Analytical Methods最新文献

Direct sample extraction methods suitable for lipids such as desorption electrospray ionization (DESI), rapid evaporative ionization mass spectrometry (REIMS), and liquid extraction surface analysis (LESA) are combined with ionization or direct sample delivery to a mass spectrometer. Here, we describe three types of off-line direct sample extraction methods and their combination with multiple reaction monitoring (MRM) profiling to survey lipids present on the surface of beef and chicken meat as proof-of-concept samples. A collection of 679 MRMs selected from over 3200 MRMs related to lipids was profiled using a conventional capillary binary pump, autosampler and a triple quadrupole mass spectrometer system. The surface extraction experiments were performed manually by simply dispensing solvent onto the surface of the samples and recovering it immediately (liquid surface extraction - LSE), or by using solvent loaded into a large orifice tip to contact the sample for 5 seconds without dispensing (solvent "touch" extraction - STE). The third approach, surface vaporization extraction (SVE), was based on extracting vapors from the surface of the sample created using the tip of a wood-burning tool, collecting the vapors in a microtube, and diluting them for flow injection. LSE was used to evaluate the effect of different solvent compositions on the number of MRMs detected. Solvent acidification was also evaluated. Compared to the Bligh & Dyer extraction method using homogenized beef samples, LSE provided a consistently lower number of MRMs detected and the most informative solvent for surface extraction was pure acetonitrile. Since meat samples' surfaces are not completely flat and also present natural irregularities, the solvent volume recovered was variable. Therefore, we turned to STE to evaluate whether the lipid composition of beef brown spots was different from the red regions and to probe changes in composition due to one freeze-thaw cycle. Also, the reproducibility of STE between three users was evaluated. The third surface extraction approach, SVE, was applied to study the lipid profiles of vapors collected from raw and cooked meat. Overall, the three surface methods were able to provide informative discrimination for the different aspects assayed.

Although water quality monitoring using optical sensors has been extensively studied, it remains a frontline research area owing to its simplicity and adaptability. In this study, we continue to develop a kinetic-based sensing strategy based on multiple optical measurements during an indicator reaction. The effect on the reaction rate makes it possible to observe the effect of sample components that do not otherwise manifest themselves in photometry and fluorimetry. The oxidation of calcein (fluorescein-methyleneiminodiacetic acid) with hypochlorite or hydrogen peroxide and riboflavin with H₂O₂ in the presence of Cu(II) or Fe(II) were used as indicator reactions. Fluorescence intensity and absorbance/reflectance of reaction mixtures were measured by periodic photography of 96-well plates. Optical data were processed using supervised chemometric methods: linear discriminant analysis (LDA), logistic regression (LR) and others. To demonstrate the sensitivity of the indicator systems to compounds of various natures, six transition metal ions (Cu(II), Ni(II), Mn(II), Co(II), Fe(II), and Cr(III)) and five odor-causing organic compounds (trimethylamine, phenol, 2-chlorophenol, o-cresol, and mercaptoethanol), selected as model pollutants, were discriminated based on their nature and concentration with an accuracy of up to 95-100%. Eleven water samples were differentiated by sample and by water type (spring, well, borehole, pond, and tap) using the same indicator reactions. Municipal sewage water diluted up to 100 000 times was discriminated from river water, enabling the identification of unexpected cases of water source contamination. The obtained results surpass the benchmarks of previous studies and should serve as an incentive for further research aimed at the application of kinetic optical fingerprinting in water quality monitoring.

The concentration of iron ions is a crucial indicator for assessing water quality. In this study, nitrogen-doped carbon dots (NCDs) were synthesized using a microwave-assisted method with citric acid and urea as precursors, thereby establishing a fluorescence sensing platform for the detection of alkaline pH and Fe³⁺. During Fe³⁺ detection, the fluorescence intensity of NCDs was specifically quenched as the concentration of Fe³⁺ increased, demonstrating good linearity across the ranges of 1-10 µM and 10-100 µM, with a detection limit of 0.55 µM. By integrating smartphone-based image analysis, visual semi-quantitative detection of alkaline pH and Fe³⁺ was achieved. To enhance prediction accuracy across a broad concentration range, a machine learning model was introduced to develop a high-precision quantitative analysis method for Fe³⁺. The spiked recovery rates in actual water samples ranged from 99.26% to 101.14%, with relative standard deviations below 3%. This platform combines fluorescence sensing, smartphone imaging, and machine learning technologies, offering the advantages of simple operation and low cost, thus providing a novel strategy for the on-site rapid detection of Fe³⁺ in water environments.

This study presents the design of a multicommuted flow analysis system that utilizes an air stream to separate ethanol from wine samples. The separated ethanol is then oxidized with a dichromate solution, followed by spectrophotometric determination. The design adheres to the principles of green analytical chemistry and focuses on integrating the benefits of multicommuted flow analysis with an emphasis on versatility, robustness, minimal reagent usage, and waste reduction. The experimental setup, controlled by an Arduino Due board with electronic interfaces, was operated using custom software designed for this study. Ethanol molecules were extracted from the sample using an air stream, trapped in a reaction chamber, and subjected to derivatization with potassium dichromate (K₂Cr₂O₇), followed by photometric detection with an LED-based photometer. After optimizing the control parameters, the method's efficacy was confirmed by analyzing ethanol levels in red wine samples. The system demonstrated several advantages, including a linear response range of 2.5-25.0% (r² = 0.999), a detection limit of 0.59% (v/v) ethanol, a coefficient of variation of 1.78% (n = 10) for a 10.0% (v/v) ethanol standard solution, a sampling rate of 36 determinations per hour, a waste generation of 1.0 mL per determination, and a reagent consumption of 17 mg of K₂Cr₂O₇ per determination. Based on the AGREE - Analytical GREEnness Metric Approach, the analytical greenness of the proposed method is estimated to be 66%.

Serotonin (5-hydroxytryptamine, 5-HT) is a critical biomarker for carcinoid tumor diagnosis, yet its precise quantification in clinical settings remains challenging. Herein, we develop a high-performance optical fiber localized surface plasmon resonance (LSPR) biosensor functionalized with in situ grown gold nanoflowers (AuNFs). The hierarchical branched architecture of AuNFs concentrates electromagnetic fields into dense nanoscale "hotspots", delivering a ∼2.2-fold signal amplification compared to spherical AuNPs. Integrated with a specific 5-HT aptamer, the sensor achieves a wide linear range (10-1000 ng mL^-1) and a low limit of detection (7.06 ng mL^-1), seamlessly covering physiological to pathological concentrations. Validation in human serum confirms excellent accuracy with recoveries of 99.9-102.9%. This label-free, rapid, and cost-effective platform offers a highly promising tool for point-of-care carcinoid screening and neuroendocrine biomarker monitoring.

The transition toward decentralized environmental monitoring demands the development of integrated, portable platforms capable of combining sampling, pre-concentration, and electrochemical detection into a single device. This study introduces a proof of concept for a novel semisolid-state electrochemical platform driven by low-cost poly(sodium acrylate) hydrogels integrated with unmodified 3D-printed miniaturized sensors. The devices were fabricated via 3D pen technology using conductive polylactic acid/graphite filaments and extensively characterized by cyclic voltammetry and electrochemical impedance spectroscopy. Considering the advantage of the hydrogel's swelling dynamics, the proposed approach facilitates direct analyte uptake and provides a stable, highly controlled environment for the electrochemical process, significantly simplifying sample handling. To demonstrate the analytical feasibility of this semisolid system, sulfanilamide was selected as a representative model of veterinary antibiotic residues. Under optimized square wave voltammetry conditions (15 Hz frequency, 8 mV step potential, and 55 mV amplitude in 0.1 mol L^-1 BR buffer, pH 10.0), the platform delivered a linear response from 10 to 50 µmol L^-1 and a limit of detection of 5.55 µmol L^-1. The architecture's robustness was validated through successful recovery trials (99% to 108%) in complex aquaculture water and pharmaceutical formulations. This hydrogel-based, 3D-printed platform establishes a baseline for a simple and low-cost alternative sampling strategy, representing a significant development in field-deployable tools for smart environmental monitoring.

Although many phenotypic methods have been developed for the detection of antibiotic-resistant bacteria, this emerging field still requires more rapid, practical, and economic approaches. Herein, we report a colorimetric phenotypic antimicrobial susceptibility test integrated into a microfluidic chip (mc-AST) for the detection of carbapenem (Car)- and colistin (Col)-resistant bacteria. A key component of the mc-AST is anthocyanin, a natural pH indicator that changes color based on the pH of the reaction environment. The mc-AST contains corresponding antibiotics to suppress the growth of susceptible bacteria. The color changes in the mc-AST can be detected by the naked eye and through image processing using a smartphone. The novelty of this study lies in the first ever integration of an anthocyanin-based antibiotic susceptibility test into a microfluidic chip. This integration provides a resistance profile for multiple doses of antibiotics on a single chip. Ultimately, the mc-AST reduces the workload and delivers results within 2 hours.

MicroRNAs (miRNAs) are endogenous non-protein-coding single-stranded RNAs that play a pivotal role in gene regulation and hold great biomarker potential for cancer diagnosis. However, the detection of miRNAs in blood samples still faces challenges due to their short chain length, low abundance, high sequence homology, severe matrix interference, and susceptibility to degradation. Although the RT-qPCR method is sensitive, it is optimized for long-stranded RNA amplification and requires reverse transcription and temperature cycling, which increases the complexity of detection. Enzyme-based isothermal amplification techniques such as RCA eliminate the need for reverse transcription and temperature cycling, but they rely on expensive enzymes and require strict maintenance of enzyme activity during operation, which limits their practical applications. Catalytic hairpin assembly is a sensitive enzyme-free isothermal amplification strategy with low cost and simple operation, yet the background interference is unavoidable for homogeneous environments and the non-specific adsorption of proteins in blood samples is also a practical problem that CHA must face. This paper reports a hydrogel microsphere-based CHA method that integrates CHA signal amplification with the solid-phase carrier of hydrogel microspheres for the detection of miRNAs in blood samples. As the solid-phase carrier for CHA, hydrogel microspheres allow free entry of target miRNAs while effectively blocking large biomolecules such as proteins in the matrix (block rate of 64% for BSA). The target-triggered CHA reactions occur exclusively within the microspheres, resulting in the concentration of target molecules and their effective separation from the sample matrix. In addition, natural dehydration of microspheres after CHA reduces the volume of microspheres to one-eighth of its original size, which can further enhance the signal intensity. Microfluidic droplets serve as templates for microsphere fabrication, ensuring excellent uniformity of the hydrogel microspheres (RSD of the diameter is less than 2%.). Under optimized conditions, this method achieves a limit of detection (LOD) as low as 200 pmol L^-1 for miRNA-21. Notably, this represents a 3-fold LOD enhancement that is uniquely enabled by the dehydration treatment, in addition to the inherent signal amplification effect of the CHA reaction. The assay also exhibits a wide linear detection range spanning from 500 pmol L^-1 to 100 nmol L^-1, and retains excellent single-base mismatch discrimination capability. The recovery rates of miRNA-21 in human serum samples range from 99.5% to 104%. This proof-of-concept method exhibits favorable application potential for the detection of miRNA biomarkers in complex biological samples with a simple, low-cost, enzyme-free mode.

In bioanalysis microsampling has evolved as a promising alternative to conventional blood sampling. This is also true for mass spectrometry-based protein analysis. Developments in sampling technology and liquid chromatography mass spectrometry the last 10-15 years have expanded the field from dried blood spots sampled on paper for newborn screening to a variety of sampling devices, and applications spanning from monitoring of low abundance biomarkers through therapeutic drug monitoring of biopharmaceuticals to anti-doping analysis and multi-omics. This review gives an overview of the resent progress (2021-2026) in liquid chromatography mass spectrometry-based protein analysis from dried microsamples. We start with comparing dried microsampling to conventional blood sampling. Then we describe the different dried microsampling devices and developments, and highlights applications from different biological matrices. The typical analytical protein workflow is covered with examples from recent literature. All steps from sample extraction, through bottom-up and top-down workflows to targeted and non-targeted analysis are described together with standardization methods and automation. A few recent clinical examples and novel applications are discussed in more detail. These cover therapeutic monoclonal antibody monitoring, multiplex biomarker determination, proteome profiling and multi-omics. We also present two recent innovations: dried blood immunoassay developed for field sampling, and smart sampling where the sample preparation steps proteolysis and immunoaffinity are integrated in the sampling. In the end we discuss the technology readiness and remaining barriers to clinical translation.

Microneedle patches for interstitial fluid (ISF) extraction have significant potential in minimally invasive diagnostics, but the underlying dynamics of fluid transport remain insufficiently understood. This study presents a hierarchical computational fluid dynamics (CFD) model to systematically investigate the fluid transport dynamics within a hollow microneedle array during the ISF extraction process. The research focuses on the contributions of geometric parameters, such as lumen diameter and array spacing, to the extraction rate per unit area, comparing the fluid dynamics behaviors across 2D simplified structures, 3D single-needle structures, and periodic array structures. Experimental validation was performed using 3D-printed hollow microneedles in an agarose gel model. This research may advance the theoretical understanding and practical application of hollow microneedles in fluid extraction.