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Fig. 5 in Assessing the diversity of anthocyanin composition in various tissues of purple corn (Zea mays L.)
Fig. 5. Heatmap of the average proportion of each compound separated by cluster, Rows indicate compound identities in Table 2. The color of each compound is scaled according to the legend. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3 in Classification of sugarcane genotypes susceptible and resistant to the initial attack of sugarcane borer Diatraea saccharalis using epicuticular wax composition
Fig. 3. Graph with the importance of each selected compound by OPSDA. A) Resistant class – before infestation; B) Susceptible class – before infestation; C) Resistant class – after infestation; and D) Susceptible class – after infestation.
Fig. 2 in Classification of sugarcane genotypes susceptible and resistant to the initial attack of sugarcane borer Diatraea saccharalis using epicuticular wax composition
Fig. 2. Classification of GC-MS dataset before (A–D) and after (E–H) infestation for PLS-DA, LDA, OPSDA, and GA-LDA models. Filled red circles (●) and empty red circles (○) are samples of resistant class. Filled black squares (■) and empty black squares (□) are samples of susceptible class. Filled and empty shapes refer respectively to training and test sets. AI: after infestation; BI: before infestation; Res: resistant; Sus: susceptible. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 1 in Classification of sugarcane genotypes susceptible and resistant to the initial attack of sugarcane borer Diatraea saccharalis using epicuticular wax composition
Fig. 1. Chromatogram obtained from refined wax after derivatization of genotypes IM76-228 (resistant) and RB047016 (susceptible) highlights important peaks. AI: after infestation; BI: before infestation; Res: resistant; Sus: susceptible. Peak number identification was listed in Table 2.
Fig. 1 in Comprehensive evaluation of Bletilla striata and its substitutes by combining phenotypic characteristic, chemical composition, and anti-melanogenic activity
Fig. 1. Plant morphological characteristics of B. striata (A1 aerial part, A2 pseudobulb), B. ochracea (B1 aerial part, B2 pseudobulb) and B. formosana (C1 aerial part, C2 pseudobulb).
Fig. 3 in Comprehensive evaluation of Bletilla striata and its substitutes by combining phenotypic characteristic, chemical composition, and anti-melanogenic activity
Fig. 3. UPLC chromatographic fingerprints of 27 Bletillae Rhizoma samples (S1–S27) and the reference fingerprint (R). The peaks marked with 1–19 represent the 19 common peaks.
Fig. 2 in Comprehensive evaluation of Bletilla striata and its substitutes by combining phenotypic characteristic, chemical composition, and anti-melanogenic activity
Fig. 2. Microscopic characteristics of B. striata (A), B. ochracea (B), and B. formosana (C). (1.Epidermal cell 2. Raphid of calcium oxalate 3. Mucilage cell 4. Vessel 5. Fiber 6. Starch granule).
Fig. 9 in Comprehensive evaluation of Bletilla striata and its substitutes by combining phenotypic characteristic, chemical composition, and anti-melanogenic activity
Fig. 9. The docking complex of two compounds with tyrosinase and adenylate cyclase. (A) Coelonin in active pocket site of tyrosinase. (B) Batatasin III in an active pocket site of adenylate cyclase. (C) Coelonin formed 2 hydrogen bonds with the amino acid residues of tyrosinase. (D) Batatasin III formed 2 hydrogen bonds with the amino acid residues of adenylate cyclase.
Fig. 8 in Comprehensive evaluation of Bletilla striata and its substitutes by combining phenotypic characteristic, chemical composition, and anti-melanogenic activity
Fig. 8. Total optical density of melanin(A) and anti-melanogenic effect(B) comparison of Control, Winona, B. striata (SR), B. formosana (FS), and B. ochracea (OS). Values given are the means ± SD (n = 30). *P <0.05, ***P <0.001 versus control group.
Fig. 3 in Seed tannin composition of tropical plants
Fig. 3. Examples of the UV chromatograms (280 nm), quantification data and biological activities of the proanthocyanidin-rich samples. a) Lacistema aggregatum, b) Cnestidium rufescens, c) Platypodium elegans. Abbreviations: 3-CQA: 3-O-caffeoylquinic acid, 5-CQA: 5-O-caffeoylquinic acid, CAF: caffeic acid derivative, CAT: catechin, ECAT: epicatechin, G: galloyl group, GCAT: gallocatechin, PA: proanthocyanidin (in the info box: portion of proanthocyanidins), PC: procyanidin, 2PC: dimeric PC, PD: prodelphinidin, 3PD: trimeric PD, PT: mass spectrometric quantitation of selected polyphenolics, HT: portion of hydrolysable tannins, FC: total phenolics quantified using Folin-Ciocalteu assay, pH 10: portion of easily oxidized total phenolics, PPC: protein precipitation capacity reported in relation to the total phenolics.
Fig. 2 in Seed tannin composition of tropical plants
Fig. 2. Examples of the UV chromatograms (280 nm), quantification data and biological activities of the ellagitannin-rich samples. a) Combretum laxum, b) Eugenia coloradoensis, c) Myrcia splendens. Abbreviations: CAT: catechin, EA: ellagic acid, ET: ellagitannin, GlcA: glucuronic acid, PA: proanthocyanidin (in the info box: portion of proanthocyanidins), PC: procyanidin, PT: mass spectrometric quantitation of selected polyphenolics, HT: portion of hydrolysable tannins, FC: total phenolics quantified using Folin-Ciocalteu assay, pH 10: portion of easily oxidized total phenolics, PPC: protein precipitation capacity reported in relation to the total phenolics.
Fig. 1 in Seed tannin composition of tropical plants
Fig. 1. Examples of the UV chromatograms (280 nm), quantification data and biological activities of the gallic acid derivative-rich samples. a) Doliocarpus multiflorus, b) Anacardium excelsum, c) Canavalia campylocarpa. Abbreviations: 1GG: monogalloyl glucose, 2GG: digalloyl glucose, 3GG: trigalloyl glucose, 3GG (GT): gallotannintype 3GG, 4GG: tetragalloyl glucose, CAT: catechin, G: galloyl group, PT: mass spectrometric quantitation of total phenolics, HT: portion of hydrolysable tannins, PA: portion of proanthocyanidins, FC: total phenolics quantified using Folin-Ciocalteu assay, pH 10: portion of easily oxidized total phenolics, PPC: protein precipitation capacity reported in relation to the total phenolics.
Figure S2.13 in Seed tannin composition of tropical plants
Figure S2.13). Presumably due to the lower number of hydroxyl groups, these PAs were more hydrophobic than PCs and PDs – the hump of Psychotria PAs began to elute at ca. 4.0 min as opposed to ca. 2.0 min of PDs and ca. 3.0 min of PCs in other species. While fragmentation patterns characteristic to PAs appear in the mass spectra (retro-Diels-Alder fragmentation, heterocyclic ring fission, and quinone-methide fragmentation; Friedrich et al., 2000; Gu et al., 2003), coelution makes the assignation of the fragment ions to the correct corresponding molecular ions impossible. Based on our knowledge on the oxidative activities of phenolics, the high activities of these samples (see the following section) would indicate a presence of pyrogallol moieties (Kim et al, 2018, 2020; Vihakas et al., 2014). However, this would also require highly unusual PA structures, as this would mean that there would be no additional hydroxyl groups in 258 Da subunits, and for 274 Da subunits, there would only be one, likely at positions 3, 5 or 7. Alternatively, the high activity of Psychotria extracts was governed by compounds that were not detected or identified in this study, or by an unknown structure/activity relationship.
Fig. 1 in Volatile constituents of Eupatorieae (Asteraceae). Compositional multivariate analysis of volatile oils from Southern Brazilian species in the subtribe Disynaphiinae
Fig. 1. Samplings for the study series showing subtribes of Eupatorieae with relative sizes (in number of species) both inside and outside the Rio Grande do Sul State territory. Fleishmanninae, Hebeclininae, Hofmeisterinae, Liatrinae, Neomirandeinae, Oaxacaninae, and Trichocoroniinae have no representatives in the area. For other subtribes, the number of species in the area and its proportion to the total number in the subtribe is represented in light green. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 5 in Volatile constituents of Eupatorieae (Asteraceae). Compositional multivariate analysis of volatile oils from Southern Brazilian species in the subtribe Disynaphiinae
Fig. 5. Compositional PCA of the chemical composition of VO of species from the subtribe Disynaphiinae (according to Rivera et al., 2016) sampled in Rio Grande do Sul, Southern Brazil. S. itatiayensis was transferred to an uncertain place, Grazielia was transferred to Neocabreria and Campovassouria was merged into Disynaphia. Samples were colored according to the newly proposed genera. Ten variables contributing the most to variability are depicted. Upper Left: PC1 and PC2; Upper Right: PC2 and PC3. The exclusion of S. itatiayensis from Symphyopappus is well-supported by the chemical data. Samples from R. tremula (green spheres in top-left (bottom panel), have a very similar chemistry to S. itatiayensis (yellow cube). Two samples of R. crenulata from the same area previously published by our group were included in the analysis (de Souza et al., 2007). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 4 in Volatile constituents of Eupatorieae (Asteraceae). Compositional multivariate analysis of volatile oils from Southern Brazilian species in the subtribe Disynaphiinae
Fig. 4. Compositional robust PCA of the chemical composition of VO of species from the subtribe Disynaphiinae (according to Rivera et al., 2016) sampled in Rio Grande do Sul, Southern Brazil. S. itatiayensis was transferred to an uncertain place while Grazielia was transferred to Neocabreria. Samples are identified by species and colored according to the newly proposed genera. PC1 and PC2. Two samples of R. crenulata from the same area previously published by our group were included in the analysis (de Souza et al., 2007).
Fig. 3 in Volatile constituents of Eupatorieae (Asteraceae). Compositional multivariate analysis of volatile oils from Southern Brazilian species in the subtribe Disynaphiinae
Fig. 3. Compositional PCA of the chemical composition of VO of species from the subtribe Disynaphiinae (King and Robinson, 1987) sampled in Rio Grande do Sul, Southern Brazil. Samples are colored according to genera. Ten variables contributing the most to variability are depicted. Top: PC2 and PC3; Bottom: PC2, PC3, and PC4 with Mahalanobis distances (Aconthostyles buniifolius was excluded for clarity). Two samples of R. crenulata from the same area previously published by our group were included in the analysis (de Souza et al., 2007).
Fig. 2 in Volatile constituents of Eupatorieae (Asteraceae). Compositional multivariate analysis of volatile oils from Southern Brazilian species in the subtribe Disynaphiinae
Fig. 2. The number of genera and species recognized in the subtribe Disynaphiinae is given in white, while the number of genera and species reported in the area as well as the number of sampled species is given in black. The number of species in the genus, species in the sampled area, and sampled species are given in gray alongside each genus.
Fig. 6 in Volatile constituents of Eupatorieae (Asteraceae). Compositional multivariate analysis of volatile oils from Southern Brazilian species in the subtribe Disynaphiinae
Fig. 6. Compositional robust PCA of the chemical composition of VO of species from the subtribe Disynaphiinae (according to Rivera et al., 2016) sampled in Rio Grande do Sul, Southern Brazil. Samples are identified at the species level and colored according to the newly proposed genera. Neocabreria serrulata (Critoniinae) and Urolepis hecatantha (Gyptidinae) are included after transference from their respective subtribes. Top panel: Grazielia was merged into Neocabreria. Bottom panel: Neocabreria and Grazielia were merged into Symphyopappus (excluding S. itatiayensis). Two samples of R. crenulata from the same area previously published by our group were included in the analysis (de Souza et al., 2007).
Fig. 4 in Cuticular wax composition contributes to different strategies of foliar water uptake in six plant species from foggy rupestrian grassland in tropical mountains
Fig. 4. Chain-length distribution of the very-long-chain (VLC) aliphatic compounds of leaf cuticular waxes of each of the six plant species with two different strategies of foliar water uptake. Data are shown as mean ± SD (n = 3). Bars stand for the contribution of a single chain-length to the total of VLC aliphatic wax load. Dark and grey bars represent plants with fast and slow FWU strategies, respectively. ACL: average-chain-length of the aliphatic wax fraction.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.