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19 pages, 5717 KiB  
Article
Exploring the Biological Potential of Mountain Germander Polyphenolic Extract on Cellular Model Macromolecules, Human Cell Lines, and Microbiome Representatives
by Ana Mandura Jarić, Ksenija Durgo, Ana Huđek Turković, Petra Petek, Andrea Petrinić, Danijela Šeremet, Aleksandra Vojvodić Cebin and Draženka Komes
Appl. Sci. 2024, 14(22), 10602; https://doi.org/10.3390/app142210602 (registering DOI) - 17 Nov 2024
Abstract
In the context of revitalizing the use of traditional plant species as remarkable sources of bioactive compounds, the determination of their biological effects is of utmost importance. Among Lamiaceae species, Teucrium montanum (Mountain Germander) represents understudied Mediterranean plant species; it is rich in [...] Read more.
In the context of revitalizing the use of traditional plant species as remarkable sources of bioactive compounds, the determination of their biological effects is of utmost importance. Among Lamiaceae species, Teucrium montanum (Mountain Germander) represents understudied Mediterranean plant species; it is rich in polyphenols, which are well-studied biologically active compounds for human disease prevention and the reduction of oxidative stress, i.e., phenolic acids, phenylethanoid glycosides, and flavonoids. For that purpose, the aim of this study was to investigate the antioxidant, cytotoxic, and genotoxic effects of Mountain Germander (MG) polyphenolic extract (0.025, 0.050, 0.150, and 0.500 mg extract mL−1) on the hepatocellular (HepG2), tongue (CAL 27), gastric (AGS), and colorectal (Caco-2) continuous human cancer cell lines, as well as its bacteriostatic potential on representative members of human microbiota. In addition, the antioxidant potential of the MG polyphenolic extract was determined using bovine serum album and DNA plasmid as cellular model macromolecules. In vitro analysis revealed a significant cytotoxic effect of all MG extract concentrations on AGS and Caco-2 cell lines after prolonged treatment (24 h). In addition, treatment with 0.500 mg extract mL−1 showed the most pronounced antioxidant effect under prolonged treatment (24 h) on CAL 27 and HepG2 cell lines. All of the applied MG extract concentrations seem to have a genoprotective effect on DNA plasmid. Furthermore, a significant inhibitory effect on E. coli was detected upon the treatment with 0.150 mg extract mL−1, reducing the cell viability by 56%. Full article
(This article belongs to the Special Issue Natural Products and Bioactive Compounds)
Show Figures

Figure 1

Figure 1
<p>Protein oxidation rate of bovine serum albumin (BSA) protein treated with Mountain Germander extract concentrations (0.025–0.500 mg mL<sup>−1</sup>). Statistical data processing was carried out by one-way analysis of variance with Tukey’s post hoc test. * = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to the negative control (water); a = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.025 mg mL<sup>−1</sup>; b = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.050 mg mL<sup>−1</sup>; c = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.150 mg mL<sup>−1</sup>; d = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.500 mg mL<sup>−1</sup>.</p>
Full article ">Figure 2
<p>Visualization of oxidative damage of model DNA plasmid induced by UV-photolysis of H<sub>2</sub>O<sub>2</sub> during treatment with MG extract concentrations (0.025–0.500 mg mL<sup>−1</sup>). RCP: relaxed circular plasmid; SCCP: supercoiled circular plasmid; NC1: plasmid+buffer; NC2: H<sub>2</sub>O<sub>2</sub>; NC3: UV radiation; PC: plasmid + H<sub>2</sub>O<sub>2</sub> + UV radiation; 0.025–0.500: extract concentration for plasmid treatment (mg mL<sup>−1</sup>).</p>
Full article ">Figure 3
<p>The effect of Mountain Germander extract concentrations (0.025–0.500 mg mL<sup>−1</sup>) on DNA plasmid oxidative damage. SCCP/RCP = ratio of supercoiled and relaxed circular plasmid; NC = sum of all tested negative control; PC = positive control (plasmid + H<sub>2</sub>O<sub>2</sub> + UV radiation). Statistical data processing was carried out by one-way analysis of variance with Tukey’s post hoc test. # = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to the positive control; * = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to the negative control; a = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.025 mg mL<sup>−1</sup>; b = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.050 mg mL<sup>−1</sup>; c = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.150 mg mL<sup>−1</sup>; d = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.500 mg mL<sup>−1</sup>.</p>
Full article ">Figure 4
<p>Cell viability of tested lines: (<b>a</b>) CAL 27; (<b>b</b>) AGS; (<b>c</b>) Caco-2; and (<b>d</b>) HepG2 after 2 and 24 h of treatment with Mountain Germander extract concentrations (0.025–0.500 mg mL<sup>−1</sup>). One-way analysis of variance was carried out between the tested concentrations with Tukey’s post hoc test. The values marked with the sign # are statistically significantly (<span class="html-italic">p</span> &lt; 0.05) different in regard to the treatment time for each extract concentration, and were obtained by performing the Mann–Whitney test (<span class="html-italic">p</span> &lt; 0.05). * = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to negative control (water); a = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.025 mg mL<sup>−1</sup>; b = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.050 mg mL<sup>−1</sup>; c = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.150 mg mL<sup>−1</sup>; d = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.500 mg mL<sup>−1</sup>.</p>
Full article ">Figure 4 Cont.
<p>Cell viability of tested lines: (<b>a</b>) CAL 27; (<b>b</b>) AGS; (<b>c</b>) Caco-2; and (<b>d</b>) HepG2 after 2 and 24 h of treatment with Mountain Germander extract concentrations (0.025–0.500 mg mL<sup>−1</sup>). One-way analysis of variance was carried out between the tested concentrations with Tukey’s post hoc test. The values marked with the sign # are statistically significantly (<span class="html-italic">p</span> &lt; 0.05) different in regard to the treatment time for each extract concentration, and were obtained by performing the Mann–Whitney test (<span class="html-italic">p</span> &lt; 0.05). * = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to negative control (water); a = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.025 mg mL<sup>−1</sup>; b = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.050 mg mL<sup>−1</sup>; c = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.150 mg mL<sup>−1</sup>; d = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.500 mg mL<sup>−1</sup>.</p>
Full article ">Figure 5
<p>Induction of free radicals (ROS) on cell lines: (<b>a</b>) CAL 27; (<b>b</b>) AGS; (<b>c</b>) Caco-2; and (<b>d</b>) HepG2 after 2 and 24 h of treatment with Mountain Germander extract concentrations (0.025–0.500 mg mL<sup>−1</sup>). One-way analysis of variance was carried out between the tested concentrations with Tukey’s post hoc test. The values marked with the sign # are statistically significantly (<span class="html-italic">p</span> &lt; 0.05) different in regard to the treatment time for each extract concentration, and were obtained by performing the Mann–Whitney test (<span class="html-italic">p</span> &lt; 0.05). * = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to negative control (water); a = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.025 mg mL<sup>−1</sup>; b = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.050 mg mL<sup>−1</sup>; c = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.150 mg mL<sup>−1</sup>; d = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.500 mg mL<sup>−1</sup>.</p>
Full article ">Figure 6
<p>The effect of Mountain Germander extract concentrations (0.025–0.500 mg mL<sup>−1</sup>) on DNA tail length and tail intensity of the cell lines: (<b>a</b>,<b>b</b>) CAL 27; (<b>c</b>,<b>d</b>) AGS; (<b>e</b>,<b>f</b>) Caco-2; and (<b>g</b>,<b>h</b>) HepG2 cells after 2 and 24 h of treatment. One-way analysis of variance was carried out between the tested concentrations with Tukey’s post hoc test. The values marked with the sign # are statistically significantly (<span class="html-italic">p</span> &lt; 0.05) different in regard to the treatment time for each extract concentration, and were obtained by performing the Mann–Whitney test (<span class="html-italic">p</span> &lt; 0.05). * = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to negative control (culture medium); a = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.025 mg mL<sup>−1</sup>; b = significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.050 mg mL<sup>−1</sup>; c = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.150 mg mL<sup>−1</sup>; d = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.500 mg mL<sup>−1</sup>.</p>
Full article ">Figure 6 Cont.
<p>The effect of Mountain Germander extract concentrations (0.025–0.500 mg mL<sup>−1</sup>) on DNA tail length and tail intensity of the cell lines: (<b>a</b>,<b>b</b>) CAL 27; (<b>c</b>,<b>d</b>) AGS; (<b>e</b>,<b>f</b>) Caco-2; and (<b>g</b>,<b>h</b>) HepG2 cells after 2 and 24 h of treatment. One-way analysis of variance was carried out between the tested concentrations with Tukey’s post hoc test. The values marked with the sign # are statistically significantly (<span class="html-italic">p</span> &lt; 0.05) different in regard to the treatment time for each extract concentration, and were obtained by performing the Mann–Whitney test (<span class="html-italic">p</span> &lt; 0.05). * = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to negative control (culture medium); a = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.025 mg mL<sup>−1</sup>; b = significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.050 mg mL<sup>−1</sup>; c = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.150 mg mL<sup>−1</sup>; d = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.500 mg mL<sup>−1</sup>.</p>
Full article ">Figure 7
<p>Cell viability of tested bacterial strains treated with Mountain Germander extract concentrations (0.025–0.500 mg mL<sup>−1</sup>). One-way analysis of variance was carried out with Tukey’s post hoc test. * = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to negative control (PBS buffer); a = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.025 mg mL<sup>−1</sup>; b = significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.050 mg mL<sup>−1</sup>; c = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.150 mg mL<sup>−1</sup>; d = statistically significantly different (<span class="html-italic">p</span> &lt; 0.05) compared to 0.500 mg mL<sup>−1</sup>.</p>
Full article ">
16 pages, 5372 KiB  
Article
Exposure Scenarios for Estimating Contaminant Levels in Healthy Sustainable Dietary Models: Omnivorous vs. Vegetarian
by Helena Ramos, Ana Reis-Mendes, Marta Silva, Mafalda Ribeiro, Ana Margarida Araújo, Cristiane Borges, Olga Viegas, Armindo Melo, Zita Martins, Miguel A. Faria and Isabel M. P. L. V. O. Ferreira
Foods 2024, 13(22), 3659; https://doi.org/10.3390/foods13223659 (registering DOI) - 17 Nov 2024
Abstract
Consumers are regularly exposed to well-known food contaminants (FCs), which are typically assessed for risk on an individual basis. However, there is limited knowledge about the overall levels and combinations of these compounds depending on dietary choices. The goal of this study was [...] Read more.
Consumers are regularly exposed to well-known food contaminants (FCs), which are typically assessed for risk on an individual basis. However, there is limited knowledge about the overall levels and combinations of these compounds depending on dietary choices. The goal of this study was to estimate the real-life mixtures of FCs in different dietary models by integrating extensive data from the scientific literature concerning the reliable quantification of FCs in foods. A FAIR database detailing the occurrence of 73 FCs in 16 foods commonly consumed was built. The data were integrated into an omnivorous and a vegetarian dietary model. A weighted estimate of the 25th, 50th, and 75th percentiles of FCs in both dietary models revealed that the omnivorous model presented slightly higher levels of FCs than the vegetarian. At the 25th percentile, the FC levels in both dietary models fall within the European Food Safety Authority (EFSA) reference exposure levels for chemical hazards, except for arsenic, lead, cadmium, fumonisin B1, and OTA. At the 75th percentile, the FC levels exceed the EFSA reference levels for those FCs and additional mycotoxins. Using in vitro models, the 25th percentile can mimic real-life FC exposure, while the 75th percentile simulates a possible worst-case scenario. Full article
(This article belongs to the Special Issue Prospects for Risks and Benefits in the Context of Food and Health)
24 pages, 13337 KiB  
Article
Variations over 20 Years in Vegetation Dynamics and Its Coupled Responses to Individual and Compound Meteorological Drivers in Sichuan Province, China
by Qian Deng, Chenfeng Zhang, Jiong Dong, Yanchun Li, Yunyun Li, Yi Huang, Hongxue Zhang and Jingjing Fan
Atmosphere 2024, 15(11), 1384; https://doi.org/10.3390/atmos15111384 (registering DOI) - 17 Nov 2024
Abstract
Abstract: This study presents an innovative investigation into the spatiotemporal dynamics of vegetation growth and its response to both individual and composite climatic factors. The Normalized Difference Vegetation Index (NDVI), derived from SPOT satellite remote sensing data, was employed as a proxy for [...] Read more.
Abstract: This study presents an innovative investigation into the spatiotemporal dynamics of vegetation growth and its response to both individual and composite climatic factors. The Normalized Difference Vegetation Index (NDVI), derived from SPOT satellite remote sensing data, was employed as a proxy for vegetation growth. Multiple analytical methods, including the coefficient of variation, Mann–Kendall trend analysis, and Hurst index, were applied to characterize the spatiotemporal patterns of the NDVI in Sichuan Province from 2000 to 2020. The Standardized Precipitation Evapotranspiration Index (SPEI) was calculated using monthly precipitation and temperature data from 45 meteorological stations to examine the influence of composite climatic factors on vegetation growth, while the time lag effects between the NDVI and various climatic variables were also explored. Our findings unveil three key insights: (1) Vegetation coverage in Sichuan Province exhibited an overall increasing trend, with the highest NDVI values in summer and the lowest in winter. Significant NDVI fluctuations were observed in spring in the western Sichuan plateau and in winter in northern, eastern, and southern Sichuan. (2) A significant upward trend in the NDVI was detected across Sichuan Province, except for Chengdu Plain, where a downward trend prevailed outside the summer season. (3) On shorter time scales, the NDVI was positively correlated with precipitation, temperature, and the SPEI, with a one-month lag. The response of the NDVI to sunlight duration showed a two-month lag, with the weakest correlation and a five-month lag in western Sichuan. This research advances our understanding of the complex interactions between vegetation dynamics and climatic factors in Sichuan Province and provides valuable insights for predicting future vegetation growth trends. Full article
27 pages, 1722 KiB  
Review
Beyond Essential Oils: Diterpenes, Lignans, and Biflavonoids from Juniperus communis L. as a Source of Multi-Target Lead Compounds
by Alina Arabela Jojić, Sergio Liga, Diana Uţu, Graţiana Ruse, Liana Suciu, Andrei Motoc, Codruța Marinela Şoica and Diana-Simona Tchiakpe-Antal
Plants 2024, 13(22), 3233; https://doi.org/10.3390/plants13223233 (registering DOI) - 17 Nov 2024
Abstract
Abstract: Common Juniper (Juniperus communis L.) is a gymnosperm that stands out through its fleshy, spherical female cones, often termed simply “berries”. The cone berries and various vegetative parts (leaves, twigs and even roots) are used in traditional phytotherapy, based on [...] Read more.
Abstract: Common Juniper (Juniperus communis L.) is a gymnosperm that stands out through its fleshy, spherical female cones, often termed simply “berries”. The cone berries and various vegetative parts (leaves, twigs and even roots) are used in traditional phytotherapy, based on the beneficial effects exerted by a variety of secondary metabolites. While the volatile compounds of Juniperus communis are known for their aromatic properties and have been well-researched for their antimicrobial effects, this review shifts focus to non-volatile secondary metabolites—specifically diterpenes, lignans, and biflavonoids. These compounds are of significant biomedical interest due to their notable pharmacological activities, including antioxidant, anti-inflammatory, antimicrobial, and anticancer effects. The aim of this review is to offer an up-to-date account of chemical composition of Juniperus communis and related species, with a primary emphasis on the bioactivities of diterpenes, lignans, and biflavonoids. By examining recent preclinical and clinical data, this work assesses the therapeutic potential of these metabolites and their mechanisms of action, underscoring their value in developing new therapeutic options. Additionally, this review addresses the pharmacological efficacy and possible therapeutic applications of Juniperus communis in treating various human diseases, thus supporting its potential role in evidence-based phytotherapy. Full article
(This article belongs to the Section Phytochemistry)
11 pages, 455 KiB  
Review
Understanding the Best Nutritional Management for Creutzfeldt–Jakob Disease Patients: A Comparison Between East Asian and Western Experiences
by Alessia Perna, Massimo Santoro and Elisa Colaizzo
Life 2024, 14(11), 1496; https://doi.org/10.3390/life14111496 (registering DOI) - 17 Nov 2024
Abstract
(1) Background: Creutzfeldt–Jakob disease (CJD) is a rare and fatal neurodegenerative disorder caused by the accumulation of an altered prion protein, which usually leads to death within one year after clinical onset. CJD patients usually present with rapid cognitive impairment associated with declines [...] Read more.
(1) Background: Creutzfeldt–Jakob disease (CJD) is a rare and fatal neurodegenerative disorder caused by the accumulation of an altered prion protein, which usually leads to death within one year after clinical onset. CJD patients usually present with rapid cognitive impairment associated with declines in cerebellar, motor, visual, behavioral, and swallowing functions. Moreover, CJD patients lose their ability to eat and take medications orally very early on in treatment; nevertheless, there are no specific nutritional guidelines for this disease shared worldwide. (2) Methods: This review aims to describe the nutritional outcomes of CJD patients in Western countries to compare them with those described in East Asian countries and then aims to explore the most recent trends in the nutritional management of CJD patients, including some dietary compounds that present neuroprotective effects. (3) Results: In Japan’s, Taiwan’s, and China’s healthcare systems, CJD patients receive intensive life-sustaining treatment that prolongs their survival (i.e., artificial feeding); conversely, in Western countries, intensive life-sustaining treatments like tube feeding are not commonly provided to CJD patients. (4) Conclusions: It is difficult to pinpoint the reasons for these discrepancies around CJD palliative care supply, but it is clear that specific nutritional guidelines may directly improve the nutritional management of CJD patients and thus allow their families and caregivers to ensure the best end-of-life care for these patients. Full article
(This article belongs to the Section Physiology and Pathology)
15 pages, 6465 KiB  
Article
A Spectroscopic and In Silico Description of the Non-Covalent Interactions of Phthalic Acid Imide Derivatives with Deoxyribonucleic Acid—Insights into Their Binding Characteristics and Potential Applications
by Aleksandra Marciniak, Edward Krzyżak, Dominika Szkatuła, Krystian Mazurkiewicz and Aleksandra Kotynia
Molecules 2024, 29(22), 5422; https://doi.org/10.3390/molecules29225422 (registering DOI) - 17 Nov 2024
Abstract
The treatment of cancer represents one of the most significant challenges currently facing modern medicine. The search for new drugs that are effective in the treatment of patients is an ongoing endeavor. It is frequently the case that the molecular target of anticancer [...] Read more.
The treatment of cancer represents one of the most significant challenges currently facing modern medicine. The search for new drugs that are effective in the treatment of patients is an ongoing endeavor. It is frequently the case that the molecular target of anticancer drugs is a DNA molecule. The therapeutic effect of a drug is achieved by influencing the structure of a macromolecule or by inhibiting its function. Among the synthetic substances with potential anticancer effects, particular attention should be paid to phthalic acid imide derivatives. Three phthalimide derivatives are employed in the treatment of multiple myeloma: thalidomide, pomalidomide, and lenalidomide. Nevertheless, the search for new derivatives with a diverse range of biological activities is ongoing. In light of the above, the subject of our investigation is four non-toxic phthalic acid imide derivatives. The objective was to analyze the interaction of these compounds with DNA. The use of spectroscopic and in silico methods has enabled us to demonstrate that all of the tested analogs can act as ligands for deoxyribonucleic acid, forming non-covalent bonds with it. All four compounds tested interact with the ctDNA molecule, binding in its minor groove. The most stable complex is formed here between deoxyribonucleic acid and the C derivative, in which the -CF3 group is attached to the benzene ring. What is interesting and important, the described mechanism of action is analogous to that observed between ctDNA and thalidomide, pomalidomide, and lenalidomide. Full article
(This article belongs to the Section Bioorganic Chemistry)
Show Figures

Figure 1

Figure 1
<p>The structures of analyzed phthalic acid imide derivatives (<b>A</b>–<b>D</b>).</p>
Full article ">Figure 2
<p>The absorption spectra in the absence and presence of various molar concentrations (M) of ctDNA added to phthalic acid imide derivative solutions (10 μM): (<b>a</b>) compound <b>A</b>, (<b>b</b>) compound <b>B</b>, (<b>c</b>) compound <b>C</b>, and (<b>d</b>) compound <b>D</b>.</p>
Full article ">Figure 3
<p>The UV data fitting line to the Benesi–Hildebrand equation. The absorption changes assumed by the addition of ctDNA to phthalic acid imide derivative solutions (10 μM): compound <b>A</b> (black, dotted line), compound <b>B</b> (red, dashed line), compound <b>C</b> (blue, dash-dotted line), and compound <b>D</b> (green, solid line).</p>
Full article ">Figure 4
<p>The CD spectra of ctDNA with increasing the concentration of the tested compounds: (<b>a</b>) compound <b>A</b>, (<b>b</b>) compound <b>B</b>, (<b>c</b>) compound <b>C</b>, and (<b>d</b>) compound <b>D</b>. The measurements were performed for the following molar ratios of ctDNA to phthalimide analog: 1:0, 1:0.5, and 1:1.</p>
Full article ">Figure 5
<p>The emission spectra of (<b>a</b>) compound <b>A</b>, (<b>b</b>) compound <b>B</b>, and (<b>c</b>) compound <b>C</b> with ctDNA (1:1 reagents molar ratio) with the increasing NaCl concentration.</p>
Full article ">Figure 6
<p>The emission spectra of ctDNA–acridine orange complex with an increase in the concentration of the tested compounds: (<b>a</b>) compound <b>A</b>, (<b>b</b>) compound <b>B</b>, (<b>c</b>) compound <b>C</b>, and (<b>d</b>) compound <b>D</b>. The measurements were performed for the following molar ratios of ctDNA to phthalimide analog: 1:0, 1:0.5, 1:1, 1:1.5, and 1:2.</p>
Full article ">Figure 7
<p>The pose of compounds <b>A</b> (red), <b>B</b> (blue), <b>C</b> (green), and <b>D</b> (pink) in the DNA minor groove.</p>
Full article ">Figure 8
<p>The 2D plot of the interactions between (<b>A</b>–<b>D</b>) and DNA.</p>
Full article ">Figure 9
<p>The RMSD plots of the DNA backbone atoms for systems with compounds <b>A–D</b>.</p>
Full article ">
17 pages, 974 KiB  
Review
Chemical Composition, Bioactivities, and Applications of Spirulina (Limnospira platensis) in Food, Feed, and Medicine
by Maria P. Spínola, Ana R. Mendes and José A. M. Prates
Foods 2024, 13(22), 3656; https://doi.org/10.3390/foods13223656 (registering DOI) - 17 Nov 2024
Abstract
Spirulina (Limnospira platensis) is a microalga recognised for its rich nutritional composition and diverse bioactive compounds, making it a valuable functional food, feed, and therapeutic agent. This review examines spirulina’s chemical composition, including its high levels of protein, essential fatty acids, [...] Read more.
Spirulina (Limnospira platensis) is a microalga recognised for its rich nutritional composition and diverse bioactive compounds, making it a valuable functional food, feed, and therapeutic agent. This review examines spirulina’s chemical composition, including its high levels of protein, essential fatty acids, vitamins, minerals, and bioactive compounds, such as the phycocyanin pigment, polysaccharides, and carotenoids, in food, feed, and medicine. These compounds exhibit various biological activities, including antioxidant, anti-inflammatory, immunomodulatory, antiviral, anticancer, antidiabetic and lipid-lowering effects. Spirulina’s potential to mitigate oxidative stress, enhance immune function, and inhibit tumour growth positions it as a promising candidate for preventing chronic diseases. Additionally, spirulina is gaining interest in the animal feed sector as a promotor of growth performance, improving immune responses and increasing resistance to diseases in livestock, poultry, and aquaculture. Despite its well-documented health benefits, future research is needed to optimize production/cultivation methods, improve its bioavailability, and validate its efficacy (dose–effect relationship) and safety through clinical trials and large-scale human trials. This review underscores the potential of spirulina to address global health and nutrition challenges, supporting its continued application in food, feed, and medicine. Full article
(This article belongs to the Special Issue Microalgae in Food Systems: From Cultivation to Application)
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<p>Chemical composition, bioactive compounds, effects, and applications of spirulina microalga.</p>
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<p>SWOT analysis summarizing the strengths, weaknesses, opportunities, and threats associated with <span class="html-italic">Spirulina</span> utilization.</p>
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15 pages, 1463 KiB  
Article
Integration of FTIR Spectroscopy, Volatile Compound Profiling, and Chemometric Techniques for Advanced Geographical and Varietal Analysis of Moroccan Eucalyptus Essential Oils
by Aimen El Orche, Abdennacer El Mrabet, Amal Ait Haj Said, Soumaya Mousannif, Omar Elhamdaoui, Siddique Akber Ansari, Hamad M. Alkahtani, Shoeb Anwar Ansari, Ibrahim Sbai El Otmani and Mustapha Bouatia
Sensors 2024, 24(22), 7337; https://doi.org/10.3390/s24227337 (registering DOI) - 17 Nov 2024
Abstract
Eucalyptus essential oil is widely valued for its therapeutic properties and extensive commercial applications, with its chemical composition significantly influenced by species variety, geographical origin, and environmental conditions. This study aims to develop a reliable method for identifying the geographical origin and variety [...] Read more.
Eucalyptus essential oil is widely valued for its therapeutic properties and extensive commercial applications, with its chemical composition significantly influenced by species variety, geographical origin, and environmental conditions. This study aims to develop a reliable method for identifying the geographical origin and variety of eucalyptus oil samples through the application of advanced analytical techniques combined with chemometric methods. Essential oils from Eucalyptus globulus and Eucalyptus camaldulensis were analyzed using Gas Chromatography–Flame Ionization Detection (GC–FID) and Fourier Transform Infrared (FTIR) Spectroscopy. Chemometric analyses, including Orthogonal Partial Least Squares-Discriminant Analysis (O2PLS-DA) and Hierarchical Cluster Analysis (HCA), were utilized to classify the oils based on their volatile compound profiles. Notably, O2PLS-DA was applied directly to the raw FTIR data without additional spectral processing, showcasing its robustness in handling unprocessed data. For geographical origin determination, the GC–FID model achieved a Correct Classification Rate (CCR) of 100%, with 100% specificity and 100% sensitivity for both calibration and validation sets. FTIR spectroscopy achieved a CCR of 100%, specificity of 100%, and sensitivity of 100% for the calibration set, while the validation set yielded a CCR of 95.83%, specificity of 99.02%, and sensitivity of 94.44%. In contrast, the analysis based on species variety demonstrated 100% accuracy across all metrics CCR, specificity, and sensitivity—for both calibration and validation using both techniques. These findings underscore the effectiveness of volatile and infrared spectroscopy profiling for quality control and authentication, providing robust tools for ensuring the consistency and reliability of eucalyptus essential oils in various industrial and therapeutic applications. Full article
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<p>The geographical positions of the samples.</p>
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<p>Key Constituents of Eucalyptus Leaf Essential Oils.</p>
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<p>Comprehensive O2PLS-DA and HCA Analysis of Essential Oils: (<b>a</b>) Varietal Differentiation Score Plot, (<b>b</b>) Geographical Origin Score Plot, (<b>c</b>) Key Volatile Compound Loading Plot, and (<b>d</b>) HCA Dendrogram for Regional Classification (KE: Kenitra, TA: Taounate, TI: Tiflet, CA: Casablanca, KH: Khemisset, ME: Marrakech).</p>
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<p>FTIR Spectral Analysis of Essential Oils: Comparison of Spectral Profiles for Camaldulensis and Globulus Varieties (R1: Kenitra, R2: Taounate, R3: Tiflet for Camaldulensis; and R4: Casablanca, R5: Khemisset, R6: Marrakech for Globulus).</p>
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<p>Classification and Clustering of Eucalyptus Essential Oils: O2PLS-DA and HCA Analysis. (<b>a</b>): Classification of Eucalyptus Essential Oils by Variety: LV1 vs. LV2 Plot, (<b>b</b>): Geographical Origin Classification of Eucalyptus Essential Oils: LV1 vs. LV2 Plot, (<b>c</b>): Geographical Origin Classification of Eucalyptus Essential Oils: LV1 vs. LV3 Plot, and (<b>d</b>): Hierarchical Cluster Analysis (HCA) of Eucalyptus Essential Oils (KE: Kenitra, TA: Taounate, TI: Tiflet, CA: Casablanca, KH: Khemisset, ME: Marrakech).</p>
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21 pages, 3964 KiB  
Article
Emission and Transcriptional Regulation of Aroma Variation in Oncidium Twinkle ‘Red Fantasy’ Under Diel Rhythm
by Yan Chen, Shengyuan Zhong, Lan Kong, Ronghui Fan, Yan Xu, Yiquan Chen and Huaiqin Zhong
Plants 2024, 13(22), 3232; https://doi.org/10.3390/plants13223232 (registering DOI) - 17 Nov 2024
Abstract
Oncidium hybridum is one of the important cut-flowers in the world. However, the lack of aroma in its cut-flower varieties greatly limits the sustainable development of the Oncidium hybridum cut-flowers industry. This paper is an integral investigation of the diel pattern and influencing [...] Read more.
Oncidium hybridum is one of the important cut-flowers in the world. However, the lack of aroma in its cut-flower varieties greatly limits the sustainable development of the Oncidium hybridum cut-flowers industry. This paper is an integral investigation of the diel pattern and influencing factors of the aroma release of Oncidium Twinkle ‘Red Fantasy’. GC-MS analysis revealed that the release of 3-Carene peaked at 10:00, while Butyl tiglate and Prenyl senecioate did so at 14:00, with a diel rhythm. By analyzing the correlation network between aroma component synthesis and differentially expressed genes, 15 key structural genes were detected and regulated by multiple circadian rhythm-related transcription factors. Cluster-17371.18_TPS, Cluster-65495.1_TPS, Cluster-46699.0_TPS, Cluster-60935.10_DXS, Cluster-47205.4_IDI, and Cluster-65313.7_LOX were key genes in the terpenoid and fatty acid derivative biosynthetic pathway, which were co-expressed with aroma release. Constant light/dark treatments revealed that the diurnal release of 3-Carene may be influenced by light and the circadian clock, and Butyl tiglate and Prenyl senecioate may be mainly determined by endogenous circadian clock. Under constant light treatment, the TPS, DXS, IDI, and LOX genes seem to lose their regulatory role in the release of aroma compounds from Oncidium Twinkle ‘Red Fantasy’. Under constant dark treatment, the TPS genes were consistent with the release pattern of 3-Carene, which may be a key factor in regulating the diel rhythm of 3-Carene biosynthesis. These results laid a theoretical foundation for the study of floral transcriptional regulation and genetic engineering technology breeding of Oncidium hybridum. Full article
(This article belongs to the Special Issue Recent Advances in Horticultural Plant Genomics)
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<p>The emission patterns of three floral scent compounds—3-Carene, Butyl tiglate, and Prenyl senecioate—in <span class="html-italic">Oncidium</span> Twinkle ‘Red Fantasy’ under normal photoperiod (under 12 h light/12 h dark). (<b>a</b>) Overlapping analysis of 3-Carene ion current in samples at different time points within 24 h. The abscissa represents the retention time (min), and the ordinate represents the ion current intensity. (<b>b</b>) The emission patterns of 3-Carene from <span class="html-italic">Oncidium</span> Twinkle ‘Red Fantasy’ flowers within 48 h. (<b>c</b>) Overlapping analysis of Butyl tiglate ion current in samples at different time points within 24 h. The abscissa represents the retention time (min), and the ordinate represents the ion current intensity. (<b>d</b>) The emission patterns of Butyl tiglate from <span class="html-italic">Oncidium</span> Twinkle ‘Red Fantasy’ flowers within 48 h. (<b>e</b>) Overlapping analysis of Prenyl senecioate ion current in samples at different time points within 24 h. The abscissa represents the retention time (min), and the ordinate represents the ion current intensity. (<b>f</b>) The emission patterns of Prenyl senecioate from <span class="html-italic">Oncidium</span> Twinkle ‘Red Fantasy’ flowers within 48 h. Each treatment was conducted in triplicate with three technical repeats. Values are mean ± SD. Different lowercase letters indicate a statistically significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Transcriptomic analysis of <span class="html-italic">Oncidium</span> Twinkle ‘Red Fantasy’ at different time points within 24 h (under 12 h light/12 h dark). (<b>a</b>) Principal component analysis (PCA) plot showed overall differences among six groups (2:00, 6:00, 10:00, 14:00, 18:00, and 22:00) and the variability between intra-group samples. (<b>b</b>) Heatmap of differentially expressed genes (DEGs) sorted by K-means clustering across the samples collected at different time points. The numbers 1, 2, and 3 with each sample represented number of replicates. (<b>c</b>) Eight K-means clusters (Clusters 1–8) showed differential expression trends of DEGs at different time points. (<b>d</b>) KEGG enrichment analysis of DEGs in Cluster 4. The red boxes indicate metabolic pathways related to aroma rhythm release. (<b>e</b>) KEGG enrichment analysis of DEGs in Cluster 6. The red boxes indicate metabolic pathways related to aroma rhythm release. (<b>f</b>) KEGG enrichment analysis of DEGs in Cluster 8. The red boxes indicate metabolic pathways related to aroma rhythm release.</p>
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<p>Overview of metabolites and DEGs in the biosynthesis pathways of fatty acid derivative and terpenoid in <span class="html-italic">Oncidium</span> Twinkle ‘Red Fantasy’. (<b>a</b>) The DEGs of Cluster 6 were enriched in the fatty acid derivative biosynthesis pathway. <span class="html-italic">9-lipoxygenase</span> (<span class="html-italic">9-LOX</span>), <span class="html-italic">13-lipoxygenase</span> (<span class="html-italic">13-LOX</span>), <span class="html-italic">9-hydroperoxide lyase</span> (<span class="html-italic">9-HPL</span>), <span class="html-italic">13-hydroperoxide lyase</span> (<span class="html-italic">13</span>-<span class="html-italic">HPL</span>), <span class="html-italic">alcohol dehydrogenase</span> (<span class="html-italic">ADH</span>), <span class="html-italic">allene oxide synthase</span> (<span class="html-italic">AOS</span>), and <span class="html-italic">alcohol acyltransferase</span> (<span class="html-italic">AAT</span>). The black dashed boxes represent genes enriched in the LOX pathway, and the red fonts represent differentially expressed genes. (<b>b</b>) The DEGs of Cluster 4 and Cluster 8 were enriched in the terpenoid biosynthesis pathway. <span class="html-italic">Acetyl</span>-<span class="html-italic">CoA acetyltransferase</span> (<span class="html-italic">AACT</span>), <span class="html-italic">hydroxymethylglutaryl</span>-<span class="html-italic">CoA synthase</span> (<span class="html-italic">HMGS</span>), <span class="html-italic">hydroxymethylglutaryl</span>-<span class="html-italic">CoA reductase</span> (<span class="html-italic">HMGR</span>), <span class="html-italic">mevalonate kinase</span> (<span class="html-italic">MVK</span>), <span class="html-italic">mevalonate phosphate decarboxylase</span> (<span class="html-italic">MPD</span>), <span class="html-italic">phosphomevalonate kinase</span> (<span class="html-italic">PMK</span>), <span class="html-italic">isopentenyl phosphate kinase</span> (<span class="html-italic">IPK</span>), <span class="html-italic">mevalonate diphosphate decarboxylase</span> (<span class="html-italic">MPDC</span>), <span class="html-italic">isopentenyl diphosphate isomerase</span> (<span class="html-italic">IDI</span>), <span class="html-italic">farnesyl pyrophosphate synthase</span> (<span class="html-italic">FPPS</span>), <span class="html-italic">terpenoid synthase</span> (<span class="html-italic">TPS</span>), <span class="html-italic">1-deoxy-D-xylulose 5-phosphate synthase</span> (<span class="html-italic">DXS</span>), <span class="html-italic">1-deoxy-D-xylulose 5-phosphate reductoisomerase</span> (<span class="html-italic">DXR</span>), <span class="html-italic">2-C-methyl-D-erythritol 4-phosphate cytidylyltransferase</span> (<span class="html-italic">MCT</span>), <span class="html-italic">4-(cytidine 5′-diphospho)-2-C-methyl-D-erythritol kinase</span> (<span class="html-italic">CMK</span>), <span class="html-italic">2-C-methyl-D-erythritol 2,4-cyclodiphosphate synthase</span> (<span class="html-italic">MECPS</span>), <span class="html-italic">4-hydroxy-3-methylbut-2-en-1-yl diphosphate synthase</span> (<span class="html-italic">HDS</span>), <span class="html-italic">isoprenyl diphosphate synthase</span> (<span class="html-italic">IDS</span>), <span class="html-italic">geranylgeranyl pyrophosphate synthase</span> (<span class="html-italic">GGPPS</span>), and <span class="html-italic">geranyl diphosphate synthase</span> (<span class="html-italic">GPPS</span>). The black dashed boxes represent genes enriched in the MVA and MEP pathway, and the red fonts represent differentially expressed genes.</p>
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<p>Establishment of weighted gene co-expression network analysis (WGCNA) modules of the differentially expressed genes (DEGs) at different time points. (<b>a</b>) Hierarchical clustering tree of the co-expression modules. The major tree branches constituted 10 distinct co-expression modules. (<b>b</b>) The gene expression patterns of the Blue, Red, Yellow, and Brown modules in WGCNA. The upper part was the clustering heatmap of genes within this module, with red indicating high expression and green indicating low expression. The lower part showed the expression patterns of module feature values in different samples. (<b>c</b>) Co-expression network of the genes from the Blue module. The red circles represent the key hub genes enriched in fatty acid derivative biosynthesis pathway, and the blue circles represent aroma synthesis related transcription factors (TFs). (<b>d</b>) Co-expression network of the genes from the Red module. The red circles represent the key hub genes enriched in terpenoid biosynthesis pathway, and the blue circles represent aroma synthesis related TFs. The red font represents TFs that were differentially enriched in the “Circadian rhythm-plant” pathway. (<b>e</b>) Co-expression network of the genes from the Brown module. The red circles represent the key hub genes enriched in terpenoid biosynthesis pathway, and the blue circles represent aroma synthesis related TFs. (<b>f</b>) Co-expression network of the genes from the Yellow module. The red circles represent the key hub genes enriched in terpenoid biosynthesis pathway, and the blue circles represent aroma synthesis related TFs. The red font represents TFs that were differentially enriched in the “Circadian rhythm-plant” pathway. The networks were visualized by Cytoscape (v3.5.1) software.</p>
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<p>Relative expression of structural genes <span class="html-italic">Cluster-17371.18_TPS</span>, <span class="html-italic">Cluster-65495.1_TPS</span>, <span class="html-italic">Cluster-46699.0_TPS</span>, <span class="html-italic">Cluster-60935.10_DXS</span>, <span class="html-italic">Cluster</span>-<span class="html-italic">47205.4_IDI</span>, and <span class="html-italic">Cluster-65313.7_LOX</span> in <span class="html-italic">Oncidium</span> Twinkle ‘Red Fantasy’ flowers within 48 h (under 12 h light/12 h dark). Each treatment was conducted in triplicate with three technical repeats. Values are mean ± SD. Different lowercase letters indicate a statistically significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Analysis of aroma release pattern of <span class="html-italic">Oncidium</span> Twinkle ‘Red Fantasy’ under constant light and constant dark treatments. (<b>a</b>) The emission patterns of three floral scent compounds from <span class="html-italic">Oncidium</span> Twinkle ‘Red Fantasy’ flowers within 48 h under constant light. (<b>b</b>) The emission patterns of three floral scent compounds from <span class="html-italic">Oncidium</span> Twinkle ‘Red Fantasy’ flowers within 48 h under constant dark. Different lowercase letters indicate a statistically significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Analysis of aroma synthesis genes expression of <span class="html-italic">Oncidium</span> Twinkle ‘Red Fantasy’ under constant light and constant dark treatments. (<b>a</b>) Relative expression of structural genes <span class="html-italic">Cluster-17371.18_TPS, Cluster-65495.1_TPS</span>, <span class="html-italic">Cluster-46699.0_TPS, Cluster-60935.10_DXS</span>, <span class="html-italic">Cluster-47205.4_IDI</span>, and <span class="html-italic">Cluster-65313.7_LOX</span> in <span class="html-italic">Oncidium</span> Twinkle ‘Red Fantasy’ flowers within 48 h under constant light. (<b>b</b>) Relative expression of structural genes <span class="html-italic">Cluster-17371.18_TPS, Cluster-65495.1_TPS</span>, <span class="html-italic">Cluster-46699.0_TPS, Cluster-60935.10_DXS</span>, <span class="html-italic">Cluster-47205.4_IDI</span>, and <span class="html-italic">Cluster-65313.7_LOX</span> in <span class="html-italic">Oncidium</span> Twinkle ‘Red Fantasy’ flowers within 48 h under constant dark. Each treatment was conducted in triplicate with three technical repeats. Values are mean ± SD. Different lowercase letters indicate a statistically significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Schematic model of the mechanism by which the circadian rhythm regulates the aroma release of <span class="html-italic">Oncidium</span> Twinkle ‘Red Fantasy’. The main aroma compounds of <span class="html-italic">Oncidium</span> Twinkle ‘Red Fantasy’ were 3-Carene, Butyl tiglate, and Prenyl senecioate. 3-Carene were mainly released at 10:00, while Butyl tiglate and Prenyl senecioate were mainly released at 14:00. <span class="html-italic">DXS</span>, <span class="html-italic">CMK</span>, <span class="html-italic">IDI</span>, <span class="html-italic">TPS</span>, and <span class="html-italic">LOX</span> were key genes in the terpenoid or fatty acid derivative biosynthetic pathway, which were co-expressed with aroma release. Under the treatment of constant light or dark, the aroma release maintained a circadian rhythm.</p>
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24 pages, 2012 KiB  
Article
Exploring Toxicity of Per- and Polyfluoroalkyl Substances (PFAS) Mixture Through ADMET and Toxicogenomic In Silico Analysis: Molecular Insights
by Katarina Baralić, Teodora Petkovski, Nađa Piletić, Đurđica Marić, Aleksandra Buha Djordjevic, Biljana Antonijević and Danijela Đukić-Ćosić
Int. J. Mol. Sci. 2024, 25(22), 12333; https://doi.org/10.3390/ijms252212333 (registering DOI) - 17 Nov 2024
Abstract
This study aimed to explore the health impacts, mechanisms of toxicity, and key gene biomarkers of a mixture of the most prominent perfluoroalkyl/polyfluoroalkyl substances (PFAS) through in silico ADMET and toxicogenomic analysis. The following databases and tools were used: AdmetSAR (2.0), ADMETlab (2.0), [...] Read more.
This study aimed to explore the health impacts, mechanisms of toxicity, and key gene biomarkers of a mixture of the most prominent perfluoroalkyl/polyfluoroalkyl substances (PFAS) through in silico ADMET and toxicogenomic analysis. The following databases and tools were used: AdmetSAR (2.0), ADMETlab (2.0), Comparative Toxicogenomic Database, ToppGene Suite portal, Metascape (3.5), GeneMANIA server, and CytoHubba and CytoNCA Cytoscape (3.10.3) plug-ins. ADMET analysis showed that PFAS compounds pose risks of organ-specific toxicity, prolonged retention, and metabolic disruptions. Forty mutual genes were identified for all the tested PFAS. The mutual gene set was linked to disruption of lipid metabolism, particularly through nuclear receptors. The most important gene clusters identified were nuclear receptor signaling and PPAR signaling pathways, with kidney and liver diseases, diabetes, and obesity as the most significant related diseases. Phenotype data showed that PFAS compounds impact cell death, growth, inflammation, steroid biosynthesis, and thyroid hormone metabolism. Gene network analysis revealed that 52% of the 40 mutual genes showed co-expression, with co-localization as the next major interaction (18.23%). Eight key genes were extracted from the network: EHHADH, APOA2, MBL2, SULT2A1, FABP1, PPARA, PCK2, and PLIN2. These results highlight the need for further research to fully understand the health risks of PFAS mixtures. Full article
(This article belongs to the Topic Environmental Toxicology and Human Health—2nd Edition)
23 pages, 2541 KiB  
Article
Chaga Mushroom Triterpenoids Inhibit Dihydrofolate Reductase and Act Synergistically with Conventional Therapies in Breast Cancer
by Junbiao Wang, Daniela Beghelli, Augusto Amici, Stefania Sut, Stefano Dall’Acqua, Giulio Lupidi, Diego Dal Ben, Onelia Bistoni, Daniele Tomassoni, Barbara Belletti, Sanaa Musa, Jamal Mahajna, Stefania Pucciarelli and Cristina Marchini
Biomolecules 2024, 14(11), 1454; https://doi.org/10.3390/biom14111454 (registering DOI) - 17 Nov 2024
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Abstract
Inonotus obliquus (Chaga) is a medicinal mushroom with several pharmacological properties that is used as a tea in traditional Chinese medicine. In this study, Chaga water extract was digested in vitro to mimic the natural processing and absorption of its biocomponents when it [...] Read more.
Inonotus obliquus (Chaga) is a medicinal mushroom with several pharmacological properties that is used as a tea in traditional Chinese medicine. In this study, Chaga water extract was digested in vitro to mimic the natural processing and absorption of its biocomponents when it is consumed as functional beverage, and its anticancer activities were evaluated in breast cancer (BC) cell lines, representing HER2-positive and triple-negative subtypes. After chemical characterization by liquid chromatography/mass spectrometry (HR-QTOF) analysis, the effect of Chaga biocomponents on cell viability and cell cycle progression was assessed by MTT assay, FACS analysis, and Western blot. Dihydrofolate reductase (DHFR) activity was measured by an enzymatic assay. Four highly bioactive triterpenoids (inotodiol, trametenolic acid, 3-hydroxy-lanosta-8,24-dien-21-al, and betulin) were identified as the main components, able to decrease BC cell viability and block the cell cycle in G0/G1 by inducing the downregulation of cyclin D1, CDK4, cyclin E, and phosphorylated retinoblastoma protein. DHFR was identified as their crucial target. Moreover, bioactive Chaga components exerted a synergistic action with cisplatin and with trastuzumab in SK-BR-3 cells by inhibiting both HER2 and HER1 activation and displayed an immunomodulatory effect. Thus, Inonotus obliquus represents a source of triterpenoids that are effective against aggressive BC subtypes and display properties of targeted drugs. Full article
14 pages, 638 KiB  
Article
Exploring Ultrasonic Energy Followed by Natural Fermentation Processing to Enhance Functional Properties and Bioactive Compounds in Millet (Pennisetum glaucum L.) Grains
by Mohammed Saeed Alkaltham, Akram A. Qasem, Mohamed A. Ibraheem and Amro B. Hassan
Fermentation 2024, 10(11), 590; https://doi.org/10.3390/fermentation10110590 (registering DOI) - 17 Nov 2024
Viewed by 6
Abstract
This study explores the effect of ultrasonic treatment followed by fermentation on the in vitro protein digestibility, protein solubility, functional properties, antioxidant activity, total carotenoid content, and gamma-aminobutyric acid (GABA) levels in millet grains. Ultrasonic treatment was applied at different temperatures (20, 40, [...] Read more.
This study explores the effect of ultrasonic treatment followed by fermentation on the in vitro protein digestibility, protein solubility, functional properties, antioxidant activity, total carotenoid content, and gamma-aminobutyric acid (GABA) levels in millet grains. Ultrasonic treatment was applied at different temperatures (20, 40, and 60 °C). The findings indicated significant improvements in phenolic and flavonoid contents and antioxidant activity in terms of the results of the DPPH, FRAP, and ABTS assays of millet grains after ultrasonic treatment alone or combined with fermentation. Moreover, the carotenoid and GABA contents were found to be significantly higher in the ultrasonic-treated grains. The protein solubility functional properties of the millet grains were also improved after the ultrasonic treatment alone or coupled with the fermentation process. Principal component analysis (PCA) revealed that the combined ultrasonic treatment and fermentation of the millet grains could enhance their antioxidant activity, functional characteristics, and vital compounds. Furthermore, the partial least squares (PLS) validation model emphasised that the ultrasonic treatment of millet at 40 °C, followed by fermentation, is the most optimal treatment among the other treatments. Hence, the conclusions highlight the potential of combined ultrasonic (40 °C) and fermentation treatments to improve grains’ nutritional value and functional properties, making millet more suitable for use in health-promoting food products. Full article
(This article belongs to the Section Fermentation Process Design)
34 pages, 6053 KiB  
Article
Insights into the Identification of iPSC- and Monocyte-Derived Macrophage-Polarizing Compounds by AI-Fueled Cell Painting Analysis Tools
by Johanna B. Brüggenthies, Jakob Dittmer, Eva Martin, Igor Zingman, Ibrahim Tabet, Helga Bronner, Sarah Groetzner, Julia Sauer, Mozhgan Dehghan Harati, Rebekka Scharnowski, Julia Bakker, Katharina Riegger, Caroline Heinzelmann, Birgit Ast, Robert Ries, Sophie A. Fillon, Anna Bachmayr-Heyda, Kerstin Kitt, Marc A. Grundl, Ralf Heilker, Lina Humbeck, Michael Schuler and Bernd Weigleadd Show full author list remove Hide full author list
Int. J. Mol. Sci. 2024, 25(22), 12330; https://doi.org/10.3390/ijms252212330 (registering DOI) - 17 Nov 2024
Viewed by 75
Abstract
Macrophage polarization critically contributes to a multitude of human pathologies. Hence, modulating macrophage polarization is a promising approach with enormous therapeutic potential. Macrophages are characterized by a remarkable functional and phenotypic plasticity, with pro-inflammatory (M1) and anti-inflammatory (M2) states at the extremes of [...] Read more.
Macrophage polarization critically contributes to a multitude of human pathologies. Hence, modulating macrophage polarization is a promising approach with enormous therapeutic potential. Macrophages are characterized by a remarkable functional and phenotypic plasticity, with pro-inflammatory (M1) and anti-inflammatory (M2) states at the extremes of a multidimensional polarization spectrum. Cell morphology is a major indicator for macrophage activation, describing M1(-like) (rounded) and M2(-like) (elongated) states by different cell shapes. Here, we introduced cell painting of macrophages to better reflect their multifaceted plasticity and associated phenotypes beyond the rigid dichotomous M1/M2 classification. Using high-content imaging, we established deep learning- and feature-based cell painting image analysis tools to elucidate cellular fingerprints that inform about subtle phenotypes of human blood monocyte-derived and iPSC-derived macrophages that are characterized as screening surrogate. Moreover, we show that cell painting feature profiling is suitable for identifying inter-donor variance to describe the relevance of the morphology feature ‘cell roundness’ and dissect distinct macrophage polarization signatures after stimulation with known biological or small-molecule modulators of macrophage (re-)polarization. Our novel established AI-fueled cell painting analysis tools provide a resource for high-content-based drug screening and candidate profiling, which set the stage for identifying novel modulators for macrophage (re-)polarization in health and disease. Full article
(This article belongs to the Special Issue Advanced Research on Macrophages in Human Health and Disease)
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<p>IDM generation from 201B7 via CD14+ or CD34+ progenitors. (<b>A</b>) Schematic of the used differentiation protocols to generate CD34+- or CD14+-derived MΦs from the hiPSC line 201B7. Representative brightfield images illustrate the differentiation stages over 22 days. (<b>B</b>) Flow cytometry analysis of CD14 expression of CD34+- versus CD14+-derived MΦs across harvest rounds 1–3 (in %; <span class="html-italic">n</span> = 3; gating is based on a 1% isotype control). The surface marker expression of CD14 was tracked to verify the differentiation of CD34+ progenitors and CD14+ progenitors towards MΦs. Yield comparison of produced CD34+ and CD14+ progenitors from each harvest (<span class="html-italic">n</span> = 3). (<b>C</b>) Representative brightfield images illustrate frozen CD34+-derived MΦ differentiation from day 7 (d7) to day 14 (d14). Schematic of the used differentiation protocol of frozen CD34+ progenitors towards IDMs. Flow cytometry analysis of CD14 and CD34 expression of frozen CD34+-derived progenitors (in %; <span class="html-italic">n</span> = 3; gating is based on a 1% isotype control).</p>
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<p>Polarizing compound-induced modulation of MΦ morphology. (<b>A</b>) Schematic of Hu et al. 2021 [<a href="#B30-ijms-25-12330" class="html-bibr">30</a>], who published M1- and M2-like cpds (created by BioRender.com and ChemDraw 23.1). (<b>B</b>) Flow cytometry analysis of CD80 and CD206 expression of cpd-treated (thiostrepton 2.5 μM and bosutinib 1 μM) and biologically stimulated (LPS and IL4+IL13) MΦs (CD34+-derived IDMs versus MDM donor CL119) (in %; <span class="html-italic">n</span> = 3; gating is based on a 1% isotype control). (<b>C</b>) Equation and Z-score calculation for cell roundness analysis; data are depicted as the mean ± SD from 20× magnification. Representative high-content Opera Phenix<sup>TM</sup> confocal images (40×; nucleus–Hoechst3342; cytoplasm/ER concanavalin A-Alexa488; one field out of ten) of PhenoVue Kit-stained IDMs and the MDM donor CL090 treated with illustrated conditions for 24 h. Each condition (12 wells; 5 fields per well) was imaged in two replicate 384-well plates. Statistics: two-way ANOVA with significance **** <span class="html-italic">p</span> &lt; 0.0001. (<b>D</b>) Representative high-content Opera Phenix<sup>TM</sup> confocal images (40× one field out of ten or 20× one field out of five; nucleus–Hoechst3342; cytoplasm/ER concanavalin A-Alexa488) of PhenoVue Kit-stained IDMs and the MDM donor CL090 treated with illustrated conditions for 24 h. Each condition (12 wells) was imaged in two replicate 384-well plates. Statistics: two-way ANOVA with significance **** <span class="html-italic">p</span> &lt; 0.0001. Z-score calculation for cell roundness analysis: data are depicted as the mean ± SD at 20× or 40× magnification.</p>
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<p>Heterogeneity of morphology changes upon compound treatment and biological stimuli. (<b>A</b>) Z-score calculation for cell roundness analysis: data are depicted as the mean ± SD at 20× magnification. Representative high-content Opera Phenix<sup>TM</sup> confocal images (40×; nucleus–Hoechst3342; cytoplasm/ER concanavalin A-Alexa488; one field out of five) of PhenoVue Kit-stained IDMs and several MDM donors (CL090, CL415, CL541, and CL091) treated with illustrated conditions for 24 h. Each condition (12 wells; 5 fields per well) was imaged in two replicate 384-well plates. Statistics: two-way ANOVA with significance **** <span class="html-italic">p</span> &lt; 0.0001 and ** to <span class="html-italic">p</span> &lt; 0.001. ns = non-significant. (<b>B</b>) Conditions as in A with described cpd stimulation. Statistics: two-way ANOVA with significance **** <span class="html-italic">p</span> &lt; 0.0001 and * to <span class="html-italic">p</span> &lt; 0.01. ns = non-significant. (<b>C</b>) Dose–Response analysis of Z-score calculated cell roundness. Data are depicted as the mean ± SD. Representative high-content Opera Phenix<sup>TM</sup> confocal images (20×; nucleus–Hoechst3342; cytoplasm/ER concanavalin-Alexa488; one field out of five) of IDMs treated with illustrated conditions (alsterpaullone, bosutinib, thiostrepton, and fenbendazole) for 24 h. Each condition (4 wells; 5 fields per well) was imaged in one 384-well plate. IDMs were generated from different frozen CD34+-progenitor stocks (harvest) across different progenitor production rounds (batch).</p>
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<p>Cell painting features for the description of the phenotypic spectrum of MΦ polarization. (<b>A</b>) Representative high-content Opera Phenix<sup>TM</sup> confocal images of cell-painted (PhenoVue Kit: PhenoVue 641 mitochondrial stain, PhenoVue Hoechst 33342 nuclear stain, PhenoVue Fluor 488-concanavalin A, PhenoVue 512 nucleic acid stain, PhenoVue Fluor 555-WGA and PhenoVue Fluor 568-Phalloidin) IDMs and an MDM donor CL090 with indicated cell painting controls (berberine chloride, fenbendazole, etoposide, cytochalasin D, CA-074Me and tetrandrine; 12 wells per condition; 10 fields per well; from two independent replicate 384-well plates) after 24 h of stimulation. The effect of the cpds on the respective cellular compartment and organelles is indicated by the white arrows. (<b>B</b>) Schematic of the established feature-based analysis using SImA: ‘preset cell painting building block’ and ‘custom-made cell painting building block combined with linear classifier’. bosutinib-treated IDM Opera Phenix<sup>TM</sup> confocal imagery is shown as a representative example. The whole analysis pipeline is described in Materials and Methods 4.8. (<b>C</b>) Principal component analysis of ‘Preset cell painting building block’ and ’Custom-made cell painting building block’ features indicated cpd- and biologically stimulated IDMs and an MDM donor CL961 for 24 h. Each datapoint indicates the mean of 4 replicate wells (5 fields per well; 20× magnification) per condition. ‘Preset cell painting building block’ is based on 4710 used features. ’Custom-made cell painting building block’ is based on 1279 features.</p>
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<p>‘Linear classifier’ analysis for the quantification of M1 and M2(-like) compound states. (<b>A</b>) Schematic of SImA ‘linear classifier’ IDM-trained models 1-3 (created by BioRender.com). Quantification of the indicated 24 h of cpd- and biologically stimulated IDMs from two 384-replicate plates. DMSO 0.1%-normalized values %M2(-like)—%M1(-like) correspond to a mean of 4 wells imaged at 20× magnification (replicate 1 and 2; 5 fields per well). DMSO-normalized %M2(-like)—%M1(-like) values are listed in <a href="#app1-ijms-25-12330" class="html-app">Table S1</a>. (<b>B</b>) SImA ‘linear classifier’ analysis of the indicated 24 h of cpd-stimulated IDMs and several MDM donors (CL090, CL091, CL541, and CL415) from two to four 384-well replicate plates by model 2 from A trained on IDMs. DMSO-normalized %M2(-like)—%M1(-like) values correspond to a mean of 12 wells imaged at 20× magnification (5 fields per well). DMSO-normalized %M2(-like)—%M1(-like) values are listed in <a href="#app1-ijms-25-12330" class="html-app">Table S2</a>. The four used reference cpds from [<a href="#B30-ijms-25-12330" class="html-bibr">30</a>] are indicated abbreviated in the figure.</p>
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<p>Identification and quantification of compound-induced MΦ reprogramming effects. (<b>A</b>) Representative high-content Opera Phenix<sup>TM</sup> confocal images of cell-painted (PhenoVue Kit: PhenoVue 641 mitochondrial stain, PhenoVue Hoechst 33342 nuclear stain, PhenoVue Fluor 488-concanavalin A, PhenoVue 512 nucleic acid stain, PhenoVue Fluor 555-WGA, and PhenoVue Fluor 568-Phalloidin) IDMs with indicated M1- and M2-like cpds single-treated or combined with biological stimuli (4 wells per condition; 5 fields per well; 20× magnification) for 24 h or 48 h. Z-score calculation for cell roundness analysis: data are depicted as the mean ± SD at 20× magnification (from one 384-well plate). Statistics: two-way ANOVA with significance **** <span class="html-italic">p</span> &lt; 0.0001. ns = non-significant. (<b>B</b>) SImA ‘linear classifier’ quantification of IDMs trained on IDM model 2 from <a href="#ijms-25-12330-f005" class="html-fig">Figure 5</a>A. DMSO-normalized %M2(-like)—%M1(-like) values correspond to a mean of 4 wells imaged at 20× magnification (5 fields per well). DMSO-normalized %M2(-like)—%M1(-like) values are listed in <a href="#app1-ijms-25-12330" class="html-app">Table S3</a>. Treatment conditions used from A. Normalization was performed for the duration of the treatment. (<b>C</b>) Z-score calculation for cell roundness analysis of cell-painted (PhenoVue Kit: PhenoVue 641 mitochondrial stain, PhenoVue Hoechst 33342 nuclear stain, PhenoVue Fluor 488-concanavalin A, PhenoVue 512 nucleic acid stain, PhenoVue Fluor 555-WGA, and PhenoVue Fluor 568-Phalloidin) IDMs (ChiPSC12 and 201B7) and two MDM donors (CL961 and CL414) with indicated M1- and M2-like cpds, single-treated or combined with biological stimuli (4 wells per condition; 5 fields per well; 20× magnification) for 24 h or 48 h. Data are depicted as the mean ± SD at 20× magnification (from two independent 384-well plates). Statistics: two-way ANOVA with significance **** <span class="html-italic">p</span> &lt; 0.0001 and ** <span class="html-italic">p</span> &lt; 0.01. ns = non-significant. (<b>D</b>) SImA ‘linear classifier’ analysis of indicated 24 h cpd- and biologically stimulated IDMs (201B7 and ChiPSC12) and two MDM donors (CL414 and CL961) from one 384-well plate trained on IDM model 2 from <a href="#ijms-25-12330-f005" class="html-fig">Figure 5</a>A. DMSO-normalized %M2(-like)—%M1(-like)values correspond to a mean of 4 wells imaged at 20× magnification (5 fields per well). DMSO-normalized %M2(-like)—%M1(-like)values are listed in <a href="#app1-ijms-25-12330" class="html-app">Table S4</a>.</p>
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<p>Relevance of standard morphological properties and cell roundness feature for compound-induced MΦ (re-)polarization. (<b>A</b>) SImA ‘linear classifier’ analysis of indicated 24 h treated cpd- and biologically stimulated IDMs from one 384-well plate trained on IDM model 2 from <a href="#ijms-25-12330-f005" class="html-fig">Figure 5</a>A. Model 2 differs in the usage of all or no standard morphology (area, roundness, width, length, and ratio of width to length) or no cell roundness features. DMSO-normalized %M2(-like)—%M1(-like) values correspond to a mean of 4 wells imaged at 20× magnification (5 fields per well). DMSO-normalized %M2(-like)—%M1(-like) values are listed in <a href="#app1-ijms-25-12330" class="html-app">Table S6</a>. (<b>B</b>,<b>C</b>) List of relevant features for M0, M1-like, and M2-like classification and their corresponding linear coefficient value based on the three models in A. The cell roundness feature is highlighted in orange. The common relevant features of all three ‘linear classifiers’ are illustrated in bold.</p>
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<p>DL-fueled cell painting analyses for MΦ (re-)polarization effects. (<b>A</b>) Scatter plot correlating the cell ratios (% M1(-like) and M2(-like) proportion) of the DL-fueled analysis of 24 h cpd- and biologically stimulated IDMs (201B7 and ChIPSC12) and MDMs (CL414 and CL961) from one 384-well plate trained on the IDM DL-model 2 (40× magnification). DMSO 0.1%-normalized values correspond to a mean of 4 wells imaged at 40× magnification (10 fields per well). The correlation coefficient was calculated by the Pearson correlation. (<b>B</b>) Scatter plot correlating the cell ratios (DMSO normalized %M2(-like)—%M1(-like); <a href="#app1-ijms-25-12330" class="html-app">Table S7</a>) of the DL-based and ‘linear classifier’ analyses of conditions in A using 20× magnification (5 fields per well). The correlation coefficient was calculated by the Pearson correlation.</p>
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20 pages, 19658 KiB  
Article
Chemical Composition, In Silico Investigations and Evaluation of Antifungal, Antibacterial, Insecticidal and Repellent Activities of Eucalyptus camaldulensis Dehn. Leaf Essential Oil from ALGERIA
by Ghozlane Barboucha, Noureddine Rahim, Houssem Boulebd, Amina Bramki, Anna Andolfi, Maria Michela Salvatore and Marco Masi
Plants 2024, 13(22), 3229; https://doi.org/10.3390/plants13223229 (registering DOI) - 17 Nov 2024
Viewed by 124
Abstract
This study investigated the phytochemical profile and evaluated the antimicrobial and insecticidal properties of Eucalyptus camaldulensis Dehn. essential oil (EC-EO) from Algeria, using in vitro and in silico approaches. The yield of EC-EO was 0.27%, with gas chromatography-mass spectrometry (GC-MS) revealing spathulenol (58.24%), [...] Read more.
This study investigated the phytochemical profile and evaluated the antimicrobial and insecticidal properties of Eucalyptus camaldulensis Dehn. essential oil (EC-EO) from Algeria, using in vitro and in silico approaches. The yield of EC-EO was 0.27%, with gas chromatography-mass spectrometry (GC-MS) revealing spathulenol (58.24%), cryptone (17.22%), and o-cymene (15.53%) as the major compounds. EC-EO exhibited notable antibacterial activity, particularly against Salmonella typhimurium (14 ± 1.00 mm) and Staphylococcus aureus (14.5 ± 0.50 mm). It also showed effective antifungal activity against Penicillium sp. (11.5 ± 0.49 mm), Candida albicans (11.2 ± 0.29 mm), and Aspergillus fumigatus (9.8 ± 0.27 mm). Insecticidal assays against Tribolium castaneum were conducted using contact toxicity, fumigation toxicity, and repellent activity methods. The median lethal concentration (LC50) for contact toxicity was 0.011 μL/insect after 72 h, while the fumigation test had an LC50 of 122.29 μL/L air. Repellent activity tests showed percentage repellency (PR) values exceeding 80% after 6 h. The molecular geometry and electronic properties of the main compounds were studied using density functional theory (DFT) calculations. In addition, the interaction mode and binding affinity of these molecules with three key enzymes involved in antimicrobial activity, DNA gyrase, dihydrofolate reductase (DHFR) and Tyrosyl-tRNA synthetase (TyrRS), were explored by molecular docking. Full article
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<p>Annoted total ion current chromatogram (TICC) from GC-MS analysis of the essential oil extracted from <span class="html-italic">E. camaldulensis</span> leaves.</p>
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<p>Molecular geometry (<b>A</b>), distribution and energies of LUMO (<b>B</b>) and HOMO (<b>C</b>), and ESP (<b>D</b>) of the <span class="html-italic">E. camaldulensis</span> essential oil compounds, calculated at the B3LYP/6-31+G(d,p) level.</p>
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<p>Superimposition of the docked models of <span class="html-italic">E. camaldulensis</span> EO compounds into the active site of DNA Gyrase (<b>A</b>), DHFR (<b>B</b>), and TyrRS enzymes (<b>C</b>).</p>
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<p>Interaction modes of <span class="html-italic">o</span>-cymene (<b>A</b>), eucalyptol (<b>B</b>), cryptone (<b>C</b>), cumic aldehyde (<b>D</b>), phellandral (<b>E</b>), and spathulenol (<b>F</b>) into the active site of DNA Gyrase enzyme.</p>
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<p>Interaction modes of <span class="html-italic">o</span>-cymene (<b>A</b>), eucalyptol (<b>B</b>), cryptone (<b>C</b>), cumic aldehyde (<b>D</b>), phellandral (<b>E</b>), and spathulenol (<b>F</b>) into the active site of DHFR enzyme.</p>
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<p>Interaction modes of <span class="html-italic">o</span>-cymene (<b>A</b>), eucalyptol (<b>B</b>), cryptone (<b>C</b>), cumic aldehyde (<b>D</b>), phellandral (<b>E</b>), and spathulenol (<b>F</b>) into the active site of TyrRS enzyme.</p>
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19 pages, 8747 KiB  
Article
Stereoview Images of Hydrogen-Bonded Quinoxalines with a Helical Axis; Pyrimidines and a Pyridazine That Form Extended Tapes
by Michael John Plater and William T. A. Harrison
Int. J. Mol. Sci. 2024, 25(22), 12329; https://doi.org/10.3390/ijms252212329 (registering DOI) - 17 Nov 2024
Viewed by 132
Abstract
Different supramolecular motifs are formed by the crystallisation of amino-substituted derivatives of quinoxaline, pyrimidine and pyridazine. These were made from the corresponding mono- or dichlorinated heterocycles by a nucleophilic displacement reaction. The pyridine-type nitrogen atoms activate the chlorine atoms because they can stabilise [...] Read more.
Different supramolecular motifs are formed by the crystallisation of amino-substituted derivatives of quinoxaline, pyrimidine and pyridazine. These were made from the corresponding mono- or dichlorinated heterocycles by a nucleophilic displacement reaction. The pyridine-type nitrogen atoms activate the chlorine atoms because they can stabilise a negative charge, which forms when the amine attacks the ring. One amino group can be attached under mild conditions in hot ethanol or acetonitrile, but the first then deactivates the ring so the second requires more forceful conditions using a pressure vessel at 150 °C. Butylamine is frequently used because it reduces the polarity of the product, making it easier to purify and isolate. The extended structure of the quinoxaline derivatives 1618 show a common ‘pincer’ hydrogen-bond motif, with a quinoxaline nitrogen atom accepting two N–H···N hydrogen bonds, giving a spiral or helical axis. The chain symmetries are 41, 21 and 31, respectively, depending on the substituents. A stereoview of each is shown. The pyrimidine derivatives 19, 12, 20, 14 and 21 form hydrogen-bonded tapes and compound 20 forms inversion dimers. Full article
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<p>Quinoxaline, triazine, pyrimidine and pyridazine with activated chlorine atoms.</p>
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<p>Some tetracyclic heterocycles made from 2,3-dichloroquinoxaline <b>1</b>.</p>
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<p>Synthesis of 2,4-bis(butylamino)-6-chloro-1,3,5-triazine <b>12</b>.</p>
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<p>Reactions of compounds <b>3</b>–<b>5</b> with butylamine.</p>
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<p>Amino derivatives of quinoxaline, pyrimidine and pyridazine.</p>
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<p>Drawing of tributylaminotriazine [an oil from DCM].</p>
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<p>The molecular structure of compound <b>16</b> showing 50% displacement ellipsoids. Only the major orientation of the disordered C13–C16 butyl chain is shown.</p>
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<p>Unit-cell packing for compound <b>16</b> viewed down [001] showing the 4<sub>1</sub>-symmetry helical columns of molecules propagating towards the viewer. Carbon-bound hydrogen atoms are omitted for clarity and columnar hydrogen bonds are shown as black dashed lines. The red and green components of the unit-cell outline indicate the crystallographic [100] and [010] directions, respectively.</p>
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<p>Detail of the packing of <b>16</b> showing a side-on view of the spiral hydrogen-bonded chain.</p>
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<p>The molecular structure of the C1 molecule of compound <b>17</b> showing 50% displacement ellipsoids.</p>
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<p>Unit-cell packing for compound <b>17</b> viewed down [010] with the 2<sub>1</sub>-symmetry chains of hydrogen-bonded molecules propagating towards the viewer. Carbon-bound hydrogen atoms are omitted for clarity and hydrogen bonds are shown as black dashed lines. The red and blue components of the unit-cell outline indicate the crystallographic [100] and [001] directions, respectively.</p>
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<p>The molecular structure of the C1 molecule of compound <b>18</b> showing 50% displacement ellipsoids.</p>
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<p>The unit-cell packing for compound <b>18</b> viewed down [001] showing the 3<sub>1</sub>-symmetry helical columns of molecules propagating towards the viewer. Carbon-bound hydrogen atoms are omitted for clarity and hydrogen bonds are shown as black dashed lines. The red and green components of the unit-cell outline indicate the crystallographic [100] and [010] directions, respectively.</p>
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<p>The molecular structure of compound <b>19</b> showing 50% displacement ellipsoids. Symmetry code: (i) − <span class="html-italic">x</span>, 1 − <span class="html-italic">y</span>, 1 − <span class="html-italic">z</span>.</p>
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<p>Fragment of a (010) supramolecular sheet in compound <b>19</b> showing the primary N–H…N hydrogen bonds (black dashed lines) and secondary C–H…N links (orange dashed lines). The red and blue components of the unit-cell outline indicate the crystallographic [100] and [001] directions, respectively.</p>
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<p>The molecular structure of compound <b>12</b> showing 50% displacement ellipsoids. Only one disorder component of the C8–C11 butyl chain is shown.</p>
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<p>Fragment of a [110] hydrogen-bonded supramolecular tape in the extended structure of compound <b>12</b>. The primary N–H<sup>…</sup>N and secondary C–H<sup>…</sup>Cl hydrogen bonds are shown as blue and orange dashed lines, respectively.</p>
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<p>The molecular structure of compound <b>20</b> showing 50% displacement ellipsoids.</p>
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<p>The unit-cell packing for compound <b>20</b> viewed down [010]. Carbon-bound hydrogen atoms are omitted for clarity and hydrogen bonds are shown as black dashed lines. The red and blue components of the unit-cell outline indicate the crystallographic [100] and [001] directions, respectively.</p>
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<p>The molecular structure of compound <b>14</b> showing 50% displacement ellipsoids.</p>
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<p>Fragment of a [010] hydrogen-bonded supramolecular tape in the extended structure of compound <b>14</b> with N–H<sup>…</sup>N hydrogen bonds shown as black dashed lines.</p>
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<p>The molecular structure of compound <b>21</b> showing 50% displacement ellipsoids. Hydrogen bonds are shown as double-dashed lines.</p>
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<p>Fragment of a [110] hydrogen-bonded supramolecular tape in the extended structure of compound <b>21</b> with N–H<sup>…</sup>N and C–H<sup>…</sup>N hydrogen bonds shown as black and orange dotted lines, respectively.</p>
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<p>Stereoview of compound <b>16</b>.</p>
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<p>Stereoview of compound <b>17</b>.</p>
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<p>Stereoview of compound <b>18</b>.</p>
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