Progesterone (P4) residues, whether resulting from improper veterinary application or environmental persistence, are established endocrine disruptors within the food supply chain. This underscores the need for analytical methods that are both sensitive and dependable. In response, we constructed a lateral flow immunoassay (LFIA) with dual-signal output, utilizing colorimetric changes and photothermal effects for the quantitative determination of P4. The assay employs Au-Pt-CdS hetero-nanostructures as versatile signal-enhancing probes. The Au-Pt-CdS nanohybrids exhibit strong and broad optical absorption spanning the visible to near-infrared (VIS-NIR) region, coupled with a high photothermal conversion efficiency of 45.60%, which collectively amplifies the signal in both detection channels. After optimization, the limits of detection (LODs) for the colorimetric/photothermal dual-mode LFIA were measured to be 0.352 ng mL[-1] and 0.087 ng mL[-1], respectively. These values represent sensitivity improvements of 1.7-fold and 6.9-fold over conventional LFIA systems based on gold nanoparticles (AuNPs). The developed method showed strong resilience to matrix interference in fortified milk and pork samples, with recovery rates between 81.49% and 123.06% and reproducible results (RSD <10%). Consequently, this dual-mode approach provides a robust, rapid, and user-friendly platform suitable for the on-site monitoring of steroid hormone residues in food systems with intricate composition.

Triclosan (TCS), a widely used antimicrobial agent, is recurrently detected in environmental and biological matrices. Its environmental persistence and potential endocrine-disrupting effects raise significant toxicological concerns. Sensitive and selective analytical strategies are therefore essential for trace-level monitoring in complex samples.

Therapeutic drug monitoring (TDM) for type 2 diabetes medications like metformin is challenging due to the lack of rapid and sensitive methods. Standard assays are often inaccurate, time-consuming, and fail to capture real-time pharmacokinetic (PK) fluctuations. Here, we developed a portable organic electrochemical transistor (OECT) sensing system for continuous, real-time tracking of metformin levels. The laser-engraved OECT biosensor is functionalized with a specific Fe2O3 nanozyme on the gate electrode for electrocatalytic oxidation of metformin, enabling highly sensitive and selective detection. Seamless integration with a smartphone application and OECT system provides dynamic real-time metformin PK monitoring in vitro, fostering a pharmacologically informed approach to diabetes management. Our findings confirm the system's potential for home-care precision PK monitoring, paving the way for personalized diabetes care.

Ulinastatin (UTI) is a glycoprotein extracted and purified from human urine. As a protease inhibitor, it mainly functions to inhibit the activity of various proteases such as trypsin and elastase, while also exerting anti-inflammatory effects and protecting tissues and organs. Therefore, the detection of UTI is of great significance in guiding clinical medication, evaluating disease severity, monitoring treatment effects, and judging prognosis. Based on CeO2:Eu[3+] nanomaterials and luminol molecules, a dual-mode biosensor integrating electrochemiluminescence (ECL) and fluorescence (FL) was constructed for the sensitive detection of UTI. CeO2:Eu[3+] significantly enhanced the ECL intensity of luminol; combined with a sandwich-type immunoreaction, this enabled sensitive and selective ECL detection of UTI. Meanwhile, FL detection of UTI was realized by leveraging the change in the intensity of luminol's characteristic emission peak in FL. Moreover, this dual-mode detection strategy can effectively improve detection accuracy, enabling the detection of UTI with high sensitivity, accuracy, and selectivity. Experimental results showed that the ECL sensor exhibited good linearity for UTI with a limit of detection (LOD) of 8.28 pM in the concentration range of 10[-11]-10[-5] M. The FL sensor exhibited good linearity for UTI with a LOD of 0.026 nM in the linear range of 10[-10] - 10[-4] M. When this dual-mode biosensor was applied to the detection of UTI in serum samples, the results of both detection modes were satisfactory.

A quadruple isotope spiking methodology has been developed and applied for the study of Hg-species-specific transformations in incubation experiments. The method enables for the first time discrimination between interconversions reactions occurring during the incubation step from those occurring during the analytical procedure. Two different mathematical models for quadruple spiking were developed and applied here in model incubation experiments to track inorganic Hg(II) methylation and methylmercury demethylation. The results showed identical Hg compounds concentrations and interconversion reactions using both mathematical approaches so that an internal validation of the calculation procedure could be achieved. The methodology was also applied to determine Hg(II) methylation, methylmercury demethylation to Hg(II) and methylmercury loss rate in incubations performed with biofilms, sediments, freshwaters and pure phytoplankton cultures with Hg concentrations ranging from pg L-1 to μg L-1. At the initial incubation time, analytical and undesired Hg(II) methylation and/or methylmercury demethylation was fully corrected and eliminated after applying the quadruple spiking methodology. Methylation during analytical procedure was found negligible for all matrices (<0.2%) whereas significant demethylation during analytical procedure (from 3 to 10%) was observed for all samples. Natural Hg(II) methylation was only found in biofilms and sediments and, the discrimination of methylmercury demethylation and loss was achieved for all samples. The overall analytical uncertainty of the newly formed compounds was clearly affected by the concentration range. Specifically, the uncertainty of the experimental peak integration and the isotopic abundances of the isotopically enriched tracers were the main parameters contributing to the overall analytical uncertainty of the newly-formed Hg compounds concentration in natural samples. This work establishes a novel approach to study transformations of Hg compounds in biological and environmental matrices. The mathematical framework, based on multiple linear regression, is in principle transferable to other poly-isotopic elements with at least five stable isotopes and commercially available isotopically enriched species standards (e.g., tin), although such extension remains to be demonstrated experimentally.

Tire rubber contains many chemicals that can enter aquatic ecosystems through tire wear particles or leachates from crumb rubber surfaces. The antiozonant N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD) and its transformation product, 6PPD-quinone, are of particular concern due to their toxicity associated with aquatic species mortality. Other relevant compounds from the PPD family are DPPD and IPPD. Vulcanizing and crosslinking agents, including benzothiazole, 2-mercaptobenzothiazole, N-cyclohexylbenzothiazole-2-sulfenamide (CBS) and hexamethoxymethylmelamine (HMMM), together with alkyl organophosphate esters and alkyldimethylamines are also of great interest. This work aimed to develop an analytical method for detecting and quantifying 11 emerging tire rubber contaminants in urban waters. The method is based on solid-phase microextraction (SPME) using commercial fibers followed by gas chromatography coupled to tandem mass spectrometry (GC-MS/MS). SPME parameters were optimized via multivariate design to efficiently extract all analytes. The method was successfully validated for linearity, precision, and accuracy, with mean recoveries of 84-105%. In all the urban water samples analyzed, 6PPD and 6PPDQ were detected. To our knowledge, this is the first time that GC-MS/MS has been applied to the analysis of most of these compounds, including PPDs, as well as the first proposal of SPME for the extraction and analysis of many of these compounds. This is also the first investigation of these substances in real water samples originating from recycled tire rubber surfaces as a potential source of contamination. Due to its simplicity, this multiresidue method, which includes antiozonants, vulcanizing, and crosslinking agents, can be easily implemented in any routine laboratory.

The monitoring of perfluorocarboxylic acids (PFCAs), a new class of persistent pollutants, has attracted widespread public concern. However, achieving highly selective enrichment of trace PFCAs in environmental samples remains a challenge for analysts.

This study explores the potential of reaction-based optical fingerprinting and total X-ray fluorescence (TXRF) elemental analysis, both separately and in combination, as a rapid and inexpensive approach to preliminary cancer diagnostics. Plasma samples from BALB/c mice with transplanted mammary carcinoma (EMT-6) and BDF1 mice with Lewis lung carcinoma (LLC) or B16 melanoma were analyzed. The optical fingerprinting method relies on differences in the oxidation rate of a carbocyanine dye in the presence of blood plasma samples. Changes in fluorescence and absorption intensity were recorded photographically, enabling high-throughput analysis. The obtained images were digitized and the resulting dataset was processed using various statistical methods. Reaction-based optical fingerprinting achieved up to 100% observed accuracy in several classification tasks within the limited proof-of-concept dataset, distinguishing between healthy and diseased animals with transplanted tumors at different time points after tumor cell inoculation: 1 week for LLC, 2 weeks for B16, and 3 weeks for EMT-6. The same samples were simultaneously analyzed using TXRF, which also achieved 100% recognition accuracy when distinguishing between healthy animals and mice bearing LLC (after 1 and 2 weeks) or B16 melanoma (after 2 weeks). Although a direct combination of the reaction-based optical fingerprinting and TXRF analysis data into a single array did not consistently improve discrimination accuracy, the individual methods complement each other and enable effective screening of various cancer types. Overall, the kinetic-based fingerprint method demonstrated significant potential in distinguishing between different types and stages of malignancies in mice.

Chikungunya virus (CHIKV) is a mosquito-borne pathogen posing a growing global threat, yet existing nucleic acid detection methods remain difficult to implement in resource-limited settings. In this study, we developed complementary catalytic hairpin assembly (CHA)-based lateral flow immunochromatography assay platforms for CHIKV nucleic acid detection by coupling CHA with time-resolved fluorescence immunochromatographic assay (TRFIA) and colloidal gold immunochromatographic assay (GICA). After systematic optimization of reaction conditions to reduce background leakage, CHA-TRFIA achieved a detection limit of 100 fM with a linear range of 100 fM to 1 μM (R[2] = 0.976), whereas CHA-GICA showed a visual detection limit of 1 pM with a linear range of 1 pM to 1 μM (R[2] = 0.947). Both platforms effectively discriminated CHIKV from mutant sequences and non-target viral sequences (dengue virus, Zika virus, Mayaro virus, Ross River virus, and Sindbis virus; P < 0.0001). In blinded trials using 100 pseudovirus-spiked human serum samples (50 positive and 50 negative), at 35 °C, CHA-TRFIA and CHA-GICA achieved sensitivities of 94% and 92%, with AUCs of 0.970 and 0.984, respectively; at room temperature, the corresponding sensitivities were 92% and 88%, with AUCs of 0.980 and 0.917, respectively. Specificity was 100% for both platforms under both conditions. Both platforms completed detection within 30 min. CHA-TRFIA is suitable for quantitative analysis, whereas CHA-GICA is more appropriate for rapid equipment-free visual screening, together providing a practical option for CHIKV testing in resource-limited settings.

Real-time continuous monitoring of soil salinity and alkalinity is essential for sustainable agriculture, yet the in-situ detection of carbonate ions (CO32-), a key indicator of soil alkalinity, remains a challenge. Herein, we designed a portable electrochemical sensor for the real-time continuous detection of free CO32- in soil. The CuO-Cu2O nanowires were synthesized by in-situ oxidation and topological transformation. The nanowires exhibited excellent chemical and structural stability and resistance to alkali, which were used as sensing material. The CuO-Cu2O sensor exhibited excellent sensing performance over a wide temperature range (0-40 °C) and pH (pH value: 7-11), and in complex media including aqueous solutions, slurry and soil, which demonstrated that the CuO-Cu2O sensor possessed excellent resistance to biological interference, immunity to colloidal particle effects and high ion selectivity, highlighting its great potential for practical applications in complex environments. The sensor demonstrated a low detection limit (5.4 ppb), wide detection range (0.01-1600 ppm), high sensitivity (264.98 μA mM-1 cm-2), excellent selectivity, and long-term stability. Density functional theory (DFT) calculations showed that CuO-Cu2O heterostructure-induced electron redistribution triggered a shift of the d-band center toward the Fermi level, strengthened CO32- adsorption, facilitated charge transfer, and then resulted in superior electrochemical response. Furthermore, it was integrated with ESP32 and Internet of Things (IoT) technology into a portable device for real-time monitoring of free CO32- concentration in soil. This work provides a strategy for soil sensors to support precision agriculture and environmental monitoring.