Analytical Letters

Teo, Po Sian; Yeo, Wan Sieng; Ming Hao, Lee; Das, Mainak; Saptoro, Agus

doi: 10.1080/00032719.2025.2592224pmid: N/A

Abstract This study presents a novel approach to accurately estimate calcium hypochlorite (CHC) concentrations in sago flour using hyperspectral imaging (HSI) and regression models. As consumers prefer pure white sago, CHC is a bleaching additive that is added to sago powder to whiten its appearance. Spectral data from 380 to 1,100 nm reveals the spectral characteristics of sago samples with CHC concentrations of 0.005–2 wt%. A total of 42 sago images were captured across these concentrations and 405 spectral sets were obtained for model training. Four regression models, including principal component regression, partial least squares regression (PLSR), kernel PLSR (KPLSR) with exponential radial basis (ERBF) kernel function, and least square support regression (LSSVR), were evaluated. In this study, the developed KPLSR model with ERBF kernels with the kernel parameter of 0.1 and 57 latent variables, with the coefficient of determination, R2 of 0.9930, RMSE of 0.0584, and MAE of 0.044 for the testing dataset, was found to be the best-performing model for monitoring CHC in sago due to its high prediction accuracy and efficiency. This study highlights the potential of HSI and regression models for nondestructive and real-time quality monitoring of sago flour in the food industry. Future research should focus on assessing model performance with data outliers and exploring commercialization opportunities, which could revolutionize food quality assessment and control systems for safety purposes.

Meimanat Abadi, Ali; Kamalabadi, Mahdie; Derakhshandeh, Katayoun; Mohammadi, Mojdeh

doi: 10.1080/00032719.2025.2592870pmid: N/A

Abstract Patulin (PAT) is a common mycotoxin that contaminates various fruits, especially apples, and apple beverages, threatening food security and human health. Therefore, accurate detection of PAT in food items, particularly in apple juice, is essential. In this work, we focused on the development of a rapid and sensitive method that benefited from the advantages of dispersive liquid-liquid microextraction (DLLME) as a practical extraction step and ion mobility spectrometry (IMS) as a fast detection instrument. The variables influencing the IMS performance and the extraction efficiency were investigated. Under the optimum conditions, the analytical parameters exhibited desirable results with favorable linearity (0.1-90 ng mL−1, correlation coefficient= 0.9962), the detection limit of 0.016 ng mL−1, the limit of quantification of 0.053 ng mL−1, and relative standard deviation (RSD) of 4.8%. The good practical performance of the proposed method was confirmed through the analysis of apple juices and the achievement of high recovery values. The suitability and reliability of the present method were confirmed using a comparison study of DLLME-IMS and DLLME coupled with high performance liquid chromatography (DLLME-HPLC).

Zhang, Kun; Jia, Jinfeng

doi: 10.1080/00032719.2025.2593582pmid: N/A

Abstract Thrombin is a key serine protease in the coagulation cascade and a critical biomarker for thrombotic disorders; thus, the ability to selectively detect thrombin is important for clinical diagnostics. Herein, we report a novel fluorescence sensor for thrombin detection based on the inner filter effect (IFE) between silicon quantum dots (SiQDs) and gold nanoparticles (AuNPs). A specially designed peptide substrate CGGEE–LVPR|GS–KK (Cys-Gly-Gly-Glu-Glu-Leu-Val-Pro-Arg-Gly-Ser-Lys-Lys) that can be specifically cleaved by thrombin at the Arg–Gly bond was employed. Enzymatic cleavage releases positively charged, thiol-containing peptide fragments that trigger the aggregation of AuNPs. This aggregation disrupts the IFE between AuNPs and SiQDs, leading to a remarkable recovery of SiQD fluorescence. Thrombin detection was achieved based on changes in fluorescence intensity of SiQDs. The developed sensor had a linear detection range over the thrombin concentrations of 10–500 pM, and its detection limit was as low as 3 pM, outperforming that of many previously reported fluorescence-based thrombin assays. Moreover, the sensor showed high selectivity toward the targets over other proteases and biomolecules and was successfully applied for thrombin detection in human plasma samples, achieving recovery rates between 94.9% and 105.7%. This work demonstrates a simple, rapid, and reliable thrombin detection strategy that can potentially be employed in the diagnosis of thrombotic diseases and the monitoring of anticoagulant therapy.

Wang, Tianze; Wang, Lu; Zhang, Yu; Liu, Liming; Zhang, Bo; Qian, Weiping

doi: 10.1080/00032719.2025.2595153pmid: N/A

Abstract The determination of human serum albumin (HSA) is of great significance for the noninvasive diagnosis and treatment of modern diseases. Label-free immunoassay has been regarded as one of the most prominent techniques for HSA detection because of its reliability and sensitivity. In this work, an optical label-free biosensing method based on ordered porous polystyrene inverse opal (PS-IO) substrate was developed. Based on the methodology of inhibitory immunoassay, human serum albumin (HSA) was immobilized on the PS substrate with sufficient density, enabling one-step detection, while the interconnected inverse opal substrate enhances the mass transfer efficiency of the sensing unit. HSA level can be determined without either the label of protein molecules or sensor signal amplification, which simplifies the operation procedure and improves the detection efficiency. The linear range of the developed sensing system is 0.05–50 μg/mL, with a limit of quantitation of 50 ng/mL. At the same time, the sensor has strong selectivity and specificity, resists environmental molecular interference, and maintains stable sensing performance during long-term storage and recycling. This study provides valuable insights for the development of new clinical measurement devices.

Losev, Vladimir N.; Buyko, O. V.; Shimanskii, A. F.; Metelitsa, S. I.; Borodina, E. V.; Zhyzhaev, A. M.; Samoilo, A. S.; Kazantsev, Ya. V.; Li, M.

doi: 10.1080/00032719.2025.2596230pmid:

Tezgin, Emine; Zaman, Buse Tuğba; Öztürk Er, Elif; Dalgıç Bozyiğit, Gamze; Turak, Fatma; Bakırdere, Sezgin

doi: 10.1080/00032719.2025.2596956pmid: N/A

Abstract The ease of synthesis, abundant surface-active sites and cost-effectiveness make metal oxide-based nanomaterials promising adsorbents for fast and efficient removal of heavy metals. This study introduces a new metal oxide adsorbent for the removal of Cd(II) ions from domestic wastewater. Barium oxide nanorods were successfully synthesized via a simple precipitation route and characterized using X-ray diffraction (XRD), Fourier transform-infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM). The batch adsorption process demonstrated high efficiency with the key parameters including solution pH (9.0), adsorbent amount (50 mg), and contact period (10 min). It was found that increasing the adsorbent amount up to the surface saturation level and adjusting the solution pH favor the removal of Cd(II) ions. The adsorption isotherm data well suited to the Langmuir model, with a determination coefficient above 0.95, suggesting a monolayer adsorption mechanism. The maximum adsorption capacity was found to be 67.54 mg/g. These findings show that barium oxide nanorods are promising adsorbents for the rapid and efficient removal of Cd(II) ions from domestic wastewater.

Sun, Qinqin; Wang, Jing; Liu, Zhengzheng; Wang, Lujie; Zhang, Jun; Liu, Biaowei; Huang, Liqiong; Yan, Fei; Liu, Jinsong

doi: 10.1080/00032719.2025.2598341pmid: N/A

Abstract Convenient and sensitive detection of hydroquinone (HQ) and catechol (CC) in environmental samples holds great importance for monitoring. Herein, a vertically-ordered mesoporous silica film (VMSF) supported on the electrochemically pretreated glassy carbon electrode (p-GCE) is prepared by a simple and environmentally friendly electrochemical method and employed to construct a sensitive and anti-fouling sensing interface for quantitative detection of HQ and CC. In virtue of a simple electrochemical polarization, the p-GCE shows enhanced electroactive area and promoted electrochemical activity, as well as oxygen-containing groups, rendering a sensitive electrode substrate with improved analytical performance and the functional interface for stable growth of VMSF. The obtained VMSF/p-GCE has superior electroanalytical capacity toward HQ and CC due to the synergistic effect of hydrogen bonding of VMSF and the sensitive p-GCE electrode substrate. The developed VMSF/p-GCE sensor enables the determination of HQ and CC with a wide linear range (1 ∼ 120 μM), high sensitivity (0.368 μA/μM for HQ and 0.404 μA/μM) and low limit of detection (268 nM for HQ and 80 nM for CC). Furthermore, the capacity of the prepared VMSF/p-GCE in the analysis of HQ and CC in environmental water samples and soil leaching solutions has been studied, showing acceptable results and therefore offering a simple and low-cost way for environmental analysis.

Meng, Liujun; Liang, Haonan; Wu, Yi; Xu, Zhengyi; Du, Xiaoxia; Xiao, Wenxiang; Li, Hua

doi: 10.1080/00032719.2025.2601070pmid: N/A

Abstract In order to improve the detection signal strength and resolution of high-field asymmetric waveform ion mobility spectrometry (FAIMS), a hollow needle-to-ring ion source based on mixed gas discharge was designed. Two sample injection methods were used. At an RF voltage of 250 V, the signal intensity for acetone injected via the needle electrode is 48.2 pA, which is 5.1 times higher than that for acetone injected via the ring electrode. For acetic acid, the signal intensity injected via the needle electrode is 14 pA, which is 1.63 times higher than that for the ring electrode injection. At the same time, the value of compensation voltage also increases accordingly by injecting via the needle electrode. The mass spectrometry experiment of acetone shows that the intensity for the needle electrode injection is greater than that for the ring electrode injection. It indicates that injecting via the needle electrode significantly enhances the FAIMS signal intensity and resolution, which is advantageous for detecting low-concentration samples.

Ren, Guangxin; Zhang, Yinfeng; Zhen, Ting; Yin, Chang; Ning, Jingming

doi: 10.1080/00032719.2025.2602728pmid: N/A

Abstract Traditional sensory quality evaluation of Panji crisp melons was inconvenient and subjective, hindering digitization efforts. This study established a quantitative analysis model for sensory quality scoring of Panji crisp melon based on portable near-infrared spectroscopy. During the model establishment process, the impact of feature wavelength optimization methods on the prediction model was explored. First, the acquired near-infrared spectral data were preprocessed using Savitzky-Golay smoothing. Subsequently, the 132 samples were divided into training set samples (n = 88) and prediction set samples (n = 44). Boot-strapping soft shrinkage, competitive adaptive reweighting sampling, iterative variable set optimization (IVSO), and whale optimization algorithm were employed to select for the optimal feature wavelength variables associated with sensory quality indices. Finally, based on the optimal wavelengths, partial least squares regression (PLSR) linear prediction models and support vector regression (SVR) nonlinear prediction models were established for the sensory quality evaluation of Panji crisp melons. A comparison of the model results showed that the four feature wavelength optimization methods mentioned above could effectively reduce the number of variables and further minimize the model prediction error. The root mean square error of prediction (RMSEP) of the nonlinear SVR model was significantly smaller than that of the PLSR model, while the relative percent deviation (RPD) was higher than that of the PLSR model. The IVSO-SVR model demonstrated optimal predictive performance, with RMSEP and RPD of 0.9262 and 5.27, respectively. These findings provided a theoretical foundation for practical near-infrared spectroscopy applications in rapid sensory quality prediction of Panji crisp melons.

Rani, Gita; Kumar, Sunil; Siddharth, ; Suman, ; Kumar, Naveen

doi: 10.1080/00032719.2025.2604143pmid: N/A

Abstract Organic pollutants in water present persistent environmental and public health risks. Conventional treatments such as adsorption, chlorination, and membrane filtration frequently fail to mineralize recalcitrant compounds. Heterogeneous photocatalysis using metal-organic frameworks (MOFs) within advanced oxidation processes (AOPs) has emerged as a promising approach for generating reactive oxygen species and achieving efficient degradation. This review critically evaluates how MOF composition, structure, and electronic properties influence photocatalytic performance. It compares synthesis strategies, including solvothermal and microwave routes, the use of modulators, post-synthetic modification, defect engineering, and the formation of heterojunctions or composites. The impacts of these strategies on crystal structure, surface area and porosity, particle size, thermal and chemical stability, band structure, and active-site accessibility are systematically mapped. The review places particular emphasis on bandgap tuning, light harvesting, and suppression of charge recombination through linker design, metal-node selection, defect control, cocatalysts, and the incorporation of semiconductor or carbonaceous composites. Key knowledge gaps are identified, such as the absence of standardized activity metrics and quantum efficiency reporting, limited durability and selectivity in complex water matrices, challenges in scalable synthesis with controlled electronic structure, and incomplete mechanistic understanding of charge-carrier dynamics. The review concludes by outlining design guidelines and research directions for the practical application of MOF-based photocatalysis in AOPs.