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Spectral intensity drift is a frequent issue in analytical processes, especially in long time excitation scanning for large size metal materials, which can significantly adversely impact the accuracy and stability of analysis results. Spectral intensity drift correction is the process of preprocessing spectral data using mathematical algorithms in order to facilitate the subsequent qualitative and quantitative analysis of spectra, especially in combination with stoichiometric methods. Up to now, spectral intensity drift correction within prolonged excitation has not been reported yet. We propose an intensity drift correction method for element content of large-size samples using the Spark Mapping Analysis for Large Samples (SMALS) technique. By considering the row-by-row and column-by-column mapping modes of the SMALS, this includes curve fitting baseline correction for in-row and in-column correction, as well as total average value correction for inter-row and inter-column correction. The final measurement values are derived by coupling rows with columns. The careful implementation of correction steps can enhance baseline correction performance, effectively reducing measurement errors a drift errors. Application of this method to characterize the cross and longitudinal sections of an oversized steel billet indicates high agreement with composition distribution obtained by micro-beam X-ray fluorescence (μ-XRF). The corrected longitudinal and cross-sectional data also exhibit strong alignment. Comparison of statistical analysis results pre- and post-correction demonstrates significant improvements in the clarity of elements segregation pattern. This intensity drift correction method not only enhances the spectral quality but also improves the accuracy and robustness of quantitative and qualitative spectral analysis. This study contributes to establishing a robust foundation for component characterization of large-size metal materials using the SMALS technique. The novel spectral intensity correction method shows theoretical significance and practical value for large-scale, long-duration excitation scanning analysis. [Display omitted] • The measurement error was eliminated by in-row/in-column, inter-row/inter-column correction and complementary coupling. • The intensity drift correction method significantly improves the accuracy and stability of analysis results of the SMALS. • This work laid a firm foundation of component characterization for large-size metal material using the SMALS. [ABSTRACT FROM AUTHOR]

The utilization of near-infrared (NIR) spectroscopy, in conjunction with chemometric techniques, has been widely used in a variety of sectors, including agricultural production and pharmaceutical production. Nevertheless, the laborious and arduous procedure of gathering samples and evaluating their physicochemical properties leads to relatively limited training set sizes for modeling. This problem severely limits the optimization and practical application of NIR spectrum analysis models. The Safer Active Semi-Supervised Sample Augmentation Learning Model (Safer-AS3A) proposed in this paper tries to address the problem by incorporating active learning (AL) and semi-supervised learning (SSL) techniques. Experiments were conducted on two sets of publicly available NIR spectral datasets, and the Safer-AS3A model was compared to other models with similar characteristics. The experimental results indicate that the Safer-AS3A model proposed in our study outperforms comparable models in terms of accuracy and robustness when dealing with scenarios having a limited number of labeled samples. Furthermore, after the training set was expanded with the Safer-AS3A model, the Partial least squares regression (PLSR), Bayesian ridge regression (BRR), and Support vector regression (SVR) models on the Diesel dataset improved their R 2 on the test set by 5.923 %, 3.018 %, and 7.331 %, respectively, compared to the models using only the labeled sample set. On the other hand, the Ridge regression (RR), BRR, and SVR models on the test set on the Shoot dataset improved the R 2 by 4.169 %, 4.449 %, and 11.597 %, respectively. Overall, the Safer-AS3A model can effectively expand the NIR spectral dataset and considerably improve the performance of the NIR spectral analysis model. Using the AL method, the SSL method, and the co-training method together, a novel and effective method is presented for generating high-quality pseudo-labels. This method opens up new avenues for enhancing the efficiency and precision of NIR spectrum analysis. It also provides novel perspectives on sample diversification and prospective applications in other disciplines. [Display omitted] • A deep active learning method is developed to analyze near-infrared spectroscopy data. • The stability principle and voting mechanism are added to the confidence evaluation of pseudo-labeling. • The co-training method effectively alleviates the problem of insufficient labeled spectral samples. [ABSTRACT FROM AUTHOR]

Background: Hand, foot, and mouth (HMFD) disease caused by enterovirus 71 (EV 71), is closely associated with severe clinical manifestations and can be deadly. Early detection of EV 71 can be achieved by detecting the increment in miR296 and miR16 in the serum. Using HCR to amplify signals and convert biological signals into metal nanoparticle signals detectable by ICP-MS is a detection method that can collect more accurate and reliable information, compared with traditional methods, in the detection of biological samples., Results: We described a strategy for the simultaneous detection of miR296 and miR16 by ICP-MS based on metal nanoparticles (NPs) labeling with HCR. Briefly, single-stranded DNA (ssDNA) and magnetic beads (MBs), as well as NPs and signal probes for miRNA (Sp -miR ) were firstly conjugated via the streptavidin-biotin recognition system, constituting ssDNA-MBs and NPs-Sp -miR complex, respectively. The latter complex then hybridized with the former through HCR, generating the nanosensors for targets. Then, the targets were added and hybridized with ssDNA, and the HCR complex with NPs was released into the solution. Finally, the corresponding signals of the NPs were measured by ICP-MS. Results demonstrated that the developed method had good sensitivity and satisfactory selectivity and precision. Furthermore, when applied to biological samples with a complex matrix, the developed method also showed good recovery (88 % - 92 %) and reproducibility (RSD<10 %)., Significance: This method contributes to the early diagnosis of HFMD and opens up ideas for the further development of high-throughput biomarker detection. The strategy has practical potential for miR296 and miR16 detection in biological samples and provides a promising tool for multiple miRNA detection., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Recent papers on LA-ICP-MS have reported that certain elements are transported in particulate form, others in gaseous form and still others in a combination of both upon ablation of C-based materials. These two phases display different transport behaviour characteristics, potentially causing smearing in elemental maps, and could be processed differently in the ICP which raises concerns as to accuracy of quantification and emphasizes the need for matrix-matching of external standards. This work aims at a better understanding of two-phase sample transport by evaluating the peak profile changes observed upon varying parameters such as laser energy density and wavelength., Results: It is demonstrated that upon ablation of gelatin, elements are transported predominantly in particulate phase, but already at low laser energy density, a significant fraction of some elements is transported in the gaseous phase, which is even more expressed at higher energy density. This behaviour is element-specific since the ratio of the signal intensity for the analyte element transported in gas phase to the total signal intensity was 0 % for 23 Na, 43 % for 66 Zn and as high as 95 % for 13 C using a 193 nm laser. The results also suggest an effect of the laser wavelength, as all elements show either the same or higher amount of gas phase formation upon ablating with 213 nm versus 193 nm. It was even established that elements that fully occur in particulate form upon ablation using 193 nm laser radiation are partly converted into gaseous phase when using 213 nm., Significance: This work provides a thorough investigation of the underexposed phenomenon of two-phase sample transport upon ablation of biological samples upon via LA-ICP-MS. It is shown that for some elements a fraction of the ablated material is converted and transported in the gas phase, which can lead to significant smearing effects. As such, it is important to evaluate element-specific peak profiles on beforehand and, if necessary, adapt instrument settings and slow down data acquisition., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Frank Vanhaecke has patent #EP3195346B1 licensed to Teledyne Photon Machines., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: Miniaturized microplasma-based atomic emission spectrometry (AES) has been extensively used for element analysis in recent years due to the advantages of low power consumption, low gas consumption, relatively low manufacturing and running cost, and the potential for real-time and field analysis. However, few applications in bioassay detection have been reported based on microplasma AES systems because of their relatively low sensitivity and the absence of indirect analytical strategies. It is still a challenge to develop a simple, sensitive, and portable microplasma-based AES bioassay approach., Results: In this work, a portable analytical system was designed based on point discharge chemical vapor generation atomic emission spectrometry (PD-CVG-AES) coupling with gold filament enrichment. The detection of ascorbic acid (AA) was realized indirectly by means of the highly sensitive analysis of Hg 2+ . The measurement was based on Ag  +  can decrease the concentration of Hg 2+ by forming Ag-Hg amalgam in the presence of the reductant SnCl 2 , while AA can pre-reduce Ag  +  to Ag 0 , leading to the generation of silver nanoparticles (Ag NPs). The pre-reduce procedure can decrease the generation of Ag-Hg amalgam, resulting in the recovery of Hg 2+ signal. The dissociative Hg 2+ was further detected by PD-CVG-AES combination of gold filament enrichment, which significantly improved the detection sensitivity for both Hg 2+ and AA. Under optimal conditions, the limit of detection (LOD) of AA is as low as 19 nM with a relative standard deviation (RSD, n = 5) of 0.7 %., Significance: The developed novel analytical strategy obviously broadens the application of microplasma-based AES, and it is well demonstrated by the determination of AA in several traditional Chinese medicines (TCMs), offering a higher level of sensitivity compared to current AA detection techniques. It has potential for future application in point-of-care testing (POCT) assays., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

In a qualitative analysis of near-infrared spectroscopy (NIRS), when the samples to be analyzed are difficult to obtain or there are few counterexamples, the robustness of the models is poor, resulting in the decline of the generalization ability of the models. In this case, the effective method is to construct virtual samples to achieve the balance of categories. In this contribution, three virtual spectrum construction strategies including Synthetic Minority Oversampling Technique (SMOTE), Adaptive Synthetic Sampling (ADASYN), and Deep Convolutional Generative Adversarial Network (DCGAN) were explored to deal with the problem of insufficient or imbalanced sample numbers in NIRS analysis. The strategies were tested with the melamine and Yali pears two spectral datasets. The PLS-DA and Correct Recognition Rate (CRR) were used for discriminant model construction and accuracy evaluation, respectively. The results show that SMOTE, ADASYN, and DCGAN processing strategies can all improve the global CRR (CRR glob). The SMOTE and ADASYN can improve the CRR for majority class sample (CRR maj), but the CRR for minority class sample (CRR min) has decreased. For the DCGAN method, the CRR glob , CRR maj , and CRR min were all improved. The standard deviation of the results of the multiple parallel calculations demonstrates the robustness of DCGAN generation method. Therefore, the DCGAN method has good reliability and practicability, and can increase the robustness and generalization ability of the NIRS model. [Display omitted] • Exploring virtual spectrum construction strategies. • Evaluate the plausibility and diversity of the virtual spectrum. • Improve the robustness and generalization ability of the NIRS model. • Test model performance on public datasets and experimental data. [ABSTRACT FROM AUTHOR]

Background: Silver nanoparticles (Ag NPs) are extensively used in various applications, but their reactivity leads to oxidative dissolution into Ag(I). When dealing with real samples involving Ag NPs, it is inevitable to encounter situations where both Ag NPs and Ag(I) coexist. Single particle-inductively coupled plasma mass spectrometry (SP-ICP-MS) is a valuable technique for nanoparticle size characterization. However, the presence of coexisting dissolved ions strongly interferes with the accuracy of particle size analysis using SP-ICP-MS. Therefore, it is crucial to develop a reliable separation analysis method to accurately measure both Ag NPs and Ag(I)., Results: In this study, we synthesized a silver ion-imprinted magnetic adsorbent with high adsorption capacity (149 mg g -1 ) and rapid adsorption kinetics (30 min) at both μg L -1 and mg L -1 concentration. The adsorbent selectively adsorbs Ag(I) at pH 7 while hardly adsorbing Ag NPs. It is reusable for more than 5 cycles after regeneration. Using this magnetic adsorbent prior to SP-ICP-MS, we accurately determined the sizes of standard Ag NPs in agreement with the size determined by transmission electron microscopy. The detection limit of particle size and number concentrations of Ag NPs was 12.6 nm and 6.3 × 10 5 particles L -1 . Moreover, we successfully applied the developed method to analyze Ag(I) and Ag NPs in antibacterial gel extracts and validated its accuracy through acid digestion-ICP-MS, TEM, and spiking experiments., Significance and Novelty: Direct SP-ICP-MS analysis in the presence of Ag(I) led to a high baseline, obscuring signals from smaller Ag NPs. Our method of selectively removing Ag(I) substantially improves the accuracy of Ag NPs detection via SP-ICP-MS in the antibacterial gel extracts (e.g. from 48.26 to 35.67 nm). Compared to other approaches used in SP-ICP-MS, our method has a higher adsorption capacity, allowing for better tolerance of coexisting Ag(I)., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Generative adversarial linear discriminant analysis (GALDA) is formulated as a broadly applicable tool for increasing classification accuracy and reducing overfitting in spectrochemical analysis. Although inspired by the successes of generative adversarial neural networks (GANs) for minimizing overfitting artifacts in artificial neural networks, GALDA was built around an independent linear algebra framework distinct from those in GANs. In contrast to feature extraction and data reduction approaches for minimizing overfitting, GALDA performs data augmentation by identifying and adversarially excluding the regions in spectral space in which genuine data do not reside. Relative to non-adversarial analogs, loading plots for dimension reduction showed significant smoothing and more prominent features aligned with spectral peaks following generative adversarial optimization. Classification accuracy was evaluated for GALDA together with other commonly available supervised and unsupervised methods for dimension reduction in simulated spectra generated using an open-source Raman database (Romanian Database of Raman Spectroscopy, RDRS). Spectral analysis was then performed for microscopy measurements of microsphereroids of the blood thinner clopidogrel bisulfate and in THz Raman imaging of common constituents in aspirin tablets. From these collective results, the potential scope of use for GALDA is critically evaluated relative to alternative established spectral dimension reduction and classification methods. [Display omitted] • Generative adversarial linear discriminant analysis (GALDA) was developed for spectral classification. • A theoretical foundation for implementing GALDA for spectral dimension reduction and classification was derived. • Simulations with known ground truth spectral classes supported the assessment of GALDA. • Application of GALDA improved classification accuracy in polymorph discrimination by conventional Raman spectroscopy. • Pixel-wise application of GALDA produced composition maps in good agreement with manual assignments for model system. [ABSTRACT FROM AUTHOR]

It is well known that the coexisting metal ions could significantly influence the atomic spectroscopy (AS) analysis. In this work, a cation-modulated mercury ions (Hg 2+ ) strategy via chemical vapor generation (CVG) was developed for oxalate assay due to the phenomenon that the Ag  +  can significantly reduce the Hg 2+ signal. The regulation effect was studied in depth via experimental investigations. Since Ag  +  can be reduced to silver nanoparticles (Ag NPs) by reductant SnCl 2 , the decrease of the Hg 2+ signal is attributed to the formation of a silver-mercury (Ag-Hg) amalgam. Due to the oxalate can react with Ag  +  to generate Ag 2 C 2 O 4 , which can reduce the generation of Ag-Hg amalgam, a portable and low-power point discharge chemical vapor generation atomic emission spectrometry (PD-CVG-AES) system was constructed to quantify the content of oxalate via monitoring the signal of Hg 2+ . Under optimal conditions, the limit of detection (LOD) was as low as 40 nM in the range of 0.1-10 μM for oxalate assay, while exhibiting good specificity. This method was applied to quantitative oxalate in 50 clinical urine samples of urinary stones patients. The levels of oxalate detected in clinical samples were consistent with clinical imaging results, which is promising for point-of-care testing in clinical diagnosis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Monitoring the dimerization state of the mesenchymal-epithelial transition factor (Met) was essential for in-depth understanding of the tumor signal transduction network. At present, the dimerization activation pathway of Met protein was mainly studied at the macro level, while the research at the single molecule level was far from comprehensive. Herein, the dimerization activation of Met protein's extracellular domain induced by ligand hepatocyte growth factor (HGF) was dynamically studied by single-molecule force spectroscopy. Met protein was immobilized on a biomimetic lipid membrane for ensuring its physiological environment, and then the Met dimers were recognized by bivalent probe which was formed by two Met-binding aptamers. Then the dimeric state of Met protein could be distinguished from monomeric state of Met protein through some parameters, (such as unimodal ratio, bimodal ratio and separation work). The unimodal indicates the occurrence of single molecule binding event, and the bimodal represents the occurrence of double binding event (also represents the presence of Met dimer). Before HGF treatment, most of the Met protein on the lipid membrane was still in the form of monomer, so the unimodal ratio in the force curve was larger (78.8 ± 5.2%), and the bimodal ratio was smaller (17.0 ± 4.1%). After HGF treatment, the unimodal ratio decreased to 54.0 ± 7.4%, and the bimodal ratio increased to 43.2 ± 7.3%. It was due to the formation of dimers after the binding of Met protein on the fluidity lipid membrane with HGF. In addition, the average separation work increased to about 2 times after HGF treatment. Given that studies of Met protein dimerization inhibitors have contributed to the development of more potent and safe inhibitors to significantly inhibit tumor metastasis, the effects of different medicines (including anticoagulant medicines, different antibiotics and anti-cancer medicines) on the dimerization activation of Met protein were then explored by the platform described above. The results showed that anticoagulant medicines heparin and its analogs can significantly inhibit HGF-mediated Met protein activation, while different antibiotics and anticancer medicines had no significant effect on the dimerization of Met protein. This work provided a platform for studying protein dimerization as well as for screening Met protein dimerization inhibitors at the single-molecule level., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Sulfur isotope ratios are often used as biogeochemical tracers to gain understanding of abiotic and biological processes involved in the sulfur cycle in both modern and ancient environments. There is however a lack of matrix-matched well-characterized isotopic reference materials that are essential for controlling the accuracy and precision. This study therefore focused on expanding and complementing the currently available sulfur isotope ratio data by providing the bulk sulfur isotopic composition, as determined using multi-collector inductively coupled plasma-mass spectrometry (MC-ICP-MS), for a comprehensive set of commercially and/or readily available biological and geological reference materials. A total 7 isotopic reference materials and 41 elemental reference materials were studied. These reference materials include standards of terrestrial and marine animal origin, terrestrial plant origin, human origin, and geological origin. Different sample preparation protocols, including digestion and subsequent chromatographic isolation of S, were evaluated and the optimum approach selected for each matrix type. For achieving enhanced robustness, the sample preparation and sulfur isotope ratio measurements were done at two different laboratories for selected reference materials, while at one of the laboratories the measurements were additionally performed using two different MC-ICP-MS instruments. Determined δ 34 S VCDT and δ 33 S VCDT values compared well between the different laboratories, as well as between the different generation MC-ICP-MS instruments, and for standards that were previously characterized, our data are similar to literature values. The δ 34 S VCDT ranges determined for the different categories of the reference materials - terrestrial animal origin: +2 to +9‰, marine animal origin: +15 to +20‰, human origin: +6 to +10‰, terrestrial plant origin: -20 to +7‰, and geological origin: -12 to +21‰ - fit the expected values based on previous studies of similar types of matrices well. No significant mass-independent fractionation is observed when considering the expanded uncertainties for Δ 33 S V-CDT ., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper, (Copyright © 2022 Elsevier B.V. All rights reserved.)

To meet the demand for multi-element/isotope analysis at the single nanoparticle (NP) or cell level, different types of inductively coupled plasma mass spectroscopy (ICP-MS) have been used to simultaneously monitor multiple mass-to-charge ratios in single-particle/cell ICP-MS (SP/SC-ICP-MS) analysis. Systematic evaluation and comparison of the performance of these techniques are urgently required. Herein, three ICP-quadrupole (Q)-MS, two ICP-time of flight (TOF)-MS, and one multi-collector (MC)-ICP-MS instruments were employed to simultaneously detect 107 Ag and 109 Ag on single Ag NPs and Ag-exposed cyanobacteria cells. The evaluation was conducted by comparing the measured event-specific 109 Ag: 107 Ag ratios with the natural ratio. Duration of NP or cell events and time resolution in the peak hopping mode were the main factors affecting the performance of ICP-Q-MS. Under the optimal condition (100 μs for both dwell time and settling time), less than 45% of the NP or cell events had a 109 Ag: 107 Ag ratio deviating <30% from the natural ratio. Most events obtained via ICP-TOF-MS were paired events with both isotopes detected. For large-size NPs and cells with high exposure levels, nearly 80% of the events had a ratio deviation within ±30%. MC-ICP-MS performed particularly well in isotope determination with all the events having a ratio deviation within ±5%. For ICP-TOF-MS and MC-ICP-MS, the signal intensity of the events was the main factor affecting the accuracy of the measured 109 Ag: 107 Ag ratios due to the counting statistics. The established methods and results provide insight on the analyses of two elements/isotopes or more on single NPs or cells. Based on the comparison of the advantages and limitations of these instruments, this study provides a critical reference for future multi-element/isotope SP/SC-ICP-MS analyses., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Cysteine (Cys), one of cellular biothiols in the organism, is associated with many diseases, such as Parkinson's disease, Alzheimer's disease, liver damage, rheumatoid arthritis, and cancer. However, activatable fluorescence/photoacoustic (FL/PA) probes for non-invasive, real-time, and deep imaging of Cys in vivo are still lacking, and this hinders the diagnosis of Cys-related diseases. Herein, we designed and synthesized a novel activated FL/PA dual-modality cyanine-base probe (FP 700 ) for real-time detection of Cys. The probe FP 700 was established with near-infrared emissive dye cyanin as the fluorophore, linking with 2, 4-dinitrobenzenesulfonyl group as the recognition moiety for Cys. Using the FP 700 , we found that the FP 700 exhibited intensive "turn-on" FL/PA signals under the excitation of 700 nm, which realized noninvasive in vivo detection of exogenous Cys. Significantly, FP 700 accurately detected endogenous Cys though the FL/PA dual-mode imaging technology in tumor-bearing mice and obtain 3D PA diagnostic images with deep penetration depth and spatial resolution. Thus, the new dual-modality probe FP 700 has advantage of high potential for deep tumor diagnosis of Cys in vivo, which may provide a new approach for the detection of cervical cancer and identification of its potential therapeutic targets., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

To achieve the quantitative elemental analysis of aluminum alloy samples, the one-point and multi-line calibration (OP-MLC) method and femtosecond laser-ablation spark-induced breakdown spectroscopy (fs-LA-SIBS) were combined in this study. An ultrafast Ti: sapphire laser with high single-pulse energy and high repetition-rate operation was used as the laser source to ablate the sample at a 1k Hz pulse repetition rate and achieve re-excitation using spark discharge. Subsequently, an enhanced spectral peak intensity was achieved, which increased the sensitivity and analytical capabilities of laser-induced breakdown spectroscopy (LIBS) technique. Considering only one confirmed sample, the OP-MLC method was used to calculate the concentration ratios of trace elements Mg, Cr, Cu, Mn and Zn in four aluminum alloy samples to the calibration samples by the integral intensity ratio of the elemental characteristic lines between the two samples. The average relative errors with the identified concentrations were 3.99%, 15.13%, 8.76%, 9.30% and 9.64%, respectively. The results showed that the combination of OP-MLC method and fs-LA-SIBS has good accuracy in the quantitative analysis of elements, and has the advantages of simplicity, rapidity and high sensitivity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

On-site and sensitive analysis of phytoavailable heavy metals is the key to fast evaluate the pollution incidents, while the development of convenient and efficient sample introduction approaches against matrix interference is crucial to improve the performances of field-deployable instruments. Herein, trace phytoavailable heavy metals in soil are first extracted by 0.1 M NaNO 3 , afterwards adsorbed onto an activated carbon tip via electroextraction (EE), and finally analyzed by dielectric barrier discharge (DBD) microplasma optical emission spectrometry (OES) via in situ desorption. The activated carbon tip is not only able to extract heavy metals from alkali metals/alkaline earth metals matrix, resisting the interference of coexisting anions and non-electroactive species in saline soil extract, but also significantly improves the detection sensitivity of subsequent DBD-OES analysis by increasing loading amounts of analytes. Taking the key heavy metals pollution as model, the detection limits of Cd, Zn, Cu and Pb reach 0.8, 2.3, 6.0 and 4.5 μg kg -1 , respectively, and precisions are within 2.7-4.6%. The accuracy and practicability of the present miniaturized EE-DBD-OES device have been verified by measuring several certified reference materials and real soil samples, providing a promising tool for convenient and sensitive analysis of trace phytoavailable heavy metals in soil., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The selection of a training set is the key to determining the quality of the model. In the spectrum analysis, due to various interference factors, the quality of the collected spectral data of some samples has a serious deviation. If directly used in modeling, it will introduce bias to the establishment of the model. Therefore, to get the most representative samples, it is necessary to select samples before establishing the model. This paper proposes a two-dimensional sample selection (TDSS) method, which selects samples from two angles of spectral data quality and variable correlation. This method and Mahalanobis distance method were respectively applied to dynamic spectrum (DS) data to screen samples. The samples screened by the two methods were used for modeling. Finally, establish partial least squares (PLS) linear regression model with a quadratic nonlinear correction method to predict the target components. The experimental results show that the sample screening method significantly improved the accuracy and prediction performance of the model, and it is better than the Mahalanobis distance method. In the prediction of triglyceride and total cholesterol, the correlation coefficient can reach above 0.82. The experimental results fully prove the effectiveness of the sample selection method in this paper, and it has a remarkable effect on improving the accuracy and robustness of the model. This paper provides a new way for sample selection of modeling set in spectral analysis of complex solutions. [Display omitted] • Propose a new training set sample screening method. • Consider two dimensions: sample data quality and variable correlation. • Based on statistical and dynamic spectrum data. • Improve the accuracy of non-invasive blood component detection. • This method is a universal method for sample screening in spectral analysis. [ABSTRACT FROM AUTHOR]

Single particle-inductively coupled plasma-mass spectrometry (SP-ICP-MS) was used in the analysis of single particles/cells. Although quadrupole mass analyzers are widely used, the long settling time restricts measurement to single elements in individual particles. Recently, dual-elemental analysis has successfully been developed with the assistance of oxygen gas in the collision cell. This simple approach greatly expands the capability of quadrupole-based ICP-MS. In this study, we adopted bandpass mode in the first quadrupole (Q1) to improve the limit of detection of single particles against spectral interference. A model was developed to explain the rationale behind the selection of quadrupole voltages. The quadrupole voltages were optimized systematically so that the mass bandwidth of Q1 allowed the transmission of two target analytes while the interference species were rejected. As a result, the signal from the polyatomic interference was reduced by 98% with no significant change in the analyte signal. The bandpass mode was further applied to accurately determine the isotope ratio of 109 Ag/ 107 Ag in 80-nm Ag nanoparticles, as well as the Ag content in AgSn alloy particles, under the polyatomic interference of 91 Zr 16 O originating from dissolved ions and particles. This technique was further applied to the determination of two Yb isotopes in algal cells with interference from Gd. Results indicate that this approach has great potential for assessing single particles and biological cells in the presence of severe interference from imaging agents, drugs, or biological fluids., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The cellular metabolism of metals is highly critical to elucidate their potential cytotoxicity or cell protection mechanism. In this work, an asymmetric serpentine microfluidic device (ASMD) with high sampling efficiency and excellent focusing performance was developed for single-cell focusing. ASMD coupling with ICP-MS ensures single-cell assay to provide the information for trivalent arsenic (As(III)) uptake by HepG2 cells, which reveals the heterogeneity of cellular arsenic distribution, and elucidates the arsenic elimination behaviors in single HepG2 cells. Further, the metabolism and transformation of As(III) in HepG2 cells was tracked by hyphenating capillary electrophoresis (CE) separation with ICP-MS. The results for single-cell analysis and arsenic elimination kinetics illustrated that the half-life of arsenic elimination is 0.9 ± 0.04 h with the elimination constant of 0.77 ± 0.03, i.e., 77% of accumulated As in HepG2 cells may be eliminated per hour. Moreover, arsenobetaine (AsB) was identified to be the main metabolite and biotransformation species of As in HepG2 cells. ASMD-ICP-MS and CE-ICP-MS are powerful for tracking the fate of metals or metal drugs in single cells to comprehensively understand their metabolic pathway and transformation behaviors., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Quantitative mass spectrometry analysis for multi-component gas phase reaction processes is a typical multi-input and multi-output (MIMO) nonlinear problem. Conventional calibration and analytical methods that are based on the common hypothesis of linearity of the detected signal and gas parameters, could result in misjudgment of the reaction mechanism and inaccuracy in the determination of the reaction kinetics. In the present work, theoretical derivations based on equivalent characteristic spectrum analysis (ECSA®), discrete mode experiments and continuous mode experiments were performed, and the nonlinearity of mass spectrometry was confirmed. It is only possible to determine the physical parameters such as flow rate and/or concentrations of gases by properly handling the nonlinearity of mass spectrometry. In such case comprehensive reaction mechanisms and even the kinetics of the process can be accurately characterized. Well-handled nonlinear mass spectrometry analysis ensures a reliable and highly accurate identification for the multi-component gas phase reaction processes, and ensures high signal-to-noise ratio for detecting the small-flow gases at a wide range of carrier gas flow. [Display omitted] • The MS nonlinearity between MI and MO signals is found and expounded firstly. • The MS nonlinearity is confirmed through theoretical derivation and experiments. • Taking the nonlinearity ensures the MS reliability, and high signal-to-noise ratio. • Using ECSA® it was possible to well interpret the nonlinearity. [ABSTRACT FROM AUTHOR]

Cannabis has been at the center of scientific attention for some years now. Since its pharmacological potential has been highlighted, cannabis has become a hot topic in research laboratories, leading to the publication of many scientific studies. Focusing on analytical chemistry, an enormous number of analytical methods for cannabinoid (CNB) determination have been published, involving various techniques. However, no globally accepted reference method for CNB determination has yet been chosen. This review aims to identify very recent analytical methods developed to analyze phytocannabinoids in cannabis herbal samples. For certain techniques, stagnation in terms of employed operational conditions can be observed. In this context, a reference method of analysis should be proposed and accepted worldwide to standardize CNB determination. In contrast, for other techniques, we are witnessing a scientific ferment, which is resulting in the development of new interesting analytical options. In this regard, particular focus has been given to these niche techniques, which are now emerging in the analytical panorama of cannabis analysis, offering new important perspectives for the future of cannabis testing. Supercritical fluid chromatography and infrared spectroscopy showed tangible advantages when applied to CNB determination in herbal samples., (Copyright © 2021 Elsevier B.V. All rights reserved.)

A fast and cost-effective procedure based on Inductively Coupled Plasma - Mass Spectrometry (ICP-MS) for the selective determination of methylmercury (MeHg) is proposed and validated for fish tissue analysis. Selectivity for MeHg is achieved by simply inserting a strong anion exchange resin to block inorganic mercury as negatively charged chloride species, leaving MeHg unretained. The procedure features a 15 min extraction time followed by a 100 s analysis time achieving a limit of detection of 1.6 μg kg -1 on solid samples. The effect of the solution composition and inorganic mercury concentration were extensively studied to fully assess the selectivity of the procedure: Hg(II):MeHg ratios up to 50 are tolerated and cause systematic errors lower than 15%. The entire procedure was successfully validated by standard reference material from the marine food web, namely fish muscle and liver plus zooplankton. The method was finally applied to the detection of MeHg in the marine trophic web of Djibouti (Gulf of Aden): a trophic magnification factor of 13.5 proved the high risk associated with the biomagnification of methylmercury., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

This paper presents a novel approach, based on the standard addition method, for overcoming the matrix effects that often hamper the accurate characterization of nanoparticles (NPs) in complex samples via single particle inductively coupled plasma mass spectrometry (SP-ICP-MS). In this approach, calibration of the particle size is performed by two different methods: (i) by spiking a suspension of NPs standards of known size containing the analyte, or (ii) by spiking the sample with ionic standards; either way, the measured sensitivity is used in combination with the transport efficiency (TE) for sizing the NPs. Moreover, such transport efficiency can be readily obtained from the data obtained via both calibration methods mentioned above, so that the particle number concentration can also be determined. The addition of both ionic and NP standards can be performed on-line, by using a T-piece with two inlet lines of different dimensions. The smaller of the two is used for the standards, thus ensuring a constant and minimal sample dilution. As a result of the spiking of the samples, mixed histograms including the signal of the sample and that of the standards are obtained. However, the use of signal deconvolution approaches permits to extract the information, even in cases of signal populations overlapping. For proofing the concept, characterization of a 50 nm AuNPs suspension prepared in three different media (i.e., deionized water, 5% ethanol, and 2.5% tetramethyl ammonium hydroxide-TMAH) was carried out. Accurate results were obtained in all cases, in spite of the matrix effects detected in some media. Overall, the approach proposed offers flexibility, so it can be adapted to different situations, but it might be specially indicated for samples for which the matrix is not fully known and/or dilution is not possible/recommended., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Herein, we developed a novel microplasma-assisted vapor generation technique based on solution anode glow discharge (SAGD) as a substitute for the pneumatic nebulization (PN) routinely used in inductively coupled plasma-optical emission spectrometry (ICP-OES). Under the optimal state of the newly proposed SAGD-ICP-OES system, the detection limits (DLs) of Cd and Hg were reduced by some 12- and 90-fold respectively, and an average of 2 times for other elements (Ag, Bi, Pb, Tl and Zn) in comparison with conventional PN. This system not only obtained the good detection limits amenable to the ultra-trace determination of Cd (DL = 0.3 μg L -1 ) and Hg (DL = 0.2 μg L -1 ), but also retained the ability of multi-element analysis. Its accuracy was demonstrated by the determination of Cd and Hg using GBW07312 (stream sediments) and GBW10029 (fish) certified reference materials (CRMs) and spiked tap water samples. The results showed good consistency with the certified values and the values obtained using inductively coupled plasma-mass spectrometry., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Laser-induced breakdown spectroscopy (LIBS) is a practical technique for in-situ detection, but self-absorption effect has been a big issue for quantitative applications of this technique. In presented work, a method was developed to correct self-absorption to improve the quantitation of underwater LIBS. We proposed "relative self-absorption coefficient" as the critical parameter to evaluate self-absorption, and the plasma image was employed as the reference to determine the coefficient value. Based on that, the LIBS detection was successfully corrected by the coefficient to realize quantitative analysis, and the "Dominant Factor-PLS" was used as assistance. The results indicated that our method greatly improved LIBS quantitation in practice. More importantly, the calibration curve was able to be established with high linearity (R 2  = 0.9999) to cover a large concentration range (0-10 3  ppm). It is hoped that our method could be a contribution to developing LIBS as an analytical tool for field measurements., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Biofilms are a major cause of health and environmental issues. Bacteria organized in biofilms are much more resistant to biocides than their equivalents in the planktonic state. In this context, spectroscopic techniques have significantly contributed to a more fundamental understanding of biofilm formation, which is crucial to prevent and limit their generation, spreading, and maturation. In this review, recent progress on the main analytical approaches enabling the spectroscopic characterization of microbial biofilms is comparatively discussed. In addition, less commonly used techniques, facilitating biofilm studies, will be also presented. Advantages and drawbacks of each discussed technique will be underlined, thus providing an overview on spectroscopic approaches for studying biofilms., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The growing importance of fluoropolymers in high-tech applications and green technologies results in the rising need for their characterization. In contrast to conventional methods used for this task, laser-induced breakdown spectroscopy (LIBS) provides the advantage of a spatially resolved analysis. Nevertheless, the high excitation energy of fluorine results in low sensitivity of the atomic F(I) lines, which limits the feasibility of its LIBS-based analysis. This work presents a novel approach for quantitative mapping of fluorine in fluoropolymer samples. It bases on monitoring of molecular emission bands (CuF or CaF) arising from fluorine containing molecules. These species were generated during later stages of the LIBS plasma by a recombination of fluorine atoms originating from fluoropolymer sample with a molecule-forming partner (Cu or Ca) stemming from a surface coating. This approach enables F detection limits in the parts per million (μg g -1 ) range and elemental imaging using single shot measurements. The elements required for molecular formation are deposited on the sample surface prior to analysis. We evaluate two techniques - spray coating and sputter coating - with regards to their effects on sensitivity and spatial resolution in elemental mapping. Overall, both methods proved to be suitable for a spatially resolved analysis of fluorine: whereas sputter-coating of copper yielded a better sensitivity, spray coating of calcium provided a higher spatial resolution., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Actinium-225 is a highly radiotoxic alpha-emitting radionuclide, which is currently in the spotlight owing to its promising radiotherapeutic applications in nuclear medicine. Personnel involved in the production and handling of actinium-225 is exposed to a risk of accidental incorporation of this radionuclide. Radiological protection regulations require regular monitoring of incorporation and internal dosimetry assessment for workers manipulating open radioactive sources. Urine is often used as a biological sample for measuring the incorporation of actinides, however it requires a radiochemical separation with a certified metrological tracer to enable quantitative determination. There is no stable, nor sufficiently long-lived radioactive isotopes of actinium to provide a metrological yield tracer. In this article, we propose an application of an ion-imprinted polymer resin to extract actinium-225 from urine employing americium-243 as a radioactive tracer. The radiochemical separation was followed by a quantitative determination with alpha-spectrometry. Solid-phase extraction of both actinides from urine using ion-imprinted polymer resin resulted in good radiochemical yields: 57.7 ± 16.5% (n = 17) for actinium-225 and 62.8 ± 18.0% (n = 17) for americium-243. Equivalent recoveries showed that americium-243 is a suitable yield tracer for the determination of actinium-225 with an ion-imprinted polymer resin. Combined with a different measurement technique, this method can be applied for the separation of other isotopes of actinium, such as actinium-227., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)