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15 pages, 7825 KiB  
Article
Batch-to-Batch Variation and Patient Heterogeneity in Thymoglobulin Binding and Specificity: One Size Does Not Fit All
by Nicoline H. M. den Hollander, Diahann T. S. L. Jansen and Bart O. Roep
J. Clin. Med. 2025, 14(2), 422; https://doi.org/10.3390/jcm14020422 - 10 Jan 2025
Viewed by 262
Abstract
Background: Thymoglobulin is used to prevent allograft rejection and is being explored at low doses as intervention immunotherapy in type 1 diabetes. Thymoglobulin consists of a diverse pool of rabbit antibodies directed against many different targets on human thymocytes that can also be [...] Read more.
Background: Thymoglobulin is used to prevent allograft rejection and is being explored at low doses as intervention immunotherapy in type 1 diabetes. Thymoglobulin consists of a diverse pool of rabbit antibodies directed against many different targets on human thymocytes that can also be expressed by other leukocytes. Since Thymoglobulin is generated by injecting rabbits with human thymocytes, this conceivably leads to differences between Thymoglobulin batches. Methods: We compared different batches for antibody composition and variation between individuals in binding to PBMC and T cell subsets, and induction of cytokines. Four different batches of Thymoglobulin were directly conjugated with Alexa-Fluor 647. Blood was collected from five healthy donors, and PBMCs were isolated and stained with Thymoglobulin followed or preceded by a panel of fluorescent antibodies to identify PBMC and T cell subsets. In addition, whole blood was incubated with unlabeled Thymoglobulin to measure cytokine induction. Results: Cluster analysis of flow cytometry data shows that Thymoglobulin bound to all PBMC subpopulations including regulatory T cells. However, Thymoglobulin binding was highly variable between donors and to a lesser extent between batches. Cytokines related to cytokine release syndrome were highly, but variably, increased by all Thymoglobulin batches, with strong differences between donors and moderate differences between batches. Discussion: The variation in Thymoglobulin binding and action between donors regarding PBMC recognition and cytokine response may underlie the different clinical responses to Thymoglobulin therapy and require personalized dose adjustment to maximize efficacy and minimize adverse side effects. Full article
(This article belongs to the Section Immunology)
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<p>Comparison of Thymoglobulin binding to PBMC and T cell subsets between different Thymoglobulin batches and donors. Cluster analysis of flow cytometry staining with PBMC markers (<b>A</b>) and T cell markers (<b>B</b>). Mean fluorescent intensity (MFI) of Thymoglobulin per cell is shown for each donor and batch (one dot = one cell). The color range represents Thymoglobulin binding to that cell (red = more Thymoglobulin bound, blue = less Thymoglobulin bound) and the color range scale is adjusted for the fluorochrome-to-Thymoglobulin conjugation efficiency of each batch. The subsets of each panel (right map) are contoured to identify which subsets are more or less bound per batch and donor. (Mono = monocyte, B = B cell, NK = natural killer cell, CD4 = CD4<sup>+</sup> T cell, CD8 = CD8<sup>+</sup> T cell, Tem = effector memory, Tcm = central memory, Temra = exhausted memory, Teff = effector, Treg = regulatory T cell, m = memory, n = naive.)</p>
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<p>Differences in Thymoglobulin binding to PBMC and T cell subsets between Thymoglobulin batches and donors. SPADE cluster analysis of flow cytometry staining shows six clusters (dots) based on PBMC marker expression (<b>A</b>) and 22 clusters based on T cell marker expression (<b>B</b>). The MFI (mean fluorescent intensity) of Thymoglobulin is shown for each donor and batch. The size of the dot represents the number of cells per cluster. The color represents the mean binding of Thymoglobulin to all cells in that cluster and ranges from blue (less Thymoglobulin bound) to red (more Thymoglobulin bound). The color range scale is adjusted for the fluorochrome-to-Thymoglobulin conjugation efficiency of each batch. (B = B cell, NK = natural killer cell, CD8 = CD8<sup>+</sup> T cell, CD4 = CD4<sup>+</sup> T cell, Mono = monocyte, Tn = naive T cell, Tem = effector memory T cell, Tcm = central memory T cell, Temra = exhausted memory T cell, Treg = regulatory T cell.)</p>
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<p>Competitive binding of Thymoglobulin to PBMC and T cell markers within different donors and batches. Cluster analysis of PBMC (<b>A</b>) and T cell (<b>B</b>) subsets from each donor and batch—with higher isobars indicating a higher cell number within a subset. Clustering is based on two different staining orders of Thymoglobulin and panel antibodies that are presented as overlays: Panel first (grey), Thymoglobulin first (orange). Distinct grey or orange isobar areas (i.e., non-overlapping) within a cluster defined by a marker indicates that Thymoglobulin contains antibodies that bind to a marker that is also expressed by that cluster, which may or may not be present in the panel. The columns on the right show the expression level per marker ranging from low (dark blue) to moderate (green) to high (orange).</p>
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<p>Cytokine levels after in vitro Thymoglobulin administration of different batches to whole blood from different donors. Heatmap showing cytokine levels without (control) or with different batches of Thymoglobulin (<b>A</b>). Absolute cytokine levels are presented for each donor; cytokine release syndrome (CRS)-related cytokines in upper four graphs. Cytokine levels for each cytokine were all significantly different between donors: IFN-γ (F = 5.336; <span class="html-italic">p</span> = 0.0071), MIP-1β (F = 39.97; <span class="html-italic">p</span> &lt; 0.0001), IL-6 (F = 47.22; <span class="html-italic">p</span> &lt; 0.0001), TNF-α (F = 173.6; <span class="html-italic">p</span> &lt; 0.0001), IL-2 (F = 109.1; <span class="html-italic">p</span> &lt; 0.0001), MCP-1 (F = 190.5; <span class="html-italic">p</span> &lt; 0.0001), IL-1β (F = 45.26; <span class="html-italic">p</span> &lt; 0.0001), GM-CSF (F = 100.3; <span class="html-italic">p</span> &lt; 0.0001), analyzed with one-way ANOVA (<b>B</b>). Two-dimensional opt-SNE plots showing clusters of all 30 samples, with different batch colors shown in the upper graph and different donor colors shown in the lower graph (<b>C</b>). Other cytokines did not differ between donors or Thymoglobulin batches; ranges (pg/mL): G-CSF (0–43.44), IL-4 (0–2.18), IL-5 (0–31.94), IL-7 (0–3.86), IL-8 (6.03–1328.24), IL-10 (0–5.05), IL-12 (0–2.09), IL-13 (0–1.61), IL-17 (0–14.0).</p>
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14 pages, 1558 KiB  
Article
Sequential Vaccination Against Streptococcus pneumoniae Appears as Immunologically Safe in Clinically Stable Kidney Transplant Recipients
by Monika Lindemann, Lukas van de Sand, Nils Mülling, Kim L. Völk, Ulrich W. Aufderhorst, Benjamin Wilde, Peter A. Horn, Andreas Kribben, Adalbert Krawczyk, Oliver Witzke and Falko M. Heinemann
Vaccines 2024, 12(11), 1244; https://doi.org/10.3390/vaccines12111244 - 31 Oct 2024
Viewed by 941
Abstract
Background: Vaccination against Streptococcus pneumoniae is advised for transplant recipients to reduce morbidity and mortality associated with invasive pneumococcal disease. However, data on alloantibodies after sequential vaccination (with a pneumococcal conjugate vaccine followed by a polysaccharide vaccine) are still lacking. Methods: In the [...] Read more.
Background: Vaccination against Streptococcus pneumoniae is advised for transplant recipients to reduce morbidity and mortality associated with invasive pneumococcal disease. However, data on alloantibodies after sequential vaccination (with a pneumococcal conjugate vaccine followed by a polysaccharide vaccine) are still lacking. Methods: In the current study, we determined HLA class I and II and major histocompatibility class I-related chain A (MICA) antibodies in 41 clinically stable kidney transplant recipients. These antibodies were measured prior to and post sequential pneumococcal vaccination over a period of 12 months. Alloantibodies were measured by Luminex bead-based assays, and pneumococcal IgG antibodies were measured by ELISA. Results: Over a 12-month period, the sequential analysis revealed no significant change in alloantibodies. One patient developed de novo donor-specific antibodies (DSA) 1.5 months after the first vaccination, with mean fluorescence intensities of up to 2300. These DSA became undetectable in the follow-up, and the patient showed no signs of allograft rejection. Another patient experienced a biopsy-proven borderline rejection 7 months after the first vaccination but did not develop de novo DSA. Both maintained stable kidney function. As expected, the pneumococcal antibodies increased significantly after vaccination (p < 0.0001). Conclusions: Given the overall risk of alloimmune responses in transplant recipients, we would not attribute the two noticeable patient courses to vaccination. Thus, we consider sequential vaccination immunologically safe. Full article
(This article belongs to the Special Issue Vaccine Efficacy and Safety in Transplant Recipients)
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<p>Study design. Sequential pneumococcal vaccination and blood collection in 41 kidney transplant recipients. The blood droplets indicate the time points of blood collection. The first vaccination was performed with a 13-valent conjugated vaccine (PCV13), the second with a 23-valent polysaccharide vaccine (PPSV23). Month 0 indicates baseline (pre-vaccination) and months 1–12 follow-up after the first vaccination. For example, month 7 means 7 months after the first vaccination and 1 month after the second vaccination.</p>
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<p>Time-course of antibodies determined in 41 kidney transplant recipients prior to vaccination (month 0, M0) and after vaccination against pneumococci (months 1 to 12, M1–M12). The first vaccination was performed at month 0 (directly after blood collection) with a 13-valent pneumococcal conjugate vaccine and the second vaccination at month 6 with a 23-valent pneumococcal polysaccharide vaccine. The time points of vaccination are indicated by arrows. The left panels show antibodies against human leukocyte antigen (HLA) class I and II and major histocompatibility class I-related chain A (MICA), which were expressed either as cumulative (cum.) antibody scores as detailed in the Methods section (<b>a</b>) or as cumulative mean fluorescence intensity (MFI) (<b>b</b>). Panel (<b>c</b>) indicates IgG antibodies against <span class="html-italic">S. pneumoniae</span>. Antibodies against HLA and MICA are presented as mean and standard error of the mean (SEM), pneumococcal antibodies as geometric mean and 95% confidence interval. To compare the results at the various time points, we used a 1-way ANOVA, the Friedman test with Dunn’s multiple comparisons test (** <span class="html-italic">p</span> &lt; 0.01; **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Patterns of antibodies in 41 kidney transplant recipients prior to vaccination (month 0, M0) and after vaccination against pneumococci (months 1 to 12, M1–M12). The time points of vaccination are indicated by arrows. Panel (<b>a</b>,<b>b</b>) indicate the number of patients with positive or negative antibody responses against human leukocyte antigen (HLA) class I and II and major histocompatibility class I-related chain A (MICA), setting the cutoff for positive responses at a ratio of 3.0 (<b>a</b>) or 4.5 (<b>b</b>), respectively. Panel (<b>c</b>) shows changes in the cumulative antibody score, determined pre-vaccination (month 0) and at month 12, i.e., after two vaccinations. Red symbols/numbers indicate patients with an increase (the score in month 12 was at least 1 higher than in month 0), black with constant values, and green with a decrease.</p>
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<p>Comparison of antibody patterns in female and male kidney transplant recipients prior to vaccination (month 0, M0) and after vaccination against pneumococci (months 1 to 12, M1–M12). The time points of vaccination are indicated by arrows. Panel (<b>a</b>) indicates cumulative antibody scores for antibodies against human leukocyte antigen (HLA) class I and II and major histocompatibility class I-related chain A (MICA); panel (<b>b</b>) indicates IgG antibodies against pneumococci and kidney function (estimated glomerular filtration rate, eGFR). Data on alloantibodies and kidney function are presented as mean and standard error of the mean (SEM), and data on pneumococcal antibodies as geometric mean and 95% confidence interval.</p>
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12 pages, 2888 KiB  
Article
Effect of Edible Wax on Postharvest Greening of Potato Tubers during Light Exposure
by Juliet Makalla Manamela, Thabiso Kenneth Satekge, Tieho Paulus Mafeo and Sasan Aliniaeifard
Horticulturae 2024, 10(9), 922; https://doi.org/10.3390/horticulturae10090922 - 29 Aug 2024
Viewed by 1159
Abstract
During retail storage, potato tubers are exposed to light that results in tuber greening. Green tubers are toxic and rejected by consumers. In the present study, the effect of Citrashine® natural wax on the postharvest tuber greening of two potato cultivars (‘Mondial’ [...] Read more.
During retail storage, potato tubers are exposed to light that results in tuber greening. Green tubers are toxic and rejected by consumers. In the present study, the effect of Citrashine® natural wax on the postharvest tuber greening of two potato cultivars (‘Mondial’ and ‘Sifra’) was studied. The tubers were irradiated with white light during a 12-day storage period at ambient temperature. During light exposure, tubers were evaluated for colour, pigmentation, chlorophyll fluorescence and starch granule distribution at 3-day intervals. The results showed that wax-treated tubers had significantly (p < 0.05) less green colour as represented by visual and objective colour parameters (a*, b*, C* and h°), compared to those treated with water (control). The pigmentation of the tubers was significantly influenced by the postharvest Citrashine® natural wax treatment. The total chlorophyll content was significantly lower in wax-treated tubers, while the carotenoid content was significantly higher in wax-treated tubers compared to their contents in control samples. Scanning electron microscopy showed that the starch granule size was normally distributed in wax-treated tubers compared to the untreated ones, which was negatively skewed. In conclusion, Citrashine® natural wax showed the potential to be a postharvest technology for controlling greening defects on potato tubers. The results provide a possible effective strategy for controlling the postharvest greening of potato tubers. Full article
(This article belongs to the Section Postharvest Biology, Quality, Safety, and Technology)
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<p>Effect of Citrashine<sup>®</sup> natural wax on postharvest greening of ‘Mondial’ and ‘Sifra’ potato cultivars during 12 days of light exposure. Data were averages of five replicates ± standard error. Different letters represent statistical significance (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Peel colour of ‘Mondial’ tubers treated with Citrashine<sup>®</sup> natural wax or untreated during 12-day light exposure.</p>
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<p>Peel colour of ‘Sifra’ tubers treated with Citrashine<sup>®</sup> natural wax or untreated during 12-day light exposure.</p>
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<p>Effect of Citrashine<sup>®</sup> natural wax on objective colour parameters of ‘Mondial’ potato cultivars during 12 days of light exposure. Data were averages of five replicates ± standard error. Different letters represent statistical significance (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of Citrashine<sup>®</sup> natural wax on objective colour parameters of ‘Sifra’ potato cultivars during 12 days of light exposure. Data were averages of five replicates ± standard error. Different letters represent statistical significances (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of Citrashine<sup>®</sup> natural wax on total chlorophyll content of ‘Mondial’ and ‘Sifra’ potato tubers peel during 12-day light exposure in ambient storage. Data were averages of five replicates ± standard error. Different letters represent statistical significance (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Confocal laser scanning micrograph of potato tuber skin of ‘Sifra’ cultivar of wax-treated and untreated (control) tubers on day three of light exposure. Tubers were illuminated with Phillips fluorescent light in ambient storage. Chl indicates presence of chloroplasts.</p>
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<p>Starch granule size distribution on surface of wax-treated and untreated ‘Sifra’ potato tubers following 12-day light exposure at ambient temperature.</p>
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13 pages, 1292 KiB  
Article
Evaluation of Lipid Damage, Microbial Spoilage and Sensory Acceptance of Chilled Pouting (Trisopterus luscus), an Underutilized Lean Fish Species
by Julio Maroto, Marcos Trigo, José M. Miranda, Santiago P. Aubourg and Jorge Barros-Velázquez
Appl. Sci. 2024, 14(16), 6905; https://doi.org/10.3390/app14166905 - 7 Aug 2024
Viewed by 643
Abstract
The present study focused on the use of pouting (Trisopterus luscus), an underutilized gadoid fish species, as a fresh product of potential commercial interest. Accordingly, non-degutted pouting specimens (145–195 g and 15–22 cm) were stored under chilling conditions (0 °C) for [...] Read more.
The present study focused on the use of pouting (Trisopterus luscus), an underutilized gadoid fish species, as a fresh product of potential commercial interest. Accordingly, non-degutted pouting specimens (145–195 g and 15–22 cm) were stored under chilling conditions (0 °C) for microbial, chemical and sensory analyses to evaluate their commercial quality and shelf life. A progressive quality loss (p < 0.05) was detected for this lean species (5.58 g lipids·kg−1 muscle) as the storage time increased, as determined through microbial (aerobes, psychrotrophs and Enterobacteriaceae counts), lipid hydrolysis (free fatty acid value), lipid oxidation (conjugated diene and triene, thiobarbituric acid reactive substance, and fluorescence values) and sensory acceptance assessment. A detailed comparison to related lean fish species revealed that the pouting exhibited a fast quality breakdown under refrigeration conditions. Thus, after 9 d of chilled storage, the psychrotroph counts exceeded the acceptable limits (8.54 log CFU·g−1), and the fish specimens were found to be rejectable, with the sensory panel, external odor and eye appearance being the limiting factors. In contrast, the pouting specimens exhibited high quality after 3 d of storage, with the quality being still acceptable after 6 d. According to the current search for novel, underutilized species, pouting is proposed as a promising source. Full article
(This article belongs to the Special Issue Antioxidant Compounds in Food Processing)
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<p>Evolution of trimethylamine (TMA; mg TMA-N·kg<sup>−1</sup> muscle) value in pouting muscle subjected to chilling storage. Average values of three independent determinations (<span class="html-italic">n</span> = 3), with standard deviations denoted by bars. Different letters (a, b and c) denote differences (<span class="html-italic">p</span> &lt; 0.05) with chilling time.</p>
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<p>Formation of free fatty acids (FFAs; g·kg<sup>−1</sup> lipids) in pouting muscle subjected to chilling storage. Average values of three independent determinations (<span class="html-italic">n</span> = 3), where standard deviations are denoted by bars. Different letters (a, b, c and d) denote differences (<span class="html-italic">p</span> &lt; 0.05) in chilling time.</p>
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<p>Fluorescent compound formation (fluorescence ratio (FR)) in pouting muscle subjected to chilling storage. Average values of three independent determinations (<span class="html-italic">n</span> = 3), with standard deviations indicated by bars. Different letters (a, b and c) denote differences (<span class="html-italic">p</span> &lt; 0.05) in chilling time.</p>
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17 pages, 2913 KiB  
Article
Long-Term Performance Evaluation and Fouling Characterization of a Full-Scale Brackish Water Reverse Osmosis Desalination Plant
by Sabrine Chebil, A. Ruiz-García, Soumaya Farhat and Mahmoud Bali
Water 2024, 16(13), 1892; https://doi.org/10.3390/w16131892 - 1 Jul 2024
Viewed by 1254
Abstract
Water scarcity in Tunisia’s semi-arid regions necessitates advanced brackish water desalination solutions. This study evaluates the long-term performance and fouling characteristics of the largest brackish water reverse osmosis desalination plant in southern Tunisia over a period of 5026 days. The plant employs two-stage [...] Read more.
Water scarcity in Tunisia’s semi-arid regions necessitates advanced brackish water desalination solutions. This study evaluates the long-term performance and fouling characteristics of the largest brackish water reverse osmosis desalination plant in southern Tunisia over a period of 5026 days. The plant employs two-stage spiral-wound membrane elements to treat groundwater with a salinity of 3.2 g L−1. The pre-treatment process includes oxidation, sand filtration, and cartridge filtration, along with polyphosphonate antiscalant dosing. Membrane performance was assessed through the analysis of operational data, standardization of permeate flow (Qps) and salt passage (SPs), and the calculation of water (A), solute (B), and ionic (Bj) permeability coefficients. Over the operational period, there was an increase in operating pressure, pressure drop, and permeate conductivity, accompanied by a gradual increase in SPs as well as in the solute B and ionic Bj permeability coefficients. The average B increased by 82%, reflecting a decrease in solute rejection over time. Additionally, the ionic permeability coefficients for both SO42− and Cl ions increased, with Cl showing an 88% increase and SO42− showing an 87% increase. The produced water’s salinity increased by 67%, indicating a significant loss of membrane performance. To identify the cause of these problems, membrane characterization was analyzed using visual inspection, X-ray fluorescence (XRF), and Fourier transform infrared spectroscopy (FTIR). The characterization revealed the complex nature of the foulants, with a predominant presence of calcium sulfate, along with minor quantities of calcite, dolomite, and silica. The extent of CaSO4 deposition suggests poor antiscaling efficiency, highlighting the critical importance of selecting an effective antiscalant to mitigate membrane fouling. Full article
(This article belongs to the Topic Membrane Separation Technology Research)
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<p>BWRO desalination plant.</p>
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<p>Process diagram of the BWRO desalination plant.</p>
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<p>Reverse osmosis membrane cut out for autopsy tests.</p>
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<p>Evolution of operating data over time. (<b>a</b>) Feed pressure over time; (<b>b</b>) Pressure drop over time; (<b>c</b>) Conversion rate over time; (<b>d</b>) Permeate flow over time; (<b>e</b>) Permeate conductivity over time; (<b>f</b>) Specific energy consumption.</p>
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<p>Standardization of operating data. (<b>a</b>) Standardization of permeate flow; (<b>b</b>) Standardization of salt passage.</p>
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<p>Evolution of permeability coefficients. (<b>a</b>) Water permeability coefficient; (<b>b</b>) Solute permeability coefficient; (<b>c</b>) Sulfate ion permeability coefficient; (<b>d)</b> Chloride ion permeability coefficient.</p>
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<p>Fouling characterization. (<b>a</b>) Visual inspection of membrane fouling; (<b>b</b>) X-ray diffraction spectra of deposit sample; (<b>c</b>) IR spectra of deposit sample.</p>
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18 pages, 2746 KiB  
Article
Valorization of the Residual Fraction of Coal Tailings: A Mineral Circularity Strategy for the Clay Ceramic Industry in the Carboniferous Region of Santa Catarina, Southern Brazil
by Wagner Benedet Rebelo, Alexandre Zaccaron, Emily Saviatto, Eduarda Fraga Olivo, Juliana Acordi, Fabiano Raupp-Pereira and Manuel Joaquim Ribeiro
Materials 2024, 17(9), 2131; https://doi.org/10.3390/ma17092131 - 1 May 2024
Cited by 1 | Viewed by 1090
Abstract
Mineral extraction of coal in the carboniferous region of southern Santa Catarina (Brazil) plays a significant role in the regional economy. However, this activity has severe environmental impacts, with approximately 65% of the extracted mineral being discarded as a rejected material (deposited in [...] Read more.
Mineral extraction of coal in the carboniferous region of southern Santa Catarina (Brazil) plays a significant role in the regional economy. However, this activity has severe environmental impacts, with approximately 65% of the extracted mineral being discarded as a rejected material (deposited in landfills). The identification of the technological potential of these materials, based on the geological aspects of the extraction site and the beneficiation operations applied to obtain coal, provides the opportunity to add value to different residual fractions that can be reused. Thus, waste valorization, the main objective of this work, has recently become a strategy for the application of these minerals in the production of clay ceramics using a systematic approach named CPQvA, which means “classification, potentiality, quantity/viability, and applicability”. The use of these materials as secondary mineral sources can avoid the deposition of these materials in industrial landfills and help to reduce the pressure on landfills, which receive an average of four million tons of material annually. In this study, the residual fraction, part of the tailing from coal beneficiation, known as coal fines, was evaluated for formulation valorization in clay ceramics. This residual fraction was classified as non-hazardous (class II-A, non-inert). X-ray fluorescence spectrometry, X-ray diffraction, and thermogravimetric analysis were performed to characterize the moisture content, particle-size distribution, and coal content to be used in the development of different formulations using the residual fraction of coal tailings (ranging from 0 to 40%) that are of technological interest to the sector. Processing parameters, such as firing at different temperatures (750, 800, 850, and 900 °C), were also correlated with these formulations. The results were compared with those of a reference ceramic formulation from the local productive arrangement of Morro da Fumaça (Arranjo Produtivo Local Cerâmica Vermelha de Morro da Fumaça). The various relationships between the materials were characterized in terms of their thermal shrinkage, water absorption, and mechanical resistance. Leaching and solubilization environmental tests revealed that both the industrial standard formulation and formulations with the application of the residual fraction were classified as non-hazardous materials. Thus, the method of using a mining residual fraction in the formulation of clay ceramics proved to be beneficial for the circular economy in the regional mineral sector through productive and environmental gains; the primary mineral resource and energy consumptions and the impacts related to waste generation were reduced. The results of this study can be applied to similar situations in other parts of the world. Full article
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<p>Geographic representation of the industrial hub of Morro da Fumaça, which is the focus in this study. Source: [<a href="#B35-materials-17-02131" class="html-bibr">35</a>].</p>
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<p>Representation of the CPQvA methodology for the valorization of the studied residual fraction, along with feasibility of application in a ceramic material.</p>
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<p>Map of the Morro da Fumaça Ceramic hub area (<b>left</b>) and schematic representation of industry density (<b>right</b>). Source: [<a href="#B61-materials-17-02131" class="html-bibr">61</a>].</p>
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<p>X-ray diffraction analysis of the studied samples for examining mineralogical composition.</p>
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<p>Cumulative distribution and particle size density of the studied samples.</p>
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<p>Differential thermal analysis (DTA) and thermogravimetric analysis (TGA) of the studied samples.</p>
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<p>Technological characterization of the formulations: (<b>a</b>) moisture and drying shrinkage; (<b>b</b>) firing shrinkage; (<b>c</b>) water absorption; and (<b>d</b>) mechanical strength.</p>
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33 pages, 4723 KiB  
Article
Beneficiation of High-Density Tantalum Ore in the REFLUX™ Concentrating Classifier Analysed Using Batch Fractionation Assay and Density Data
by Simon M. Iveson, Nicolas Boonzaier and Kevin P. Galvin
Minerals 2024, 14(2), 197; https://doi.org/10.3390/min14020197 - 14 Feb 2024
Cited by 1 | Viewed by 1357
Abstract
A laboratory-scale REFLUX™ Concentrating Classifier was operated in continuous mode to beneficiate a sub 0.100 mm tantalum ore with a head grade of 0.56 wt.% Ta. The unit incorporated a lower section with a reduced diameter to accommodate a low yield. At a [...] Read more.
A laboratory-scale REFLUX™ Concentrating Classifier was operated in continuous mode to beneficiate a sub 0.100 mm tantalum ore with a head grade of 0.56 wt.% Ta. The unit incorporated a lower section with a reduced diameter to accommodate a low yield. At a yield to underflow product of 4.0 wt.%, a product grade of 13.3 wt.% was achieved (23.7 upgrade) at a recovery of 88.3%. Samples of the feed, product and reject were then fractionated in a batch REFLUX™ Classifier unit using dense lithium heteropolytungstate (LST) solution into 11 fractions. Each of these fractions was then screened into seven size intervals and analysed by pycnometry and X-ray fluorescence (XRF). Most of the material was found to reside in four relatively narrow density bands. A new analysis based on the recovery of selected tracer elements showed that the partition curve had good closure at both ends and that the density cut point and Ep both increased with decreasing particle size. For the +0.045 mm material, the density cut point was estimated to be around 3952 kg/m3 with an Ep of 317 kg/m3, but it was expected that this new method could overestimate Ep. An alternative novel approach for estimating the partition performance was developed. This method estimated the cut point and Ep values to be 3764 kg/m3 and 107 kg/m3, respectively. However, sensitivity analysis found that due to the near total absence of material in the density range from 3400 kg/m3 to 4700 kg/m3, the Ep could likely lie anywhere in the range from 0 to 250 kg/m3. The methodology proved useful in establishing these limitations in the analysis. Full article
(This article belongs to the Section Mineral Processing and Extractive Metallurgy)
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<p>Schematic summary of the processing steps. The original continuous experiment furnished three samples—feed, product and reject. The +0.045 mm material from each of these samples was then batch fractioned into 11 flow fractions. Each of these fractions was then screened into 7 size intervals, thus resulting in a total of 3 × 11 × 7 = 231 portions.</p>
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<p>Cumulative mass fraction less than size distribution of the tantalum ore feed.</p>
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<p>Rendered images of the continuous RC™100-40 system: (<b>a</b>) overall structure and (<b>b</b>) close-up details of the midsection.</p>
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<p>Schematic of batch fractionation setup.</p>
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<p>Upgrade and recovery of Sn, Ta and Nb plotted as a function of average particle size. Recovery calculated from Equation (2) applied to the reconstituted assays in each size interval (<a href="#minerals-14-00197-t0B5" class="html-table">Table B5</a>), except for the 0–0.045 mm size interval, which is based on the raw assays of the −0.045 wet-screened material (<a href="#minerals-14-00197-t001" class="html-table">Table 1</a>).</p>
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<p>Cumulative mass fraction plotted as a function of average density for the combined flow fraction × size interval portions of the +0.045 mm wet-screened feed, product and reject samples. Portions with insufficient mass for pycnometry were assigned the same properties as the portion in the nearest adjacent size interval in that same flow fraction.</p>
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<p>Density frequency distributions of the combined flow fractionation × size interval portions of the +0.045 mm wet-screened feed, product and reject stream samples. Labels indicate the major minerals most likely responsible for each peak (see <a href="#minerals-14-00197-t002" class="html-table">Table 2</a> and discussion of the XRD data below). Portions with insufficient mass for pycnometry were assigned the same properties as the portion in the nearest adjacent size interval in that same flow fraction.</p>
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<p>Product cumulative mass plotted as a function of density for each of the 19 species (elements or their oxides) plotted versus the average portion density for the flow × size portions of the +0.045 mm wet-screened sample. Percentages are based on the total amount of that species in the sample and so all 19 sets of data rise towards 100% at the lowest density. Portions with insufficient mass for assay and pycnometry were assigned the same properties as the portion in the nearest adjacent size interval in that same flow fraction.</p>
Full article ">Figure 9
<p>Reject cumulative mass plotted as a function of density for each of the 19 species (elements or their oxides) versus average portion density for the flow × size portions of the +0.045 mm wet-screened sample. Percentages are based on the total amount of each species in the sample, and so all 19 sets of data rise to 100% at the lowest density. Portions with insufficient mass for assay and pycnometry were assigned the same properties as the portion in the nearest adjacent size interval in that same flow fraction.</p>
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<p>Cumulative mass plotted as a function of density distributions of selected species in the +0.045 mm wet-screened composite feed sample made by combining the product and reject data at a yield of 4.1%. Percentages are based on the total amount of that species in the sample, and so do not indicate amounts of the different species relative to each other.</p>
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<p>Density frequency mass distribution of selected species in the +0.045 mm wet-screened composite feed sample made by combining the product and reject data at a yield of 4.1%. Percentages are based on the total amount of that species in the sample, and so do not indicate amounts of the different species relative to each other. Labels indicate the mineral most likely responsible for the peak based on the XRD data (see <a href="#minerals-14-00197-t002" class="html-table">Table 2</a>).</p>
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<p>Recovery of selected tracer species calculated by applying Equation (2) to the reconstituted size interval assay data in <a href="#minerals-14-00197-t0B5" class="html-table">Table B5</a> for the +0.045 mm wet-screened feed, product and reject samples plotted as a function of the average density associated with that species calculated using Equation (7) for the flow × size portion data (see <a href="#minerals-14-00197-t002" class="html-table">Table 2</a>).</p>
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<p>Relative difference between compositions fitted by the Full Species Distribution Method and the mass-balanced assay data for +0.045 mm wet-screened feed, product and reject samples (<a href="#minerals-14-00197-t0A1" class="html-table">Table A1</a>).</p>
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<p>Results of the Full Species Distribution Method with <span class="html-italic">Y</span> = 0.041 when <span class="html-italic">Ep</span> is fixed and <span class="html-italic">D</span><sub>50</sub> is allowed to vary to minimise <span class="html-italic">SSRE</span>. The optimum <span class="html-italic">D</span><sub>50</sub> is strongly correlated with <span class="html-italic">Ep</span>, and there is a wide range of <span class="html-italic">Ep</span> values that give <span class="html-italic">SSRE</span><sub>min</sub> &lt; 2.</p>
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<p>Partition curve of the wet-screened +0.045 mm material found by the Full Species Distribution Method with <span class="html-italic">Y</span> = 0.041. Dashed blue curves show range of results that give <span class="html-italic">SSRE</span><sub>min</sub> &lt; 2 when <span class="html-italic">Ep</span> is fixed and <span class="html-italic">D</span><sub>50</sub> is allowed to vary. Also shown are the +0.045 mm recovery values plotted in <a href="#minerals-14-00197-f012" class="html-fig">Figure 12</a> and the best fit of Equation (5) through that data. Upper and lower error bars on those data show approximate fractions of the species found, respectively, below and above the narrow density range in which most of that species is found (see <a href="#minerals-14-00197-f011" class="html-fig">Figure 11</a>).</p>
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<p>Product XRD scan.</p>
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<p>Reject XRD scan.</p>
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10 pages, 254 KiB  
Brief Report
Clinical Outcome of Kidney Transplant Recipients with C1q-Binding De Novo Donor Specific Antibodies: A Single-Center Experience
by Smaragdi Marinaki, Angeliki Vittoraki, Stathis Tsiakas, Ioannis Kofotolios, Maria Darema, Sofia Ioannou, Kalliopi Vallianou and John Boletis
J. Clin. Med. 2023, 12(13), 4475; https://doi.org/10.3390/jcm12134475 - 4 Jul 2023
Viewed by 1444
Abstract
Complement activation by HLA antibodies is a key component of immune-mediated graft injury. We examined the clinical outcomes of kidney transplant recipients with complement-fixing de novo donor-specific antibodies (dnDSA) who were followed in our center. The C1q-binding ability was retrospectively assessed in 69 [...] Read more.
Complement activation by HLA antibodies is a key component of immune-mediated graft injury. We examined the clinical outcomes of kidney transplant recipients with complement-fixing de novo donor-specific antibodies (dnDSA) who were followed in our center. The C1q-binding ability was retrospectively assessed in 69 patients with dnDSA and mean fluorescence intensity (MFI) values > 2000 out of the 1325 kidney transplant recipients who were screened for DSA between 2015 and 2019. Luminex IgG single antigen beads (SAB)and C1q-SAB assays (One Lambda) were used. C1q-binding dnDSA was identified in 32/69 (46.4%) of the patients. Significantly higher MFI values were observed in C1q-positive DSA (18,978 versus 5840, p < 0.001). Renal graft biopsies were performed in 43 of the kidney transplant recipients (62.3%) with allograft dysfunction. Antibody-mediated rejection (ABMR) was detected in 29/43 (67.4%) of the patients. The incidence of ABMR was similar among patients with C1q-binding and non-C1q-binding DSA (51.7% vs. 48.3%, p = 0.523). Graft loss occurred in 30/69 (43.5%) of the patients at a median time of 82.5 months (IQR 45–135) from DSA detection. C1q-binding DSA was present in more patients who experienced graft loss (53.1% vs. 35.1%, p = 0.152). Higher MFI values and inferior clinical outcomes occurred in most of the kidney transplant recipients with C1q-binding dnDSA. Full article
(This article belongs to the Special Issue Recent Advances of Kidney Transplantation)
14 pages, 4243 KiB  
Article
Removal of NOMs by Carbon Nanotubes/Polysulfone Nanocomposite Hollow Fiber Membranes for the Control of Disinfection Byproducts (DBPs)
by Jun Yin, Maria Fidalgo and Baolin Deng
Water 2023, 15(11), 2054; https://doi.org/10.3390/w15112054 - 29 May 2023
Cited by 2 | Viewed by 1376
Abstract
It has been well established that natural organic matters (NOMs) are precursors for the formation of disinfection by-products (DBPs) in drinking water supplies, thus the removal of NOMs is often used as an effective approach to limit DBPs production. In this study, we [...] Read more.
It has been well established that natural organic matters (NOMs) are precursors for the formation of disinfection by-products (DBPs) in drinking water supplies, thus the removal of NOMs is often used as an effective approach to limit DBPs production. In this study, we evaluated the application of oxidized multi-walled carbon nanotubes (OMWNTs)/polysulfone (PSU) nanocomposite hollow fiber membranes (HFM) for the removal of NOMs and its impact on the production of DBPs following water chlorination. Analysis of source water samples by fluorescence excitation/emission matrix (EEM) spectrometry indicated that the dominant dissolved organic matters were humic acid. Evaluation of the fabricated nanocomposite HFMs showed improved water fluxes (30~50%), better fouling resistance, and a comparable solute rejection rate when compared with the conventional PSU membranes. The flux increase was attributed to the increased surface hydrophilicity and porosity of the membrane after embedding the hydrophilic OMWNTs. The membrane filtration resulted in a reduction of UV254 by approximately 52%, 48%, and 38% for three water samples from Missouri River, Eagle Bluffs Conservation Area, and Columbia Water Treatment Plant, respectively. The corresponding reduction in trihalomethane formation potential (THMFP) reached 40%, 70%, and 27%, respectively. Overall, this study demonstrated that proper OMWNTs/PSU ultrafiltration membranes could remove a portion of NOMs from water at a relatively low cross-membrane pressure. It also illustrates the innovative concept that membrane design could be tailored for specific water quality conditions and regulatory requirements; in this particular case, to fabricate a membrane to reduce the THMFP to a level that meets the regulatory standards for trihalomethanes when the water was disinfected by chlorine. Full article
(This article belongs to the Special Issue Membrane Technology for Water Treatment and Desalination)
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Figure 1
<p>Locations of water sampling.</p>
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<p>A schematic illustrating the DBPs formation and analysis protocols.</p>
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<p>EEM fluorescence spectra of water samples from different locations: (<b>a</b>) Missouri River, (<b>b</b>) Eagle Bluffs, and (<b>c</b>) Water Treatment Plant. Colored lines are used to aid visualization of fluorescence contours.</p>
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<p>Removal rates of UV254 and EEM intensity (EX = 320 nm, EM = 420 nm) by using membranes with various MWCO.</p>
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<p>EEMs of water samples (Eagle Bluffs) after filtration by membranes with various molecular weight cut-off (MWCO), showing an increasing degree of NOM removal with a decreasing MWCO. Colored lines are used to aid visualization of fluorescence contours.</p>
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<p>EEM spectra of water samples with dilution ratio of (<b>a</b>) 0.25, (<b>b</b>) 0.50, (<b>c</b>) 0.75, (<b>d</b>) 1.00. Colored lines are used to aid visualization of fluorescence contours. The fluorescence emission intensities at EX = 320 nm (<b>e</b>) and the relationship between the fluorescence intensity and dilution ratio (<b>f</b>) are also illustrated.</p>
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<p>Pure water fluxes of membranes.</p>
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<p>Fouling behaviors of membranes containing 18% PSU (<b>a1</b>,<b>b1</b>,<b>c1</b>) and membranes containing 20% PSU (<b>a2</b>,<b>b2</b>,<b>c2</b>) when applied for filtrating water sample from Eagle Bluffs (<b>a</b>), Missouri River (<b>b</b>), and Columbia Drinking Water Treatment Plant (<b>c</b>). The TMP is 10 psi.</p>
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<p>Removal rates of NOMs and THMFP by different types of membranes (18% or 20% PSU and with or without OMWNTs) for water samples from Eagle Bluffs (<b>a</b>), Missouri River (<b>b</b>), and Columbia Drinking Water Treatment Plant (<b>c</b>). The TMP is 10 psi.</p>
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22 pages, 4782 KiB  
Article
Comparing Performance of Spectral Image Analysis Approaches for Detection of Cellular Signals in Time-Lapse Hyperspectral Imaging Fluorescence Excitation-Scanning Microscopy
by Marina Parker, Naga S. Annamdevula, Donald Pleshinger, Zara Ijaz, Josephine Jalkh, Raymond Penn, Deepak Deshpande, Thomas C. Rich and Silas J. Leavesley
Bioengineering 2023, 10(6), 642; https://doi.org/10.3390/bioengineering10060642 - 25 May 2023
Cited by 5 | Viewed by 2102
Abstract
Hyperspectral imaging (HSI) technology has been applied in a range of fields for target detection and mixture analysis. While HSI was originally developed for remote sensing applications, modern uses include agriculture, historical document authentication, and medicine. HSI has also shown great utility in [...] Read more.
Hyperspectral imaging (HSI) technology has been applied in a range of fields for target detection and mixture analysis. While HSI was originally developed for remote sensing applications, modern uses include agriculture, historical document authentication, and medicine. HSI has also shown great utility in fluorescence microscopy. However, traditional fluorescence microscopy HSI systems have suffered from limited signal strength due to the need to filter or disperse the emitted light across many spectral bands. We have previously demonstrated that sampling the fluorescence excitation spectrum may provide an alternative approach with improved signal strength. Here, we report on the use of excitation-scanning HSI for dynamic cell signaling studies—in this case, the study of the second messenger Ca2+. Time-lapse excitation-scanning HSI data of Ca2+ signals in human airway smooth muscle cells (HASMCs) were acquired and analyzed using four spectral analysis algorithms: linear unmixing (LU), spectral angle mapper (SAM), constrained energy minimization (CEM), and matched filter (MF), and the performances were compared. Results indicate that LU and MF provided similar linear responses to increasing Ca2+ and could both be effectively used for excitation-scanning HSI. A theoretical sensitivity framework was used to enable the filtering of analyzed images to reject pixels with signals below a minimum detectable limit. The results indicated that subtle kinetic features might be revealed through pixel filtering. Overall, the results suggest that excitation-scanning HSI can be employed for kinetic measurements of cell signals or other dynamic cellular events and that the selection of an appropriate analysis algorithm and pixel filtering may aid in the extraction of quantitative signal traces. These approaches may be especially helpful for cases where the signal of interest is masked by strong cellular autofluorescence or other competing signals. Full article
(This article belongs to the Special Issue Recent Advances in Biomedical Imaging)
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Figure 1
<p>Light path schematics and corresponding spectral scan range illustrations for emission-scanning and excitation-scanning HSI microscope systems. (<b>A</b>) A typical emission-scanning HSI microscope system utilizes one or several narrow bandwidths of illumination for excitation while acquiring fluorescence emission over many narrow spectral bands using a tunable filter or other wavelength sampling device (prism, grating, etc.). (<b>B</b>) An illustration of the spectral scan range for an emission-scanning HSI system. The fluorescence excitation and emission spectra of a hypothetical fluorescence label are shown as dotted and solid green lines. Excitation is provided at one narrow band, illustrated by the solid green bar placed at the peak excitation wavelength. Fluorescence emission is sampled across many narrow bands, illustrated by the many individual bars across the fluorescence emission spectrum. (<b>C</b>) The excitation-scanning HSI microscope system utilizes a tunable filter to sequentially select between many narrow excitation wavelength bands while acquiring fluorescence emission using a broad-band or long-pass emission filter (LP EM Filter). (<b>D</b>) An illustration of the spectral scan range for an excitation-scanning HSI system. The fluorescence excitation spectrum is sequentially sampled using many narrow excitation bands, as indicated by narrow bars placed over the excitation spectrum. The emitted fluorescence is detected in bulk using a broad-band or long-pass emission filter.</p>
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<p>An example theoretical sensitivity analysis, as performed for non-negatively constrained linear unmixing (LU). (<b>A</b>) The theoretical sensitivity curve (TSC) demonstrates a linear response of the LU algorithm to varying levels of the added target endmember, Cal 520. (<b>B</b>) The thresholded positive pixel curve (TPPC) indicates a sharp slope in detection accuracy for a threshold of 15 (unmixed intensity units). Importantly, using the threshold of 15, no false-positive pixels were detected when the 0 endmember signal was added. (<b>C</b>) The receiver operator characteristic (ROC) curve demonstrates a high predicted performance for LU for this application of Cal 520 detection, with an area under the curve (AUC) of 0.96. The TSC analysis was performed for all 4 spectral analysis algorithms, as described in the Results.</p>
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<p>Spectral image data from three single-label control samples were analyzed to construct a spectral library. (<b>A</b>) Representation of HSI image data from HASMCs labeled with the nuclear label, NucBlue. For visualization purposes, all wavelength bands have been summed to represent a total or summed fluorescence intensity image, and the intensity range linearly adjusted from 0 to 6300 A.U. for display. (<b>B</b>) A summed fluorescence intensity representation of HSI image data from a separate sample of unlabeled HASMCs with intensity range linearly adjusted from 0 to 315 A.U. for display. (<b>C</b>) A summed fluorescence intensity representation of HSI image data from a separate sample of HASMCs labeled with Cal 520 with intensity range linearly adjusted from 0 to 550 A.U. (<b>D</b>) A spectral library was generated by selecting a region of high signal intensity within each of the single-label control spectral images (<b>A</b>–<b>C</b>), extracting the pixel-averaged spectrum, and normalizing to a peak value of unity. (<b>E</b>) Comparison of measured spectra for NucBlue (blue squares) and Cal 520 (green triangles) to reported spectra. The Cal 520 spectrum was supplied from AAT Bioquest, while the NucBlue spectrum was approximated as that of DAPI and obtained using the Semrock Searchlight spectral plotting tool [<a href="#B58-bioengineering-10-00642" class="html-bibr">58</a>].</p>
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<p>Linear spectral unmixing of spectral images from Cal 520 labeled HASMCs. All wavelength bands were summed to show the total intensity of raw spectral images (column 1) at different time points. A region of interest corresponding to a single cell was selected to illustrate the change in excitation spectrum over time (Column 2). The primary contributors to the mixed spectra shown in Column 2 were NucBlue (excitation peak at 360 nm) and Cal 520 (excitation peak at 520 nm). Note that the excitation peak of Cal 520 is beyond the scan range used for the current study, and hence the highest wavelength response for Cal 520 occurs at the last wavelength scanned of 480 nm—see <a href="#bioengineering-10-00642-f003" class="html-fig">Figure 3</a>E for a comparison of measured and manufacturer excitation spectra. Note that the Cal 520 contribution is increased at time point 340 s, which corresponds to 40 s after agonist addition and a strong Ca<sup>2+</sup> release response visualized in the unmixed Cal 520 images (Column 4). Columns 3–5 show false-colored unmixed endmember images of NucBlue, Cal 520, and AF signals. Column 6 shows the RMS error associated with linear spectral unmixing. The color bar at the right represents the color look-up table used to visualize Ca<sup>2+</sup> signal intensity in Column 4.</p>
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<p>A comparison of 4 common spectral analysis algorithms for identifying endmembers in excitation-scanning spectral image data. Analyzed images were displayed using a greyscale look-up table for each endmember: NucBlue, Cal 520, and autofluorescence (AF). Images were analyzed using constrained energy minimization (CEM), linear unmixing (LU), matched filtering (MF), and spectral angle mapper (SAM). A video showing the full timelapse data set can be viewed in <a href="#app1-bioengineering-10-00642" class="html-app">Supplemental Video S1</a>. The same look-up tables were used for both <a href="#bioengineering-10-00642-f004" class="html-fig">Figure 4</a> and <a href="#bioengineering-10-00642-f005" class="html-fig">Figure 5</a> to permit comparison.</p>
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<p>A theoretical sensitivity analysis was applied using 4 spectral analysis algorithms for identifying fluorescence excitation-scanning signals. Three curves were calculated for each analysis algorithm: the Theoretical Sensitivity Curve (TSC), Thresholded Positive Pixel Curve (TPPC), and Receiver Operator Characteristic (ROC) curve. (<b>A</b>–<b>C</b>) TSC, TPPC, and ROC for linear unmixing (LU); (<b>D</b>–<b>F</b>) TSC, TPPC, and ROC for spectral angle mapper (SAM); (<b>G</b>–<b>I</b>) TSC, TPPC, and ROC for constrained energy minimization (CEM); (<b>J</b>–<b>L</b>) TSC, TPPC, and ROC for matched filter (MF). TSC and TPPC plots were generated by adding the spectrum of the target endmember, Cal 520, to a specified region of interest (ROI) in set amounts (increments of 1 were 0–30, 0–25, 0–25, and 0–30 for LU, SAM, CEM, and MF, respectively). ROC scale factors were 5 for all algorithms. Threshold values for TPPC were 15 for LU, 0.98 radians for SAM, and 15 for both CEM and MF. ROC threshold values were varied from 0 to 50 in increments of 1 for LU, CEM, and MF. ROC threshold values for SAM varied from 0 to 1.8 radians. ROC performance, as described by area under the curve (AUC), was 0.963 for LU, 0.570 for SAM, 0.872 for CEM, and 0.957 for MF.</p>
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<p>Effects of pixel filtering on time-lapse Ca<sup>2+</sup> image data acquired using excitation-scanning spectral imaging microscopy and matched filter (MF) analysis. Thresholds for pixel filtering were determined using a theoretical sensitivity analysis and a standard Otsu thresholding algorithm available in ImageJ. (<b>A</b>) A representative endmember image of Cal 520 at time point 40 s after treatment obtained using the MF algorithm. The Cal 520 image from panel (<b>A</b>) was also processed using pixel filtering to remove low-intensity (below detection limit) pixels using a threshold estimated from the theoretical sensitivity analysis ((<b>B</b>), threshold = 20) and from Otsu ((C), threshold = 24). (<b>D</b>) The field of view averaged time course for Cal 520 signal as estimated from the original and pixel-filtered image sets. Agonist-induced Ca<sup>2+</sup> signals in three different cells (cells 1, 2, and 3 shown as red, yellow, and blue regions on image panels (<b>A</b>–<b>C</b>)) were measured using the original and pixel-filtered image sets ((<b>E</b>)—(cell1), (<b>F</b>)—(cell2), and (<b>G</b>)—(cell3)).</p>
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<p>Effects of pixel filtering were further evaluated using time-lapse excitation-scanning HSI data of Cal 520 and NucBlue labeled HASMCs to identify dynamic Ca<sup>2+</sup> signals. Hyperspectral images were analyzed using a matched filter (MF) algorithm, and thresholds for pixel filtering were set to a value of 20, corresponding to the theoretical sensitivity analysis identified threshold used in <a href="#bioengineering-10-00642-f007" class="html-fig">Figure 7</a>B. (<b>A</b>) The initial time point Cal 520 endmember image (time point 0 s) corresponding to baseline Cal 520 fluorescence. Outlines for single-cell regions of interest (ROIs) are shown in yellow, and the cell number is indicated by colored text. A video showing all time points is provided in <a href="#app1-bioengineering-10-00642" class="html-app">Supplemental Video S3</a>. (<b>B</b>) The Cal 520 endmember image at a time point of 300 s, corresponding to a time point immediately after addition of 50 μM carbochol. A high-intensity response is seen in most cells. (<b>C</b>) The corresponding time trace for Cal 520 intensity for each of the single-cell ROIs. (<b>D</b>) The Cal 520 endmember image at time point 0 after applying a pixel threshold of 20. (<b>E</b>) The Cal 520 image at time point 300 after applying a pixel threshold of 20. A video showing all time points after pixel thresholding is provided in <a href="#app1-bioengineering-10-00642" class="html-app">Supplemental Video S4</a>. (<b>F</b>) The corresponding time trace for pixel-thresholded Cal 520 intensity for each of the single-cell ROIs. Periodic oscillations in Cal 520 intensity can be seen in cell 1 in the pixel-thresholded image data that are not visible in the non-thresholded data.</p>
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<p>Effects of pixel filtering were also evaluated in hyperspectral images of HASMCs treated with 50 μM histamine. Hyperspectral images were acquired and analyzed identically to images shown in <a href="#bioengineering-10-00642-f008" class="html-fig">Figure 8</a>. (<b>A</b>) The initial time point Cal 520 endmember image (time point 0 s), corresponding to baseline Cal 520 fluorescence. Outlines for single-cell regions of interest (ROIs) are shown in yellow, and the cell number is indicated by colored text. A video showing all time points is provided in <a href="#app1-bioengineering-10-00642" class="html-app">Supplemental Video S5</a>. (<b>B</b>) The Cal 520 endmember image at a time point of 330 s, corresponding to a time point immediately after addition of 50 μM carbochol. A high-intensity response is seen in most cells. (<b>C</b>) The corresponding time trace for Cal 520 intensity for each of the single-cell ROIs. (<b>D</b>) The Cal 520 endmember image at time point 0 after applying a pixel threshold of 20. (<b>E</b>) The Cal 520 image at time point 330 after applying a pixel threshold of 20. A video showing all time points after pixel thresholding is provided in <a href="#app1-bioengineering-10-00642" class="html-app">Supplemental Video S6</a>. (<b>F</b>) The corresponding time trace for pixel-thresholded Cal 520 intensity for each of the single-cell ROIs. Fluctuations in Cal 520 signal prior to treatment can be seen in cell 1 in the pixel-thresholded image data that are not present in the non-thresholded data.</p>
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11 pages, 1367 KiB  
Communication
Background Rejection in Two-Photon Fluorescence Image Scanning Microscopy
by Colin J. R. Sheppard, Marco Castello, Giorgio Tortarolo, Alessandro Zunino, Eli Slenders, Paolo Bianchini, Giuseppe Vicidomini and Alberto Diaspro
Photonics 2023, 10(5), 601; https://doi.org/10.3390/photonics10050601 - 22 May 2023
Cited by 1 | Viewed by 2092
Abstract
We discuss the properties of signal strength and integrated intensity in two-photon excitation confocal microscopy and image scanning microscopy. The resolution, optical sectioning and background rejection are all improved over nonconfocal two-photon microscopy. Replacing the pinhole of confocal two-photon microscopy with a detector [...] Read more.
We discuss the properties of signal strength and integrated intensity in two-photon excitation confocal microscopy and image scanning microscopy. The resolution, optical sectioning and background rejection are all improved over nonconfocal two-photon microscopy. Replacing the pinhole of confocal two-photon microscopy with a detector array increases the peak intensity of the point spread function. The outer pixels of a detector array give signals from defocused regions, and thus the processing of these, such as through subtraction, can further improve optical sectioning and background rejection. Full article
(This article belongs to the Topic Biomedical Photonics)
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Figure 1
<p>A log-log plot of the variation in integrated intensity with defocus for different point detector offsets. We call this the axial fingerprint. The integrated intensity is equivalent to the intensity from a fluorescent sheet object. For a large offset, the integrated intensity decays as the fourth power of defocus, an indication of strong optical sectioning. For offsets larger than about 1.3 AU, the maximum intensity occurs away from the focal plane.</p>
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<p>The variation in intensity in the detector plane for a fluorescent sheet object with different defocus values. This is equal to the integrated intensity for a point object and an offset point detector. For larger offsets, the intensity is greater for the defocused cases than the in-focus case. For <math display="inline"> <semantics> <mrow> <mi>u</mi> <mo>=</mo> <mn>4</mn> <mi>π</mi> </mrow> </semantics> </math>, the intensity is almost independent of the offset.</p>
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<p>The integrated intensity <math display="inline"> <semantics> <msub> <mi>I</mi> <mi>int</mi> </msub> </semantics> </math> for a ring of detectors. For a given ring radius larger than about 1.2 AU, the greatest contribution to <math display="inline"> <semantics> <msub> <mi>I</mi> <mi>int</mi> </msub> </semantics> </math> comes from the defocused regions of the object.</p>
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<p>The variation in integrated intensity for a detector disk, with the radius of the disk for different defocus values. The integrated intensity increases monotonically with the detector disk radius. Even for an infinite detector radius, the integrated intensity decreases with defocus, as there is still an optical sectioning effect from 2PE. The background from a volume object is also shown, being very similar to that for <math display="inline"> <semantics> <msub> <mi>I</mi> <mi>int</mi> </msub> </semantics> </math> for <math display="inline"> <semantics> <mrow> <mi>u</mi> <mo>=</mo> <mn>5</mn> <mi>π</mi> <mo>/</mo> <mn>3</mn> <mo>≈</mo> <mn>5.24</mn></mrow> </semantics> </math>.</p>
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<p>The integrated intensities for disk detectors of various sizes, including nonconfocal 2PE, as a function of defocus, normalized to unity for an in-focus, non-confocal two-photon microscope. All the curves decay monotonically with defocus. For nonconfocal 2PE, for large defocus values, the integrated intensity decays as the square of the defocus value. For finite-sized detectors, the integrated intensity decays as the fourth power of defocus. The integrated intensity, after subtracting 0.98 times the signal from an annular detector, outer radius 2 AU and inner radius 1.4 AU, from that from a disk detector radius 1.4 AU, labeled “subtraction”, is also shown.</p>
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<p>Cross-sections through the 3D PSF for two-photon excitation and an offset point detector without pixel reassignment for different detector offsets: (<b>top left</b>) 0.5 AU; (<b>top right</b>) 1 AU; (<b>bottom left</b>) 1.5 AU; and (<b>bottom right</b>) 2 AU. The cross-section is the plane containing the direction of offset and the optical axis, and <span class="html-italic">v</span> represents a normalized <span class="html-italic">x</span> distance.</p>
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12 pages, 5896 KiB  
Article
Thin and Scalable Hybrid Emission Filter via Plasma Etching for Low-Invasive Fluorescence Detection
by Erus Rustami, Kiyotaka Sasagawa, Kenji Sugie, Yasumi Ohta, Hironari Takehara, Makito Haruta, Hiroyuki Tashiro and Jun Ohta
Sensors 2023, 23(7), 3695; https://doi.org/10.3390/s23073695 - 3 Apr 2023
Cited by 3 | Viewed by 1989
Abstract
Hybrid emission filters, comprising an interference filter and an absorption filter, exhibit high excitation light rejection performance and can act as lensless fluorescent devices. However, it has been challenging to produce them in large batches over a large area. In this study, we [...] Read more.
Hybrid emission filters, comprising an interference filter and an absorption filter, exhibit high excitation light rejection performance and can act as lensless fluorescent devices. However, it has been challenging to produce them in large batches over a large area. In this study, we propose and demonstrate a method for transferring a Si substrate, on which the hybrid filter is deposited, onto an image sensor by attaching it to the sensor and removing the substrate via plasma etching. Through this method, we can transfer uniform filters onto fine micrometer-sized needle devices and millimeter-sized multisensor chips. Optical evaluation reveals that the hybrid filter emits light in the 500 to 560 nm range, close to the emission region of green fluorescent protein (GFP). Furthermore, by observing the fluorescence emission from the microbeads, a spatial resolution of 12.11 μm is calculated. In vitro experiments confirm that the fabricated device is able to discriminate GFP emission patterns from brain slices. Full article
(This article belongs to the Special Issue Fluorescence Sensors for Biological and Medical Applications)
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<p>Schematic of the thin and scalable hybrid filter fabrication using the plasma etching technique.</p>
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<p>(<b>a</b>) Schematic of the hybrid filter fabrication using the plasma etching technique. (<b>b</b>) Photograph of the image sensor assembled with the designated printed circuit board.</p>
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<p>Photographs of the image sensor before and after filter deposition. (<b>a</b>) After etching, the multisensor area in the chip is flawlessly covered by a hybrid filter. The enlarged image shows the Si remaining on the filter post-etching (black dots). (<b>b</b>) Uniform hybrid filter covering the entire area of the needle-type sensor after etching.</p>
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<p>(<b>a</b>) Filter transmission spectra compared with the green fluorescence protein (GFP) emission on a logarithmic scale. (<b>b</b>) Transmission spectra of the interference filter with the various angles of incidence. (<b>c</b>) Transmission spectra of the hybrid filter with the various angles of incidence.</p>
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<p>(<b>a</b>) Photograph of the microbead emission captured by the needle sensor. (<b>b</b>) Enlarged image of the ROI, denoted with a yellow square on (<b>a</b>) the merged beads in the upper left corner and the separated beads in the lower right corner; this image is compared with the microscope image (<b>c</b>). (<b>d</b>) Single-microbead emission intensity in the vertical direction, plotted and fitted with the Gaussian distribution. The FWHM is 12.11 μm. (<b>e</b>) Two close microbeads can be distinguished, as the distance between them is almost twice the FWHM.</p>
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<p>Fluorescent image from a brain slice captured by the needle sensor integrated with the hybrid filter. Owing to the narrow excitation light, four different irradiation spots (1–4) are required to excite all the sensor imaging areas. These images are merged for a large FOV by simple image processing. An ROI of the merged image, denoted by the dashed square, is enlarged and compared with the image obtained by the fluorescence microscope.</p>
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13 pages, 2079 KiB  
Article
A Low-Cost, Portable Device for Detecting and Sorting Aflatoxin-Contaminated Maize Kernels
by Haibo Yao, Fengle Zhu, Russell Kincaid, Zuzana Hruska and Kanniah Rajasekaran
Toxins 2023, 15(3), 197; https://doi.org/10.3390/toxins15030197 - 4 Mar 2023
Cited by 5 | Viewed by 2818
Abstract
Aflatoxin contamination of maize is a major food safety issue worldwide. The problem is of special significance in African countries because maize is a staple food. This manuscript describes a low-cost, portable, non-invasive device for detecting and sorting aflatoxin-contaminated maize kernels. We developed [...] Read more.
Aflatoxin contamination of maize is a major food safety issue worldwide. The problem is of special significance in African countries because maize is a staple food. This manuscript describes a low-cost, portable, non-invasive device for detecting and sorting aflatoxin-contaminated maize kernels. We developed a prototype employing a modified, normalized difference fluorescence index (NDFI) detection method to identify potentially aflatoxin-contaminated maize kernels. Once identified, these contaminated kernels can be manually removed by the user. The device consists of a fluorescence excitation light source, a tablet for image acquisition, and detection/visualization software. Two experiments using maize kernels artificially infected with toxigenic Aspergillus flavus were implemented to evaluate the performance and efficiency of the device. The first experiment utilized highly contaminated kernels (71.18 ppb), while mildly contaminated kernels (1.22 ppb) were used for the second experiment. Evidently, the combined approach of detection and sorting was effective in reducing aflatoxin levels in maize kernels. With a maize rejection rate of 1.02% and 1.34% in the two experiments, aflatoxin reduction was achieved at 99.3% and 40.7%, respectively. This study demonstrated the potential of using this low-cost and non-invasive fluorescence detection technology, followed by manual sorting, to significantly reduce aflatoxin levels in maize samples. This technology would be beneficial to village farmers and consumers in developing countries by enabling safer foods that are free of potentially lethal levels of aflatoxins. Full article
(This article belongs to the Special Issue Advances in Rapid Detection and Reduction of Aflatoxins)
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<p>Aflatoxin distribution before and after sorting (experiment 1).</p>
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<p>Aflatoxin distribution before and after sorting (experiment 2).</p>
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<p>Maize rejection and aflatoxin reduction ratios for experiments 1 and 2. (<b>a</b>) Experiment 1, (<b>b</b>) Experiment 2.</p>
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<p>The portable detection device. (<b>a</b>) Prototype detection device component diagram, (<b>b</b>) Finished device.</p>
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<p>Flowchart of the image analysis steps for kernel aflatoxin contamination detection.</p>
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<p>Inoculation method: (<b>a</b>) side-needle inoculation and (<b>b</b>) silk inoculation.</p>
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24 pages, 3483 KiB  
Article
Optimising the Performance of CO2-Cured Alkali-Activated Aluminosilicate Industrial By-Products as Precursors
by Ghandy Lamaa, David Suescum-Morales, António P. C. Duarte, Rui Vasco Silva and Jorge de Brito
Materials 2023, 16(5), 1923; https://doi.org/10.3390/ma16051923 - 25 Feb 2023
Cited by 6 | Viewed by 2748
Abstract
Three industrial aluminosilicate wastes were studied as precursors to produce alkali-activated concrete: (i) electric arc furnace slag, (ii) municipal solid waste incineration bottom ashes, and (iii) waste glass rejects. These were characterized via X-ray diffraction and fluorescence, laser particle size distribution, thermogravimetric, and [...] Read more.
Three industrial aluminosilicate wastes were studied as precursors to produce alkali-activated concrete: (i) electric arc furnace slag, (ii) municipal solid waste incineration bottom ashes, and (iii) waste glass rejects. These were characterized via X-ray diffraction and fluorescence, laser particle size distribution, thermogravimetric, and Fourier-transform infrared analyses. Distinctive combinations of anhydrous sodium hydroxide and sodium silicate solution were tried by varying the Na2O/binder ratio (8%, 10%, 12%, 14%) and SiO2/Na2O ratio (0, 0.5, 1.0, 1.5) to find the optimum solution for maximized mechanical performance. Specimens were produced and subjected to a three-step curing process: (1) 24 h thermal curing (70 °C), (2) followed by 21 days of dry curing in a climatic chamber (~21 °C, 65% RH), and (3) ending with a 7-day carbonation curing stage (5 ± 0.2% CO2; 65 ± 10% RH). Compressive and flexural strength tests were performed, to ascertain the mix with the best mechanical performance. The precursors showed reasonable bonding capabilities, thus suggesting some reactivity when alkali-activated due to the presence of amorphous phases. Mixes with slag and glass showed compressive strengths of almost 40 MPa. Most mixes required a higher Na2O/binder ratio for maximized performance, even though, contrary to expectations, the opposite was observed for the SiO2/Na2O ratio. Full article
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<p>Magnified images of a WGR sample showing the presence of (<b>a</b>) aluminum and (<b>b</b>) ceramic particles in parallel with glass particles.</p>
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<p>XRD analysis of OPC, FA, EAFS, MIBA, and WGR.</p>
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<p>Particle size distribution for all precursors.</p>
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<p>SEM images (<b>a</b>) and mapping (<b>b</b>) for WGR.</p>
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<p>TGA-DTA analysis of (<b>a</b>) OPC, (<b>b</b>) FA, (<b>c</b>) MIBA, (<b>d</b>) EAFS, and (<b>e</b>) WGR (inert argon atmosphere).</p>
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<p>FTIR spectra of OPC, FA, MIBA, EAFS, and WGR.</p>
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<p>Compressive strength values for mixes with FA, MIBA, EAFS, and WGR with Na<sub>2</sub>O/binder ratios of (<b>a</b>) 8%, (<b>b</b>) 10%, (<b>c</b>) 12%, and (<b>d</b>) 14%, respectively.</p>
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<p>Efflorescence caused by sodium carbonate precipitation on the surface of N14S0 WGR specimen.</p>
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<p>The change in color by spraying phenolphthalein solution pH indicator on (<b>a</b>) N8S0.5, (<b>b</b>) N10S0.5, (<b>c</b>) N12S0.5, and (<b>d</b>) N14S0.5 WGR mixes.</p>
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<p>Flexural strength values for mixes with FA, MIBA, EAFS, and WGR with Na<sub>2</sub>O/binder ratios of (<b>a</b>) 8%, (<b>b</b>) 10%, (<b>c</b>) 12%, and (<b>d</b>) 14%, respectively.</p>
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<p>Flexural versus compressive strengths of all alkali-activated binders of this study compared to other studies from the literature [<a href="#B92-materials-16-01923" class="html-bibr">92</a>,<a href="#B93-materials-16-01923" class="html-bibr">93</a>,<a href="#B94-materials-16-01923" class="html-bibr">94</a>,<a href="#B95-materials-16-01923" class="html-bibr">95</a>,<a href="#B96-materials-16-01923" class="html-bibr">96</a>,<a href="#B97-materials-16-01923" class="html-bibr">97</a>,<a href="#B98-materials-16-01923" class="html-bibr">98</a>,<a href="#B99-materials-16-01923" class="html-bibr">99</a>].</p>
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10 pages, 3405 KiB  
Article
Time-Gated Pulsed Raman Spectroscopy with NS Laser for Cultural Heritage
by Xueshi Bai and Vincent Detalle
Heritage 2023, 6(2), 1531-1540; https://doi.org/10.3390/heritage6020082 - 1 Feb 2023
Cited by 5 | Viewed by 2772
Abstract
Raman spectroscopy, a non-destructive reference technique, is used in heritage science to directly identify materials like pigments, minerals, or binding media. However, depending on the material, the laser source can induce a strong fluorescence signal that may mask the Raman signal during spectral [...] Read more.
Raman spectroscopy, a non-destructive reference technique, is used in heritage science to directly identify materials like pigments, minerals, or binding media. However, depending on the material, the laser source can induce a strong fluorescence signal that may mask the Raman signal during spectral detection. This photo-induced effect can prevent the detection of a Raman peak. A pulsed Raman spectroscopy, using a time-gated detection and pulsed laser, is proven capable of rejecting the fluorescence background and working with the environmental light, which makes Raman spectroscopy more adapted for in situ applications. In this paper, we investigated how an ns pulsed laser can be an excitation source of Raman spectroscopy by focusing on different parameters of laser excitation and collection. With proper implementation, this pulsed Raman technique can be used for cultural heritage with an ns pulsed laser for the first time. Full article
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<p>A Gaussian function describes the temporal profile of a 7 ns nominal duration of the laser pulse: theoretical curve (dashed line) and experimental curve (solid line).</p>
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<p>Comparison of Raman spectra from (<b>a</b>) the Paraloid B72 and (<b>b</b>) lead white sample in continuous and pulsed laser excitation. <math display="inline"><semantics> <mrow> <msub> <mi>I</mi> <mi>P</mi> </msub> </mrow> </semantics></math>: Intensity of Raman peak at 1450 cm<sup>−1</sup> (C-H bend), <math display="inline"><semantics> <mrow> <msub> <mi>I</mi> <mrow> <mi>f</mi> <mn>0</mn> </mrow> </msub> </mrow> </semantics></math> (1366 cm<sup>−1</sup>), and <math display="inline"><semantics> <mrow> <msub> <mi>I</mi> <mrow> <mi>f</mi> <mn>1</mn> </mrow> </msub> </mrow> </semantics></math> (1530 cm<sup>−1</sup>): Intensity of fluorescence adjacent to the Raman peak, <math display="inline"><semantics> <mrow> <msub> <mi>I</mi> <mi>B</mi> </msub> </mrow> </semantics></math> : Intensity of background at 2660 cm<sup>−1</sup> where no fluorescence emits.</p>
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<p>Raman spectra of Paraloid B72 obtained by three wavelengths of Nd:YAG laser harmonics: 266, 355, and 532 nm.</p>
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<p>The pulsed Raman spectra obtained by a 355 nm and 532 nm laser on the sample (<b>a</b>) Paraloid 72 after subtraction of the spectra fluorescence baseline in <a href="#heritage-06-00082-f003" class="html-fig">Figure 3</a> and (<b>b</b>) white marble [<a href="#B21-heritage-06-00082" class="html-bibr">21</a>].</p>
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<p>Raman spectra from beeswax with different laser pulse energy (power) and a detection window of 5 ns.</p>
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<p>Raman spectra from Paraloid B72 with a high resolution induced by 532 nm laser pulse recorded by different delays (<b>a</b>) −10 ns to 0 ns and (<b>b</b>) 0 ns to 10 ns. The detection windows were fixed at 10 ns, and the minus value means the detection started before the laser pulse arriving the sample surface.</p>
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<p>Global Raman spectra from Paraloid B72 with fluorescence emission induced by 355 nm (23 mJ/cm<sup>−2</sup>) laser pulse recorded by different delays (<b>a</b>) −10 ns to 0 ns and (<b>b</b>) 2 ns to 10 ns. The detection windows were fixed at 10 ns, and the minus value means the detection started before the laser pulse arriving the sample surface.</p>
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