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28 pages, 9988 KiB  
Article
Concurrent Oncolysis and Neurolesion Repair by Dual Gene-Engineered hNSCs in an Experimental Model of Intraspinal Cord Glioblastoma
by Xiang Zeng, Alexander E. Ropper, Zaid Aljuboori, Dou Yu, Theodore W. Teng, Serdar Kabatas, Esteban Usuga, Jamie E. Anderson and Yang D. Teng
Cells 2024, 13(18), 1522; https://doi.org/10.3390/cells13181522 - 11 Sep 2024
Abstract
Intramedullary spinal cord glioblastoma (ISCG) is lethal due to lack of effective treatment. We previously established a rat C6-ISCG model and the antitumor effect of F3.CD-TK, an hNSC line expressing CD and TK, via producing cytocidal 5FU and GCV-TP. However, the neurotherapeutic potential [...] Read more.
Intramedullary spinal cord glioblastoma (ISCG) is lethal due to lack of effective treatment. We previously established a rat C6-ISCG model and the antitumor effect of F3.CD-TK, an hNSC line expressing CD and TK, via producing cytocidal 5FU and GCV-TP. However, the neurotherapeutic potential of this hNSC approach has remained uninvestigated. Here for the first time, cultured F3.CD-TK cells were found to have a markedly higher oncolytic effect, which was GJIC-dependent, and BDNF expression but less VEGF secretion than F3.CD. In Rowett athymic rats, F3.CD-TK (1.5 × 106 cells/10 µL × 2), injected near C6-ISCG (G55 seeding 7 days earlier: 10 K/each) and followed by q.d. (×5/each repeat; i.p.) of 5FC (500 mg/kg/5 mL/day) and GCV (25 mg/kg/1 mL/day), robustly mitigated cardiorespiratory, locomotor, and sensory deficits to improve neurofunction and overall survival compared to animals receiving either F3.CD or F3.CD-TK+F3.CD debris formula. The F3.CD-TK regimen exerted greater tumor penetration and neural inflammation/immune modulation, reshaped C6-ISCG topology to increase the tumor’s surface area/volume ratio to spare/repair host axons (e.g., vGlut1+ neurites), and had higher post-prodrug donor self-clearance. The multimodal data and mechanistic leads from this proof-of-principle study suggest that the overall stronger anti-ISCG benefit of our hNSC-based GDEPT is derived from its concurrent oncolytic and neurotherapeutic effects. Full article
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>In vitro evaluations of F3.hNSC and G55 cells for key biofactors related to NSC functional multipotency and GDEPT. (<b>A</b>) All cell lines showed a dose-dependent increase in VEGF production when incubated separately. F3.CD-TK cells had significantly lower VEGF secretion than F3.CD, G55, and HFB2050 in the largest culturing concentration (<span class="html-italic">p</span> &lt; 0.05, one-way ANOVA with Tukey’s post hoc test; n = 9 wells/group). (<b>B</b>) Under a 1:1 ratio, the F3.CD-TK|G55 group expressed VEGF at a mean level that was statistically similar to that of G55 alone and significantly lower than F3.CD|G55, which had an average VEGF level significantly higher than the G55-only group (<span class="html-italic">p</span> &lt; 0.05: * vs. G55+F3.CD or F3.CD-TK, # vs. all other groups; two-way ANOVA with Tukey’s post hoc test; n = 9 wells/group). (<b>C</b>,<b>D</b>) ELISA of BDNF production revealed that when cultured separately, F3.CD-TK and F3.CD both had a cell dose-dependent elevation of BDNF, but at the highest cell dose, F3.CD-TK had a significantly higher mean BDNF level than F3.CD. Notably, HFB2050 prototype hNSCs as positive control cells produced the highest amount of BDNF. Coculture of F3.CD-TK or F3.CD with G55 produced BDNF that, on average, was significantly higher than that of the F3.CD-TK, F3.CD, or G55 alone group (<span class="html-italic">p</span> &lt; 0.05: * vs. G55, # vs. F3.CD; two-way ANOVA with Tukey’s post hoc test; n = 9 wells/group). (<b>E</b>) Culturing G55 cells alone for 96 h produced abundant Cx43 (grey bar) in either type of the 2-chamber system. Relative to the IRL of Cx43 in either pore size monoculture set as the reference value (100%), coculture of G55 with F3.CD-TK or F3.CD cells generated comparable group average IRLs of Cx43, which were, however, lower than G55 monoculture. Cocultured cells separated by smaller pores (ϕ = 0.4 µm) had significantly higher mean IRL values of Cx43 compared to that of the larger pore size (ϕ = 6 µm) group (<span class="html-italic">p</span> &lt; 0.05: * vs. G55, # vs. 0.4 µm/ϕ group; one-way ANOVA with Tukey’s post hoc test; n = 9 wells/group). (<b>F</b>,<b>G</b>) Cocultured G55 and F3.CD-TK exhibited IR of Cx43 (green) alongside the membrane of the DiI+/red cells including loci within the pores (arrows; ϕ = 6 µm; <b>F</b>). The general IRL of Cx43 appeared to be stronger than that of Cx26, another gap junction protein expressed in the cell membrane (green IR in <b>G</b>) (arrowhead: loci in the pores; ϕ = 6 µm), which was assessed separately (scale bar: 10 µm). (<b>H</b>–<b>K</b>) Compared to the 96 h cell culture data, monoculture of G55 for 24 h had very low expression of Cx43 (insets in <b>H</b>): confocal z-stacks) and Cx26 (insets in <b>J</b>): confocal z-stacks). Both Cx43 and Cx26 expressions were markedly increased between G55 and F3.CD-TK cells after 24 h coculturing (Cx43: insets in <b>I</b>; Cx26: insets in <b>K</b>; scale bars for <b>H</b>–<b>K</b> insets: 20 µm). F3.CD-TK cells (with high hNestin IRL: red) also formed Cx43- or Cx26-containing gap junctions (color code: white) with G55 cells that were CD133+ (green; i.e., cells showing yellowish overlapping pixels in <b>I</b>,<b>K</b>; scale bars: 25 µm/<b>H</b>–<b>K</b>).</p>
Full article ">Figure 2
<p>In vitro assessments of the oncolytic effect of F3.hNSC treatment against G55 cells. (<b>A</b>) Three days after adding 5FC (2.1 mM) to F3.CD (DiI+, upper panel) and G55 coculture, G55 cells (DiI−) were physically attached, although ~60% of the cells had immunostains for cleaved caspase-3, a sign of apoptosis (lower panel); (<b>B</b>), DiI+ F3.CD cells surrounded by caspase-3+ G55 cells). (<b>C</b>) Orthogonal optical slicing confirmed the proper IHC signal loci of hNuclei (red) and capspase-3 (green) in z-stack images of G55 cells (DiI−). (<b>D</b>) In contrast, 3 days after delivering 5-FC (2.1 mM) and GCV (12 µM), F3.CD-TK+G55 coculture had a large fraction (~60–70%) of G55 cells that had died and fallen off, with most residual attached G55 cells being cleaved caspase-3+. F3.CD-TK cells spread more widely (in <b>D</b>) than F3.CD cells that often appeared in small clusters (in <b>B</b>) in contact with G55 cells (<b>B</b>,<b>D</b>: 30 µm/scale bar; arrows, putative G55 chemoattractant diffusion direction to induce F3.hNSC migration). (<b>E</b>) F3.CD-TK regimen treatment dose-dependently killed G55 cells. GCV was more potent than 5FC when given individually, and 5FC+GCV was markedly more effective than 5FC or GCV administered alone. Treatment of 2-APB, a connexin channel antagonist, dose-dependently blocked the G55 cytotoxic effect of 40 µM GCV (inset in <b>E</b>), suggesting that the effect is GJIC dependent. (<b>F</b>) Regarding the oncolytic efficacy difference, F3.CD-TK cells were significantly more potent than F3.CD cells when only 5FC was given for 72 h. (<b>G</b>) F3.CD-TK had a significantly stronger oncolytic effect compared to F3.CD when 5FC and GCV were both applied for 72 h. (<b>H</b>) A similar degree of efficacy difference was observed in the F3.CD-TK+G55 coculture treated with the same prodrug dosages for 36 h, and the formula of 5FC+GCV exposure for 72 h had the strongest oncolytic effect (n = 9 wells/group; * <span class="html-italic">p</span> &lt; 0.05, one-way ANOVA with post hoc unpaired Student’s <span class="html-italic">t</span>-test).</p>
Full article ">Figure 3
<p>The effect of F3.CD-TK regimen on the motosensory function and overall survival of C6-ISCG animals. (<b>A</b>) C6-ISCG growth aggressively triggered the onset of the BBB score of 9 (i.e., the primary criterion of animal termination) as early as 16 days after G55 injection in the control animals that received F3.CD-TK+F3.CD cell debris+5FC&amp;GCV. Rats treated with the F3.CD-TK regimen had significantly reduced hindlimb deficits starting ~2 weeks following the treatment compared to the F3.CD formula or control cell debris group (* <span class="html-italic">p</span> &lt; 0.05, n = 6/group; two-way repeated measures ANOVA with Tukey’s post hoc test). (<b>B</b>) Kaplan–Meier curve data showed that overall survival in the F3.CD-TK-treated group was significantly longer than in the other two groups (two-sided <span class="html-italic">p</span> = 0.01, rank test and the test based on medians). The F3.CD formula did not significantly increase the survival of C6-ISCG rats relative to the control group (two-sided <span class="html-italic">p</span> &gt; 0.05, the rank test and the test based on medians). (<b>C</b>) The F3.CD-TK regimen significantly improved mean bodyweight compared to F3.CD and cell debris groups (* <span class="html-italic">p</span> &lt; 0.05 vs. F3.CD and cell debris, #<span class="html-italic">p</span> &lt; 0.05 vs. 3 d after G55; two-way repeated measures ANOVA with post hoc Tukey’s test). (<b>D</b>) Animals on the F3.CD-TK regimen had significantly better forelimb locomotor function relative to the other two groups (<span class="html-italic">p</span> &lt; 0.05: # vs. before surgery, * vs. cell debris or F3.CD; two-way repeated measures ANOVA with post hoc Tukey’s test). (<b>E</b>) Von Frey filament test revealed that rats in all three groups had a transient early phase mechanical hypersensitivity/allodynia, which was followed by a gradual development of mechanical hyposensitivity in the forepaw. The F3.CD-TK-treated animals had no discernible forepaw sensory abnormality for ~2 weeks of prodrug dosing, in contrast to the significantly perturbated sensory function shown in the other two groups. F3.CD-TK-treated animals had significantly less forepaw mechanical hyposensitivity than the other two groups during the terminal stage (<span class="html-italic">p</span> &lt; 0.05: # vs. before surgery, * vs. F3.CD or cell debris; two-way repeated measures ANOVA with post hoc Tukey’s test).</p>
Full article ">Figure 4
<p>The effect of F3.CD-TK regimen on the autonomic function of C6-ISCG rats. (<b>A</b>) A noninvasive blood pressure monitoring system was used (VPR: volume pressure recording). (<b>B</b>,<b>C</b>) Three days succeeding C6 injection of G55 cells, all animals had significantly elevated systolic blood pressure, which returned to the pre-tumor level 3–7 days after F3.hNSC administration. Three weeks following C6 tumor seeding, the control group receiving cell debris had significant systolic and diastolic blood pressure decreases compared to baseline values and those of the two treated groups. (<b>D</b>) The changes resulted in significant reductions in mean artery pressure (MAP), which were efficaciously corrected by the F3.CD-TK and F3.CD treatments (<span class="html-italic">p</span> &lt; 0.05: # vs. before surgery, * vs. cell debris or F3.CD; two-way repeated measures ANOVA with post hoc Tukey’s test). (<b>E</b>) Plethysmographic recording of conscious and free moving animals (upper panel) showed that in the termination week, the respiratory flow (RF: mL/s) pattern of the control rats was evidently abnormal (lower panel). (<b>F</b>) Additionally, the cell debris or F3.CD groups had significantly decreased respiratory rates (<span class="html-italic">f</span>: breaths/min) in weeks 1 and 2 after receiving intervention compared to pre-tumor baseline values. F3.CD-TK regimen, not F3.CD formula, maintained <span class="html-italic">f</span> within a normal range during that same period. (<b>G</b>,<b>H</b>) The reduced respiratory rate was caused by a significant increase of mean inspiration time (Ti: s) in the control group (<b>G</b>), while the mean expiratory time (Te: s) was comparable between the 3 groups (<b>H</b>). (<b>I</b>,<b>J</b>) The F3.CD-TK-treated group demonstrated significantly improved tidal volume (Vt: mL/per breath) (<b>I</b>) and minute ventilation (Ve: mL/min) (<b>J</b>) relative to the other two groups. Finally, no significant differences in the groups’ mean Vt and Ve were found between the 3 groups at the terminal stage (<span class="html-italic">p</span> &lt; 0.05: # vs. before surgery, * vs. cell debris or F3.CD; two-way repeated measures ANOVA with post hoc Tukey’s test).</p>
Full article ">Figure 5
<p>The effect of F3.CD-TK regimen on the volume, histopathological feature, and apoptosis of C6-ISCG. (<b>A</b>–<b>C</b>) Termination time gross pathology photos showed that all spinal cords had intramedullary GBs in similar sizes (i.e., the dotted areas). (<b>D</b>–<b>F</b>) A similar outcome was found in transverse histopathology images (insets: left/H&amp;E stain, middle/fluorescent confocal z-stack, and right/camera lucida image). The F3.CD-TK-treated tissue had a much wider intratumor distribution of DiI+ F3.CD-TK cells (middle inset: F3.CD-TK/<b>D</b> vs. F3.CD/<b>E</b> and cell debris/<b>F</b> as negative control). Regarding tumor topology, relative to F3.CD- or cell debris-treated tumors, post-F3.CD-TK regimen tumors had much denser and deeper longitudinal grooves and circumferential indentations, which increased the overall surface terrain (insets: <b>D</b> vs. <b>E</b>,<b>F</b>) to produce the largest surface area (S) to volume (V) ratio (see below). (<b>G</b>) Quantification of 3D tumor reconstruction data (samples in <b>D</b>–<b>F</b>) demonstrated that the mean GB volumes in the terminal stage were statistically indiscernible between the three groups. (<b>H</b>) The F3.CD-TK regimen more effectively impeded tumor growth, as per data in the scatterplot. (<b>I</b>) The mean S/V ratio of the F3.CD-TK-treated GBs was significantly higher than the other two groups (<span class="html-italic">p</span> &lt; 0.05: * vs. cell debris, ∧ vs. F3.CD; one-way ANOVA with Tukey’s post hoc test). (<b>J</b>) The average percentage of G55 cell apoptosis in F3.CD-TK and F3.CD groups was significantly higher than that of the cell debris group: F3.CD-TK-treated animals had the highest rate of activated caspase 3+ G55 cells (confocal images in the left panel; statistics in the right panel; <span class="html-italic">p</span> &lt; 0.05; one-way ANOVA with Tukey’s post hoc test; n = 6 rats/group). Scale bar: 1 mm/<b>A</b>–<b>F</b>.</p>
Full article ">Figure 6
<p>The impact of F3.CD-TK regimen on host neurite rescuing as well as neuroinflammation and neuroimmune modulation. (<b>A</b>–<b>C</b>) There was a significantly augmented group average IRL of neurofilament H (NF-H) in the host neurites (DiI−) of F3.CD-TK-treated C7 dorsolateral spinal cords within the grooved/indented interface around Rexed lamina-I (RL-I) compared to cell debris controls (n = 6/group; * <span class="html-italic">p</span> &lt; 0.01, Student’s <span class="html-italic">t</span>-test). (<b>D</b>) About 10–15% NF-H+ (upper inset) neurites expressed the growth-associated protein 43-kD (GAP-43) that is a marker of neurite growth (arrows in (<b>D</b>); bottom inset: tissue location of the images). (<b>E</b>) Confocal imaging disclosed that ~6–10% NF-H+ axons within the interface zone were ensheathed by a thin layer of myelin basic protein (MBP) in F3.CD-TK-treated tissue only. (<b>F</b>) A similar fraction (i.e., 2–10%) of the NF-H+ neurites expressed vesicular glutamate transporter 1 (vGlut 1), an instrumental molecule of the propriospinal fiber terminals. (<b>G</b>–<b>I</b>) A significantly increased GFAP IRL presented along the interface zone and mainly on the host parenchyma side (left to the dotted line; upper inset: area sampled; <b>G</b>) in F3.CD-TK-regimen-treated spinal cords relative to controls (inset: area sampled; <b>H</b>) receiving cell debris (n = 6/group; * <span class="html-italic">p</span> &lt; 0.01, Student’s <span class="html-italic">t</span>-test; <b>I</b>). Notably, cells with augmented GFAP expression contained no DiI (<b>G</b>), indicating that they were host astrocytes. DiI+ F3.CD-TK cells in the interface zone of an adjacent tissue section (dotted line in <b>G</b> lower inset) formed Cx43 gap junctions with both host cells (left side) and G55 cells (right side), which were revealed by yellow IR signals pointed by arrows in <b>G</b> lower inset. (<b>J</b>–<b>L</b>) Triple immunostaining disclosed that the F3.CD-TK regimen significantly increased the alternatively activated (arginase+/CD68+ and anti-inflammatory/immune modulatory) M2 microglia (arrowheads, <b>J</b>) quantity but decreased classically activated (CD86+/CD68+ and pro-inflammatory/cytotoxic) M1 (arrows, <b>J</b>) numbers when compared to the cell debris control formula (M2/arrowhead; M1/arrow in <b>K</b>), reducing the M1/M2 ratio (<b>L</b>; n = 6/group; * <span class="html-italic">p</span> &lt; 0.01, Student’s <span class="html-italic">t</span>-test). The M2 increase in F3.CD-TK-treated tissues mostly occurred at loci deeper inside the host spinal cord (i.e., the upper left section in <b>J</b>) while the M1 cells were concentrated in areas adjacent to the tumor interface (i.e., the lower right section in <b>J</b>). In contrast, M1 microglia distribution was more even in the control tissue (<b>K</b>). Scale bars: 250 µm/<b>A</b>,<b>B</b>, and insets; 125 µm/<b>D</b> and insets; 10 µm/<b>E</b>; 20 µm/<b>F</b> and insets; 100 µm/<b>G</b>,<b>H</b>; and 80 µm/<b>J</b>,<b>K</b>, and insets.</p>
Full article ">Figure 7
<p>Comparison of self-clearance rate between F3.CD-TK and F3.CD cells in vivo. (<b>A</b>) The mean number of DiI+ cells was significantly less in F3.CD-TK-treated animals (upper panel) than F3.CD group (lower panel). (<b>B</b>) The residual F3.CD-TK cell number, averaged from DiI+ cell numbers from 6 slices (section thickness: 20 µm), with each sampled from one consecutive 500 μm-long tissue block, was merely ~25% of that of F3.CD-treated tissues (* <span class="html-italic">p</span> &lt; 0.05, Student’s <span class="html-italic">t</span>-test). (<b>C</b>–<b>F)</b> Only ~5% of these residual F3.CD-TK cells (DiI+, <b>C</b>) expressed Ki67, a cell proliferation marker in the nucleus (<b>D</b>) and even fewer of which (~4%) had nuclear presence of cleaved capase-3 (<b>E</b>; DAPI nuclear stain in <b>F</b>), suggesting that they were in senescence after the vast majority had died off (statistics in <b>K</b>). (<b>G</b>–<b>J</b>) In contrast, ~72% of the residual F3.CD cells (<b>G</b>) exhibited nuclear IR of Ki67 (i.e., proliferating, <b>H</b>) and cleaved caspase-3 (i.e., experiencing apoptosis; <b>I</b>; DAPI nuclear stain in <b>J</b>; statistics in <b>L</b>). The F3.CD-TK/5FC+GCV regimen therapy more effectively eliminated proliferating donor cells. Scale bars: 700 µm/<b>A</b>; 40 µm/<b>C</b>–<b>J</b>.</p>
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17 pages, 6425 KiB  
Article
Quantile Regression Illuminates the Heterogeneous Effect of Water Quality on Phytoplankton in Lake Taihu, China
by Lu Wang, Shuo Liu, Shuqin Ma, Zhongwen Yang, Yan Chen, Wei Gao, Qingqing Liu and Yuan Zhang
Water 2024, 16(18), 2570; https://doi.org/10.3390/w16182570 - 10 Sep 2024
Viewed by 206
Abstract
Lake Taihu, a subtropical shallow lake in the Yangtze River Basin, is the third-largest freshwater lake in China. It serves not only as a crucial source of drinking water and an ecological resource but also holds significant economic, tourism, and fisheries value. Phytoplankton, [...] Read more.
Lake Taihu, a subtropical shallow lake in the Yangtze River Basin, is the third-largest freshwater lake in China. It serves not only as a crucial source of drinking water and an ecological resource but also holds significant economic, tourism, and fisheries value. Phytoplankton, a vital component of aquatic ecosystems, plays a critical role in nutrient cycling and maintaining water structure. Its community composition and concentration reflect changes in the aquatic environment, making it an important biological indicator for monitoring ecological conditions. Understanding the impact of water quality on phytoplankton is essential for maintaining ecological balance and ensuring the sustainable use of water resources. This paper focuses on Lake Taihu, with water samples collected in February, May, August, and November from 2011 to 2019. Using quantile regression, a robust statistical analysis tool, the study investigates the heterogeneous effects of water quality on phytoplankton and seasonal variations. The results indicate significant seasonal differences in water quality in Lake Taihu, which substantially influence phytoplankton, showing weakly alkaline characteristics. When phytoplankton concentrations are low, pondus hydrogenii (pH), chemical oxygen demand (COD), total phosphorus (TP), total nitrogen (TN), water temperature (WT), and conductivity significantly affect them. At medium concentrations, COD, TP, TN, and WT have significant effects. At high concentrations, transparency and dissolved oxygen (DO) significantly impact phytoplankton, while TP no longer has a significant effect. These findings provide valuable insights for policymakers and environmental managers, supporting the prevention and control of harmful algal blooms in Lake Taihu and similar aquatic systems. Full article
(This article belongs to the Section Biodiversity and Functionality of Aquatic Ecosystems)
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Figure 1

Figure 1
<p>Location of Lake Taihu in China and sampling sites in Lake Taihu.</p>
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<p>Pearson correlation coefficient matrix between phytoplankton and each water quality parameters. Blue indicates the positive correlation, and red indicates the negative correlation.</p>
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<p>Scatter plot between phytoplankton and eight water quality variables. The fitting lines of univariate linear regression and univariate quantile regression (<math display="inline"><semantics> <mrow> <mi>τ</mi> <mo>=</mo> <mn>0.5</mn> </mrow> </semantics></math>) and the <span class="html-italic">t</span>-value and <span class="html-italic">p</span>-value of the significance test are shown. Pink indicates the linear regression results, and blue indicates the quantile regression results.</p>
Full article ">Figure 3 Cont.
<p>Scatter plot between phytoplankton and eight water quality variables. The fitting lines of univariate linear regression and univariate quantile regression (<math display="inline"><semantics> <mrow> <mi>τ</mi> <mo>=</mo> <mn>0.5</mn> </mrow> </semantics></math>) and the <span class="html-italic">t</span>-value and <span class="html-italic">p</span>-value of the significance test are shown. Pink indicates the linear regression results, and blue indicates the quantile regression results.</p>
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<p>Quantile regression coefficient plot under different quantiles. Blue line indicates quantile regression coefficients, Blue shade indicates the confidence intervals under different quantiles, and Black indicates linear regression coefficient and confidence interval.</p>
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<p>Violin plot of phytoplankton distribution under different seasons.</p>
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<p>Quantile regression coefficient plot under different seasons.</p>
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23 pages, 9095 KiB  
Article
Characterizing the Tumor Microenvironment and Its Prognostic Impact in Breast Cancer
by Wenjuan Zhang, Alex Lee, Amit K. Tiwari and Mary Qu Yang
Cells 2024, 13(18), 1518; https://doi.org/10.3390/cells13181518 - 10 Sep 2024
Viewed by 254
Abstract
The tumor microenvironment (TME) is crucial in cancer development and therapeutic response. Immunotherapy is increasingly recognized as a critical component of cancer treatment. While immunotherapies have shown efficacy in various cancers, including breast cancer, patient responses vary widely. Some patients receive significant benefits, [...] Read more.
The tumor microenvironment (TME) is crucial in cancer development and therapeutic response. Immunotherapy is increasingly recognized as a critical component of cancer treatment. While immunotherapies have shown efficacy in various cancers, including breast cancer, patient responses vary widely. Some patients receive significant benefits, while others experience minimal or no improvement. This disparity underscores the complexity and diversity of the immune system. In this study, we investigated the immune landscape and cell–cell communication within the TME of breast cancer through integrated analysis of bulk and single-cell RNA sequencing data. We established profiles of tumor immune infiltration that span across a broad spectrum of adaptive and innate immune cells. Our clustering analysis of immune infiltration identified three distinct patient groups: high T cell abundance, moderate infiltration, and low infiltration. Patients with low immune infiltration exhibited the poorest survival rates, while those in the moderate infiltration group showed better outcomes than those with high T cell abundance. Moreover, the high cell abundance group was associated with a greater tumor burden and higher rates of TP53 mutations, whereas the moderate infiltration group was characterized by a lower tumor burden and elevated PIK3CA mutations. Analysis of an independent single-cell RNA-seq breast cancer dataset confirmed the presence of similar infiltration patterns. Further investigation into ligand–receptor interactions within the TME unveiled significant variations in cell–cell communication patterns among these groups. Notably, we found that the signaling pathways SPP1 and EGF were exclusively active in the low immune infiltration group, suggesting their involvement in immune suppression. This work comprehensively characterizes the composition and dynamic interplay in the breast cancer TME. Our findings reveal associations between the extent of immune infiltration and clinical outcomes, providing valuable prognostic information for patient stratification. The unique mutations and signaling pathways associated with different patient groups offer insights into the mechanisms underlying diverse tumor immune infiltration and the formation of an immunosuppressive tumor microenvironment. Full article
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Figure 1
<p>Analysis of breast cancer patient subgroups derived from immune infiltration profiles. (<b>a</b>) Hierarchical clustering based on immune infiltration levels revealed patient groups in the TCGA dataset: high T cell abundance (S2), moderate infiltration (S1), and low infiltration (S3). (<b>b</b>) The moderate infiltration group (S1) showed the best survival rate, while the low infiltration group (S3) had the poorest survival. (<b>c</b>) Immune checkpoint genes <span class="html-italic">PDCD1</span>, <span class="html-italic">CD274</span>, and <span class="html-italic">CTLA4</span>, as well as genes associated with T cell response, <span class="html-italic">GZMB</span>, and <span class="html-italic">IFNG</span>, were significantly more highly expressed in the T cell abundance group (S2) than in the other two groups (S1 and S3). **** <math display="inline"><semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.0001</mn> </mrow> </semantics></math>. (<b>d</b>) The moderate infiltration group (S1) demonstrated the highest stromal score, while the low infiltration group (S3) had the highest tumor purity. The <span class="html-italic">p</span>-values were calculated using the Mann–Whitney U test.</p>
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<p>Analysis of immune infiltration and activity scores. (<b>a</b>) Comparison of infiltration levels of 24 innate and adaptive immune cells, along with activity scores for angiogenesis and antigen-presenting machinery (APM), across the three patient groups. The immune cells were ranked based on differences between the moderate infiltration (S1) and low infiltration (S3) groups, which were associated with favorable and poor patient survival, respectively. (<b>b</b>) Pearson correlation analysis of immune cell infiltration levels and activity levels of angiogenesis and APM.</p>
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<p>(<b>a</b>) Comparison of tumor burden across the three immune infiltration groups. Mann–Whitney tests revealed a significantly higher tumor burden in the high T cell abundance (S2) group compared to the moderate infiltration (S1) and the low infiltration (S3) groups. (<b>b</b>) Analysis of amplification regions in the genomes among patients in distinct groups. The moderate infiltration group (S1) exhibited significantly lower rates of amplification compared to the other groups, as determined by Mann–Whitney tests. (<b>c</b>) Analysis of deletion regions in the genomes among patients in distinct groups. The moderate infiltration group (S1) showed significantly lower deletion rates than the other two groups, as determined by Mann–Whitney tests. (<b>d</b>) Spearman correlation analysis between tumor burden and the infiltration of each immune cell type, as well as angiogenesis and APM activity scores. * <math display="inline"><semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.05</mn> </mrow> </semantics></math>, ** <math display="inline"><semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.01</mn> </mrow> </semantics></math>, *** <math display="inline"><semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.001</mn> </mrow> </semantics></math>. (<b>e</b>) Identification of the top mutated genes in the three immune infiltration groups. <span class="html-italic">TP53</span> was highly mutated in the high T cell abundance (S2) group, whereas <span class="html-italic">PIK3CA</span> was predominantly mutated in the moderate infiltration group (S1).</p>
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<p>Analysis of single-cell RNA sequencing data from breast cancer patients. (<b>a</b>) Visualization of major cell types in the tumor microenvironment (TME) using UMAP. (<b>b</b>) Hierarchical clustering analysis of the pseudo-bulk expression data revealed three distinct infiltration groups: SC1, SC2, and SC3. These groups, represented by red, yellow, and purple sidebars, respectively, closely mirror the groups identified in the TCGA bulk RNA sequencing data (S1, S2, and S3). (<b>c</b>) Distribution of the three infiltration groups across different cell populations. (<b>d</b>) Evaluation of stromal score and tumor purity across the three groups, demonstrating trends in SC1, SC2, and SC3 similar to those observed in S1, S2, and S3 from the TCGA dataset.</p>
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<p>Overview of the cell–cell communications in the immune-active (SC1) and immune-suppressed (SC3) groups. (<b>a</b>) The number of interactions (<b>left</b>) and interaction strength (<b>right</b>) within each group. (<b>b</b>) Changes in the number (<b>left</b>) and strength (<b>right</b>) of cell–cell communications between the immune-active and -suppressed groups. Blue arrows indicate a decrease in the number or strength of interactions in the immune-suppressed group compared to the immune-active group, while red arrows indicate an increase in these metrics in the immune-suppressed group. In the weighted directed graphs, the arrows represent the signaling pathways, pointing from the signal-originating cell type (ligand-producing) to the target cell type (signal-receiving). The width of the arrows reflects the differences in the number or strength of communication interactions between the two groups. (<b>c</b>) Detailed analysis of differential cell–cell communication numbers (<b>left</b>) and communication strength (<b>right</b>) between the immune-active and -suppressed groups. Cell types are plotted on the x-axis as receivers and on the y-axis as senders of communication signals. The color gradient from red to blue indicates decreasing values in the number or strength of interactions in the immune-suppressed group relative to the immune-active group.</p>
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<p>Cell–cell communication patterns coordinated by various cell types and signal pathways. This figure illustrates four communication patterns (P1, P2, P3, and P4) linking cell types and signaling pathways within the TME of the immune-active and -suppressed groups. The color gradient from red to blue indicates the probability of communication, ranging from 1 (high) to 0 (low). (<b>a</b>) Incoming signals in the immune-active group: The left panel displays signal-receiving cell types, while the right panel shows the pathways involved in these communication patterns. (<b>b</b>) Outgoing signals in the immune-active group: The left panel illustrates signal-sending cell types, with the right panel depicting the pathways involved. (<b>c</b>) Incoming signals in the immune suppressive group: The left panel presents signal-sending cell types, and the right panel shows the pathways involved in these communication patterns. (<b>d</b>) Outgoing signals in the immune-suppressed group: The left panel features signal-receiving cell types, while the right panel displays the associated pathways.</p>
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<p>Pathways in the immune-active (SC1) and immune-suppressed (SC3) groups: (<b>a</b>) Functional similarity clusters of signaling pathways in the immune-active and immune-suppressed groups. (<b>b</b>) Overlapping pathways ranked based on functional differences. (<b>c</b>) Overlapping pathways ranked based on structural differences. (<b>d</b>) Heatmap illustrating the relative significance of each cell type derived from network centrality measures within the IGF signaling network in the immune-active group (top panel) and immune-suppressed group (bottom panel). (<b>e</b>) Ranking of signaling pathways based on their involvement in the immune-active (SC1) and immune-suppressed (SC3) groups. (<b>f</b>) Interactions of the SPP1 and EGF pathways with various cell types in the immune-active (SC1) and immune-suppressed (SC3) groups. (<b>g</b>) Top panel: Contribution of ligand–receptor pairs in the SPP1 pathway. Bottom panel: Contribution of ligand–receptor pairs in the EGF pathway.</p>
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15 pages, 3019 KiB  
Article
Spatial Variability in Soil Water-Physical Properties in Southern Subtropical Forests of China
by Lili Han, Chao Wang, Jinghui Meng and Youjun He
Forests 2024, 15(9), 1590; https://doi.org/10.3390/f15091590 - 10 Sep 2024
Viewed by 197
Abstract
Quantification of soil water-physical properties and their spatial variation is important to better predict soil structure and functioning, as well as associated spatial patterns in the vegetation. The provision of site-specific soil data further facilitates the implementation of enhanced land use and management [...] Read more.
Quantification of soil water-physical properties and their spatial variation is important to better predict soil structure and functioning, as well as associated spatial patterns in the vegetation. The provision of site-specific soil data further facilitates the implementation of enhanced land use and management practices. Using geostatistical methods, this study quantified the spatial distribution of soil bulk density (SBD), soil moisture (SM), capillary water-holding capacity (CWHC), capillary porosity (CP), non-capillary porosity (NCP), and total porosity (TP) in southern subtropical forests located at the Tropical Forest Research Center in Pingxiang City, China. A topographic map (scale = 1:10,000) was used to create a grid of l km squares across the study area. At the intersections of the grid squares, the described soil water-physical properties were measured. By calculating the coefficient of variation for each soil water-physical property, all measured soil water-physical properties were found to show moderate spatial heterogeneity. Exponential, gaussian, spherical, and linear models were used to fit the semivariograms of the measured soil water-physical properties. Across all soil water-physical properties, the range A0 variable (i.e., the separation distance between the semivariance and the sill value) measured between 3419 m and 14,156 m. The nugget-to-sill ratio ranged from 9 to 41%, indicating variations in the level of spatial autocorrelation among the soil water-physical properties. Many of the soil water-physical properties were strongly correlated (as assessed using Pearson correlation coefficients). Spatial distribution maps of the soil water-physical properties created via ordinary kriging (OK) showed that most water-physical properties had clumped (aggregated) distributions. SBD showed the opposite spatial pattern to SM and CWHC. Meanwhile, CP and TP showed similar distributions. Full article
(This article belongs to the Section Forest Soil)
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<p>Distribution of the 238 sample plots within the study area and location of the study area within China.</p>
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<p>Semivariograms with fitted models for each soil water-physical property.</p>
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<p>Cross-validation of ordinary kriging interpolation of soil water-physical properties (the dashed line represents a 1:1 relationship).</p>
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<p>Thematic maps of soil water-physical properties produced using OK models and interpolation.</p>
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13 pages, 3140 KiB  
Article
A New Numerically Improved Transient Technique for Measuring Thermal Properties of Anisotropic Materials
by Svetozár Malinarič, Peter Bokes and Goran Bulatovič
Thermo 2024, 4(3), 394-406; https://doi.org/10.3390/thermo4030021 - 10 Sep 2024
Viewed by 185
Abstract
A new transient technique of the thermal conductivity and diffusivity measurement for anisotropic materials is presented and validated. It is based on measuring the through-plane properties using the extended dynamic plane source (EDPS) method and in-plane conductivity employing the transient plane source (TPS) [...] Read more.
A new transient technique of the thermal conductivity and diffusivity measurement for anisotropic materials is presented and validated. It is based on measuring the through-plane properties using the extended dynamic plane source (EDPS) method and in-plane conductivity employing the transient plane source (TPS) and modified dynamic plane source (MDPS) methods. The key advantage of this technique is that only one pair of specimens is required for measurements. While the EDPS method is implemented on real measurements, the TPS and MDPS are applied to the finite elements method (FEM) simulation of the experiment. The accuracy of the results is enhanced by the application of the FEM and is better than 1% for materials with through-plane conductivity of less than 2 W m−1 K−1 and a specimen thickness of 9 mm. Full article
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<p>Schematic diagram of the TPS setup and bifilar spiral structure of the sensor Hot Disk Type 5501 (−253 to 300 °C) [<a href="#B26-thermo-04-00021" class="html-bibr">26</a>].</p>
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<p>Schematic diagram of the EDPS setup.</p>
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<p>The experimental setup of the MDPS method.</p>
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<p>The numerical mesh in MDPS method simulation.</p>
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<p>Comparison between analytical and FEM temperature responses for PMMA at 2.84 mm specimen thickness.</p>
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15 pages, 11327 KiB  
Article
An Investigation into Mechanical Properties of 3D Printed Thermoplastic-Thermoset Mixed-Matrix Composites: Synergistic Effects of Thermoplastic Skeletal Lattice Geometries and Thermoset Properties
by Saleh Khanjar, Srimanta Barui, Kunal Kate and Kameswara Pavan Kumar Ajjarapu
Materials 2024, 17(17), 4426; https://doi.org/10.3390/ma17174426 - 9 Sep 2024
Viewed by 284
Abstract
This study aims to develop thermoplastic (TP) and thermoset (TS) based mixed matrix composite using design dependent physical compatibility. Using thermoplastic-based (PLA) skeletal lattices with diverse patterns (gyroid and grid) and different infill densities (10% and 20%) followed by infiltration of two different [...] Read more.
This study aims to develop thermoplastic (TP) and thermoset (TS) based mixed matrix composite using design dependent physical compatibility. Using thermoplastic-based (PLA) skeletal lattices with diverse patterns (gyroid and grid) and different infill densities (10% and 20%) followed by infiltration of two different thermoset resin systems (epoxy and polyurethane-based) using a customized FDM 3D printer equipped with a resin dispensing unit, the optimised design and TP-TS material combination was established for best mechanical performance. Under uniaxial tensile stress, the failure modes of TP gyroid structures with polyurethane-based composites included ‘fiber pull-out’, interfacial debonding and fiber breakage, while epoxy based mixed matrix composites with all design variants demonstrated brittle failure. Higher elongation (higher area under curve) was observed in 20% infilled gyroid patterned composite with polyurethane matrix indicating the capability of operation in mechanical shock absorption application. Electron microscopy-based fractography analysis revealed that thermoset matrix properties governed the fracture modes for the thermoplastic phase. This work focused on the strategic optimisation of both toughness and stiffness of mixed matrix composite components for rapid fabrication of construction materials. Full article
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<p>nTopology designs showcasing the thermoset phase (<b>left</b>), PLA thermoplastic phase (<b>middle</b>), and the resulting hybrid composite structure for Gyroid and Grid designs at 10% and 20% infill densities (<b>right</b>).</p>
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<p>Custom mold fabrication process involving 3D printing of customised CAD, silicon casting within the 3D printed mold, and the resulting flexible silicon mold. On the right, the PLA skeletons were kept in the silicon mould and the custom designed resin infiltration assembly dispensed the epoxy and polyurethane resin ‘on-demand’.</p>
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<p>Schematic representation of the process of developing hybrid mixed matrix composites (thermoset-thermoplastic).</p>
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<p>FTIR spectroscopy revealing the chemical structure of the skeleton PLA (<b>A</b>) and different thermoset matrix resins [epoxy (<b>B</b>) and polyurethane (<b>C</b>), both cured and uncured].</p>
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<p>Representative stress-strain curves for mixed matrix composites of epoxy with PLA and polyurethane with PLA for (<b>a</b>) Grid and (<b>b</b>) Gyroid infill designs. The uniaxial tensile behaviour of the baseline materials are shown in (<b>c</b>).</p>
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<p>Summary of the ultimate tensile strength (UTS) and % elongation of 3D printed PLA thermoplastic—epoxy and PU based thermoset mixed matrix composites. (<b>a</b>) demonstrates the UTS for the grid and gyroid infill designs with two infill densities for both types of resin infiltrations, while (<b>b</b>) showcase(ed the % elongation values of the same specimens. Young’s moduli of all the baseline and mixed matrix composites are represented in (<b>c</b>).</p>
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<p>Optical microscope images of the fractured surfaces after tensile tests. The top panel (<b>a</b>) shows the fractured interfaces of different mixed matrices with PLA–polyurethane system, while the bottom panel (<b>b</b>) represents the fracture behavior of the specimens with PLA–epoxy based mixed matrix composites after tensile tests.</p>
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<p>Scanning electron microscopy-based fractography studies for PLA skeletal lattice-based composites of epoxy and polyurethane matrices. Top panel (<b>a</b>,<b>b</b>) demonstrates the failure trend of PLA-polyurethane based mixed matrix composites, while the bottom panel (<b>c</b>–<b>f</b>) represents the brittle failure modes of the PLA-epoxy based composite systems.</p>
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23 pages, 8143 KiB  
Article
Enhancing Remote Sensing Water Quality Inversion through Integration of Multisource Spatial Covariates: A Case Study of Hong Kong’s Coastal Nutrient Concentrations
by Zewei Zhang, Cangbai Li, Pan Yang, Zhihao Xu, Linlin Yao, Qi Wang, Guojun Chen and Qian Tan
Remote Sens. 2024, 16(17), 3337; https://doi.org/10.3390/rs16173337 - 8 Sep 2024
Viewed by 597
Abstract
The application of remote sensing technology for water quality monitoring has attracted much attention recently. Remote sensing inversion in coastal waters with complex hydrodynamics for non-optically active parameters such as total nitrogen (TN) and total phosphorus (TP) remains a challenge. Existing studies build [...] Read more.
The application of remote sensing technology for water quality monitoring has attracted much attention recently. Remote sensing inversion in coastal waters with complex hydrodynamics for non-optically active parameters such as total nitrogen (TN) and total phosphorus (TP) remains a challenge. Existing studies build the relationships between remote sensing spectral data and TN/TP directly or indirectly via the mediation of optically active parameters (e.g., total suspended solids). Such models are often prone to overfitting, performing well with the training set but underperforming with the testing set, even though both datasets are from the same region. Using the Hong Kong coastal region as a case study, we address this issue by incorporating spatial covariates such as hydrometeorological and locational variables as additional input features for machine learning-based inversion models. The proposed model effectively alleviates overfitting while maintaining a decent level of accuracy (R2 exceeding 0.7) during the training, validation and testing steps. The gap between model R2 values in training and testing sets is controlled within 7%. A bootstrap uncertainty analysis shows significantly improved model performance as compared to the model with only remote sensing inputs. We further employ the Shapely Additive Explanations (SHAP) analysis to explore each input’s contribution to the model prediction, verifying the important role of hydrometeorological and locational variables. Our results provide a new perspective for the development of remote sensing inversion models for TN and TP in similar coastal waters. Full article
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<p>Model workflow (The red blocks represent steps involving only remote sensing data as input, while the blue blocks represent steps involving both remote sensing and hydrometeorological locational data as input).</p>
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<p>Map of the study area (Blue dots denote monitoring stations; ‘ROI’ represents regions of interests; ‘HKG’ represents Hong Kong international airport; refer to <a href="#sec2dot2dot1-remotesensing-16-03337" class="html-sec">Section 2.2.1</a> for details regarding the water quality parameters monitored by the stations).</p>
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<p>The correlation coefficients between the WQPs and remote sensing reflectance.</p>
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<p>The temporal distribution of matched data pairs (MODIS, ERA5 and in situ data).</p>
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<p>The statistics histogram of matched data pairs (MODIS, ERA5 and in situ data).</p>
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<p>Training Set, Test Set and Validation Set performance of inversion models (<b>a</b>,<b>b</b>) TP (<b>c</b>,<b>d</b>) TN.</p>
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<p>Uncertainty analysis of model (<b>a</b>,<b>b</b>) TP and (<b>c</b>,<b>d</b>) TN. The uncertainty analysis is performed on the test set samples using bootstrap resampling, conducted 1000 times. The Confidence Interval Coverage Ratio (CR) quantifies the proportion of true values that fall within the confidence interval, with a higher CR indicating stronger model reliability. The Relative Confidence Interval (CI) Width, shown as a percentage, reflects the uncertainty of the model’s predictions. A smaller Relative CI Width signifies lower uncertainty, indicating that the model’s predictions are more tightly concentrated around the estimated values.</p>
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<p>Average concentration during 2003–2019 (<b>a</b>) TP (<b>b</b>) TN (Shenzhen Bay, located on the border between Hong Kong and Shenzhen, is selected due to its high nutrient pollution from urban and industrial runoff. Tuen Mun, situated in the northwestern New Territories, and Lantau Island, the largest island in Hong Kong, are chosen for their diverse hydrodynamic conditions and moderate pollution levels).</p>
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<p>Interannual change in estimated TP and TN concentrations during 2003–2019 (<b>a</b>) Shenzhen Bay Area (<b>b</b>) Tuen Mun and Lantau Island.</p>
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<p>Highest season for average concentration during 2003–2019 (<b>a</b>) TP and (<b>b</b>) TN.</p>
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<p>SHAP summary plots (<b>a</b>) TP model (<b>b</b>) TN model (SHAP values represent the impact of each feature on the model’s predictions. Higher SHAP values indicate greater importance of the feature in predicting TP and TN concentrations).</p>
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<p>SHAP dependence plots of significant features (<b>a</b>–<b>c</b>) TP model (<b>d</b>–<b>f</b>) TN model.</p>
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<p>Spatial and temporal distribution of SHAP values for spectral bands (left) and predicted concentrations (right) (<b>a</b>) TP model (<b>b</b>) TN model.</p>
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<p>Spatial distribution of hydrological and meteorological data during 2003–2019 (<b>a</b>) Total Precipitation (<b>b</b>) Surface Pressure (<b>c</b>) Temperature.</p>
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<p>Yearly average direction and intensity of winds during 2003–2019.</p>
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16 pages, 790 KiB  
Article
Dietary Effects of Black-Oat-Rich Polyphenols on Production Traits, Metabolic Profile, Antioxidative Status, and Carcass Quality of Fattening Lambs
by Zvonko Antunović, Željka Klir Šalavardić, Boro Mioč, Zvonimir Steiner, Mislav Đidara, Vinko Sičaja, Valentina Pavić, Lovro Mihajlović, Lidija Jakobek and Josip Novoselec
Agriculture 2024, 14(9), 1550; https://doi.org/10.3390/agriculture14091550 - 7 Sep 2024
Viewed by 278
Abstract
The study aimed to establish the dietary effects of black oat rich in polyphenols on the production traits, metabolic profile, antioxidant status, and carcass quality of fattening lambs, after weaning. In the BO group, in the feed mixture, common oats replaced the black [...] Read more.
The study aimed to establish the dietary effects of black oat rich in polyphenols on the production traits, metabolic profile, antioxidant status, and carcass quality of fattening lambs, after weaning. In the BO group, in the feed mixture, common oats replaced the black oat compared to the CO group. The research comprehensively investigated production indicators, blood metabolic profile, antioxidant status, and lamb carcass quality. No significant differences were found in the fattening or slaughter characteristics of lamb carcasses, except for lower pH1 values in BO lamb carcasses. Significant increases in RBC, HCT, and MCV levels as well as TP, ALB, and GLOB concentrations and GPx and SOD activities in the blood of BO lambs were found. The glucose and EOS content as well as the activity of the enzymes ALT and ALP were significantly lower in the blood of the BO group than in the CO group. In the liver, the DPPH activity was significantly higher in the BO lambs compared to the CO lambs. The observed changes in glucose, protein metabolism, and antioxidant status in the blood and tissues of lambs indicate that the use of polyphenol-rich black oats in the diet of lambs under stress conditions is justified. Full article
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<p>Content of TBARS (reactive thiobarbituric acid substances) in muscle (musculus semimembranosus), liver, and kidney of lambs from the CO (control oat) and BO groups (black oat).</p>
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<p>DPPH (2,2-diphenyl-1-picrylhydrazyl radical) scavenging activity in muscle (musculus semimembranosus), liver, and kidney of lambs from CO (control oat) and BO groups (black oat); * <span class="html-italic">p</span>-values for DPPH-liver is 0.031.</p>
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17 pages, 3699 KiB  
Article
Application of Immobilized Microorganism Gel Beads in Black-Odor Water with High Nitrogen and Phosphorus Removal Performance
by Fengbin Zhao, Shumin Liu, Xin Fang and Ning Yang
Water 2024, 16(17), 2534; https://doi.org/10.3390/w16172534 - 7 Sep 2024
Viewed by 315
Abstract
Black-odor water, which is caused by the excessive accumulation of nitrogen and phosphorus in water, is a significant problem. Immobilized microorganisms are considered to be an effective technical solution, but there are still many key parameters to be determined, such as organic matter [...] Read more.
Black-odor water, which is caused by the excessive accumulation of nitrogen and phosphorus in water, is a significant problem. Immobilized microorganisms are considered to be an effective technical solution, but there are still many key parameters to be determined, such as organic matter dissolution, insufficient stability, and insufficient phosphorus removal capacity, among other problems. In this study, the optimum raw material ratios of immobilized microorganism gel beads were determined by means of a response surface experiment. The optimal ratio of raw materials was 5% polyvinyl alcohol (PVA), 1% sodium alginate (SA), and 6% bacterial powder. In addition, the nitrogen and phosphorus removal performance of the materials was improved by loading inorganic compounds, such as 0.5 wt.% zeolite, 0.5 wt.% iron powder, and 0.2 wt.% activated carbon. Tolerance analysis determined that these gel beads could maintain a good performance in a series of harsh environments, such as during intense agitation, at high temperatures, and at low pH values, etc. The total nitrogen (TN), ammonia nitrogen (NH3-N), and phosphorus (TP) removal efficiencies were 88.9%, 90%, and 95%. Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
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<p>Schematic diagram of the simulated device for immobilized microorganisms to treat contaminated water.</p>
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<p>The response surface 3D maps of NH<sub>3</sub>-N removal rates with the variation sources (5% bacterial dose (<b>a</b>), 1% SA content (<b>b</b>), and 5% PVA content (<b>c</b>)).</p>
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<p>The covalent immobilization of microbial cells on microchannel surfaces. SEM of common carrier (<b>a</b>) and immobilized microorganism (<b>b</b>) surface; SEM diagram of immobilized gel beads (surface structure (<b>c</b>) and internal structure (<b>d</b>)); the CLSM images of the granules of immobilized beads (living cells (green) (<b>e</b>), dead cells (red) (<b>f</b>), and combined image of living and dead cells (<b>g</b>)).</p>
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<p>The concentration of TOC change curves of the gel beads with time under different cross-linking time conditions (<b>a</b>), concentrations of calcium chloride (<b>b</b>), and PVA viscosities (<b>c</b>).</p>
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<p>Total amounts of nitrogen (<b>a</b>), ammonia nitrogen (<b>b</b>), and phosphorus (<b>c</b>) removed by immobilized microorganism loaded with zeolite; total nitrogen (<b>d</b>), ammonia nitrogen (<b>e</b>), and phosphorus (<b>f</b>) removal by immobilized microorganisms loaded by iron powder; total nitrogen (<b>g</b>), ammonia nitrogen (<b>h</b>), and phosphorus (<b>i</b>) removal by immobilized microorganism loaded with activated carbon.</p>
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<p>The proportion of complete particles and damaged particles in the immobilized microorganism particle oscillation experiment (<b>a</b>) should be changed, and the relationship between the repeated use of immobilized microorganisms and the removal rate of ammonia nitrogen (<b>b</b>).</p>
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<p>Removal of nitrogen and phosphorus pollutants by immobilized microorganisms and non-immobilized agent under different temperature conditions (<b>a</b>) and OD600 changes by immobilized microorganisms and non-immobilized agent under different pH conditions (<b>b</b>).</p>
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<p>The total nitrogen (<b>a</b>), ammonia nitrogen (<b>b</b>), and phosphate (<b>c</b>) concentration changes in black and odorous water.</p>
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<p>Changes in microbial community structure of the black-odor water before and after treatment (genus level).</p>
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24 pages, 6101 KiB  
Article
Potential Impact of Drought and Rewatering on Plant Physiology and Fruit Quality in Long-Shelf-Life Tomatoes
by Cristina Patanè, Sarah Siah, Valeria Cafaro, Salvatore L. Cosentino and Sebastiano A. Corinzia
Agronomy 2024, 14(9), 2045; https://doi.org/10.3390/agronomy14092045 - 6 Sep 2024
Viewed by 391
Abstract
In this study, the effects of repeated cycles of drying and rehydration on some physiological traits were assessed in long shelf-life tomatoes cultivated in a typical semi-arid area of Southern Italy. Three Sicilian landraces (‘Custonaci’, ‘Salina’, and ‘Vulcano’) from the germplasm collection at [...] Read more.
In this study, the effects of repeated cycles of drying and rehydration on some physiological traits were assessed in long shelf-life tomatoes cultivated in a typical semi-arid area of Southern Italy. Three Sicilian landraces (‘Custonaci’, ‘Salina’, and ‘Vulcano’) from the germplasm collection at CNR-IBE (Catania, Italy) and a commercial tomato mini-plum (‘Faino Hy., control) were investigated under three water regimes: DRY (no irrigation), IRR (long-season full irrigation) and REW (post-drought rewaterings). Net photosynthetic assimilation rate (Pn), leaf transpiration (E), stomatal conductance (gs), instantaneous water use efficiency (WUEi), leaf intercellular CO2 (Ci, ppm), and leaf temperature (°C), were measured during the growing season. At harvest (late July), fruit production per plant was measured and ripened fruits were analysed for total solids (TS), soluble solids (SS), reducing sugars (RS), vitamin C (AscA), and total phenols (TP). Pn promptly responded to rewatering (REW), quickly increasing immediately after irrigation, and declined with soil drying up. All genotypes had similar physiological pathways in DRY, but in IRR, ‘Faino’ had higher Pn (up to 31 μmol CO2 m−2s−1) and E (up to 18 mmol H2O m−2s−1). Stomatal conductance (gs) after rewatering steeply increased and quickly declined after that. All local landraces had the same gs in IRR and REW. Variations in RWC were less pronounced than those in other physiological parameters. WUEi in REW and DRY proceeded similarly (up to 3 μmol CO2 mmol H2O). Irrigation in REW significantly promoted plant productivity over the DRY control (up to +150% in ‘Vulcano’). TS and SS in REW were lower than those in DRY, but higher (+19 and +7%, respectively) than in IRR. Vitamin C was greater in DRY and REW (26 and 18% higher than in IRR, respectively). TP in all local tomatoes were significantly higher (up to +29% in ‘Vulcano’) than those in the commercial control. Water regime had a minor effect on TP in ‘Custonaci’ and ‘Salina’. Principal Component Analysis (PCA) provided information on the changes in physiological and fruit quality traits in tomatoes in relation to cultivars and water regimes. The results of this study also revealed that a water-saving irrigation strategy where few irrigations are applied after prolonged periods of drought might be profitable in terms of fruit production enhancement in long shelf-life tomatoes and that limited rewaterings in most cases, help retaining high levels of fruit quality traits. Full article
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<p>Meteorological data recorded during the field experiment.</p>
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<p>Soil water deficit at a depth of 0.40 m in each irrigation treatment. The constant horizontal short dashed lines indicate the empirical minimum threshold for irrigation in IRR.</p>
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<p>Course of net photosynthetic assimilation rate (<span class="html-italic">P</span>n, μmol CO<sub>2</sub> m<sup>−2</sup>s<sup>−1</sup>) during the field experiment in the four tomato genotypes under different water regimes. Vertical arrows indicate the time of irrigation in the REW. Small vertical bars indicate the standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Effect of interaction between ‘<span class="html-italic">water regime (I)</span> × <span class="html-italic">genotype (G)’</span> on net photosynthetic assimilation rate (<span class="html-italic">P</span>n) in tomatoes on two dates (June 23 and July 11). IRR: full irrigation; DRY: no irrigation; REW: rewatering. Bars with the same letter do not significantly differ at <span class="html-italic">p</span> &lt; 0.05, according to Tukey’s test. Small black vertical bars indicate the standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Course of leaf transpiration (<span class="html-italic">E</span>, mmol H<sub>2</sub>O m<sup>−2</sup>s<sup>−1</sup>) during the field experiment in four tomato genotypes under different water regimes. Vertical arrows indicate the time of irrigation in REW. Small vertical bars indicate the standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Effect of interaction between ‘<span class="html-italic">water regime (I)</span> × <span class="html-italic">genotype (G)’</span> on leaf transpiration (<span class="html-italic">E</span>) in tomatoes at two dates (June 23 and July 11). IRR: full irrigation; DRY: no irrigation; REW: rewatering. Bars with the same letter do not significantly differ at <span class="html-italic">p</span> &lt; 0.05 according to Tukey’s test. Small black vertical bars indicate the standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Course of stomatal conductance (<span class="html-italic">g<sub>s</sub></span>, mol H<sub>2</sub>O m<sup>−2</sup>s<sup>−1</sup>) during the field experiment in the four tomato genotypes under different water regimes. Vertical arrows indicate the time of irrigation in REW. Small vertical bars indicate the standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Effect of interaction between ‘<span class="html-italic">water regime (I)</span> × <span class="html-italic">genotype (G)</span>’ on stomatal conductance (<span class="html-italic">g</span><sub>s</sub>) in tomatoes on two dates (June 23 and July 11). IRR: full irrigation; DRY: no irrigation; REW: rewatering. Bars with the same letter do not significantly differ at <span class="html-italic">p</span> &lt; 0.05 according to Tukey’s test. Small black vertical bars indicate the standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Course of leaf relative water content (RWC, %) during the field experiment for four tomato genotypes under different water regimes. Vertical arrows indicate the time of irrigation in REW. Small vertical bars indicate the standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Effect of interaction between ‘<span class="html-italic">water regime (I)</span> × <span class="html-italic">genotype (G)’</span> on leaf relative water content (RWC) in tomatoes (July 11). IRR: full irrigation; DRY: no irrigation; REW: rewatering. Bars with the same letter do not significantly differ at <span class="html-italic">p</span> &lt; 0.05 according to Tukey’s test. Small black vertical bars indicate the standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Course of Instantaneous water use efficiency (WUE<sub>i</sub>, μmol CO<sub>2</sub> mmol<sup>−1</sup> H<sub>2</sub>O) during the field experiment in four tomato genotypes under different water regimes. Vertical arrows indicate the time of irrigation in REW. Small vertical bars indicate the standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Effect of interaction between ‘<span class="html-italic">water regime (I)</span> × <span class="html-italic">genotype (G)’</span> on instantaneous water use efficiency (WUE<span class="html-italic">i</span>) in tomatoes on two dates (June 23 and July 11). IRR: full irrigation; DRY: no irrigation; REW: rewatering. Bars with the same letter do not significantly differ at <span class="html-italic">p</span> &lt; 0.05 according to Tukey’s test. Small black vertical bars indicate the standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Course of intercellular CO<sub>2</sub> (C<span class="html-italic"><sub>i</sub></span>, ppm) during the field experiment in the four tomato genotypes under different water regimes. Vertical arrows indicate the time of irrigation in REW. Small vertical bars indicate the standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Effect of interaction between ‘<span class="html-italic">water regime (I)</span> × <span class="html-italic">genotype (G)’</span> on intercellular CO<sub>2</sub> (<span class="html-italic">C<sub>i</sub></span>) in tomatoes (June 23). IRR: full irrigation; DRY: no irrigation; REW: rewatering. Bars with the same letter do not significantly differ at <span class="html-italic">p</span> &lt; 0.05 according to Tukey’s test. Small black vertical bars indicate the standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Course of stress degree (Ta-Tl, °C) during the field experiment in four tomato genotypes under different water regimes. Vertical arrows indicate the time of irrigation in REW. Small vertical bars indicate the standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Effect of interaction between ‘<span class="html-italic">water regime (I)</span> × <span class="html-italic">genotype (G)’</span> on stress degrees (Tair-Tleaf) in tomatoes (June 23). IRR: full irrigation; DRY: no irrigation; REW: rewatering. Bars with the same letter do not significantly differ at <span class="html-italic">p</span> &lt; 0.05 according to Tukey’s test. Small black vertical bars indicate the standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Effect of interaction ‘<span class="html-italic">water regime (I)</span> × <span class="html-italic">genotype (G)</span>’ and mean effects ‘<span class="html-italic">water regime’</span> and ‘<span class="html-italic">cultivar</span>’ on fruit production. IRR: full irrigation; DRY: no irrigation; REW: rewatering. Within the interaction values for each mean effect, bars with the same letter do not significantly differ at <span class="html-italic">p</span> &lt; 0.05, according to Tukey’s test. Small black vertical bars indicate the standard error (<span class="html-italic">n</span> = 3). Significant at <span class="html-italic">p</span> &lt; 0.001 ***.</p>
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<p>Effect of interaction between ‘<span class="html-italic">water regime (I)</span> × <span class="html-italic">genotype (G)’</span> on total soluble solids content (SS). IRR: full irrigation; DRY: no irrigation; REW: rewatering. Bars with the same letter do not significantly differ at <span class="html-italic">p</span> &lt; 0.05, according to Tukey’s test. Small black vertical bars indicate the standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Effect of interaction between ‘<span class="html-italic">water regime (I)</span> × <span class="html-italic">genotype (G)’</span> on total phenol content. IRR: full irrigation; DRY: no irrigation; REW: rewatering. Bars with the same letter do not significantly differ at <span class="html-italic">p</span> &lt; 0.05, according to Tukey’s test. Small black vertical bars indicate the standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Principal component biplot and scores of PCA for physiological traits (<span class="html-italic">P</span>n: net photosynthetic assimilation rate; <span class="html-italic">E</span>: leaf transpiration; <span class="html-italic">g</span><sub>s</sub>: stomatal conductance; Ta−Tl: stress degree; RWC: relative water content, C<span class="html-italic">i:</span> leaf intercellular CO<sub>2</sub>; WUE<span class="html-italic">i</span>: instantaneous water use efficiency), fruit production (FP), and quality traits (TS: total solids; SS: soluble solids; RS: reducing sugars; AscA: ascorbic acid; TP: total phenols) in tomato, as modulated by water regime (DRY: no irrigation; REW: rewaterings; IRR: full irrigation) and cultivar.</p>
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18 pages, 5588 KiB  
Article
Pangenome Identification and Analysis of Terpene Synthase Gene Family Members in Gossypium
by Yueqin Song, Shengjie Han, Mengting Wang, Xueqi Ni, Xinzheng Huang and Yongjun Zhang
Int. J. Mol. Sci. 2024, 25(17), 9677; https://doi.org/10.3390/ijms25179677 - 6 Sep 2024
Viewed by 251
Abstract
Terpene synthases (TPSs), key gatekeepers in the biosynthesis of herbivore-induced terpenes, are pivotal in the diversity of terpene chemotypes across and within plant species. Here, we constructed a gene-based pangenome of the Gossypium genus by integrating the genomes of 17 diploid and 10 [...] Read more.
Terpene synthases (TPSs), key gatekeepers in the biosynthesis of herbivore-induced terpenes, are pivotal in the diversity of terpene chemotypes across and within plant species. Here, we constructed a gene-based pangenome of the Gossypium genus by integrating the genomes of 17 diploid and 10 tetraploid species. Within this pangenome, 208 TPS syntelog groups (SGs) were identified, comprising 2 core SGs (TPS5 and TPS42) present in all 27 analyzed genomes, 6 softcore SGs (TPS11, TPS12, TPS13, TPS35, TPS37, and TPS47) found in 25 to 26 genomes, 131 dispensable SGs identified in 2 to 24 genomes, and 69 private SGs exclusive to a single genome. The mutational load analysis of these identified TPS genes across 216 cotton accessions revealed a great number of splicing variants and complex splicing patterns. The nonsynonymous/synonymous Ka/Ks value for all 52 analyzed TPS SGs was less than one, indicating that these genes were subject to purifying selection. Of 208 TPS SGs encompassing 1795 genes, 362 genes derived from 102 SGs were identified as atypical and truncated. The structural analysis of TPS genes revealed that gene truncation is a major mechanism contributing to the formation of atypical genes. An integrated analysis of three RNA-seq datasets from cotton plants subjected to herbivore infestation highlighted nine upregulated TPSs, which included six previously characterized TPSs in G. hirsutum (AD1_TPS10, AD1_TPS12, AD1_TPS40, AD1_TPS42, AD1_TPS89, and AD1_TPS104), two private TPSs (AD1_TPS100 and AD2_TPS125), and one atypical TPS (AD2_TPS41). Also, a TPS-associated coexpression module of eight genes involved in the terpenoid biosynthesis pathway was identified in the transcriptomic data of herbivore-infested G. hirsutum. These findings will help us understand the contributions of TPS family members to interspecific terpene chemotypes within Gossypium and offer valuable resources for breeding insect-resistant cotton cultivars. Full article
(This article belongs to the Special Issue Physiology and Molecular Biology of Plant Stress Tolerance)
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Figure 1

Figure 1
<p>Overview of syntelog-based <span class="html-italic">Gossypium</span> pangenome. (<b>A</b>) Composition of gene types in the pangenome. (<b>B</b>) Variation in number of pangenes (red) and core genes (blue) with increasing number of sampled genomes. (<b>C</b>) Ratios of core, softcore, dispensable, and cloud genes across 27 <span class="html-italic">Gossypium</span> species genomes, with the total count of pangenes normalized to 1. (<b>D</b>) CDS length distribution of core, softcore, dispensable, and private genes in the pangenome. (<b>E</b>) Exon counts of core, softcore, dispensable, and private genes in the pangenome. Core genes are present in all 27 genomes; softcore genes are present in over 90% of the 27 genomes; dispensable genes are present in more than 1 but less than 90% of the 27 genomes; and private genes are exclusive to a single genome.</p>
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<p>Phylogenetic tree of terpene synthases encoded by genes from <span class="html-italic">Arabidopsis</span> and <span class="html-italic">Gossypium</span> pangenome.</p>
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<p><span class="html-italic">TPS</span> gene family in the <span class="html-italic">Gossypium</span> pangenome. (<b>A</b>) Heatmap of presence/absence variation (PAV) for 206 variable <span class="html-italic">TPS</span> genes across six subfamilies (TPS-a–c, TPS-e–g) in 27 <span class="html-italic">Gossypium</span> species genomes. (<b>B</b>) Ratios of identified genes for each of the six subfamilies across 27 <span class="html-italic">Gossypium</span> species genomes. (<b>C</b>) Number of identified genes in each of the six subfamilies in the <span class="html-italic">Gossypium</span> pangenome. (<b>D</b>) Number of <span class="html-italic">TPS</span> genes exclusive to a single genome.</p>
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<p>Selection pressure analysis. (<b>A</b>) Waterfall plot of the variation burden of <span class="html-italic">TPS</span> genes in the 216 <span class="html-italic">Gossypium</span> accessions. (<b>B</b>) The distribution of Ka/Ks for each <span class="html-italic">TPS</span> gene in 27 samples.</p>
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<p>Structure of representative <span class="html-italic">TPS</span> genes <span class="html-italic">TPS12</span> and <span class="html-italic">TPS4</span> across various <span class="html-italic">Gossypium</span> species.</p>
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<p>Atypical <span class="html-italic">TPS</span> genes in <span class="html-italic">Gossypium</span> pangenome. (<b>A</b>) Heatmap for atypical <span class="html-italic">TPS</span> genes across 27 <span class="html-italic">Gossypium</span> species genomes. “Both” indicates the presence of both typical and atypical <span class="html-italic">TPS</span> genes in the same species. (<b>B</b>) Count of atypical <span class="html-italic">TPS</span> genes in each of the six subfamilies (TPS-a–c, TPS-e–g). (<b>C</b>) CDS length distribution and (<b>D</b>) gene length distribution of atypical and typical <span class="html-italic">TPS</span> genes.</p>
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<p>Herbivory-responsive <span class="html-italic">TPS</span> genes. (<b>A</b>) Heatmaps of the expression patterns of <span class="html-italic">TPS</span> genes in AD1-genome species infested with herbivores. T1, plants of <span class="html-italic">Gossypium hirsutum</span> (cotton) infested with <span class="html-italic">Apolygus lucorum</span> alone (CK1, control plants); T2, plants simultaneously infested with <span class="html-italic">A. lucorum</span> and <span class="html-italic">Helicoverpa armigera</span> (CK2, control plants). (<b>B</b>) Heatmaps of the expression patterns of <span class="html-italic">TPS</span> genes in AD2-genome species infested by <span class="html-italic">H. armigera</span> alone. (<b>C</b>) Venn diagram of common and unique TPSs under different treatments. (<b>D</b>) Distribution of expression levels for all <span class="html-italic">TPS</span> genes, atypical, private, and typical <span class="html-italic">TPS</span> genes. (<b>E</b>) A coexpression module involved in the TPS pathway. AB6I, ABC transporter I family member 6; ATPG, ATP synthase gamma chain; BSMT2, benzoic acid/salicylic acid carboxyl methyltransferase 2; CYPH, peptidyl-prolyl cis-trans isomerase; GDPD2, Glycerophosphodiester phosphodiesterase 2; INVA, scid beta-fructofuranosidase; RS103, small ribosomal subunit protein eS10x.</p>
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20 pages, 25243 KiB  
Article
The Designs and Testing of Biodegradable Energy-Absorbing Inserts for Enhanced Crashworthiness in Sports Helmets
by Paweł Kaczyński, Mateusz Skwarski, Anna Dmitruk, Piotr Makuła and Joanna Ludwiczak
Materials 2024, 17(17), 4407; https://doi.org/10.3390/ma17174407 - 6 Sep 2024
Viewed by 289
Abstract
This article addresses manufacturing structures made via injection molding from biodegradable materials. The mentioned structures can be successfully used as energy-absorbing liners of all kinds of sports helmets, replacing the previously used expanded polystyrene. This paper is focused on injection technological tests and [...] Read more.
This article addresses manufacturing structures made via injection molding from biodegradable materials. The mentioned structures can be successfully used as energy-absorbing liners of all kinds of sports helmets, replacing the previously used expanded polystyrene. This paper is focused on injection technological tests and tensile tests (in quasi-static and dynamic conditions) of several composites based on a PLA matrix with the addition of other biodegradable softening agents, such as PBAT and TPS (the blends were prepared via melt blending using a screw extruder with mass compositions of 50:50, 30:70, and 15:85). Tensile tests showed a positive strain rate sensitivity of the mixtures and a dependence of the increase in the ratio of the dynamic to static yield stress on the increase in the share of the plastic component in the mixture. Technological tests showed that increasing the amount of the plasticizing additive by 35% (from 50% to 85%) results in a decrease in the minimal thickness of the thin-walled element that can be successfully injection molded by about 32% in the case of PLA/PBAT blends (from 0.22 mm to 0.15 mm) and by about 26% in the case of PLA/TPS blends (from 0.23 mm to 0.17 mm). Next, the thin-walled elements (dimensions of 55 × 55 × 20 mm) were manufactured and evaluated using a spring-loaded drop hammer. The 60 J impact energy was tested in accordance with the EN 1078 standard. The dynamic crushing test included checking the influence of the materials’ temperature (−20, 0, 20, and 40 °C) and the impact velocity. It was proven that the maximum deflection increases with increasing material temperature and an increase in the share of the plastic component in the mixture. The PLA15PBAT85 blend was selected as the most effective material in terms of its use as an energy-absorbing liner for sport helmets. Johnson–Cook and Cowper–Symonds material plasticizing models were constructed. Their use during dynamic FE simulation provided results that were in good agreement with those of the conducted experiment. Full article
(This article belongs to the Section Green Materials)
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Figure 1
<p>Geometry of samples used for tensile tests: (<b>a</b>) quasi-static tests; (<b>b</b>) dynamic tensile tests.</p>
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<p>Rotary flywheel hammer: (<b>a</b>) diagram of the device; (<b>b</b>) photograph.</p>
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<p>The geometry of energy-absorbing structures subjected to injection testing.</p>
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<p>Injection mold used for the production of energy-absorbing structures: (<b>a</b>) tools mounted on the injection molding machine; (<b>b</b>) cross-section of the tools—model.</p>
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<p>Spring-loaded dynamic crushing test stand—Instron 9250HV: (<b>a</b>) general view; (<b>b</b>) impactor’s tup; (<b>c</b>) impactor’s anvil.</p>
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<p>FEM model of the energy-absorbing protective insert: (<b>a</b>) mesh; (<b>b</b>) boundary conditions.</p>
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<p>Engineering stress–engineering strain plasticizing curves of tested materials: (<b>a</b>) PLA50PBAT50; (<b>b</b>) PLA30PBAT70; (<b>c</b>) PLA15PBAT85; (<b>d</b>) PLA50TPS50; (<b>e</b>) PLA30TPS70; (<b>f</b>) PLA15TPS85.</p>
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<p>Location of measuring points for calculation of minimal thickness for successful injection molding.</p>
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<p>Force–deflection graphs of inserts made of blends based on (<b>a</b>) PLA and PBAT; (<b>b</b>) PLA and TPS.</p>
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<p>A graph of the maximum deformation of the inserts and the maximum overload occurring during crushing.</p>
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<p>The influence of temperature on the average force (at a deflection of 12 mm) and on the maximum deflection of the energy-absorbing structures.</p>
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<p>Typical crushing mode of PLA30TPST70 and PLA15TPS85.</p>
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<p>Average crushing force–deflection of selected structures: (<b>a</b>) PLA30PBAT70, (<b>b</b>) PLA15PBAT85.</p>
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<p>The influence of temperature on the average force (at a deflection of 7 mm) and on the maximum deflection of the energy-absorbing structures.</p>
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<p>The influence of temperature on the deformation mode of specimens at an impact velocity of 3.77 m/s.</p>
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<p>The influence of temperature on crushing force–displacement curves of (<b>a</b>) PLA30PBAT70; (<b>b</b>) PLA15PBAT85.</p>
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<p>Correlation of the material plasticity models to the experimental data: (<b>a</b>) Johnson–Cook simplified model; (<b>b</b>) Cowper–Symonds model.</p>
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<p>Comparison of the simulation and the crushing experiment (dynamic conditions): (<b>a</b>) deformation mode; (<b>b</b>) crushing force–deflection curve.</p>
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21 pages, 6567 KiB  
Article
Influence of Long Pressure and Short Suction Ventilation Parameters on Air Flow Field and Dust Migration in Driving Face
by Yuannan Zheng, Bo Ren and Guofeng Yu
Sustainability 2024, 16(17), 7786; https://doi.org/10.3390/su16177786 - 6 Sep 2024
Viewed by 352
Abstract
A combination of similar tests and numerical simulation was used to study the distribution of the air flow field and the dust field in the driving face under the conditions of long pressure and short suction ventilation. The results show that the air [...] Read more.
A combination of similar tests and numerical simulation was used to study the distribution of the air flow field and the dust field in the driving face under the conditions of long pressure and short suction ventilation. The results show that the air flow field is divided into return, jet, and vortex zones. When the distance (L) is 1.6 m, the wind speed (Va) is 8 m/s, and the ratio of pumped air volume to pressure air volume (Q) is 0.8, the total and exhaled dust concentration (Td, Rd, Tp, and Rp) at the driver’s and pedestrian’s position were the lowest. According to the grey correlation analysis, the importance of factors affecting Td and Tp is ranked as L > Va > Q, Rd is ranked as Va > L > Q, and Rp is as follows: Va > Q > L. The increase in Va and the decrease in L have a significant effect on the expulsion of exhaled dust. Full article
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Figure 1
<p>Long pressure short suction ventilation dust removal experimental platform.</p>
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<p>Variation in wind speed.</p>
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<p>Verification of wind speed and dust concentration along the roadway. (<b>a</b>) Wind velocity. (<b>b</b>) Dust concentration.</p>
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<p>Effect of L on the wind flow field.</p>
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<p>Changes in roadway wind speed along different distances from the air outlet of the pressure duct to the driving surface. (<b>a</b>) Pressure side. (<b>b</b>) Central axis. (<b>c</b>) Extraction side.</p>
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<p>Air flow field along the roadway at different pressure tuyere wind speeds.</p>
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<p>Changes in roadway wind speed along different pressure tuyere wind speeds. (<b>a</b>) Pressure side. (<b>b</b>) Central axis. (<b>c</b>) Extraction side.</p>
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<p>Conditions of air flow field in roadway under different ratios of pumping pressure and air volume.</p>
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<p>Changes in roadway wind speed along the road with different pumping air volume ratios. (<b>a</b>) Pressure side. (<b>b</b>) Central axis. (<b>c</b>) Extraction side.</p>
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<p>Effect of L on particulate matter distribution.</p>
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<p>Influence of L on dust distribution along the roadway. (<b>a</b>) Total dust concentration on the pressure side. (<b>b</b>) Total dust concentration at the central axis. (<b>c</b>) Total dust concentration on the exhaust side. (<b>d</b>) Respirable dust concentration on the pressure side. (<b>e</b>) Respirable dust concentration at the central axis. (<b>f</b>) Respirable dust concentration on the exhaust side.</p>
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<p>Distribution of particulate matter under different pressure wind speeds.</p>
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<p>Influence of V<sub>a</sub> on dust distribution along the roadway. (<b>a</b>) Total dust concentration on the pressure side. (<b>b</b>) Total dust concentration at the central axis. (<b>c</b>) Total dust concentration on the exhaust side. (<b>d</b>) Respirable dust concentration on the pressure side. (<b>e</b>) Respirable dust concentration at the central axis. (<b>f</b>) Respirable dust concentration on the exhaust side.</p>
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<p>Distribution of particulate matter under different pumping air volume ratios.</p>
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<p>Influence of Q on dust distribution along the roadway. (<b>a</b>) Total dust concentration on the pressure side (<b>b</b>) Total dust concentration at the central axis (<b>c</b>) Total dust concentration on the exhaust side (<b>d</b>) Respirable dust concentration on the pressure side (<b>e</b>) Respirable dust concentration at the central axis (<b>f</b>) Respirable dust concentration on the exhaust side.</p>
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<p>Correlation degree of each influencing factor.</p>
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18 pages, 2880 KiB  
Article
Transcriptomic Analysis Provides Insights into the Energetic Metabolism and Immune Responses in Litopenaeus vannamei Challenged by Photobacterium damselae subsp. damselae
by Libao Wang, Qiuwen Xu, Zhijun Yu, Zhenxin Hu, Hui Li, Wenjun Shi and Xihe Wan
Fishes 2024, 9(9), 350; https://doi.org/10.3390/fishes9090350 - 6 Sep 2024
Viewed by 279
Abstract
To explore the molecular mechanisms of the Litopenaeus vannamei response to infection by Photobacterium damselae, reveal its immune response and energetic metabolic effect, and provide a valuable genetic data source for the scientific prevention and control of Vibrio infection, transcriptomic analysis, RT-qPCR, [...] Read more.
To explore the molecular mechanisms of the Litopenaeus vannamei response to infection by Photobacterium damselae, reveal its immune response and energetic metabolic effect, and provide a valuable genetic data source for the scientific prevention and control of Vibrio infection, transcriptomic analysis, RT-qPCR, and physiological and biochemical tests were conducted. The results showed that the expression of key genes involved in lipid and carbohydrate transport, such as apolipoprotein and TPS, was upregulated after pathogenic infection, which brought the accumulation of triacylglycerol and trehalose into the hemolymph. Additionally, the pathogenic infection selectively triggered an immune response in infected L. vannamei, activating certain immune pathways, such as the serpins and MAPK pathways. The pathogenic infection suppressed the activity of phenoloxidase (PO), and the prophenoloxidase (PPO) cascade responses were suppressed by the invasive bacteria. This paper will help us understand the energetic metabolism, immune response, and activation of the immune recognition response after pathogenic infection by P. damselae, and it lays a theoretical foundation for the biological prevention and control of P. damselae infection. Full article
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Graphical abstract

Graphical abstract
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<p>Schematic diagram of the experimental design.</p>
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<p>Volcano plot picture of the differentially expressed genes of <span class="html-italic">L. vannamei</span> under an artificial challenge.</p>
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<p>The DEGs in the infected <span class="html-italic">L. vannamei</span> were clustered into six assemblages (DEGs, fold change of &gt;2, <span class="html-italic">p</span>-value of &lt;0.005). DEG, differential expression gene; DS, DEGs in the shrimp infected with <span class="html-italic">P. damselae</span>; NS, DEGs in the control group of the shrimp injected with sterilized physiological saline.</p>
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<p>Hierarchical cluster results of the transcripts of the energetic metabolism-related (<b>A</b>) and immune response-related (<b>B</b>) genes in the infected <span class="html-italic">L. vannamei</span>. DS, shrimp infected with <span class="html-italic">P. damselae</span>; NS, control group of the shrimp injected with sterilized physiological saline.</p>
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<p>Hierarchical cluster results of the transcripts of the energetic metabolism-related (<b>A</b>) and immune response-related (<b>B</b>) genes in the infected <span class="html-italic">L. vannamei</span>. DS, shrimp infected with <span class="html-italic">P. damselae</span>; NS, control group of the shrimp injected with sterilized physiological saline.</p>
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<p>Expression profiles of the energetic metabolism- and immune response-related genes in the infected <span class="html-italic">L. vannamei. APO</span>, Apolipoprotein; <span class="html-italic">TPS</span>, trehalose-6-phosphate synthase; <span class="html-italic">Mttp</span>, Microsomal triglyceride transfer protein; <span class="html-italic">Lipl-1</span>, triacylglycerol lipase; <span class="html-italic">Serpin</span>, serine proteinase inhibitor; <span class="html-italic">MAPK</span>, mitogen-activated protein kinase kinase; <span class="html-italic">GPX</span>, glutathione peroxidase; <span class="html-italic">CAT</span>, catalase. DS, shrimp infected with <span class="html-italic">P. damselae</span>; NS, control group of the shrimp injected with sterilized physiological saline. Two treatment groups (NS and DS) were set up in the experiment, with triplicates per treatment (**: <span class="html-italic">p</span> &lt; 0.01, and ***: <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>Changes in the TAG and trehalose concentrations and activities of PO, TPS, lysozyme, CAT, and GSH-PX in the hemolymph samples of the infected <span class="html-italic">L. vannamei</span>. The hemolymph samples harvested from the infected <span class="html-italic">L. vannamei</span> were used for measuring the TAG (<b>A</b>) and trehalose concentrations (<b>B</b>), PO activity (<b>C</b>), TPS activity (<b>D</b>), lysozyme activity (<b>E</b>), CAT activity (<b>F</b>), and GSH-PX activity (<b>G</b>). DS, shrimp infected with <span class="html-italic">P. damselae</span>; NS, control group of the shrimp injected with sterilized physiological saline. Two treatment groups (NS and DS) were set up in the experiment, with triplicates per treatment (***: <span class="html-italic">p</span> &lt; 0.001).</p>
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14 pages, 836 KiB  
Article
Chemical and Sensory Properties of Corn Extrudates Enriched with Tomato Powder and Ascorbic Acid
by Valentina Obradović, Jurislav Babić, Antun Jozinović, Đurđica Ačkar and Drago Šubarić
Appl. Sci. 2024, 14(17), 7968; https://doi.org/10.3390/app14177968 - 6 Sep 2024
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Abstract
The chemical and sensory properties of corn extrudates enriched with spray-dried tomato powder (TP) in 4, 6 and 8% ratios were researched. Two extrusion temperature regimes were used: 135/170/170 °C (E1) and 100/150/150 °C (E2). Ascorbic acid (AA) at levels of 0.5 and [...] Read more.
The chemical and sensory properties of corn extrudates enriched with spray-dried tomato powder (TP) in 4, 6 and 8% ratios were researched. Two extrusion temperature regimes were used: 135/170/170 °C (E1) and 100/150/150 °C (E2). Ascorbic acid (AA) at levels of 0.5 and 1% was also added to the raw mixtures in order to prevent the undesirable oxidation of the constituents, primarily carotenoids. AA was especially efficient in the case of the lutein content and 1% AA, but lutein originating from TP was more sensitive to the extrusion conditions than corn lutein, and zeaxanthin was more sensitive than lutein. Lycopene, α-carotene, 13-cis-β carotene and 9-cis-β carotene degraded completely in all the samples, at both extrusion regimes. The proposed models for the color of the extrudates showed the significant influence of TP and AA. Extrudates obtained at the E1 temperature regime containing 4% TP and pure corn extrudate with 1% AA were the best-rated samples by the sensory panel. Full article
(This article belongs to the Special Issue Enrichment of Foods with Phytonutrients)
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Figure 1

Figure 1
<p>Response surface plots for color values as a function of tomato powder level and ascorbic acid level.</p>
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