Analytical Methods最新文献

Chiral substances such as proline and glutamine have garnered increasing attention due to their distinct biological roles in different enantiomeric forms. In this study, proline and glutamine were investigated using powder X-ray diffraction (PXRD), Raman spectroscopy, and terahertz time-domain spectroscopy (THz-TDS). PXRD confirmed the crystalline structures of the samples, while Raman spectroscopy showed limited ability to distinguish between enantiomers. In contrast, THz-TDS enabled clear differentiation based on peak positions and intensities. Quantitative analysis reveals a strong linear correlation between concentration and THz response. For L-proline, the average prediction accuracy attains 96% based on peak amplitude and 98% based on peak area. Similarly, for L-glutamine, the corresponding accuracies are 96% and 92%, respectively. Notably, the most effective indicators are the peak area of L-proline at 2.08 THz (R² = 0.99980) and the peak amplitude of L-glutamine at 1.71 THz (R² = 0.98521). Furthermore, THz spectral characteristics consistent with those of pure samples were observed in two commercial dietary supplements. These findings demonstrate that THz spectroscopy offers a rapid and effective method for identifying chiral active ingredients in dietary supplements.

A single-nucleotide polymorphism (SNP) is a point mutation occurring at a defined genomic locus, and its precise and rapid detection in circulating tumor cells (CTCs) is essential for early diagnosis and therapeutic monitoring of non-small cell lung cancer (NSCLC). In this study, a CRISPR/Cas9-regulated dual-ring topological allosteric probe was developed for ultrasensitive and specific detection of the EGFR L858R mutation. The recognition ring selectively hybridizes with the target sequence and is cleaved by the Cas9–sgRNA complex, triggering the release of the reporter ring. The released reporter ring then serves as a template for rolling circle amplification (RCA), generating products that hybridize with dual-labeled fluorescent probes to yield measurable signals. This assay clearly distinguished L858R from the wild-type sequence and detected mutation frequencies as low as 1.0% with high specificity against other common EGFR variants. Its robustness was further validated using clinical blood samples, enabling sensitive detection of low-abundance L858R mutations. These results demonstrate that the integration of programmable target recognition, efficient signal amplification, and fluorescence readout provides a promising platform for SNP analysis in liquid biopsy, supporting precision diagnosis and treatment monitoring in NSCLC.

This study addresses the on-site challenge posed by large-particle (0–6 mm) coal samples, which are difficult to mill and exhibit pronounced matrix effects and strong nonlinearities that degrade the accuracy of online calorific-value prediction. We propose an NIRS–XRF fused-spectra framework—PLS–AE–RR (Partial Least Squares – Autoencoder – Ridge Regression)—for coal-quality prediction. The principal novelty of the framework is a three-tier hybrid architecture combining a linear baseline (PLS), nonlinear feature extraction (AE), and residual correction (RR). By confining complex nonlinear modeling to the residual domain of the linear model, employing an autoencoder to learn deep latent features, and applying ridge regression for precise residual correction, the approach substantially enhances robustness while preserving interpretability and facilitating engineering deployment. Using a custom NIRS–XRF dual-spectroscopy system, the method was validated on 153 mixed-particle coal samples collected from two power plants. Results demonstrate a marked improvement in calorific-value prediction for coarse coal: the PLS–AE–RR model achieved test-set R² values of 0.974 and 0.938 for lignite and bituminous coal, respectively, with MAE values of 0.233 MJ kg⁻¹ and 0.216 MJ kg⁻¹. PLS–AE–RR also consistently outperformed alternative nonlinear correction schemes (PLS-AE-RF and PLS-AE-SVR), yielding the lowest MAE and RMSE and thereby underscoring the generalization advantage of ridge regression for residual fitting. The proposed method offers coal-fired power plants a high-accuracy, high-reliability online tool for raw-coal calorific-value measurement that obviates labor-intensive sample pretreatment and supports refined fuel management and coal-blending optimization.

Food safety has become a critical global concern, with foodborne diseases affecting approximately 600 million people annually and causing 420 000 deaths each year, posing significant risks to human health and well-being. Rapid, efficient, and reliable detection methods are essential to mitigate these risks. Traditional detection methods, such as PCR and culture-based assays, while widely used, often face challenges related to speed, accuracy, and portability. Over the past 5 years (2020–2025), the (CRISPR)/Cas system has emerged as a powerful tool for food safety detection due to its high sensitivity, specificity, and versatility. This review highlights recent advances in CRISPR/Cas-based biosensors and their applications in food safety. First, we discuss the key challenges in food safety detection and the design principles of CRISPR/Cas biosensors. Next, we comprehensively summarize their applications in detecting foodborne pathogens (viruses and bacteria), food fraud, genetically modified organisms (GMOs), toxins, heavy metals, antibiotic residues, and pesticides. Finally, we address the current limitations and future prospects of CRISPR/Cas biosensors, providing insights into their potential for next-generation food safety solutions.

Surface-enhanced Raman spectroscopy (SERS) is a powerful analytical tool for the observation, the detection and the identification of chemical or biological species at low concentrations due to its high sensitivity, specific fingerprinting capability and real-time detection. However, a key challenge lies in establishing a suitable and reliable measurement protocol to ensure both reproducibility and repeatability when SERS is used as a sensing nanoplatform. In this paper, we propose a specific methodology to investigate the performance of SERS substrates, with a particular focus on their reproducibility and repeatability. Furthermore, we validate our approach on one commercial SERS Hamamatsu substrate from Hamamatsu Photonics by using diluted solution of 4-mercaptobenzoic acid (MBA) at an excitation wavelength of 633 nm. This proposed protocol consists in recording 25 SERS maps equally distributed on the whole surface substrate. For each map, 16 spectra have been acquired and averaged to provide a representative SERS signal. In total, 400 spectra have been collected and analyzed by using the integrated intensities of characteristic MBA bands to determine both reproducibility and repeatability. This approach enables us to quantify signal variations, at the micrometer scale, as well as across the entire substrate. We demonstrated that while the SERS response is highly reproducible locally, it becomes less consistent when evaluated across the full surface. However, the SERS signal is not repeatable at the local scale but it can be repeatable at the whole substrate scale as the average SERS intensity is identical for both SERS measurements. Furthermore, we demonstrated that this method can also be applied to DNA strands thereby demonstrating its effectiveness in evaluating biosensors. Finally, the proposed methodology and protocol can then be used as a standard to precisely evaluate the sensing performances of other substrates.

Detection of matrix metalloproteinase-2 (MMP-2) is of great significance for clinical diagnosis and therapy of cancer in the early stage. In this study, a novel magnetic-fluorescent nanocomposite probe for simple, fast and sensitive detection of MMP-2 was innovatively developed by self-assembly of a specifically designed MMP-2 substrate peptide and cobalt-nitrilotriacetate (Co²⁺-NTA) modified magnetic beads via the chelation mechanism. The specifically designed peptide consisted of green fluorescein (FITC) that acted as the fluorescence signal donor, and the MMP-2 cleavage sequence fused with the hexa-histidine (6× His) tag. In the presence of MMP-2, the His-tagged fluorescent peptides conjugated to the Co²⁺-NTA modified magnetic beads would be cleaved by MMP-2 due to specific substrate recognition, releasing the FITC-labeled peptide segment into the solution. After the nanocomposite probe was removed from the reaction solution by magnetic separation, high fluorescence signal intensity of the supernatant would be obtained. The proposed nanoprobe demonstrated a wide linear range and a high sensitivity for MMP-2 with a detection limit of 0.3 ng mL^-1. It also exhibited satisfactory performance in cell samples. Additionally, the novel nanoprobe could be effectively separated and recycled using a magnet, which allows it to exhibit reusable characteristics. This method not only provides a novel strategy for MMP-2 assay but also offers potential application in biomedical and clinical studies.

The development of sunscreens incorporating nanostructured lipid carriers (NLCs) is gaining traction in the cosmeceutical industry to enhance photoprotection. These innovative systems require robust and precise analytical methods to accurately quantify the chemical filters encapsulated within the lipid matrix. This study presents a fully validated RP-HPLC method specifically designed for the simultaneous quantification of three UV filters: diethylamino hydroxybenzoyl hexyl benzoate (DHHB), bis-ethylhexyloxyphenol methoxyphenyl triazine (BEMT), and ethylhexyl triazone (EHT), which were encapsulated in nanostructured lipid carriers (NLCs). The methods reported in the literature lack validation for nanostructure systems as they usually focus on exploring methods for free filters. Here, our approach was to optimize and validate an analytical method for NLCs, which demonstrated robustness, high sensitivity (LOD as low as 0.6 µg mL⁻¹), and compliance with the ICH guidelines. The method enabled the accurate and precise determination of filter extracted content, based on the extraction method, and encapsulation efficiency, supporting formulation optimization and industrial scalability by identifying a pool of interchangeable prototypes. Encapsulation efficiency of the UV-filters as the main response evaluated, which was interpreted through the critical quality attributes (CQAs) of values above 70%. Hence, the present study addresses a critical gap in the analytical methodologies for emerging nanoformulation technologies.

Insertion/deletion (indel) polymorphisms in the promoter region (23 bp) and intron 1 (12 bp) of the bovine PRNP gene influence gene expression and susceptibility to bovine spongiform encephalopathy (BSE). Conventional detection strategies dependent on DNA sequencing are cumbersome and costly. A tetra-primer amplification refractory mutation system PCR (tetra-ARMS PCR) assay was developed which can enable efficient and cost-effective genotyping of each indel locus. Optimized tetra-ARMS PCR primers and multiplex conditions allowed electrophoretic genotyping of the 23 bp indel via the size and presence of 422 bp, 259 bp, and 193 bp amplicons, whereas the 12 bp indel was genotyped based on the size and presence of 598 bp, 472 bp, and 153 bp fragments. Furthermore, the compatibility of these primer sets was preliminarily investigated, demonstrating the potential for co-amplification in a single-tube multiplex format. Validation against Sanger sequencing using 62 randomly selected cattle-derived retail samples demonstrated complete concordance. This straightforward, specific and cost-effective method requires only conventional PCR instrumentation, thereby establishing a robust and accessible platform for PRNP-assisted breeding and cattle product genotyping.

Saracatinib (AZD-0530; SRB) is a pharmaceutical agent produced by AstraZeneca and is currently undergoing clinical studies. It is classified as a dual-kinase inhibitor, exhibiting selective activity both as an Src inhibitor and a Bcr–Abl tyrosine kinase inhibitor. No metabolic stability study for SRB has been reported; hence, so the goal of the present study was to establish an ultra-fast, green, sensitive, and validated UPLC-MS/MS method for the quantification of SRB levels in human liver microsomes (HLMs) using different in silico software to support the practical outcomes. The validated approach was used to estimate the SRB metabolic stability in HLMs. In silico software tools were employed to predict the potential sites of metabolic lability and toxicity within the SRB structure. SRB and baricitinib, used as an internal standard (IS), were isolated from HLMs using protein precipitation with acetonitrile (ACN) as the extracting agent. Chromatographic separation was conducted utilizing a Luna 3 µm HILIC column (200 Å: 50 × 2 mm, Ea), with the mobile phase comprising 0.1% formic acid in ACN (85%) and 10 mM ammonium formate in water (15% at pH 3.2), and the total run time was 1.0 min. SRB and IS were analyzed utilizing the MRM mass analyzer mode. The approach was validated according to the latest FDA guidelines for bioanalytical method validation. The SRB calibration curve demonstrated significant sensitivity, with a range of statistical linearity from 1 to 4000 ng mL⁻¹. The intraday and interday accuracies of the four quality controls varied from −4.17% to 12.25% and −3.92% to 13.50%, respectively. The metabolic stability parameters, including the in vitro half-life (t_1/2) and intrinsic clearance (Cl_int) of SRB, were assessed at 17.24 min and 47.02 mL min⁻¹ kg⁻¹, respectively. In silico research indicated that slight structural modifications to the N-methyl piperazine ring in the drug design may enhance metabolic stability and safety compared with those of SRB.

The development of fast, simple, and visual methods for detecting adenosine triphosphate (ATP) is crucial for point-of-care diagnostics and environmental monitoring. Colorimetric assays based on the integration of DNA aptamer-triggered hybridization chain reaction (HCR) with gold nanoparticles (AuNPs) offer high potential, but existing methods often suffer from prolonged detection times (e.g., >130 min). To address this limitation, this study systematically investigated and optimized the core parameters of the aptamer-triggered HCR system and its subsequent mixing conditions with AuNPs to achieve a rapid visual detection platform. The HCR kinetics were accelerated by the high concentrations of single-stranded DNA (ssDNA) components, particularly the H0 initiator, as well as by the critical presence of divalent magnesium ions (Mg²⁺), which also support the functionality of the aptamer. This optimization allowed for a degree of HCR progression comparable to the traditional 24-hour incubation to be achieved within just 60 minutes. Subsequently, recognizing the inherent trade-off between the high ssDNA concentration required for fast HCR and the AuNP dispersion stability, we optimized the mixing ratio between the HCR product and the AuNP solution. Under these optimized conditions, the assay demonstrated the capability for rapid visual detection of ATP at the 100 µM level within a total assay time of 15 minutes, representing a significant acceleration compared to previously reported methods. Further improvements in sensitivity are anticipated through future fine-tuning of AuNP parameters and the use of post-reaction salt aggregation enhancers.