Recent advances in analytical techniques have revealed trace amounts of D-amino acids in higher animals. A variety of their functions, which differ from those of L-forms, have also been clarified (e.g., regulation of neuronal transmission, hormonal synthesis/secretion, antioxidative effects, and barrier function in the skin). As dietary intake is considered one of the sources of D-amino acids in mammals, including humans, finding foodstuffs containing high amounts of D-forms and utilizing them as the functional ingredients are expected. For the analysis of chiral amino acids in real-world samples, high-performance liquid chromatography (HPLC) is widely adopted. However, determining minor amino acid enantiomers in complicated matrices is often affected by the co-elution of countless interfering substances, so highly selective methods are recommended for accurate quantification. To address this issue, we have developed highly selective analytical techniques for proteinogenic and metabolic-related chiral amino acids in complex matrices, either by extending the enantioselective column length or by integrating multiple separation modes (i.e., multi-dimensional HPLC). This article introduces the HPLC methods we have developed for determining chiral amino acids, particularly in food and beverage samples, and presents the results of their application.
Platinum group elements (PGEs) are rare on Earth and are considered precious metals. Their diverse industrial uses have led to concerns about the inflow of anthropogenic PGMs into the environment. However, because their concentrations in aquatic environments are extremely low, analytical methods for PGMs have not been established, and background levels remain unclear. Recent advances in analytical technology have led to the development of highly accurate and sensitive analytical methods. Solid-phase extraction using anion exchange resin, followed by measurement with an inductively coupled plasma mass spectrometry and quantification using isotope dilution, has enabled the analysis of platinum and palladium in aquatic environments, present at pmol L-1 levels. Platinum and palladium concentrations in various aquatic environments were measured and found to exhibit a conservative type of vertical distribution in the open ocean. Furthermore, concentrations were higher in coastal areas than in the open ocean, with a tendency for concentrations to increase near the seafloor. These findings suggest that platinum and palladium are being supplied to seawater from sediments. Furthermore, it was revealed that platinum exists in river water as Pt(OH)(2) and is attached to particles, but when chloride ions are mixed in, it changes form to PtCl5(OH)(2-), which repels the negatively charged particle surface and dissolves into seawater.
High-performance liquid chromatography (HPLC) is a powerful separation technique widely utilized across diverse research fields due to its high analytical precision. In the pharmaceutical industry, HPLC plays an essential role in the quality design and control of active pharmaceutical ingredients (APIs) and drug products. Efficient drug development requires the selection of an optimal HPLC condition based on the physicochemical properties of APIs and drug products, as well as appropriate separation modes and detection methods. In fact, during the coronavirus disease 2019 (COVID-19) pandemic that began in 2020, HPLC contributed significantly to the rapid development and quality assessment of COVID-19 vaccines within a remarkably short timeframe of approximately three years. This review summarizes HPLC-based analytical methods for mRNA-loaded lipid nanoparticles (LNPs) used in COVID-19 vaccines. Furthermore, we present an HPLC-based analytical method for evaluating the mRNA encapsulation efficiency within LNPs. Additionally, we discuss potential future HPLC-based applications in this evolving field, given that certain aspects of quality design in COVID-19 vaccines remain unvalidated.
Extracellular vesicles (EVs) are lipid bilayer-enclosed nanoparticles secreted by virtually all cell types and are known to carry a wide range of biomolecules, including proteins, nucleic acids, lipids and glycans, thereby mediating intercellular communication. Because their molecular profiles sensitively reflect the physiological and pathological states of the cells of origin, EVs are attracting considerable attention as non-invasive biomarkers for cancers, cardiovascular diseases and neurodegenerative disorders. In addition, their excellent immune-evasive properties and intrinsic targeting capabilities have highlighted EVs as promising next-generation modalities to enhance the precision of drug delivery, bioimaging and cancer therapy. On the other hand, EVs exhibit pronounced heterogeneity in terms of size, density and surface markers, and they are difficult to separate from coexisting lipoproteins and protein aggregates; consequently, standardization of EV isolation and purification methods remains insufficient. Moreover, robust methodologies for biomedical applications and rational design principles for nanomaterials that faithfully mimic EV functions have yet to be fully established. In this review, we summarize the diverse functions of EVs and the characteristics of related analytical technologies from the perspective of analytical chemistry, and we discuss future prospects for their diagnostic and therapeutic applications.
In this study, prompt gamma-ray analysis (PGA), which measures gamma rays emitted from nuclear reactions between neutrons and hydrogen nucleus in a sample, was applied to deter-mine hydrogen in low-melting-point metals. NIST SRM 2454a (Hydrogen in Titanium Alloy) was used as the calibration standard, and six metals bismuth, lead, gallium, tellurium, tin, and zinc were examined. Hydrogen was successfully quantified in bismuth and lead, and measure-ment uncertainties were evaluated. The hydrogen mass fractions were 7.1 mg kg-1 3.4 mg kg-1 (k = 2) for bismuth and 4.9 mg kg-1 2.0 mg kg-1 (k = 2) for lead. In contrast, quantita-tive determination for the remaining metals was not feasible due to high background levels or interfering peaks; therefore, hydrogen contents were assessed as detection limits. This study demonstrates that PGA is an effective method for hydrogen analysis in low-melting-point met-als, for which conventional inert gas fusion-based techniques are inadequate. The findings pro-vide SI-traceable fundamental data that can contribute to advanced characterization of materi-als, such as performance evaluation of hydrogen-processed products and improvement of hydrogen storage materials.
The accelerated rise in energy demand has increased the importance of electrochemical technologies, including batteries and electrolysis. Conventional analytical methods rely on simplified equations that idealize the surrounding environment of the system. However, applied systems such as batteries and electrolysis have "non-idealities" such as high electrolyte concentrations, non-uniform pH distribution, heterogeneous distribution of catalytic active sites, and insufficient supporting electrolytes. The application of idealized equations in the analysis of these phenomena risks overlooking true characteristics. The present paper discusses three analytical approaches that incorporate non-idealities. First, the effects of high electrolyte concentration and local pH in the vicinity of the electrode on water electrolysis are analyzed. Secondly, the study proposes a method for analyzing steady-state current-potential curves in oxygen reduction reactions involving catalysts with heterogeneous distribution. Thirdly, the effect of migration potential on electrode reactions in systems with low or absent supporting electrolyte concentrations is analyzed. The establishment of analytical methodologies that accurately assess non-ideal behavior in actual device environments is imperative for the advancement of applied electrochemistry. This paper discusses research aimed to bridge the gap between theory and practical systems, contributing to the further evolution of next-generation energy technologies.
Film-forming amines (FFAs) are promising corrosion inhibitors for power plant water-steam cycles, but their mechanisms of corrosion inhibition had remained unclear. This review presents a series of studies elucidating the film structure and hydrothermal reaction mechanisms of FFAs using analytical chemistry approaches. For film structure analysis, multiple complementary techniques with different principles and spatial scales were integrated: quantitative NMR spectroscopy, microscopic reflection-absorption IR spectroscopy, X-ray photoelectron spectroscopy, atomic force microscopy, and inductively coupled plasma atomic emission spectrometry. Crossvalidation through independent agreement of film thickness and adsorption data from each method demonstrated a multilayer structure with an average thickness of 0.5 mu m (corresponding to several hundred layers). For hydrothermal reaction analysis, NMR measurements using high-pressure-resistant quartz cells combined with multinuclear NMR and isotope labeling enabled identification of decomposition products and elucidation of reaction pathways. These studies provide a scientific foundation for practical application of FFAs and demonstrate the role of analytical chemistry in deepening scientific understanding of complex practical systems through a multi-faceted analytical approach.
The aggregation-induced electrochemiluminescence (AIECL) of phenanthroimidazole-functionalized tetraphenylethene (pTPI) was reported in this work. The electrochemiluminescence (ECL) intensity of pTPI was significantly enhanced with the increase of water content in DMF/water mixture. The strong emission in the aggregated state could be attributed to the restriction of intramolecular motions, which effectively suppressed the nonradiative relaxation pathway. The ECL behavior of pTPI in N,N-dimethylformamide (DMF) was investigated by transient ECL test, where the annihilation reaction was found to follow the "S-path". To achieve the application of pTPI in aqueous solution, pTPI nanowires (pTPI NWs) were synthesized via nanoprecipitation method. With triethylamine (TEA) as a coreactant, pTPI NWs demonstrated bright anodic ECL emission, with the relative ECL efficiency reaching 10.6% compared with that of Ru(bpy)(2+)(3). This work paved a new avenue for development of highly efficient ECL luminophores, and the developed pTPI NWs showed promising application prospects in the fields of biosensing and light-emitting devices.
Laccase is a member of the blue multicopper oxidase family,which catalyzes the oxidation of phenolic compounds in the presence of oxygen.As a versatile biocatalyst with broad substrate specificity,laccase holds promise for various applications such as biosensing,environmental remediation,and green catalysis.However,the practical deployment of native laccase is often hindered by the limitations of high production costs and poor operational stability.In the catalytic process of natural laccase,the redox couple between monovalent and divalent copper(Cu2+/Cu+)plays a key role in transferring electrons from the reducing substrate to oxygen molecules.Inspired by this mechanism,layered potassium birnessite(KBir)with remarkable laccase-mimicking activity was synthesized in this work.By utilizing the redox characteristics of the interlayer manganese couple(Mn4+/Mn3+),active center and catalytic function of natural laccase were successfully mimicked.Steady-state kinetic analysis confirmed that KBir had excellent catalytic efficiency,along with good stability under various conditions(Temperature,pH,inorganic salts,and organic solvents),making it a promising alternative to natural laccase.Based on this,KBir was successfully applied to detection of quercetin(QUE),demonstrating great potential in the field of biosensing.This work provided new insights into the rational design of advanced laccase-mimicking enzymes and highlighted their broad application prospects.
Cardiac troponin I (cTnI) exhibits high specificity and sensitivity for myocardial injury, serving crucial biomarker for the early diagnosis of high-risk cardiovascular diseases (CVD), such as acute myocardial infarction (AMI). Recently, to meet the demand for early screening of high-risk CVD, various nanomaterial-based analytical methods with high-performance have been developed for the precise detection of low-abundance cTnI blood samples. This review summarized recent research advancements over the past five years, focusing on physicochemical properties of different nanomaterials to enhance the performance of electrochemical and optical detection methods for cTnI. It also discussed the limitations and prospects of as-developed methods in clinical applications, providing a detailed outline for the development of new methods for precise early screening of high risk CVD.
The ultra-low abundance of tumor markers and interference from complex matrices in liquid biopsy represent the primary bottlenecks for early cancer screening,and single amplification strategyis can bardly achieve a good balance among sensitivity,specificity,and reaction speed.In recent years,clustered regularly interspaced short palindromic repeats(CRISPR)and CRISPR-associated proteins(Cas)system-assisted molecular self-assembly strategy was used in detection of tumor biomarker.Leveraging the precise recognition and efficient cleavage activity of CRISPR-Cas system,this synergistic strategy effectively overcomes the challenges of background leakage and sluggish kinetics associated with traditional enzyme-free self-assembly.By constructing a cascade signal amplification loop,CRISPR-Cas system-assisted molecular self-assembly strategies enable the ultrasensitive and highly specific detection of trace markers such as circular tumor DNA(ctDNA)and micro RNA(miRNA).Herein,recent research progress on CRISPR-Cas system-assisted molecular self-assembly strategies for tumor marker detection was reviewed.The applications of this dual signal amplification mechanism in the field of physical sensing were introduced.The deep integration of the CRISPR-Cas system-assisted molecular self-assembly strategies with artificial intelligence,solid-state reagent storage,and microfluidic technology constituted a pivotal direction for advancing its application in clinical point-of-care testing.
The abuse of drugs,including narcotics and psychotropic substances,antibiotics,and additives,has become a significant threat to global public health security and social stability.Therefore,the development of rapid,efficient,portable,and on-site screening technologies suitable for resource-limited environments is of great importance for the early detection,effective regulation,and monitoring of trends in drug abuse.Lateral flow immunoassay(LFIA),leveraging its operational simplicity,rapid response,cost-effectiveness,and suitability for non-laboratory settings,has emerged as a pivotal platform for point-of-care testing(POCT)of abuse drugs.Among these,nanotags,serving as signal carriers,play a key role in enabling high-performance LFIA by conjugating antibodies to output detection signals.This review began with a brief introduction to LFIA technology,systematically summarized recent research progress in LFIA recognition mechanisms,novel nanolabels,and signal transduction strategies for drug abuse detection,and discussed the remaining challenges and future trends in this field.
Poor targeting specificity and low intracellular bioavailability have become key factors restricting the improvement of clinical therapeutic efficacy in tumor treatment.The tumor microenvironment(TME)exhibits characteristics including acidity,hypoxia,overexpression of specific enzymes,and redox imbalance,which provide natural targets for tumor tissue-specific response behavior of nanodrugs.Moreover,the functional homeostasis of subcellular organelles such as mitochondria,lysosomes,endoplasmic reticulum,and nucleus is a core determinant regulating the fate of tumor cells.This paper focuses on the signal-driven cascade targeting strategy,which takes TME characteristic signals as the primary trigger to help nanodrugs overcome in vivo physiological barriers and achieve specific responses in tumor tissues.Subsequently,cascade reactions expose organelle-targeting moieties,and secondary precise localization is realized by virtue of the microenvironmental differences between subcellular organelles and cytosol,thereby achieving specific intervention in subcellular organelle functions.This study systematically summarizes the design principles of cascade targeting driven by acidic,enzymatic,redox,and hypoxic signals,with a focus on the application pathways of core mechanisms(e.g.,charge reversal,structural conformation change,and prodrug activation)in subcellular organelle precision therapy,as well as the synergistic potential of this strategy to ameliorate tumor therapy resistance and remodel the tumor immune microenvironment.This work aims to provide a theoretical reference for the development of intelligent nanodrugs and precise tumor therapy.
Accurate identification of single nucleotide variants (SNVs) is essential for diagnosing pathogen drug resistance. However, current isothermal amplification-based assays often suffer from insufficient specificity in SNVs discrimination and limited multiplexing capability. Here, an enzyme-free nucleic acid circuit for SNVs detection based on a four-way junction (4WJ) was developed. By exploiting a toehold-mediated strand exchange (TMSE) mechanism within an"X-shaped"topological framework, the circuit enabled highly sensitive discrimination of single-base mismatches. By using katG S315T mutation associated with isoniazid resistance in M. tuberculosis as a model, the circuit reliably distinguished targets differing by SNVs. When coupled with loop-mediated isothermal amplification (LAMP), the system achieved selective detection of mutant targets down to 1 copy/mu L, generating signals significantly stronger than 5000 copies/mu L wild-type background. Moreover, modular extension of the supporting strands enabled the construction of an OR logic gate for simultaneous detection of isoniazid and rifampicin resistance mutations (rpoB S531L), demonstrating the multiplexing capability of the platform. This strategy operated without the need for precise thermal cycling instrumentation and offered a rapid, simple, and high-fidelity approach, providing a promising method for preliminary screening of pathogen drug resistance in resource-limited settings.
Bacterial infections pose a severe threat to human health and public health security.Existing detection methods suffer from limitations including long time duration,complex operation,and reliance on professional skills.Moreover,the detection systems often lack antibacterial functionality,leading to delays in early warning and intervention for infection,thus creating an urgent demand for rapid detection and efficient bacteriostatic technologies.To address these issues,a dual-functional system integrating colorimetric detection and bacteriostasis based on chlorogenic acid(CGA),a natural herbal extract,was developed in this study.Firstly,the detection medium was screened based on simulated body fluid(SBF),and its key components and CGA concentration were further optimized.Using Escherichia coli(E.coli)and Staphylococcus aureus(S.aureus)as model bacteria,the visual detection range for both strains with CGA reached 104-108 CFU/mL,and the maximum bacteriostatic rate was 100%.Biocompatibility experiments demonstrated that the hemolysis rate of CGA was below 5%within the effective concentration range.After treating human umbilical vein endothelial cells(HUVECs)and mouse fibroblasts(L929 cells)with this system,the cell viability exceeded 80%,preliminarily indicating good biocompatibility.In practical application tests,this system showed a certain ability to identify infections in terms of warning about bacterial contamination of contact lenses and detecting bacterial infections in clinical urine samples.This work provided a green,convenient,and low-cost new strategy for rapid diagnosis,prevention,and control of bacterial infections,holding broad application prospects in the fields such as medical device quality control and daily hygiene protection.
Copper-based metal-organic framework nanofibers (Cu-MOF NFs) were synthesized via a solvothermal method using 1,2,4,5-benzenetetracarboxylic acid (H4BTEC) as ligand for electrochemical detection of metronidazole (MET) residues in the gingival crevicular fluid (GCF) of periodontitis patients. The morphology and crystal structure of the samples were characterized using scanning electron microscopy (SEM) and X-ray diffraction (XRD). The results showed that the Cu-MOF NFs prepared with a reaction time of 60 min exhibited a long-range ordered crystal structure and had the highest specific surface area (121.4 m(2)/g). By optimizing the electrochemical detection parameters, square wave voltammetry (SWV) results showed that the constructed electrochemical sensor exhibited high sensitivity toward MET detection, the detection sensitivity was 228.18 & micro;A/(& micro;mol & centerdot;cm(2)), linear detection range was 1-6 & micro;mol/L, and limit of detection (3 sigma) was 0.333 & micro;mol/L. When applied to detection of MET in real GCF samples, this sensor also showed satisfactory detection accuracy, thus providing preliminary research experience for its practical application in complex oral environment.
Neurodegenerative diseases are a group of major chronic disorders characterized by continuous neuronal damage and functional degeneration of the central nervous system,including Alzheimer's disease,Parkinson's disease,Huntington's disease,and amyotrophic lateral sclerosis.They exhibit insidious onset,slow progression,and irreversible impairment,with pathological changes often occurring long before clinical symptoms appear.Therefore,developing highly sensitive detection technologies capable of achieving early diagnosis and dynamic monitoring is of great importance.Surface-enhanced Raman spectroscopy(SERS),relying on strong signal enhancement induced by localized surface plasmon resonance and charge-transfer effects,can achieve ultrasensitive,conformation-specific,and molecular"fingerprint"-level detection of a wide range of disease-related biomarkers in complex biofluids,providing a new approach to compensate for the limitations of traditional imaging,immunoassays,and mass spectrometry in early screening,noninvasive detection,and high-throughput applications.This review systematically summarizes the research progress of SERS in major neurodegenerative diseases over the past decade,highlighting representative advances in protein aggregate structural analysis,fluid biomarker detection,and cellular and tissue imaging,and further discussing how strategies such as lateral-flow assays,microfluidic integration,and machine-learning methods enhance SERS sensitivity,selectivity,and stability.Finally,current challenges in substrate standardization,signal repeatability,and clinical validation are summarized,and the potential of constructing high-performance and multi-biomarker SERS detection platforms for precise diagnosis of neurodegenerative diseases is envisioned.
