Direct Labeling Research Articles

Advances in Biosensor Applications of Metal/Metal-Oxide Nanoscale Materials

Biosensing shows promise in detecting cancer, renal disease, and other illnesses. Depending on their transducing processes, varieties of biosensors can be divided into electrochemical, optical, piezoelectric, and thermal biosensors. Advancements in material production techniques, enzyme/protein designing, and immobilization/conjugation approaches can yield novel nanoparticles with further developed functionality. Research in cutting-edge biosensing with multifunctional nanomaterials, and the advancement of practical biochip plans utilizing nano-based sensing material, are of current interest. The miniaturization of electronic devices has enabled the growth of ultracompact, compassionate, rapid, and low-cost sensing technologies. Some sensors can recognize analytes at the molecule, particle, and single biological cell levels. Nanomaterial-based sensors, which can be used for biosensing quickly and precisely, can replace toxic materials in real-time diagnostics. Many metal-based NPs and nanocomposites are favorable for biosensing. Through direct and indirect labeling, metal-oxide NPs are extensively employed in detecting metabolic disorders, such as cancer, diabetes, and kidney-disease biomarkers based on electrochemical, optical, and magnetic readouts. The present review focused on recent developments across multiple biosensing modalities using metal/metal-oxide-based NPs; in particular, we highlighted the specific advancements of biosensing of key nanomaterials like ZnO, CeO2, and TiO2 and their applications in disease diagnostics and environmental monitoring. For example, ZnO-based biosensors recognize uric acid, glucose, cholesterol, dopamine, and DNA; TiO2 is utilized for SARS-CoV-19; and CeO2 for glucose detection.

Engineering a Novel NIR RNA-Specific Probe for Tracking Stress Granule Dynamics in Living Cells.

Real-time monitoring of the dynamics of cytosolic RNA-protein condensates, termed stress granules (SGs), is vital for understanding their biological roles in stress response and related disease treatment but is challenging due to the lack of simple and accurate methods. Compared with protein visualization that requires complex transfection procedures, direct RNA labeling offers an ideal alternative for tracking SG dynamics in living cells. Here, we propose a novel molecular design strategy to construct a near-infrared RNA-specific fluorescent probe (HQBT) for tracking SGs in living cells. The positively charged probe HQBT was designed to target the negative groove of RNA, and its binding affinity to RNA was significantly improved by adjusting the position of the nitrogen atom in the molecule. Furthermore, an additional hydroxyl group was introduced to achieve near-infrared emission and enhance the RNA-binding capability. HQBT can rapidly stain RNA within 5 s in living cells and showed performance superior to the commercial SYTO RNA-Select dye in terms of photostability and selectivity. Importantly, the reversible assembly and disassembly dynamics of SGs are successfully visualized in living cells using this simple and direct RNA-selective imaging probe.

A comparison and evaluation of strategies for bulk sequencing of mitogenomes from museum collections

Abstract Collecting mitochondrial genome sequences from museum collections has garnered increasing attention in recent years. Currently, several sequencing strategies have been proposed for this purpose, including direct DNA pooling, DNA labelling and mtDNA enrichment. It is important to understand the advantages and limitations of these methods before embarking on large‐scale sequencing efforts. However, there is currently no comprehensive comparison and evaluation of the performance of these sequencing methods. In this study, we evaluated the performance of four different strategies for sequencing mitogenomes by comparing reagent expense, experiment time, bioinformatics time, and the length and the base error rate of the obtained mitochondrial sequences. The four sequencing strategies mainly differ in: (1) whether to label the DNA of each specimen and (2) whether to perform mtDNA enrichment. To reduce experiment difficulty and expenses, we presented an ‘in‐situ’ DNA labelling protocol for cost‐effectively ligating barcode sequences to DNA samples and used PCR‐generated baits for mtDNA enrichment. The widely adopted ‘direct pooling’ sequencing strategy is the fastest but performs the worst among the four strategies. Of the 96 samples analysed, this approach yields averagely only 670 bp of mitochondrial sequences per sample. The most complicated sequencing strategy, which labels the DNA of each specimen and performs mtDNA enrichment, performs the best, producing mitogenome sequences of ~9.3 kb per sample. The sequencing accuracy is highly related to the sequencing depths of mtDNA but not the storage time of samples. We hope that our comparisons will assist researchers in selecting suitable strategies for large‐scale sequencing of mitogenomes from museum specimens, thereby advancing museomics.

Gold nanomaterials capped with bovine serum albumin for cell and extracellular vesicle imaging

Bovine serum albumin-capped gold nanoclusters (AuNC@BSA) are ionic, ultra-small, and eco-friendly nanomaterials that exhibit red fluorescence emission. Upon modification, these nanomaterials can serve as imaging probes with multimodal functionality. Owing to their nanoscale properties, AuNC@BSA-based nanomaterials can be readily endocytosed by cells for imaging. With the increasing interest in cell therapy, extracellular vesicles (EVs) have attracted considerable attention from researchers; however, effective methods for imaging EVs remain limited. Although several studies have explored imaging strategies for cells and EVs using compounds, nuclear pharmaceuticals, nanoparticles, or genetic constructs, the use of AuNC@BSA-based nanomaterials for labeling EVs and their parental cells has rarely been discussed, with even less attention paid to their multimodal potential. To address this gap, we utilized three types of AuNC@BSA-based derivatives: AuNC@BSA, AuNC@BSA-Gd, and AuNC@BSA-Gd-I. Our findings demonstrate that these derivatives can effectively label both cells and EVs using a simple direct labeling approach, which is particularly notable for EVs, as they typically require more complex labeling procedures. Furthermore, the multimodal potential of labeled cells and EVs was evaluated, revealing their capabilities for multimodal imaging. In summary, this study presents an effective strategy for labeling EVs and their parental cells using multimodal nanomaterials. These findings will contribute to accelerating the development of drug delivery systems, cell- and EV-based therapies, and advanced imaging strategies.

‘We are all children of war’: a qualitative inquiry into parenting following adolescents’ recent traumatic exposure in a multiple crisis setting in Beirut, Lebanon

ABSTRACT Background: Strong familial bonds are crucial to building resilience among youth exposed to traumatic events in socially adverse environments. Exploring parental experiences in the aftermath of adolescents’ traumatic exposure in these settings would help tailor early interventions. Objective: We qualitatively explored experiences and perceived needs among parents of teenagers aged 11–16 years who were exposed in the last three months to a potentially traumatic event in Beirut, Lebanon. Method: We purposively sampled 28 parents of 24 adolescents meeting the inclusion criteria. Semi-structured interviews were conducted, and thematic analysis was applied combined with a grounded theory approach. Results: The most frequent traumatic event was direct exposure to the violent clashes that happened in Beirut on 14 October 2021. Parents identified that the recent event exacerbated pre-existing mental health difficulties caused by cumulative stress. They were reminded of their own war experiences and tended to reject the ‘sick role’ associated with trauma. A majority of participants viewed resilience as a fixed trait characteristic of the Lebanese and avoided communication with their children about traumatic memories, while a significant minority criticised resilience as a myth that added pressure on them and had more open communication about trauma. Parenting styles oscillated between controlling behaviours, warmth, and avoidance, which impacted the family dynamic. Despite adversity, most parents tried to cope through social connectedness, humour, and living day by day. Conclusions: Our findings hold implications for contextual adaptations of early posttraumatic interventions aimed at strengthening family support, such as addressing parental mental health; increasing awareness among first-line responders on parents’ potential representations of trauma and resilience; addressing the issue of controlling parenting; and including a component in psychoeducation on traumatic stress that validates the impact of daily stressors on mental health while avoiding direct labelling. Further research is needed to validate the impact of these domains.

Comparative Kidney Uptake of Nanobody-Based PET Tracers Labeled with Various Fluorine-18-Labeled Prosthetic Groups.

Nanobodies, or single-domain antibody fragments, are promising candidates for molecular imaging due to their small size, rapid tissue penetration, and high target specificity. However, a significant challenge in their use is high renal uptake and retention, which can limit the therapeutic efficacy and complicate image interpretation. This study compares five different fluorine-18-labeled prosthetic groups for nanobodies, aiming to optimize pharmacokinetics and minimize kidney retention while maintaining tumor targeting. Using an epidermal growth factor receptor (EGFR) targeting nanobody as a model, two labeling approaches were evaluated; direct labeling of RESCA (with and without polyethylene glycol (PEG))-conjugated nanobody using Al[18F]F and indirect labeling using ([18F]F-fluoropyridine ([18F]F-FPy)-based prosthetic groups (site-specific and nonsite-specific). Labeled nanobodies were characterized in vitro for binding affinity and cell uptake with in vivo behavior assessed in EGFR + A431 tumor-bearing mice using PET imaging and biodistribution studies. Labeling with Al[18F]F showed high renal retention, which was partially mitigated by PEGylation. However, PEGylation also led to a decreased tumor uptake, particularly with longer PEG chains. Labeling using [18F]F-FPy prosthetic groups exhibited the most favorable pharmacokinetics, with rapid renal clearance and minimal kidney retention while maintaining high tumor uptake. These constructs showed excellent tumor-to-background contrast as early as 1 h postinjection. The study confirms that the selection of the prosthetic group significantly impacts the in vivo behavior of nanobodies, particularly regarding kidney accumulation. [18F]F-FPy-based prosthetic groups show the most promising results, with high tumor and minimal kidney uptake. Robust production of [18F]F-FPy on Sep-Pak is adaptable to clinical translation. Moreover, the potential substitution of 18F with therapeutic radioisotopes such as 131I or 211At could expand the application of these nanobodies from diagnostics to targeted radionuclide therapy while maintaining a low kidney exposure. These findings have important implications for optimizing nanobody-based radiopharmaceuticals for molecular imaging and targeted radionuclide therapy.

Copper-Mediated Cross-Coupling Selective for Pyroglutamate Post-Translational Modifications.

Pyroglutamate is a cyclic N-terminal post-translational modification that occurs in both proteins and peptide hormones. The prevalence and biological roles of pyroglutamate are little understood, in part due to limited tools to identify, quantify, and manipulate its pyrrolidinone structure. Selective modification of pyroglutamate residues in complex polypeptides may provide unique tools to better understand its biological roles and to allow late-stage diversification of biologically active pyroglutamate-containing sequences. This work describes a copper-catalyzed N-H cross-coupling of unprotected peptides that is selective for N-terminal pyroglutamate residues. The reaction is operationally simple under mild conditions and tolerates all canonical residues. Mechanistic studies point to a key role for a multidentate copper-binding mode of the extended polypeptide structure in delivering the observed reactivity. The reaction allows for direct labeling and identification of a pyroglutamate hormone present in porcine intestinal extracts.

Farm characteristics determine why a large share of organically produced wine is not labelled as organic

Abstract Organic agricultural production is increasing globally and is of high policy relevance, particularly in Europe. Various measures incentivize farmers to adopt organic practices, such as direct payments and labelling. We here address a rarely considered aspect of organic production, that not all organic producers in Europe opt for organic labelling for their products at the point of sale. We investigate the discrepancy between organic production and labelling in Swiss viticulture. Out of 115 grapevine growers who adhere to organic principles in production, 43.5% do not use organic labelling when marketing their wines. We find that especially farms using alternative labelling strategies (e.g. for fungus-resistant varieties), smaller farms and farms less specialized in viticulture to be more likely to forgo organic labelling. We draw conclusions for policy and science. For example, our findings show that there may be, for some crops, more organic products on shelves than indicated from sales statistics of organically labelled products. The use of statistics that indicate the share of sales of organic products for specific products and food sales at large may thus be misleading.

Direct Labeling of Gold Nanoparticles with Iodine-131 for Tumor Radionuclide Therapy.

Gold nanoparticles (Au NPs) are widely used as versatile templates to develop multifunctional nanosystems for disease diagnosis and treatment. Iodine can bind to gold via chemisorption, making this a simple method for labeling Au NPs with radioactive iodine. However, the evaluation of tumor radionuclide therapy is insufficient. In this study, we investigated the feasibility of 131I-adsorbed Au NPs as novel nanoprobes for tumor radionuclide therapy. Radiolabeling was performed by mixing Au NPs and 131I, and the radiochemical purity (RCP) and in vitro stability of 131I-adsorbed Au NPs were analyzed under different conditions, including various temperatures, pH values, and 131I concentrations. The tumor accumulation and therapeutic potential of 131I-adsorbed Au NPs were assessed using a subcutaneous tumor model after intratumoral injection. The data showed that the chemisorption of the Au NPs onto 131I was instant, specific, and quantitative. The 131I-adsorbed Au NPs exhibited high in vitro stability in different media, distinct inhibitory effects on tumor cells in vitro, good retention ability, and therapeutic effects after intratumoral injection into tumor-bearing mice in vivo. Our work demonstrates that chemisorption of Au NPs and radioiodine has great potential as a strategy for constructing various nanosystems for theranostic applications.

Comparative Characteristics of Immunochromatographic Test Systems for Tylosin Antibiotic in Meat Products.

Tylosin (TYL) is a macrolide antibiotic widely used in animal husbandry. Due to associated health risks, there is a demand for sensitive methods for mass screening of TYL in products of animal origin. This article describes the development of lateral flow immunoassays (LFIAs) for TYL detection using direct (anti-TYL antibodies conjugated with nanoparticles) and indirect antibody labeling (anti-species antibodies conjugated with nanoparticles and combined with native anti-TYL antibodies). The choice of LFIA conditions, such as concentrations of hapten-protein conjugates, specific antibodies, and gold nanoparticle (GNP) conjugates with antibodies, as well as incubation time of reagents and the concentration of detergent in the sample buffer, is presented. The achieved limits of TYL detection using LFIAs with indirect labeling were 0.8 ng/mL (visual) and 0.07 ng/mL (instrumental), compared to 4 ng/mL (visual) and 0.4 ng/mL (instrumental) for the case of direct labeling. The sensitivity of the LFIA using the indirect format was up to seven times higher, allowing the determination of the target analyte at low concentrations. TYL detection in ground meat using LFIA with indirect antibody labeling ranged from 76-119%.

SPOT: spatial proteomics through on-site tissue-protein-labeling

BackgroundSpatial proteomics seeks to understand the spatial organization of proteins in tissues or at different subcellular localization in their native environment. However, capturing the spatial organization of proteins is challenging. Here, we present an innovative approach termed Spatial Proteomics through On-site Tissue-protein-labeling (SPOT), which combines the direct labeling of tissue proteins in situ on a slide and quantitative mass spectrometry for the profiling of spatially-resolved proteomics.Materials and MethodsEfficacy of direct TMT labeling was investigated using seven types of sagittal mouse brain slides, including frozen tissues without staining, formalin-fixed paraffin-embedded (FFPE) tissues without staining, deparaffinized FFPE tissues, deparaffinized and decrosslinked FFPE tissues, and tissues with hematoxylin & eosin (H&E) staining, hematoxylin (H) staining, eosin (E) staining. The ability of SPOT to profile proteomes at a spatial resolution was further evaluated on a horizontal mouse brain slide with direct TMT labeling at eight different mouse brain regions. Finally, SPOT was applied to human prostate cancer tissues as well as a tissue microarray (TMA), where TMT tags were meticulously applied to confined regions based on the pathological annotations. After on-site direct tissue-protein-labeling, tissues were scraped off the slides and subject to standard TMT-based quantitative proteomics analysis.ResultsTissue proteins on different types of mouse brain slides could be directly labeled with TMT tags. Moreover, the versatility of our direct-labeling approach extended to discerning specific mouse brain regions based on quantitative outcomes. The SPOT was further applied on both frozen tissues on slides and FFPE tissues on TMAs from prostate cancer tissues, where a distinct proteomic profile was observed among the regions with different Gleason scores.ConclusionsSPOT is a robust and versatile technique that allows comprehensive profiling of spatially-resolved proteomics across diverse types of tissue slides to advance our understanding of intricate molecular landscapes.

Graph-Based Semi-Supervised Learning with Bipartite Graph for Large-Scale Data and Prediction of Unseen Data

Recently, considerable attention has been directed toward graph-based semi-supervised learning (GSSL) as an effective approach for data labeling. Despite the progress achieved by current methodologies, several limitations persist. Firstly, many studies treat all samples equally in terms of weight and influence, disregarding the potential increased importance of samples near decision boundaries. Secondly, the detection of outlier-labeled data is crucial, as it can significantly impact model performance. Thirdly, existing models often struggle with predicting labels for unseen test data, restricting their utility in practical applications. Lastly, most graph-based algorithms rely on affinity matrices that capture pairwise similarities across all data points, thus limiting their scalability to large-scale databases. In this paper, we propose a novel GSSL algorithm tailored for large-scale databases, leveraging anchor points to mitigate the challenges posed by large affinity matrices. Additionally, our method enhances the influence of nodes near decision boundaries by assigning different weights based on their importance and using a mapping function from feature space to label space. Leveraging this mapping function enables direct label prediction for test samples without requiring iterative learning processes. Experimental evaluations on two extensive datasets (Norb and Covtype) demonstrate that our approach is scalable and outperforms existing GSSL methods in terms of performance metrics.

Sortase-Mediated Site-Specific Conjugation to Prepare Fluorine-18-Labeled Nanobodies.

Single-domain antibodies, or nanobodies (Nbs), are promising biomolecules for use in molecular imaging due to their excellent affinity, specificity, and fast clearance from the blood. Given their short blood half-life, pairing Nbs with short-lived imaging radioisotopes is desirable. Because fluorine-18 (18F) is routinely used for clinical imaging, it is an attractive radioisotope for Nbs. We report a novel sortase-based, site-specific 18F-labeling method applied to three nanobodies. Labeled nanobodies were synthesized either by a two-step indirect radiolabeling method in one pot or by a one-step direct labeling method using a sortase-mediated conjugation of either the radiolabeled chelator (H-GGGK((±)-Al[18F]FH3RESCA)-NH2) or the unlabeled chelator (H-GGGK((±)-H3RESCA)-NH2) followed by labeling with Al[18F]F, respectively. The overall radiochemical yields were 15-43% (n = 22, decay-corrected) in 70 min (indirect labeling) and 23-58% (n = 12, decay-corrected) in 50 min (direct labeling). The radiochemical purities of the labeled nanobodies prepared by both methods were >98% with a specific activity of 400-600 Ci/mmol (n = 22) for each of the three Nbs tested and exhibited excellent stability profiles under physiological conditions. This simple, site-specific, reproducible, and generalizable 18F-labeling method to prepare nanobodies (Nb-Al[18F]F-RESCA) or other low molecular weight biomolecules can easily be adopted in various settings for preclinical and clinical studies.

Cell Proliferation and Cytotoxicity Assays, The Fundamentals for Drug Discovery

Review Cell Proliferation and Cytotoxicity Assays, The Fundamentals for Drug Discovery Jingyi Niu†, Minai Li† and Ying Wang* State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Avenida da Universidade, Taipa, Macao 999078, China * Correspondence: emilyywang@um.edu.mo † These authors contributed equally to this work Received: 6 May 2024; Revised: 19 June 2024; Accepted: 21 June 2024; Published: 20 August 2024 Abstract: Cell proliferation and cytotoxicity assays are fundamental to drug discovery. This review summarizes prevalent methodologies for assessing cell proliferation and cytotoxicity, including direct cell count, metabolic activity, luminescent labeling, and tri-color viability imaging. The critical determinants that can significantly impact these assay outcomes, such as cellular doubling time, transitional states like quiescence and autophagy, cell cycle stages, metabolic enzyme functions, and genetic variability, are also explored. It is necessary to integrate the commonly used assays with additional analytical techniques to achieve precision in drug discovery. A multi-tiered approach that combines cellular assays with molecular analyses can improve screening processes, reduce false negatives, and increase confidence in the therapeutic potential of lead compounds.

Fast In Vitro Synthesis and Direct Labeling of Nanobodies for Prototyping in Microscopy Applications.

Small antigen binders, such as nanobodies, have become widely used in biomedical research and pharmaceutical development. However, the pipeline for the generation of functional conjugated probes and drugs from identified binders remains a major time-consuming bottleneck. Here, we developed a method for fast nanobody production and conjugation based on an in vitro synthesis platform. Our system allows for small batch synthesis of nanobodies with the inclusion of a noncanonical amino acid (NCAA). This NCAA can then be used for direct conjugation of molecules to the synthesized nanobody using click-chemistry, reducing the time from binder-encoding DNA to a conjugated probe tremendously. In this study, we conjugated a fluorescent dye to an anti-Green fluorescent protein (GFP) nanobody and attained a fully functional probe suitable for advanced super-resolution microscopy within a short time frame of 2 days. Our work illustrates that an in vitro synthesis platform in combination with click-chemistry can be successfully employed to produce conjugated small antigen binding probes. The fast production and conjugation, combined with the possibility for parallelization as well as precise analysis by microscopy, forms an excellent platform for nanobody prototyping. The here-illustrated method can be used for quick selection and benchmarking of obtained nanobody sequences/clones, e. g., from a phage-display, for use as conjugated small-molecule carriers. This procedure can accelerate the bioengineering of nanobodies for research and pharmaceutical applications.

Exploring the Correlation between Emojis and Mood Expression in Thai Twitter Discourse

Mood, a long-lasting affective state detached from specific stimuli, plays an important role in behavior. Although sentiment analysis and emotion classification have garnered attention, research on mood classification remains in its early stages. This study adopts a two-dimensional structure of affect, comprising ”pleasantness” and ”activation,” to classify mood patterns. Emojis, graphic symbols representing emotions and concepts, are widely used in computer-mediated communication. Unlike previous studies that consider emojis as direct labels for emotion or sentiment, this work uses a pre-trained large language model which integrates both text and emojis to develop a mood classification model. Our contributions are three-fold. First, we annotate 10,000 Thai tweets with mood to train the models and release the dataset to the public. Second, we show that emojis contribute to determining mood to a lesser extent than text, far from mapping directly to mood. Third, through the application of the trained model, we observe the correlation of moods during the Thai political turmoil of 2019-2020 on Thai Twitter and find a significant correlation. These moods closely reflect the news events and reveal one side of Thai public opinion during the turmoil.

Role of palmitoylation on the neuronal glycine transporter GlyT2.

The neuronal glycine transporter GlyT2 removes glycine from the synaptic cleft through active Na+, Cl-, and glycine cotransport contributing to the termination of the glycinergic signal as well as supplying substrate to the presynaptic terminal for the maintenance of the neurotransmitter content in synaptic vesicles. Patients with mutations in the human GlyT2 gene (SLC6A5), develop hyperekplexia or startle disease (OMIM 149400), characterized by hypertonia and exaggerated startle responses to trivial stimuli that may have lethal consequences in the neonates as a result of apnea episodes. Post-translational modifications in cysteine residues of GlyT2 are an aspect of structural interest we analyzed. Our study is compatible with a reversible and short-lived S-acylation in spinal cord membranes, detectable by biochemical and proteomics methods (acyl-Rac binding and IP-ABE) confirmed with positive and negative controls (palmitoylated and non-palmitoylated proteins). According to a short-lived modification, direct labeling using click chemistry was faint but mostly consistent. We have analyzed the physiological properties of a GlyT2 mutant lacking the cysteines with high prediction of palmitoylation and the mutant is less prone to be included in lipid rafts, an effect also observed upon treatment with the palmitoylation inhibitor 2-bromopalmitate. This work demonstrates there are determinants of lipid raft inclusion associated with the GlyT2 mutated cysteines, which are presumably modified by palmitoylation.

Towards Domain-Aware Stable Meta Learning for Out-of-Distribution Generalization

Deep learning models are often trained on datasets that are limited in size and distribution, which may not fully represent the entire range of data encountered in practice. Thus, making deep learning models generalize to out-of-distribution data has received a significant amount of attention in recent studies due to the critical importance of this ability in real-world applications. Meta learning as an effective knowledge transfer paradigm, which learns a base model with high generalization ability to adapt to new data distributions by minimizing domain shifts across tasks during meta-training. However, most existing meta learning methods assume that the base model can access the labels of different domains, and this assumption is demanding in many real application scenarios. In addition, these methods focus on narrowing data-level domain shifts, while ignoring task-level domain shifts, which may lead to inadequate or even negative transfer. Inspired by human learners who use induction to learn and master new tasks, we propose a novel domain-aware meta learning framework for out-of-distribution generalization, termed SMLG. This framework enables the base model to generalize effectively to unseen domains without relying on domain-specific labels. Specifically, we develop a domain-aware transformation module to obtain meta representation and pseudo domain labels. As a result, the base model can be trained robustly without the need for direct domain label input. Furthermore, to investigate the impact of domain shifts at different levels, we introduce a joint loss function that combines cross-entropy with a domain alignment constraint. Extensive experiments on benchmark datasets demonstrate the efficacy of our framework.

Folate and synthetic folic acid content in Canadian fortified foods two decades after mandatory fortification.

In 1998, Health Canada mandated folic acid fortification of white flour and enriched grain products to prevent neural tube defects. At the time, neither the Canadian Nutrient File (CNF) nor product labels reflected the actual folate content of foods. We aimed to assess if 20 years post-fortification, the CNF values for total folate and synthetic folic acid accurately reflect amounts determined by direct analysis. Using the 2001 Food Expenditure Survey and ACNielsen Company data, we identified 10-15 of the most purchased fortified foods across seven food categories in Canada. Total folate concentrations were determined by tri-enzyme digestion and microbial assay. Folic acid concentrations were determined using liquid chromatography-tandem mass spectrometry. Except for "cooked pastas", mean total folate content of foods (n=89) were significantly higher than CNF values across categories (p<0.05), reflecting 167% ± 54% of CNF values. Similarly, mean folic acid content of foods was higher than CNF values for all categories except "cooked pastas" (p<0.05), with a mean of 188% ± 94% of CNF values; the latter CNF values included uncooked pasta. In sum, 20 years post-fortification, and 10 years since the last direct measurement, CNF and product label values still underestimate actual total folate and the folic acid content of foods. These findings emphasize that dietary estimates established using the CNF may significantly underestimate actual intakes and thus caution should be exercised when interpreting estimates of nutritional adequacy based on these values.

Optimal dispatch of integrated electricity and heating systems considering the quality-quantity regulation of heating systems to promote renewable energy consumption

The integrated electricity and heating system (IEHS) can improve energy efficiency and promote renewable energy consumption. When quality-quantity regulation (QQR) is adopted, namely adjusting hydraulic and thermal conditions of heating system, the increase in operation flexibility is more remarkable. However, present IEHS dispatch models considering QQR overlook hydraulic characteristics of valves and variable frequency pumps resulting in inexecutable dispatch results easily and hindering IEHS's flexibility potential. Furthermore, loop networks and the access of multiple heat sources in heating systems may lead to flow reversal, but current research adopts a fixed flow direction which suppresses the potential of flow reversal to improve flexibility. In this paper, we propose an IEHS dispatch model considering QQR to promote renewable energy consumption, which considers hydraulic characteristics of valves and variable frequency pumps, and flow reversal. Specifically, we introduce two binary flow direction labels for every branch in heating system model and then the IEHS dispatch model which can deal with flow reversal is established. A sequential solution process combining linear and nonlinear optimization is formulated to overcome the non-convex feature of IEHS dispatch model. Specifically, piecewise linearization and piecewise McCormick relaxation are combined to handle complex nonlinear terms in the dispatch model. Therefore, a mixed integer linear programming model is obtained and solved, of which results are used as initial values for nonlinear optimization. Results in the case study show that operation cost is decreased by 0.97 % and renewable power consumption rate is increased from 83.31 % to 84.42 % after considering valve adjustment. Operation cost is further decreased by 6.06 % and renewable power consumption rate is increased to 94.04 % after considering flow reversal.