Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental contaminants with severe ecological toxicity, released via both biogenic and anthropogenic pathways. Ultra-sensitive analytical methods for the quantitative monitoring of trace PAHs in real samples are urgently required, yet preconcentration is indispensable for accurate analysis due to complex environmental matrices and ultra-trace PAH levels. Herein, a quinoxaline-based conjugated microporous polymer(CMP) with a fluffy rod-groove structure and large π-conjugated plane (CMP-1) was synthesized via the Sonogashira-Hagihara coupling reaction and employed as a solid-phase microextraction (SPME) coating material. Two analytical methods, direct immersion SPME (DI-SPME) and headspace SPME (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS) were established for the highly sensitive detection of 8 trace PAHs in environmental samples. Under optimized conditions, the methods exhibited excellent analytical performance: low limits of detection (LODs) of 0.001-0.0051 ng mL-1, a wide linear range of 0.036-1200 ng mL-1, and good reproducibility with relative standard deviations (RSDs) of 2.8-14.8%. The applicability and reliability of the methods were validated by analyzing three environmental water samples (artificial lake water, rainwater, and Jinlong Lake water) and three soil samples (sugarcane field soil, roadside soil, and gas station soil), with recoveries ranging from 81.2-116.4% for water samples and 70.6-106.6% for soil samples, respectively. Adsorption mechanism studies revealed that the CMP-1 coating endows efficient PAH extraction via a synergistic effect of its fluffy rod-groove porous structure, large specific surface area, hydrophobic interactions, and molecular size filling effect with PAHs. Furthermore, a greenness assessment using four authoritative metrics (GAPI, Complex GAPI, AGREE, and AGREEprep) confirmed the good green analytical chemistry characteristics and practical applicability of the proposed methods.

Early diagnosis of hepatocellular carcinoma (HCC) is crucial for improving patient survival; however, conventional detection methods using HepG2 cells (a typical HCC cell line) have inherent limitations. To address this issue, we constructed a magnetic separation-based dual-mode aptasensor that integrates FRET fluorescence (using FAM-labeled aptamers and BHQ-modified P2 strands) with AgNPs-based UV absorption. This design enables dual-signal self-validation from the precipitate (fluorescence) and the supernatant (UV). Key experimental conditions were systematically optimized. Under optimal conditions, the aptasensor exhibited good linear responses to HepG2 cells in the range of 0-5 × 105 cells per mL. For the FRET fluorescence mode, the calibration curve was FL = 249.5C + 317.1 (R2 = 0.989), while for the UV mode, it was A = 0.0504C + 0.1154 (R2 = 0.981). The aptasensor also demonstrated excellent specificity. Furthermore, it effectively detected HepG2 cells in human serum, with regression equations of FL = 285C + 620 (R2 = 0.991) for the fluorescence mode and A = 0.0296C + 0.1405 (R2 = 0.978) for the UV mode. This dual-mode aptasensor provides a novel and reliable method for the early diagnosis of HCC, leveraging the complementary advantages of FRET fluorescence and UV absorption.

Abnormal structure or function of the nucleolus can lead to dynamic imbalances in intracellular viscosity, which is a core pathological feature of major diseases, including inflammation and cancer. However, existing fluorescent probes face challenges in synchronously and accurately detecting nucleolar RNA dynamics and viscosity changes. Therefore, in this study, probes NK-1 and NK-2, which specifically target the nucleolus, were developed and synthesized. Both probes incorporate a donor-π-acceptor (D-π-A) structure with a positively charged quinolinium salt as the core, enabling specific RNA recognition through electrostatic interactions and responding to viscosity changes based on the molecular rotor mechanism. Experiments demonstrated that the two probes exhibit a rapid response, high sensitivity, robust stability, and excellent biocompatibility. They can penetrate cell membranes and nuclear membranes without a permeabilizing agent, specifically target the nucleolus, and effectively monitor nucleolar number loss in HepG2 cells. In inflammation models induced by lipopolysaccharide (LPS) and rapamycin (Rap), inflammation-induced viscosity elevation led to a marked increase in the probes' fluorescence intensity, enabling synchronous visual monitoring of nucleolar RNA dynamics and viscosity changes in living cells. The two probes provide an effective tool for identifying nucleolar abnormalities under inflammatory conditions and offer new molecular tools for early research on RNA and inflammation-related diseases, with potential to advance in-depth analysis of nucleolar functions and disease mechanisms.

The excessive and improper application of pesticides severely jeopardizes ecological balance and poses serious threats to human health. Fluorescence polarization immunoassay (FPIA) is a homogeneous immunoassay technique that offers operational simplicity and rapid analysis, demonstrating significant advantages for the high-throughput screening of pesticide residues. This review systematically elaborates on the fundamental principles of FPIA. It provides a detailed discussion on tracer design strategies, including the optimal selection of fluorophores, spacer arms, and haptens. The progress in core recognition elements is also summarized. Furthermore, the current applications of this method for pesticide detection in food and environmental matrices are reviewed, along with an analysis of the challenges it faces, such as matrix effects and sensitivity limitations. Finally, future directions for the FPIA technology are discussed, including miniaturization, intelligent integration, and the incorporation of novel materials. These directions provide a theoretical reference for enhancing its performance and broadening its application.

This work developed a novel analytical method to detect short- and ultra-short chain perfluoroalkyl carboxylic acids (PFCAs) in freshwater samples by direct injection using ion chromatography mass spectrometry (IC-MS). Ultra-short chain PFCAs, including trifluoroacetic acid (TFA), are often present in aqueous environments at higher concentrations than longer chain PFCAs, however there are currently a limited number of methods that can analyze them. Detection limits ranged between 1.3 and 2.8 ng L-1 (ppt) of the PFCAs (C2-C6) analyzed and were comparable to those of other LC-MS and GC-MS methods. The precision of this method ranged from 0.4-7.6% for all the PFCAs (C2-C6). An advantage of this method is that small samples sizes under 1 mL can be used. This method was applied to real freshwater samples including tap water, precipitation, lake water, and river water. TFA was detectable in most of the samples with online pre-concentration and no other additional pretreatment sample preparation; however, method performance decreased in samples with high conductivity. A new unidentified isobaric interferent for TFA was present in most of the freshwater samples.

Although computer vision approaches based on machine learning (ML) and deep learning (DL) have been applied to image-based food quality analysis, they typically require large labeled datasets, intensive training, and expert knowledge. Recent advances in large language models (LLMs) have enabled enhanced reasoning capabilities and flexible multimodal perception. In this work, an LLM-driven vision inspection framework featuring two inference routes was developed. The text-only inference (TOI) converts pre-extracted image features into structured textual prompts for LLM-based reasoning. The vision-language inference (VLI) directly processes raw food images using LLMs with built-in visual encoders, enabling end-to-end multimodal inference. A lightweight graphical user interface (GUI) was integrated to automate feature extraction and structured data generation with one-click operation. Several state-of-the-art LLMs were evaluated on food ripeness, freshness, and authenticity datasets. Using GPT-5, the TOI approach attained an accuracy of 1.000 on low-complexity datasets and maintained strong performance (0.875) on more complex tasks, while the VLI approach demonstrated consistently high accuracy (0.964-1.000) with substantially fewer training images, matching or surpassing traditional ML and DL baselines. The proposed framework relies solely on prompt-based in-context learning, eliminating task-specific fine-tuning. These results demonstrate the feasibility and practicality of efficient, fine-tuning-free, LLM-driven vision inspection for food quality analysis.

Highly sensitive nucleic acid detection is essential for biomedical diagnostics and bioanalytical applications, yet remains challenging due to the limited amplification efficiency and system complexity of existing sensing strategies. Herein, we report a simplified yet efficient cascade amplification strategy for nucleic acid detection by exploiting the multifunctionality of Exonuclease III (Exo III). In this design, a single Exo III enzyme simultaneously drives two mechanistically distinct amplification processes. In the first stage, the target DNA triggers Exo III-assisted strand displacement, enabling efficient target recycling and generation of abundant trigger strands. In the second stage, the released strands activate an Exo III-powered DNA walker amplification process on gold nanoparticle surfaces, resulting in an amplified fluorescence signal. Benefiting from the synergistic integration of solution-phase target recycling and interface-confined DNA walker-based amplification, the proposed system achieves high sensitivity with reduced enzymatic and operational complexity, and the limit of detection is 48.8 pM. This work provides a versatile and sequence-independent cascade amplification strategy for sensitive nucleic acid assay.

Undeclared phosphodiesterase type 5 (PDE-5) inhibitors in sexual-enhancement supplements remain a public health and regulatory concern, creating demand for rapid and affordable screening methods suitable for routine control. A capillary electrophoresis method with capacitively coupled contactless conductivity detection (CE-C4D) was developed for simultaneous determination of sildenafil, homosildenafil, hydroxyhomosildenafil, and avanafil. Separation was performed in a 60 cm × 50 µm i.d. fused-silica capillary (35 cm effective length) using 20 mM Arg/MES containing 30% (v/v) acetonitrile at pH 6.00, a voltage of 18 kV, and hydrodynamic injection by siphoning at 20 cm for 90 s. Matrix-matched calibration showed excellent linearity up to 60 ppm for all analytes (R2 > 0.99). In a surrogate supplement matrix, limits of detection and quantification were 0.59-0.86 ppm and 1.96-2.87 ppm, respectively. Precision and accuracy were suitable for screening, with repeatability and reproducibility below 10% RSD and recoveries of 102-106%. Eight commercial products were analyzed; four samples contained sildenafil, and one also contained homosildenafil, despite the absence of label declaration. Results agreed with the reference LC-MS/MS method, with deviations below 10%. These findings support CE-C4D as a practical first-tier tool for regulatory screening of PDE-5 inhibitor adulteration in health supplements.

Iron fortification of flours is an important public health strategy for reducing iron-deficiency anemia. Conventional procedures for iron determination in fortified flours generally involve acid digestion followed by determination using either flame atomic absorption spectrometry or inductively coupled plasma optical emission spectrometry (ICP-OES), which require labor-intensive sample preparation, hazardous reagents, and costly instrumentation. An alternative analytical method, based on an extraction-complexation using a thymol-1,10-phenanthroline deep eutectic solvent (DES), is proposed to reduce costs, simplify the process, and minimize the number of analytical steps. The reaction was carried out in polypropylene microtubes, followed by stirring, centrifugation and measurement of the colored DES phase using a smartphone camera. The images were processed using the RGB color system, and channel B, corresponding to the complementary color of the formed complex, was selected as the analytical response. Under optimized conditions (50 µL aqueous Fe(II) solution or 50 mg flour, 100 µL DES, 200 µL of 2.5% (m/v) ascorbic acid, and 5 min of reaction under agitation). A linear response was obtained for Fe concentrations ranging from 1.5 to 20.0 mg L-1, corresponding to 9 to 120 mg kg-1 in flour, described by the equation S = (2.5 ± 0.1)C + (100 ± 1), with an R2 of 0.994, where S corresponds to the analytical signal defined as (255 - B). The limit of detection was 0.5 mg L-1 (3.0 mg kg-1), and the coefficient of variation was 1.4% (n = 10), indicating good precision of the proposed method. Results agreed with the reference procedures based on spectrophotometry and ICP-OES after extraction with diluted acid as evaluated by Bland-Altman analysis yelding mean biases of -0.52 mg kg-1 for spectrophotometry and 1.10 mg kg-1 for ICP-OES. Relative errors ranged, respectively, from -17.1% to 4.1% for spectrophotometry and from 0% to 18% for ICP-OES. The proposed method requires low sample amounts and reduces reagent consumption, resulting in minimal waste generation. Owing to its simplicity, cost-effectiveness, and alignment with green analytical chemistry, the proposed method represents a promising alternative for routine quality control of iron-fortified flours, and the application may be extended to other food matrices.

Hypochlorous acid (HClO/HOCl) is a reactive oxygen species closely associated with immune defense and oxidative stress-related pathology, creating demand for fast and convenient analytical tools for its detection in environmental and biological matrices. Herein, a coumarin-derived fluorescent probe (XDS) was synthesized by condensing a coumarin aldehyde with a benzothiazolium salt. XDS exhibited an obvious color change (purple to colorless) and a turn-on fluorescence response toward HClO in a DMSO/PBS (3 : 7, v/v, pH 7.4) system. Under optimized conditions, XDS exhibited high selectivity against common anions, biothiols, and several reactive oxygen/nitrogen species, and reached its fluorescence plateau within ∼15 s after HClO addition. The probe was further integrated into a solid support format by loading it onto silica gel plates, enabling visual readout for HClO-spiked tap water, stream water, and mineral water samples. In addition, XDS was applied to fluorescence imaging of exogenous HClO in HepG2 cells and to adult zebrafish imaging following chemical stimulation. These results support the potential of XDS as a rapid dual-mode (colorimetric/fluorescent) platform for HClO sensing in aqueous samples and biological systems.