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17 pages, 1389 KiB  
Article
Kojic Acid Gene Clusters and the Transcriptional Activation Mechanism of Aspergillus flavus KojR on Expression of Clustered Genes
by Perng-Kuang Chang, Leslie L. Scharfenstein, Noreen Mahoney and Qing Kong
J. Fungi 2023, 9(2), 259; https://doi.org/10.3390/jof9020259 - 15 Feb 2023
Cited by 6 | Viewed by 2372
Abstract
Kojic acid (KA) is a fungal metabolite and has a variety of applications in the cosmetics and food industries. Aspergillus oryzae is a well-known producer of KA, and its KA biosynthesis gene cluster has been identified. In this study, we showed that nearly [...] Read more.
Kojic acid (KA) is a fungal metabolite and has a variety of applications in the cosmetics and food industries. Aspergillus oryzae is a well-known producer of KA, and its KA biosynthesis gene cluster has been identified. In this study, we showed that nearly all section Flavi aspergilli except for A. avenaceus had complete KA gene clusters, and only one Penicillium species, P. nordicum, contained a partial KA gene cluster. Phylogenetic inference based on KA gene cluster sequences consistently grouped section Flavi aspergilli into clades as prior studies. The Zn(II)2Cys6 zinc cluster regulator KojR transcriptionally activated clustered genes of kojA and kojT in Aspergillus flavus. This was evidenced by the time-course expression of both genes in kojR-overexpressing strains whose kojR expression was driven by a heterologous Aspergillus nidulans gpdA promoter or a homologous A. flavus gpiA promoter. Using sequences from the kojA and kojT promoter regions of section Flavi aspergilli for motif analyses, we identified a consensus KojR-binding motif to be an 11-bp palindromic sequence of 5′-CGRCTWAGYCG-3′ (R = A/G, W = A/T, Y = C/T). A CRISPR/Cas9-mediated gene-targeting technique showed that the motif sequence, 5′-CGACTTTGCCG-3′, in the kojA promoter was critical for KA biosynthesis in A. flavus. Our findings may facilitate strain improvement and benefit future kojic acid production. Full article
(This article belongs to the Special Issue Genomics Analysis of Fungi)
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Figure 1

Figure 1
<p>Phylogenetic tree of twenty-four <span class="html-italic">Aspergillus</span> section <span class="html-italic">Flavi</span> species inferred from KA gene cluster sequences using NJ analysis. A total of 5776 conserved sites (i.e., concatenated sequences of total SNPs) from each species were used. Bootstrap values are shown at the nodes. The branch length scale is shown. Branch lengths represent genetic change; the longer the branch, the more divergence has occurred. The exact species name of ATCC12892, originally designated as <span class="html-italic">A. oryzae</span>, is not known.</p>
Full article ">Figure 2
<p>Determination of <span class="html-italic">kojR</span> copy numbers and relative expression levels of <span class="html-italic">kojR</span>, <span class="html-italic">kojA</span>, and <span class="html-italic">kojT</span> of <span class="html-italic">kojR</span>-overexpressing strains. (<b>A</b>) <span class="html-italic">kojR</span> copy numbers of overexpression strains whose <span class="html-italic">kojR</span> expression was driven by the <span class="html-italic">A. nidulans gpdA</span> promoter or the <span class="html-italic">A. flavus gpiA</span> promoter. The copy numbers of <span class="html-italic">kojA</span> and <span class="html-italic">kojT</span> of the control and overexpression strains were used as single-gene-copy checks. (<b>B</b>) Relative expression levels of <span class="html-italic">kojR</span> to those of the control strain at 48 h and 72 h. (<b>C</b>) Relative expression levels of <span class="html-italic">kojA</span> and <span class="html-italic">kojT</span> to those of the ∆kojR strain, which presumably were the basal expression levels at 48 h and 72 h.</p>
Full article ">Figure 2 Cont.
<p>Determination of <span class="html-italic">kojR</span> copy numbers and relative expression levels of <span class="html-italic">kojR</span>, <span class="html-italic">kojA</span>, and <span class="html-italic">kojT</span> of <span class="html-italic">kojR</span>-overexpressing strains. (<b>A</b>) <span class="html-italic">kojR</span> copy numbers of overexpression strains whose <span class="html-italic">kojR</span> expression was driven by the <span class="html-italic">A. nidulans gpdA</span> promoter or the <span class="html-italic">A. flavus gpiA</span> promoter. The copy numbers of <span class="html-italic">kojA</span> and <span class="html-italic">kojT</span> of the control and overexpression strains were used as single-gene-copy checks. (<b>B</b>) Relative expression levels of <span class="html-italic">kojR</span> to those of the control strain at 48 h and 72 h. (<b>C</b>) Relative expression levels of <span class="html-italic">kojA</span> and <span class="html-italic">kojT</span> to those of the ∆kojR strain, which presumably were the basal expression levels at 48 h and 72 h.</p>
Full article ">Figure 3
<p>Putative KojR-binding motif identified by MEME using <span class="html-italic">kojA</span> and <span class="html-italic">kojT</span> promoter sequences of section <span class="html-italic">Flavi</span> aspergilli. The logo is the downloaded EPS (for publication) version from the MEME site, whose appearance is somewhat different from the PNG (for web) version in that all positions have the same baseline. The relative height indicates how certain it is to observe a particular nucleotide at a particular position, and high heights indicate high conservation/low uncertainty. In the MEME analysis, the maximum motif width was arbitrarily set at eleven and searched for palindromic motifs. Promoter sequences listed in <a href="#app1-jof-09-00259" class="html-app">Table S2</a> are the input sequences.</p>
Full article ">Figure 4
<p>Identification of KojR-binding site in <span class="html-italic">A. flavus kojA</span> promoter. (<b>A</b>) Six indel defects in the motif of <span class="html-italic">kojA</span>, 5′- CGACTTTGCCG-3′, rendered the transformants unable to produce KA. (<b>B</b>) Six indel defects disrupted the identified motif of <span class="html-italic">kojT</span>, 5′-CGGCTAAGTCG-3′. However, they did not affect KA production of the transformants. The recipient strain used for the CRISPR/Cas9 work is wild-type <span class="html-italic">A. flavus</span> CA14. Wt represents wild-type sequences. Yellow-highlighted sequences are the target sites of the CRISPR/Cas9 complexes. Red trinucleotides CCG and CGG are protospacer adjacent motifs (PAM) that follow the regions targeted for cleavage by the Cas9 nuclease. Dash lines are deleted sequences. Gray-highlighted sequences are additional nucleotides inserted into respective motifs. The symbol ∆403 indicates a large deletion extending to the <span class="html-italic">kojT</span>-coding sequence (see <a href="#app1-jof-09-00259" class="html-app">Figure S3</a>). The photos above the sequences are colony morphologies of six mutants on KAM agar plates, which are shown alternatively on their front and reverse sides. Colonies were grown at 30 °C for five days in the dark. Orange-red plates are KA-producing colonies. (<b>C</b>) Graphic representation showing the location of the functional KojR-binding site in the <span class="html-italic">kojA</span> and <span class="html-italic">kojR</span> intergenic regions inferred from the present study. The site is 266 nucleotides from the translation start codon of <span class="html-italic">kojA</span> and 466 nucleotides from the start codon of <span class="html-italic">kojR</span>.</p>
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12 pages, 2638 KiB  
Article
Investigation of Gentamicin Release from Polydopamine Nanoparticles
by Rahila Batul, Abdul Khaliq, Ahmed Alafnan, Mrinal Bhave and Aimin Yu
Appl. Sci. 2022, 12(13), 6319; https://doi.org/10.3390/app12136319 - 21 Jun 2022
Cited by 6 | Viewed by 2142
Abstract
Polydopamine (PDA), being highly reactive in nature, has acquired great attention in multi-disciplinary fields. Owing to its fascinating properties, including its biocompatible, non-toxic and readily bio-degradative nature, we investigated the drug loading and release behavior, using an aminoglycoside antibiotic gentamicin (G) as a [...] Read more.
Polydopamine (PDA), being highly reactive in nature, has acquired great attention in multi-disciplinary fields. Owing to its fascinating properties, including its biocompatible, non-toxic and readily bio-degradative nature, we investigated the drug loading and release behavior, using an aminoglycoside antibiotic gentamicin (G) as a model drug. The gentamicin was loaded into the PDA nanoparticles (NPs) via an in situ polymerization method. The release kinetics of the gentamicin was then studied in pH 3, 5 and 7.4. Two batches with varied gentamicin loadings, G-PDA NPs 1:1 (with approx. 84.1% loaded gentamicin) and G-PDA NPs 0.6:1 (with approx. 72.7% loaded gentamicin), were studied. The drug release data were analyzed by LC–MS. The PDA showed good stability in terms of gentamicin release at alkaline pH over a period of seven days. The negative surface charge of PDA at pH 7.4 makes a strong bond with gentamicin, hence preventing its release from the PDA NPs. However, at pH 5 and 3, the amine groups of PDA are more prone towards protonation, making PDA positively charged, hence the repulsive forces caused the gentamicin to detach and release from the G-PDA NPs. Consequently, approx. 40% and 55% drug release were observed at pH 5 and 3, respectively, from the G-PDA NPs 1:1. However, the drug released from G-PDA NPs 0.6:1 was found to be one half as compared to the G-PDA NPs 1:1, which is obvious to the concentration gradient. These findings suggested that the in situ loading method for gentamicin could provide drug release over a period of seven days, hence defending the drug’s efficacy and safety challenges. Furthermore, two kinetic models, namely the Ritger–Peppas and Higuchi models, were implemented to determine the drug release kinetics. Curve fitting analysis supported our findings for the drug release kinetics which are followed by PDA structural changes in response to pH. Full article
(This article belongs to the Section Nanotechnology and Applied Nanosciences)
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Figure 1

Figure 1
<p>(<b>A</b>–<b>C</b>) are representing non-cumulative gentamicin release at pH 7.4, 5 and 3, respectively; and (<b>D</b>) is representing cumulative percent release of gentamicin at all pH conditions from G-PDA 1:1. Data were mean ± SD (<span class="html-italic">n</span> = 3).</p>
Full article ">Figure 2
<p>(<b>A</b>–<b>C</b>) are representing non-cumulative gentamicin release at pH 7.4, 5 and 3, respectively; and (<b>D</b>) is representing cumulative percent release of gentamicin at all pH conditions from G-PDA 0.6:1. Data were mean ± SD (<span class="html-italic">n</span> = 3).</p>
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<p>Comparison between % drug release from G-PDA 0.6:1 and G-PDA 1:1 at various pH conditions.</p>
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<p>Fitting of cumulative % drug release data to (<b>A</b>) Ritger–Peppas and (<b>B</b>) Higuchi model for pH 7.4.</p>
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<p>Fitting of cumulative % drug release data to (<b>A</b>) Ritger–Peppas and (<b>B</b>) Higuchi model for pH 5.</p>
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<p>Fitting of cumulative % drug release data to (<b>A</b>) Ritger–Peppas and (<b>B</b>) Higuchi model for pH 3.</p>
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16 pages, 3422 KiB  
Article
Controlled Transcription of Regulator Gene carS by Tet-on or by a Strong Promoter Confirms Its Role as a Repressor of Carotenoid Biosynthesis in Fusarium fujikuroi
by Julia Marente, Javier Avalos and M. Carmen Limón
Microorganisms 2021, 9(1), 71; https://doi.org/10.3390/microorganisms9010071 - 29 Dec 2020
Cited by 5 | Viewed by 2898
Abstract
Carotenoid biosynthesis is a frequent trait in fungi. In the ascomycete Fusarium fujikuroi, the synthesis of the carboxylic xanthophyll neurosporaxanthin (NX) is stimulated by light. However, the mutants of the carS gene, encoding a protein of the RING finger family, accumulate large [...] Read more.
Carotenoid biosynthesis is a frequent trait in fungi. In the ascomycete Fusarium fujikuroi, the synthesis of the carboxylic xanthophyll neurosporaxanthin (NX) is stimulated by light. However, the mutants of the carS gene, encoding a protein of the RING finger family, accumulate large NX amounts regardless of illumination, indicating the role of CarS as a negative regulator. To confirm CarS function, we used the Tet-on system to control carS expression in this fungus. The system was first set up with a reporter mluc gene, which showed a positive correlation between the inducer doxycycline and luminescence. Once the system was improved, the carS gene was expressed using Tet-on in the wild strain and in a carS mutant. In both cases, increased carS transcription provoked a downregulation of the structural genes of the pathway and albino phenotypes even under light. Similarly, when the carS gene was constitutively overexpressed under the control of a gpdA promoter, total downregulation of the NX pathway was observed. The results confirmed the role of CarS as a repressor of carotenogenesis in F. fujikuroi and revealed that its expression must be regulated in the wild strain to allow appropriate NX biosynthesis in response to illumination. Full article
(This article belongs to the Special Issue Microbial Pigments)
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Graphical abstract

Graphical abstract
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<p>Model of the Tet-on mechanism to control the expression of <span class="html-italic">mluc</span>. Plasmid pVG3.1 contains the gene for the tetracycline-dependent transactivator <span class="html-italic">rtTA2<sup>S</sup>-M2</span> under control of the constitutive promoter of the glyceraldehyde-3-phosphate dehydrogenase gene from <span class="html-italic">Aspergillus nidulans</span> (P<span class="html-italic">gpdA).</span> In the presence of Dox, rtTA2<sup>S</sup>-M2 binds to the operator sequence <span class="html-italic">tetO7</span>, activates the fungal minimal promoter of P<span class="html-italic">gpdA</span> (Pmin), and consequently induces <span class="html-italic">mluc</span> gene expression. This gene encodes the enzyme luciferase that converts luciferin into oxyluciferin and emits light.</p>
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<p>Luminescence emission of TET<span class="html-italic">luc</span> transformants induced with doxycycline (Dox) and compared to the wild strain: (<b>A</b>) The TETluc transformants (SG253 and SG255) and the wild strain (WT) were grown in DGpep medium for 16 h in 96-well plates; then, 0.2 mM luciferin and 20 μg/mL of Dox were added to the wells and incubated in the dark at 30 °C for the time indicated. Data are average and standard deviation for two independent experiments. As a negative control, strains were grown without Dox. (<b>B</b>) Luminescence emitted by the TET<span class="html-italic">luc</span> transformant SG255 in DGpep medium in 96-well plates. Dox was added at desired final concentrations (0, 2.5, 5, 10, and 20 μg/mL) to mycelia previously grown for 18 h. (<b>C</b>) Growth of SG255 in the 96-well plates described in panel B, measured by their absorbance at 600 nm. Data are average and standard deviations for three independent experiments.</p>
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<p>Control of expression of the <span class="html-italic">carS</span> gene using the Tet-on system in <span class="html-italic">F. fujikuroi</span>: (<b>A</b>) Phenotypic characterization of TET<span class="html-italic">carS</span> transformant (SG260 and SG262) and parental strains, wild type (WT) and SG39 (<span class="html-italic">carS</span> mutant), grown in DG agar medium (control) and in DG with 20 μg/mL Dox (20 Dox) at 30 °C for five days in the dark. (<b>B</b>) Transcripts levels of the <span class="html-italic">carS</span> gene in the strains grown in minimal DG medium for 18 h and induced with 20 μg/mL of Dox (20 Dox) or grown without Dox (control) and then incubated for up to three days in darkness. Values in the left graph refer to those of WT without Dox, and values in the right graph refer to those of SG39 without Dox. The qRT-PCR data are the average of two independent experiments and bars represent the standard deviation. *-indicates <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Repression of the carotenoid biosynthesis pathway by <span class="html-italic">carS</span> overexpression in the <span class="html-italic">carS</span> mutant: (<b>A</b>) Transcripts levels for the <span class="html-italic">carB</span> and <span class="html-italic">carRA</span> genes in the TET<span class="html-italic">carS</span> transformant (SG262) and the <span class="html-italic">carS</span> mutant (SG39). Cultures of SG39 and SG262 grown for 18 h were induced with 20 μg/mL of Dox and then incubated for up to three days in darkness. The noninduced controls were grown for three days without Dox. Quantitative RT-PCR values represent average and standard deviations of two independent experiments. (<b>B</b>) Carotenoid content from the same strains grown on DG agar medium with 20 μg/mL of Dox, and without Dox as control, for seven days in darkness. Mycelial samples were taken from three independent experiments. ** <span class="html-italic">p</span> &lt; 0.01; **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Growth and pigmentation of strains induced with a range of Dox concentrations. TET<span class="html-italic">carS</span> transformants (SG260 and SG262), the wild strain (WT) and <span class="html-italic">carS</span> mutant (SG39) were grown on minimal DG agar medium with different Dox concentrations (0, 2.5, 5, 10, and 20 μg/mL) at 30 °C, for five days under light.</p>
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<p>Effect of optimized Dox concentration on gene expression: (<b>A</b>) Transcripts levels for the <span class="html-italic">carS</span> gene in the wild strain (WT), <span class="html-italic">carS</span> mutant (SG39), and TET<span class="html-italic">carS</span> transformant (SG262). (<b>B</b>) Transcript levels for the <span class="html-italic">mluc</span> gene in TET<span class="html-italic">luc</span> transformants SG253 and SG255. Values were normalized to those of SG253 in the absence of Dox. (<b>C</b>) Transcript levels for the <span class="html-italic">carRA</span> gene in WT, SG39, and SG262. (<b>D</b>) Transcript levels for the <span class="html-italic">carB</span> gene in WT, SG39 and SG262. The strains were grown for two days in DG medium in darkness, then induced with 10 μg/mL Dox (10 Dox) for 24 h; noninduced cultures (control) were incubated for the same time. Data of qRT-PCR are the average and standard deviation of three independent experiments. Values were normalized to those of the noninduced wild strain, except for the <span class="html-italic">mlu</span>c gene. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 7
<p>Effect of constitutive expression of the <span class="html-italic">carS</span> gene in <span class="html-italic">F. fujikuroi:</span> (<b>A</b>) Phenotypes of two OE<span class="html-italic">carS</span> transformants (SG263 and SG264) and the wild strain (WT) grown on DG agar medium for five days at 30 °C in the dark or under light. (<b>B</b>) Carotenoid content in mycelia of WT and OE<span class="html-italic">carS</span> transformants grown for seven days in darkness or under light. Data are the average and standard deviation from three independent experiments. (<b>C</b>–<b>E</b>) Transcript levels of <span class="html-italic">carS</span>, <span class="html-italic">carRA</span>, and <span class="html-italic">carB</span> in WT and OE<span class="html-italic">carS</span> transformants; RNA was isolated from strains grown in darkness for three days and exposed to light for one hour or kept for this time in the dark. Data of qRT-PCR are the average and mean error of five independent experiments. Values were normalized to the WT samples in the dark. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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22 pages, 3064 KiB  
Article
Computer-Aided Engineering Environment for Designing Tailored Forming Components
by Tim Brockmöller, Renan Siqueira, Paul C. Gembarski, Iryna Mozgova and Roland Lachmayer
Metals 2020, 10(12), 1589; https://doi.org/10.3390/met10121589 - 27 Nov 2020
Cited by 13 | Viewed by 3121
Abstract
The use of multi-material forming components makes it possible to produce components adapted to the respective requirements, which have advantages over mono-material components. The necessary consideration of an additional material increases the possible degrees of freedom in product and manufacturing process development. As [...] Read more.
The use of multi-material forming components makes it possible to produce components adapted to the respective requirements, which have advantages over mono-material components. The necessary consideration of an additional material increases the possible degrees of freedom in product and manufacturing process development. As a result, development becomes more complex and special expert knowledge is required. To counteract this, computer-aided engineering environments with knowledge-based tools are increasingly used. This article describes a computer-aided engineering environment (CAEE) that can be used to design hybrid forming components that are produced by tailored forming, a process chain developed in the Collaborative Research Center (CRC) 1153. The CAEE consists of a knowledge base, in which the knowledge necessary for the design of tailored forming parts, including manufacturer restrictions, is stored and made available. For the generation of rough and detailed design and for elaboration the following methods are used. The topology optimization method, Interfacial Zone Evolutionary Optimization (IZEO), which determines the material distribution. The design of optimized joining zone geometries, by robust design. The elaboration of the components by means of highly flexible computer-aided design (CAD) models, which are built according to the generative parametric design approach (GPDA). Full article
(This article belongs to the Special Issue Hybrid Bulk Metal Components)
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Figure 1

Figure 1
<p>General tailored forming process chain, according to [<a href="#B2-metals-10-01589" class="html-bibr">2</a>].</p>
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<p>Process chain for the production of a hybrid shaft by tailored forming [<a href="#B11-metals-10-01589" class="html-bibr">11</a>].</p>
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<p>Structure of the computer-aided engineering environment (CAEE) for tailored forming.</p>
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<p>Model representation of the interfacial evolutionary process [<a href="#B81-metals-10-01589" class="html-bibr">81</a>].</p>
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<p>Relationship between geometric constraints and manufacturing techniques [<a href="#B79-metals-10-01589" class="html-bibr">79</a>].</p>
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<p>Generative parametric design approach (GPDA) model of a connection rod: (<b>a</b>) skeleton and interfaces, (<b>b</b>) computer-aided design (CAD) model, according to [<a href="#B84-metals-10-01589" class="html-bibr">84</a>].</p>
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<p>Schematic structure of the GPDA engineering Environment [<a href="#B83-metals-10-01589" class="html-bibr">83</a>].</p>
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<p>Domain with load and boundary conditions of the shaft for the 3D optimization.</p>
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<p>Rotational symmetry applied to: (<b>a</b>) joining zone only; (<b>b</b>) component body only; (<b>c</b>) both joining zone and component body.</p>
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<p>Rotational symmetric components with joining zone constrained by: (<b>a</b>) radial growth only; (<b>b</b>) radial and unidirectional growth.</p>
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<p>Optimization evolution for the tailored forming shaft model with IZEO.</p>
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<p>Plot of every parametric simulation over safety factor and weight, where a Pareto front is observed.</p>
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<p>Shaft design for same requirements, where a reduction of 11% in weight is seen for the multi-material shaft (<b>a</b>) in comparison to the mono-material one (<b>b</b>).</p>
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<p>Structure of design catalogs.</p>
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<p>Skeleton (<b>a</b>) and CAD model (<b>b</b>) of tailored foming shafts.</p>
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<p>Parameters for a relief groove (type F) that extends over two design elements (DE1 and DE2).</p>
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<p>(<b>a</b>) Joining zone position and (<b>b</b>) resulting v. Mises stresses (max. <math display="inline"><semantics> <mrow> <mn>278.9</mn> <mfrac> <mi>N</mi> <mrow> <mi>m</mi> <msup> <mi>m</mi> <mn>2</mn> </msup> </mrow> </mfrac> </mrow> </semantics></math>) at <math display="inline"><semantics> <mrow> <mi>F</mi> <mo>=</mo> <mn>5.5</mn> </mrow> </semantics></math> kN and <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>40</mn> </mrow> </semantics></math> Nm.</p>
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<p>Exceeded yield strength (max. <math display="inline"><semantics> <mrow> <mn>363.07</mn> <mfrac> <mi>N</mi> <mrow> <mi>m</mi> <msup> <mi>m</mi> <mn>2</mn> </msup> </mrow> </mfrac> </mrow> </semantics></math>) at a joining zone position of <math display="inline"><semantics> <mrow> <mi>P</mi> <mo>=</mo> <mn>73</mn> </mrow> </semantics></math> mm at <math display="inline"><semantics> <mrow> <mi>F</mi> <mo>=</mo> <mn>8</mn> </mrow> </semantics></math> kN and <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>40</mn> </mrow> </semantics></math> Nm.</p>
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<p>(<b>a</b>) Joining zone position (<b>b</b>) and resulting stresses (max. <math display="inline"><semantics> <mrow> <mn>375.39</mn> <mfrac> <mi>N</mi> <mrow> <mi>m</mi> <msup> <mi>m</mi> <mn>2</mn> </msup> </mrow> </mfrac> </mrow> </semantics></math>) at <math display="inline"><semantics> <mrow> <mi>F</mi> <mo>=</mo> <mn>8</mn> </mrow> </semantics></math> kN and <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>40</mn> </mrow> </semantics></math> Nm.</p>
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<p>Rocker arm (<b>left</b>) and derived tailored forming component variants in IZEO (<b>center</b>) and CAD (<b>right</b>).</p>
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13 pages, 5233 KiB  
Article
Polydopamine Nanosphere with In-Situ Loaded Gentamicin and Its Antimicrobial Activity
by Rahila Batul, Mrinal Bhave, Peter J. Mahon and Aimin Yu
Molecules 2020, 25(9), 2090; https://doi.org/10.3390/molecules25092090 - 30 Apr 2020
Cited by 88 | Viewed by 6037
Abstract
The mussel inspired polydopamine has acquired great relevance in the field of nanomedicines, owing to its incredible physicochemical properties. Polydopamine nanoparticles (PDA NPs) due to their low cytotoxicity, high biocompatibility and ready biodegradation have already been widely investigated in various drug delivery, chemotherapeutic, [...] Read more.
The mussel inspired polydopamine has acquired great relevance in the field of nanomedicines, owing to its incredible physicochemical properties. Polydopamine nanoparticles (PDA NPs) due to their low cytotoxicity, high biocompatibility and ready biodegradation have already been widely investigated in various drug delivery, chemotherapeutic, and diagnostic applications. In addition, owing to its highly reactive nature, it possesses a very high capability for loading drugs and chemotherapeutics. Therefore, the loading efficiency of PDA NPs for an antibiotic i.e., gentamicin (G) has been investigated in this work. For this purpose, an in-situ polymerization method was studied to load the drug into PDA NPs using variable drug: monomer ratios. Scanning electron microscope (SEM), Fourier-transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS) confirmed the successful loading of drug within PDA NPs, mainly via hydrogen bonding between the amine groups of gentamicin and the hydroxyl groups of PDA. The loading amount was quantified by liquid chromatography–mass spectrometry (LC-MS) and the highest percentage loading capacity was achieved for G-PDA prepared with drug to monomer ratio of 1:1. Moreover, the gentamicin loaded PDA NPs were tested in a preliminary antibacterial evaluation using the broth microdilution method against both Gram-(+) Staphylococcus aureus and Gram-(−) Pseudomonas aeruginosa microorganisms. The highest loaded G-PDA sample exhibited the lowest minimum inhibitory concentration and minimum bactericidal concentration values. The developed gentamicin loaded PDA is very promising for long term drug release and treating various microbial infections. Full article
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<p>(<b>a</b>) Fourier-transform infrared spectroscopy (FTIR), and (<b>b</b>) X-ray photoelectron spectroscopy (XPS) survey spectra of polydopamine (PDA), gentamicin sulphate, and gentamicin-polydopamine nanoparticles (G-PDA NPs).</p>
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<p>High resolution XPS spectra (<b>a</b>) C1s, (<b>b</b>) N1s; and (<b>c</b>) O1s spectra of PDA NPs; and (<b>d</b>) C1s, (<b>e</b>) N1s; and (<b>f</b>) O1s of G-PDA NPs.</p>
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<p>Schematic diagram showing proposed mechanism of hydrogen bonding between hydroxyl and amine moieties of PDA and gentamicin, respectively.</p>
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<p>Scanning electron microscope (SEM) images of various batches prepared by changing the concentration of gentamicin; (<b>a</b>)PDA NPs; (<b>b</b>) G-PDA NPs 0.4:1; (<b>c</b>) G-PDA NPs 0.6:1; (<b>d</b>) G-PDA NPs 0.8:1; (<b>e</b>) G-PDA NPs 1:1. The scale bar is 1 µm.</p>
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<p>(<b>a</b>) Liquid chromatography–mass spectrometry (LC-MS) calibration curve for various gentamicin concentrations. (<b>b</b>) Mass percentage of gentamicin loading into PDA NPs with variable gentamicin to dopamine ratios.</p>
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<p>Evidence of antimicrobial activity of all batches of G-PDA NPs viz; 0.4:1, 0.6:1, 0.8:1 and 1:1 represented by figure (<b>a</b>–<b>d</b>), respectively against <span class="html-italic">Staphylococcus aureus</span> and (<b>e</b>–<b>h</b>) respectively against <span class="html-italic">Pseudomonas aeruginosa</span>. The petri dishes with no bacterial colonies representing the minimum bactericidal concentration (MBC) values for each G-PDA NPs batch.</p>
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12 pages, 1762 KiB  
Article
Performance Evaluation of Asphalt Rubber Mixture with Additives
by Xianpeng Cheng, Yamin Liu, Wanyan Ren and Ke Huang
Materials 2019, 12(8), 1200; https://doi.org/10.3390/ma12081200 - 12 Apr 2019
Cited by 11 | Viewed by 3466
Abstract
Crumb rubber, as a recycled material used in asphalt mixture, has gained more attention in recent years due to environmental benefits and the advantages of its pavement, such as excellent resistance to cracking, improved durability, less road maintenance, lower road noise, etc. However, [...] Read more.
Crumb rubber, as a recycled material used in asphalt mixture, has gained more attention in recent years due to environmental benefits and the advantages of its pavement, such as excellent resistance to cracking, improved durability, less road maintenance, lower road noise, etc. However, the high-temperature performance of mixture with crumb rubber does not perform well. In order to improve the performance, this paper examined the effect of additives on the laboratory performance of asphalt rubber Stone Matrix Asphalt (AR-SMA) with additives. Three groups of AR-SMA: no additives, Styrene–Butadiene–Styrene (SBS) and Granular Polymer Durable additive (GPDa) were included, with no additives as a control group. Each group was investigated at three asphalt rubber content (ARC): 6.4%, 6.9%, 7.4% with regard to high-temperature and fatigue properties. The results show that with increasing ARC, the high-temperature performance of mixture without additive decreases, and the high-temperature performance increases first and then decreases for SBS and GPDa. Moreover, the rutting resistance of AR-SMA with GPDa at 6.9% ARC performs best. Under the condition of mixtures with appropriate ARC, AR-SMA with GPDa has higher fatigue life and sensitivity to fatigue cracking than the control group. Simultaneously, the fatigue performance of AR-SMA with GPDa is not as significant as that without additive with increasing ARC. In a word, GPDa is a good choice to improve the performance of AR-SMA. However, it should be noted that optimal asphalt content of AR-SMA mixtures with GPDa is higher than that of traditional mixtures. Full article
(This article belongs to the Special Issue Sustainability in Construction and Building Materials)
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<p>Additives: (<b>a</b>) Granular Polymer Durable additive (GPDa); (<b>b</b>) Styrene–Butadiene–Styrene (SBS).</p>
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<p>Dynamic stability of mixtures with different asphalt rubber contents (ARCs) and different additives. GPDa: Granular Polymer Durable additive; SBS: Styrene–Butadiene–Styrene.</p>
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<p>Curves for mixtures at different asphalt rubber contents (ARCs): (<b>a</b>) ARC of 6.4%; (<b>b</b>) ARC of 6.9%; (<b>c</b>) ARC of 7.4%. GPDa: Granular Polymer Durable additive.</p>
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<p>Curves for mixtures with different additives: (<b>a</b>) mixtures with no additives; (<b>b</b>) mixtures with Granular Polymer Durable additive (GPDa).</p>
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15 pages, 2045 KiB  
Article
Self-Tuning Threshold Method for Real-Time Gait Phase Detection Based on Ground Contact Forces Using FSRs
by Jing Tang, Jianbin Zheng, Yang Wang, Lie Yu, Enqi Zhan and Qiuzhi Song
Sensors 2018, 18(2), 481; https://doi.org/10.3390/s18020481 - 6 Feb 2018
Cited by 15 | Viewed by 4650
Abstract
This paper presents a novel methodology for detecting the gait phase of human walking on level ground. The previous threshold method (TM) sets a threshold to divide the ground contact forces (GCFs) into on-ground and off-ground states. However, the previous methods for gait [...] Read more.
This paper presents a novel methodology for detecting the gait phase of human walking on level ground. The previous threshold method (TM) sets a threshold to divide the ground contact forces (GCFs) into on-ground and off-ground states. However, the previous methods for gait phase detection demonstrate no adaptability to different people and different walking speeds. Therefore, this paper presents a self-tuning triple threshold algorithm (STTTA) that calculates adjustable thresholds to adapt to human walking. Two force sensitive resistors (FSRs) were placed on the ball and heel to measure GCFs. Three thresholds (i.e., high-threshold, middle-threshold andlow-threshold) were used to search out the maximum and minimum GCFs for the self-adjustments of thresholds. The high-threshold was the main threshold used to divide the GCFs into on-ground and off-ground statuses. Then, the gait phases were obtained through the gait phase detection algorithm (GPDA), which provides the rules that determine calculations for STTTA. Finally, the STTTA reliability is determined by comparing the results between STTTA and Mariani method referenced as the timing analysis module (TAM) and Lopez–Meyer methods. Experimental results show that the proposed method can be used to detect gait phases in real time and obtain high reliability when compared with the previous methods in the literature. In addition, the proposed method exhibits strong adaptability to different wearers walking at different walking speeds. Full article
(This article belongs to the Special Issue Sensors for Gait, Posture, and Health Monitoring)
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<p>FSRs placed inside one shoe with one in the ball and the other in the heel. A lid is made to enlarge the press area.</p>
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<p>Three thresholds used for the GCFs processing.</p>
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<p>The reliabilities of the proposed STTTA in various values of <span class="html-italic">β</span> and <span class="html-italic">γ</span>.</p>
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<p>(<b>a</b>) the GCFs of heel and ball measured by FSRs; (<b>b</b>) three self-tuning thresholds for the processing of GCF from the ball; (<b>c</b>) three self-tuning threshold for the processing of GCF from the heel; (<b>d</b>) the result of gait phase detection through GPDA; (<b>e</b>) thresholds calculated for the ball by four kinds of methods; and (<b>f</b>) thresholds calculated for the heel by four kinds of methods.</p>
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<p>(<b>a</b>) the GCFs of heel and ball measured by FSRs; (<b>b</b>) three self-tuning thresholds for the processing of GCF from the ball; (<b>c</b>) three self-tuning threshold for the processing of GCF from the heel; (<b>d</b>) the result of gait phase detection through GPDA; (<b>e</b>) thresholds calculated for the ball by four kinds of methods; and (<b>f</b>) thresholds calculated for the heel by four kinds of methods.</p>
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<p>(<b>a</b>) the GCFs of heel and ball measured by FSRs; (<b>b</b>) three self-tuning thresholds for the processing of GCF from the ball; (<b>c</b>) three self-tuning threshold for the processing of GCF from the heel; (<b>d</b>) the result of gait phase detection through GPDA; (<b>e</b>) thresholds calculated for the ball by four kinds of methods; and (<b>f</b>) thresholds calculated for the heel by four kinds of methods.</p>
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<p>Reliabilities of the Mariani and STTTA method for one male subject at five walking speeds: (<b>a</b>) TAM method as reference method; (<b>b</b>) Lopez–Meyer method as reference method. Reliabilities of the Mariani and STTTA method for one female subject at five walking speeds; (<b>c</b>) TAM method as reference method; (<b>d</b>) Lopez–Meyer method as reference method.</p>
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<p>Reliabilities of the Mariani and STTTA method for one male subject at five walking speeds: (<b>a</b>) TAM method as reference method; (<b>b</b>) Lopez–Meyer method as reference method. Reliabilities of the Mariani and STTTA method for one female subject at five walking speeds; (<b>c</b>) TAM method as reference method; (<b>d</b>) Lopez–Meyer method as reference method.</p>
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<p>Reliabilities of the Mariani and STTTA method for one male subject at five walking speeds: (<b>a</b>) TAM method as reference method; (<b>b</b>) Lopez–Meyer method as reference method. Reliabilities of the Mariani and STTTA method for one female subject at five walking speeds; (<b>c</b>) TAM method as reference method; (<b>d</b>) Lopez–Meyer method as reference method.</p>
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<p>(<b>a</b>) the description of using one threshold for threshold adjustment; (<b>b</b>) demonstration of threshold adjustment using one threshold and analysis of twice threshold computations.</p>
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