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Analysis of Phenolic and Cyclic Compounds in Plants Using Derivatization Techniques in Combination with GC-MS-Based Metabolite Profiling

Metabolite profiling has been established as a modern technology platform for the description of complex chemical matrices and compound identification in biological samples. Gas chromatography coupled with mass spectrometry (GC-MS) in particular is a fast and accurate method widely applied in diagnostics, functional genomics and for screening purposes. Following solvent extraction and derivatization, hundreds of metabolites from different chemical groups can be characterized in one analytical run. Besides sugars, acids, and polyols, diverse phenolic and other cyclic metabolites can be efficiently detected by metabolite profiling. The review describes own results from plant research to exemplify the applicability of GC-MS profiling and concurrent detection and identification of phenolics and other cyclic structures.

Introduction
Chromatographic techniques for the detection and identification of metabolites in plant material have undergone major changes in recent years due to improvements of analysis time, detection limit and separation characteristics. Depending on the biological question, one might distinguish between targeted and non-targeted strategies. Gas chromatography (GC) in particular is characterized by sensitivity and reliability of separations and detection of complex sample mixtures. Coupling with mass spectrometry (MS) provides highly robust analysis platforms compared to liquid chromatography (LC-MS) and allows

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for the identification of compounds based on the use of commercially or publicly available MS libraries and resources (Table 1) in combination with retention time index (RI) data. Table 1. Selection of commercially and publicly available MS libraries and resources for structure elucidation and compound identification of GC-MS data. Included is also a list of freely software tools for identification, deconvolution and alignment purposes.

GC-MS Profiling of Complex Chemical Matrices
Beside parameters related to proper MS compound identification and use of retention index (RI) data, several aspects related to metabolite extraction and derivatization need to be considered in GC-MS-based metabolite profiling. Depending on the biological question, metabolite targets, and sample matrix, solvents of differing polarity and varying phases have been investigated for compound extraction. For global metabolomics approaches, the use of extraction mixtures covering a wide range from polar to apolar metabolites such as H2O:MeOH:CHCl3 (1:2.5:1) or H2O:MeOH are favoured [2,5]. In other cases, one might need to separate lipids from the polar phase as described by Lisec et al. [1], either for separate chromatographic study of the different fractions [6], or for a more targeted metabolite analysis.

Extraction Methods and Metabolite Coverage
While sample preparation and processing need to be individually adapted and customized, sample extraction often follows standardized procedures using established protocols for comprehensive metabolite profiling and non-targeted metabolomics approaches as already outlined at the beginning. An important parameter in high-throughput metabolite profiling is the high degree of miniaturization and automation in sample handling, requiring the processing of small or ultrasmall sample sizes as low as a few milligrams. Unless secondary metabolites are highly abundant, their potential recovery under such extraction conditions and GC-MS detection proves insufficient. Moreover, microextraction techniques such as sorbent-based solid-phase microextraction (SPME) [7], stirbar-sorptive extraction (SBSE) [8], and solvent-based methods such as e.g., single-drop microextraction (SDME) and liquid-liquid microextraction (LLME) [9] establish sensitive methods for the characterization of complex profiles of volatile compounds found in plant and food samples. Microextraction might also be successfully combined with derivatization techniques and subsequent gas chromatographic separation for the detection of a wide range of volatiles with different polarity [10][11][12]. In general, metabolomic approaches based on SPME extraction and detection of non-derivatized volatiles, emphasize the technique's tremendous capacity to cover a broad range of different compound groups [13], also including aromatic structures, as shown for e.g., tomato [14] and peach [15].

Derivatization of Metabolites
Derivatization prior to GC-MS is an essential preparatory step, which reduces polarity and increases volatility, and simultaneously, thermal stability of metabolites. Compound derivatization is either based on silylation, alkylation or acylation reactions, and a wide range of reagents with different properties are available. Comprehensive studies have shown the superior properties of silylation agents [16], which substitute protons bound to heteroatoms in functional groups (-OH, -COOH, -NH2, -NH, -SH, -OP(=O)(OH)2, etc.) and generate trimethylsilyl (TMS) and tert-butyldimethylsilyl (TBS) derivatives [17]. (BSTFA) and N-methyl-N-(trimethylsilyl)trifluoroacetamide (MSTFA) are widely applied in biological analyses, the use of MSTFA as derivatization agent has been favoured by leading metabolomics labs worldwide. In specific cases, the use of other derivatization agents might be advised. Newer studies suggest alkylation with e.g., methyl chloroformate (MCF) instead of, or in combination with compound silylation due to improved analytical performance [18]. MCF derivatization shows improved reproducibility and compound stability compared to silylation, and is suitable for the analysis of microbial-derived samples with matrices mainly composed of amino and non-amino organic acids, amines and nucleotides [18]. However, due to the wide range of compound structures being covered by combined methoximation and TMS derivatization [19], comprising amino acids, fatty acids, lipids, amines, alcohols, sugars, amino-sugars, sugar alcohols, sugar acids, organic phosphates, hydroxyl acids, aromatics, purines, and sterols, major metabolomics attempts towards the development of MS libraries have favoured the coverage of oximated and silylated metabolites.
Despite the feasibility and power of combined oximation/silylation in global metabolite profiling approaches, several factors impair sample analysis and data quality. A major point is that silylation reactions have to be carried out under anhydrous reaction conditions [18], which requires an additional drying step of sample extracts (e.g., SpeedVac TM (Thermo Scientific, Waltham, MA, USA) or lyophilization). Excess derivatization reagents are commonly introduced in the GC injection port, potentially leading to additional peaks in the chromatogram. Moreover, also non-volatile non-derivatized metabolites or even macromolecules such as peptides, proteins or polysaccharides might be injected, depending on preceding sample clean-up conditions (precipitation, centrifugation and/or filtration) and thus, impede separation performance and GC data analysis. Nevertheless, the utilization of packed inlet liners and/or suitable guard columns circumvent these problems and can protect analytical capillary columns from sample impurities.
Another important factor affecting the quality of metabolite data is the occurrence of artefacts of silylated compounds in GC-MS profiling [17]. Unexpected by-products might add to the complexity of peaks in a chromatogram and interfere with the identification process. This includes also conversion reactions of unstable intermediates, e.g., arginine to ornithine when using BSTFA or MSTFA, potentially leading to misinterpretation of metabolic data [4]. But more important, multiple peaks of one and the same metabolite, i.e., with different degree of TMS silylation of the original molecule, might be detected. This is particularly true for those metabolites with several functional groups such as amino acids (-COOH, -NH2, -OH) and monosaccharides which carry a high number of hydroxy groups. The amino acid serine e.g., shows four active hydrogens which might be exchanged by TMS groups (Figure 1).

Figure 1.
Trimethylsilylation levels of the amino acid serine commonly found in TMS derivatized samples. In serine (2TMS), the OH-and COOH-group are trimethylsilylated, in serine (3TMS) one OH-group of the amino group is exchanged, while in serine (4TMS) all active hydrogens are exchanged.
In GC-MS one might deal with both the 2TMS stage, where only the carboxy and hydroxy group are silylated, and the 3TMS and 4TMS stage with one or both H + of the amino group exchanged. For this reason, MS data of metabolites showing a varying numbers of TMS groups, and both oximate/ TMS metabolite derivatives have been included in MS libraries (e.g., GMD database, NIST, etc.). Such considerations play an important role if metabolites levels shall be quantitatively acquired. Expected that multiple compounds show the same detection response, their individual responses might be summed. Regarding secondary metabolites, it is likely to assume that artifact formation also occurs for these compounds depending on the number of active hydrogens and the given derivatization conditions. However, MS information of such by-products is scarcely, if at all, included in available TMS-MS libraries.

GC-MS Metabolite Profiling-Applications, Performance and Reliability
The term metabolite profiling has already existed for many years, but first the development of high-capacity and high-throughput chromatographic systems in recent years has established the basis to generate extensive amounts of profiling data, which is comparable in its extent to the output of proteomics and transcriptomic analyses. Moreover, the applicability and significance of particularly GC-MS metabolite profiling in functional genomics was early recognized using the plant model systems Arabidopsis thaliana and potato (Solanum tuberosum) [20,21]. Common for those reports is the low coverage of secondary structures which primarily include major phenolic acids, pyridines, tocopherols and sterols. The concept of metabolomics has been applied also for the study of crop plants in more recent years [22]. Using tomato (Solanum lycopersicum) as an example, breeding goals towards nutritional quality [23] and yield [24], impact of environment such as fertilization [25], and temporal metabolite patterns in molecular crop physiology have been addressed [26]. Also here, GC-MS metabolite profiling had major focus on central metabolism and less on secondary structures. However, phenolic acids commonly found in plant material have been detected in potato [27,28], maize [29], soybean leaves [30] and tobacco [31]. GC-MS profiling of lipophilic compounds including sterols/triterpenes and tocopherols has been described for tomato cuticles [32] and maize grain [29]. One important and necessary concept for the description of genetically modified (GM) crops is the so-called substantial equivalence based on the evaluation whether the chemical composition of a GM crop differs from the non-GM counterpart or not. Metabolite profiling is utilized as an essential tool for screening of GM crops with regard to quality and health requirements in order to investigate potential changes in metabolite profiles in e.g., wheat [33], rice [34], and maize [35].
Global metabolomic approaches based on derivatization techniques following GC-MS for the mapping of biosynthetic pathways and characterization of metabolic perturbations and genotypes appear to be less laborious and more cost-effective compared to metabolite targeting. The use of highly sensitive and fast-scanning GC-TOF-MS instrumentation in particular facilitates proper compound detection and resolution of co-eluting peaks. The latter point is a common feature in comprehensive metabolite matrices, and can successfully be addressed based on the acquired data information, including exact retention time, accurate mass, and characteristic MS fragmentation patterns and ion intensities. In GC-QMS or GC-ITMS, on the other hand, analysis time might be extended in order to improve separation performance and resolution of overlapping peaks. In recent years, more advanced extraction and separation methods have been added to the tool box of automated profiling techniques. Such advances include GC × GC-MS (or so-called 2D GC-MS), where samples are subsequently separated on columns of different polarity, thus increasing separation capacity and performance in the detection of biomolecules [36].
However, even the use of accurate mass, MS spectra and RI values might lead to misidentification of compound structures, not least because mass spectra of different TMS derivatives might be notoriously similar (e.g., sugar alcohols), or totally different metabolites might have the same RI value. Another major problem when analysing complex sample mixtures is the fact that metabolite abundances can vary by many orders of magnitude. The linearity and detector response dynamics of metabolites from different structure groups differ greatly [18], thus impeding quantitation of absolute compound concentrations. For that purpose, levels of distinct metabolites might be determined by comparison with calibration standard curve response ratios of various concentrations of standard substance solutions as described by e.g., Roessner-Tunali et al. [37]. Moreover, variations in sample volume, i.e., when using a sample range with a defined maximal tolerance, only allows for relative quantitative detection of metabolites, in contrast to procedures using the same exact amounts of samples and allowing for absolute quantitation [38]-a fact which needs suitable consideration when working with small sample sizes.

Secondary Metabolites in GC-MS-Based Metabolomic Approaches
GC-MS-based metabolite profiling of TMS derivatives does not only generate vast chemical information about primary metabolism, but includes also extensive MS data about secondary metabolites and "unknowns". In order to advance the identification process of less abundant structures in plant samples, comprehensive RI tables for cinnamic acids and other simple phenolic structures, flavonoids, tocopherols and sterols have been generated to provide useful information about the elution order of silylated secondary metabolites on a GC system [27,39]. Furthermore, MS fragmentation patterns have been reported for a wide range of secondary metabolites including phenols and phenolic acids [40][41][42][43], flavonoids [42,44,45], alkylresorcinols [46], phytoestrogens [47], secoiridoids and ligstrosides [41,48], diterpenes and diterpenic acids [49], phenolic diterpenes and pentacyclic triterpenes [50], sterols, stanols, and esters thereof [51,52], lignans [53], stilbenes [54,55], and alkaloids [56]. The utilization of relevant scientific literature reporting GC-MS information about phytochemicals is crucial for the tentative identification of less abundant chemical structures in profiling experiments. Regarding the restricted number of primary and major secondary metabolites, which are commonly included in spectral libraries of TMS analytes, several specific secondary structures are described based on case studies presented in Section 4.

Detection of Plant Phenolics and Other Cyclic Structures
The following classification of the quite diverse group of phenolic structures and other plant-derived cyclic compounds follows chemical structure characteristics rather than biosynthetic relationships, which makes it easier to discuss the topic from an analytical point of view. In a wider sense phenolic structures addressed here contain either one (Section 3.1) or several aromatic rings (Section 3.2) as part of the molecule. In order to cope with the tremendous variability of primary but also secondary metabolites detectable by GC-MS, several attempts have been made to facilitate identification through the construction of combined RI and MS databases of derivatized compounds, generally termed as mass spectral tags (MST) [57]. Retention time indices are a prerequisite for tentative metabolite annotation of mass spectra showing high similarity such as pentoses and hexoses. Recent efforts have focused on the need for extended and comprehensive RI information by compiling RI values of TMS analytes of various phytochemicals including phenolic acids and flavonoids [39,45,51,58,59], diterpenes [49], sterols [51] and tocopherols [32].
Moreover, several research groups and consortia have addressed the complexity of compound structures, since commercially available libraries (e.g., NIST or Wiley) contained insufficient MS information about derivatized analytes, which are frequently acquired in metabolomics experiments. The Golm Metabolome Database GMD [60] comprise today online information of about >4600 MS analyte entries including >3500 analytes with valid spectra (TMS derivatives, tributylsilyl (TBS) derivatives, and isotopically-labeled compounds). However more than 1400 spectra have not been annotated underscoring the need for further chemical information in order to approach the metabolome of plants and other organisms. The downloadable and searchable GMD library contains about 3600 analytes and MST information about 1200 single metabolites. In comparison, the Fiehn GC-MS Metabolomics RTL Library [19] is based on 1400 analyte entries relating to 900 metabolites, while the Massbank database [61] contains 963 MSTs of TMS analytes relating to >700 single metabolites. Hopefully, public repositories of GC-MS-based spectral information such as MetabolomeExpress [62] might help to extend accessible MS library information also including secondary metabolites.
Only those phenolic and cyclic structures which are commonly detectable in derivatized (silylated) samples following GC-MS profiling protocols applied by the majority of metabolomics labs worldwide [1,2,63,64], will be discussed in Subsections 3.1 through 3.6. Information about readily searchable and publicly available MS databases and libraries, providing MS spectra of silylated metabolites, presented and discussed in Sections 3 and 4, will be included in each figure

Simple Phenolics, Aromatic Acids and Related Structures
In most cases phenolic structures are derived from aromatic amino acids such as phenylalanine and tyrosine. Detectable phenolic structures comprise monophenols such as thymol (an aromatic monoterpene), benzyl alcohols, phenylethanoids (e.g., tyrosol), and the coumarins (e.g., umbelliferone) ( Figure 2). The huge class of aromatic acids include benzoic acid and cinnamic acid derivatives with different degree of hydroxylation and methoxylation. Metabolites with vitamin function such as vitamin E (tocopherols) and vitamin K (phylloquinone and menaquinone) represent minor groups of phenolic structures found in food materials. However, tocopherols like α-, β-, γ-and δ-tocopherol are readily detected in biological samples during profiling experiments. More complexly structured monophenolics comprise phenolic diterpenes (e.g., carnosic acid), phenolic amides including the capsaicinoids with capsaicin as well-known representant, the phenolic lipids, e.g., alkylresorcinols, which are commonly found in cereals (wheat, rye, barley and sorghum), but also in certain tree species and bacteria, and finally benzothiazoles which are mentioned in Subsection 3.6.

Polyphenols
The highly diverse group of plant flavonoids comprise flavonols (e.g., kaempferol and quercetin), flavanones (e.g., naringenin and hesperidin), flavones (e.g., luteolin and apigenin), flavan-3-ols (e.g., catechin and gallocatechin), and flavanonols (e.g., taxifolin) ( Figure 3). All these structures, either as aglycon or glycoside, are characterized by a certain number of hydroxy groups which can be silylated. However, due to relatively higher molecular weight of glycosylated polyphenols, the detection and structure elucidation of intact glycosides is preferably achieved on LC platforms, which is also true for hydolyzable tannins. Another closely related group of polyphenols, the phytoestrogens, comprise well-known structures such as isoflavonoids (e.g., genistein and daidzein) commonly found in species of the Fabaceae family, and the lignans (e.g., secoisolariciresinol and pinoresinol) derived from different plant food sources. Also the minor class of stilbenoids, hydroxylated stilbene derivatives such as resveratrol and piceatannol, are readily silylated and detectable if present in appreciable amounts in the sample. In contrast, the important group of anthocyanidins and their glycosylated counterpart, the anthocyanins, show high abundances in fruits and berries but also other plant tissues. These metabolites are normally detected on LC-MS systems not least due to the molecules' positive charge.

Terpenoids and Sterols
The terpenoids including the biosynthetically-derived sterols establish a huge class of secondary metabolites which can be found in diverse organisms (Figure 4). Mono-and sesquiterpenes are volatile and lipophilic metabolites commonly found in high abundances in herbs and spices, conifers and other tree species. The lipophilic phase might preferably be analysed separately prior to GC-MS profiling. However, this step is not always practically feasible, and might result in detection of silylated derivatives of alcoholic mono-and sesquiterpenes, hydroxylated and/or carboxylated di-and triterpenes, and phytosterols including sterols and stanols. Structurally close related is the group of secosteroids including cholecalciferol (vitamin D) and derivatives which are also determined in profiling studies.

N-Containing Cyclic Structures
Alkaloids establish a chemically quite diverse group of basic, nitrogenous secondary metabolites, most of which are characterized by heterocyclic structures (Figure 5). Well-known metabolites include stimulant and/or medicinally significant compounds such as nicotine (based on pyrrolidine/pyridine ring structures), caffeine (a purine), morphine (an isoquinoline), serotonin (an indole), and cocaine (a tropane). Apart from alkaloids, tryptophan-derived indoles establish also the basic ring structures of the plant-hormone related auxines (e.g., indole-3-acetic acid) and several amino acids. Also the cytokinins are N-heterocyclic structures with zeatin (a purine) as an important representative compound. Furthermore, most B-vitamins are built up of N-heterocycles comprising detectable structures such as B3 niacin and B6 pyridoxine (both pyridines), B7 biotin (an imidazole), and B9 folic acid (a pteridine). Importantly, nitrogenous bases, their nucleosides and phosphorylated nucleotides, which are essential components of RNA and DNA in all organisms, are readily detected in profiling experiments. Cyclic structures comprise pyrimidines (thymine, uracil and cytosine) and purines (adenine and guanine). The vast diversity of N-containing cyclic metabolites from plants does not allow to present all structural classes here. However, it is noteworthy that only a minor fraction of potentially detectable compounds is included in MS libraries of silylated compounds.

O-Containing Cyclic Structures
Silylated carbohydrates comprise the largest group of GC-MS detectable oxygen-containing cyclic metabolites. Pentoses and hexoses and oligosaccharides thereof occur in all biological samples showing cyclic structures either as furanoside or pyranoside ( Figure 6). Furan structures, in particular lactones derived from sugar acids (e.g., ascorbic acid) but also amino acids are readily determined. This includes the potentially detection of glycosylated compounds such as terpenes, aromatic structures and purines during profiling experiments. Benzopyran structures have already been mentioned in the context of tocopherols (see subsection 3.1).

S-Containing Cyclic Structures
Though nature produces a vast diversity of S-containing metabolites, only few cyclic structures have been included in MS libraries of silylated compounds. Those mentioned here both include natural products but also compounds which are not biosynthesized by organisms (Figure 7). Lipoic acid and its derivatives represent dithiolane structures with characteristic disulfide bonds in a pentacyclic structure. Though normally covalently bound in mitochondrial enzyme complexes, these compounds might potentially be detected in profiling experiments. This is also true for thiazoles, i.e., pentacyclic N-and S-containing structures, heterocyclic compounds such as natural and synthetic benzothiazoles (e.g., the artificial sweetener saccharin), and S-containing polycyclic thioxanthenes used as photoinitiators (e.g., 2-ITX) in paper and packaging materials.

Case Studies-GC-MS Profiling of Plant Samples
GC-MS is one of the most efficient technology platforms to approach complex mixtures of organic compounds based on a combination of MS database search and the use of calculated RI values. Suitable MS and RI resources have been developed and are well established for the analysis of e.g., essential oil constituents [67][68][69], and investigation of environmental samples using either the comprehensive NIST or Wiley MS libraries or vendor-specific and customized databases. In the case of silylation-based derivatization techniques which cover a broad range of molecular masses and different polarities, the information base regarding phenolic and other cyclic structures, belonging to the complex group of plant secondary metabolites, is rather limited. This is particularly true for higher molecular weight compounds (≥300) as pointed out by Isidorov and Szczepaniak [39]. However, the specificity of molecular structures and thus MS fragmentation patterns in most cases allow for the assignment of distinct compound groups and sub-classes.
In the following Subsections from 4.1 to 4.4, these aspects will be addressed by using examples from the analysis of various plant raw materials and processed plant food to emphasize the applicability of GC-MS profiling for the separation, detection and identification of phenolics and cyclic structures with respect to metabolic phenotyping and quality assessment purposes. Extraction, derivatization and GC-QMS conditions followed procedures for plant samples as described earlier [35,[70][71][72].

Fresh Plant Samples: Flavonoids and Derivatives
Flavonoids represent a highly diverse class of polycyclic secondary structures commonly found in the plant kingdom. In addition to their function as pigments for insect attraction, seed dispersal and UV light absorption, flavonoids serve as antioxidants and radical scavengers, in plant signaling and as defense compounds. Chemically, flavonoids are characterized by a C6-C3-C6 flavone skeleton (A-C-B rings) enclosed with oxygen in the 3-carbon bridge (C-ring) between the phenyl groups. The different sub-classes of flavonoid structures include flavones, flavonols, flavanones, flavanols, flavanonols, anthocyanidins, isoflavones, chalcones and neoflavonoids, as reviewed by Tsao and McCallum [73].
Depending on desaturation and oxidation status of the C-ring and moreover, hydroxylation, methoxylation, and/or prenylation patterns of the flavone backbone (for examples refer to Figure 3), EI-based fragmentation is expected to generate quite stable MS fragments with distinct molecular masses, thus providing sufficient identification capability for structure elucidation.
Strawberry (Fragaria × ananassa Duch.) is renown as a marketable fruit due to its pleasant taste and flavour [74], and its high content of health-beneficial polyphenolic compounds [75][76][77]. Also other plant parts of different Fragaria species were shown to contain high levels of phenolic structures as studied in flowers [78], leaves [79,80] and roots [81,82]. Moreover, GC-MS profiling has been recently applied for the characterization of shifts in metabolite pools in leaf and crown tissue of strawberry plants exposed to cold temperatures [70,72,83] in order to identify those compounds uniquely linked to cold acclimation. Published chemical information was related to primary metabolites in the first place, however a large number of secondary structures could be deduced easily based on the available high-resolution MS information from crown [83], and leaf and root samples [72]. Besides cinnamic acid-and benzoic acid-derived structures, vegetative tissue contains reasonable amounts of flavan-3-ols (catechin derivatives) and flavonols as presented in Figures 8 and 9.

Plant-Based Aquafeeds: Phenolic Acids
Fish feeds are formulated from marine (fish meal and oil), animal (e.g., blood meal and poultry by-products), and plant (e.g., starchy grains, protein meals, and oils) feedstuffs, and additional amino acid and micronutrient supplements. Due to limited resources of fishmeal and fish oil and the over-exploitation of wild fish stocks, plant feedstuffs derived from seeds are considered more sustainable, cost efficient and highly valuable as protein ingredients in aquafeeds. On the other hand, seeds contain well-characterized and supposedly unknown phytochemicals (secondary metabolites), which might impair appetite, nutrient utilization, physiology, fish health and growth [84], particularly in carnivorous fishes.
Therefore, these substances are also termed as antinutritional factors (ANF) because of their non-nutrient function [85]. In a recent study, GC-MS-based metabolite profiling was applied in order to gain detailed chemical information about plant derived feedstuffs with regard to nutritious small molecules (carbohydrates, lipids, amino acids and amines) and simultaneously potential ANFs [35], comprising compounds from diverse structure groups such as phenolics, alkaloids, terpenes, and glycosides. Protein-rich seeds from the legume plant family (e.g., soybean and pea) or refined plant ingredients derived from industrial processes after vegetable oil or starch extraction (e.g., sunflower, rapeseed and corn) represent good sources of plant proteins ( Figure 10). Despite industrial refinement and concentration steps, plant ingredients such as sunflower meal, soy protein concentrate and corn gluten might still contain reasonable amounts of free and bound phenolic ANFs due to interactions with polysaccharides and/or proteins [86], showing a broad spectrum of compounds derived from benzoic acid, cinnamic acid and phenyl ethanol ( Figure 11). Relatively high levels of vanillic acid (20-100 mg/kg), syringic acid (40-150 mg/kg), (E)-ferulic acid (20-60 mg/kg) and sinapic acid (20-60 mg/kg) were found in soybean meal and thus, underscore the potential ANF content related to non-flavonoid phenolics ranging between 660 to 2000 mg/kg in dehulled beans [87]. In comparison, sunflower seeds are known to contain relatively high levels of mono-and diacylquinic acids [88], which might negatively affect taste and nutrient uptake in humans [89]. Levels of different caffeoylquinic acid structures including chlorogenic acid in sunflower meal ( Figure 11) ranged between 600 to 2200 mg/kg and compared well with reported estimates in literature e.g., [90,91].

Cereals: Alkyresorcinols
Cereal grains (wheat, rye, barley and oat) constitute one of the major sources of staple foods for human consumption worldwide due to their nutritious content of carbohydrates, proteins and lipids, also including minerals, vitamins and dietary fibre. Moreover, recent epidemiological studies have shown that intake of whole grain products is positively linked to prevention of metabolic syndrome, obesity, cardiovascular disease and type 2 diabetes [92]. Despite relatively high concentrations of phenolic antioxidants in fruits and berries, the impact of levels of phenolic compounds in grain products and cereals on human health is underestimated. In other words, based on Western food traditions the intake of health-beneficial plant phenolics is not necessarily and primarily based on the consumption of fruits and vegetables. Cereal products contain relatively high levels of benzoic acid and cinnamic acid derivatives [93], either free or in bound form esterified with cell wall components. Based on data from the multinational HEALTHGRAIN study, wheat, rye and oat grain show comparable levels of phenolics, while concentration levels in barley are somewhat lower [94].
The so-called alkylresorcinols (AR) establish a characteristic sub-class of phenolic compounds found in cereals. ARs are based on a 1,3-dihydroxy-5-alkylbenzene structure being linked with an odd-numbered alkyl or alkenyl chain (C17:0 to C25:0) [95][96][97], and have been suggested to be used as biomarkers for the estimation of whole grain consumption in humans [98]. Due to their unique chemical structure, ARs show distinct EI-MS fragmentation patterns generating a base peak of m/z = 268 and a molecular ion (M + ) peak, depending on the length and degree of saturation of the side chain ( Figure 12). These molecular features facilitate the straight-forward detection and identification also in comprehensive GC-MS metabolite profiles. Detected levels of ARs in industrially-processed grain and bakery products were clearly depending on coarseness and declined with the degree of refinement. AR levels in bread ranged from 10 to 300 mg/kg dry weight (DW) and 200 to 300 mg/kg DW in wholemeal bread, while levels in low-processed four-grain meals were estimated at 500 to 650 mg/kg DW, thus corresponding well with results from other studies [46,91,[95][96][97].

Olive Oil: Simple Phenolic Structures and Secoiridoids
Olive oil is a vegetable oil produced from fruits of the olive tree (Olea europaea L.) and its subspecies. The olive tree is a traditional wood species in Mediterranean countries, the main production region in the world, but olive oil is also produced in Asia, the Americas and Australia. The oil is commonly used in cooking, cosmetics, pharmaceuticals, soaps and as a fuel for oil lamps. Olive oil is considered as a highly-valuable and healthy oil because of its high content of glyceridic-bound monounsaturated fatty acids, mainly oleic acid (C18:1), linoleic acid (18:2) and α-linolenic acid (C18:3). In addition, olive oil contains sterols, triterpenic compounds, aliphatic alcohols and esters, and reasonable amounts of different phenolic structures. Tyrosol and its derivatives, namely oleuropeins and ligstrosides, represent characteristic phenolic structures found in olive exerting health-beneficial effects as reported by the European Food Safety Authority (EFSA) [99]. Other commonly detected phenolic compounds comprise hydroxybenzoic-, hydroxycinnamic-and hydroxyphenylacetic acids, lignans and flavonoids [91]. Phenolic patterns found in olive oil can be used to study regional and varietal differences [100], and effects of oil production and processing [101]. Different approaches towards extraction and chromatographic separation have been described [102,103], also including derivatization methods following GC-MS for the analysis of olive and other vegetable oils [41,[104][105][106].
The quality of olive oils is mainly based on extraction and processing conditions, and distinct quality parameters such as acidity, taste and flavour characteristics. According to the classification system of the International Olive Council, oils can be divided into extra-virgin, virgin and the chemically-treated refined oils which all are originally obtained by pressing, and the solvent-extracted pomace oils. Depending on the physical and chemical extraction and processing steps utilized, the content and composition of phenolics shows a high degree of variation. Extra virgin oils often show two to three times higher levels of phenolic compounds compared to refined oil qualities [91].    As an effect of oil processing, refined oils generally show higher abundance of simple tyrosol structures due to the degradation of oleuropeins and ligstrosides. On the other hand, oleuropein and ligstroside content is generally much higher in extra-virgin and virgin oils, not uncommonly exceeding levels above 300 mg/kg. Based on a quality screening of different commercially available olive oils and olive extracts, variations in phenolic metabolites could easily be characterized using liquid-liquid extraction techniques and compound derivatization. Due to EI fragmentation patterns, secoiridoid aglyca could be easily traced using selected ion monitoring (SIM) plots depicting the distinct MS base peaks related to ligstroside (m/z = 192) and oleuropein (m/z = 280) structures ( Figure 13). A total of 55 phenolic metabolites and three other cyclic structures could be detected, of which 28 compounds were tentatively identified based on a combination of MS database search and retention index values ( Table 2).

Conclusions
GC-MS is frequently applied to characterize the chemical complexity of analytical samples based on its separation and identification capacity. Recent developments in GC-MS technology have facilitated global metabolomics approaches in order to approach biological functions and perturbations of biological systems, and for diagnostics and quality assessment purposes. However, one should be aware of the limitations of global GC-MS metabolite profiling. Processing, automated sample handling, and analysis conditions need to be strictly defined and controlled in order to minimize data variation and allow for quantitative calculations. When using standard protocols which are adapted to cover a broad range of biochemical structures, single metabolites or groups of compounds might be discriminated due to generalized compound extraction and derivatization conditions and thus, negatively affect compound recovery rates. Moreover, GC-MS analysis of highly complex mixtures of derivatized metabolites might impair separation and detection capacity with regard to the level of confidence in compound identification due to co-eluting peaks and similarity of MS spectra. For determination of absolute metabolite concentrations, the use of standard compounds is required, otherwise targeted methods need to be applied for the proper quantitation of compounds of interest. Despite limitations in GC-MS with respect to the mass range and polarity of metabolites, the utilization of derivatization techniques and automation technology have extended the range of separable and detectable compounds in high-throughput profiling experiments. Beside the qualitative and quantitative analysis of trimethylsilyl derivatives of highly abundant compounds found in plant samples such as sugars, amino acids and polyols, instrument sensitivity and resolution also allows for the successful detection of minor constituents such as plant secondary metabolites. Even though mass spectral information about monophenolic, polyphenolic and other cyclic compounds in MS libraries is limited, structure-specific MS fragmentation patterns enable to trace and identify low-concentration metabolites, often based on and in combination with published MS data from targeted GC-MS analyses. Current limitations in MS-based metabolomics due to the relatively small number of compounds included in MS databases, in particular secondary metabolites, and hurdles in compound identification, might be overcome by on-going and future efforts. These include in silico derivatization, retention indices and mass spectra matching [107], in silico enzymatic synthesis of biochemical compounds for non-targeted metabolomics [108], and endeavours such as web-based and shared collections of experimental metabolomics datasets, MS spectra and RI values for the processing and interpretation of GC-MS data [62]. Based on experimental data from own research, the present review has emphasized the capabilities of GC-MS to deduce chemical information on phenolics and cyclic compounds found in complex mixtures of plant metabolites.


s2fieldsofstudy:
Chemistry
Materials Science

text:
Synthesis, binding and self-assembly properties of a well-defined pillar[5]arene end functionalised polydimethylacrylamide

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction
The amalgamation of polymer and supramolecular chemistry has led to the development of fascinating self-assembling polymeric materials with bespoke structures and tuneable properties. 1,2 The incorporation of non-covalent recognition motifs into polymeric systems offers the unique opportunity to tune polymer structures (e.g., topology and morphology) and to impart unique additional properties, including self-healing, 3 adaptability 4 and responsiveness [5][6][7] to materials. Furthermore, the non-covalent modification of polymers has allowed their solubility and correspondingly their processability to be greatly improved. 8,9 The development of this field has largely gone hand-in-hand with the enormous progress that has been made in the development of well-defined polymers synthesised using controlled radical polymerisation (CRP) techniques that feature specific recognition motifs (hydrogen acceptor/donor, 10,11 ionic unit, 12,13 metal/ligand, 14,15 host/guest [16][17][18] molecules) attached in specific locations (end or side chain) to polymer backbones. Pillar[n]arenes (n = 5, 6, 7, 8…) have emerged as important host units for the construction of supramolecular assemblies with applications spanning materials, 19,20 medicine 21-23 and sensing. 24,25 Their burgeoning interest as macrocyclic hosts relies mainly on their convenient synthesis, 26 ability to be conveniently functionalised and their unique symmetrical and rigid electron-rich pillar architecture that enable various neutral and electron-deficient guests to be accommodated within their cavities. [27][28][29][30] Due to the hydrophobic nature of these macrocycles, host-guest complexation and self-assembly of pillar[n]arene derivatives has been largely investigated in organic media. However, as many recognition events in nature occur in aqueous media, effort has also been directed towards the development of pillararene based receptors capable of recognizing guests in aqueous environments. In this context, the main strategy consists of grafting hydrophilic groups, such as carboxylate, 31 39 and creating gel-like supramolecular networks. 40 Here, we describe the synthesis of a trithiocarbonate-type RAFT agent MePilla-CTA incorporating a partially methylated pillar [5]arene moiety and its propensity to control the polymerisation of DMAC (Dimethylacrylamide) and, therefore, to produce a well-defined methylated pillar [5]arene end functionalised polydimethylacrylamide (PDMAC) (MePilla-PDMAC) (Scheme 1). An interesting characteristic of the PDMAC type chain is that it imparts solubility in both aqueous and organic solvents to the methylatedpillar [5]arene scaffold. This feature was exploited to specifically and reversibly end-modify MePilla-PDMAC (M n , NMR = 14 500 g mol −1 , Đ = 1.1) with electron deficient partners (G1 and G2) through host-guest complexation both in organic and aqueous media. Preliminary self-assembly properties of MePilla-PDMAC in water are also described.

Results and discussion
The RAFT agent MePilla-CTA was conveniently prepared by coupling the N-hydroxysuccinimide (NHS) activated ester of the trithiocarbonate 2-(1-isobutyl)sulfanylthiocarbonylsulfanyl-2-methylpropionic acid (CTA-NHS) 41     Control over molecular weight was also demonstrated by the linear increase of M n versus DMAC conversion and dispersity (Đ) values of the resulting polymers of 1.1-1.3 (Fig. 2b). SEC analysis also revealed polymers with symmetrical traces (Fig. S4 †) and experimental molar masses in accordance with theoretical values, indicating that the number of chains is governed by the RAFT agent concentration which remained constant during the polymerisation. The pseudo-living character of the RAFT polymerisation was also evidenced by restarting the polymerisation of DMAC from a macromolecular RAFT agent (M n , SEC = 22 260 g mol −1 ) which gave rise to a well-defined polymer with a higher molar mass (M n , SEC = 59 500 g mol −1 ) with a narrow molecular mass distribution (Đ = 1.3) (Fig. S5 †).
The 1 H NMR spectrum recorded in CDCl 3 of MePilla-PDMAC (Fig. 3) clearly shows the presence of the pillararene unit connected to polymer chains with the presence of characteristic resonances of H 1,2 (δ = 6.7 ppm) and H 3 (δ = 3.7 ppm) belonging to the host unit and PDMAC chains (0.8 < δ < 3.2 ppm). This was further confirmed by performing 2D diffusion-ordered spectroscopy (DOSY) 1 H NMR experiments that showed a single diffusion coefficient value of 0.6 × 10 −10 m 2 s −1 at 298 K for the aforementioned protons in CDCl 3 .
An interesting characteristic of the PDMAC type chain is that it imparts solubility in water and organic solvents to the methylatedpillar [5]arene scaffold, thereby allowing binding properties of MePilla-PDMAC to be investigated in both aqueous and organic media. The complexation properties of MePilla-PDMAC were first investigated by 1 H NMR spectroscopy in CDCl 3 (Fig. 4A) and D 2 O (Fig. S6 †) in the presence of G1 and G2 as guest molecules, respectively. In both cases, a broadening and a shielding effect for the resonances of protons of the guest and host partners were observed. This is particularly noteworthy for H a-1 , H b-1 , H c-1 of G1 that show upfield shifts of 0.3, 2.2, 3.6 ppm upon complexation in CDCl 3 , respectively. A slight downfield shift (+0.05 ppm) was also observed for H 1,2 protons of MePilla-PDMAC. A similar trend was evidenced for H c-2 and H d-2 of G2 that shift upfield by 0.3 and 3.2 ppm in D 2 O, respectively, upon the addition of an equimolar solution of MePilla-PDMAC (Fig. S6 †).
To further prove the ability of MePilla-PDMAC to form pseudorotaxane-like complexes with G1 and G2, 2D-NOESY (Fig. S7 †) and 2D-DOSY (Fig. 4B) experiments were undertaken. As expected, correlations between most aromatic and alkyl protons of guest molecules G1/G2 and protons located on the host unit were observed, suggesting the formation of pseudorotaxane architectures between MePilla-PDMAC and G1 and G2. 2D-DOSY experiments showed that H 1,2 protons of MePilla-PDMAC were not impacted in terms of diffusion coefficient by the presence of the significantly smaller guest molecules G1 and G2. On contrary, the diffusion coefficient values of H a-1 and H c-2 of G1 and G2, respectively, were dramatically affected upon complexation and moved to much lower and almost identical values to those obtained for MePilla-PDMAC in the different media, thereby further demonstrating the formation of complexes. Finally, association constants for MePilla-PDMAC complexing with G1 and G2 were estimated by 1   ments and were found to be 0.9 (±0.1) × 10 2 (Fig. S8 †) and 1.5 (±0.1) × 10 3 M −1 (Fig. S9 †), respectively, by employing a nonlinear fitting method using one-site binding models. In addition, the 1 : 1 binding mode was further evidenced through the continuous variation method (Job plot method) using 1 H NMR spectroscopy (Fig. S10 †). With complexation confirmed for MePilla-PDMAC·G1 and MePilla-PDMAC·G2 in chloroform and water, respectively, we next turned our attention to whether complex formation of this type could be controlled by applying an external stimulus. First, we investigated the opportunity to switch off the complexation between MePilla-PDMAC and G1 in chloroform by adding chloride anions. Indeed, Huang 43 and Wang 24 have recently demonstrated that pillar [5]arene based complexes could be dissociated in chloroform by adding tetrabutylammonium chloride (TBACl), leading to the exchange of the soft counter ion PF 6 − of the guests by a hard counter ion Cl − and the formation of an intimate ion pair between ammonium cations and Cl − . Fig. 5A shows the evolution of chemical shifts corresponding to the MePilla-PDMAC·G1 complex in the presence of an excess of TBACl. As expected, a disassembly process between G1 and MePilla-PDMAC can be observed through a downfield and upfield shift of H a-1 and H 1,2 protons, respect-ively, that move toward the resonances observed for the uncomplexed G1 and MePilla-PDMAC.

H NMR (in CDCl 3 ) and fluorescence (in H 2 O) titration experi-
Next, we have explored the effect of heating the MePilla-PDMAC·G2 complex using variable-temperature 1 H NMR (Fig. 5B) and 2D-DOSY experiments (Fig. S11 †). As shown in Fig. 5B, a clear gradual downfield shift in the resonances of H a-2 , H b-2 , H c-2 of G2 with a concomitant sharpening of NMR signals for both guest and host moieties was observed. This is particularly noticeable for H a-2 and H c-2 which spilt into two distinct and sharp signals at 340 K, which is similar to the resonances observed in the NMR spectrum of the uncomplexed G2. Moreover, a similar behaviour was evidenced by estimating diffusion coefficients for H c-2 and H 1,2 versus temperature. Indeed, while D(H 1,2 ) remained almost identical with temperature, D(H c-2 ) increased progressively from 300 to 340 K and then rose sharply above this temperature, thereby suggesting a disassembly of the complex (Fig. S11 †). To confirm this dissociation with temperature, VT-fluorescence studies were carried out on the uncomplexed MePilla-PDMAC and the MePilla-PDMAC·G2 complex. While the complexed MePilla-PDMAC shows a much lower relative fluorescence intensity than the free MePilla-PDMAC at 300 K, above 340 K both species display a nearly identical relative fluorescence intensity to their non-complexed states, thereby suggesting the dissociation of the MePilla-PDMAC·G2 upon heating (Fig. S12 †).
Having demonstrated that the methylatedpillar [5]arene moiety was located at one end of PDMAC chain, and that specific non-covalent modification with electron deficient guests was possible, we next investigated the impact of the presence of the hydrophobic pillarane unit on PDMAC chains and host-guest complexation has on the self-assembly properties of MePilla-PDMAC in water. DLS (Fig. 6A) and cryo-  TEM (Fig. 6B) experiments were carried out on MePilla-PDMAC which revealed the existence of nanosized aggregates with an average hydrodynamic diameter (<D h >) of 24 nm ( poly: 0.02) corresponding to micelle-like aggregates (according the cryo-TEM). Hence, these results clearly indicate that the hydrophobic behaviour of methylatedpillar [5]arene moiety can be exploited to create self-assembled architectures when connected to hydrophilic polymers. The critical aggregation concentration (CAC) in water was estimated to be 0.5 mg mL −1 based on the dependence of the fluorescence intensity of MePilla-PDMAC versus its concentration (Fig. S13 †). Interestingly, VT-DLS experiments performed on MePilla-PDMAC and its complex MePilla-PDMAC·G2 indicated that both complex formation and temperature had no effect on the size distribution of micelles (Fig. S14 †). Therefore, taking into account that above 340 K, VT-NMR ( 1 H) experiments performed (at the same concentration as the VT-DLS measurements) on MePilla-PDMAC·G2 (Fig. 5B) indicated the dissociation of the complex, and that VT-DLS investigations demonstrated the persistence of micelles upon heating, the micelle-like architectures prepared from MePilla-PDMAC appear to have the propensity to bind, and then to release on demand upon heating, the electron deficient guest G2 (Fig. 6C).

Conclusions
In conclusion, we have described the synthesis of a trithiocarbonate type RAFT agent incorporating a partially methylated pillar [5]arene moiety. By using this specifically designed RAFT agent, the polymerisation of DMAC was found to be controlled, affording a well-defined dimethypillarene end-decorated PDMAC. This polymer has the ability to recognize, in a reversible manner, electron deficient guests both in organic and aqueous media. Furthermore, the hydrophobic nature of the pillararane unit has permitted the self-assembly of MePilla-PDMAC in water into micelle-like aggregates displaying reversible recognition properties. Since the RAFT procedure may be applied to the synthesis of a range well-defined macromolecular architectures, this study paves the way for the development of other pillararene-polymer conjugates with new applications.


extfieldsofstudy: Chemistry Medicine

text:
Redetermined crystal structure of N-(β-carboxyethyl)-α-isoleucine

Redetermination of the crystal structure of N-(β-carboxyethyl)-α-isoleucine, C9H18N2O3, reported earlier by Nehls et al. [Acta Cryst. (2013), E69, o172–o173], was undertaken in which the ionization state assigned to the molecule as unionized has been modified as zwitterionic in the present work. Single-crystal X-ray intensity data obtained from freshly grown crystals and freely refining the amino H atoms provide enhanced refinement and structural parameters, particularly the hydrogen-bonding scheme. N—H⋯O hydrogen bonds dominate the intermolecular interactions along with a C—H⋯O hydrogen bond. The intermolecular interaction pattern is a three-dimensional network. The structure was refined as a two-component perfect inversion twin.

S1. Introduction
Amino acids in their free form exist as 'zwitterions′ in their crystals with a deprotonated carboxyl group (COO-) and a protonated NH 3 + group (NH 2 + in proline). Any deviation from this general preferences of amino acids is worth careful considerations. The motivation for the present work is the unionized state reported by Nehls et al., 2013, for the title compound in contrast to the usually preferred 'zwitterionic′ state. In this context, redetermination of the crystal structure of the title compouned was undertaken.

S2.2. Refinement
Coordinates were refined for amino H atoms; other H atoms were positioned with idealized geometry, with fixed C-H = 0.98 (methyl), 0.99 (methylene) or 1.00 Å (methine). U iso (H) values were set at 1.2U eq of the carrier atom or at 1.5U eq for methyl and amino groups. The absolute configuration could not be determined by anomalous-dispersion effects in the X-ray diffraction measurements of the crystal, but assigned as L-based on an unchanged chiral centre in the synthetic procedure. The absoulte structure was refined as a perfect inversion twin. Nehls et al., (2013) seem to have presumed an unionized state for the title compound with an undissociated carboxyl (COOH) and a deprotonated amino (NH) group. A scrutiny of the work by Nehls et al. revealed that all the H-atoms, including the donor group H atoms were assigned an idealized geometry and refined as riding on their respective non-H atoms to which they are attached. Redetermination of the crystal structure carried out by measuring X-ray intensity data from freshly grown crystals and freely refining the amino-H atoms clearly indicate that the title compound indeed exist as a zwitterion. The correct assignment of the ionized state provided enhanced refinement and structural parameters. Thus, the present redtermination demonstrates the importance of freely refining donor group hydrogens. The S,S (equivalently L-) absolute configuration is deduced from the synthetic pathway as the starting material involved L-isoleucine. The absoulte structure was refined as a perfect inversion twin in order that the Flack x (Flack, 1983;Flack & Bernardinelli, 2000;Parsons et al., 2013) and Hooft y parameters (Spek, 2009) showed good agreement.

S3. Results and discussion
The correct assignment of the ionization state to the title compound as 'zwitterion′ presents an acceptable description of the intermolecular interaction patterns with all the amino-H atoms participating in them. The carboxylate O1 atom of the amino acid derivative participates in a strong head-to-tail N-H···O hydrogen bond characteristic of amino acids, in addition to a C-H···O hydrogen-bond as acceptor. This has consequently resulted in the lengthening of the C6- hydrogen-bonds within themselves leading to C 3 2 (8) chains linking screw related molecules along the shortest a-axis. The respective amino and carboxylate group N and O atoms form characteristic head-to-tail hydrogen-bonds leading to a layers parallel to the ab-plane. The intermolecular interaction pattern is a three-dimensional network dominated by N-H···O hydrogen bonds, in addition to a C-H···O hydrogen-bond involving the α-carbon atom (C2) as donor and the carboxylate O1 as acceptor.

Figure 1
Thermal ellipsoid plot of the title compound, showing the atom numbering scheme.

Figure 2
The characteristic head-to-tail N-H···O hydrogen bonds involving the carboxylate and the amino groups. Non pariticipating N-carboxyethl group atoms have been omitted for clarity.  Carbamoyl group N2 and O3 forming N-H···O hydrogen-bonds within themselves leading to C32(8) chains linking screw related molecules along the a axis.


text:
One-Pot Cannizzaro Cascade Synthesis of ortho-Fused Cycloocta-2,5-dien-1-ones from 2-Bromo(hetero)aryl Aldehydes

An intramolecular Cannizzaro-type hydride transfer to an in situ prepared allene enables the synthesis of ortho-fused 4-substituted cycloocta-2,5-dien-1-ones with unprecedented technical ease for an eight-ring carboannulation. Various derivatives could be obtained from commercially available (hetero)aryl aldehydes, trimethylsilylacetylene, and simple propargyl chlorides in good yields.

Readily(oftencommercially)available2-bromo(hetero)aryl aldehydes (1,S cheme 1) constitute powerful and popular units for the construction of ortho-fused carbocyclic rings. [1] Tw os trategies commonly employed in the multitudinous syntheses described in the literature involve 1) the derivatization of 1 to intermediates of type A,w ith a p-system attacking an electrophile that is ultimately derived from the aldehyde by functional-group manipulations (e.g., an alcohol, acetal, or even the aldehyde itself);o r2 )formyl group homologation to an anion-stabilizing unit that attacks as uitably activated p-bond (B). Whereas many elegant catalytic systems that use intermediates A or B have already been described, [2,3] thep reparation of the suitable precursors is often step-intensive,r aising questions on the overall process efficiency in the "age of sustainability". [4] We speculated that an ew annulation strategy,b ased on aC annizzaro-type reaction via intermediate C,might be possible.Asthe hydride transfer simultaneously exposes apowerful Michael acceptor (ynone or equivalent) and ac arbanion in close proximity, efficient annulation might be expected to occur (especially if C is directly attained in situ). Herein, we describe the use of such as trategy for the formation of eight-membered rings. Thep aucity of direct single-pot/step procedures to such medium rings attests to the known issues associated with their synthesis; [5] they therefore provide as tringent test for strategy C. Although redox-based Cannizzaro reactions, including asymmetric and triggered C À Cb ond-forming versions,h ave recently been developed, [6] to the best of our knowledge,they have not been employed for carboannulation reactions to medium rings.G enuine single-pot/step procedures to eight-membered rings are very limited-Reppes historical catalytic access to cyclooctatetraene [7] and Murakamis [4+ +2+ +2] approach [8] being notable exceptions.Modern alternatives frequently describe catalytic cyclizationst hat proceed with exquisitely high yields (for the final step). Unfortunately,t heir overall synthetic efficiency is often compromised by the multistep syntheses required to obtain the cyclization precursors. [9] Initial investigation of our own proposal (C) centered on the combination of readily available 2-bromobenzaldehyde (1a), trimethylsilylacetylene (2a), and propargyl chloride 3a.
Encouragingly,e ven an initial run returned significant amounts of benzo [8]annulene derivative 4aaa (Table 1, entry 1, ca. 7%)w hose identity and regiochemistry was confirmed by X-ray crystallography (see the Supporting Information) as initial NMR data was not conclusive. [10] Unfortunately,u nder the conditions of entry 1, multiple side products were also produced. Upon changing from an organocopper to an organocuprate formulation (entry 2), the reaction became much cleaner, but the yield of 4aaa remained low.T he recovered side products of entry 2 included significant amounts of the alcohols 5a and 6a together with unreacted 3a.W ecould confirm that formation of D was almost quantitative in < 20 min under all conditions tried (Et 2 Oo rT HF, À78 to 0 8 8C, based on recovered 5a in independent reactions). We therefore suspected issues associated with both nBuLi-halogen exchange from D and the copper-promoted S N 2' reaction leading to the progenitor for eight-ring formation. Further experiments were designed to probe these hypotheses (Table 1).
With an optimized procedure for the preparation of parent compound 4aaa in hand, we studied the scope of the reaction with respect to the 2-bromo(hetero)aryl aldehyde component 1.U sing the conditions of entry 4( Table 1) and aldehydes 1b-1j,the eight-ring compounds that are shown in Scheme 2w ere attained. Substitution at the 3-position was better tolerated than at the 1-and 4-positions (products 4baa/ 4caa vs. 4daa/4faa). Monosubstitution at the 2-postion was also tolerated. Ac omparison of the yields of 4baa-4gaa indicates that steric factors are more important than electronic ones;for example,intramolecular OMe steric contacts increase the ortho steric profile of 4eaa versus 4jaa.T he yields of compounds 4haa-4jaa also support this trend. Whereas the yields of 4aaa-4jaa are modest, it should be borne in mind that they represent one-pot processes to analytically pure crystalline products on up to multigram scales,u sing only inexpensive commercial starting materials. Thenew process compares very favorably to the consolidated yields and time efficiencies of previously reported eight-ring syntheses. [9] By varying the acetylene component using the readily attained starting materials 2b-2f,f ive further examples of eight-ring compounds 4 were synthesized (Scheme 3). The terminal alkyne substituent could encompass alkyl, vinyl, or aryl units,a nd the corresponding products were all obtained in acceptable yields.F inally,v ariation of the propargyl chloride was investigated using simple 3b-3i (Scheme 3). Thea ryl moiety could accommodate both electron-donating and -withdrawing substituents and some functional groups (4aae and 4aaf).

Angewandte
Chemie is presumably placed in close proximity to the potent ynone Michael acceptor,w hich leads to efficient ring closure.T he use of an aryl moiety as the R 2 substituent is apparently sufficient to stabilize the allyl anion and allow the necessary trans to cis isomerization. Protonation of the non-classical enolate G results in the formation of 4.S everal pieces of evidence support this chain of events.F irst, attempts to use 2-thienylcyanocuprates derived from ar elated aza substrate led to the isolation of 7 (X-ray structure) where the intermediate allene has been carbometalated rather than having accepted ah ydride.F or the formation of 4iaa,w e could isolate appreciable amounts of 8,which is the expected product of aC annizzaro-type hydride transfer without subsequent annulation. Use of the deuterated aldehyde 2-BrC 6 H 4 CDO ([D]-1a)led to the formation of the expected product [D]-4aaa,c onfirming the participation of the aldehyde in the Cannizzaro process. Them echanistic proposal shown in Scheme 4w as also probed by DFT calculations at the M06-2X/6-31G(d) and CBS-QB3 levels of theory [11] on the "metal-free" anions anti-C' ' and syn-C' ' (Scheme 5; see also the Supporting Information). Whereas the relationship of anti-C' ' and syn-C' ' to the reaction coordinate of the true organometallic species involved in the cascade process needs to be treated with caution, it does provide further evidence for the proposed mechanism. Thec alculated barriers for the Cannizzaro-type hydride transfer and the rearrangement of the allyl anion (the equivalent of the transformation of C' ' into F in Scheme 4) were approximately 5a nd 7kcal mol À1 ,r espectively.T he calculations also indicate that non-classical enolates of type G are favored in the reaction over the equivalent allenoate structures.This idea was further reinforced by the observation that trapping of the reaction intermediates with iodine, iodomethane,o rc arbon dioxide,a so pposed to ap roton, leads to the formation of derivatives 9-11 (Scheme 5).
To the best of our knowledge,t his Cannizzaro-triggered cascade process is unique.T he nearest analogues that we could find are cyclizationsr eported by the Oonishi and Sato groups; [9b,d] however, in these cases,t he allene intermediate must be separately synthesized, and no Cannizzaro-type process is involved. Similarly,asingle eight-ring side product (formed in 10 %y ield) was obtained by Alajarin and Vidal through a1 ,5-hydride shift/8p electrocyclization from an eutral 1,2-allenylacetal at 110 8 8C. [12] Again, no Cannizzaro-type trigger was proposed. Whereas Cannizzaro shifts have been used for oxidation-state manipulations in ortho-fused systems, in these processes,noa nnulation steps were involved. [13] The most similar ynone eight-ring closure process that could be identified was developed by Schreiber and Kelly, [14] but this transformation involves an alkoxide nucleophile.
In conclusion, we believe that this very simple formation of ortho-fused cycloocta-2,5-dien-1-one units demonstrates the potential of the developed method for rapid and efficient annulations.I nvestigations into extending the scope of both the present reaction and other variants are ongoing. development and demonstration (308768). J.R. is grateful to European Thermodynamics Ltd and the Engineering Physical Sciences Research Council (EPSRC) for provision of as tudentship.L .B.t hanks the EPSRCs National Service for Computational Chemistry (NSCCS) for providing computational facilities,a nd O.K. acknowledges aK ishore Va igyanik Protsahan Yojana (KVPJ) Fellowship.


Phonon study of rhombohedral BS under high pressure

Raman spectra of rhombohedral boron monosulfide (r-BS) were measured under pressures up to 34 GPa at room temperature. No pressure-induced structural phase transition was observed, while strong pressure shift of Raman bands towards higher wavenumbers has been revealed. IR spectroscopy as a complementary technique has been used in order to completely describe the phonon modes of r-BS. All experimentally observed bands have been compared with theoretically calculated ones and modes assignment has been performed. r-BS enriched by 10B isotope was synthesized, and the effect of boron isotopic substitution on Raman spectra was observed and analyzed.

Introduction
Boron and its compounds are of great interest due to a rich variety of remarkable properties, which are of both fundamental and technological interest. Among these properties are high hardness and mechanical strength, low density, high melting temperatures, extraordinary chemical and thermal stability, etc., that can be explained by the structures of boron-rich solids consisting of three-dimensional rigid network of B12 icosahedra [1]. However, boron compounds are not limited to the B12-based structures. Recently new boron sulfides have been synthesized at high pressure i.e. r-BS [2], B2S3 (II) and B2S3 (III) [3]. B2S3 (III) has a tetragonal structure (space group I41/a) based on BS4-tetrahedra, while r-BS is a layered compound with γ-GaS structure (space group R3m, C3v point group). r-BS was revealed to be layered semiconductor (estimated band gap value is 3.4 eV [2]), one layer being built by B-B pairs aligned along the c-axis, placed between hexagonal layers of S atoms (Fig. 1), rotated by /3 relative to each other. The bonding scheme is hence the same as that of the A III B VI layered compounds, i.e. strong covalent intralayer bonds and weak Van der Waals interlayer bonds. Hence, the physical properties of r-BS should be affected by its anisotropic structure. Unlike other A III B VI semiconductors (GaS, GaSe, InSe, etc.) [4][5][6][7][8][9], the properties of r-BS are very ill-studied, especially, under pressure.
Raman and IR spectroscopy is powerful tools to study vibrational properties of solids and their modifications due to structural defects isotopic composition, which is of particular importance in the case of boron compounds [10][11][12]. In this paper we report Raman and IR studies of r-BS at PACS: 62.50.-p; 61.50.Ks; 63.20.D-; 63.20.dd * Corresponding author: vladimir.solozhenko@univ-paris13.fr ambient and high (up to 34 GPa) pressure. Experimental results have been compared with calculated phonon properties of r-BS, and bands assignment has been implemented.

II. Experimental technique
Polycrystalline r-BS was synthesized at 7.5 GPa and 2200 K from amorphous boron (Johnson Matthey, 99%) and sulfur (Johnson Matthey, spectrographic grade) powders mixed in the 1:1 molar ratio using a toroid-type high-pressure apparatus with specially designed high-temperature cell [13]. Boron nitride (grade AX05, Saint-Gobain) capsules were used to isolate the reaction mixture from the graphite heater. Isotope enriched r-10 BS was synthesized by the same method from amorphous 10 B (enrichment > 95%) (for convenience, further we will mark the r-BS with natural B isotope distribution as r-BS and the phase enriched by 10 B isotope as r-10 BS). The structure and phase purity of as-synthesized yellow-green polycrystalline samples were confirmed by powder X-ray diffraction (G3000 TEXT Inel diffractometer, Cu Kα1 radiation). The lattice parameters of both r-BS and r-10 BS are close to the literature data (a = 3.0522 Å, c = 20.4119 Å) [2] and presented in Table I. Bond lengths and angles of r-BS synthesized in the present work, as well as literature values [2], are listed in Table I.
In-situ high-pressure experiments were carried out in a membrane diamond anvil cell (DAC) [14] with 250 µm culet anvils. A small (~20 µm) sample of r-BS was loaded into a 90-µm hole drilled in a rhenium gasket pre-indented down to 35 µm. Neon pressure transmitting medium has been used. Pressure in the DAC was determined by the ruby luminescence technique [15] using the calibration by Mao et al. [16]. Pressure was measured before and after each run; drift during experiment was less than 0.4 GPa in the 2-34 GPa pressure range.
Raman spectra were excited with the 632.8 nm line of a He-Ne laser (10 µm beam spot) and recorded in the 200-2000 cm -1 range using Horiba Jobin Yvon HR800 Raman spectrometer. The spectrometer was calibrated using a single crystal of cubic Si at room temperature. A laser power at the sample was estimated to be less than 30 mW. No effect due to laser heating of the sample was observed. The positions of individual and overlapped Raman bands have been evaluated by fitting the experimental profile to the Pearson shape function using DatLab software [17]. Raman spectra of r-BS were measured in 23 pressure points from 1.8 to 34.0 GPa at room temperature. The Raman study of r-10 BS was performed only at ambient conditions with the aim to identify the modes impacted by the isotopic effect, and thus to help understand the modes symmetry.
The Fourier transform infrared (FTIR) absorption spectra in mid-infrared range (450-4000 cm -1 ) were recorded using a Bruker IFS 125HR spectrometer. Samples were uniformly mixed with KBr powder and pressed into pellets.

III. Calculation details
In the present work the r-BS has been studied using first principles LCAO calculations performed using the CRYSTAL09 code [18]. For the boron atoms, we used the all-electron basis sets, which were optimized in earlier calculations [19]. The core electrons of the sulfur atom were excluded from consideration using the effective small-core pseudopotential (ECP) and the corresponding atomic basis set [20], which excludes any diffuse Gaussian-type orbitals with the exponents less than 0.1. In the CRYSTAL09 code, the accuracy in evaluating the Coulomb series and the exchange series is controlled by a set of tolerances, which were taken to be (10 -8 , 10 -8 , 10 -8 , 10 -8 , and 10 -16 ). The Monkhorst-Pack scheme [21] for a 8×8×8 k-point mesh in the Brillouin zone was applied. Self-consistent field calculations were performed for hybrid DFT-HF WCGGA-PBE-16% functional [22]. The percentages 16% define the Hartree-Fock admixture in the exchange part of DFT functional.
The full structure optimization procedure according to the energy minima criterion has been performed for r-BS. The optimized structural parameters, such as the lattice parameters (a, b, c), unit cell volume (V0), bond lengths and angles (see Fig. 1) are compared with experimental ones and listed in Table I. The bulk modulus and its first derivative for r-BS have been calculated using routine implemented in the CRYSTAL09 code. In order to obtain E(V) dependence, the unit cell volume was varied from 76% to 100% of the equilibrium volume (V0). At each volume the structure optimization was performed. Obtained E(V) dependence has been fitted to the Murnaghan equation of state [23] taking V0 = 57.61 Å 3 and E0 = -69.97 eV. P(V) dependence was estimated using equations (1), (2).
The calculated values are reported in Table II. The phonon frequencies at selected pressure points up to 34 GPa have been calculated using optimized geometries for corresponding reduced volume unit cells.

IV. Results and discussion
According to the powder X-ray diffraction (XRD) data [2], r-BS has a space group R3m (160), the same as -GaS [4] and -GaSe [6]. Rietveld refinement was not performed in our study because boron is a low-Z element. Thus, the refined atomic coordinates determined in [2] have been used in combination with lattice parameters obtained from our XRD data. As one can see from Fig. 1 and Table I, the r-BS trigonal anti-prism [2] is slightly distorted. Accurate measurements of all bond lengths and angles in r-BS and r-10 BS obtained from experimental XRD data reveal the same distortion. However, the geometry optimization procedure in the LCAO calculations for r-BS* doesn't support the experimentally observed distortion. This fact could not be explained yet as well as slightly different c parameters of r-10 BS and r-BS. r-BS (or -BS) has one layer in the primitive rhombohedral cell (rhombohedral setting). Structural unit of r-BS is trigonal anti-prism containing B-B pairs and sulfur atoms in vertices, forming two hexagonal sheets of S rotated around the c-axis by /3 relative to each other. Consequently, the coordination number of boron atoms in r-BS is four. r-BS can be represented in a hexagonal setting with three layer in a crystallographic cell (Fig. 1). It can be compared with the MX2 transition metal chalcogenides where the B-B pair is replaced by an M atom.
In layered crystals, the vibration modes may be separated in the modes of the isolated layer (internal modes in molecular crystals), and the whole crystal modes. Since the layers contain the same number of atoms and due to weak Van der Waals interlayer interactions, the number of modes from isolated layer should be multiplied by the number of layers in the primitive unit cell. That gives rise to "rigid layer modes" (similar to the external modes in molecular crystals) and "Davydov multiplets". However, the Raman studies on the GaSe polytypes [25][26][27][28][29][30] have proved that the layer modes are not dependent on the number of layers.
r-BS has 4 atoms in the unit cell of rhombohedral crystal structure. Thus, 12 normal modes of vibration at the zone center are described by the irreducible representation of the C3v point group: where the E modes are doubly degenerate. All the optic modes are both infrared and Raman active and thus there should be 6 non-degenerate Raman active modes, since A1(1) and E(1) modes ( Fig. 2(a)) are the acoustic ones. An irreducible representation is assigned to a set of atomic displacement pattern in Fig. 3, in a manner similar to that previously used [27]. In this Figure the bracketed numbers associated with the group representations have no physical meaning and are used only as labels. At ambient conditions Raman spectra were investigated in the 200-2500 cm -1 frequency range. Five Raman active modes of r-BS have been observed in the 200-1200 cm -1 range ( Fig. 2(a)). In the case of isotope enriched r-10 BS, only four bands have been observed in the same frequency domain. No peak was observed above 1200 cm -1 for both compounds. In the Raman spectra of r-BS and r-10 BS less than six bands predicted from the irreducible representation of non-degenerate Raman modes were observed. The frequencies of all modes for r-10 BS and r-BS are presented in Table II.
IR spectrum of r-BS ( Fig. 2(b)) in the 200-4000 cm -1 frequency range shows many bands. Most of them can be explained by the presence of impurities and adsorbed water. However, based on the shape and relative intensities of IR spectrum of one of GaS polymorphs [5] we characterize two bands, which we suppose are vibrational modes of r-BS. Our suggestion is supported by the LCAO calculations (see Table II). In the IR spectrum the r-BS bands are placed at 656.6 cm -1 and 702.9 cm -1 . As far as in transmission IR spectroscopy only TO modes could be measured, we observed E(2) (TO) and A1(2) (TO).
The results of our LCAO calculations corresponding to the lowest temperature limit (T = 0 K) agree with the experimentally observed bands wavenumbers (Table II). Based on LCAO calculations performed for r-11 BS* and r-10 BS*, the Raman-and IR-active modes assignment has been performed. The deviation of calculated Raman modes from experimentally observed ones does not exceed 3.4% and 5.6% for r-BS and r-10 BS, respectively. The deviation of calculated IR modes from experimentally observed bands for r-BS is less than 5.5%. To confirm the obtained results we provided test calculation of phonon frequencies of γ-GaSe. Results of these calculations are presented in Table II. One can see that the sequence of the modes found in Raman spectra (E(3), A1(3), E(4), A1(4)) of γ-GaSe [27] is the same as for r-BS. This fact makes it clear that compounds of the same symmetry and almost similar structure exhibit the common sequence of the phonons presented in Raman and IR spectra.
The LCAO calculations have shown that the IR intensity of the E(2) and A1(2) modes is much higher than that of the other modes. In spite of the fact that all modes are both Raman and IR active, the most intense IR modes have not been observed in Raman spectra. Taking into account this fact, we suppose that those modes, which have not been observed in Raman spectra are observed in IR spectra.
The isothermal bulk modulus of r-BS B0 = 37.9 GPa and its first derivative B0` = 7.5 have been estimated using the E(V) dependence obtained from LCAO calculations (Fig. 4). Volume dependence V(P) fitted to the Murnaghan equation of state is shown in Fig. 5. The rather high value of B0´ is evidently due to the anisotropy of the r-BS structure similar to graphite (B0´ = 8.9) [31], hexagonal graphite-like boron nitride (B0´ = 5.6) [32] and turbostratic BN (B0´ = 11.4) [33]. The band gap value Eg = 3.45 eV found from LCAO calculations is in good agreement with the estimation made in Ref. 2 (~3.4 eV). Figure 6 presents the dependence of the lattice parameters on the pressure. The most significant compression occurs along the c axis in contrast to directions along a and b axes, which is consistent with the fact that the interlayer interactions are of the Van der Waals type, whereas the intralayer ones are iono-covalent. Hence, the compressibility along c is much larger than in other directions and results in the rather low value of B0. Compression of the B-B and B-S bonds in the layer are similar (Fig. 7) similar to that for GaSe [7,8] and GaSe [28,30].
There are significant differences between Raman spectra of r-BS with natural B isotope distribution (80% 11 B -20% 10 B) and of r-BS enriched in 10 B isotope (95% 10 B -5% 11 B). As expected, all the bands of the 10 B-enriched sample are shifted to high-frequencies. Isotope shift exceeds 20 cm -1 for the pair of high-frequency phonons while it does not exceed 2 cm -1 for the lowfrequency ones. It has been concluded that frequencies of E(4) and A1(4) are significantly influenced by the oscillation frequencies of the boron atoms, and therefore by boron atoms mass change. This conclusion has been confirmed by LCAO calculations i.e. experimentally observed bands of r-10 BS and theoretically predicted phonons revealed good coincidence (see Fig. 2(a)).
The rather intense band at 1037.9 cm -1 observed in Raman spectrum of r-BS is not predicted by LCAO calculations. It has been observed only in the Raman spectra of r-BS with the natural boron isotope content. The coincidence of XRD patterns of r-10 BS and r-BS excludes any possibility of structural difference or systematic alternating defects. Moreover, it has been noted [27] that the vibrational frequencies are dominated by the intralayer forces and that changes in stacking sequence has no influence on the frequency of the "internal" layer modes. However, invisible for XRD technique random structural defects may occur in the polycrystalline sample and thus could lead to unpredictable bands arrangement and relative intensities or even appearance of band splitting in Raman and IR spectra. Moreover, one can remark that Raman spectra of GaSe and GaS polymorphs (structural analogs of r-BS) have the same doublet at high-frequency wavenumbers [27,29]. Hoff et al. [27] showed that some of the bands can appear as result of combination of A(LO) -E(LO) and A(TO) -E(TO) modes. This could be an explanation of the doublet appearance, but proving this assumption requires techniques that are not available in the present work.
The pressure dependence of the five vibrational modes has been measured in r-BS up to 34 GPa. Raman spectra at different pressures are shown in Fig. 8, indicating rather strong phonon's shift. During the compression, all the lines have shifted monotonically toward high frequencies (Fig. 9), and no new line appeared (Fig. 8). Thus, one can conclude that no phase transition nor amorphization is observed in the studied pressure range. In contrast, one should note that GaS and GaSe do have phase transitions at 18÷19 GPa [28] and 24÷25 GPa [8], respectively. Phase transition of β-GaS observed in [30] was followed by total disappearing of all Raman bands except one. It has been stated that at ambient pressure intralayer bonds are one order of magnitude larger than interlayer restoring forces [30]. Thus, an increase of the latter under pressure brings them into the range of the intralayer forces and, therefore, structure becomes quasi-three-dimensional near the phase transition. A broad band in the 500 -625 cm -1 range is observed, but no correlation between band's intensity, frequency shift and pressure applied to the system could be found. Thereby we suppose that the origin of this band is connected with the non-homogeneity of the powder sample under study. There are strong grounds to believe that no new additional bands appear up to the highest experimental pressure due to the provided LCAO calculations. One can see from Fig. 9 that the theoretical calculations completely match with Raman bands shift observed experimentally in the whole studied pressure range.
Simultaneous growing of the background and bands broadening has been observed. Highfrequency bands at 1037.9 and 1046.6 cm -1 became indistinguishable above 29 GPa. It should be noted that there are monotonic dependencies of full width at half maximum (FWHM) of the second (~320 cm -1 ) and third (~700 cm -1 ) bands with increasing pressure. That of the first band can be approximated by a straight line. The absence of sharp breaks in the pressure dependencies of the FWHM may be considered as indirect evidence of absence of phase transition in r-BS over the investigated pressure range.
In order to estimate the Grüneisen parameters of observed Raman modes we fitted the Raman modes pressure dependencies (Fig. 9) by the same equation as in Ref. 34: A least-squares fit of Eq. (4) to the experimental data yields the values of first-order parameters (δ0) 0.0064(5) GPa -1 for E(3) mode (209.4 cm -1 ), 0.0136(3) GPa -1 for A1(3) mode (319.3 cm -1 ), 0.0071(2) GPa -1 for E(4) mode (686.5 cm -1 ), and 0.0048(1) GPa -1 for A1(4) mode (1046.6 cm -1 ). Also the pressure dependence of the band at 1037.9 cm -1 has been fitted by Eq. (4), and δ0 value of 0.0048(2) GPa -1 has been determined. The Grüneisen parameters γG = B0δ0 of all bands are presented in Table II. All the observed phonons moved to high frequency, but the extension of these shifts was different (Fig. 9). The dashed lines have been fitted using the quadratic equation: The parameters ω1 used in Eq. (5) are given in Fig. 9. Observed coefficients ω1 and ω2 have values typical for boron-rich compounds [10][11][12]: ω1 values are not exceeding 5, while ω2 values are slightly negative tending to zero. Besides, these coefficients are of the same order of magnitude as those of the corresponding modes of GaSe [7] and GaS [30].
The initial slope of the low-frequency mode E(3) is much smaller than that of the A1(3), E(4) and A1(4) modes. Also (as shown in Fig. 3) only E(3) reveals the same amplitude of vibration for boron and sulfur atoms. Summing up, we can conclude the particularity of the E(3) mode with respect to the other observed modes. This mode is similar to the E mode (60 cm -1 ) of γ-GaSe, E" mode (60 cm -1 ) in -GaSe and E1g mode (74 cm -1 ) in -GaS, because all these modes have the same displacement pattern (rigid half layer shear modes). Moreover, in these compounds, these modes have low pressure coefficients, in contrast to the other modes. In Ref. 30, the peculiar pressure coefficient of the E1g mode was explained by the similarity of its displacement pattern with an edgeof-the-zone TA mode as regards the destabilizing effect of pressure upon electronic contributions to restoring forces. The pressure coefficient of the E(3) can be explained in the same way. It is a halflayer shear mode, involving mainly B-B restoring forces, as far as vibration amplitudes for B and S atoms are the same in this mode. Since this mode does not change much the B-S distance within the same half-layer, this vibration will be viewed as a transverse acoustical (TA) mode of BS molecules, on a chain along the c axis. Edge-of-the-zone TA modes in 3D crystals are known to exhibit negative coefficients of the pressure dependence. Under pressure the electronic charges involved in the first neighbors bonds delocalize towards interlayer space, which soften the total restoring spring, and results in a negative pressure coefficient. We assumed that explanation given in [30] can be used also for E(3) mode. Low coefficient of the pressure dependence of E(3) mode is a result of two contributions: a positive one coming from the increase with pressure of the interlayer interaction and therefore distance decrease between the atoms, and a negative one coming from the shear motion and the TA-like character in this mode. The total may be slightly positive, zero, or slightly negative i.e. much less than for other intralayer modes.
The same explanation concerning weak pressure dependence of the low-frequency Raman band was proposed in [7]. Very small pressure coefficient of such mode can be explained by the compensation of the decrease in the B-B bond length, which leads to the frequency increase under pressure, and the charge delocalization, which tends to depopulate the B2 radical environment and thus decrease the B-B bond strength. The same effect can be observed in diatomic molecules under the pressure (I2, H2 etc.), where the charge transfer occurs between the space towards to the intermolecular region, tending to symmetrization of the bonds and eventually leading to the same intensity of intra-and intermolecular ones. In other words, the charge density between the layers increases with the pressure because of interlayer space decrease and also of the total effective number of electrons squeezed out from intralayer space.

Conclusions
Rhombohedral boron monosulfide, r-BS has been studied by Raman and IR spectroscopy at ambient and high pressure. Basing on the results of LCAO calculations, observed isotope effect and Raman spectra of isostructural A III B VI compounds, the correlation between Raman and IR bands and phonon modes was performed. The evolution of Raman bands of r-BS has been studied up to 34 GPa at ambient temperature. Modes behavior under pressure was described and explained. Finally, it was found that there is no phase transition of r-BS in the explored pressure range.  Table II. Experimental (ω0) and calculated (ωt) phonon frequencies of r-BS, r-10 BS and γ-GaSe; r-BS isotope shifts [Δω = ω(r -10 BS) -ω(r -BS)] for the experimentally observed Raman bands and theoretically calculated modes; modes assignment and Grüneisen parameters (γG).


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The Synthesis of the Metabolites of 2′,3′,5′-Tri-O-acetyl-N6-(3-hydroxyphenyl) Adenosine (WS070117)

Seven metabolites of 2′,3′,5′-tri-O-acetyl-N6-(3-hydroxyphenyl) adenosine (WS070117) were synthesized by deacetylation, hydrolysis, cyclization, sulfonylation and glycosylation reactions, respectively. All these compounds, which could be useful as material standards for metabolic research, were characterized by NMR and HPLC-MS (ESI) analyses.

Introduction
2 1 ,3 1 ,5 1 -Tri-O-acetyl-N 6 -(3-hydroxyphenyl) adenosine (also known as WS070117) is a new adenosine analog anti-hyperlipidemic drug candidate currently in many preclinical studies [1][2][3][4][5]. Guo and coworkers have investigated and elucidated the in vivo metabolites of WS070117 in rat urine after oral administration of WS070117 by HPLC-DAD, ESI-MS and Off-Line Microprobe NMR [6]. In the study, seven metabolites of WS070117 were observed in the HPLC trace (the metabolites are ranked M2-M8 according to the retention time; Figure 1). The structure elucidation results unambiguously revealed that there are two phase I metabolites, including a deacetylation product of WS070117 (M8) and an adenine derivative formed by the loss of ribofuranose (M7). In addition, there are five phase II metabolites: M6 is the oxidation product of M7 at C-8; M2 and M4 are the glycosylation products of M7 and M8 on the phenolic hydroxyl groups, respectively; M3 and M5 are the sulfonylation products of M6 and M8, respectively. Herein, the synthesis of the above metabolites was carried out to provide metabolites material standards for preclinical pharmacokinetic studies.

Results and Discussion
The metabolite M8 was prepared in quantitative yield by the hydrolysis of the acetyl groups in WS070117 with NaOH [7] (Scheme 1). Treatment of WS070117 with chlorosulfonic acid [8] afforded the corresponding sulphonate 1, which was converted to the desired product M5 by subsequent deacetylation with Na 2 CO 3 . Direct hydrolysis of the glycosidic bond in WS070117 with concentrated hydrochloric acid and 95% ethanol solution at reflux smoothly afforded M7.
We initially attempted to synthesize M6 by bromination and hydrolysis reactions at C-8 of M7 [9], but liquid bromine and NaH did not afford the needed C8-brominated adenine. Then 4,5-diamino-6-chloropyrimidine 2 and N,N 1 -carbonyldiimidazole (CDI) were employed to synthesize 8-hydroxy-6-chloroadenine (3) [10], which could be ammoniated at C-6 to prepare M6 (Scheme 2). The amination was catalyzed by hydrochloric acid to afford the desired product in 70%   Initially, the glycosylation reaction with tetra-O-acetyl-β-D-glucopyranuronic acid methyl ester as the donor and WS070117 as the receptor was catalyzed by SnCl 4 to synthesize M4, but the yield of the desired product was poor, with the formation of a complex mixture of by-products. The Koenigs-Knorr glycosylation reaction with acetobromo-α-D-glucuronic acid methyl ester as the donor was then employed, but Ag 2 O failed to catalyze the reaction even at two equivalents, which may be due to its complexation with the nitrogen-atoms. Afterwards the Schmitt glycosylation reaction was tried with trichloroacetimidate as donor (Scheme 3). A series of conditions for selective anomeric deacetylation of 4 were investigated, including benzylamine/DMF [11], FeCl 3¨6 H 2 O/CH 3 CN [12] and Nd(OTf) 3 /CH 3 OH [13]. The results showed that Nd(OTf) 3 /CH 3 OH gave a cleaner reaction in quantitative yield and the product could be used directly in the next step without purification. Under the catalysis of BF 3¨E t 2 O, trichloroacetimidate 6 reacted smoothly with WS070117 to give the desired β-glucoside 7 due the neighboring group participation effect. After deacetylation with Cs 2 CO 3 , M4 was obtained in 83.3% yield. However, the glycosylation reaction of M7 under the same conditions only afforded the desired product M2 with a 25% conversion because of the poor solubility of the raw material in dichloromethane. An alternate route such as selective hydrolysis of the N-glycoside bond of M4 with aqueous hydrochloric acid solution afforded M2 in moderate yield. Initially, the glycosylation reaction with tetra-O-acetyl-β-D-glucopyranuronic acid methyl ester as the donor and WS070117 as the receptor was catalyzed by SnCl4 to synthesize M4, but the yield of the desired product was poor, with the formation of a complex mixture of by-products. The Koenigs-Knorr glycosylation reaction with acetobromo-α-D-glucuronic acid methyl ester as the donor was then employed, but Ag2O failed to catalyze the reaction even at two equivalents, which may be due to its complexation with the nitrogen-atoms. Afterwards the Schmitt glycosylation reaction was tried with trichloroacetimidate as donor (Scheme 3). A series of conditions for selective anomeric deacetylation of 4 were investigated, including benzylamine/DMF [11], FeCl3·6H2O/CH3CN [12] and Nd(OTf)3/CH3OH [13]. The results showed that Nd(OTf)3/CH3OH gave a cleaner reaction in quantitative yield and the product could be used directly in the next step without purification. Under the catalysis of BF3·Et2O, trichloroacetimidate 6 reacted smoothly with WS070117 to give the desired β-glucoside 7 due the neighboring group participation effect. After deacetylation with Cs2CO3, M4 was obtained in 83.3% yield. However, the glycosylation reaction of M7 under the same conditions only afforded the desired product M2 with a 25% conversion because of the poor solubility of the raw material in dichloromethane. An alternate route such as selective hydrolysis of the N-glycoside bond of M4 with aqueous hydrochloric acid solution afforded M2 in moderate yield.

General Information
WS070117 was prepared in our laboratory in 98% purity. Unless otherwise indicated, all commercial reagents and solvents were used without additional purification. 1 H-NMR and 13 C-NMR spectra were recorded on a Mercury-300M (Varian, Salt Lake City, UT, USA,) or Bruker 400M (Varian) spectrometer. Chemical shifts (in ppm) were referenced to tetramethylsilane (δ= 0) in deuterated solvent as internal standard. HPLC-mass spectra (ESI) were recorded on an Acquity UPLC-MS system (Waters, Milford, MA, UK). Optical rotations were recorded on p-2000 polarimeter (Jasco, Tokyo, Japan) at 20 °C in 589 nm.

Synthesis of N6-(3-Hydroxyphenyl) Adenosine (M8)
NaOH (2.1 g, 52.5 mmol) was added to a stirred suspension of WS070117 (8.0 g, 16.5 mmol) in H2O (50 mL), and the mixture was stirred at room temperature for 2 h until the disappearance of the solid. The solution was cooled to 5 °C and the precipitated solid was filtered and washed with water to give M8 (5.90 g, 99%)

General Information
WS070117 was prepared in our laboratory in 98% purity. Unless otherwise indicated, all commercial reagents and solvents were used without additional purification. 1 H-NMR and 13 C-NMR spectra were recorded on a Mercury-300M (Varian, Salt Lake City, UT, USA,) or Bruker 400M (Varian) spectrometer. Chemical shifts (in ppm) were referenced to tetramethylsilane (δ = 0) in deuterated solvent as internal standard. HPLC-mass spectra (ESI) were recorded on an Acquity UPLC-MS system (Waters, Milford, MA, UK). Optical rotations were recorded on p-2000 polarimeter (Jasco, Tokyo, Japan) at 20˝C in 589 nm. N,N 1 -Carbonyldiimidazole (CDI, 1.6 g, 10 mmol) was added into a stirred solution of 4,5-diamino-6-chloropyrimidine (2, 0.76 g, 5.23 mmol) in 1,4-dioxane. The reaction mixture was refluxed for 6 h and then cooled to room temperature. The precipitated solid was filtered and washed with water to give 8-hydroxy-6-chloroadenine (3, 700 mg). Concentrated hydrochloric acid (1 mL) was then added into a stirred solution of intermediate 3 (0.7 g, 4.12 mmol) and 3-aminophenol (0.7 g, 6.42 mmol) in ethanol (20 mL) in a sealed tube, which was irradiated in a microwave reactor at 120˝C for 4 h and then cooled to room temperature. The precipitating solid was filtered and washed with water to give M6 (0.