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Fig. 18 in Review of lignans from 2019 to 2021: Newly reported compounds, diverse activities, structure-activity relationships and clinical applications

Fig. 18. The "source-category-activities" network of lignans. (The green nodes represent the source (families), the red nodes indicate the category, and the purple nodes emblem the activities). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 17 in Review of lignans from 2019 to 2021: Newly reported compounds, diverse activities, structure-activity relationships and clinical applications

Fig. 17. The potential structure-activity relationships of lignans in antitumor, anti-inflammatory and antioxidant effects.

Fig. 16 in Review of lignans from 2019 to 2021: Newly reported compounds, diverse activities, structure-activity relationships and clinical applications

Fig. 16. Structure based activity distribution. (A) The proportion of pharmacological activities; (B) distribution of bioactivities in different classification.

Fig. 15 in Review of lignans from 2019 to 2021: Newly reported compounds, diverse activities, structure-activity relationships and clinical applications

Fig. 15. Distribution of molecular resources analysis. (A) Main classifications of lignans; (B) distribution of lignan subclass structures; (C) distribution of lignans in top eight families.

Fig. 16 in Stilbenes: Source plants, chemistry, biosynthesis, pharmacology, application and problems related to their clinical Application-A comprehensive review

Fig. 16. Biological activities of stilbenes and their action mechanisms: The major biological activities of stilbenes are anticancer (through inhibiting β-hexosaminidase, DNA topoisomerase, expression of cylin B1 & D1, and NOR 1 activity); anti-inflammatory (through inhibition of expression of proinflammatory cytokines such as Tumor necrosis factor-alpha (TNF-α) and Interleukin-1 (IL-1)); regulation of Nrf2/HO-1 and NF-kB/ TGF-β pathway as well as inhibiting direct binding between siCAM-1 and LFA-1); antimicrobial (by damaging microbial cell wall and cell membrane damage, condensation of cytoplasm, perturbation of membrane potential, interacting with the conserved ubiquitin-specific protease residues of PLpro), and down-regulation of ergosterol biosynthesis and Camp/Ras pathway; antidiabetic (through inhibiting TNF-α, α-glucosidase, intestinal sucrose transfer, elevation of blood glucose as well as inducing/ increasing PPAR gamma 2 and GLUT4); antioxidant (through inhibiting lipid peroxidation, NO production, NOS activity, and increasing SOD activity); and neuroprotective (by inhibiting NOS activity, NO production, and HO-1 expression) activities.

Fig. 12 in Stilbenes: Source plants, chemistry, biosynthesis, pharmacology, application and problems related to their clinical Application-A comprehensive review

Fig. 12. Biosynthesis of stilbenes in microbes: For high production of stilbenes in microbes such as E. coli, the metabolic pathway of malonyl-CoA, the major and common extender substrate during conversion of coumaroyl, cinnamyl, and caffeoyl-CoAs to their respective monomeric stilbenes, is mainly manipulated. Enzymes of side pathways leading to the synthesis of fatty acids and acetate from acetyl-CoA, the direct precursor of malonyl-CoA, are inhibited, or their encoding enzymes are down-regulated or knocked out. For more efficient and high production of the stilbenes, there is also host, pathway, and enzyme engineering in the pathway of converting coumaroyl, cinnamyl, and caffeoyl- CoAs to monomeric stilbenes using STS.

Fig. 15 in Stilbenes: Source plants, chemistry, biosynthesis, pharmacology, application and problems related to their clinical Application-A comprehensive review

Fig. 15. Chemical synthesis of resveratrol derivatives: The derivatives 3,4′,5-trimethoxy-cis-stilbene (b), 3,4′,5-trimethoxy-trans-stilbene (c), 3,4,4′,5-tetramethoxytrans-stilbene (DMU-212, d), 2,3′,4,4′,5′-pentamethoxy-trans-stilbene (PMS, e), and 2′,3,4′,5-tetramethoxy (TMS; f) are synthesized by methoxylation of the central resveratrol (a), while the synthetic analogs 3′,4′,3,5-tetrahydroxy-trans-stilbene (piceatannol); (g) and 3,3′,4,4′,5,5′-hexahydroxy-trans-stilbene (h) are produced by hydroxylation of (a). The result of fluorination and esterification is 3,4-difluoro-4′-acetoxy-trans-stilbene (i), while bromination and methoxylation give 3,4,5-trimethoxy-4′-bromostilbene (j). The analogous 2,3-thiazolidin-4-one RSV derivatives (l and k) are synthesized through replacement of the olefinic group of (a) by heterocyclic compounds.

Fig. 1 in Stilbenes: Source plants, chemistry, biosynthesis, pharmacology, application and problems related to their clinical Application-A comprehensive review

Fig. 1. Phylogenetic tree of known stilbene-producing plants: Each family was marked with a different color in the figure. The circle-marked species are capable of producing stilbenes. Kappaphycus striatum (JN897024.1) and Silvetia siliquosa (JF718409.1) are included as out-groups. The phylogenetic tree was constructed using the ITS2 (ribosomal internal transcribed spacer 2) genus sequence. ITS2 sequences were obtained from NCBI (National Center for Biotechnology Information) (https://www.ncbi.nlm.nih.gov/). Some unannotated sequences were identified and delimited based on Hidden Markov models (HMMs), which was performed through the online website-ITS2 Database (http://its2.bioapps.biozentrum.uni-wuerzburg.de/). The MUSCLE program in MEGA6.0 software was used to perform multiple sequence alignments, and the neighbor-joining (NJ) method was used to construct phylogenetic trees with 1000 bootstrap replicates. The kimura-2- parameter substitution model was also employed, and the confidence interval was 95%. The evolutionary tree is visualized and beautified by the online software iTOL (https://itol.embl.de/). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 11 in Stilbenes: Source plants, chemistry, biosynthesis, pharmacology, application and problems related to their clinical Application-A comprehensive review

Fig. 11. Biosynthesis of stilbenes in plant suspension cell culture: plants with a high stilbene content will be cut to a specific size. These will be incubated in agarized medium (Murashige and Skoog (MS) medium or CHU (N6) medium or Gamborg's B5 medium (B5)) with supplements such as 6-benzyl amino purine (6-BA), kinetin (KT), Naphthalene acetic acid (NAA), and 2,4-Dichlorophenoxyacetic acid (2,4-D). After some specific days, friable cells will be produced in the medium, and these cells are then transferred into a new fresh medium with the specific supplements. Finally, elicitors such as 12-oxo-phytodienoic acid (OPDA), cornatine (COR), jasmonic acid (JA), methyl jasmonate (MeJA), salicylic acid (SA), ethylene (ET), abscisic acid (ABA), and reactive oxygen species (ROS) will be added for high production of stilbenes.

Fig. 14 in Stilbenes: Source plants, chemistry, biosynthesis, pharmacology, application and problems related to their clinical Application-A comprehensive review

Fig. 14. Synthetic derivatives of CA-4 (1): These are produced by replacement, substitution, and modification at both the cis-olefinic bond and the aromatic rings of 1. N-acyl hydrazone CA-4 (4), azo CA-4 (3), 1, 3, 4, oxadiazole CA-4 (9), benzoxazole CA-4 (8) which are produced by replacement and modifications at the olefinic group. Through modifications to the cis-olefinic bond and aromatic rings of CA-4, analogs such as 2 and 7 (benzothiazole derivatives of CA-4 with fluorine), 5 and 6 (imidazole and indole derivatives of CA-4) are also synthesized.

opencc-zeroAug 2023View details →

Supplementary material 1 from: Sakhnatska N, Aliekperova N, Kosyachenko K, Kostenko A (2023) The application of digital tools in Ukrainian pharmacies within holistic marketing. Pharmacia 70(3): 625-633. https://doi.org/10.3897/pharmacia.70.e108555

Survey for research the attitude of pharmacists to digitalization processes in ukrainian pharmacies within holistic marketing

opencc-by-4.0May 2023View details →

Density Functional Theory and Machine Learning for Electrochemical Square-Scheme Prediction: An Application to Quinone-type Molecules Relevant to Redox Flow Batteries

The uploaded data contains (i) "01_Data" optimized molecular structure in XYZ format and the primary attributes and SMILES, (ii) "02_Datasets" datasets used in the publication, and (iv) "03_pynb_script" a Jupyter-Notebook. The 01_Data directory contains more than 8000 subdirectories. Each is for a molecule that undergoes a two-proton two-electron transfer reaction. In each subdirectory, one finds the following files: (1) directories named corresponding to the ones in Figure 1 of the paper. Inside each, there are geometries and properties in XYZ and CSV format, respectively. (2) "freeEnergy.dat" contains the free energy of different states. (3) "schemesquare.dat" has the parameters of the electrochemical scheme of square representation. ├── A │   ├── info.csv │   └── pos.xyz ├── A1- │   ├── info.csv │   └── pos.xyz ├── A2- │   ├── info.csv │   └── pos.xyz ├── AH │   ├── info.csv │   └── pos.xyz ├── AH1+ │   ├── info.csv │   └── pos.xyz ├── AH1- │   ├── info.csv │   └── pos.xyz ├── AH2 │   ├── info.csv │   └── pos.xyz ├── AH21+ │   ├── info.csv │   └── pos.xyz ├── AH22+ │   ├── info.csv │   └── pos.xyz ├── freeEnergy.dat └── schemesquare.dat ****************************************************** The new version (v1.1) contains some updates around: (i) The DFT calculations workflow in a folder called "04_workflow_of_DFT"           The Gaussian input files have been explained in the "README" file. (ii) The Python scripts for data extraction have been added and can be found in "05_how_to_extracted_data" (iii) We explained how to compute the Purbaix diagram in great detail "06_how_to_compute_Pourbaix_diagram/" All these changes/improvements were applied/made following the Referee of Digital Discovery Journal. Here, we would like to thank him/her.

Fig. 4 in Biochemical and molecular insights of PGPR application for the augmentation of carotenoids, tocopherols, and folate in the foliage of Moringa oleifera

Fig. 4. HPLC Chromatograms of 1–5,6,7,8 tetrahydro folic acid (THF) in Control and 937b- B. subtilis IN937b treated M. oleifera foliage.

Fig. 3 in Biochemical and molecular insights of PGPR application for the augmentation of carotenoids, tocopherols, and folate in the foliage of Moringa oleifera

Fig. 3. HPLC Chromatograms of 1- Violaxanthin, 2- Lutein, 3- Chl b, 4-Chl a, 5- β-carotene in control and GBO3- B. subtilis GB03 treated M. oleifera foliage.

Fig. 5 in Biochemical and molecular insights of PGPR application for the augmentation of carotenoids, tocopherols, and folate in the foliage of Moringa oleifera

Fig. 5. Differential expression of mRNA levels of γ-tocopherol methyltransferase (γ-TMT), phytoene synthase (PSY), phytoene desaturase (PDS), lycopene β-cyclase (LBC) and dihydrofolate reductase thymidylate (DHFR-TS) in M. oleifera foliage after treatment with GB03-B. subtilis GB03, T4-B. pumilus T4, COM1- Combination 1, COM2- Combination 2, COM3-Combination 3. Experiments were repeated three times, each with three replicates. Columns without a common lowercase letter indicate significantly different values among treatments based on Tukey's test (P value ≤ 0.05).

Fig. 2 in Biochemical and molecular insights of PGPR application for the augmentation of carotenoids, tocopherols, and folate in the foliage of Moringa oleifera

Fig. 2. HPLC Chromatograms of 1- δ-tocopherol, 2- γ-tocopherol and 3- α-tocopherol in control, 937a- B. amyloliquefaciens IN937a and SE34- B. pumilus SE34 treated M. oleifera foliage.

Fig. 1. M. oleifera treated with 1 in Biochemical and molecular insights of PGPR application for the augmentation of carotenoids, tocopherols, and folate in the foliage of Moringa oleifera

Fig. 1. M. oleifera treated with 1) B. amyloliquefaciens IN937a, 2) B. subtilis IN937b, 3) Brevibacillus brevis IPC 11, 4) B. subtilis GB03, 5) B. pumilus INR7, 6) B. pumilus SE34, 7) B. pumilus T4, 8) P. fluorescens UOM14 shown compared to control.

opennotspecifiedJun 2020View details →

Fig. 6 in Acetogenins from Annonaceae family. Their potential biological applications

Fig. 6. Chromatographic and spectroscopic methods employed. Results summary: Involves the formation of a pink magenta compound by reaction with Kedde's reagent, coincidence or similarity in retention times during a chromatographic run or excellent correlation between fragmentation patterns.

opencc-by-4.0Aug 2023View details →

Dataset associated to the manuscript "A novel method for characterising the inter- and intra-lake variability of CH4 emissions: validation and application across a latitudinal transect in the Alpine region"

The dataset comprises data collected from nine specifically chosen lakes located across the eastern Alps during the ALCH4 project. The primary objective of this project was to assess the efficacy of a mobile Eddy Covariance platform in characterizing CH4 emissions. The field measurements were conducted throughout the ice-free periods in the years 2018 and 2019. This dataset encompasses: i) the EddyPro 7.0.6 (LI-COR Inc., Lincoln, NE, USA) output for all Eddy Covariance campaigns; ii) outcomes of the chamber measurements; iii) data obtained from surface samples.  This research was funded by the Autonomous Province of Bozen/Bolzano.