Rapid Analytical Method Research Articles

A Novel Neural Network Architecture Dedicated for LIBS Spectrum Analysis With Its Application to Steel Pipe Classification

Abstract As a non-destructive rapid composition analysis method, Laser-induced breakdown spectroscopy (LIBS) has received widespread attention in recent years. However, its application in the steel industry has not achieved an effective breakthrough in its detection accuracy due to the existence of matrix effect. This paper introduces a neural network model for LIBS spectral line analysis, which can automatically construct the features and analyze the correlation between them, and this model has been applied in the steel sample classification of seamless steel pipe with good results.

Convolutional-free Malware Image Classification using Self-attention Mechanisms

Malware analysis is a critical aspect of cybersecurity, aiming to identify and differentiate malicious software from benign programmes to protect computer systems from security threats. Despite advancements in cybersecurity measures, malware continues to pose significant risks in cyberspace, necessitating accurate and rapid analysis methods. This paper introduces an innovative approach to malware classification using image analysis, involving three key phases: converting operation codes into RGB image data, employing a Generative Adversarial Network (GAN) for synthetic oversampling, and utilising a simplified Vision Transformer (ViT)-based classifier for image analysis. The method enhances feature richness and explainability through visual imagery data and addresses imbalanced classification using GAN-based oversampling techniques. The proposed framework combines the strengths of convolutional autoencoders, hybrid classifiers, and adapted ViT models to achieve a balance between accuracy and computational efficiency. As shown in the experiments, our convolutional-free approach possesses excellent accuracy and precision compared with convolutional models and outperforms CNN models on two datasets, thanks to the multi-head attention mechanism. On the Big2015 dataset, our model outperforms other CNN models with an accuracy of 0.8369 and an AUC of 0.9791. Specifically, our model reaches an accuracy of 0.9697 and an F1 score of 0.9702 on MALIMG, which is extraordinary.

Smartphone-integrated inkjet-printed paper sensor and UV/Vis spectrophotometric method for on-site detection of As3+ and L-cysteine in food samples using novel AMTPP-functionalized silver nanoparticles

The increasing prevalence of arsenic (As3+) in water and its health impacts necessitate advanced detection methods. Similarly, monitoring L-Cysteine, a vital thiol-containing amino acid, is crucial for assessing physiological processes and disorders. This study presents a novel method for detecting As3+ and L-Cysteine in food samples using 4-amino-3-(D-galactopentitol-1-yl)-5-mercapto-1,2,4-triazole (AMTPP) functionalized silver nanoparticles (AMTPP-AgNPs) by UV/Vis spectrophotometric method and smartphone-assisted inkjet-printed paper-based sensors. AMTPP-AgNPs, synthesized through a detailed process, show exceptional selectivity and sensitivity to As3+ and L-Cysteine, undisturbed by other metal ions and amino acids. Characterization techniques like FTIR, DLS, Zeta Potential, AFM, and SEM detailed their morphological and interaction properties. Optimizing detection parameters, such as response time, pH, and temperature, improved sensitivity and achieved low detection limits. The limits of detection (LODs) were 0.0052 μM for L-cysteine and 0.0092 μM for As3+, as calculated using UV–Vis spectrophotometric methods. The method also demonstrated high recovery rates in spiked meat and corn samples. This research offers a cost-effective, rapid method for on-site food analysis, significantly aiding environmental and public health monitoring.

Novel rapid molecular diagnosis methods for comprehensive genetic analysis of 21-hydroxylase deficiency

BackgroundMolecular analysis of the CYP21A2 gene is highly important for understanding the aetiology of 21-hydroxylase deficiency (21-OHD). The aim of this study was to use a novel approach named CNVplex, together with the SNaPshot assay and direct sequencing, to identify CYP21A2 mutations efficiently and comprehensively. Targeted CYP21A2 mutation analysis was performed in 113 patients and 226 parents. Large rearrangements of CYP21A2 were characterized by CNVplex; twenty prevalent mutations, including nine common micro-conversions and eleven high-frequency mutations reported in the literature, were detected by SNaPshot; and rare mutations were investigated by direct sequencing.ResultsAmong the 113 21-OHD patients, 95.6% of the affected alleles were detected accurately by SNaPshot and CNVplex. Prevalent mutations were detected in 69.5% of the alleles; 62.4% of alleles contained pseudogene-derived micro-conversions, 1.8% contained nonpseudogene-derived mutations, and 5.3% contained complex variations resulting from multiple recombinations between CYP21A2 and CYP21A1P. Large rearrangements were identified in 27.0% of the alleles, including five types (CH-1, CH-3, CH-4, CH-5 and CH-8) of chimeric CYP21A1P/CYP21A2 genes. Two novel CYP21A2 haplotypes and four de novo CYP21A2 mutations were characterized. A rare haplotype with a c.955 C > T mutation in the duplicated CYP21A2 gene was found in 0.9% of the probands and 33.3% of the parents. In addition, four parents were also diagnosed with 21-OHD.ConclusionCNVplex and SNaPshot appear to be highly efficient and reliable techniques for use in a molecular diagnosis laboratory, and combined with direct sequencing based on locus-specific PCR, they might constitute a definitive way to detect almost all common and rare 21-OHD-related alleles.

A Rapid Analysis Method for Determination of Hydrocarbon Types in Aviation Turbine Fuel by Gas Chromatography-Mass Spectrometry.

A rapid analysis method for determination of hydrocarbon types in aviation turbine fuel was investigated in this study. A kind of reversible adsorption material packed as an unsaturated trap was used to separate saturated hydrocarbons and unsaturated hydrocarbons in the GC-MS system. No manual process or organic reagent was needed during the entire analysis process. The contents of 13 kinds of hydrocarbons, including paraffins, monocycloparaffins, dicycloparaffins, tricycloparaffins, monoolefins, cycloolefins, alkylbenzenes, CnH2n-8 aromatics, CnH2n-10 aromatics, naphthalenes, CnH2n-14 aromatics, CnH2n-16 aromatics, and CnH2n-18 aromatics were calculated by the characteristic mass fragments detected by MS with the modified matrices of ASTM D2425. The overall analysis time was less than 10 min. The precision of this test method has been conducted with 8 laboratories attended and 16 samples analyzed. The performance of this new method was demonstrated by comparing the results tested by ASTM D1319, ASTM D2425, and ASTM D6379. This rapid analysis method can provide hydrocarbon compositions of aviation turbine fuels or other liquid hydrocarbon samples within the same distillation range.

Analysis and experimental evaluation framework for buckling and post-buckling of composite stiffened panels

The composite thin-walled stiffened panel exhibits considerable potential for post-buckling bearing capacity. However, due to the limitations in post-buckling analysis and experimental evaluation capabilities, local buckling under limited loads is not permissible for current aircraft composite panels, significantly diminishing the weight reduction effect of composite panels. In this paper, experimental research on composite fuselage curved panels under combined compression and shear loads was conducted with an experimental system. The buckling analysis and failure prediction of composite fuselage curved panels were performed by the finite element method, using the interlaminar failure criterion and an improved Tsai-Wu failure criterion. Meanwhile, interaction formulaes were utilized to predict buckling correlation curves and failure envelopes. The results show that the finite element model with improved criteria and the rapid analysis method based on interaction formulaes exhibit high accuracy, which are available for properties analysis of composite panels. The experimental techniques and analytical methods proposed in this paper can provide a way to evaluate the buckling and post-buckling performance of composite stiffened panels.

Fast Determination and Source Apportionment of Eight Polycyclic Aromatic Hydrocarbons in PM10 Using the Chemometric-Assisted HPLC-DAD Method

Polycyclic aromatic hydrocarbons (PAHs) are a group of organic compounds that are both toxic and hazardous to human health and ecological systems. In recent work, a novel analytical strategy based on the chemometric-assisted HPLC-DAD method was proposed for the quantification and source apportionment of eight PAHs in PM10 samples. Compared to traditional chromatographic methods, this approach does not require the purification of complex PM10 samples. Instead, it utilizes a mathematical separation method to extract analytes’ profiles from overlapping chromatographic peaks, enabling precise quantification of PAHs in PM10. Firstly, 40 PM10 samples collected in Loudi city during two sampling periods were used for analysis. Subsequently, the second-order calibration method based on alternating trilinear decomposition (ATLD) was employed to handle the three-way HPLC-DAD data. Finally, the pollution sources of PAHs were analyzed by the feature component analysis method according to the obtained relative concentration matrix. For the validation model, the average recoveries of eight PAHs were between (88.8 ± 7.6)% and (105.6 ± 7.5)%, and the root-mean-square errors of prediction ranged from 0.03 μg mL−1 to 0.47 μg mL−1. The obtained limits of quantification for eight PAHs were in the range of 0.0050 μg mL−1 to 0.079 μg mL−1. For actual PM10 samples, results of the feature component analysis indicated that the main source of PAHs in PM10 may be traffic emissions and coal combustion. In summary, the proposed method provided a new and rapid analysis method for the accurate determination and source apportionment of PAHs in atmospheric aerosols.

Voltammetric Determination of Diazepam – A Comprehensive Review

The review deals with the fundamental characteristics of an important biologically active substance – diazepam, summarizing voltammetric methods for its determination in various samples. This 1,4-benzodiazepine derivative is used as an adjunct to treat anxiety associated with psychiatric illnesses (e.g. schizophrenia). Due to the increasing number of forensic cases related to overdose of diazepam (often in combination with alcohol), the development of rapid and reliable analytical methods for its detection and determination in pharmaceutical samples and alcoholic drinks is an important goal of analysts. In this review, an overview of the voltammetric methods to determine diazepam in various samples is briefly summarized.

An Integrated Strategy for Chemical Profile Establishment of Premna Microphylla Turcz. leaves and Metabolites in Vivo.

Premna microphylla Turcz. (PMT) is a traditional food and medicinal plant, which has been used to treat cure hemostasis, rheumatism and dysentery. However, it still lacks a clear understanding about chemical profile of PMT and metabolites in vivo. To establish a rapid and efficient analytical method for the identification of phytochemical in PMT and metabolites in vivo. Firstly, the fingerprint of PMT was established by high-performance liquid chromatography (HPLC) with methodology validation. Then, the phytochemical composition in PMT leaves were identified using ultra-performance liquid chromatography tandem quadruple time-of-flight mass spectrometry (UPLC-QTOF-MS/MS). Finally, the prototype and correlated metabolites were detected after oral administration in mice to understand the absorption and metabolism of phytochemical in vivo. The result showed established HPLC method for fingerprints evaluation of PMT has good precision, repeatability and stability. Additionally, a total of 103 phytochemicals were identified in PMT, mainly including flavonoids and terpenoids. Then, 37 prototype components and 20 derived metabolites in vivo were detected. In this study, we constructed a fingerprint method which has good stability, precision and repeatability, and the fingerprint of PMT was established. Then the chemical profile of PMT in vitro and in vivo was performed. The result showed that flavonoids and terpenoids were the main phytochemicals in PMT, and methylation, sulfonation, dihydroxylation were the main metabolic pathway in vivo. The present study provided the phytochemical basis for the subsequent study of pharmacological activity.

Rapid analysis method of helicopter fuselage bullet damage based on bullet penetration theory

Helicopter fuselage has a complex shape and structure. Numerical simulation analysis of helicopter fuselage bullet damage based on the finite element method is computationally intensive and takes a long time. It is difficult to quickly analyze and evaluate helicopter fuselage bullet damage in a complex multi-bomb environment. To this end, the bullet penetration theory and the bullet impact calculation model were coupled to establish a rapid analysis method for helicopter fuselage bullet damage, and the accuracy of the rapid analysis method was verified by comparing with test results and finite element numerical simulation results. Then the helicopter fuselage bomb coordinates, residual speed and fuselage damage area of the multi-bomb strike were studied. Research shows that the residual velocity calculated by the rapid analysis method is consistent with the test results; compared with the finite element numerical simulation of bullet damage, the maximum error of the projectile residual velocity calculated by the rapid analysis method is 4.7%, and the maximum error of the fuselage damage area is 9.56%, and the calculation time is reduced 92.1%. Computational efficiency is significantly improved. As the incident angle of the projectile increases, the residual velocity decreases and the damage area increases; when the incident angle of the projectile is too large, the projectile cannot penetrate the surface of the fuselage, causing sink-like sliding damage, causing a larger area of damage.

Electrochemical Determination of Tartrazine and Carmoisine Dyes from Aqueous Solutions on Modified Electrodes

Introduction: The recognition of the health hazards of azo dyes has highlighted the need to develop efficient, rapid, and reliable analytical methods for dye determination. Method: In this work, electrochemical probing of the azo group of Tartrazine (TZ) and Carmoisine (CR) in food dyes was carried out. Synthesized bismuth and zinc oxide nanoparticles were used to modify Graphite Electrode (GE). Results: Electrochemical analysis showed a much better electrochemical response using ZnO+Bi/GE as a modifier than individually nanoparticle-modified graphite electrodes. From the CV analysis, it was found that both the dyes exhibited irreversible electrochemical behavior, and the redox parameters were calculated. The Limit of Detection (LOD) values recorded for TZ and CR for ZnO+Bi/GEbased sensors were 0.84 uM and 2.80 uM, respectively. The obtained sensitivity values were 11.86 uA/uM/cm2 for TZ and 17.3 uA/uM/cm2 for CR. Conclusion: The sensor evidently demonstrated reliable simultaneous detection of both dyes, making it suitable for practical applications in food safety analysis.

Plasmonic Coacervate as a Droplet-Based SERS Platform for Rapid Enrichment and Microanalysis of Hydrophobic Payloads.

A novel and simple coacervate microdroplet-based detection platform for the quantification of trace hydrophobic analytes is presented. Herein, taking advantage of the effective encapsulation and enrichment performance of the condensed coacervates, plasmonic metallic silver nanoparticles (AgNPs) and target hydrophobic analytes are simultaneously concentrated into a single microdroplet. The coencapsulation of AgNPs within coacervates promotes the formation of aggregates with a lot of "hot spots" for surface-enhanced Raman scattering (SERS) enhancement, facilitating the sensitive analysis of hydrophobic analytes by SERS technology. Such plasmonic coacervates are easily prepared and exhibit good reproducibility and signal uniformity. Optimized SERS performance by modulating the volume of encapsulated AgNPs enables quantitative determination of hydrophobic analytes of Nile Red, chlorpyrifos, benzo[e]pyrene, 20 and 50 nm polystyrene nanoplastics with low detection limits of 10-12 M, 10-9 M, 10-10 M, 0.05 ppb, and 0.5 ppb, and an approximately linear correlation between SERS signals and the analytical concentrations. This study opens a new convenient SERS platform for the ultrasensitive detection of hydrophobic hazardous substances, potentially becoming a rapid analysis method for extensive applications ranging from food safety to environment monitoring.

Study on the differentiation of sensory quality of mainstream Jiang-flavor baijiu in the Chinese market based on Pivot Profile.

Jiang-flavor baijiu (JFB) is a prominent type of Chinese baijiu, known for its unique flavor attributes, sensory experience, and high tasting value. Previous research has mainly focused on the detection and identification of its flavor substances, but in-depth studies on the precise sensory description and differentiation of its flavor qualities are still lacking. In this study, a rapid sensory analysis method, Pivot Profile (PP), was applied to 30 mainstream JFBs in the Chinese market, generating 91 sensory attributes with independent definitions, from which 29 main sensory attributes were established that were easy to perceive and descriptive, as well as convenient for transmitting their sensory qualities and distinguishing differences in price and production region, including color (one descriptor), aroma (21 descriptors), taste, and mouthfeel (seven descriptors). The nine key sensory attributes that distinguish JFB quality are as follows: Jiang, Grain, Chen, Qu, Rancid, Acid, Sweet, Fullness, and Harmony. It was found that price was positively correlated with sensory quality, with greater variation in the quality of samples within the medium price range (RMB 500-1000). All samples from MTCQ1 (the core production area of Maotai Town) performed better in sensory quality. In addition, salted vegetable showed a high degree of regional characteristics, concentrated in most of the production regions of Guizhou Province. Aroma attributes were more suitable than taste and mouthfeel as sensory indicators for distinguishing production regions. This study has opened the direction of systematic construction of sensory description of JFB and provided a successful case for the evaluation of Chinese baijiu using novel sensory analysis techniques.

Development and validation of a model for early prediction of residual feed intake in beef cattle using plasma biomarkers

Identification of plasma biomarkers for feed efficiency in growing beef cattle offers a promising opportunity for developing prediction models to improve precision feeding strategies. However, these models must accurately predict feed efficiency at early stages of fattening. Our study aimed to evaluate the reliability of candidate biomarkers previously identified in late-fattening cattle when analyzed during early fattening stages and to develop diet-specific prediction equations for residual feed intake (RFI). From a total of 364 Charolais bulls across 7 cohorts, we selected 64 animals with extreme RFI values. The animals were fed either a corn‑ or grass-silage diets. These animals were chosen from 4 out of available 7 cohorts. Animals from three cohorts (24 high-RFI and 24 low-RFI, having a mean RFI difference of 1.48 kg/d) were used for biomarker confirmation and prediction model training. Animals from a fourth cohort (8 high-RFI and 8 low-RFI, having a mean RFI difference of 0.98 kg/d) were used for model external validation. Blood samples were collected at the beginning of the feed efficiency test (333±20 days), and plasma underwent targeted metabolomic for 630 metabolites, natural abundance of 15N (δ15N), insulin, and IGF-1 analysis. Seven previously identified plasma biomarkers for RFI in late-fattening beef cattle still kept their capability for discriminating low and high RFI animals when analyzed during early fattening stages (P < 0.05). Among these confirmed biomarkers, five were common for both grass- and corn-fed animals (creatinine, β-alanine, triglyceride TG18:0_34:2, symmetric dimethyl-arginine and phosphatidylcholine PC aa C30:2) while two were diet-specific (insulin-like growth factor 1 for grass silage-based diet, and isoleucine for corn silage-based diet. No new plasma biomarkers of RFI were identified at early-fattening stages (false discovery rate, FDR>0.05). Prediction models were developed based on seven confirmed RFI biomarkers analyzed during early-fattening. Two logistic regression models incorporating creatinine and either IGF-1 (for grass silage-based diet) or PC aa C30:2 (for corn silage-based diet) effectively distinguished between high and low-RFI animals with high sensitivity and specificity (area under the curve, AUC > 0.80). The biomarkers used in the models showed moderate to high repeatability between early and late fattening stages (45 < r <65). The models were successfully externally validated, with more than 85% of animals from the fourth cohort correctly classified. Once validated in larger cohorts and utilizing cost-effective and rapid analytical methods, these models could support precision feeding and breeding programs, aiming to reduce the cost of raising beef cattle.

Electrochemical Oxidation of Glutathione in the Presence of Tryptophan at Carbon Paste Electrode Modified with Ni-Zn-Metal-Organic Frameworks/Graphene Oxide and Ferrocene Derivative

Glutathione (GSH) plays a vital physiological role as it is implicated in the progression and pathogenesis of a wide range of medical conditions, including diabetes, various types of cancer, and Parkinson’s disease. Due to the fundamental physiological importance of GSHand its relevance to numerous medical conditions, there is a clear need to develop simple, rapid, and cost-effective analytical methods. These methods could significantly aid in clinical diagnostics and guide the optimization of treatment approaches. This work reports the synthesis and characterization of a Ni-Zn-metal-organic framework/graphene oxide (Ni-Zn-MOF/GO) composite material, and its application as a modifier for a carbon paste electrode (CPE) in the electrochemical detection of GSH. The Ni-Zn-MOF/GO/ferrocene (FC)-modified CPE (Ni-Zn-MOF/GO/FC/CPE) was developed for this purpose. The Ni-Zn-MOF/GO/FC/CPE electrochemical sensor exhibited two linear response ranges for GSH: from 0.01–90.0 μM, and from 90.0–800.0 μM, with a detection limit estimated to be 0.003 μM. Importantly, Ni-Zn-MOF/GO/FC/CPE was shown to be suitable for the determination of GSH in the presence of tryptophan in real samples, such as human blood, GSH tablet and urine samples. The results highlight the potential of the Ni-Zn-MOF/GO/FC/CPE electrochemical sensor as a reliable and sensitive platform for the detection of GSH.

Rapid on-site detection of illicit drugs in urine using C18 pipette-tip based solid-phase extraction coupled with a miniaturized mass spectrometer

Drug abuse is a social issue worldwide, and there is an increasing demand for on-site rapid detection of illicit drugs. In this study, a rapid and simple analytical method for the detection of 6-monoacetylmorphine (6-MAM), methamphetamine (MA), methylenedioxymethamphetamine (MDMA), ketamine (K), norketamine (NK), and cocaine (COC) in urine was developed. The developed method combines C18 pipette-tip based solid-phase extraction (C18 PT-SPE) with a miniaturized mass spectrometer (miniMS), exhibiting remarkable simplicity, high sensitivity, and strong reliability, compared with the conventional method. The optimal extraction and elution conditions for C18 PT-SPE were considered as 9 and 3 aspirating-dispensing cycles, respectively. The miniMS parameters including spray voltage, isolation potential, and collision-induced dissociation energy for the detection of these six illicit drugs were optimized using a nano-electrospray ionization method. The limit of detection (LOD), limit of quantification (LOQ), linear range, and linearity for the analysis of six illicit drugs in urine with the proposed C18 PT-SPE-miniMS method were determined. Except for the LOD of K and COC was determined as 0.5 and 0.25 ng mL−1 respectively, and the LOD of 6-MAM MA, MDMA, and NK was determined as 1 ng mL−1. This method enables rapid on-site detection, providing easier operation, lower cost, and better portability compared to conventional methods, making it a potential tool in drug crime investigation and forensic science.

An index-based multi-hazard risk assessment method for prioritisation of existing bridge portfolios

In recent years, several catastrophic collapses of existing bridges have highlighted the need for rapid risk analysis methods aimed at supporting infrastructure managers in the prioritisation of detailed assessments and, if any, risk mitigation actions. A large percentage of existing road bridges were built between the 1960s and 1980s, having thus already reached or even exceeded their design lifetime. Several studies have also shown that bridges often collapse due to either natural or human-related events, such as floods, collisions or overloading that, in addition to earthquakes, should be duly considered in risk assessment. This calls for multi-hazard approaches that provide an integrated perspective of the risk of bridge portfolios, to identify critical structures to support decision-makers. This study proposes a multi-hazard risk-based prioritisation methodology for application to a large number of bridges under limited level of knowledge. Specifically, the risk level is quantified through indices, accounting for uncertainties, that are used for comparative purposes among bridges. The methodology is applied to a highway bridge portfolio located in northern Italy, producing a risk-based ranking that is critically discussed. Analysis results are then compared with the outcome of the current Italian guidelines for safety assessment and maintenance of existing bridges.

Should Routine Diagnostics Implement Gut Microbiota Analysis?

The gut microbiota plays a key role in human health. Dominated by the phyla Firmicutes and Bacteroidetes, its composition is highly individualized and influenced by diet, age, genetics, and the environment. The gut-liver axis highlights the bidirectional re-lationship between the gut and the liver, impacting metabolic homeostasis and immune reg-ulation. Gut dysbiosis, an imbalance in the gut microflora, contributes to liver diseases by disrupting gut barrier function and bile acid metabolism, leading to inflammation and fibro-genesis. Advancements in omics approaches, such as metagenomics, metatranscriptomics, metaproteomics, and metabolomics, have enhanced our understanding of the gut microbi-ota. These approaches offer insights into microbial composition and function, although they vary in cost, efficiency, and complexity. Metagenomics is widely used for its cost-effec-tiveness and rapid turnaround time despite limitations in taxonomic resolution, while meta-transcriptomics, metaproteomics, and metabolomics offer functional and metabolic insights but require sophisticated techniques and expertise. The Firmicutes/Bacteroidetes (F/B) ratio is a potential biomarker of gut dysbiosis linked to obesity, type 2 diabetes mellitus, and liver diseases. However, its diagnostic reliability is debated due to variations in individual factors and a lack of data on its associations with several diseases. Future research should focus on integrating multi-omics approaches so as to provide a holistic view of the gut microbiota and its role in health and disease, aiming for applications in precision medicine. While promising, the F/B ratio should be used cautiously alongside other diagnostic measures. In addition, renewed efforts are needed to develop cost-effective and rapid analysis methods for clinical use.

Efficient linear analysis of coupled-cavity traveling-wave tubes using minimum number of dispersion frequency points

Coupled-cavity traveling-wave tubes (CCTWTs) are high-power amplifiers operating in the microwave and millimeter-wave regions of the spectrum, utilizing beam-wave coupling within an electromagnetic slow-wave structure (SWS). The linear (small-signal) analysis of these amplifiers is a crucial initial step in their electromagnetic design. This paper presents and evaluates a method for analyzing these structures in the linear regime using only three frequency points from the SWS. The results obtained from this method are compared with full-wave particle-in-cell simulations, demonstrating satisfactory agreement. This approach offers a rapid analysis method for examining CCTWTs in the linear state, eliminating the need for lumped circuit modeling and detailed knowledge of the SWS dispersion characteristics.

A novel fast analytical method for the determination of N-nitroso vonoprazan in vonoprazan tablets and raw materials using LC-ESI-MS/MS

ABSTRACT The presence of N-nitrosamine contaminants in pharmaceuticals, particularly N-nitroso vonoprazan (NVP), poses significant health risks due to their genotoxic and carcinogenic properties. This study describes a novel, rapid analytical method for detecting and quantifying NVP in vonoprazan tablets and raw materials. The NVP was separated and quantified using an LC-ESI-MS/MS system with ESI ionisation and an Exion LC Sciex 5500-QTrap. The system utilised an ACE 3 C18-PFP column with dimensions of 4.6 mm × 150 mm and 3.0 µm. It achieved a high correlation coefficient (R2 = 0.9955) and met linearity and accuracy criteria. The method was developed and validated using ICH guidelines and against standard solutions, and it demonstrated high precision, accuracy, and specificity. The method validation results showed that the quantification is accurate, with an RSD of less than 10% and LOD and LOQ values of 0.5 and 1.0 ng/mL, respectively. The analysis of 150 vonoprazan tablets and 100 raw material samples revealed low levels of NVP, mostly falling below the FDA’s Acceptable Daily Intake limit of 96 ng/day. This novel approach provides a powerful and dependable tool for ensuring the safety and quality of vonoprazan-based pharmaceuticals.