRESSION FOR INCOMPLETE OBSERVATIONS WITH APPLICATION TO LONGITUDINAL STUDIES.

Multivariate longitudinal data are frequently encountered in practice such as in our motivating longitudinal microbiome study. It is of general interest to associate such high-dimensional, longitudinal measures with some univariate continuous outcome. However, incomplete observations are common in a regular study design, as not all samples are measured at every time point, giving rise to the so-called blockwise missing values. Such missing structure imposes significant challenges for association analysis and defies many existing methods that require complete samples. In this paper we propose to represent multivariate longitudinal data as a three-way tensor array (i.e., sample-by-feature-by-time) and exploit a parsimonious scalar-on-tensor regression model for association analysis. We develop a regularized covariance-based estimation procedure that effectively leverages all available observations without imputation. The method achieves variable selection and smooth estimation of time-varying effects. The application to the motivating microbiome study reveals interesting links between the preterm infant's gut microbiome dynamics and their neurodevelopment. Additional numerical studies on synthetic data and a longitudinal aging study further demonstrate the efficacy of the proposed method.

The effects of different interruption conditions on mental workload: an experimental study based on multimodal measurements.

Interruptions in the working environment cause extra mental workload for the operators, and this phenomenon has garnered significant research attention. This study designed four interruption conditions based on the perceptual and cognitive perspectives of human information processing, using a 2(perceptual primary task and cognitive primary task)*2(perceptual interruption task and cognitive interruption task) factorial design. Multimodal measurement methods were used to evaluate mental workload in different interruption conditions. The results show that when the primary task and the interruption task are different load types, they generate a higher mental workload than the same load type. It can be attributed to the fact that perceptual tasks and cognitive tasks increase mental workload during switching. In addition, based on the multimodal index data, the prediction model of interruption recovery delay time and the classification model of interruption conditions are established, which provides a basis for rational scheduling of work and preventing mental overload.

This study's results enhance our understanding of interruptions from the perspectives of perception and cognition, providing a more accurate theoretical basis for managing mental workload in interruption conditions. The proposed interruption recovery delay time prediction model and the interruption condition classification model have certain reference values for improving interruption management capabilities.

Comparison of a radiofrequency electric and magnetic field source-based job-exposure matrix with personal radiofrequency exposure measurements.

OBJECTIVES: Assessing occupational exposure to radiofrequency electromagnetic fields (RF-EMF) presents significant challenges due to the considerable variability in exposure levels within and between occupations. This spatial and temporal variability complicates the reliable evaluation of potential health risks associated with RF-EMF exposure in the workplace. Accurate assessment methods are crucial to understand the extent of exposure and to evaluate potential health risks, especially given the potential for higher exposures in occupational settings compared to the general population. This study compares the historical RF-EMF exposure estimates in the INTEROCC RF-EMF job-exposure matrix (RF-JEM) with recent personal measurement data collected in 2 countries as part of the OccRF-Health study, to assess the broader applicability of the RF-JEM. METHODS: Weighted kappa (k  w) coefficients and Spearman rank correlation tests were performed to assess the alignment between RF-JEM estimates and measurements for 8 h time-weighted average exposure intensity and prevalence estimates across various occupations. The comparisons were mainly based on 22 jobs having ≥5 measured workers in the OccRF-Health study. RESULTS: Poor agreement was found for both exposure prevalence and intensity between both methods (k  w < 0.1). RF-JEM values likely overestimated exposure levels for both electric (E) and magnetic (H) fields (mean percentage difference >194%) compared to current personal measurements. CONCLUSIONS: Findings suggest that the INTEROCC-JEM likely overestimates current exposure intensity levels in the measured jobs. Adopting a semiquantitative JEM could also mitigate misclassification errors due to exposure variability, improving accuracy in exposure assessment. These findings indicate the need for more targeted personal measurements, including among highly exposed workers, and for potentially considering new exposure metrics to more accurately assess occupational RF-EMF exposures in occupational epidemiological research.

PARAFAC under non-negativity constraint is adapted to recover the underlying Beer-Lambert law of the excitation-emission fluorescence matrix measurements acquired from analyte-triggered semiconductor QDs photoluminescence modulation. When and why?

BACKGROUND: Analyte-triggered semiconductor quantum dots (QDs) modulation in the presence of non-consistently responsive fluorescent species represents a challenging analytical issue in concrete multi-way data handling. QDs with heterogeneous sizes and/or uneven distribution of functional moieties on their surfaces exhibit significant fluctuations in the fluorescent response components, known as chemical rank, across different excitation/emission modes. This phenomenon may lead to a substantial deviation from the proportionality prescribed by Beer-Lambert law. Nonetheless, even in the presence of such deviation, a multi-way model may be successfully selected after determining a proper chemical rank in a QDs system. RESULTS: We show that in a valid PARAllel FACtor (PARAFAC) model under properly determined chemical rank, meaningfully resolved pure spectral profiles can be reached for each fluorescent responsive constituent in the original excitation-emission fluorescence matrix (EEFM) measurements. This was thoroughly illustrated by applying PARAFAC trilinear decomposition of a three-way data array of two distinct datasets acquired from semiconductor QDs sensing systems with low-rank trilinear assumption. The first dataset, presented here for the first time, comprises EEFM measurements of the ligand-driven quenching of thiomalic acid (TMA)-capped AgInS2 (AIS) QDs by vomitoxin. The second dataset, employed for illustrative purposes, comprises EEFM measurements of the quenching, via cation bridging, of glutathione (GSH)-capped CdTe QDs by Pb(II). The results of this study enabled the determination of vomitoxin at a ppb level in real samples of fish feeds, showcasing the efficacy of the PARAFAC model in resolving spectral signatures (loadings) and pure concentration profiles (scores). SIGNIFICANCE: PARAFAC under a properly examined chemical rank can be easily adapted for retrieval the underlying Beer-Lambert law of the original EEFM measurements with a low-rank trilinear structure through the chemically meaningful information either when (i) no deviation of Beer-Lambert law was observed as deeply discussed in connection with the dataset acquired from vomitoxin-driven molecular sensing through TMA-capped AIS QDs, or when (ii) substantial deviations of the Beer-Lambert law are evident, as discussed in connection with the dataset collected from sensing ionic species through Pb(II) bridging of GSH-capped CdTe QDs.

Assessment of Changes in Selected Features of Pine and Birch Wood after Impregnation with Graphene Oxide.

In this work, pine and birch wood were modified by graphene oxide using a single vacuum impregnation method. The research results indicate that the impregnation of wood with graphene oxide increases the crystallinity of cellulose in both pine and birch wood, and the increase in crystallinity observed in the case of birch was more significant than in the case of pine. FT-IR analyses of pine samples impregnated with graphene oxide showed changes in intensity in the absorption bands of 400-600, 700-1500 cm-1, and 3200-3500 cm-1 and a peak separation of 1102 cm-1, which may indicate new C-O-C connections. In the case of birch, only some differences were noticed related to the vibrations of the OH group. The proposed modification also affects changes in the color of the wood surface, with earlywood containing more graphene oxide than latewood. Analysis of scanning electron microscope images revealed that graphene oxide adheres flat to the cell wall. Considering the differences in the anatomical structure of both wood species, the research showed a statistically significant difference in water absorption and retention of graphene oxide in wood cells. Graphene oxide does not block the flow of water in the wood, as evidenced by the absorbability of the working liquid at the level of 580-602 kg/m3, which corresponds to the value of pure water absorption by wood in the impregnation method using a single negative pressure. In this case, higher graphene oxide retention values were obtained for pine wood.

Influence of Zinc Chloride Exposure on Microstructure and Mechanical Behavior of Age-Hardened AZ91 Magnesium Alloy.

The AZ91 magnesium alloy was subjected to a complex treatment involving age hardening (supersaturation and artificial aging) and simultaneous surface layer modification. The specimens were supersaturated in contact with a mixture containing varying concentrations of zinc chloride, followed by cooling either in air or water. After supersaturation, the specimens were subjected to artificial aging and then air-cooled. This process resulted in the formation of a surface layer made of zinc-rich phases. The thickness and microstructure of the surface layer were influenced by the process parameters, namely, the zinc chloride content in the mixture and the cooling rate during supersaturation. The treated specimens exhibited favorable tensile strength and greater elongation compared to the as-cast AZ91 alloy, with values comparable to those of the alloy subjected to standard T6 tempering. No cracking of the layer was observed under moderate deformation, though greater deformation resulted in the formation of cracks, primarily in the areas containing the Mg5Al2Zn2 intermetallic phase. The produced layer demonstrated strong metallurgical bonding to the AZ91 substrate.

Deep Indentation Tests of Soft Materials Using Mobile and Stationary Devices.

Measurements of the properties of soft materials are important from the point of view of medical diagnostics of soft tissues as well as testing the quality of food products and many technical materials. One of the frequently used techniques for testing such materials, attractive due to its non-invasive nature, is the indentation technique, which does not puncture the material. The difficulty of testing soft materials, which affects the objectivity of the results, is related to the problems of stable positioning of the studied material in relation to the indentation apparatus, especially with a device held by the operator. This work concerns the comparison of test results using an indentation apparatus mounted on mobile and stationary handles. The tested materials are cylindrical samples of polyurethane foams with three different stiffnesses and the same samples with a 0.5 or 1 mm thick silicone layer. The study presented uses an apparatus with a flat cylindrical indenter, with a surface area of 1 cm2, pressed to a depth of 10 mm (so-called deep tests). Based on the recorded force changes over time, five descriptors of the indentation test were determined and compared for both types of handles. The tests performed showed that the elastic properties of foam materials alone and with a silicone layer can be effectively characterized by the maximum forces during recessing and retraction and the slopes of the recessing and retraction curves. In the case of two-layer materials, these descriptors reflect both the characteristics of the foams and the silicone layer. The results show that the above property of the deep indentation method distinguishes it from the shallow indentation method. The repeatability of the tests performed in the mobile and stationary holders were determined to be comparable.

Severe Microbial Corrosion of L245 Transportation Pipeline Triggered by Wild Sulfate Reducing Bacteria in Shale Gas Produced Water.

The development of pitting corrosion on L245 carbon steel in a culture medium solution containing sulfate-reducing bacteria (SRB) was investigated. The results showed that the occurrence of corrosion in L245 carbon steel is closely linked to the evolution of biofilm and product film. As the test duration extended, overall corrosion was inhibited. Simultaneously, bacteria beneath the film layer promoted the generation and development of pitting corrosion, and the aggregation of bacteria (colonies) led to the aggregation of pitting corrosion.

One-Port Coaxial Line Sample Holder Characterisation Method of Dielectric Spectra.

A technique for solving the one-port closed coaxial transmission line sample holder scattering equation for complex permittivity inversion for lossy materials is presented. A non-linear least-squares procedure is used for the determination of parameters for the specification of the spectral functional form of the complex permittivity. The method allows for accurate retrieval of many low- and high-permittivity dielectric materials in the frequency range of 1 GHz to 3 GHz inserted into the coaxial cell. Using this method, the complex permittivity of a number of liquids and a Maltese soil known as Bajjad soil have been extracted by measurements using a short terminated coaxial transmission line sample holder. The proposed novel inversion method is mainly based on the reflection coefficient of the test material. The measured results of the complex permittivity of liquid dielectrics such as ethanol, methanol, and TX100 are validated and compared with previously published data obtained from measurements made by the National Physical Laboratory (NPL) using a two-port measurement setup made with the same commercial coaxial transmission line sample holder used in the one-port setup. Since the technique allows broadband measurements, it has been used to characterise the soil dielectric spectrum in the frequency range of 1-3 GHz, which is also compared with results from a two-port setup of the same coaxial line. The experimental results are a validation of the proposed approach for different types of materials.

Conductive Atomic Force Microscopy-Ultralow-Current Measurement Systems for Nanoscale Imaging of a Surface's Electrical Properties.

One of the most advanced and versatile nanoscale diagnostic tools is atomic force microscopy. By enabling advanced imaging techniques, it allows us to determine various assets of a surface, including morphological, electrical, mechanical, magnetic, and thermal properties. Measuring local current flow is one of the very important methods of evaluation for, for instance, photovoltaic materials or semiconductor structures and other nanodevices. Due to contact areas, the current densities can easily reach above 1 kA/m2; therefore, special detection/measurement setups are required. They meet the required measurement range, sensitivity, noise level, and bandwidth at the measurement scale. Also, they prevent the sample from becoming damaged and prevent unwanted tip-sample issues. In this paper, we present three different nanoscale current measurement solutions, supported with test results, proving their performance.

Low-Cost CO2 NDIR Sensors: Performance Evaluation and Calibration Using Machine Learning Techniques.

The study comprehensively evaluates low-cost CO2 sensors from different price tiers, assessing their performance against a reference-grade instrument and exploring the possibility of calibration using different machine learning techniques. Three sensors (Sunrise AB by Senseair, K30 CO2 by Senseair, and GMP 343 by Vaisala) were tested alongside a reference instrument (Los Gatos precision greenhouse gas analyzer). The results revealed differences in sensor performance, with the higher cost Vaisala sensors exhibiting superior accuracy. Despite its lower price, the Sunrise sensors still demonstrated reasonable accuracy. Meanwhile, the K30 sensor measurements displayed higher variability and noise. Machine learning models, including linear regression, gradient boosting regression, and random forest regression, were employed for sensor calibration. In general, linear regression models performed best for extrapolating data, whereas decision tree-based models were generally more useful in handling non-linear datasets. Notably, a stack ensemble model combining these techniques outperformed the individual models and significantly improved sensor accuracy by approximately 65%. Overall, this study contributes to filling the gap in intercomparing CO2 sensors across different price categories and underscores the potential of machine learning for enhancing sensor accuracy, particularly in low-cost sensor applications.

Validity and Reliability of Movesense HR+ ECG Measurements for High-Intensity Running and Cycling.

Low-cost, portable devices capable of accurate physiological measurements are attractive tools for coaches, athletes, and practitioners. The purpose of this study was primarily to establish the validity and reliability of Movesense HR+ ECG measurements compared to the criterion three-lead ECG, and secondarily, to test the industry leader Garmin HRM. Twenty-one healthy adults participated in running and cycling incremental test protocols to exhaustion, both with rest before and after. Movesense HR+ demonstrated consistent and accurate R-peak detection, with an overall sensitivity of 99.7% and precision of 99.6% compared to the criterion; Garmin HRM sensitivity and precision were 84.7% and 87.7%, respectively. Bland-Altman analysis compared to the criterion indicated mean differences (SD) in RR' intervals of 0.23 (22.3) ms for Movesense HR+ at rest and 0.38 (18.7) ms during the incremental test. The mean difference for Garmin HRM-Pro at rest was -8.5 (111.5) ms and 27.7 (128.7) ms for the incremental test. The incremental test correlation was very strong (r = 0.98) between Movesense HR+ and criterion, and moderate (r = 0.66) for Garmin HRM-Pro. This study developed a robust peak detection algorithm and data collection protocol for Movesense HR+ and established its validity and reliability for ECG measurement.

Enhancing the sensitivity of immunomagnetic assay for 3-phenoxybenzonic acid: a novel approach utilizing magnetosome-nanobody complexes and gold nanoparticles probes.

The 3-phenoxybenzoic acid (3-PBA) residues in environment are posing a significant challenge to our daily lives. To establish a more sensitive and rapid detection method, anti-3-PBA nanobodies (Nbs) were immobilized onto magnetosomes (bacterial magnetic nanoparticles, termed as BMPs), forming a robust BMP-Nb complex. The 3-PBA derivative was labeled with horseradish peroxidase (HRP) and further associated with gold nanoparticles (AuNPs) to create a highly sensitive probe (3-PBA-HRP-AuNP). An innovative immunoassay that combined BMP-Nb complex with 3-PBA-HRP-AuNP was developed for determinaton of 3-PBA. This method enabled the determination of 3-PBA with a half-maximum signal inhibition concentration (IC50) of 1.03 ng/mL, which was more sensitive than that of using 3-PBA-HRP as tracer with an IC50 of 2.18 ng/mL. The reliability of the assay was evidenced by the quantitative recovery of 3-PBA from water and soil samples ranging from 76.85 to 95.64%. The 3-PBA residues determined by this assay in actual water samples were between < LOD and 2.54 ng/mL and were between < LOD and 11.25 ng/g (dw) in real soils, respectively, which agreed well with those of liquid chromatography mass spectrometry (LC-MS). Collectively, the BMP-Nb and 3-PBA-HRP-AuNP-based immunoassay provides a powerful tool for the precise detection of 3-PBA residues in environment matrices, reinforcing our capacity to monitor and mitigate potential ecological and health impacts associated with this prevalent pollutant.