Lignan contents of Schisandra chinensis (Turcz.) Baill. from different origins-A new model for evaluating the content of prominent components of Chinese herbs.

BACKGROUND: As a traditional Chinese herbal medicine, Schisandra chinensis exhibits various effects such as liver protection, blood sugar regulation, blood lipid regulation, immune function regulation, antidepressant activity, etc. However, because of its intricate composition, diverse origins, and medicinal effects depending on complex compound groups, there are differences in the lignan composition of S. chinensis from different origins. Therefore, it is currently difficult to evaluate the quality of medicinal materials from plants of different origins using a single qualitative quality control index. PURPOSE: This paper aims to investigate the potential relationship between the lignan components of S. chinensis from different origins and to establish stable assessment indices for determining the lignan content of S. chinensis from multiple perspectives. METHODS: In this study, we collected S. chinensis samples of seven major origins in China, and randomly sampled 6-9 batches of each origin for a total of 60 batches. The lignan content was determined by HPLC, and its distribution law of the ratio of each lignan component of S. chinensis to Schisandrol A content was analyzed. Combining network pharmacology and differential analysis between samples, the stable and effective substances used as quality markers were determined. RESULTS: There were some correlations among the lignan contents of S. chinensis, some correlations between schisandrin A and other lignans of S. chinensis could be determined. The ratio of each component to the indicator component schisandrol A was evenly distributed and reflected the lignan content of S. chinensis to some extent. Four substances (schisandrol A, schisandrol B, schisantherin A, and schisandrin C) were determined by network pharmacology combined with the analysis results of HCA, PCA and PLS-DA to further optimize the model. They displayed a strong connection with the core target, a large contribution rate to the principal components, and a stable content in each batch of samples, suggesting that these components may be the main active substances of S. chinensis lignans. Therefore, they could be used as main indicators evaluating the advantages and disadvantages of S. chinensis by examining the consistency of component proportions. CONCLUSION: This method can intuitively evaluate the content of main lignans in S. chinensis. This quality assessment model is an exploration of the multi-component comprehensive evaluation system of S. chinensis, providing a new concept for the quality evaluation system of Chinese herbal medicines.

Combined Application of Fluorescence Spectroscopy and Principal Component Analysis in Characterisation of Selected Herbhoneys.

This study reports the use of front-face fluorescence spectroscopy with principal component analysis (PCA) as a tool for the characterisation of selected Polish herbhoneys (raspberry, lemon balm, rose, mint, black current, instant coffee, pine, hawthorn, and nettle). Fluorimetric spectra registered in the ranges ascribed to fluorescence of amino acids, polyphenols, vitamins, and products of Maillard's reaction enabled the comparison of herbhoney compositions. Obtained synchronous spectra combined with PCA were used to investigate potential differences between analysed samples and interactions between compounds present in them. The most substantial influence on the total variance had the intensities of polyphenols fluorescence. These intensities were the main factor differentiated by the analysed products.

Integrating chemical similarity and bioequivalence: an overall evaluation of the quality consistency of traditional decoction and dispensing granule decoction of Amomum villosum.

OBJECTIVE: This study aims to investigate the quality consistency between traditional decoction (TD) of Amomum villosum and its dispensing granule decoction (DGD). Fifteen batches of TD and nine batches of dispensing granules (manufactured by A, B, and C) were prepared and evaluated for their consistency. METHODS: Firstly, The chemical similarity of TD and DGD was examined using GC and HPLC, coupled with hierarchical cluster analysis (HCA), criteria importance though intercrieria correlation(CRITIC) weighting method, and principal component analysis (PCA). Secondly, the gastrointestinal motility experiments in mice, along with the CRITIC weighting method, were employed to assess the bioequivalence of TD and DGD of Amomum villosum. Finally, the entropy weight technique-gray relative analysis(GRA) method was used to compare the quality of Amomum villosum decoctions. RESULTS: ①The CRITIC weighting method indicated significantly higher scores for TD than DGD (p < 0.01). HCA and PCA results demonstrated a clear distinction between TD and DGD. ②Gastrointestinal motility test results revealed no significant difference between TD and DGD in other indicators (p > 0.05).③Gray relative analysis results showed that the relative correlation of TD was more significant than that of DGD. CONCLUSION: The chemical composition of DGD and TD differed. The biological activity of DGD-A/B was consistent with that of TD, while the difference between DGD-C and TD was significant. A comprehensive evaluation showed that TD exhibited better quality than DGD. DGD manufacturers should optimize the preparation process to enhance product quality.

Evaluation of edible oil types used in packaged foods in Türkiye with principal component analysis.

In our rapidly changing world, where consumers' expectations for healthy food are on the rise, the edible oil content in packaged foods has become a central focus. Among various types of oils, palm oil is often regarded as one of the most contentious. This research study aimed to identify the types of fats present in packaged food products in Türkiye and examined the reasons for their utilization. A total of 1380 packaged food items, classified into 11 categories, were scrutinized, and the types of oils within their ingredients were classified using principal component analysis and hierarchical cluster analysis. The study's results have determined that among packaged food products available in Türkiye, 50.1% contain palm oil, 30.4% contain sunflower oil, 16.4% contain canola oil, 14.9% contain cottonseed oil, 17.9% contain cocoa oil, and 12.6% contain coconut oil. In particular, it was determined that palm oil was used in 91% of bakery products, 81% of margarine and shortening products, and 71.3% of ice creams. Consequently, the data obtained in the context of ongoing debates regarding the fat content in packaged foods, especially concerning palm oil usage, will make a valuable contribution to the literature.

Identification of Commercial Antimalarial Herbal Drugs Using Laser-Induced Autofluorescence Technique and Multivariate Algorithms.

In malaria-prone developing countries the integrity of Anti-Malarial Herbal Drugs (AMHDs) which are easily preferred for treatment can be compromised. Currently, existing techniques for identifying AMHDs are destructive. We report on the use of non-destructive and sensitive technique, Laser-Induced-Autofluorescence (LIAF) in combination with multivariate algorithms for identification of AMHDs. The LIAF spectra were recorded from commercially prepared decoction AMHDs purchased from accredited pharmacy shop in Ghana. Deconvolution of the LIAF spectra revealed secondary metabolites belonging to derivatives of alkaloids and classes of phenolic compounds of the AMHDs. Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA) were able to discriminate the AMHDs base on their physicochemical properties. Based on two principal components, the PCA- QDA (Quadratic Discriminant Analysis), PCA-LDA (Linear Discriminant Analysis), PCA-SVM (Support Vector Machine) and PCA-KNN (K-Nearest Neighbour) models were developed with an accuracy performance of 99.0, 99.7, 100.0, and 100%, respectively, in identifying AMHDs. PCA-SVM and PCA-KNN provided the best classification and stability performance. The LIAF technique in combination with multivariate techniques may offer a non-destructive and viable tool for AMHDs identification.

GC-MS Fingerprinting Combined with Chemical Pattern-Recognition Analysis Reveals Novel Chemical Markers of the Medicinal Seahorse.

Seahorse is a valuable marine-animal drug widely used in traditional Chinese medicine (TCM), and which was first documented in the "Ben Cao Jing Ji Zhu" during the Liang Dynasty. Hippocampus kelloggi (HK) is the most common seahorse species in the medicinal material market and is one of the genuine sources of medicinal seahorse documented in the Chinese pharmacopeia. It is mainly cultivated in the Shandong, Fujian, and Guangxi Provinces in China. However, pseudo-HK, represented by Hippocampus ingens (HI) due to its similar appearance and traits, is often found in the market, compromising the safety and efficacy of clinical use. Currently, there is a lack of reliable methods for identifying these species based on their chemical composition. In this study, we employed, for the first time, a strategy combining gas chromatography-mass spectrometry (GC-MS) fingerprints and chemical patterns in order to identify HK and HI; it is also the first metabolomic study to date of HI as to chemical components. The obtained results revealed remarkable similarities in the chemical fingerprints, while significant differences were also observed. By employing hierarchical cluster analysis (HCA) and principal component analysis (PCA), based on the relative contents of their characteristic peaks, all 34 samples were successfully differentiated according to their species of origin, with samples from the same species forming distinct clusters. Moreover, nonadecanoic acid and behenic acid were exclusively detected in HK samples, further distinguishing them from HI samples. Additionally, the relative contents of lauric acid, tetradecanoic acid, pentadecanoic acid, n-hexadecanoic acid, palmitoleic acid, margaric acid, oleic acid, fenozan acid, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) exhibited significant differences between HK and HI (p < 0.0001), as determined by an unpaired t-test. Orthogonal partial least squares discriminant analysis (OPLS-DA) identified seven components (DHA, EPA, n-hexadecanoic acid, tetradecanoic acid, palmitoleic acid, octadecanoic acid, and margaric acid) with high discriminatory value (VIP value > 1). Thus, nonadecanoic acid, behenic acid, and these seven compounds can be utilized as chemical markers for distinguishing HK from HI. In conclusion, our study successfully developed a combined strategy of GC-MS fingerprinting and chemical pattern recognition for the identification of HK and HI, and we also discovered chemical markers that can directly differentiate between the two species. This study can provide a foundation for the authentication of Hippocampus and holds significant importance for the conservation of wild seahorse resources.

Exploring band-free Raman microspectrometry combined with PCA and MCR-ALS for size-resolved forensic analysis of uranium in aerosols in a model nuclear atmosphere.

Achieving non-destructive micrometer-scale molecular and structural analysis of uranic materials in atmospheric aerosols with traditional methodologies is a challenge. Spatially resolved analysis of uranium in actinide-bearing aerosols is critical for nuclear forensics. Although laser Raman microspectrometry enables this, for the normally low uranium concentrations in the aerosols the spectra are indiscernible (band-free) against pronounced background: trace analysis requires a push in analytical strategy. We combined laser Raman microspectrometry (utilizing two lasers (λ = 532 nm, λ = 785 nm)) with principal component analysis (PCA) and multivariate curve resolution-alternate least squares (MCR-ALS) to perform size-resolved analysis of uranium in aerosols. Uranium-specific Raman scatter bands corresponding to uranyl nitrate (860 cm-1), uranium sulphate (868 cm-1), uranyl chloride (816 cm-1) and uranium trioxide (839 cm-1) were detected. The 816 cm-1, 854 cm-1, 868 cm-1 bands were resolved by MCR-ALS and used to identify and map uranium in PM4.5 size aerosols. Based on spectral feature selection of the signature bands, PCA identified two sources of aerosol particles in model nuclear atmosphere - Sea spray for PM4.5 and re-suspension of 'nuclear' dust from a rare earth element (REE) mine for PM2.5. The MCR-ALS-resolved uranium bands showed the potential for attributive nuclear forensic analysis.

A genetic history of continuity and mobility in the Iron Age central Mediterranean.

The Iron Age was a dynamic period in central Mediterranean history, with the expansion of Greek and Phoenician colonies and the growth of Carthage into the dominant maritime power of the Mediterranean. These events were facilitated by the ease of long-distance travel following major advances in seafaring. We know from the archaeological record that trade goods and materials were moving across great distances in unprecedented quantities, but it is unclear how these patterns correlate with human mobility. Here, to investigate population mobility and interactions directly, we sequenced the genomes of 30 ancient individuals from coastal cities around the central Mediterranean, in Tunisia, Sardinia and central Italy. We observe a meaningful contribution of autochthonous populations, as well as highly heterogeneous ancestry including many individuals with non-local ancestries from other parts of the Mediterranean region. These results highlight both the role of local populations and the extreme interconnectedness of populations in the Iron Age Mediterranean. By studying these trans-Mediterranean neighbours together, we explore the complex interplay between local continuity and mobility that shaped the Iron Age societies of the central Mediterranean.

Quality Assessment and Classification of Codonopsis Radix Based on Fingerprints and Chemometrics.

In China, Codonopsis Radix (CR) is frequently consumed both as food and medicine. Here, a comprehensive strategy based on fingerprinting and chemometric approaches was created to explore the influence of origins, storage time and kneading processing on the quality of CR. Firstly, high-performance liquid chromatography with diode array detection was used to obtain the fingerprints of 35 batches of CR from six different origins and 33 batches of CR from varying storage times or kneading procedures. Secondly, chemometric methods including similarity analysis (SA), principal component analysis (PCA), hierarchical clustering analysis (HCA), and two-way orthogonal partial least square with discriminant analysis (O2PLS-DA) were used to evaluate the differences of chemical components in CR so as to identify its source and reflect its quality. Moreover, 13 and 16 major compounds were identified as marker compounds for the discrimination of CR from different origins, storage time and kneading processing, respectively. Furthermore, the relative content of the marker components and the exact content of Lobetyolin were measured, indicating that the contents of these components vary significantly between various CR samples. Meanwhile, the chemical components of CR were identified using Mass spectrometry. According to the findings of our investigation, the quality of CR from Gansu was the best, followed by Shanxi and then Sichuan. The quality of CR from Chongqing and Guizhou was poor. At the same time, the quality of CR was the best when it was kneaded and stored for 0 years, indicating that the traditional kneading process of CR is of great significance. Conclusively, HPLC fingerprint in conjunction with chemical pattern recognition and component content determination can be employed to differentiate the raw materials of different CR samples. Additionally, it is also a reliable, comprehensive and prospective method for quality control and evaluation of CR.

Discrimination of Polygonati Rhizoma Species: An Investigation Utilizing High-Performance Liquid Chromatography Fingerprints and Chemometrics.

Polygonati Rhizoma has been a famous traditional Chinese medicine (TCM) for two thousand years. It is increasingly being used not just as a traditional herbal medicine but also as a popular functional food. In this study, qualitative and quantitative analysis of PR from three different origins were initially performed using chemical fingerprint and chemometrics methods. Hierarchical cluster analysis (HCA) and Principal component analysis (PCA) were used to classify 60 PR samples from three different origins. The results revealed that the PR samples fell into three clusters related to the origins. In addition, pairwise comparison of varying PR and obtaining chemical markers between different species through the establishment of partial least squares discriminant analysis. Finally, chemical markers 9,13 and 17 were identified by LC/MS as disporopsin, 5,7-dihydroxy-3-(4'-hydroxybenzyl)-6,8-dimethylchroman-4-one and (3R)-5,7-dihydroxy-3-(4'-hydroxybenzyl)-6-methylchroman-4-one or isomer, respectively. In conclusion, these methods can be applied to identify and distinguish the quality of PR with other original plants and provide novel ideas for evaluating herbal products used in TCM.

Evaluation of Different Processes Impact on Flavor of Camellia Seed Oil Using HS-SPME-GC/MS.

In this study, the flavor compounds of Camellia seed oils obtained by four processes were characterized by headspace solid phase microextraction/gas chromatography/mass spectrometry (HS-SPME/GC/MS). A variety of about 76 volatile flavor compounds were identified from all the oil samples. Of the four processing processes, the pressing process can retain a lot of volatile components. Among these, compounds nonanal and 2-undecenal were predominantly in the majority of the samples. Meanwhile, other compounds such as octyl ester formic acid, octanal and 2-nonenal (E), 3-acetyldihydro 2(3H)-furanone, (E)-2-decenal, dihydro-5-penty 2(3H)-furanone, nonanoic acid, and dodecane were also among the most consistently found compounds among the oil samples analyzed. The principal component analysis carried out to categorize the data produced seven clusters of the total oil samples based on the number of flavor compounds obtained in each sample. This categorization would lead to understanding the components which highly contributed to the characteristic volatile flavor and build up the flavor profile of Camellia seed oil.

Chemical fingerprint analysis and quality assessment of Tibetan medicine Triphala from different origins by high-performance liquid chromatography.

INTRODUCTION: Although the Tibetan medicine Triphala (THL) is widely used in many countries, insufficient progress has been made in quality control. OBJECTIVES: The present study aimed to propose a methodology for quality control of THL based on HPLC fingerprinting combined with an orthogonal array design. METHODS: Seven identified peaks were used as indicators to examine the effects of temperature, extraction time, and solid-liquid ratio on the dissolution of active ingredients in THL. Fingerprint analysis was performed on 20 batches of THL from four geographical areas (China, Laos, Thailand, and Vietnam). For further chemometric assessment, analysis techniques including similarity analysis, hierarchical clustering analysis, principal component analysis, and orthogonal partial least squares discrimination analysis (OPLS-DA) were used to classify the 20 batches of samples. RESULTS: Fingerprints were established and 19 common peaks were identified. The similarity of 20 batches of THL was more than 0.9 and the batches were divided into two clusters. Four differential components of THL were identified based on OPLS-DA, including chebulinic acid, chebulagic acid, and corilagin. The optimal extraction conditions were an extraction time of 30 min, a temperature of 90°C, and a solid-liquid ratio of 30 mL/g. CONCLUSION: HPLC fingerprinting combined with an orthogonal array design could be used for comprehensive evaluation and quality assessment of THL, providing a theoretical basis for further development and utilization of THL.

An intelligent extraction approach of feature information from three-dimensional DAD chromatogram for integrated quality control of traditional Chinese medicines: Gardenia jasminoides root as an example.

Traditional Chinese medicine (TCM) fingerprinting, which has the characteristics of holism and ambiguity, is a conventional strategy for the holistic quality control of TCMs. However, the fingerprinting of TCMs at the current stage generally adopts a single wavelength or few wavelengths, lacking the effective utilization of diode-array detector (DAD) chromatogram data. This study proposes an intelligent extraction approach of feature information from a three-dimensional DAD chromatogram to establish a novel bar-form-diagram (BFD) for integrated quality control of TCMs. The BFD was automatically established by the chromatographic and spectral information of a complex hybrid system in a DAD chromatogram. This covered the peak areas of target compositions at the optimal absorption wavelength. Taking 27 batches of Gardenia jasminoides root as samples, the BFD combined with chemometrics was applied for assessing the quality of samples completely, which improved the accuracy of origin classification using hierarchical cluster analysis, principal component analysis, soft independent modeling of class analogy and orthogonal partial least squares discriminant analysis. Single-wavelength fingerprinting and BFD used 23 and 38 common peaks as variables respectively, and the adjusted rand index results of the single wavelength and BFD were 0.559 and 0.819, respectively. Compared with the ergodic methods of each single wavelength, the peak recognition method in this study improved the operation speed from 180 s to 4 s and the computational complexity. The established BFD approach performed more abundant characteristic information of chemical components of TCMs and more accurate origin classification ability, and it had great advantages in the overall quality control of TCMs.

[Quality evaluation of Cnidii Fructus in commodity grade based on theory of "quality evaluation through morphological identification"].

From the perspective of market classification of Cnidii Fructus, this paper revealed the scientific connotation of evaluating the quality grade of Cnidii Fructus by its appearance traits. Thirty batches of Cnidii Fructus in different grades were selected as the research objects. The canonical correlation analysis and principal component analysis(PCA) were used to explore the measurement values of 15 appearance traits and intrinsic content indexes. The results of correlation analysis showed that except the aspect ratio, the 5 appearance trait indexes(length, width, 1 000-grain weight, broken grain weight proportion, and chroma) and 9 internal content indexes(the content of moisture, total ash, acid insoluble ash, osthole, imperatorin, 5-methoxy psoralen, isopimpinellin, xanthotoxin, and xanthotol) showed significant correlation to varying degrees. In addition, there was a significant positive correlation between the first typical variable U_1 composed of appearance traits and the first typical variable V_1 composed of internal content indexes(CR_1=0.963, P<0.01). The results of PCA showed that the classification results of appearance traits for 30 batches of Cnidii Fructus were consistent with the actual information of the samples. Under the same analysis conditions, 30 batches of Cnidii Fructus were reclassified by 9 groups of internal content indexes, and the analysis results were consistent. From the classification standard of the appearance traits of the system study, the statistical results of 6 appearance traits of Cnidii Fructus showed a correlation with grades. There was a good correlation between the appearance and the internal content of Cnidii Fructus, and the appearance quality effectively predicted the level of the internal content. There is a certain scientific basis for the quality classification of Cnidii Fructus by main appearance traits. Appearance classification can replace quality grading to realize the "quality evaluation through morphological identification" of Cnidii Fructus.

Assessment of the Physicochemical Properties of Fragrant Rapeseed Blended Hotpot Oil by Principal Component Analysis.

In this study, a nutritious, healthy Chongqing hotpot oil with excellent flavor was blended while considering nutrition, flavor, and health aspects. Four blended hotpot oils prepared from fragrant rapeseed, palm, sesame, and chicken oils were analyzed to determine their physicochemical properties, antioxidant capacities, levels of harmful substances, and nutritional compositions, and their sensory qualities were evaluated. Principal component analysis was performed to identify the best hotpot oil (10% chicken oil + 20% palm oil + 10% sesame oil + 60% fragrant rapeseed oil), which exhibited good antioxidant capacity (Oxidation Stability Index: 7.95 h; 2,2-diphenyl-1-picrylhydrazyl: 168.6 µmol/kg, 2,2'-azinobis-(3-ethylbenzothiazoline-6-sulfonate): 116.7 µmol/kg, and ferric-reducing/antioxidant power: 63.9 µmol/kg), a high sensory score (7.7/10), stable physicochemical properties (acid value: 0.27 mg/g and peroxide value: 0.01 g/100 g), and high tocopherol (54.22%), and phytosterol retention (98.52%) after boiling for 8 h. Although the 3,4-benzopyrene content of this hotpot oil exceeded the EU standard after boiling for 7 h, the increase in the amount of harmful substances was the lowest.

Discriminant Principal Component Analysis of ToF-SIMS Spectra for Deciphering Compositional Differences of MSC-Secreted Extracellular Matrices.

Identifying characteristic extracellular matrix (ECM) variants is a key challenge in mechanistic biology, bioengineering, and medical diagnostics. The reported study demonstrates the potential of time-of-flight secondary ion mass spectrometry (ToF-SIMS) to detect subtle differences between human mesenchymal stromal cell (MSC)-secreted ECM types as induced by exogenous stimulation or emerging pathology. ToF-SIMS spectra of decellularized ECM samples are evaluated by discriminant principal component analysis (DPCA), an advanced multivariate analysis technique, to decipher characteristic compositional features. To establish the approach, signatures of major ECM proteins are determined from samples of pre-defined mixtures. Based on that, sets of ECM variants produced by MSCs in vitro are analyzed. Differences in the content of collagen, fibronectin, and laminin in the ECM resulting from the combined supplementation of MSC cultures with polymers that induce macromolecular crowding and with ascorbic acid are detected from the DPCA of ToF-SIMS spectra. The results are verified by immunostaining. Finally, the comparative ToF-SIMS analysis of ECM produced by MSCs of healthy donors and patients suffering from myelodysplastic syndrome display the potential of the novel methodology to reveal disease-associated alterations of the ECM composition.

Characterization of Calculus bovis by principal component analysis assisted qHNMR profiling to distinguish nefarious frauds.

A new approach is developed for the reliable classification of Calculus bovis along with the identification of willfully contaminated C. bovis species and the quantification of unclaimed adulterants. Guided by a principal component analysis, NMR data mining achieved a near-holistic chemical characterization of three types of authenticated C. bovis, including natural C. bovis (NCB), in vitro cultured C. bovis (Ivt-CCB), and artificial C. bovis (ACB). In addition, species-specific markers used for quality evaluation and species classification were confirmed. That is, the content of taurine in NCB is near negligible, while choline and hyodeoxycholic acid are characteristic for identifying Ivt-CCB and ACB, respectively. Besides, the peak shapes and chemical shifts of H2-25 of glycocholic acid could assist in the recognition of the origins of C. bovis. Based on these discoveries, a set of commercial NCB samples, macroscopically identified as problematic species, was examined with deliberately added sugars and outliers discovered. Absolute quantification of the identified sugars was realized by qHNMR using a single, nonidentical internal calibrant (IC). This study represents the first systematic study of C. bovis metabolomics via an NMR-driven methodology, which advances the toolbox for quality control of TCM and provides a more definitive reference point for future chemical and biological studies of C. bovis as a valuable materia medica.

Free tocopherols and tocotrienols in 82 plant species' oil: Chemotaxonomic relation as demonstrated by PCA and HCA.

The tocopherol (T) and tocotrienol (T3) profile were investigated in the present study for four hundred and eighteen plant oil samples, including thirty-one families, eighty-two species, and five cross-species. Fifteen species were dominated by tocotrienols, while sixty-seven - by tocopherols. The mean proportion of γ-T was almost half of the total tocochromanol content (49.3%) in the investigated samples, while α-T constituted to one quarter (25.0%), and the remaining other tocochromanols were present as minor constituents. A strong relationship between the taxonomic plant origin and the presence of the characteristic tocochromanol profile in oils obtained from those plants was noted. This is the first study to demonstrate that not only monocotyledonous, but also dicotyledons families can be rich in tocotrienols. The usefulness of statistical tools - principal component analysis (PCA) and hierarchical cluster analysis (HCA) for plant sample discrimination based on their tocochromanol profile was also shown.

In vivo phosphorus magnetic resonance spectroscopic imaging of the whole human liver at 7 T using a phosphorus whole-body transmit coil and 16-channel receive array: Repeatability and effects of principal component analysis-based denoising.

Quantitative three-dimensional (3D) imaging of phosphorus (31 P) metabolites is potentially a promising technique with which to assess the progression of liver disease and monitor therapy response. However, 31 P magnetic resonance spectroscopy has a low sensitivity and commonly used 31 P surface coils do not provide full coverage of the liver. This study aimed to overcome these limitations by using a 31 P whole-body transmit coil in combination with a 16-channel 31 P receive array at 7 T. Using this setup, we determined the repeatability of whole-liver 31 P magnetic resonance spectroscopic imaging (31 P MRSI) in healthy subjects and assessed the effects of principal component analysis (PCA)-based denoising on the repeatability parameters. In addition, spatial variations of 31 P metabolites within the liver were analyzed. 3D 31 P MRSI data of the liver were acquired with a nominal voxel size of 20 mm isotropic in 10 healthy volunteers twice on the same day. Data were reconstructed without denoising, and with PCA-based denoising before or after channel combination. From the test-retest data, repeatability parameters for metabolite level quantification were determined for 12 31 P metabolite signals. On average, 31 P MR spectra from 100 ± 25 voxels in the liver were analyzed. Only voxels with contamination from skeletal muscle or the gall bladder were excluded and no voxels were discarded based on (low) signal-to-noise ratio (SNR). Repeatability for most quantified 31 P metabolite levels in the liver was good to excellent, with an intrasubject variability below 10%. PCA-based denoising increased the SNR ~ 3-fold, but did not improve the repeatability for mean liver 31 P metabolite quantification with the fitting constraints used. Significant spatial heterogeneity of various 31 P metabolite levels within the liver was observed, with marked differences for the phosphomonoester and phosphodiester metabolites between the left and right lobe. In conclusion, using a 31 P whole-body transmit coil in combination with a 16-channel 31 P receive array at 7 T allowed 31 P MRSI acquisitions with full liver coverage and good to excellent repeatability.

Study on the Correlation Between the Appearance Traits and Intrinsic Chemical Quality of Bitter Almonds Based on Fingerprint-Chemometrics.

Bitter almond is a well-known and commonly used traditional Chinese medicine (TCM) for relieving coughs and asthma. However, the bioactive chemical composition of bitter almonds, especially their amygdalin content, which determines their quality for TCM use, is variable and this can cause problems with formulating and prescribing TCMs based on bitter almonds. Therefore, a simple method was developed to evaluate the compositional quality of bitter almonds from their appearance traits, based on a combination of chromatographic fingerprinting and chemometrics. Bitter almonds were analyzed by high-performance liquid chromatography (HPLC). Hierarchical cluster analysis (HCA) and principal components analysis (PCA) were applied to classify bitter almonds, which split the samples into two independent clusters. Three chemical markers (amygdalin, prunasin, and one unidentified component) were found by partial least squares-discriminant analysis (PLS-DA). What's more, a new PLS-DA model was reconstructed to confirm the obtained chemical markers from PLS-DA. Additionally, the appearance trait indices and amygdalin content of bitter almond were determined and the classification was confirmed by one-way analysis of variance. This method can easily determine the quality of bitter almonds from their appearance alone, high quality correlated closely with kernels that were larger, oblong in shape and heavier.