Rapid Discrimination Research Articles

A rapid and sensitive colorimetric discrimination and detection of cysteine, homocysteine and glutathione by phloroglucinol-functionalized silver nanoresonators with real applications

The phloroglucinol-functionalized silver nanoparticles exhibited naked eye detection for cysteine, homocysteine and glutathione through three different colors and UV-Vis spectral patterns.

Chromatographic printed array strip (C-PAS) method for cultivar-specific identification of sweetpotato cultivars 'Beniharuka' and 'Fukumurasaki'.

Sweetpotato (Ipomoea batatas) cultivars grown in Japan are highly valued for their excellent sweetness, high quality, and good texture. The export volume of sweetpotato from Japan has been rising rapidly, with a 10-fold increase on a weight basis over the last 10 years. However, since sweetpotato is propagated vegetatively from storage roots, it is easy to cultivate and propagate this crop, prompting concerns that Japanese sweetpotato cultivars/lines are being exported overseas, cultivated without permission, or reimported. Therefore, a rapid and accurate cultivar identification methodology is needed. In this study, we comprehensively analyzed the insertion sites of Cl8 retrotransposon to develop a cultivar identification technique for the Japanese cultivars 'Beniharuka' and 'Fukumurasaki'. These two cultivars were successfully distinguished from other cultivars using a minimum of two marker sets. Using the chromatographic printed array strip (C-PAS) method for DNA signal detection, 'Beniharuka' and 'Fukumurasaki' can be precisely identified using a single strip of chromatographic paper based on multiplex DNA signals derived from the amplicons of the Cl8 insertion sites. Since this method can detect DNA signals in only ~15 minutes, we expect that our method will facilitate rapid, reliable, and convenient cultivar discrimination for on-site inspection of sweetpotato.

Integrated portable food safety testing pipette based on a color-switchable fluorescence probe for rapid visual discrimination of mild food deterioration.

A sensitive, portable, easy-to-operate, directly-readable food freshness monitoring device has been developed for rapid visual identification of mild food spoilage.

Geographical origin traceability of rice using a FTIR-based metabolomics approach.

Infrared spectroscopy is a crucial tool to achieve the origin traceability of rice, but it is constrained by data mining. In this study, a novel infrared spectroscopy-based metabolomics analytical method was proposed to discriminate rice products from 14 Chinese cities by seeking 'wave number markers'. Principal component analysis (PCA), cluster analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) were employed to separate all rice groups. The S-plot, permutation test and variable importance in projection (VIP) are used to screen eligible 'markers', which were further verified by a pairwise t-test. There are 55-265 'markers' picked out from 14 rice groups, with their characteristic wave number bands to be 2935.658-3238.482, 3851.846-4000.364, 3329.136-3518.160, 1062.778-1213.225, 1161.147-1386.819, 3348.425-3560.594, 3115.038-3624.245, 2567.254-2872.007, 3334.923-3560.594, 3282.845-3543.235, 3338.780-3518.160, 3197.977-3560.594, 3163.258-3267.414 and 3292.489-3477.655 cm-1, respectively. All but No. 5 rice groups show significantly low absorbance on their 'marker' bands. A mixed rice containing congenial No. 5 and No. 6 rice (80 : 20, m/m) was employed to test the validity of the method, and found that the 'marker' band of the mixed rice is the range of 1170.791-1338.598 cm-1, implying the existence of considerable discrepancy between the mixed rice and other rice. The results indicate that infrared spectroscopy coupled with metabolomics analysis is competent for origin traceability of rice; thus, it provides a novel and workable approach for the accurate and rapid discrimination of rice from different geographical origins, and a distinctive perspective of metabolomics to explore infrared spectroscopy and beyond, especially not confined in the field of origin traceability.

Rapid and Accurate Discrimination of Mycobacterium abscessus Subspecies Based on Matrix-Assisted Laser Desorption Ionization-Time of Flight Spectrum and Machine Learning Algorithms.

Mycobacterium abscessus complex (MABC) has been reported to cause complicated infections. Subspecies identification of MABC is crucial for adequate treatment due to different antimicrobial resistance properties amid subspecies. However, long incubation days are needed for the traditional antibiotic susceptibility testing (AST). Delayed effective antibiotics administration often causes unfavorable outcomes. Thus, we proposed a novel approach to identify subspecies and potential antibiotic resistance, guiding early and accurate treatment. Subspecies of MABC isolates were determined by secA1, rpoB, and hsp65. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) spectra were analyzed, and informative peaks were detected by random forest (RF) importance. Machine learning (ML) algorithms were used to build models for classifying MABC subspecies based on spectrum. The models were validated by repeated five-fold cross-validation to avoid over-fitting. In total, 102 MABC isolates (52 subspecies abscessus and 50 subspecies massiliense) were analyzed. Top informative peaks including m/z 6715, 4739, etc. were identified. RF model attained AUROC of 0.9166 (95% CI: 0.9072-0.9196) and outperformed other algorithms in discriminating abscessus from massiliense. We developed a MALDI-TOF based ML model for rapid and accurate MABC subspecies identification. Due to the significant correlation between subspecies and corresponding antibiotics resistance, this diagnostic tool guides a more precise and timelier MABC subspecies-specific treatment.

Dual Classification Approach for the Rapid Discrimination of Metabolic Syndrome by FTIR

Metabolic syndrome is a complex of interrelated risk factors for cardiovascular disease and diabetes. Thus, new point-of-care diagnostic tools are essential for unambiguously distinguishing MetS patients, providing results in rapid time. Herein, we evaluated the potential of Fourier transform infrared spectroscopy combined with chemometric tools to detect spectra markers indicative of metabolic syndrome. Around 105 plasma samples were collected and divided into two groups according to the presence of at least three of the five clinical parameters used for MetS diagnosis. A dual classification approach was studied based on selecting the most important spectral variable and classification methods, linear discriminant analysis (LDA) and SIMCA class modelling, respectively. The same classification methods were applied to measured clinical parameters at our disposal. Thus, the classification's performance on reduced spectra fingerprints and measured clinical parameters were compared. Both approaches achieved excellent discrimination results among groups, providing almost 100% accuracy. Nevertheless, SIMCA class modelling showed higher classification performance between MetS and no MetS for IR-reduced variables compared to clinical variables. We finally discuss the potential of this method to be used as a supportive diagnostic or screening tool in clinical routines.

Preparation of fluorescein-modified polymer dots and their application in chiral discrimination of lysine enantiomers.

Fluorescein-functionalized fluorescent polymer dots (F-PDs) were prepared by a facile one-pot method by magnetic stirring under mild conditions based on carboxymethylcellulose (CMC) and fluorescein as the precursors. The obtained F-PDs exhibited a nanoscale size of 3.2 ± 1.1nm, excellent water solubility, and bright yellow fluorescence emission with a fluorescence quantum yield of 12.0%. The fluorescent probe displays rapid and sensitive chiral discrimination for lysine focused on different complexation abilities between lysine enantiomers and Cu2+. The concentration of L-lysine in the range4 to 14mM (R2 = 0.997) wasmeasured by the fluorescence intensity ratio (I513/I429); the exitation wavelength was set to λex = 365nm. The detection limit was 0.28mM (3σ/slope). Importantly, this sensor accurately predicted the enantiomeric excess (ee) of lysine enantiomers at the designed concentration (lysine: 20mM; Cu2+: 10mM) ranges. Theproposed sensor was successfully applied to determineL-lys (recovery: 95.8-101%; RSD: 0.465-3.34%) and ee values (recovery: 98.5-102%; RSD: 2.61-3.21%) in human urine samples using the standard addition method.

Rapid discrimination of enantiomers by ion mobility mass spectrometry and chemical theoretical calculation: Chiral mandelic acid and its derivatives

Because R/S-mandelic acids (MA) and their derivatives are critical starting materials or intermediates in the synthesis of chiral drugs, their chirality discrimination is important. In this study, R/S-MA and its derivatives, including R/S-2-phenylpropionic acid (2-PPA), R/S-methoxyphenylaceticacid (MPA), and R/S-2-hydroxy-4-phenylbutyric acid (HPBA), were accurate simultaneous mobility-discriminated by forming diastereomer complexes for the first time, which were obtained by simply mixing with cyclodextrins (α, β, γ-CD) and transition-metal ions (Mn2+, Fe2+, Co2+, Ni2+, Cu2+, and Zn2+). The mass spectra revealed non-covalent diastereomer complexes formed by CD, enantiomers, and metal ions, and ion-mobility spectrometry (IMS) was performed for 109 pairs of complexes. Significant chiral discrimination was observed in the formed diastereomeric complexes, and their separation peak-to-peak resolution (Rp−p) for the enantiomers depended on the transition metal ion type. In most cases, the Rp−p value gradually increases with CD size, with quaternary complexes having the largest Rp−p value. The greatest chiral distinctions of 2-PPA, MA, MPA, and HPBA were obtained by the diastereomeric complex ions of [(2-PPA)(α)2+Zn2+-H]+, [(MA)(α)2+Zn2+-H]+, [(MPA)2(β)+Co2+-H]+, and [(HPBA)(α)2+Fe2+-H]+, with Rp−p values of 1.35, 1.57, 1.70, and 0.71, respectively. Furthermore, the favorable conformation and collisional cross section (CCS) value of the different [CD + R/S-MA + Cu–H]+ complexes were measured using chemical theoretical calculations to detail their intermolecular interaction, revealing that [α-CD + R/S-MA + Cu–H]+ has two favored gas complexes, and the CCS calculated were consistent with the TIMS observed. In addition, R2 > 0.99 was obtained for the relative quantification of the chiral enantiomers. Overall, the proposed method provides a promising strategy for distinguishing the enantiomers of MA and their derivatives, with the advantages of simplicity, speed, and accuracy, without the need for complex chemical derivatization or chromatographic separation.

Identification of and discrimination between the Mycobacterium abscessus complex and Mycobacterium avium complex directly from sputum using quadruplex real-time PCR.

Introduction. Cystic fibrosis (CF) is a serious disease with multisystemic clinical signs that is easily and frequently complicated by bacterial infection. Recently, the prevalence of nontuberculous mycobacteria as secondary contaminants of CF has increased, with the Mycobacterium avium complex (MAC) and Mycobacterium abscessus complex (MABSC) being the most frequently identified. The MABSC includes subspecies of significant clinical importance, mainly due to their resistance to antibiotics.Gap statement. Sensitive method for early detection and differentiation of MABSC members and MAC complex for use in routine clinical laboratories is lacking. A method based on direct DNA isolation from sputum, using standard equipment in clinical laboratories and allowing uncovering of possible sample inhibition (false negative results) would be required. The availability of such a method would allow accurate and accelerated time detection of MABSC members and their timely and targeted treatment.Aim. To develop a real time multiplex assay for rapid and sensitive identification and discrimination of MABSC members and MAC complex.Methodology. The method of DNA isolation directly from the sputum of patients followed by quadruplex real-time quantitative PCR (qPCR) detection was developed and optimised. The sensitivity and limit of detection (LOD) of the qPCR was determined using human sputum samples artificially spiked with a known amount of M. abscessus subsp. massiliense (MAM).Results. The method can distinguish between MAC and MABSC members and, at the same time, to differentiate between M. abscessus subsp. abscessus/subsp. bolletii (MAAb/MAB) and MAM. The system was verified using 61 culture isolates and sputum samples from CF and non-CF patients showing 29.5 % MAAb/MAB, 14.7 % MAM and 26.2 % MAC. The LOD was determined to be 1 490 MAM cells in the sputum sample with the efficiency of DNA isolation being 95.4 %. Verification of the qPCR results with sequencing showed 100 % homology.Conclusions. The developed quadruplex qPCR assay, which is preceded by DNA extraction directly from patients' sputum without the need for culturing, significantly improves and speeds up the entire process of diagnosing CF patients and is therefore particularly suitable for use in routine laboratories.

Rapid discrimination of Brassica napus varieties using visible and Near-infrared (Vis-NIR) spectroscopy

Brassica napus is an oilseed plant that is mostly used to produce edible oils, industrial oils, modified lipids and biofuels. The number of varieties/cultivars is high for the species, owing to their higher level of economic use. The aim of this study is to assess the use of visible-near infrared (Vis-NIR) spectroscopy in combination with multiple chemometric methods that have been explored for the discrimination of eight Brassica napus varieties in Korea. In this study, the spectra from leaves of the eight B. napus varieties were measured in the Vis-NIR spectra in the range of 325–1075 nm with a stepping of 1.5 nm in reflectance mode. The spectral data were preprocessed with three different preprocessing methods and eight different chemometric analyses were used for effective discrimination. After the outlier detection, the samples were split into two sets, one serving as a calibration set and the remaining one as a validation set. When using multiple preprocessing and chemometric methods for the discrimination, the maximum classification accuracy was witnessed in the combination of standard normal variate and support vector machine up to 98.2 %. The use of Savitzky-Golay filter smoothing as a preprocessing method had the best and most satisfactory discrimination of all other chemometric methods. The results suggest that the use of handheld Vis-NIR spectroscopy in combination with chemometric approaches can be used as an effective tool for the discrimination of B. napus varieties in the field.

Energy transfer mediated rapid and visual discrimination of tetracyclines and quercetin in food by using N, Cu Co-doped carbon dots

The appearance of multi-drug resistant Escherichia coli makes the combination of tetracyclines (TCs) and quercetin (QCT) more common to fight stubborn bacterial infections so that the effective detections of TCs and QCT are essential and necessary. Here, a novel fluorescence probe for differentiating TCs and QCT is developed based on the nitrogen and copper co-doped carbon dots (N, Cu-CDs). The N, Cu-CDs are prepared from ethylene diamine tetraacetic acid (EDTA) and anhydrous copper chloride as precursors through hydrothermal process and exhibit bright blue fluorescence with excellent optical stability. With the presence of four tetracyclines (DOX, TC, CTC and OTC), the fluorescence intensity of N, Cu-CDs is quenched directly due to the internal filtration effect (IFE), and the detection limit obtained through single-signal fluorescence sensing is as low as 23.8 nM for DOX, 37.2 nM for TC, 43.8 nM for OTC and 28.8 nM for CTC. More remarkably, three dimensional ratiometric fluorescence probe for detecting QCT is proposed based on the appearance of another emission at (410 nm, 490 nm) due to electron transform (ET) process. This new method shows a good linear relationship in the range of 10–100 μM with a low detection limit of 59.3 nM. Furthermore, a dual-channel fluorescence sensing platform based on microfluidics paper-based analytical devices (μPADs) is developed for simultaneously visual discrimination of TCs (DOX is chosen as the typical detecting model for TCs) and QCT. This investigation provides a new way for the development of CDs as multifunction fluorescence probes.

A Portable MR Sensor for Rapid Discrimination of Ex Vivo Breast Cancerous Tissue in Mice

The conventional diagnosis examination for cancerous tissue relies on the cumbersome and time-consuming pathologic section technology. In this article, we propose a 1-T portable magnetic resonance (MR) sensor equipped with a 3-mm probe, which enabled the rapid discrimination of ex vivo breast cancerous tissue in mice based on the MR longitudinal relaxation time ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${T}_{{1}}$ </tex-math></inline-formula> ) measurement approach. First, the excellent distinction ability between ex vivo breast cancerous tissue and normal tissue using the proposed 1-T portable MR sensor is demonstrated. The <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${T}_{{1}}$ </tex-math></inline-formula> contrast (i.e., <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${T}_{\text {1cancerous}}/{T}_{\text {1normal}})$ </tex-math></inline-formula> is also compared with the other magnetic field strength MR systems, i.e., 0.23, 0.51, and 1.41 T. The results show that the average values of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${T}_{{1}}$ </tex-math></inline-formula> contrast at different MR measurement systems are all about 1.41. Then, the potential of the proposed 1-T MR sensor is validated in terms of sensitivity and portability. Finally, the limitations and future work of this preliminary study are discussed. Taken together, the proposed 1-T portable MR sensor with the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${T}_{{1}}$ </tex-math></inline-formula> value measurement approach has the promise to provide a low-cost, rapid, and accurate means for clinical assessment of the properties of tissue specimens, especially the trace tissue specimen taken from biopsy techniques.

Leveraging single-cell Raman spectroscopy and single-cell sorting for the detection and identification of yeast infections

Invasive fungal infection serves as a great threat to human health. Discrimination between fungal and bacterial infections at the earliest stage is vital for effective clinic practice; however, traditional culture-dependent microscopic diagnosis of fungal infection usually requires several days, meanwhile, culture-independent immunological and molecular methods are limited by the detectable type of pathogens and the issues with high false-positive rates. In this study, we proposed a novel culture-independent phenotyping method based on single-cell Raman spectroscopy for the rapid discrimination between fungal and bacterial infections. Three Raman biomarkers, including cytochrome c, peptidoglycan, and nucleic acid, were identified through hierarchical clustering analysis of Raman spectra across 12 types of most common yeast and bacterial pathogens. Compared to those of bacterial pathogens, the single cells of yeast pathogens demonstrated significantly stronger Raman peaks for cytochrome c, but weaker signals for peptidoglycan and nucleic acid. A two-step protocol combining the three biomarkers was established and able to differentiate fungal infections from bacterial infections with an overall accuracy of 94.9%. Our approach was also used to detect ten raw urinary tract infection samples. Successful identification of fungi was achieved within half an hour after sample obtainment. We further demonstrated the accurate fungal species taxonomy achieved with Raman-assisted cell ejection. Our findings demonstrate that Raman-based fungal identification is a novel, facile, reliable, and with a breadth of coverage approach, that has a great potential to be adopted in routine clinical practice to reduce the turn-around time of invasive fungal disease (IFD) diagnostics.

Discrimination of influenza A virus subtypes by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Influenza is a contagious respiratory illness caused by influenza viruses which possess the enormous threat to older people and young children. Rapid and precise discrimination of virus subtypes are quite crucial for the early therapy, prophylaxis and the prevention of epidemic outbreaks. Herein, a universal strategy, with influenza A virus (IAV) as a model, is proposed for the discrimination of virus subtypes based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Reference library based on nine IAVs subtypes (i.e., H1N1, H3N2, H4N8, H5N8, H6N6, H7N7, H9N2, H10N8, and H11N8) was set up for matching various IAVs subtypes. The simulative test spectra from IAVs showed that the corresponding IAVs subtypes could be distinguished in 90 min, accurately. Furthermore, the principal component analysis results also show that nine virus subtypes can be reliably distinguished. More importantly, this strategy provides an alternative method for identifying and distinguishing other viruses with high variability characteristics, such as SARS-CoV-2, which could be helpful for implementing public health strategies to counter pandemics.

Chemical profiling and rapid discrimination of Blumea riparia and Blumea megacephala by UPLC-Q-Exactive-MS/MS and HPLC

ObjectiveTo rapidly identify the two morphologies and chemical properties of similar herbal medicines, Blumea riparia and B. megacephala as the basis for chemical constituent analysis. MethodsUPLC-Q-Exactive-MS/MS was utilized for profiling and identification of the constituents in B. riparia and B. megacephala. Chemical pattern recognition (CPR) was further used to compare and distinguish the two herbs and to identify their potential characteristic markers. Then, an HPLC method was established for quality evaluation. ResultsA total of 93 constituents are identified, including 54 phenolic acids, 35 flavonoids, two saccharides, one phenolic acid glycoside, and one other constituent, of which 67 were identified in B. riparia and B. megacephala for the first time. CPR indicates that B. riparia and B. megacephala samples can be distinguished from each other based on the LC–MS data. The isochlorogenic acid A to cryptochlorogenic acid peak area ratio calculated from the HPLC chromatograms was proposed as a differentiation index for distinguishing and quality control of B. riparia and B. megacephala. ConclusionThis study demonstrates significant differences between B. riparia and B. megacephala in terms of chemical composition. The results provide a rapid and simple strategy for the comparison and evaluation of the quality of B. riparia and B. megacephala.

Introducing "DoPP": A Graphical User-Friendly Application for the Rapid Species Identification of Psychoactive Plant Materials and Quantification of Psychoactive Small Molecules Using DART-MS Data.

The widespread abuse of "legal high" psychoactive plants continues to be of global concern because of their negative impacts on public health and safety. In forensic science, a major challenge in controlling these substances is the paucity of methods to rapidly identify them. We report the development of the Database of Psychoactive Plants (DoPP), a new user-friendly tool featuring an architecture for the identification of plant unknowns, and the necessary regression statistics for the development and validation of psychoactive compound quantification. The application relies on the knowledge that terrestrial plants exhibit species-specific chemical signatures that can be revealed by direct analysis in real time─high-resolution mass spectrometry (DART-HRMS). Subsequent automated machine learning processing of libraries of these spectra enables rapid discrimination and species identification. The chemical signature database includes 57 available plant species. The rapid acquisition of mass spectra and the ability to sample the materials in their native form enabled the generation of the vast amounts of spectral replicates required for database construction. For the identification of sample unknowns, a data analysis workflow was developed and implemented using the DoPP tool. It utilizes a hierarchical classification tree that integrates three machine learning methods, namely, random forest, k-nearest neighbors, and support vector machine, all of which were fused using posterior probabilities. The results show accuracies of 98 and 99% for 10-fold cross-validation and external validation, respectively, which make the classification model suitable for identity prediction of real samples.

Rapid discrimination of the authenticity and geographical origin of bear bile powder using stable isotope ratio and elemental analysis.

Bear bile powder (BBP) is one of the most famous traditional Chinese medicines derived from animals. It has a long history of medicinal use and is widely used in the treatment of hepatobiliary and ophthalmic diseases. Due to its similar morphological characterizations and chemical composition compared with other bile powders, it is difficult to accurately identify its authenticity. In addition, there are very few methods that could analyze the geographical origins of BBP. In this study, elemental analysis isotope ratio mass spectrometry (EA-IRMS) and inductively coupled plasma mass spectrometry (ICP-MS) were used to determine stable isotope ratios and elemental contents, respectively. Combined these variables with chemometrics, the discrimination models were established successfully for identifying the authenticity and geographical origins of BBP. Meanwhile, the discrimination markers were identified by calculating the variable importance for the projection (VIP) value of each variable. A total of 13 discrimination markers (δ13C, δ15N, C, Li, Mg, K, Ca, Cr, Ni, Zn, As, Se, and Sr) were used to further establish the fingerprint of BBP. According to similarity analysis, the authenticity and geographical origins of BBP could be identified without chemometrics. In conclusion, the present study established a reliable method for authenticity identification and origin traceability of BBP, which will provide references for the quality control of bile medicines.

Application of Density Measurements for Discrimination and Evaluation of Chemical Composition of Different Types of Mechanically Separated Meat (MSM).

At present, the problem of identifying and controlling different types of Mechanically Separated Meat (MSM) is a very important practical issue in the meat industry. To address this challenge, the authors propose a new, analytical method for the discrimination and characterization of MSM that uses density measurements. The method proposed by the authors, in contrast to the analytical methods existing so far, is rapid, non-destructive, relatively simple and can be computerized. The density measurements of meat samples were conducted with a modified pycnometric method. Statistically significant (p&lt;0.01) differences were found in the evaluated mean values of density for all investigated types of meat. Subsequently, the density measurements were correlated with the physicochemical properties of meat samples. A high correlation coefficient was found between the density of meat samples and the content of protein, sodium and fat. The authors have proven that density measurements allow for rapid discrimination of various types of MSM, and can also be effectively used to determine the chemical composition of MSM samples, e.g., the content of protein, fat and sodium.

Rapid discrimination of recycled and virgin poly(ethylene terephthalate) based on non-targeted screening of semi-volatile organic compounds using a novel method of DSI/GC×GC-Q-TOF-MS coupled with various chemometrics

Increasing interest has been given to the use of recycled poly(ethylene terephthalate) (PET) as food contact materials. However, the use of recycled PET without decontamination in food packages causes serious safety hazards for consumers, thus representing a major limit hurdling the recycling and reuse of PET in many countries. Herein, a feasible study was employed for the discrimination of 105 total types of virgin and recycled PET samples based on 267 semi-volatile organic compounds (SVOCs) tentatively identified by direct sample introduction/comprehensive two-dimensional gas chromatography and quadrupole time-of-flight mass spectrometry (DSI/GC×GC-Q-TOF-MS) coupled with various chemometrics. 100% prediction accuracy was accomplished using orthogonal partial least squares discrimination analysis (OPLS-DA), and principal component analysis (PCA) combined with nonparametric tests. Cross-discrimination based on misclassified samples with various chemometrics enabled identifying large sample sizes and improving prediction accuracy. The possible origins of the markers containing 46 substances could be food, medicine, cosmetics, pesticides, fuel, plastic and industrial sources, where most of them are highly toxic chemicals, indicative of the urgent requirement of employing closed-loop recycling and sorting of plastic wastes. More importantly, our strategy could also act as a basis for discriminating against other plastics, making it promising as a novel, efficient and versatile approach for sorting of plastic wastes. Finally, this report also demonstrates the combination of various chemometrics and chromatography tool is reliable and powerful to effectively address PET adulteration, thereby facilitating food contact uses of rPET bottles, which is also beneficial for the health and safety of consumers.

Rapid discrimination of the native medicinal plant Adenostemma lavenia from its adulterants using PCR-RFLP.

In Taiwan, the aerial part of Adenostemma lavenia (Al) is used in the form of herbal tea or in a folk remedy primarily to mitigate inflammatory conditions in the lungs and liver. Due to the excellent health benefits of Al against inflammation, it has become increasingly crucial and in great demand during the COVID-19 pandemic. However, Al has been found to be adulterated with Wedelia biflora, Sigesbeckia orientalis, and/or Wedelia chinensis because of similarities in appearance and vernacular names. This study aimed to develop a PCR-RFLP DNA molecular method for the authentication of Al. The restriction enzyme BsrI was used according to the sequencing and alignment results of PCR products in the ITS2 regions of Al and its adulterants. Gel electrophoresis resulted in the clear separation of Al and its adulterants into two distinct categories. In conclusion, the PCR-RFLP authentication method developed herein provides an easy, rapid, and accurate method to distinguish Al from its adulterants to assure user health and safety.