Analytical Methods最新文献

Microplastics (MPs) are an emerging pollutant of global concern, creating an urgent need for rapid and accurate monitoring workflows. Deep learning-based computer vision has demonstrated strong performance in finding particles in microscopy images, but its use as a front-end module for automated IR/Raman microscope-based MP analysis remains insufficiently developed, particularly in workflows that convert image-level particle detection results into microscope-executable operations for particle morphological characterization and spectral acquisition planning. Here, we aim to address this gap. First, reference MPs were deposited on Anodisc filters and glass slides, from which 626 bright-field micrographs containing 7010 particles were collected. The dataset was randomly split into training, validation, and test sets in a 7 : 2 : 1 ratio, and an Ultralytics YOLO11 instance segmentation model was developed. At an intersection-over-union (IoU) threshold of 0.7, testing achieved precision, recall, and F1 scores of 0.86, 0.93, and 0.89, respectively, outperforming two benchmark methods: a threshold-based method (F1 = 0.25) and Mask R-CNN (F1 = 0.84). On another test set prepared from tap water (with a relatively clean background), the model achieved precision, recall, and F1 scores of 0.78, 0.90, and 0.83 at IoU = 0.7. However, particle detection performance decreased with dirtier image backgrounds, as shown by testing on the sample prepared from commercial salt. We addressed key technical challenges required for end-to-end automation, including per-field autofocus, recovering true microscope coordinates from YOLO style outputs, converting detections into particle descriptors for downstream characterization, and programmatic microscope control for image collection and spectrum acquisition planning. Full implementation, code, and well annotated data are released openly, enabling adoption and extension of this workflow for broader MP monitoring applications.

The One Health philosophy highlights the need to sustainably balance and optimise the health of humans, animals, and ecosystems. Pharmaceuticals are essential for human health, but their usage poses downstream risks to aquatic life. Thus, pharmaceuticals need to be environmentally friendlier whilst delivering the same intended health outcomes. Chiral switch, whereby racemic formulations are replaced with enantiopure versions, is proposed to reduce the environmental burden of pharmaceuticals under the One Health philosophy. This research aimed to develop enantioselective methodologies applicable to complex environmental matrices to inform the chiral switch of commonly prescribed pharmaceuticals. This was achieved using cation exchange solid-phase extraction (SPE) and two separate chiral-high performance liquid chromatography (HPLC) methods for selective detection and quantification of 16 pharmaceuticals (anti-depressants, beta-blockers, calcium-channel blocker, central nervous system stimulant, skeletal muscle relaxant) and primary metabolites in wastewaters. An InfinityLab Poroshell 120 Chiral-V was used to separate cationic enantiomers and CHIRALPAK® ZWIX(+) for zwitterions with enantioresolutions ranging from 0.6 to 4.2. Quantitation limits and trueness values of the SPE-chiral HPLC methods ranged from 6.5 × 10^-2 ng L^-1 to 42 ng L^-1 and from 60% to 119%, respectively. Application of the methodology to wastewater samples revealed several analytes were in non-racemic composition including citalopram, fluoxetine, mirtazapine, desmethylmirtazapine, and ritalinic acid. Greatest enantiomer enrichment was observed for desmethylmirtazapine with a maximum enantiomeric fraction of 0.80. Furthermore, to the best of our knowledge this is the first study to report the enantiomeric composition of baclofen, amlodipine, hydroxyatenolol and ritalinic acid in wastewater. Further application of these newly developed methods can help develop more accurate environmental risk assessments of pharmaceutical enantiomers to inform the proposed chiral switch decision making process in healthcare.

Correction for 'Carbon-dot-encapsulated molecularly imprinted polymer as a selective optical sensor for the monitoring of tebuconazole in food samples' by Shahida Rashid et al., Anal. Methods, 2026, 18, 6810-6822, https://doi.org/10.1039/d6ay00571c.

Functionalized carbon dot nanoparticles are at the forefront of biological applications of carbon nanoparticles (CNPs), particularly in bioimaging and biosensing. In this study, both functionalized and unfunctionalized CNPs were utilized as fluorescent probes in cancer cell lines and Drosophila melanogaster. A human T lymphocyte (Jurkat), the MCF 10A cell line, and the wild-type Oregon strains of D. melanogaster were used in the study. N-doped CNPs were synthesized solely from o-phenylenediamine (oPD CNPs), and thiol-functionalized CNPs were synthesized from o-phenylenediamine and L-cysteine (SH-CNPs), both via a microwave-assisted synthesis. The synthesized SH-CNPs show maximum excitation and emission intensity at 340 nm and 412 nm, respectively. UV-vis absorption spectra present absorption peaks at 238 nm, ∼279 nm, and ∼297 nm, which are attributed to π → π* and n → π* transition states in thiol-containing aromatic systems. CNPs were spherical and polydisperse, with an average size of 64 ± 29 nm. Chemical characterization revealed the presence of the -SH functional group, characterized by an infrared absorption band at ∼2550 cm^-1, alongside other functional groups (OH, CO, COO, CC, C-C, NH, NH₂) on the surface of both the CNPs and their core. X-ray photoelectron spectroscopy analysis of S 2p also shows the binding energy of ∼164 eV allotted to C-SH. Scanning Electron Microscope/Energy Dispersive Spectroscope reveals the weight percentage (wt%) of the elemental composition of SH-CNPs to be 62.9 ± 0.2%, 17.2 ± 0.2%, 14.7 ± 0.1%, and 5.2 ± 0.1% for carbon, nitrogen, oxygen, and sulfur, respectively. A significant difference in the intensity of the SH-CNPs fluorescence between larvae treated with hydrogen peroxide (H₂O₂) and larvae treated with potassium superoxide (KO₂), with the latter group showing reduced fluorescence intensity. Taken together, these results demonstrate that surface functionalization plays a critical role in modulating the biological response and sensing capability of carbon dot nanoparticles. While unfunctionalized oPD CNPs are effective for structural bioimaging, thiol-functionalized CNPs provide additional functional sensitivity to oxidative stress conditions.

Reliable quantification of ascorbic acid (AA) is essential for pharmaceutical quality control. Herein, we report Fe-doped carbon dots (Fe-CDs) as a fluorescent nanozyme for the colorimetric/fluorometric dual-mode quantification of AA. Fe doping endows CDs with intrinsic peroxidase-like activity to catalyze H₂O₂-mediated oxidation of colorless 3,3',5,5'-tetramethylbenzidine (TMB) to blue oxidized TMB (oxTMB), quenching the fluorescence of Fe-CDs via the inner filter effect. The introduction of AA reduces the oxTMB and leads to a decrease in absorbance and recovery of fluorescence. Such Fe-CD based dual-mode method achieves high sensitivity for AA quantification with a limit of detection of 89.1 ng mL^-1 for the colorimetric mode and 90.9 ng mL^-1 for the fluorometric mode, and exhibits satisfactory quantification accuracy in commercial AA tablets, demonstrating its applicability as a reliable, sensitive, and point-of-need tool for quality control of pharmaceutical tablets.

A rapid isocratic LC-MS/MS method for quantifying busulfan in human plasma was developed and validated. Plasma samples were processed by protein precipitation with acetonitrile using busulfan-d₈ as the internal standard. Separation was performed on a Kinetex C18 column (2.1 × 50 mm, 5 µm; Phenomenex) with isocratic elution (water : acetonitrile = 70 : 30, v/v, containing 1 mM formic acid and 1 mM ammonium acetate) at 0.5 mL min^-1, with a total run time of 1 min. Detection was conducted using positive electrospray ionization in multiple reaction monitoring mode (m/z 264.1 → 151.1 for busulfan; m/z 272.1 → 159.1 for busulfan-d₈). The assay was linear over the concentration range of 0.100-10.0 µg mL^-1 (r = 0.9998). Intra- and inter-batch RSD values were <5.5% and bias ranged from -3.6% to 5.0%. Recovery and matrix effect values were 100.1-101.3% and 101.4-101.8%, respectively. The method was successfully applied to 85 pediatric patients undergoing bone marrow transplantation. AUC_0-∞ could be reliably estimated in 70 of the 85 patients (82.4%). Of these, 61.4% achieved the target AUC_0-∞ (900-1500 µmol min L^-1) after the first dose, while 18.6% fell below and 20.0% exceeded the target range, highlighting the substantial pharmacokinetic variability and the inadequacy of weight-based dosing in pediatric patients. This simple, rapid (1 min per sample) method is suitable for busulfan therapeutic drug monitoring in pediatric patients.

N-Acetylcysteine (NAC), a thiol-containing mucolytic agent for COPD, exhibits significant pharmacokinetic variability among patients, motivating the need for convenient therapeutic monitoring. Herein, a colorimetric platform based on copper-doped chiral carbon dots (Cu-D-CDs) was synthesized via a one-pot hydrothermal route using D-histidine and CuCl₂ as precursors. The Cu-D-CDs displayed enhanced peroxidase-like activity, catalyzing H₂O₂-mediated oxidation of TMB to blue oxTMB (λ_max = 652 nm). Upon NAC introduction, oxTMB was reduced via a thiol-disulfide redox reaction, producing an absorbance decrease proportional to NAC concentration. Under optimized conditions, the assay exhibited a linear dynamic range of 10-90 µM, a detection limit of 3.74 µM (LOD = 3σ/S), and recoveries of 96.00-106.60% (RSD < 4%) in mouse serum, demonstrating its feasibility for NAC quantification in serum samples. Beyond the single-wavelength readout at 652 nm, the full-spectral data were further processed by an LSTM network, which significantly improved prediction accuracy (R² > 0.9998) compared with single-wavelength calibration (R² = 0.9979), effectively mitigating matrix interference. This integrated colorimetric-LSTM strategy shows promise for COPD therapeutic drug monitoring and pharmaceutical quality control.

We developed an isothermal, equipment-minimal single-nucleotide polymorphism genotyping platform coupling recombinase polymerase amplification with toehold-mediated strand displacement. By using dU-primers and uracil-DNA glycosylase treatment to expose toeholds on amplicons, we achieved 0.1% mutant allele sensitivity and full concordance with standard genotyping methods across all tested clinical samples, providing a robust solution for potential application.

A proof-of-concept differential dual-modal aptamer array was developed for clenbuterol (CLB) and salbutamol (SAL) screening in artificial urine. A CLB-selective aptamer and AP-Ago, a broad β₂-agonist aptamer, were coupled to graphene-oxide fluorescence resonance energy transfer and to methylene-blue/ferrocene-labelled gold electrodes. Their four responses formed an analyte fingerprint by combining CLB-selective recognition with the broader response of AP-Ago. Seventy-two blind-coded samples represented six matrices, four screening classes and three independent preparation batches. Batches 1-2 (n = 48) supported model development, whereas batch 3 (n = 24; six samples per class) was locked for external assessment. Weighted calibration gave provisional procedural limits of detection of 0.083 ng mL^-1 for CLB and 0.164 ng mL^-1 for SAL. Mean external prediction-to-reference ratios were approximately 96% for CLB and 81% for SAL, distinct from controlled spike recoveries; intraday precision was 3.7% and interbatch precision was 5.8%. Against isotope-dilution LC-MS/MS, concordance correlation coefficients were 0.939 for CLB and 0.793 for SAL. A regularized multinomial logistic model achieved external balanced accuracy of 0.833, macro-F1 of 0.836 and Matthews correlation coefficient of 0.791. The reported bootstrap 95% confidence interval for balanced accuracy was 0.656-0.969, reflecting the small external set. The results support a candidate front-end triage strategy within the tested artificial matrices: differential signals identify presumptive CLB, SAL-associated high-response and mixed patterns, while any presumptive positive is referred for confirmatory LC-MS/MS rather than used for an anti-doping adjudication.

Titanium dioxide (TiO₂) is a critical functional component in paint formulations, providing essential properties such as opacity, whiteness, UV resistance, high cleaning power and durability. Given that TiO₂ is among the most expensive raw materials in the industry, accurate quantification is vital for both quality control and cost-benefit optimization. This study aimed to optimize a routine analytical method for TiO₂ determination by focusing on the sample preparation stage-the most resource-intensive phase of the process. A comparative analysis was conducted between the traditional direct acid digestion method and a proposed alternative incorporating a calcination step. The performance was evaluated using UV-vis molecular spectroscopy based on validation criteria including analysis time, reagent consumption, and sample throughput. The optimized method demonstrated high linearity (R² > 0.99) with a Limit of Detection (LOD) and Limit of Quantification (LOQ) of 4.35 and 5.76 mg L^-1, respectively. The process proved precise and accurate, with a Coefficient of Variation (CV) below 5.0% and recoveries exceeding 95% across all concentration levels. While statistical differences between analysts were noted for two solvent-based samples (t-test > t-critical of 12.7), the calcination step demonstrated significant advantages for routine operations. Implementation resulted in a 50% reduction in total analysis time, a 25% decrease in acid consumption, and a 75% reduction in energy expenditure. Furthermore, evaluation via the AGREEprep tool confirmed that the proposed method significantly enhances analyst safety and aligns with green analytical chemistry principles.