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The consequences of climate change along with diverse food regulations and agricultural practices worldwide are complexifying the occurrence and management of chemical contaminants in food. In this context, we present an ultra-high-performance liquid chromatography high-resolution mass spectrometry (LC-HRMS) approach for the simultaneous identification and quantitation of over 1100 pesticide residues, mycotoxins, and plant toxins in cereals and fruits and vegetables. Analytical conditions were optimized to maximize the scope of the targeted molecules, the reliability of compound identification, and quantification performance within a single method. The method was further transferred and validated in another laboratory to assess its ruggedness. Validation according to the SANTE 11312/2021v2 guidelines showed that 92% and 98% of the molecules fulfill the quantification criteria at the lowest validated level in the cereals and fruits and vegetables groups, respectively. Analysis of fifteen certified reference materials led to a 96% satisfactory rate of z-scores confirming method's competitiveness. Furthermore, the occurrence of these contaminants was studied in 205 cereals and grains samples collected worldwide. The low µg/kg quantification limits make this LC-HRMS method a valuable tool to ensure compliance toward regulations and to screen for non-regulated substances for which occurrence data are crucial for an appropriate risk evaluation.

Introduction: Identifying compounds with endocrine properties in food is getting increasingly important. Current chemical analysis methodology is mainly focused on the identification of known substances without bringing insight for biological activity. Recently, the application of bioassays has been promoted for their potential to detect unknown bioactive substances and to provide information on possible interactions between molecules. From the toxicological perspective, measuring endocrine activity cannot inform on endocrine disruption and/or health risks without sufficient knowledge on the nature of the responsible factors., Methods: The present study addresses a promising approach using High Performance Thin-Layer Chromatography (HPTLC) coupled to bioassays were analyzed using the Liquid Chromatography Mass-Spectrometry (LC-MS). The estrogen receptor activation was assessed using the transcription activation Estrogen Receptor Alpha Chemical Activated LUciferase gene eXpression assay (ERα- CALUX) and the HPTLC coupled to the Estrogen Screen Yeast assay (p-YES)., Results: Seven isoflavones were identified in the soy isolates. Estrogen receptor activation was assessed for both, the identified isoflavones and the soy isolates with ERα-CALUX test. Correlation between the soy isolates extracts and the identified isoflavones was shown. Moreover, p-YES revealed the presence of an estrogenic bioactive zone. Analysis of the bioactive zone through LCHRMS highlighted signals corresponding to several isoflavones already detected in the isolates as well as two additional ones. For all detected isoflavones, an estrogenic activity dose-response was established in both bioassays., Conclusion: Finally, genistein, daidzein, and naringenin were found as the most active substances. A concordance analysis integrating the analytical and bioassay data indicated that genistein and daidzein were the drivers of the estrogenic activity of these soy protein isolates. Altogether, these data suggest that the integration of HPTLC-bioassay together with chemical analysis is a powerful approach to characterize the endocrine activity of complex mixtures., Competing Interests: All authors were employed by company Société des Produits Nestlé SA., (Copyright © 2023 Debon, Gentili, Latado, Serrant, Badoud, Ernest, Christinat, Bessaire, Schilter and Marin-Kuan.)

Even though modeling is considered a valid alternative to mutagenicity testing for substances with known structures, it can be applied for mixtures only if all of the single chemical structures are identified. Within the present work, we investigate a new avenue to exploit computational toxicology for mixtures, such as plant-based food ingredients. Indeed, considering that in the absence of toxicological information, an important early consideration is whether any substance may be genotoxic through the mutagenic mechanism of action, we tried to establish a correspondence between genotoxic structural alerts (SAs) and so-called signature fragment alerts (SFAs). Once this correspondence is established, chromatograms could be screened for chemical features associated with genotoxic alerts. Pyrrolizidine alkaloids (PAs), a large group of natural toxins (several of them known as genotoxic) were used as a case study because their early identification would bring significant benefits. The method was built using 56 PA pure standards, resulting in the characterization of signature fragment alerts. Finally, the approach was verified in real plant-based samples such as herbal tea and alfalfa, where the screening of signature fragment alerts allowed highlighting quickly the presence of genotoxic PAs in plant-based mixtures. Therefore, the SFA analysis can be used for risk prioritization of newly identified PAs and for their identification in mixtures, contributing to the unnecessary use of animal experimentation for genotoxicity testing.

The idea that previously unknown hazards can be readily revealed in complex mixtures such as foods is a seductive one, giving rise to the hope that data from effect-based assays of food products collected in market surveys is of suitable quality to be the basis for data-driven decision-making. To study this, we undertook a comparative study of the oestrogenicity of blinded cereal samples, both in a number of external testing laboratories and in our own facility. The results clearly showed little variance in the activities of 9 samples when using a single method, but great differences between the activities from each method. Further exploration of these findings suggest that the oestrogenic activity is likely an inherent part of the natural food matrix which the varying sample preparation methods are able to release and extract to differing degrees. These issues indicate the current poor suitability of these types of datasets to be used as the basis for consumer advice or food decision-making. Data quality must be improved before such testing is used in practice.

An analytical workflow including mass spectral library, generic sample preparation, chromatographic separation, and analysis by high-resolution mass spectrometry (HRMS) was developed to gain insight into the occurrence of plant toxins, mycotoxins and phytoestrogens in plant-based food. This workflow was applied to 156 compounds including 90 plant toxins (pyrrolizidine alkaloids, tropane alkaloids, glycoalkaloids, isoquinoline alkaloids and aristolochic acids), 54 mycotoxins (including ergot alkaloids and Alternaria toxins) and 12 phytoestrogens (including isoflavones, lignans and coumestan) in plant-based protein ingredients, cereal and pseudo-cereal products. A mass spectral library was built based on fragmentation spectra collected at 10 different collision energies in both positive and negative ionisation modes for each toxin. Emphasis was put on a generic QuEChERS-like sample preparation followed by ultra-high-pressure liquid chromatography using alkaline mobile phase allowing the separation of more than 50 toxic pyrrolizidine alkaloids. HRMS acquisition comprised a full-scan event for toxins detection followed by data-dependent MS2 for toxin identification against mass spectrum. Method performance was evaluated using fortified samples in terms of sensitivity, repeatability, reproducibility and recovery. All toxins were positively identified at levels ranging from 1 µg kg -1 to 100 µg kg -1 . Quantitative results obtained by a standard addition approach met SANTE/12682/2019 criteria for 132 out of 156 toxins. Such a workflow using generic, sensitive and selective multi-residue method allows a better insight into the occurrence of regulated and non-regulated toxins in plant-based foods and to conduct safety evaluation and risk assessments when needed.

The utilization of alternative energy substrates to glucose could be beneficial in traumatic brain injury (TBI). Recent clinical data obtained in TBI patients reported valine, β-hydroxyisobutyrate (ibHB) and 2-ketoisovaleric acid (2-KIV) as three of the main predictors of TBI outcome. In particular, higher levels of ibHB, 2-KIV, and valine in cerebral microdialysis (CMD) were associated with better clinical outcome. In this study, we investigate the correlations between circulating and CMD levels of these metabolites. We hypothesized that the liver can metabolize valine and provide a significant amount of intermediate metabolites, which can be further metabolized in the brain. We aimed to assess the metabolism of valine in human-induced pluripotent stem cell (iPSC)-derived astrocytes and HepG2 cells using 13 C-labeled substrate to investigate potential avenues for increasing the levels of downstream metabolites of valine via valine supplementation. We observed that 94 ± 12% and 84 ± 16% of ibHB, and 94 ± 12% and 87 ± 15% of 2-KIV, in the medium of HepG2 cells and in iPSC-derived astrocytes, respectively, came directly from valine. Overall, these findings suggest that both ibHB and 2-KIV are produced from valine to a large extent in both cell types, which could be of interest in the design of optimal nutritional interventions aiming at stimulating valine metabolism.

In this study, the occurrence of cannabinoids in hemp-based food products was investigated. For that purpose, a new liquid chromatography tandem mass spectrometry method for the quantification of fifteen cannabinoids was developed and validated for multiple matrices. Method performances were good, fulfilling the SANTE/11813/2017 requirements, and allowing for products compliance testing with various national legislations on cannabinoids levels in food products. The limit of quantification of each analyte was 0.15 mg/kg for hemp seed and hemp protein, 0.6 mg/kg for hemp seed oil, and 0.005 mg/kg for raw milk and milk powder. The applicability of the method was further demonstrated by conducting a limited survey on twenty hemp-based food products. The survey revealed that products from the same category can have very different cannabinoids profiles and levels. These results highlighted the importance of cannabinoids testing of food products in view of the current heterogeneous and fast evolving regulatory landscape worldwide., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The development of high throughput assays for assessing lipid metabolism in metabolic disorders, especially in diabetes research, nonalcoholic fatty liver disease (NAFLD), and nonalcoholic steatohepatitis (NASH), provides a reliable tool for identifying and characterizing potential biomarkers in human plasma for early diagnosis or prognosis of the disease and/or responses to a specific treatment. Predicting the outcome of weight loss or weight management programs is a challenging yet important aspect of such a program's success. The characterization of potential biomarkers of metabolic disorders, such as lysophospholipids and bile acids, in large human clinical cohorts could provide a useful tool for successful predictions. In this study, we validated an LC-MS method combining the targeted and untargeted detection of these lipid species. Its potential for biomarker discovery was demonstrated in a well-characterized overweight/obese cohort subjected to a low-caloric diet intervention, followed by a weight maintenance phase. Relevant markers predicting successful responses to the low-caloric diet intervention for both weight loss and glycemic control improvements were identified. The response to a controlled weight loss intervention could be best predicted using the baseline concentration of three lysophospholipids (PC(22:4/0:0), PE(17:1/0:0), and PC(22:5/0:0)). Insulin resistance on the other hand could be best predicted using clinical parameters and levels of circulating lysophospholipids and bile acids. Our approach provides a robust tool not only for research purposes, but also for clinical practice, as well as designing new clinical interventions or assessing responses to specific treatment. Considering this, it presents a step toward personalized medicine.

Background: Micronutrient supplementation has been extensively explored as a strategy to improve health and reduce risk of chronic diseases. Fat-soluble vitamins like A and E with their antioxidant properties and mechanistic interactions with lipoproteins, have potentially a key impact on lipid metabolism and lipidemia., Objective: The impact of micronutrients on lipid metabolism requires further investigation including characterization of plasma lipidome following supplementation and any cause-effect on circulating lipids., Design: In this study, we elucidate the effect and associations of a multi-micronutrient intervention in Brazilian children and teens with lipoprotein alterations and lipid metabolism., Results: Our analysis suggests a combination of short and long-term impact of supplementation on lipid metabolism, potentially mediated primarily by α-tocopherol (vitamin E) and retinol (vitamin A). Among the lipid classes, levels of phospholipids, lysophospholipids, and cholesterol esters were impacted the most along with differential incorporation of stearic, palmitic, oleic and arachidonic acids. Integrated analysis with proteomic data suggested potential links to supplementation-mediated alterations in protein levels of phospholipases and pyruvate dehydrogenase kinase 1 (PDK1)., Conclusions: Associations between the observed differences in lipidemia, total triglyceride, and VLDL-cholesterol levels suggest that micronutrients may play a role in reducing these risk factors for cardiovascular disease in children. This would require further investigation., (Copyright © 2019 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Adaptive metabolic response to injury includes the utilization of alternative energy substrates - such as ketone bodies (KB) - to protect the brain against further damage. Here, we examined cerebral ketone metabolism in patients with traumatic brain injury (TBI; n  = 34 subjects) monitored with cerebral microdialysis to measure total brain interstitial tissue KB levels (acetoacetate and β-hydroxybutyrate). Nutrition - from fasting vs. stable nutrition state - was associated with a significant decrease of brain KB (34.7 [10th-90th percentiles 10.7-189] µmol/L vs. 13.1 [6.5-64.3] µmol/L, p  < 0.001) and blood KB (668 [168.4-3824.9] vs. 129.4 [82.6-1033.8] µmol/L, p  < 0.01). Blood KB correlated with brain KB (Spearman's rho 0.56, p  = 0.0013). Continuous feeding with medium-chain triglycerides-enriched enteral nutrition did not increase blood KB, and provided a modest increase in blood and brain free medium chain fatty acids. Higher brain KB at the acute TBI phase correlated with age and brain lactate, pyruvate and glutamate, but not brain glucose. These novel findings suggest that nutritional ketosis was the main determinant of cerebral KB metabolism following TBI. Age and cerebral metabolic distress contributed to brain KB supporting the hypothesis that ketones might act as alternative energy substrates to glucose. Further studies testing KB supplementation after TBI are warranted.

Medium-chain triglyceride (MCT) ketogenic diets increase ketone bodies, which are believed to act as alternative energy substrates in the injured brain. Octanoic (C8:0) and decanoic (C10:0) acids, which produce ketone bodies through β-oxidation, are used as part of MCT ketogenic diets. Although the ketogenic role of MCT is well-established, it remains unclear how the network metabolism underlying β-oxidation of these medium-chain fatty acids (MCFA) differ. We aim to elucidate basal β-oxidation of these commonly used MCFA at the cellular level. Human-induced pluripotent stem cell-derived (iPSC) astrocytes were incubated with [U- 13 C]-C8:0 or [U- 13 C]-C10:0, and the fractional enrichments (FE) of the derivatives were used for metabolic flux analysis. Data indicate higher extracellular concentrations and faster secretion rates of β-hydroxybutyrate (βHB) and acetoacetate (AcAc) with C8:0 than C10:0, and an important contribution from unlabeled substrates. Flux analysis indicates opposite direction of metabolic flux between the MCFA intermediates C6:0 and C8:0, with an important contribution of unlabeled sources to the elongation in the C10:0 condition, suggesting different β-oxidation pathways. Finally, larger intracellular glutathione concentrations and secretions of 3-OH-C10:0 and C6:0 were measured in C10:0-treated astrocytes. These findings reveal MCFA-specific ketogenic properties. Our results provide insights into designing different MCT-based ketogenic diets to target specific health benefits.

Background: Traumatic brain injury (TBI) is recognized as a metabolic disease, characterized by acute cerebral glucose hypo-metabolism. Adaptive metabolic responses to TBI involve the utilization of alternative energy substrates, such as ketone bodies. Cerebral microdialysis (CMD) has evolved as an accurate technique allowing continuous sampling of brain extracellular fluid and assessment of regional cerebral metabolism. We present the successful application of a combined hypothesis- and data-driven metabolomics approach using repeated CMD sampling obtained routinely at patient bedside. Investigating two patient cohorts (n = 26 and n = 12), we identified clinically relevant metabolic patterns at the acute post-TBI critical care phase., Methods: Clinical and CMD metabolomics data were integrated and analysed using in silico and data modelling approaches. We used both unsupervised and supervised multivariate analysis techniques to investigate structures within the time series and associations with patient outcome., Findings: The multivariate metabolite time series exhibited two characteristic brain metabolic states that were attributed to changes in key metabolites: valine, 4-methyl-2-oxovaleric acid (4-MOV), isobeta-hydroxybutyrate (iso-bHB), tyrosyine, and 2-ketoisovaleric acid (2-KIV). These identified cerebral metabolic states differed significantly with respect to standard clinical values. We validated our findings in a second cohort using a classification model trained on the cerebral metabolic states. We demonstrated that short-term (therapeutic intensity level (TIL)) and mid-term patient outcome (6-month Glasgow Outcome Score (GOS)) can be predicted from the time series characteristics., Interpretation: We identified two specific cerebral metabolic patterns that are closely linked to ketometabolism and were associated with both TIL and GOS. Our findings support the view that advanced metabolomics approaches combined with CMD may be applied in real-time to predict short-term treatment intensity and long-term patient outcome., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)

Ketones represent an important alternative fuel for the brain under glucose hypo-metabolic conditions induced by neurological diseases or aging, however their metabolic consequences in healthy brain remain unclear. Here we report that ketones can increase the redox NAD + /NADH ratio in the resting brain of healthy young adults. As NAD is an important energetic and signaling metabolic modulator, these results provide mechanistic clues on how nutritional ketosis might contribute to the preservation of brain health.

Diabetes prevalence increases with age, and β-cell dysfunction contributes to the incidence of the disease. Dietary lipids have been recognized as contributory factors in the development and progression of the disease. Unlike long chain triglycerides, medium chain triglycerides (MCT) increase fat burning in animal and human subjects as well as serum C-peptide in type 2 diabetes patients. We evaluated the beneficial effects of MCT on β-cells in vivo and in vitro. MCT improved glycemia in aged rats via β-cell function assessed by measuring insulin secretion and content. In β-cells, medium chain fatty acid (MCFA)-C10 activated fatty acid receptor 1 FFAR1/GPR40, while MCFA-C8 induced mitochondrial ketogenesis and the C8:C10 mixture improved β cell function. We showed that GPR40 signaling positively impacts ketone body production in β-cells, and chronic treatment with β-hydroxybutyrate (BHB) improves β-cell function. We also showed that BHB and MCFA help β-cells recover from lipotoxic stress by improving mitochondrial function and increasing the expression of genes involved in β-cell function and insulin biogenesis, such as Glut2, MafA, and NeuroD1 in primary human islets. MCFA offers a therapeutic advantage in the preservation of β-cell function as part of a preventative strategy against diabetes in at risk populations., Competing Interests: The authors declare no conflict of interest.

Lipoproteins are responsible for the transport of lipids and other nutrients in the circulation and therefore play an important role in lipid metabolism and dyslipidemia. They have also been linked to multiple metabolic disorders including cardiovascular disease, and thus understanding their lipid composition is of crucial importance. Characterization of lipoproteins is a challenging task due to their heterogeneity. In particular, their fractionation is often laborious and time-consuming, making large sets of clinical samples difficult to analyze. We developed and validated lipidomics analysis of lipoproteins including chylomicrons, very low-density, low-density, and high-density lipoproteins. Lipoproteins were first fractionated by polyacrylamide tube gel electrophoresis, and, after liquid-liquid extraction, lipids were analyzed by direct-infusion mass spectrometry. About 100 unique lipid species were detected with good reproducibility and reliability. In addition to their lipid composition, valuable information on the fatty acid composition of lipoproteins and lipids was obtained. The presented method offers in-depth analysis of the lipid as well as fatty acid composition of lipoproteins while allowing a good sample throughput. It is thus especially suited for studying lipid associated diseases in clinical cohorts.

Rationale: Long-chain fatty acyl-coenzyme As (FA-CoAs) are important bioactive molecules, playing key roles in biosynthesis of fatty acids, membrane trafficking and signal transduction. Development of sensitive analytical methods for profiling theses lipid species in various tissues is critical to understand their biological activity. A high-pressure liquid chromatography/tandem mass spectrometry method has been developed for the quantitative analysis and screening of long-chain FACoAs in liver, brain, muscle and adipose tissue., Methods: The sample preparation method consists of tissue homogenization, extraction with organic solvent and reconstitution in an ammonium hydroxide buffer. Extracts are separated by liquid chromatography (LC) on a reversed-phase column and detected by electrospray ionization tandem mass spectrometry (ESI-MS/MS) in positive mode. An additional neutral loss scan allows for untargeted FA-CoAs screening., Results: Extraction was optimized for low sample load (10 mg) of four tissue types (liver, brain, muscle and adipose tissue) with recoveries between 60-140% depending on the analyte and tissue type. Targeted quantification was validated for ten FA-CoAs in the range 0.1-500 ng/mL with accuracies between 85-120%., Conclusions: We have developed and validated a LC/MS/MS method for the quantifications and screening of long-chain FA-CoAs in four different types of mammalian tissue. The extraction method is straightforward and long-chain FA-CoA species can be quantified using only minimum amount of tissue. Copyright © 2016 John Wiley & Sons, Ltd., (Copyright © 2016 John Wiley & Sons, Ltd.)

Nonesterified fatty acids are important biological molecules which have multiple functions such as energy storage, gene regulation, or cell signaling. Comprehensive profiling of nonesterified fatty acids in biofluids can facilitate studying and understanding their roles in biological systems. For these reasons, we have developed and validated a high-throughput, nontargeted lipidomics method coupling liquid chromatography to high-resolution mass spectrometry for quantitative analysis of nonesterified fatty acids. Sufficient chromatographic separation is achieved to separate positional isomers such as polyunsaturated and branched-chain species and quantify a wide range of nonesterified fatty acids in human plasma samples. However, this method is not limited only to these fatty acid species and offers the possibility to perform untargeted screening of additional nonesterified fatty acid species.

We present a high-throughput, nontargeted lipidomics approach using liquid chromatography coupled to high-resolution mass spectrometry for quantitative analysis of nonesterified fatty acids. We applied this method to screen a wide range of fatty acids from medium-chain to very long-chain (8 to 24 carbon atoms) in human plasma samples. The method enables us to chromatographically separate branched-chain species from their straight-chain isomers as well as separate biologically important ω-3 and ω-6 polyunsaturated fatty acids. We used 51 fatty acid species to demonstrate the quantitative capability of this method with quantification limits in the nanomolar range; however, this method is not limited only to these fatty acid species. High-throughput sample preparation was developed and carried out on a robotic platform that allows extraction of 96 samples simultaneously within 3 h. This high-throughput platform was used to assess the influence of different types of human plasma collection and preparation on the nonesterified fatty acid profile of healthy donors. Use of the anticoagulants EDTA and heparin has been compared with simple clotting, and only limited changes have been detected in most nonesterified fatty acid concentrations.

Medium-chain triglycerides have been used as part of a ketogenic diet effective in reducing epileptic episodes. The health benefits of the derived medium-chain fatty acids (MCFAs) are thought to result from the stimulation of liver ketogenesis providing fuel for the brain. We tested whether MCFAs have direct effects on energy metabolism in induced pluripotent stem cell-derived human astrocytes and neurons. Using single-cell imaging, we observed an acute pronounced reduction of the mitochondrial electrical potential and a concomitant drop of the NAD(P)H signal in astrocytes, but not in neurons. Despite the observed effects on mitochondrial function, MCFAs did not lower intracellular ATP levels or activate the energy sensor AMP-activated protein kinase. ATP concentrations in astrocytes were unaltered, even when blocking the respiratory chain, suggesting compensation through accelerated glycolysis. The MCFA decanoic acid (300 μM) promoted glycolysis and augmented lactate formation by 49.6%. The shorter fatty acid octanoic acid (300 μM) did not affect glycolysis but increased the rates of astrocyte ketogenesis 2.17-fold compared with that of control cells. MCFAs may have brain health benefits through the modulation of astrocyte metabolism leading to activation of shuttle systems that provide fuel to neighboring neurons in the form of lactate and ketone bodies.-Thevenet, J., De Marchi, U., Santo Domingo, J., Christinat, N., Bultot, L., Lefebvre, G., Sakamoto, K., Descombes, P., Masoodi, M., Wiederkehr, A. Medium-chain fatty acids inhibit mitochondrial metabolism in astrocytes promoting astrocyte-neuron lactate and ketone body shuttle systems., (© FASEB.)

Blood plasma has gained protagonism in lipidomics studies due to its availability, uncomplicated collection and preparation, and informative readout of physiological status. At the same time, it is also technically challenging to analyze due to its complex lipid composition affected by many factors, which can hamper the throughput and/or lipidomics coverage. To tackle these issues, we developed a comprehensive, high throughput, and quantitative mass spectrometry-based shotgun lipidomics platform for blood plasma lipid analyses. The main hallmarks of this technology are (i) it is comprehensive, covering 22 quantifiable different lipid classes encompassing more than 200 lipid species; (ii) it is amenable to high-throughput, with less than 5 min acquisition time allowing the complete analysis of 200 plasma samples per day; (iii) it achieves absolute quantification, by inclusion of internal standards for every lipid class measured; (iv) it is highly reproducible, achieving an average coefficient of variation of <10% (intra-day), approx. 10% (inter-day), and approx. 15% (inter-site) for most lipid species; (v) it is easily transferable allowing the direct comparison of data acquired in different sites. Moreover, we thoroughly assessed the influence of blood stabilization with different anticoagulants and freeze-thaw cycles to exclude artifacts generated by sample preparation. Practical applications: This shotgun lipidomics platform can be implemented in different laboratories without compromising reproducibility, allowing multi-site studies and inter-laboratory comparisons. This possibility combined with the high-throughput, broad lipidomic coverage and absolute quantification are important aspects for clinical applications and biomarker research.

The condensation of multiple building blocks in a ball mill allows molecular cages with a size up to 3.1 nm to be built.

The multicomponent reaction of 1,2-di(4-pyridyl)ethylene, catechol, 3,5-bis(trifluoromethyl)phenylboronic acid and 1,5-dinaphtho-38-crown-10 or bis-para-phenylene-34-crown-10, respectively, resulted in the formation of rotaxanes, which were characterized by X-ray crystallography.

A new synthetic strategy for the construction of boron-based macrocycles and dendrimers is described. Condensation of aryl- and alkylboronic acids with 3,4-dihydroxypyridine is shown to give pentameric macrocycles in which five boronate esters are connected by dative B-N bonds. Three macrocycles have been characterized crystallographically. The boron atoms of these assemblies represent chiral centers, and the assembly process is highly diastereoselective. Attachment of amino or aldehyde groups in the meta position of the arylboronic acid building blocks does not interfere with macrocyclization. This allows performing multicomponent assembly reactions between functionalized boronic acids, dihydroxypyridine ligands, and amines or aldehydes, respectively. Reaction of 3,5-diformylphenylboronic acid, 3,4-dihydroxypyridine, and a primary amine R-NH2 (R=Ph, Bn) gives dendritic nanostructures having a pentameric macrocyclic core and 10 amine-derived R groups in their periphery. Combination of 3,5-diformylphenylboronic acid with 2,3-dihydroxypyridine and the dendron 3,5-(benzyloxy)benzylamine, on the other hand, results in formation of a dendrimer with a tetrameric macrocyclic core and eight dendrons in its periphery.