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31 pages, 5219 KiB  
Review
On the Roles of Protein Intrinsic Disorder in the Origin of Life and Evolution
by Vladimir N. Uversky
Life 2024, 14(10), 1307; https://doi.org/10.3390/life14101307 (registering DOI) - 15 Oct 2024
Viewed by 338
Abstract
Obviously, the discussion of different factors that could have contributed to the origin of life and evolution is clear speculation, since there is no way of checking the validity of most of the related hypotheses in practice, as the corresponding events not only [...] Read more.
Obviously, the discussion of different factors that could have contributed to the origin of life and evolution is clear speculation, since there is no way of checking the validity of most of the related hypotheses in practice, as the corresponding events not only already happened, but took place in a very distant past. However, there are a few undisputable facts that are present at the moment, such as the existence of a wide variety of living forms and the abundant presence of intrinsically disordered proteins (IDPs) or hybrid proteins containing ordered domains and intrinsically disordered regions (IDRs) in all living forms. Since it seems that the currently existing living forms originated from a common ancestor, their variety is a result of evolution. Therefore, one could ask a logical question of what role(s) the structureless and highly dynamic but vastly abundant and multifunctional IDPs/IDRs might have in evolution. This study represents an attempt to consider various ideas pertaining to the potential roles of protein intrinsic disorder in the origin of life and evolution. Full article
(This article belongs to the Special Issue What Is Life?)
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Figure 1

Figure 1
<p>Correlations between three foldability scales (the scale based on the average number of contacts per residue in the ordered proteins (Galzitskaya) [<a href="#B67-life-14-01307" class="html-bibr">67</a>] (<b>A</b>), the DisProt-based scale [<a href="#B66-life-14-01307" class="html-bibr">66</a>] (<b>B</b>), and the Top-IDP scale [<a href="#B23-life-14-01307" class="html-bibr">23</a>] (<b>C</b>)) and amino acid novelty scale proposed by Trifonov [<a href="#B65-life-14-01307" class="html-bibr">65</a>]. Red and blue symbols correspond to disorder- and order-promoting residues as defined by the DisProt-based scale. Pink and cyan squares with error bars show averaged values.</p>
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<p>Modern genetic code with information on the early and late codons (shown by light red and light blue colors, respectively) and disorder- and order-promoting residues (shown by red and blue colors, respectively). Codons with intermediate ages (i.e., those located between early and late codons) are shown by the light pink color, whereas disorder-neutral residues are shown by the pink color. Adapted with permission from Ref. [<a href="#B3-life-14-01307" class="html-bibr">3</a>]. Copyright © 2013. The Protein Society.</p>
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<p>Correlations between thermostability of the codons (measured as melting enthalpies (kcal/M) of the dinucleotide stacks corresponding to the first and second codon positions [<a href="#B68-life-14-01307" class="html-bibr">68</a>]) and amino acid novelty of corresponding residue (<b>A</b>), thermostability of codons and DisProt foldability of corresponding residues (<b>B</b>), and thermostability of codons and buriability of corresponding residues (<b>C</b>), buriability of amino acids and their novelty, (<b>D</b>), and DisProt foldability and buriability (<b>E</b>). Red and blue symbols correspond to disorder- and order-promoting residues as defined by the DisProt-based scale.</p>
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<p>Correlation between intrinsic disorder content and proteome size of 3484 species of viruses, archaea, bacteria, and eukaryotes. Each symbol indicates a species. There are six groups of species: viruses expressing one polyprotein precursor (small red circles filled with blue), other viruses (small red circles), bacteria (small green circles), archaea (blue circles), unicellular eukaryotes (brown squares), and multicellular eukaryotes (pink triangles). Each viral polyprotein was analyzed as a single polypeptide chain, without parsing it into the individual proteins before predictions. The proteome size is the number of proteins in the proteome of that species and is shown as the log base. The average fraction of disordered residues is calculated by averaging the fraction of disordered residues of each sequence over all sequences of that species. Disorder prediction is evaluated by PONDR-VSL2B. Adapted with permission from Ref. [<a href="#B3-life-14-01307" class="html-bibr">3</a>]. Copyright © 2013 The Protein Society.</p>
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<p>Wavy pattern of the global evolution of protein intrinsic disorder. The x-axis represents evolutionary time and the y-axis shows disorder content in proteins at a given evolutionary time point. Here, primordial proteins are expected to be mostly disordered (left-hand side of the plot), proteins in LUA likely are mostly structured (center of the plot), whereas many proteins in eukaryotes are either totally disordered or hybrids containing both ordered and disordered regions (right-hand side of the plot). Adapted with permission from Ref. [<a href="#B3-life-14-01307" class="html-bibr">3</a>]. Copyright © 2013 The Protein Society.</p>
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<p>Intrinsic disorder in spliceosomal proteins. (<b>A</b>) The 3D structural model generated for one of the moon-lighting spliceosomal proteins RBFOX2 (UniProt ID: O43251) by AlphaFold [<a href="#B156-life-14-01307" class="html-bibr">156</a>]. The structure is colored according to the model confidence. (<b>B</b>) Per-residue intrinsic disorder profile of RBFOX2 generated by RIDAO [<a href="#B157-life-14-01307" class="html-bibr">157</a>]. (<b>C</b>) RIDAO-generated per-residue intrinsic disorder profile of spliceosomal protein SRRM2 (UniProt ID: Q9UQ35) involved in the biogenesis of nuclear speckles.</p>
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<p>Multifactorial intrinsic disorder analysis of the entire proteome of amoeboid holozoan <span class="html-italic">Capsaspora owczarzaki</span> containing 9794 proteins. (<b>A</b>) PONDR<sup>®</sup> VSL2 Score vs. VSL2 PONDR<sup>®</sup> (%) analysis. PONDR<sup>®</sup> VSL2 (%) is a percent of predicted intrinsically disordered residues (PPIDRs), i.e., residues with disorder scores above 0.5. PONDR<sup>®</sup> VSL2 score is the average disorder score (ADS) for a protein. Based on these parameters, query proteins are classified as ordered (PPIDR &lt; 10%; ADS &lt; 0.15), moderately disordered (10% ≤ PPIDR &lt; 30%; 0.15 ≤ ADS &lt; 0.5), and highly disordered (PPIDR ≥ 30%; ADS ≥ 0.5). Color blocks indicate regions in which proteins are mostly ordered (blue and light blue), moderately disordered (pink and light pink), or mostly disordered (red). If the two parameters agree, the corresponding part of the background is dark (blue or pink), whereas light blue and light pink reflect areas in which the predictors disagree with each other. The boundaries of the colored regions represent arbitrary and accepted cutoffs for ADS (y-axis) and the percentage of predicted disordered residues (PPIDR; x-axis). For comparison, in the human proteome, 0.4%, 5.1%, 33.7%, 21.0%, and 40.1% of proteins are located within blue, light blue, pink, light pink, and red segments, respectively. This distribution observed in the human proteome is remarkably close to the distribution reported here for the <span class="html-italic">C. owczarzaki</span> proteins. (<b>B</b>) Charge-Hydropathy and Cumulative Distribution Function (CH-CDF) analysis of <span class="html-italic">C. owczarzaki</span> proteins. The CH-CDF plot is a two-dimensional representation that integrates both the CH plot, which correlates a protein’s net charge and hydrophobicity with its structural order, and the CDF, which cumulates disorder predictions from the N-terminus to the C-terminus of a protein, offering insight into the distribution of disorder residues. The y-axis (ΔCH) represents the protein’s distance from the CH boundary, indicating the balance between charge and hydrophobicity, while the x-axis (ΔCDF) represents the deviation of a protein’s disorder frequency from the CDF boundary. Proteins are then stratified into four quadrants: Quadrant 1 (bottom right) indicates proteins likely to be structured; Quadrant 2 (bottom left) includes proteins that may be in a molten globule state or lack a unique 3D structure; Quadrant 3 (top left) consists of proteins predicted to be highly disordered; Quadrant 4 (top right) captures proteins that present a mixed prediction of being disordered according to CH but ordered according to CDF. For comparison, 59.1%, 25.5%, 12.3%, and 3.1% of human proteins are located within quadrants Q1, Q2, Q3, and Q4, respectively. This indicates that although the <span class="html-italic">C. owczarzaki</span> and human proteomes contain comparable fractions of ordered proteins, there are noticeably more native molten globules and noticeably less highly disordered proteins in the <span class="html-italic">C. owczarzaki</span> proteome.</p>
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<p>Three-dimensional structural model generated by AlphaFold [<a href="#B156-life-14-01307" class="html-bibr">156</a>] for mouse GATA1 (UniProt ID: P17679) (<b>A</b>), GATA2 (UniProt ID: O09100) (<b>B</b>), and PU.1 (UniProt ID: P17679) (<b>C</b>) proteins. Structures are colored according to the model confidence, with blue, cyan, yellow, and orange colors corresponding to the regions with very high, high, low, and very low confidence, respectively.</p>
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18 pages, 3676 KiB  
Article
Thermo- and pH-Responsible Gels for Efficient Protein Adsorption and Desorption
by Izabela Poplewska, Beata Strachota, Adam Strachota, Grzegorz Poplewski and Dorota Antos
Molecules 2024, 29(20), 4858; https://doi.org/10.3390/molecules29204858 - 13 Oct 2024
Viewed by 597
Abstract
Protein adsorption behavior was examined on poly(N-isopropylacrylamide-co-sodium methacrylate)-based hydrogels at different temperatures: 5, 20, and 37 °C, and pH: 4.5, 7, and 9.2. The hydrogels, whose covalent skeleton contains pendant anionic units due to the presence of the sodium methacrylate co-monomer, [...] Read more.
Protein adsorption behavior was examined on poly(N-isopropylacrylamide-co-sodium methacrylate)-based hydrogels at different temperatures: 5, 20, and 37 °C, and pH: 4.5, 7, and 9.2. The hydrogels, whose covalent skeleton contains pendant anionic units due to the presence of the sodium methacrylate co-monomer, exhibited both thermo- and pH-sensitivity with different extents, which depended on the content of ionizable moieties and the cross-linker density. The hydrogel composition, temperature, and pH influenced the zeta potential of the hydrogels and their swelling properties. The proteins selected for the study, i.e., bovine serum albumin (BSA), ovalbumin (OVA), lysozyme (LYZ), and a monoclonal antibody (mAb2), differed in their aminoacidic composition and conformation, thus in isoelectric point, molecular weight, electrostatic charge, and hydrophobicity. Therefore, the response of their adsorption behavior to changes in the solution properties and the hydrogel composition was different. LYZ exhibited the strongest adsorption of all proteins with a maximum at pH 7 (189.5 mg ggel1); adsorption of BSA and OVA reached maximum at pH 4.5 (24.4 and 23.5 mg ggel1), whereas mAb2 was strongly adsorbed at 9.2 (21.7 mg ggel1). This indicated the possibility of using the hydrogels for pH-mediated separation of proteins differing in charge under mild conditions in a water-rich environment of both the liquid solution and the adsorbed phase. The adsorption affinity of all proteins increased with temperature, which was attributed to the synergistic effects of attractive electrostatic and hydrophobic interactions. That effect was particularly marked for mAb2, for which the temperature change from 5 to 37 °C caused a twentyfold increase in adsorption. In all cases, the proteins could be released from the hydrogel surface by a reduction in temperature, an increase in pH, or a combination of both. This allows for the elimination of the use of salt solution as a desorbing agent, whose presence renders the recycling of buffering solutions difficult. Full article
(This article belongs to the Special Issue Feature Papers in Applied Chemistry: 3rd Edition)
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Graphical abstract

Graphical abstract
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<p>Structure of the tested polymer adsorbents (crosslinked PNIPAM-co-PolySMA), with highlighted monomeric units: NIPAM (the main monomer), responsible for LCST (T-induced switching between hydrophilic and hydrophobic state); SMA co-monomer responsible for swelling sensitivity to pH, which also means pH-dependent charge; BAA co-monomer incorporated as a crosslinker.</p>
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<p>Temperature and composition dependence of <span class="html-italic">Q</span> for PNIPAM-co-PolySMA for different SMA and BAA content at pH 4.5 (<b>a</b>), 7 (<b>b</b>), and 9.2 (<b>c</b>).</p>
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<p>Cartoon representation of interactions between a protein and hydrogel (<b>a</b>) at a lower pH, (<b>b</b>) at a higher pH, (<b>c</b>) at a higher temperature (T &gt; LCST), and (<b>d</b>) at a lower temperature.</p>
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<p>Illustration of the adsorption behavior of BSA on PNIPAM-co-PolySMA for different SMA and BAA content at pH 4.5 (<b>a</b>), 7 (<b>b</b>), and 9.2 (<b>c</b>).</p>
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<p>Illustration of the adsorption behavior of BSA on PNIPAM-co-PolySMA for different SMA and BAA content at pH 4.5 (<b>a</b>), 7 (<b>b</b>), and 9.2 (<b>c</b>).</p>
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<p>Illustration of the adsorption behavior of LYZ on PNIPAM-co-PolySMA for different SMA and BAA content at pH 4.5 (<b>a</b>), 7 (<b>b</b>), and 9.2 (<b>c</b>).</p>
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<p>Illustration of the adsorption behavior of mAb2 on PNIPAM-co-PolySMA for different SMA and BAA content at pH 4.5 (<b>a</b>), 7 (<b>b</b>), and 9.2 (<b>c</b>).</p>
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18 pages, 2840 KiB  
Review
Phase Separation Mediated Sub-Nuclear Compartmentalization of Androgen Receptors
by Selçuk Yavuz, Tsion E. Abraham, Adriaan B. Houtsmuller and Martin E. van Royen
Cells 2024, 13(20), 1693; https://doi.org/10.3390/cells13201693 - 13 Oct 2024
Viewed by 620
Abstract
The androgen receptor (AR), a member of the nuclear steroid hormone receptor family of transcription factors, plays a crucial role not only in the development of the male phenotype but also in the development and growth of prostate cancer. While AR structure and [...] Read more.
The androgen receptor (AR), a member of the nuclear steroid hormone receptor family of transcription factors, plays a crucial role not only in the development of the male phenotype but also in the development and growth of prostate cancer. While AR structure and AR interactions with coregulators and chromatin have been studied in detail, improving our understanding of AR function in gene transcription regulation, the spatio-temporal organization and the role of microscopically discernible AR foci in the nucleus are still underexplored. This review delves into the molecular mechanisms underlying AR foci formation, focusing on liquid–liquid phase separation and its role in spatially organizing ARs and their binding partners within the nucleus at transcription sites, as well as the influence of 3D-genome organizations on AR-mediated gene transcriptions. Full article
(This article belongs to the Collection Functions of Nuclear Receptors)
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Figure 1
<p>AR and its coregulators: schematic representation of the AR’s mode-of-action starting from hormonal stimulation (<b>A</b>), followed by DNA-binding at AR-binding sites (ARBS) containing androgen-responsive elements (AREs) at CIS-regulatory elements (CISs) as either monomer (not shown) or homodimer (<b>B</b>). Subsequently, AR interacts with various coregulators (<b>C</b>) to eventually initiate gene transcription by phosphorylating serine 5 of RNA polymerase II of the preinitiation complex (PIC) via the mediator complex (<b>D</b>).</p>
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<p>Relationship between AR structural status and LLPS: (<b>A</b>) Confocal image of a cell expressing testosterone-stimulated EGFP-AR. Arrows indicate the location of some well-defined AR foci as example. (<b>B</b>) AR full-length wild type consists of an N-terminal domain (NTD), DNA-binding domain (DBD) and Ligand-binding domain (LBD). Upon stimulation by testosterone and other (synthetic) derivates, the AR wild type forms intranuclear foci whereas AR truncated mutants lacking either the NTD, DBD or the LBD (e.g., ARv7) are not able to form foci. Biophysical measurements using fluorescence recovery after photobleaching (FRAP) revealed that AR WT diffuses the slowest over time whereas the AR truncated mutants lacking the NTD, DBD or the LBD are significantly faster diffusing.</p>
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<p>Three-dimensional chromatin regulation in context of AR biology. ARs are located at transcriptionally active and inactive regions, which are topologically organized in well-separated chromatin domain (TADs) by the cohesin complex, mainly located at euchromatic regions. Active and inactive TADs are characterized by presence of transcriptionally initiating or repressing epigenetic marks. ARs play role during Intra-TAD interactions, such as promotor-enhancer or promotor-insulator interactions, by potentially recruiting mainly cohesin-STAG2 complexes at enhancers. Outcome of this regulation depends on the type of CIS-regulatory elements (enhancer or insulator) present in the (intra-)TAD region, alongside the epigenetic status and chromatin compaction of the locus.</p>
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<p>AR condensation in live cells. (<b>A</b>) schematic illustration showing protein condensation process known as LLPS. Proteins consisting intrinsically disorder regions (IDR), such as AR, are able to form membrane-less compartments in the nuclear environment together with cofactors and other biomolecules such as DNA and RNAs. (<b>B</b>) Mobile, highly diffusive ARs in N/C conformation are not yet nucleated on the DNA upon testosterone stimulation. (<b>C</b>,<b>D</b>) Shortly afterwards, AR condensation takes place, forming either transcriptionally active condensates (<b>C</b>) (containing coactivators such as HATs) or transcriptionally repressive condensates (<b>D</b>) (consisting corepressors such as HDACs) which both consists of confined molecules with a low diffusivity as consequence of direct DNA-binding and weak protein-protein interactions.</p>
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17 pages, 10208 KiB  
Article
Calcium Carbonate as Dephosphorization Agent in Direct Reduction Roasting of High-Phosphorus Oolitic Iron Ore: Reaction Behavior, Iron Recovery, and Dephosphorization Mechanism
by Chong Chen and Shichao Wu
Minerals 2024, 14(10), 1023; https://doi.org/10.3390/min14101023 - 12 Oct 2024
Viewed by 264
Abstract
Calcium carbonate, renowned for its affordability and potent dephosphorization capabilities, finds widespread use as a dephosphorization agent in the direct reduction roasting of high-phosphorus oolitic hematite (HPOIO). However, its precise impact on iron recovery and the dephosphorization of iron minerals with phosphorus within [...] Read more.
Calcium carbonate, renowned for its affordability and potent dephosphorization capabilities, finds widespread use as a dephosphorization agent in the direct reduction roasting of high-phosphorus oolitic hematite (HPOIO). However, its precise impact on iron recovery and the dephosphorization of iron minerals with phosphorus within HPOIO, particularly the mineral transformation rule and dephosphorization mechanism, remains inadequately understood. This study delves into the nuanced effects of calcium carbonate on iron recovery and dephosphorization through direct reduction roasting and magnetic separation. A direct reduction iron (DRI) boasting 95.57% iron content, 93.94% iron recovery, 0.08% phosphorus content, and an impressive 92.08% dephosphorization is achieved. This study underscores how the addition of calcium carbonate facilitates the generation of apatite from phosphorus in iron minerals and catalyzes the formation of gehlenite by reacting with silicon dioxide and alumina, inhibiting apatite reduction. Furthermore, it increases the liquid phase, enhancing the dissociation of metallic iron monomers during the grinding procedure, thus facilitating efficient dephosphorization. Full article
(This article belongs to the Section Mineral Processing and Extractive Metallurgy)
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Figure 1
<p>Micro-features of HPOIO: (<b>a</b>) oolitic structure; (<b>b</b>,<b>c</b>) surface distributions of iron and phosphorus, respectively; (<b>d</b>–<b>f</b>) iron minerals, apatite, and chlorite, respectively.</p>
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<p>Schematic diagram of calcium carbonate-enhanced HPOIO for iron recovery and dephosphorization through CDRRMS.</p>
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<p>Thermodynamic results for varying amounts of calcium carbonate: (<b>a</b>) proportion of main products; (<b>b</b>) Gibbs free energy (ΔG<sup>θ</sup>) in relation to temperature.</p>
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<p>Effects of different roasting conditions on DRI: (<b>a</b>) effect of calcium carbonate dosage; (<b>b</b>) effect of straw charcoal dosage; (<b>c</b>) effect of roasting temperature; (<b>d</b>) effect of roasting time.</p>
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<p>Influence of calcium carbonate concentration on mineral transformation of roasted ore.</p>
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<p>SEM-EDS of roasted ores at different amounts of calcium carbonate: SEM images: (<b>a</b>) 0%; (<b>b</b>) 15%; (<b>c</b>) 28%. Energy spectrum results: points 1, 3, and 5—metallic iron; points 2, 4, and 6—apatite. The EDS spectra in subfigures (<b>d</b>–<b>f</b>) correspond to the marked points in subfigures (<b>a</b>–<b>c</b>).</p>
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<p>SEM-EDS of roasted ores at different amounts of calcium carbonate: SEM images: (<b>a</b>) 0%; (<b>b</b>) 15%; (<b>c</b>) 28%. Energy spectrum results: points 1, 3, and 5—metallic iron; points 2, 4, and 6—apatite. The EDS spectra in subfigures (<b>d</b>–<b>f</b>) correspond to the marked points in subfigures (<b>a</b>–<b>c</b>).</p>
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<p>Scanning electron microscopy energy spectrum of magnetic separation concentrate under varying calcium carbonate dosages: (<b>a</b>) 0%; (<b>c</b>) 15%; (<b>e</b>) 28%; (<b>b</b>,<b>d</b>,<b>f</b>) are enlarged images of bounding box areas in (<b>a</b>,<b>c</b>,<b>e</b>), respectively; (<b>g</b>–<b>i</b>) apatite.</p>
Full article ">Figure 7 Cont.
<p>Scanning electron microscopy energy spectrum of magnetic separation concentrate under varying calcium carbonate dosages: (<b>a</b>) 0%; (<b>c</b>) 15%; (<b>e</b>) 28%; (<b>b</b>,<b>d</b>,<b>f</b>) are enlarged images of bounding box areas in (<b>a</b>,<b>c</b>,<b>e</b>), respectively; (<b>g</b>–<b>i</b>) apatite.</p>
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<p>Examination of iron and phosphorus in roasted ore at varying calcium carbonate dosages: (<b>a</b>) iron metallization; (<b>b</b>) phosphorus distribution.</p>
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<p>Mechanism of calcium carbonate on direct reduction roasting of HPOIO.</p>
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17 pages, 2804 KiB  
Article
Quantitation of Copper Tripeptide in Cosmetics via Fabric Phase Sorptive Extraction Combined with Zwitterionic Hydrophilic Interaction Liquid Chromatography and UV/Vis Detection
by Pantelitsa Pingou, Anthi Parla, Abuzar Kabir, Kenneth G. Furton, Victoria Samanidou, Spyridon Papageorgiou, Efthimios Tsirivas, Athanasia Varvaresou and Irene Panderi
Separations 2024, 11(10), 293; https://doi.org/10.3390/separations11100293 - 12 Oct 2024
Viewed by 397
Abstract
The increasing demand for effective cosmetics has driven the development of innovative analytical techniques to ensure product quality. This work presents the development and validation of a zwitterionic hydrophilic interaction liquid chromatography method, coupled with ultraviolet detection, for the quantification of copper tripeptide [...] Read more.
The increasing demand for effective cosmetics has driven the development of innovative analytical techniques to ensure product quality. This work presents the development and validation of a zwitterionic hydrophilic interaction liquid chromatography method, coupled with ultraviolet detection, for the quantification of copper tripeptide in cosmetics. A novel protocol for sample preparation was developed using fabric phase sorptive extraction to extract the targeted analyte from the complex cosmetic cream matrix, followed by chromatographic separation on a ZIC®-pHILIC analytical column. A thorough investigation of the chromatographic behavior of the copper tripeptide on the HILIC column was performed during method development. The mobile phase consisted of 133 mM ammonium formate (pH 9, adjusted with ammonium hydroxide) and acetonitrile at a 40:60 (v/v) ratio, with a flow rate of 0.2 mL/min. A design of experiments (DOE) approach allowed precise adjustments to various factors influencing the extraction process, leading to the optimization of the fabric phase sorptive extraction protocol for copper tripeptide analysis. The method demonstrated excellent linearity over a concentration range of 0.002 to 0.005% w/w for copper tripeptide, with a correlation coefficient exceeding 0.998. The limits of detection and quantitation were 5.3 × 10−4% w/w and 2.0 × 10−3% w/w, respectively. The selectivity of the method was verified through successful separation of copper tripeptide from other cream components within 10 min, establishing its suitability for high-throughput quality control of cosmetic formulations. Full article
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Graphical abstract
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<p>Schematic workflow diagram of the fabric phase sorptive extraction method. Arrows with a depiction of the membrane being moved with forceps indicate membrane relocation between different vials.</p>
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<p>(<b>a</b>) Chemical structure of GHK-Cu and (<b>b</b>) ionization profile of GHK-Cu computed by ADME Boxes software as a function of pH with highlighted fraction at pH 9.</p>
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<p>Combined radar charts depicting the impact of (<b>a</b>) ammonium formate concentration and (<b>b</b>) water content percentage on the retention (Logk′), resolution (R × 10<sup>−1</sup>), peak symmetry (T), and theoretical plates (N × 10<sup>−3</sup>) of GHK-Cu. Resolution and theoretical plate values have been normalized to ensure all variables are presented in a comparable scale.</p>
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<p>HILIC-UV chromatogram of a 10.0 μg/mL GHK-Cu standard solution prepared in a 60:40 (<span class="html-italic">v</span>/<span class="html-italic">v</span>) water/acetonitrile mixture, using a <span class="html-italic">z</span>-axis in Empower<sup>®</sup> Software. Chromatographic conditions: ZIC<sup>®</sup>-pHILIC column; mobile phase: 133 mM ammonium formate water solution (pH 9.0) in acetonitrile at a ratio of 40:60, <span class="html-italic">v</span>/<span class="html-italic">v</span>; flow rate: 0.2 mL/min; λ = 224 nm.</p>
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<p>Scheme demonstrating sol-gel MTMS/PheTES/CW20M membrane.</p>
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<p>(<b>a</b>) Pareto chart displaying the ranked influence of key factors on GHK-Cu recovery (%), in order of decreasing statistical significance, and (<b>b</b>) 3D surface plot illustrating the effects of extraction time (min) and extraction volume (mL) on GHK-Cu recovery (%).</p>
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<p>Overlaid chromatograms from FPSE-HILIC-UV analysis of a cosmetic cream containing 0.004% <span class="html-italic">w</span>/<span class="html-italic">w</span> GHK-Cu (black line) and a placebo cream (blue line), visualized using the <span class="html-italic">z</span>-axis in Empower<sup>®</sup> Software. Chromatographic conditions: ZIC<sup>®</sup>-pHILIC column; mobile phase: 133 mM ammonium formate (pH 9.0) in acetonitrile (40:60, <span class="html-italic">v</span>/<span class="html-italic">v</span>); flow rate: 0.2 mL/min; detection at 224 nm.</p>
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14 pages, 3426 KiB  
Article
Multiphase Behavior of the Water + 1-Butanol + Deep Eutectic Solvent Systems at 101.3 kPa
by Isadora Pires Gomes, Nicolas Pinheiro dos Santos, Pedro Bernardes Noronha, Ryan Ricardo Bitencourt Duarte, Henrique Pina Cardim, Erivaldo Antônio da Silva, Renivaldo José dos Santos, Leandro Ferreira-Pinto and Pedro Arce
Molecules 2024, 29(20), 4814; https://doi.org/10.3390/molecules29204814 - 11 Oct 2024
Viewed by 569
Abstract
The growing demand for more sustainable routes and processes in the mixture separation and purification industry has generated a need to search for innovations, with new solvent alternatives being a possible solution. In this context, a new class of green solvents, known as [...] Read more.
The growing demand for more sustainable routes and processes in the mixture separation and purification industry has generated a need to search for innovations, with new solvent alternatives being a possible solution. In this context, a new class of green solvents, known as deep eutectic solvents (DESs), has been gaining prominence in recent years in both academic and industrial spheres. These solvents, when compared to ionic liquids (ILs), are more environmentally friendly, less toxic, low-cost, and easier to synthesize. In addition, they have significantly lower melting points than their precursors, offering a promising option for various applications in this industrial sector. Understanding and studying the thermodynamic behavior of systems composed of these substances in purification and separation processes, such as liquid–liquid extraction and azeotropic distillation, is extremely important. This work aimed to study the phase behavior of liquid–liquid equilibrium (LLE) and vapor–liquid equilibrium (VLE) of water + 1-butanol + DES (choline chloride + glycerol) systems with a molar ratio of 1:2. Experimental LLE data, obtained at 298.15 K and 101.3 kPa, and VLE data, obtained at 101.3 kPa and in the temperature range of 364.05 K–373.85 K, were submitted to the thermodynamic quality/consistency test, proposed by Marcilla et al. and Wisniak, and subsequently modeled using the gamma–gamma approach for the LLE and gamma–phi for the VLE. The non-random two-liquid (NRTL) model was used to calculate the activity coefficient. The results are presented for the VLE in a temperature–composition phase diagram (triangular prism) and triangular phase diagrams showing the binodal curve and tie lines (LLE). The separation and distribution coefficients of LLE were determined to evaluate the extractive potential of the DES. For the VLE, the values of the relative volatility of the system were calculated, considering the entrainer free-basis, to evaluate the presence or absence of azeotropes in the range of collected points. From these data, it was possible to compare DES with ILs as extracting agents, using data from previous studies carried out by the research group. Therefore, the results indicate that the NRTL model is efficient at correlating the fluid behavior of both equilibria. Thus, this study serves as a basis for future studies related to the understanding and design of separation processes. Full article
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<p>Phase diagram of the Water + 1-Butanol + DES system at 298.15 K (101.3 kPa).</p>
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<p>Ternary Txy phase diagram for experimental and NRTL model data for VLE of the water (1) + 1-butanol (2) + DES (3) systems (101.3 kPa).</p>
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<p>Experimental equipment used to collect LLE experimental data: (<b>a</b>) equilibrium cell; (<b>b</b>) all experimental equipment.</p>
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<p>Experimental equipment used to collect VLE experimental data.</p>
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11 pages, 457 KiB  
Review
A Review of Recent Advances in Chromatographic Quantification Methods for Cyanogenic Glycosides
by Yao Zhao, Shuai Wen, Yan Wang, Wenshuo Zhang, Xiangming Xu and Yi Mou
Molecules 2024, 29(20), 4801; https://doi.org/10.3390/molecules29204801 - 11 Oct 2024
Viewed by 322
Abstract
Cyanogenic glycosides are naturally occurring compounds found in numerous plant species, which can release toxic hydrogen cyanide upon hydrolysis. The quantification of cyanogenic glycosides is essential for assessing their potential toxicity and health risks associated with their consumption. Liquid chromatographic techniques coupled with [...] Read more.
Cyanogenic glycosides are naturally occurring compounds found in numerous plant species, which can release toxic hydrogen cyanide upon hydrolysis. The quantification of cyanogenic glycosides is essential for assessing their potential toxicity and health risks associated with their consumption. Liquid chromatographic techniques coupled with various detectors have been widely used for the quantification of cyanogenic glycosides. In this review, we discuss recent advances in chromatographic quantification methods for cyanogenic glycosides, including the development of new stationary phases, innovative sample preparation methods, and the use of mass spectrometry. We also highlight the combination of chromatographic separation with mass spectrometric detection for the identification and quantification of specific cyanogenic glycosides and their metabolites in complex sample matrices. Lastly, we discuss the current challenges and future perspectives in the development of reliable reference standards, optimization of sample preparation methods, and establishment of robust quality control procedures. This review aims to provide an overview of recent advances in chromatographic quantification methods for cyanogenic glycosides and their applications in various matrices, including food products, biological fluids, and environmental samples. Full article
(This article belongs to the Special Issue Analytical Chemistry in Asia)
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<p>General structure of cyanogenic glycosides. In the structure formula, R<sub>1</sub> represents a proton for amygdalin, prunasin, and dhurrin and a methyl group for linamarin, while R<sub>2</sub> is a changeable organic group.</p>
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13 pages, 1327 KiB  
Article
Development of a UHPLC-MS/MS Method for the Determination of Moxidectin in Rat Plasma and Its Application in Pharmacokinetics
by Hongjuan Zhang, Zhen Yang, Baocheng Hao, Di Wu, Dan Shao, Yu Liu, Wanxia Pu, Shouli Yi, Ruofeng Shang and Shengyi Wang
Molecules 2024, 29(20), 4786; https://doi.org/10.3390/molecules29204786 - 10 Oct 2024
Viewed by 340
Abstract
The aim of the present study was to establish a simple and reliable ultra-high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) method and apply it for the determination of pharmacokinetics of moxidectin-loaded microspheres (MOX-MS) in rats. Plasma samples were processed using a simplified liquid–liquid [...] Read more.
The aim of the present study was to establish a simple and reliable ultra-high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) method and apply it for the determination of pharmacokinetics of moxidectin-loaded microspheres (MOX-MS) in rats. Plasma samples were processed using a simplified liquid–liquid extraction method and were separated using an Agilent Zorbax Eclipse Plus C18 column (50 mm × 2.1 mm, 1.8 μm) with a mobile phase consisting of a 10 mM ammonium formate solution with 0.1% formic acid (A) and acetonitrile (B) at a flow rate of 0.4 mL/min for 5 min. Avermectin B1a was used as an internal standard (IS). The sample was injected at a volume of 10 μL with a column temperature of 35 °C and detected in a positive ion mode. A good linear response across the concentration range of 1.00–200 ng/mL (r2 > 0.99) and a lower limit of quantification (LLOQ) of 1.00 ng/mL were achieved. The extraction recovery of moxidectin exceeded 94.1%, the matrix effect was between 91.2% and 96.2%, the accuracy ranged from 100.1 to 103.6%, and the relative standard deviation (RSD) did not exceed 15% for the intra- and inter-day accuracy and precision. The pharmacokinetic results showed that MOX-MS significantly decreased Cmax, prolonged T1/2, and improved bioavailability. The developed method significantly reduced the assay volume, shortened detection time, simplified sample processing methods and saved assay costs, which may contribute to the development of the new antiparasitic drug. Full article
(This article belongs to the Section Analytical Chemistry)
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<p>Product ion spectra of moxidectin (<b>A</b>) and avermectin B1a (<b>B</b>).</p>
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<p>Chromatograms of moxidectin and IS in rat plasma. (<b>A</b>) blank plasma; (<b>B</b>) a blank plasma spiked with LLOQ; (<b>C</b>) a plasma sample obtained after a single subcutaneous injection of 1 mg/kg moxidectin.</p>
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<p>Plasma concentration–time curves of moxidectin in rats after subcutaneous administration (1 mg/kg) (<span class="html-italic">n</span> = 6). (<b>A</b>) Moxidectin solution; (<b>B</b>) Moxidectin microspheres.</p>
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19 pages, 2979 KiB  
Article
Quantitative Analysis of Ferrate(VI) and Its Degradation Products in Electrochemically Produced Potassium Ferrate for Waste Water Treatment
by Zoltán Homonnay, Sándor Stichleutner, Ernő Kuzmann, Miklós Kuti, Győző G. Láng, Kende Attila Béres, László Trif, Dániel J. Nagy, Gyula Záray and József Lendvai
Appl. Sci. 2024, 14(19), 9144; https://doi.org/10.3390/app14199144 - 9 Oct 2024
Viewed by 449
Abstract
Potassium ferrate(VI) (K2FeO4) as a particularly strong oxidant represents an effective and environmentally friendly waste water treatment material. When produced by anodic oxidation in highly alkaline aqueous solution, the K2FeO4 product is separated and sealed in [...] Read more.
Potassium ferrate(VI) (K2FeO4) as a particularly strong oxidant represents an effective and environmentally friendly waste water treatment material. When produced by anodic oxidation in highly alkaline aqueous solution, the K2FeO4 product is separated and sealed in inert plastic bags with the retention of some liquid phase with high pH. This method proved to be excellent for long-term storage at moderately low temperature (5 °C) for industrial applications. It is still imperative to check the ferrate(VI) content of the product whenever it is to be used. Fe-57 Mössbauer spectroscopy is an excellent tool for checking the ratio of ferrate(VI) to the degradation product iron(III) in a sample. For this purpose, normally the spectral areas of the corresponding subspectra are considered; however, this approximation neglects the possible differences in the corresponding Mössbauer–Lamb factors. In this work, we have successfully determined the Mössbauer–Lamb factors for the ferrate(VI) and for the most common iron(III) degradation products observed. We have found superparamagnetic behavior and low-temperature phase transformation for another iron(III) degradation product that made the determination of the Mössbauer–Lamb factors impossible in that case. The identities of a total of three different iron(III) degradation products have been confirmed. Full article
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<p>Temperature variation of the normalized areas for ferrate(VI) (purple squares) and for the combination of the iron(III) degradation products Fe<sup>III</sup>(1) and Fe<sup>III</sup>(2) (orange dots) with some sample Mössbauer spectra recorded at the indicated temperatures (Experiment 1).</p>
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<p>Temperature variation of the normalized spectral areas for ferrate(VI) (purple squares) and for Fe<sup>III</sup>(2) (orange dots) with some sample Mössbauer spectra recorded at the indicated temperatures (Experiment 2).</p>
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<p>Anomalous temperature variation of the spectral areas of species Fe<sup>III</sup>(2) (orange dots) in Mössbauer spectra recorded in narrow velocity range in Experiments 3. The ferrate(VI) (purple squares) behaves regularly.</p>
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<p>Mössbauer spectra of a ferrate sample containing degradation product Fe<sup>III</sup>(2) recorded at the indicated temperatures (Experiment 4), and the temperature variation of the normalized areas for ferrate(VI) (purple squares) and Fe<sup>III</sup>(2) (orange dots), the latter meaning the sum of the areas of the sextet and the iron(III) doublet.</p>
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<p>Selected Mössbauer spectra of a ferrate(VI) sample with degradation product Fe<sup>III</sup>(2) recorded in wide velocity range at the indicated temperatures (Experiment 5), and the temperature variation of the normalized areas for ferrate(VI) (purple squares) and Fe<sup>III</sup>(2) (orange dots), the latter meaning the sum of the areas of the sextet and the iron(III) doublet.</p>
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<p>Mössbauer spectra of a ferrate(VI) sample containing Fe<sup>III</sup>(2) degradation product at selected temperatures recorded in ±6 mm/s velocity range (Experiment 7), and the temperature variation of the normalized areas for ferrate(VI) (purple squares) and Fe<sup>III</sup>(2) (orange dots).</p>
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<p>Low-temperature DSC curve of a ferrate(VI) sample containing degradation product Fe<sup>III</sup>(2) in fully superparamagnetic form in the studied temperature range.</p>
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<p>Selected Mössbauer spectra of a ferrate(VI) sample containing Fe<sup>III</sup>(1) as an iron(III) degradation product, recorded in wide velocity range at the indicated temperatures (Experiment 6), together with the temperature variation of the normalized areas for ferrate(VI) (purple squares) and Fe<sup>III</sup>(1) (orange dots).</p>
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<p>Mössbauer spectra of a ferrate(VI) sample containing only Fe<sup>III</sup>(1) as a degradation product, recorded at the indicated temperatures (Experiment 8) together with the temperature variation of the normalized areas for ferrate(VI) (purple squares) and Fe<sup>III</sup>(1) (orange dots).</p>
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<p>Debye fits for ferrate(VI) (<b>left</b>) and Fe<sup>III</sup>(1) (<b>right</b>) observed in Experiment 8. The calculated Debye temperatures are 287(20) K and 300(63) K for ferrate(VI) and Fe<sup>III</sup>(1), respectively.</p>
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<p>Mössbauer spectrum of a ferrate(VI) sample, recorded at 90 K, containing the single Fe<sup>III</sup>(1) degradation product in a large quantity.</p>
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16 pages, 3414 KiB  
Article
Green and Sensitive Analysis of the Antihistaminic Drug Pheniramine Maleate and Its Main Toxic Impurity Using UPLC and TLC Methods, Blueness Assessment, and Greenness Assessments
by Nessreen S. Abdelhamid, Huda Salem AlSalem, Faisal K. Algethami, Eglal A. Abdelaleem, Alaa M. Mahmoud, Dalal A. Abou El Ella and Mohammed Gamal
Chemosensors 2024, 12(10), 206; https://doi.org/10.3390/chemosensors12100206 - 9 Oct 2024
Viewed by 371
Abstract
For the first time, two direct and eco-friendly chromatographic approaches were adapted for the simultaneous estimation of pheniramine maleate (PAM) and its major toxic impurity, 2-benzyl pyridine (BNZ). Method A used reversed-phase ultra-performance liquid chromatography; separation was achieved within 4 min using a [...] Read more.
For the first time, two direct and eco-friendly chromatographic approaches were adapted for the simultaneous estimation of pheniramine maleate (PAM) and its major toxic impurity, 2-benzyl pyridine (BNZ). Method A used reversed-phase ultra-performance liquid chromatography; separation was achieved within 4 min using a C18 column with a developing system of methanol/water (60:40 v/v) with a 0.1 mL/min flow rate. Photodiode array detection was adjusted at 215 nm. The method was linear in the ranges of 5.0–70.0 and 0.05–10.0 µg/mL for PAM and BNZ, correspondingly. Method B used thin-layer chromatography; separation was applied on silica gel TLC F254 using ethanol/ethyl acetate/liquid ammonia (8:2:0.1, in volumes) at room temperature, at 265 nm. Linearity was assured at concentration ranges 0.5–8.0 and 0.1–3.0 µg/band for the two components, respectively. Generally, the new UPLC and TLC methods outperform the old ones in terms of quickness, greenness, and sensitivity. Concisely, the greenness features were partially achieved using the Green Analytical Procedure Index (GAPI) and the Analytical Greenness (AGREE) pictograms. In contrast, the usefulness of the novel approaches was assured via the Blue Applicability Grade Index (BAGI) tool. Full article
(This article belongs to the Special Issue Green Analytical Chemistry: Current Trends and Future Developments)
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<p>Structural formula of pheniramine maleate and 2-benzyl pyridine.</p>
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<p>RP-UPLC chromatogram of mixture of pheniramine maleate and 2-benzyl-pyridine with concentration 10 µg/mL. The mobile phase used was methanol/water (60:40 <span class="html-italic">v</span>/<span class="html-italic">v</span>).</p>
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<p>Two-dimensional TLC densitogram of binary mixture of PAM and BNZ, using developed system of ethanol/ethyl acetate/ammonia (8:2:0.1, by volume) at room temperature and scanned at 265 nm.</p>
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<p>AGREE pictogram for the novel RP-UPLC method using mobile phase of methanol/water (60:40 <span class="html-italic">v</span>/<span class="html-italic">v</span>).</p>
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<p>GAPI pictogram for the novel RP-UPLC method using mobile phase of methanol/water (60:40 <span class="html-italic">v</span>/<span class="html-italic">v</span>), Each criterion is assigned a green, yellow, or red rating based on its environmental significance. White sections mean not applicable.</p>
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<p>AGREE pictogram for the novel TLC method using mobile phase of ethanol/ethyl acetate/ammonia (8:2:0.1, by volume).</p>
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<p>GAPI pictogram for the novel TLC method using mobile phase of ethanol/ethyl acetate/ammonia (8:2:0.1, by volume).</p>
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<p>BAGI pictogram for the novel UPLC approach. Scales of dark blue to white indicate compliance levels, with dark blue representing the highest and white the lowest.</p>
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<p>BAGI pictogram for the novel TLC approach.</p>
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12 pages, 1991 KiB  
Article
The HPLC–PDA Method for Simultaneous Determination of Regalosides from Bulbs of Lilium lancifolium Thunb. and Their Antioxidant Effects
by Chang-Seob Seo, No Soo Kim and Kwang-Hoon Song
Plants 2024, 13(19), 2793; https://doi.org/10.3390/plants13192793 - 5 Oct 2024
Viewed by 380
Abstract
Lilium lancifolium Thunb. is a herbal medicine that is widely used to treat inflammation and lung diseases. In this study, a simultaneous quantitative method was developed for the quality control of BLL using high-performance liquid chromatography coupled with a photodiode array detector (HPLC–PDA), [...] Read more.
Lilium lancifolium Thunb. is a herbal medicine that is widely used to treat inflammation and lung diseases. In this study, a simultaneous quantitative method was developed for the quality control of BLL using high-performance liquid chromatography coupled with a photodiode array detector (HPLC–PDA), and their antioxidant effects were evaluated. Eight regalosides (i.e., regaloside A, B, C, E, F, H, I, and K) were selected as marker substances and separated on a Gemini C18 reversed-phase analytical column by gradient elution with distilled water–acetonitrile mobile phase containing 0.1% (v/v) formic acid. The method was validated with respect to linearity, sensitivities (limit of detection (LOD) and limit of quantitation (LOQ)), accuracy, and precision. The antioxidant effects of the extract and each component were evaluated using the 2,2-diphenyl-1-picrylhydrazyl radical scavenging assay and 2-2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) assay. The coefficients of determination values used as indicators of linearity for all components were ≥0.9999. LOD and LOQ concentrations were 0.10–0.66 μg/mL and 0.29–2.01 μg/mL, respectively. The recovery was 95.39–103.925% (relative standard deviation; RSD ≤ 2.55%), and precision RSD was <2.78%. The HPLC–PDA method was applied to real samples, and all components were detected at 1.12–29.76 mg/freeze-dried g. The evaluation of antioxidant effects showed that regalosides C, E, and K exhibited significant antioxidant effects. Our knowledge will be appropriately utilized in raw material management and conducting clinical and non-clinical studies on L. lancifolium or herbal medicine prescriptions containing L. lancifolium. Full article
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<p>Chemical structures of the eight regalosides selected as a marker compound for quality control of BLL.</p>
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<p>HPLC chromatograms of mixed standard compounds (<b>A</b>) and BLL extract (<b>B</b>) measured at 305, 310, and 325 nm. Regaloside K (1), regaloside C (2), regaloside H (3), regaloside A (4), regaloside F (5), regaloside E (6), regaloside B (7), and regaloside I (8).</p>
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<p>Free radical scavenging activities of BLL extract. The cationic and anionic radical scavenging activities of BLL extract were determined using ABTS and DPPH assays, respectively (<span class="html-italic">n</span> = 2).</p>
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<p>Free radical scavenging activities of the eight regalosides. The cationic and anionic radical scavenging activities of each individual chemical were determined using ABTS and DPPH assays, respectively. Ascorbic acid was used as a positive control for both assays (<span class="html-italic">n</span> = 2).</p>
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25 pages, 3928 KiB  
Review
Overview of Theory, Simulation, and Experiment of the Water Exit Problem
by Hualin Zheng, Hongfu Qiang, Yujie Zhu and Chi Zhang
J. Mar. Sci. Eng. 2024, 12(10), 1764; https://doi.org/10.3390/jmse12101764 - 5 Oct 2024
Viewed by 388
Abstract
The water exit problem, which is ubiquitous in ocean engineering, is a significant research topics in the interaction between navigators and water. The study of the water exit problem can help to improve the structural design of marine ships and underwater weapons, allowing [...] Read more.
The water exit problem, which is ubiquitous in ocean engineering, is a significant research topics in the interaction between navigators and water. The study of the water exit problem can help to improve the structural design of marine ships and underwater weapons, allowing for better strength and movement status. However, the water exit problem involves complex processes such as three-phase gas–liquid–solid coupling, cavitation, water separation, liquid surface deformation, and fragmentation, making it challenging to study. Following work carried out by many researchers on this issue, we summarize recent developments from three aspects: theoretical research, numerical simulation, and experimental results. In theoretical research, the improved von Karman model and linearized water exit model are introduced. Several classical experimental devices, data acquisition means, and cavitation approaches are introduced in the context of experimental development. Three numerical simulation methods, namely, the BEM (Boundary Element Method), VOF (Volume of Fluid), and FVM (Finite Volume Method) with LES (Large Eddy Simulation) are presented, and the respective limitations and shortcomings of these three aspects are analyzed. Finally, an outlook on future research improvements and developments of the water exit problem is provided. Full article
(This article belongs to the Section Ocean Engineering)
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<p>Force evolution during the water entry and exit of a wedge. Reproduced from [<a href="#B63-jmse-12-01764" class="html-bibr">63</a>] with permission from Elsevier/2024.</p>
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<p><math display="inline"><semantics> <msup> <mrow> <mi>F</mi> </mrow> <mo>*</mo> </msup> </semantics></math> acting on the wedge with respect to <math display="inline"><semantics> <msup> <mrow> <mi>t</mi> </mrow> <mo>*</mo> </msup> </semantics></math>. The red line corresponds to the numerical prediction and the blue line to the present model of water exit (where <math display="inline"><semantics> <mrow> <msup> <mrow> <mi>t</mi> </mrow> <mo>*</mo> </msup> <mo>&gt;</mo> <mn>1</mn> </mrow> </semantics></math>) and the Wagner model (where <math display="inline"><semantics> <mrow> <mn>0</mn> <mo>&lt;</mo> <msup> <mrow> <mi>t</mi> </mrow> <mo>*</mo> </msup> <mo>&lt;</mo> <mn>1</mn> </mrow> </semantics></math>). Reproduced from [<a href="#B66-jmse-12-01764" class="html-bibr">66</a>] with permission from Cambridge University Press/2024.</p>
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<p><math display="inline"><semantics> <msup> <mrow> <mi>F</mi> </mrow> <mo>*</mo> </msup> </semantics></math> acting on the parabolic with respect to <math display="inline"><semantics> <msup> <mrow> <mi>t</mi> </mrow> <mo>*</mo> </msup> </semantics></math>. The red line corresponds to the numerical prediction and the blue line to the present model of water exit (where <math display="inline"><semantics> <mrow> <msup> <mrow> <mi>t</mi> </mrow> <mo>*</mo> </msup> <mo>&gt;</mo> <mn>1</mn> </mrow> </semantics></math>) and the Wagner model (where <math display="inline"><semantics> <mrow> <mn>0</mn> <mo>&lt;</mo> <msup> <mrow> <mi>t</mi> </mrow> <mo>*</mo> </msup> <mo>&lt;</mo> <mn>1</mn> </mrow> </semantics></math>). Reproduced from [<a href="#B66-jmse-12-01764" class="html-bibr">66</a>] with permission from Cambridge University Press/2024.</p>
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<p>Experimental setup in free water exit of a fully submerged object. Reproduced from [<a href="#B49-jmse-12-01764" class="html-bibr">49</a>] with permission from Elsevier/2024.</p>
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<p>L-shaped restraint mechanism from the experimental setup in <a href="#jmse-12-01764-f005" class="html-fig">Figure 5</a>. Reproduced from [<a href="#B80-jmse-12-01764" class="html-bibr">80</a>] with permission from Elsevier/2024.</p>
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<p>Snapshots of free water exit of a light sphere by Wu. Reproduced from [<a href="#B80-jmse-12-01764" class="html-bibr">80</a>] with permission from Elsevier/2024.</p>
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<p>Lifting platform used by Adel Shams to test the water entry–exit of a wedge-shaped body. Reproduced from [<a href="#B65-jmse-12-01764" class="html-bibr">65</a>] with permission from AIP Publishing/2024. (<b>a</b>) Schematics of the PIV system, illustrating the positioning of the camera and laser; (<b>b</b>) schematics of the wedge; and (<b>c</b>) front view of the wedge.</p>
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<p>Equipment of the experiment with symmetrical bodies by Tassin. Reproduced from [<a href="#B89-jmse-12-01764" class="html-bibr">89</a>] with permission from Cambridge University Press/2024. (<b>a</b>) Schematics of the system and (<b>b</b>) picture of the experimental setup.</p>
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<p>Velocity evolution diagram of nails with different lengths by Shi [<a href="#B73-jmse-12-01764" class="html-bibr">73</a>].</p>
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<p>Model parameters of each head shape (2017) [<a href="#B74-jmse-12-01764" class="html-bibr">74</a>].</p>
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<p>Connection mode of launcher and launching base in Lu’s experiment [<a href="#B95-jmse-12-01764" class="html-bibr">95</a>].</p>
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<p>Water exit process of salvo of revolving bodies in Lu’s experiment [<a href="#B95-jmse-12-01764" class="html-bibr">95</a>].</p>
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<p>Sketch of the numerical procedure for breakup of the water layer by Wu. Reproduced from [<a href="#B49-jmse-12-01764" class="html-bibr">49</a>] with permission from Elsevier/2024. (<b>a</b>) Before breakup and (<b>b</b>) after breakup.</p>
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<p>Sketch of the numerical procedure for liquid detachment from the body surface by Wu. Reproduced from [<a href="#B49-jmse-12-01764" class="html-bibr">49</a>] with permission from Elsevier/2024. (<b>a</b>) Before detachment and (<b>b</b>) after detachment.</p>
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<p>Schematic diagram of the dynamic computational domain and the boundary condition by Chen. Reproduced from [<a href="#B127-jmse-12-01764" class="html-bibr">127</a>] with permission from Elsevier/2024.</p>
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<p>Asymmetric cavitation interface at different water exit angles of attack by Chen. Reproduced from [<a href="#B127-jmse-12-01764" class="html-bibr">127</a>] with permission from Elsevier/2024. (<b>a</b>) H = 10 L, AOA = 4°, V = 35 L/s; (<b>b</b>) H = 10 L, AOA = 8°, V = 35 L/s; (<b>c</b>) H = 10 L, AOA = 12°, V = 35 L/s.</p>
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22 pages, 6969 KiB  
Article
Predicting the Release Mechanism of Amorphous Solid Dispersions: A Combination of Thermodynamic Modeling and In Silico Molecular Simulation
by Stefanie Walter, Paulo G. M. Mileo, Mohammad Atif Faiz Afzal, Samuel O. Kyeremateng, Matthias Degenhardt, Andrea R. Browning and John C. Shelley
Pharmaceutics 2024, 16(10), 1292; https://doi.org/10.3390/pharmaceutics16101292 - 2 Oct 2024
Viewed by 779
Abstract
Background: During the dissolution of amorphous solid dispersion (ASD) formulations, the drug load (DL) often impacts the release mechanism and the occurrence of loss of release (LoR). The ASD/water interfacial gel layer and its specific phase behavior in connection with DL strongly dictate [...] Read more.
Background: During the dissolution of amorphous solid dispersion (ASD) formulations, the drug load (DL) often impacts the release mechanism and the occurrence of loss of release (LoR). The ASD/water interfacial gel layer and its specific phase behavior in connection with DL strongly dictate the release mechanism and LoR of ASDs, as reported in the literature. Thermodynamically driven liquid-liquid phase separation (LLPS) and/or drug crystallization at the interface are the key phase transformations that drive LoR. Methods: In this study, a combination of Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) thermodynamic modeling and in silico molecular simulation was applied to investigate the release mechanism and the occurrence LoR of an ASD formulation consisting of ritonavir as the active pharmaceutical ingredient (API) and the polymer, polyvinylpyrrolidone-co-vinyl acetate (PVPVA64). A thermodynamically modeled ternary phase diagram of ritonavir (PVPVA64) and water was applied to predict DL-dependent LLPS in the ASD/water interfacial gel layer. Microscopic Erosion Time Testing (METT) was used to experimentally validate the phase diagram predictions. Additionally, in silico molecular simulation was applied to provide further insights into the phase separation, the release mechanism, and aggregation behavior on a molecular level. Results: Thermodynamic modeling, molecular simulation, and experimental results were consistent and complementary, providing evidence that ASD/water interactions and phase separation are essential factors driving the dissolution behavior and LoR at 40 wt% DL of the investigated ritonavir/PVPVA64 ASD system, consistent with previous studies. Conclusions: This study provides insights into the potential of blending thermodynamic modeling, molecular simulation, and experimental research to comprehensively understand ASD formulations. Such a combined approach can be leveraged as a computational framework to gain insights into the ASD dissolution mechanism, thereby facilitating in silico screening, designing, and optimization of formulations with the benefit of significantly reducing the number of experimental tests. Full article
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<p>Grouping of atoms (on the left) into particles (on the right), employed for the coarse-grained representation of ritonavir (<b>a</b>), PVPVA64 (<b>b</b>), and water (<b>c</b>) molecules. Hydrogen, oxygen, carbon, sulfur, and nitrogen atoms are displayed as small white, red, gray, yellow, and blue balls, respectively.</p>
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<p>(<b>a</b>) Schematic of ASD/water interfacial layers depicting a dry glassy ASD core, hydrated gel layer, and hydrophobic drug-rich amorphous barrier formation triggered by LLPS. (<b>b</b>) Ternary phase diagram of ritonavir/PVPVA64/water system at 37 °C, and (<b>c</b>) zoom-in showing the solubility line (orange), binodal line (black), or LLPS boundary, tie lines (solid-gray), spinodal line (dashed-gray), and the glass transition line (dashed-green). The colored lines running towards the apex indicate the hydration pathways through the ASD/water interface into the bulk, starting from the dry ASD towards increasing water concentration for 1 wt%, 5 wt%, 15 wt%, 20 wt%, and 40 wt% DLs. The lower and upper half-filled circle symbols schematically refer to the corresponding polymer-rich (<span class="html-fig-inline" id="pharmaceutics-16-01292-i001"><img alt="Pharmaceutics 16 01292 i001" src="/pharmaceutics/pharmaceutics-16-01292/article_deploy/html/images/pharmaceutics-16-01292-i001.png"/></span>) and drug-rich (<span class="html-fig-inline" id="pharmaceutics-16-01292-i002"><img alt="Pharmaceutics 16 01292 i002" src="/pharmaceutics/pharmaceutics-16-01292/article_deploy/html/images/pharmaceutics-16-01292-i002.png"/></span>) phases, respectively, after LLPS at <span class="html-italic">eGT</span>.</p>
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<p>METT images at 37 °C of (<b>a</b>) 1 wt%, (<b>b</b>) 5 wt%, (<b>c</b>) 15 wt%, (<b>d</b>) 20 wt%, and (<b>e</b>) 40 wt% ritonavir-DL ASD discs after 10 and 40 min.</p>
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<p>Illustration of the two types of simulation employed in this work. Early-stage dissolution (top), modeled by a periodic box containing an ASD formed by polymer (green tubes) and ritonavir (red spheres) in contact with an aqueous medium (blue dots), and late-stage dissolution (bottom), represented by a periodic box containing small self-assembled drug/polymer pockets enveloped by water.</p>
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<p>Snapshots displaying the evolution of the PVPVA64 (in green) and ritonavir (in purple) from ASD models with DL ranging from 1 wt% to 40 wt% obtained from early-stage dissolution molecular simulations at times of (<b>a</b>) 200 ns, (<b>b</b>) 1.4 μs, and (<b>c</b>) 2.4 μs. Only half of the simulation cells are displayed to better focus on the phenomena at the ASD/water interface. The full snapshots are provided in the <a href="#app1-pharmaceutics-16-01292" class="html-app">supplementary information</a>. Water molecules are omitted for clarity.</p>
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<p>Percentage of non-converted drug molecules remaining in the simulation box after each 200 ns conversion cycle.</p>
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<p>Snapshots displaying the associations of the polymer (in green) and drug (in purple) within water with DL of 1 wt% (<b>a</b>), 5 wt% (<b>b</b>), 15 wt% (<b>c</b>), 20 wt% (<b>d</b>), and 40 wt% (<b>e</b>), as obtained at the end of late-stage dissolution molecular simulations. Water molecules were omitted for clarity.</p>
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<p>Zoom-in of the PVPVA64 corner of the ritonavir/PVPVA64/water ternary showing the hydration pathway (blue line) of 20 wt% DL ASD through the ASD/water interface into the water, starting from the dry ASD towards increasing water concentration. The half-filled circle symbols schematically correspond to the polymer-rich (<span class="html-fig-inline" id="pharmaceutics-16-01292-i011"><img alt="Pharmaceutics 16 01292 i011" src="/pharmaceutics/pharmaceutics-16-01292/article_deploy/html/images/pharmaceutics-16-01292-i011.png"/></span>) and drug-rich (<span class="html-fig-inline" id="pharmaceutics-16-01292-i012"><img alt="Pharmaceutics 16 01292 i012" src="/pharmaceutics/pharmaceutics-16-01292/article_deploy/html/images/pharmaceutics-16-01292-i012.png"/></span>) phases after LLPS at the interface. A schematic connection between the hydration pathway and the MD dissolution simulation of 20 wt% DL ASD is shown on the right.</p>
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<p>Series of analyses obtained from late-stage molecular simulations as functions of the DL: average number of drug and polymer molecules in the main self-assembled cluster, <span class="html-italic">N</span><sub>mol</sub> (<b>a</b>), average radius of gyration of said cluster, <span class="html-italic">R</span><sub>g</sub> (<b>b</b>), average number of close contacts between drug and polymer monomer particles per monomer, <span class="html-italic">N</span><sub>mon-links</sub>/<span class="html-italic">N</span><sub>mon</sub> (<b>c</b>), and average number of close contacts between drug and water particles per drug molecule, <span class="html-italic">N</span><sub>H2O-links</sub>/<span class="html-italic">N</span><sub>drug</sub> (<b>d</b>).</p>
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23 pages, 4448 KiB  
Article
Chromatographic Comparison of Commercially Available Columns for Liquid Chromatography in Polar Pesticide Detection and Quantification Using a Score-Based Methodology
by Emanuela Verdini, Tommaso Pacini, Serenella Orsini, Stefano Sdogati and Ivan Pecorelli
Foods 2024, 13(19), 3131; https://doi.org/10.3390/foods13193131 - 30 Sep 2024
Viewed by 425
Abstract
The detection and quantification of polar pesticides in liquid chromatography coupled with mass spectrometry present significant analytical challenges. This study compares the performance of three LC columns (Hypercarb™, Raptor Polar X™, and Anionic Polar Pesticide™) in separating and quantifying eleven polar pesticides in [...] Read more.
The detection and quantification of polar pesticides in liquid chromatography coupled with mass spectrometry present significant analytical challenges. This study compares the performance of three LC columns (Hypercarb™, Raptor Polar X™, and Anionic Polar Pesticide™) in separating and quantifying eleven polar pesticides in chicken eggs using a score-based methodology. Analytes include glyphosate, its metabolites, and other high-polarity pesticides like Ethephon, Glufosinate, and Fosetyl aluminum, included in the EU’s official control plan. Polar pesticides, characterized by high polarity and hydrophilicity, lead to analytical issues such as poor retention and unconventional peak shapes with traditional reversed-phase methods. Their weak interaction with hydrophobic stationary phases complicates separation, necessitating specific stationary phases to enhance retention and selectivity. This study evaluates these columns’ efficacy in complex matrices like chicken eggs and other food samples. Chromatographic separation was performed using a UPLC system coupled with a Q-TOF mass spectrometer; extraction and purification involved freeze-out, centrifugation, and filtration steps. The study highlights the critical role of column selection in achieving accurate and reliable separation and quantification of highly polar analytes in matrices of animal origin, offering in the meantime an easy-to-apply methodology of selection for the right determination of the best chromatographic column for different purposes. Full article
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<p>Chemical Structures of main polar pesticides; AMPA, N-Acetyl Glyphosate are metabolites of Glyphosate, N-Acetyl Glufosinate G and MPP are Glufosinate metabolites.</p>
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<p>Cyanuric acid (<b>top</b>) and N-Acetyl Glyphosate (<b>bottom</b>) peaks, the concentration of which is 0.005 mg/Kg, with an APP chromatographic column.</p>
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<p>From Top to the Bottom: Glyphosate peak on Hypercarb, Injection Number 1, 15, 35 and 50.</p>
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<p>From Top to the Bottom: Glyphosate Peak on Raptor Polar X, Injection Number 1, 15, 35, and 50.</p>
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<p>From Top to the Bottom: Glyphosate peak on APP, Injection Number 1, 15, 35 and 50.</p>
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<p>From Top to Bottom: Cyanuric Acid, Maleic Hydrazide, and N-Acetyl Glyphosate on Raptor Polar X at LOD.</p>
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<p>From top to bottom, Cyanuric Acid, Maleic Hydrazide, and N-Acetyl Glyphosate on the APP at LOD.</p>
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<p>Peaks of Etephon (<b>top</b>) and Fosetyl Al (<b>bottom</b>) on Hypercarb at the first (<b>left</b>) and 500th injection (<b>right</b>).</p>
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<p>Peaks of Etephon (<b>top</b>) and Fosetyl Al (<b>bottom</b>) on APP at the first (<b>left</b>) and 500th injection (<b>right</b>).</p>
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<p>Peaks of Etephon (<b>top</b>) and Fosetyl Al (<b>bottom</b>) on Raptor Polar X at the first (<b>left</b>) and 500th injection (<b>right</b>).</p>
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<p>LC-HRMS chromatograms of chicken egg samples spiked with 0.005 mg/kg of AMPA, Etephon, Fosetyl Al, Glyphosate, HEPA, Maleic Hydrazide, N-Acetyl Glyphosate and Cyanuric Acid with 0.001 mg/kg for Glufosinate, MPP e N-Acetyl Glyphosate with the three columns of the present study: Raptor polar X (30 × 2.1 mm, 2.7 µm); Hypercarb™ (100 × 2.1 mm; 5 µm); Anionic Polar Pesticides (APP) (100 × 2.1 mm; 5 µm).</p>
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15 pages, 8452 KiB  
Article
Cooling Rate and Compositional Effects on Microstructural Evolution and Mechanical Properties of (CoCrCuTi)100−xFex High-Entropy Alloys
by Brittney Terry and Reza Abbaschian
Entropy 2024, 26(10), 826; https://doi.org/10.3390/e26100826 - 29 Sep 2024
Viewed by 371
Abstract
This study investigates the impact of cooling rate and alloy composition on phase formations and properties of (CoCrCuTi)100−xFex (x = 0, 5, 10, 12.5, 15) high-entropy alloys (HEAs). Samples were synthesized using arc-melting and electromagnetic levitation, followed by quenching through [...] Read more.
This study investigates the impact of cooling rate and alloy composition on phase formations and properties of (CoCrCuTi)100−xFex (x = 0, 5, 10, 12.5, 15) high-entropy alloys (HEAs). Samples were synthesized using arc-melting and electromagnetic levitation, followed by quenching through the use of a Cu chill or V-shaped Cu mold. Cooling rates were evaluated by measuring dendrite arm spacings (DASs), employing the relation DAS = k ɛ−n, where constants k = 16 and n = ½. Without Fe addition, a microstructure consisting of BCC1 + BCC2 phases formed, along with an interdendritic (ID) FCC Cu-rich phase. However, with the addition of 5–10% Fe, a Cu-lean C14 Laves phase emerged, accompanied by a Cu-rich ID FCC phase. For cooling rates below 75 K/s, alloys containing 10% Fe exhibited liquid phase separation (LPS), characterized by globular Cu-rich structures within the Cu-lean liquid. In contrast, for the same composition, higher cooling rates of 400–700 K/s promoted a dendritic/interdendritic microstructure. Alloys with 12.5–15 at. % Fe displayed LPS irrespective of the cooling rate, although an increase in uniformity was noted at rates exceeding 700 K/s. Vickers hardness and fracture toughness generally increased with Fe content, with hardness ranging from 444 to 891 HV. The highest fracture toughness (5.5 ± 0.4 KIC) and hardness (891 ± 66 HV) were achieved in samples containing 15 at. % Fe, cooled at rates of 25–75 K/s. Full article
(This article belongs to the Special Issue Recent Advances in High Entropy Alloys)
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<p>Schematic of electromagnetic levitation processing, illustrating a magnetically levitated sample enclosed within a quartz tube.</p>
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<p>BSE images and graph of samples magnetically solidified. (<b>a</b>) Time vs. temperature graph. (<b>b</b>) Large, hexagonal dendrites shown for 10 at. % Fe, developed in the outer region of the sample at 1 K/s.</p>
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<p>BSE images of microstructural changes as the cooling rate increases from ~20–1000 K/s. (<b>a</b>–<b>c</b>) 0 at. % Fe, (<b>d</b>–<b>f</b>) 5 at. % Fe, and (<b>g</b>–<b>i</b>) 10 at. % Fe, each corresponding to the specified cooling rates. (<b>j</b>) Schematic of a cross sectioned arc-melted sample, along with corresponding cooling rates.</p>
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<p>Samples were cast onto a Cu plate while molten, forming three main regions of solidification. (<b>a</b>–<b>c</b>) 10 at. % Fe microstructure from the chill zone and the center. (<b>d</b>–<b>f</b>) 12.5 at. % Fe sample, showing evidence of LPS. (<b>g</b>–<b>i</b>) 15 at. % Fe sample, with large L2 globules. (<b>j</b>) Schematic of samples quenched on a Cu chill.</p>
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<p>BSEs of arc-melted sample microstructures. (<b>a</b>–<b>c</b>) Alloys containing 10 at. % Fe are shown. (<b>d</b>–<b>f</b>) Images of 12.5 at. % Fe with hexagonal dendrites. (<b>g</b>–<b>i</b>) Microstructure of 15 at. % Fe. (<b>j</b>) Schematic of V-shaped Cu mold with corresponding cooling rates.</p>
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<p>EDS imaging of the 12.5 at. % Fe sample. Samples were subjected to a cooling rate of approximately 25 K/s, is shown for specimens quenched into a V-shaped Cu mold. (<b>a</b>) Overall image, (<b>b</b>) distribution of titanium across the microstructure, (<b>c</b>) distribution of cobalt, (<b>d</b>) distribution of chromium, (<b>e</b>) distribution of copper, and (<b>f</b>) distribution of iron.</p>
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<p>Phase formation diagram of 10–15 at. % Fe samples when subjected to specific cooling rates.</p>
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<p>Optical imaging of Vickers hardness indentations: (<b>a</b>) Cu mold cast sample at 10 at. % Fe. (<b>b</b>) Cu mold cast sample at 15 at. % Fe. (<b>c</b>) DAS equation and graph. (<b>d</b>) Cu mold cast sample at 12.5 at. % Fe.</p>
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