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7 recordsLinked to original sources

A smartphone-integrated Pt@Cu-HCF nanozyme-based paper sensor for on-site determination of total antioxidant capacity in marine oils.

Total antioxidant capacity (TAC) serves as a key indicator for evaluating the nutritional quality of foods. In this study, we designed a platinum-embedded copper hexacyanoferrate (denoted as Pt@Cu-HCF) nanozyme that exhibits high oxidase-like activity, efficiently catalyzing the oxidation of chromogenic substrates to generate robust colorimetric signals. Antioxidants quench hydroxyl radicals (∙OH) produced during the catalytic process, leading to a concentration-dependent suppression of the color signal. Leveraging this mechanism, a smartphone-integrated, colorimetric paper sensor for on-site TAC quantification was developed, using vitamin E as the calibration standard. The sensor was applied to determine TAC in fish oil, algal oil, and krill oil, demonstrating a linear response range of 9.78-312.5 μM and a limit of detection (LOD) of 6.41 μM. Validation using real-world marine oil samples showed excellent agreement with a commercial assay kit, confirming the reliability and practical applicability of this portable sensor for TAC measurement in complex biological matrices.

Antioxidants

Selective and sensitive colorimetric sensing of carbosulfan based on BiO2-x/Bi2O2.75 nanosheets with excellent haloperoxidase-like activity.

The development of colorimetric methods based on directly inhibiting nanozyme activity for pesticide detection has attracted considerable attention. In this study, we report a novel colorimetric sensing strategy utilizing BiO2-x/Bi2O2.75 nanosheets (BiO2-x/Bi2O2.75 NSs) with haloperoxidase (HPO)-like activity for the rapid and sensitive detection of carbosulfan (CBS) in foods. Oxygen-vacancy-rich BiO2-x/Bi2O2.75 NSs with HPO-like activity were rationally constructed. Kinetic studies revealed a remarkable Michaelis-Menten constant (Km) of 0.014 mM for I-, indicating a higher affinity for iodide ions than other reported HPO-like nanozymes, as evidenced by its lower Km. Under acidic conditions, CBS tends to be hydrolyzed to produce reductive sulfide species, which directly inhibit the iodoperoxidase-like activity of BiO2-x/Bi2O2.75 NSs, enabling selective detection with a limit of detection (LOD) of 0.18 μg/mL and a linear range of 0.20-100 μg/mL. When the concentration of interfering pesticides and substances was 5 times that of CBS, the sensor remained unaffected, exhibiting excellent stability and specificity. This work contributes to the detection of CBS in complex food matrices, bridging the application gap of HPO-like nanozymes in pesticide detection and providing a promising method for food safety detection.

Colorimetry

ZrO₂@C-based colorimetric/photothermal dual-mode immunosensor coupled with a novel monoclonal antibody for quantification of Aspergillus ochraceus biomass.

Aspergillus ochraceus contaminates agricultural products and produces nephrotoxic, carcinogenic ochratoxin A (OTA), posing severe food safety hazards. A dual-signal lateral flow immunochromatographic assay (dLFIA) based on ZrO₂@C nanoprobes was established for quantitative detection of A. ochraceus biomass. A novel monoclonal antibody (mAb 4B4) was prepared as the capture antibody to immobilize A. ochraceus mycelial lysate antigen on the test line, and a rabbit polyclonal antibody (pAb G2801) as the detection antibody to modify ZrO₂@C composites (synthesized via UiO-66 pyrolysis) into 200 nm colorimetric/photothermal nanoprobes. This dLFIA achieved limits of detection of 0.164 μg/mL (colorimetric) and 0.517 μg/mL (photothermal). This efficient and reliable method allows quantitative analysis of A. ochraceus biomass, which is suitable for routine monitoring of fungal contamination in agro-food matrices.

Antibodies, Monoclonal

Artificial neural network data fusion-mediated dual-mode sensor based on Fe3O4@PdIr for Salmonellatyphimurium detection in food.

Salmonella Typhimurium (S. typhimurium) is a major foodborne pathogen that poses a serious threat to public health. In this study, a colorimetric/electrochemical dual-mode biosensor assisted by artificial neural network (ANN) was developed for the sensitive detection of S. typhimurium. Fe3O4@PdIr nanocomposites with enhanced peroxidase-like activity and electrochemical performance were prepared and conjugated with an aptamer specific to S. typhimurium to obtain Fe3O4@PdIr-Apt. Through the sandwich binding of Fe3O4@PdIr-Apt and Apt to the target, the nanocomposites were attached to microplates or Au electrodes, thereby generating colorimetric and electrochemical signals. The ANN model deeply resolved the complex nonlinear relationship between the dual signals, enabling mutual correction and ultimately performing data fusion to output a single detection result, which significantly reduced the mean square error while improving detection sensitivity and reliability. This sensor exhibited a wide linear range of 2.7-2.7 × 108 CFU/mL and a low detection limit of 1.66 CFU/mL. Additionally, this method was successfully applied to the detection of S. typhimurium in pork and milk, with a recovery rate of 95.19% ∼ 104.07%. It indicated that the constructed sensor holds great practical potential for S. typhimurium detection.

Neural Networks, Computer

Machine learning-assisted Mn-N-C nanozyme colorimetric sensor array for trace-level detection of biogenic amines in meat.

Accurate detection of biogenic amines (BAs) in meat remains challenging due to their high structural similarity and co-occurrence. Herein, an Mn-N-C nanozyme was synthesized via a metal-organic framework confined pyrolysis strategy, possessing excellent oxidase (OXD)- and peroxidase (POD)-like activities. The dual enzyme-like activity showed Km values of 0.1584 mM (OXD) and 0.1498 mM (POD), respectively, in detection system. Leveraging these properties, a colorimetric sensor array was constructed, enabling the detection of four representative BAs within a concentration range of 2-10 ppm with 100% classification accuracy. In addition, a concentration independent recognition model based on an artificial neural network was developed to address signal nonlinearity interference in meat. The integrated system achieved accurate trace-level identification of BAs in perishable fish, pork, and chicken, demonstrating its applicability for early-stage BAs monitoring and quality deterioration warning during storage and transportation.

Biogenic Amines

PdIr bimetallic nanozyme engineered metal-organic frameworks integrated dual-mode sensor toward Stx2 detection in food.

Shiga toxin II (Stx2) has attracted extensive attention due to its toxicity and pathogenicity, making the development of sensitive detection methods urgent. This study constructed a dual-mode sensing platform for the sensitive detection of Stx2 in food. Composite material UIO-66@PdIr with peroxidase-like activity and fluorescent properties was synthesized and combined with cDNA as the signal probe, while aptamer-modified magnetic beads served as the capture probe. Specific binding of Stx2 to the aptamer triggered the release of the signal probe, enabling colorimetric and fluorescence signal readout. The colorimetric mode showed a linear range of 0.05-100 ng/mL with an LOD of 0.039 ng/mL, and the fluorescence mode exhibited 0.01-1000 ng/mL with an LOD of 0.0097 ng/mL. Additionally, this method was successfully applied to the detection of Stx2 in food, and the recovery rates were 94.33% ∼ 102.20%. It indicated that the constructed sensor holds great practical potential for Stx2 detection.

Food Contamination

Measurement of low-density lipoprotein cholesterol and other circulating lipids in Brazil: a systematic literature review.

Accurate laboratory assessment of circulating lipids underpins cardiovascular risk stratification, yet clinical interpretation depends not only on the assays but on the formula chosen to estimate low-density lipoprotein cholesterol (LDL-C). This review integrates the 2019-2025 evidence on laboratory methods for triglycerides (TG), total cholesterol (TC), and high-density lipoprotein cholesterol (HDLC), and on the formulas estimating LDL-C, VLDL-C, and non-HDL cholesterol, to determine how these should be measured, reported, and harmonized in Brazil, where lipid thresholds are adapted from international consensus. A PRISMA 2020 systematic search (PROSPERO CRD420251241064) of PubMed/MEDLINE, Scopus, SciELO, LILACS, Web of Science, and Embase retrieved 57,915 records; after removing 38,210 duplicates, 19,705 titles/abstracts were screened, 312 full texts assessed, and 25 sources included. Enzymatic colorimetric assays remain standard for TG, TC, and HDLC. For LDL-C, Martin/Hopkins classifies more accurately than Friedewald (89.6% vs 83.2% correct categorization in 5,051,467 patients), particularly at high TG and low LDL-C, while Sampson/NIH and modified Sampson/NIH extend reliable estimation into hypertriglyceridemia and very low LDL-C; direct measurement is reserved for TG beyond the validated range. Although the review centers on the Friedewald, Martin/Hopkins, and Sampson/NIH families that dominate guideline practice, other published equations exist and are addressed in context. In Brazil, atherogenic-lipid thresholds are risk-based decision limits rather than reference intervals; national surveys describe lipid distributions but were not designed to establish them. Analytical standardization through traceability programs, multicenter validation of formulas, and-where the distribution-based construct applies (HDLC, pediatrics)-nationally derived reference intervals are priorities for equitable cardiovascular risk assessment in Brazil.

Humans