An Integrated Paper Microfluidic Device Based on Isothermal Amplification for Simple Sample-to-Answer Detection of Campylobacter jejuni.

Campylobacter jejuni is recognized as the most common species in the genus Campylobacter that causes foodborne diseases. The main reservoirs harboring C. jejuni are poultry products, which are associated with most illnesses, creating a demand for effective detection methods to achieve point-of-need diagnostics. We developed an easy-to-use, hybrid paper/polymer-based microfluidic device that integrates paper-based DNA extraction, isothermal nucleic acid amplification, and lateral flow detection. Overall, the recombinase polymerase amplification (RPA) reaction was completed in 20 min and demonstrated 100% specificity to C. jejuni, including 2 reference strains and 6 wild strains isolated from the agroecosystem, 9 other Campylobacter subspecies strains, and 11 non-Campylobacter strains. The limit of detection (LOD) was 46 CFU/mL with DNA extracted on the cellulose paper. The sensitivity was reduced to 460 CFU/mL on the integrated hybrid paper/polymer-based microfluidic device. This device could detect C. jejuni spiked at concentrations ranging from 101 to 102 CFU/g in chicken meat after an enrichment of 5 to 10 h. For C. jejuni levels of >102 CFU/g, it managed to confirm positive results immediately, without bacterial enrichment. RPA reagents and primers remained stable on the paper platform at 22°C for 12 h. After lyophilization and storage on paper, the RPA reaction showed consistent sensitivity for 3 days, and the LOD was reduced to 103 CFU/mL when storage was extended to 25 days. The use of this hybrid paper/polymer-based microfluidic device enabled detection of Campylobacter in foods with high specificity and sensitivity, demonstrating its potential as a reliable point-of-need diagnostic platform for on-site conditions due to its low cost, portability, and simplicity. IMPORTANCE The global health and economic burden of Campylobacter prompts the development of novel detection techniques that can be implemented in resource-limited and on-site settings. This study described point-of-need identification of C. jejuni using a hybrid paper/polymer-based microfluidic device that is easy to operate. This device had high specificity and sensitivity toward C. jejuni and significantly reduced the total analysis time compared to conventional culture-based methods. Nucleic acid extraction was simplified from intensive pipetting to a paper dipstick, making it more convenient for use in the field as a promising tool for future routine surveillance and outbreak investigation.

Polyethersulfone-Based Microfluidic Device Integrated with DNA Extraction on Paper and Recombinase Polymerase Amplification for the Detection of Salmonella enterica.

Rising consumption, large-scale production, and widespread distribution have been accompanied by an increase in the number of Salmonella infections reported to implicate contaminated food products. We developed a portable origami microfluidic device that enabled rapid detection of S. enterica from sample preparation to end-point detection, including nucleic acid extraction on paper dipstick without pipetting, nucleic acid amplification using isothermal recombinase polymerase amplification (RPA), and lateral flow assay for results readout. We also explored the feasibility of the polyethersulfone (PES) membrane as a new reaction matrix against the widely used chromatography paper to optimize nucleic acid amplification. Nucleic acid amplification was achieved within 20 min and demonstrated 100% specificity to S. enterica. The limit of detection of this PES-based microfluidic device was 260 CFU/mL and equivalent to RPA reaction in tube. A chromatography paper-based microfluidic device was found 1-log less in sensitivity for Salmonella detection compared to the use of PES. This PES-based microfluidic device could detect S. enterica in lettuce, chicken breast, and milk at concentrations of 6 CFU/g, 9 CFU/g, and 58 CFU/mL, respectively, after 6 h enrichment. PES has shown high compatibility to isothermal nucleic acid amplification and great potential to be implemented as an integrated sample-to-answer microfluidic device for the detection of pathogens in various food commodities.

Chlorella sorokiniana FK-montmorillonite interaction enhanced remediation of heavy metals in tailings.

Non-ferrous metal mining activities are known to cause ecological irreversible damage in the tailings and surrounding areas as well as heavy metal (HM) contamination. The enhancement of Chlorella-montmorillonite interaction on the remediation of HM contaminated tailings was verified from the lab to the tailings in Daye City, Hubei Province, China. The results showed a positive correlation between the quantity of montmorillonite and the transformation of Pb and Cu into residual and carbonate-binding states, which resulted in a considerable decrease in the leaching ratio. The buildup of tailings fertility throughout this process benefited from montmorillonite's ability to buffer environmental changes and store water. This further offers a required environmental foundation for the rebuilding of microbial community and the growth of herbaceous plants. The structural equation model demonstrated that the interaction between Chlorella and montmorillonite directly affected the stability of HM, and that this interaction also had an impact on the accumulation of organic carbon, total nitrogen, and available phosphorus, which improved the immobilization of Pb, Cu, Cd, and Zn. This work made the first attempt to apply Chlorella-montmorillonite composite to in-situ tailings remediation, and proposed that the combination of inorganic clay minerals and organic microorganisms was an eco-friendly, long-lasting, and efficient method for immobilizing multiple-HMs in mining areas.

Dermal Sensory Regenerative Peripheral Nerve Interface for Reestablishing Sensory Nerve Feedback in Peripheral Afferents in the Rat.

BACKGROUND: Without meaningful, intuitive sensory feedback, even the most advanced myoelectric devices require significant cognitive demand to control. The dermal sensory regenerative peripheral nerve interface (DS-RPNI) is a biological interface designed to establish high-fidelity sensory feedback from prosthetic limbs. METHODS: DS-RPNIs were constructed in rats by securing fascicles of residual sensory peripheral nerves into autologous dermal grafts, with the objectives of confirming regeneration of sensory afferents within DS-RPNIs and establishing the reliability of afferent neural response generation with either mechanical or electrical stimulation. RESULTS: Two months after implantation, DS-RPNIs were healthy and displayed well-vascularized dermis with organized axonal collaterals throughout and no evidence of neuroma. Electrophysiologic signals were recorded proximal from DS-RPNI's sural nerve in response to both mechanical and electrical stimuli and compared with (1) full-thickness skin, (2) deepithelialized skin, and (3) transected sural nerves without DS-RPNI. Mechanical indentation of DS-RPNIs evoked compound sensory nerve action potentials (CSNAPs) that were like those evoked during indentation of full-thickness skin. CSNAP firing rates and waveform amplitudes increased in a graded fashion with increased mechanical indentation. Electrical stimuli delivered to DS-RPNIs reliably elicited CSNAPs at low current thresholds, and CSNAPs gradually increased in amplitude with increasing stimulation current. CONCLUSIONS: These findings suggest that afferent nerve fibers successfully reinnervate DS-RPNIs, and that graded stimuli applied to DS-RPNIs produce proximal sensory afferent responses similar to those evoked from normal skin. This confirmation of graded afferent signal transduction through DS-RPNI neural interfaces validate DS-RPNI's potential role of facilitating sensation in human-machine interfacing. CLINICAL RELEVANCE STATEMENT: The DS-RPNI is a novel biotic-abiotic neural interface that allows for transduction of sensory stimuli into neural signals. It is expected to advance the restoration of natural sensation and development of sensorimotor control in prosthetics.

Identifying Risk Factors for Recurrence After Cubital Tunnel Release.

PURPOSE: This study investigated specific risk factors for recurrent surgery of ulnar nerve entrapment (ie, ipsilateral clinical symptoms within 5 years after initial cubital tunnel release [CuTR]) in a large cohort. We hypothesized that recurrence is associated with lifestyle variables (eg, smoking, drinking alcohol, a high body mass index [BMI]) or comorbidities). METHODS: A retrospective cohort study was performed using the Current Procedural Terminology codes for all patients who underwent CuTR between January 2012 and November 2018. Demographic data, including sex, age, weight, height, BMI, comorbidities, smoking, and alcohol consumption, were collected. The primary outcome was the need for revision surgery after initial CuTR. Univariate and multivariate analyses were performed to identify potential risk factors for revision surgery. RESULTS: Of the 678 patients who underwent CuTR, 120 patients (18%) needed revision surgery within 5 years. Sixty-six patients required subfascial transposition (55%) and 47 patients (39%) received in situ releases. Also, sex, BMI, smoking, alcohol consumption, and comorbidities (except for spinal disc herniation) were similar between the primary and revision subgroup. Age at first occurrence was significantly lower in the revision group (48 years for revision vs 52 years for primary surgery). Moreover, cervical spinal disc herniation was associated with revision surgery (13% vs 6% in the primary group). CONCLUSIONS: Age and medical history of cervical spinal disc herniation are associated with an increased risk of revision surgery. More importantly, BMI, smoking, alcohol consumption, and other comorbidities are not associated with increased risk of revision surgery within our sample. TYPE OF STUDY/LEVEL OF EVIDENCE: Prognostic IV.

Enhanced Cd(II) biomineralization induced by microalgae after cultivating modification in high-phosphorus culture.

In this study, high-phosphorus beared microalgae was prepared by cultivating modification in high-phosphorus culture, and used for the enhanced Cd(II) biomineralization in soil. Batch experiment results showed that Chlorella sorokiniana FK was modified successfully in highly phosphate culture. Both intracellular P (Poly-P, 29.7 mg/kg) and surface P (phosphoryl based functional groups, 3.7 mol/kg) were greatly enhanced, and the Cd(II) removal capacity surged to 45.98 mg/g at equilibrium in the Langmuir simulation. The EXAFS analysis indicated that Cd tended to form a more stable bidentate complex (RPO4)2Cd when bounding with phosphate groups on the surface of the high-phosphorus microalgae. Moreover, high-phosphorus beared microalgae not only had higher immobilization amount of Cd(II), but also promoted immobilized Cd from adsorbed state to mineralized state. After high-phosphate cultured, increased density of P-related groups provided more adsorption sites, while the decomposition of intracellular Poly-P released phosphate ions into cell surface microenvironment, which combined and promoted the formation of Cd3(PO4)2/Cd(H2PO4)2 on cell surface. Cd-contaminated soil remediation experiments applying high-surface-phosphate beared microalgae further showed that more Cd stabilized as a residue fraction within 49 days. This study proposes that the high-phosphate culture strategy is a good way to improve the immobilization of heavy metals in soil induced by microorganisms.

Machine-Learning-Assisted Design of Highly Tough Thermosetting Polymers.

Despite advances in machine learning for accurately predicting material properties, forecasting the performance of thermosetting polymers remains a challenge due to the sparsity of historical experimental data and their complicated crosslinked structures. We proposed a machine-learning-assisted materials genome approach (MGA) for rapidly designing novel epoxy thermosets with excellent mechanical properties (high tensile moduli, high tensile strength, and high toughness) through high-throughput screening in a vast chemical space. Machine-learning models were established by combining attention- and gate-augmented graph convolutional networks, multilayer perceptrons, classical gel theory, and transfer learning from small molecules to polymers. Proof-of-concept experiments were carried out, and the structures designed by the MGA were verified. Gene substructures affecting the modulus, strength, and toughness were also extracted, revealing the mechanisms of polymers with high mechanical properties. The developed strategy can be employed to design other thermosetting polymers efficiently.

Molecularly imprinted core-shell Au nanoparticles for 2,4-dichlorophenoxyacetic acid detection in milk using surface-enhanced Raman spectroscopy.

Surface-enhanced Raman spectroscopy (SERS) has been extensively investigated for rapid and sensitive detection of trace level chemical contaminants in foods. Lack of selectivity to the targeted molecules in food matrices and fairly poor spectral reproducibility remain the main challenges for practical SERS applications. Herein, an ingenious strategy was proposed to hybridize molecularly imprinted polymers (MIPs) with gold nanoparticles as the functional SERS substrate for selective separation and detection of 2,4-dichlorophenoxyacetic acid (2,4-D), a systemic herbicide that has acute toxicity and potential cancer risk. The core-shell AuNPs@MIPs nanoparticles were finely tailored by wrapping an ultrathin layer of MIPs shell on the surface of AuNPs, which allowed selectively separating and enriching 2,4-D to the near surface of AuNPs and ensured the enhancement of Raman scattering signal of the analyte. Embedding an internal standard (i.e., 4-aminothiophenol) inside AuNPs@MIPs for SERS spectral calibration improved the quantification accuracy for 2,4-D. Three-dimensional finite difference time domain (3D-FDTD) simulation demonstrated the maximal electric field enhancement presented in the gap between adjacent AuNPs@MIPs with the theoretical enhancement factor (EF) as high as 5.85 × 106. Chemometric models established using SERS spectra showed accurate differentiation and quantification results for 2,4-D in milk at various contamination levels with a limit of detection (LOD) of 0.011 µg/mL. Our approach to integrate MIPs with noble metallic nanoparticles has great potential for selective and quantitative detection of analytes using SERS for practical agri-food analysis.

JPA: Joint Metabolic Feature Extraction Increases the Depth of Chemical Coverage for LC-MS-Based Metabolomics and Exposomics.

Extracting metabolic features from liquid chromatography-mass spectrometry (LC-MS) data has been a long-standing bioinformatic challenge in untargeted metabolomics. Conventional feature extraction algorithms fail to recognize features with low signal intensities, poor chromatographic peak shapes, or those that do not fit the parameter settings. This problem also poses a challenge for MS-based exposome studies, as low-abundant metabolic or exposomic features cannot be automatically recognized from raw data. To address this data processing challenge, we developed an R package, JPA (short for Joint Metabolomic Data Processing and Annotation), to comprehensively extract metabolic features from raw LC-MS data. JPA performs feature extraction by combining a conventional peak picking algorithm and strategies for (1) recognizing features with bad peak shapes but that have tandem mass spectra (MS2) and (2) picking up features from a user-defined targeted list. The performance of JPA in global metabolomics was demonstrated using serial diluted urine samples, in which JPA was able to rescue an average of 25% of metabolic features that were missed by the conventional peak picking algorithm due to dilution. More importantly, the chromatographic peak shapes, analytical accuracy, and precision of the rescued metabolic features were all evaluated. Furthermore, owing to its sensitive feature extraction, JPA was able to achieve a limit of detection (LOD) that was up to thousands of folds lower when automatically processing metabolomics data of a serial diluted metabolite standard mixture analyzed in HILIC(-) and RP(+) modes. Finally, the performance of JPA in exposome research was validated using a mixture of 250 drugs and 255 pesticides at environmentally relevant levels. JPA detected an average of 2.3-fold more exposure compounds than conventional peak picking only.

Smart traceability for food safety.

Current food production faces a tremendous challenge due to the growing human population. The global population is estimated to reach 9 billion by 2050 with 70% more food being required. Safe food is an important dimension of food security, and food traceability across the supply chain is a key component of this. However, current food traceability systems are challenged by frequent occurrences of food safety incidents and food recalls that have damaged consumer confidence, caused huge economic loss, and put pressure on food safety agencies. This review focuses on smart food traceability that has the potential to significantly improve food safety in global food supply chains. The basic concepts and critical perspectives for various detection strategies for food safety are summarized, including portable detection devices, smart indicators and sensors integrated on food packages, and data-assisted whole-genome sequencing. In addition, new digital technologies, such as Internet-of-things (IoTs) and cloud computing, are discussed with the aim of providing readers with an overview of the exciting opportunities in smart food traceability systems.

Regenerative peripheral nerve interface free muscle graft mass and function.

BACKGROUND: Regenerative peripheral nerve interfaces (RPNIs) transduce neural signals to provide high-fidelity control of neuroprosthetic devices. Traditionally, rat RPNIs are constructed with ~150 mg of free skeletal muscle grafts. It is unknown whether larger free muscle grafts allow RPNIs to transduce greater signal. METHODS: RPNIs were constructed by securing skeletal muscle grafts of various masses (150, 300, 600, or 1200 mg) to the divided peroneal nerve. In the control group, the peroneal nerve was transected without repair. Endpoint assessments were conducted 3 mo postoperatively. RESULTS: Compound muscle action potentials (CMAPs), maximum tetanic isometric force, and specific muscle force were significantly higher for both the 150 and 300 mg RPNI groups compared to the 600 and 1200 mg RPNIs. Larger RPNI muscle groups contained central areas lacking regenerated muscle fibers. CONCLUSIONS: Electrical signaling and tissue viability are optimal in smaller as opposed to larger RPNI constructs in a rat model.

[A woman with a swollen upper arm]. / Een vrouw met een gezwollen bovenarm.

A 74-year-old female patient presented at the emergency department with a swollen upper arm after a CT-scan. X-ray showed extensive extravasation with iodinated contrast media. Extravasations of high volume or high osmolality can lead to severe tissue damage. Early recognition and treatment is important, since it could prevent further injury.

Rapid Pomegranate Juice Authentication Using a Simple Sample-to-Answer Hybrid Paper/Polymer-Based Lab-on-a-Chip Device.

As a super fruit, pomegranate and its juice have attracted increased consumer demands during the past decades. Given the high production cost and market price, adulteration of pomegranate juice is highly likely to occur. To authenticate pomegranate juice and avoid the addition of cheaper fruit juices, such as apple and grape, an analytical method based on loop-mediated isothermal amplification (LAMP) was developed. This LAMP-based authentication method achieved highly sensitive (i.e., 10 pg for pomegranate DNA and 100 pg for grape and apple DNA) and specific detection of pomegranate, apple, and grape DNA present in fresh fruit juice. To further simplify the overall analysis, a hybrid paper/polymer-based lab-on-a-chip (LOC) platform was designed to integrate DNA extraction, LAMP reaction, and LAMP result visualization onto a single device. This LOC device was able to detect 2 µL of fresh pomegranate juice and 5 µL of fresh apple and grape juice. Using a homemade portable heating device, the overall analysis could be completed in ∼1 h in an almost instrument-free setting. The cost for each authentication test is estimated to be ∼4 USD and the reusable homemade portable heating device is ∼15 USD. This LAMP-based simple sample-to-answer hybrid paper/polymer-based LOC device has high potential to be adopted by government laboratories and the food industry to rapidly and routinely authenticate pomegranate juice even in a resource-limited environment.

Untargeted volatile metabolomics using comprehensive two-dimensional gas chromatography-mass spectrometry - A solution for orange juice authentication.

Orange juice is one of the most consumed fruit juices worldwide and its adulteration has been a long-lasting concern. In this study, an untargeted volatile metabolomics using a comprehensive two-dimensional gas chromatography-quadrupole mass spectrometry (GC × GC-qMS) was developed to systematically authenticate orange juice. At least 405 citrus whole fruits were collected, belongs to 58 types of orange samples and 23 types of non-orange citrus. The fruit juices were prepared in the laboratory and analyzed using the comprehensive GC × GC-qMS instrument. After optimizing the instrumental settings, this novel method was able to identified ~250 volatiles in each juice sample, covering a variety types of hydrocarbons, esters, alcohols, aldehydes, ketones and others. Combining with unsupervised principal component analysis and supervised partial least squares-discriminant analysis , this novel analytical tool was able to authenticate orange juice from a broad perspectives with a high accuracy in the cross-validation model: 1) differentiating orange juice from non-orange citrus juice (99% accuracy), 2) recognizing orange harvesting years (100% accuracy) and geographical origins (96% accuracy), and 3) distinguishing original pure orange juice from the reconstituted juice (94% accuracy). Key volatile metabolites associated with different categories of samples were also identified after thorough investigation of the loading values of the classification models. These metabolites have high potential to be used as food-markers to design targeted analytical methods for orange juice authentication. This novel comprehensive GC × GC-qMS-based method is ideal for governmental laboratories and the food industry to routinely authenticate orange juice.

Identification of camel species in food products by a polymerase chain reaction-lateral flow immunoassay.

With an increased demand for camel meat, camel meat-related food products are susceptible to food fraud. To effectively authenticate camel-containing foods, a novel analytical technique based on polymerase chain reaction (PCR)-lateral flow immunoassay (LFI) was developed. The camel-specific PCR primers were designed to target at the mitochondrial COI gene. Both of the in silico and in vitro tests confirmed that the PCR-LFI was specific. A limit of detection of 0.1% w/w of camel meat in beef was achieved for both the raw and cooked (i.e. boiling and deep frying) meat samples. This novel method was used to authenticate 20 processed camel-meat products purchased from local grocery stores in China and online. Two products purchased online were identified as containing no camel meat. Overall, this novel PCR-LFI method is ideal for governmental laboratories to rapidly authenticate camel-meat containing food products.

Development of paper-based microfluidic device for the determination of nitrite in meat.

This study employed the use of a microfluidic paper-based analytical device (µPAD) to determine the concentration of nitrite in pork and enhanced the limit of detection by analyzing the coffee-ring effect. The µPAD was fabricated by designing and embedding wax channels onto the cellulose-based filter paper through printing and subjecting the paper to heat treatment to allow wax penetration. Nitrite concentration was determined by monitoring the colorimetric reaction that occurred between nitrite and the added Griess reagent. The limit of detection of this device for nitrite in pork was determined to be 19.2 mg kg-1 by analyzing the inner-chamber reaction, while it could be as low as 1.1 mg kg-1 if the coffee-ring region was analyzed. The overall analysis could be completed within 15 min. This µPAD-based method has potential applications to routinely screen the nitrite concentration of meat products and ensure food safety and consumer health.

The Coix Genome Provides Insights into Panicoideae Evolution and Papery Hull Domestication.

Coix is a grass crop domesticated as early as the Neolithic era. It is still widely cultivated for both highly nutritional food and medicinal use. However, the genetic study and breeding of this crop are hindered by the lack of a sequenced genome. Here, we report de novo sequencing and assembly of the 1619-Mb genome of Coix, and annotation of 75.39% repeats and 39 629 protein-coding genes. Comparative genomics analysis showed that Coix is more closely related to sorghum than maize, but intriguingly only Coix and maize had a recent genome duplication event, which was not detected in sorghum. We further constructed a genetic map and mapped several important traits, especially the strength of hull. Selection of papery hull (thin: easy dehulling) from the stony hull (thick: difficult dehulling) in wild progenitors was a key step in Coix domestication. The papery hull makes seed easier to process and germinate. Anatomic and global transcriptome analysis revealed that the papery hull is a result of inhibition of cell division and wall biogenesis. We also successfully demonstrated that seed hull pressure resistance is controlled by two major quantitative trait loci (QTLs), which are associated with hull thickness and color, respectively. The two QTLs were further fine mapped within intervals of 250 kb and 146 kb, respectively. These resources provide a platform for evolutionary studies and will facilitate molecular breeding of this important crop.

Enhancing Metabolome Coverage in Data-Dependent LC-MS/MS Analysis through an Integrated Feature Extraction Strategy.

In untargeted metabolomics, conventional data preprocessing software (e.g., XCMS, MZmine 2, MS-DIAL) are used extensively due to their high efficiency in metabolic feature extraction. However, these programs present limitations in recognizing low-abundance metabolic features, thus hindering complete metabolome coverage from the analysis. In this work, we explored the possibility of enhancing the metabolome coverage of data-dependent liquid chromatography-tandem mass spectrometry (LC-MS/MS) results by rescuing metabolic features that are missed by conventional software. To achieve this goal, we first categorized the metabolic features into four confidence levels based on their chromatographic peak shapes and the presence of corresponding MS/MS spectra. We then assessed the false positives and quantitative accuracy of the metabolic features that contain MS/MS spectra but are not recognized by conventional software. Our results indicate that these missed features contain valid and important metabolic information and should be integrated into the conventional metabolomics results. Thus, we developed a data-preprocessing pipeline to extract low-abundance metabolic features and integrate them with the results from conventional programs. This integrated feature extraction strategy was tested on a set of fecal metabolomic data retrieved from mice who have undergone normal diet vs high-fat diet treatments. In our test data set, the integrated feature extraction approach increased the number of significant features being extracted by 24.4% and identified five additional metabolites bearing critical biological meanings. Our results show that this integrated feature extraction strategy remarkably improves the metabolome coverage beyond that of conventional data preprocessing, therefore facilitating the confirmation of metabolites of interest and accomplishment of a higher success rate in de novo metabolite identification.

Rapid determination of atrazine in apple juice using molecularly imprinted polymers coupled with gold nanoparticles-colorimetric/SERS dual chemosensor.

Rapid and reliable determination of atrazine, a common chemical contaminant, in agri-foods is highly necessary. We reported a novel dual-chemosensor coupling, a separation [molecularly imprinted polymers (MIPs)], an instrumental-free detection [gold nanoparticles (AuNPs)-based colorimetric assay] and an instrument-based quantification [surface enhanced Raman spectroscopy (SERS)] method for high-throughput and sensitive determination of atrazine in apple juice. Used as the selective sorbent for the solid phase extraction, MIPs effectively extracted atrazine from apple juice with high recoveries (∼93%). AuNPs of different sizes (large; medium; and small) performed differently in the two analytical methods. Large-AuNPs provided the highest sensitivity in colorimetric analysis (<0.01 mg L-1), while medium-AuNPs achieved the lowest limit of detection (0.0012 mg L-1) and quantification (0.0040 mg L-1) in SERS analysis. With minor modifications, protocols for both analytical methods can rapidly detect and/or quantify atrazine in different food products complying with the Health Canada regulation (0.005 mg L-1).