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17 pages, 1737 KiB  
Article
Characterization of New Flavored Oils Obtained Through the Co-Milling of Olives and Vegetable Food Products
by Celeste Lazzarini, Matilde Tura, Mara Mandrioli, Marco Setti, Noureddine Mokhtari, Abdelaziz Ait Elkassia, Sara Barbieri, Enrico Valli, Alessandra Bendini and Tullia Gallina Toschi
Foods 2025, 14(4), 687; https://doi.org/10.3390/foods14040687 - 17 Feb 2025
Abstract
Consumers are increasingly attracted to innovative, gourmand, and sustainable food products. This has led to a growing interest in flavored olive oils through co-milling processing. This study explores the production and characterization of flavored olive oils obtained by co-milling olives with orange pomace, [...] Read more.
Consumers are increasingly attracted to innovative, gourmand, and sustainable food products. This has led to a growing interest in flavored olive oils through co-milling processing. This study explores the production and characterization of flavored olive oils obtained by co-milling olives with orange pomace, black pepper, and hemp seeds, aiming to enhance their sensory and compositional properties while promoting sustainability through the valorization of agri-food by-products. The flavored olive oils and their control samples were analyzed for free acidity, tocopherols, phenolic compounds, volatiles, and sensory profiles. The flavored oils exhibited an acceptable hydrolytic state and peculiar sensory notes, depending on the ingredients used, as well as enhanced compositional qualities. This research highlights the potential of using oranges and hemp by-products in flavored oil production, offering an innovative approach to reducing food waste, with the possibility of future industrial applications. Full article
(This article belongs to the Section Food Quality and Safety)
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Figure 1
<p>Description of the samples produced and analyzed in this research work.</p>
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<p>Total content of reducing activity molecules expressed as mg of gallic acid per kg of oil. Letters of significance are related to the analysis of variance (ANOVA, Tukey’s HSD (<span class="html-italic">p</span> ≤ 0.05). TEST_1, TEST_2 = olive oil control samples; AR = co-milled olive oil produced by milling olives and entire oranges; ST_AR = co-milled olive oil produced by milling olives and orange pomace; ST_AR_P = co-milled olive oil produced by milling olives with orange pomace and black pepper.</p>
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<p>Generalized Procrustes Analysis (GPA) biplot of sensory data (flash profile method) of co-milled olive oils with hemp seeds at different ratios and their control samples. TEST_3 = olive oil control sample; HTEST_1 = cold-pressed hemp seed oil control sample; IUP_HS_10 = co-milled olive oil produced by milling olives with 10% intact unpeeled hemp seeds; IUP_HS_20 = co-milled olive oil produced by milling olives with 20% intact unpeeled hemp seeds; GUP_HS_10 = co-milled olive oil produced by milling olives with 10% ground unpeeled hemp seeds; GUP_HS_20 = co-milled olive oil produced by milling olives with 20% ground unpeeled hemp seeds.</p>
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<p>Multiple Factor Analysis (MFA) biplot obtained by volatile compounds (in green) and sensory data (median intensity of sensory attributes, in red) of flavored olive oils with orange, orange by-product, orange by-product and black pepper, and their control samples. TEST_1, TEST_2 = olive oil control samples; AR = co-milled olive oil produced by milling olives and entire oranges; ST_AR = co-milled olive oil produced by milling olives and orange pomace; ST_AR_P = co-milled olive oil produced by milling olives with orange pomace and black pepper.</p>
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25 pages, 1161 KiB  
Article
Enhancing Commercial Gourmet Oil Quality: The Role of Dried Cayenne Pepper Red (Capsicum annuum L.) as a Natural Additive
by Zuzana Knazicka, Branislav Galik, Ivana Novotna, Julius Arvay, Katarina Fatrcova-Sramkova, Miroslava Kacaniova, Jiri Mlcek, Eva Kovacikova, Eva Mixtajova, Tunde Jurikova, Eva Ivanisova, Adriana Kolesarova and Hana Duranova
Molecules 2025, 30(4), 927; https://doi.org/10.3390/molecules30040927 - 17 Feb 2025
Abstract
This study assessed the potential of dried Cayenne pepper (CP; Capsicum annuum L.) as a natural additive to rice bran oil (RBO), grape seed oil (GSO), and virgin olive oil (OO). Key analyses included peroxide and acid values, oxidative stability (Rancimat method), the [...] Read more.
This study assessed the potential of dried Cayenne pepper (CP; Capsicum annuum L.) as a natural additive to rice bran oil (RBO), grape seed oil (GSO), and virgin olive oil (OO). Key analyses included peroxide and acid values, oxidative stability (Rancimat method), the composition of fatty acids (FAs) (GC-FID method), antioxidant activity (AA; DPPH method), and antimicrobial properties (disc diffusion method). Capsaicin and the dihydrocapsaicin contents in CP were quantified (HPLC-DAD method) as 1499.37 ± 3.64 and 1449.04 ± 5.14 mg/kg DW, respectively. Oleic acid (C18:1cis n9) dominated in OO (69.70%), OO-CP (69.73%), and RBO-CP (38.97%), while linoleic acid (C18:2cis n6) prevailed in RBO (41.34%), GSO (57.93%), and GSO-CP (58.03%). The addition of CP influenced the FA profile, particularly linoleic acid in OO and RBO, and all FAs in GSO. Peroxide and acid values increased significantly in RBO and GSO upon CP addition, but induction times remained unaffected. The strongest AA (77.00 ± 0.13%) was observed in OO-CP. Cayenne pepper significantly enhanced the antioxidant profiles of all oils compared to the counterparts. However, the antimicrobial activity was weak (≤5.0 mm inhibition zones) against tested microorganisms. These findings support CP as a functional additive for enhancing the nutritional and functional properties of gourmet oils, while highlighting the need for further optimization to improve stability and bioactivity. Full article
(This article belongs to the Special Issue New Insight into Edible Oil: From Food Chemistry to Health Benefits)
39 pages, 9959 KiB  
Article
Utilization of Non-Composted Human Hair Hydrolysate as a Natural and Nutrient-Rich Liquid Fertilizer for Sustainable Agro-Applications and Bio-Waste Management
by Kaan Yetilmezsoy, Fatih Ilhan and Emel Kıyan
Sustainability 2025, 17(4), 1641; https://doi.org/10.3390/su17041641 - 16 Feb 2025
Viewed by 277
Abstract
Human hair, commonly considered a discarded organic waste, is a keratin-rich material with remarkable potential for sustainable agriculture as an innovative resource. This study systematically explored the potential of non-composted human hair hydrolysates as eco-friendly and nutrient-rich liquid fertilizers, emphasizing their ability to [...] Read more.
Human hair, commonly considered a discarded organic waste, is a keratin-rich material with remarkable potential for sustainable agriculture as an innovative resource. This study systematically explored the potential of non-composted human hair hydrolysates as eco-friendly and nutrient-rich liquid fertilizers, emphasizing their ability to enhance agricultural sustainability and mitigate organic waste accumulation. Eight distinct hydrolysates prepared with alkaline solutions were evaluated for their effects on plant growth using red-hot chili pepper (Capsicum frutescens) as the primary model under greenhouse conditions. The present study introduces a novel approach by employing an advanced digital image analysis technique to quantitatively assess 37 distinct plant growth parameters, providing an unprecedented depth of understanding regarding the impact of liquid human hair hydrolysates on plant development. Additionally, the integration of pilot-scale field trials and multi-species evaluations highlights the broader applicability and scalability of these hydrolysates as sustainable fertilizers. Collectively, these features establish this research as a pioneering contribution to sustainable agriculture and bio-waste management. The top-performing hydrolysates (KCaMgN, KMgN, KCaN) demonstrated significant enhancements in plant growth metrics, with fresh weight reaching up to 3210 mg, projected leaf area of approximately 132 cm2, and crown diameter of 20.91 cm for the best-performing formulations, outperforming a commercial organomineral fertilizer by 20–46% in overall growth performance. Furthermore, observational studies on various species (such as bird of paradise flower (Strelitzia reginae), avocado (Persea americana), lemon (Citrus limon L.), Mazafati date (Phoenix dactylifera L.), and red mini conical hot pepper (Capsicum annuum var. conoides) and field trials on long sweet green peppers (Capsicum annuum) confirmed the broad applicability of these hydrolysates. Toxicity assessments using shortfin molly fish (Poecilia sphenops) validated the environmental safety of plants cultivated with hydrolysates. These findings highlight that human hair hydrolysates offer a sustainable alternative to synthetic fertilizers, contributing to waste management efforts while enhancing agricultural productivity. Full article
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<p>Schematic representation of waste human hair hydrolysis and subsequent application as a liquid fertilizer.</p>
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<p>Multi-stage digital image analysis for comprehensive plant growth parameter quantification.</p>
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<p>Definition of key morphological parameters for <span class="html-italic">Capsicum frutescens</span> growth via digital image analysis approach.</p>
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<p>Flowchart of the experimental design illustrating the different treatments applied to each experimental group from initial preparations to final evaluations.</p>
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<p>Static bioassay apparatus for evaluating acute toxicity of dried chili pepper leaves (grown with waste human hair fertilizers) in <span class="html-italic">Poecilia sphenops</span>.</p>
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<p>Comparative growth response of <span class="html-italic">Capsicum frutescens</span> to human hair hydrolysates, commercial fertilizer, and control treatments.</p>
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<p>A controlled laboratory-based field model for evaluating human hair hydrolysate effects on shallot growth: (<b>a</b>) model construction (10 July 2023), (<b>b</b>) soil preparation and initial liquid fertilization (13 July 2023), (<b>c</b>) planting of shallot bulbs (13 July 2023) and (<b>d</b>) development of green shoots (5 September 2023) and subsequent harvest.</p>
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<p>Growth observation of five temperate and tropical climate plant species under controlled environment: (<b>a</b>) <span class="html-italic">Capsicum annuum</span> var. <span class="html-italic">conoides</span> (22 April 2024), (<b>b</b>) <span class="html-italic">Phoenix dactylifera</span> L. (5 September 2023), (<b>c</b>) <span class="html-italic">Citrus limon</span> L. (16 October 2023), (<b>d</b>) <span class="html-italic">Persea americana</span> (22 May 2023) (<b>e</b>) <span class="html-italic">Strelitzia reginae</span> (14 August 2023).</p>
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<p>Photographs showing the enhanced growth of long sweet green pepper (<span class="html-italic">Capsicum annuum</span>) plants treated with human hair hydrolysate (KCaMgN set) compared to controls in a pilot-scale garden (12 September 2023).</p>
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18 pages, 2584 KiB  
Article
Disease Tolerance in ‘Anaheim’ Pepper to PepGMV-D Strain Involves Complex Interactions Between the Movement Protein Putative Promoter Region and Unknown Host Factors
by Cecilia Hernández-Zepeda and Judith K. Brown
Viruses 2025, 17(2), 268; https://doi.org/10.3390/v17020268 - 15 Feb 2025
Viewed by 171
Abstract
Pepper golden mosaic virus (PepGMV) is a bipartite begomovirus of pepper and tomato from North America. In ‘Anaheim’ pepper plants PepGMV-Mo strain (Mo) causes systemic yellow foliar mosaic symptoms, while PepGMV-D strain (D) causes distortion of 1st–6th expanding leaves, and asymptomatic infection of [...] Read more.
Pepper golden mosaic virus (PepGMV) is a bipartite begomovirus of pepper and tomato from North America. In ‘Anaheim’ pepper plants PepGMV-Mo strain (Mo) causes systemic yellow foliar mosaic symptoms, while PepGMV-D strain (D) causes distortion of 1st–6th expanding leaves, and asymptomatic infection of subsequently developing leaves, like other known ‘recovery’ phenotypes. Infections established with DNA-A Mo and D components expressing red-shifted green fluorescent protein in place of coat protein and in situ hybridization, showed PepGMV-Mo localized to phloem and mesophyll cells, while -D was mesophyll restricted. Alignment of PepGMV-Mo and -D DNA-B components revealed three indels upstream of the BC1 gene that encodes the movement protein (MP). To determine if this non-coding region (*BC1) D-strain MP putative promoter contributed to ‘recovery’, plants were inoculated with chimeric DNA-B Mo/D components harboring reciprocally exchanged *BC1, and wild-type DNA-A Mo and D components. Symptoms were reminiscent but not identical to wild-type -Mo or -D infection, respectively, suggesting ‘recovery’ cannot be attributed solely to the *BC1. Both BC1 and D*BC1 were targeted by post-transcriptional gene silencing; however, ‘recovered’ leaves accumulated fewer transcripts and 21–24 nt vsiRNAs. Thus, inefficient in planta movement of PepGMV-D is associated with a non-pepper-adapted ‘defective’ BC1 that facilitates hyper-efficient PTGS, leading to BC1 transcript degradation that in turn limits virus spread, thereby recapitulating disease ‘tolerance’. Full article
(This article belongs to the Special Issue Plant Virus Interactions with Hosts: Mechanisms and Applications)
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Figure 1
<p>Schematic representation of the construction method used to build <span class="html-italic">Pepper golden mosaic virus</span> (PepGMV) DNA-B chimeras. (<b>A</b>) Subcloning <span class="html-italic">Nde</span>I/<span class="html-italic">Spe</span>I fragments (<b>top</b>) into distortion (D) strain DNA-B, black line (<b>bottom</b>) represents linearized wild-type distortion strain. (<b>1</b>–<b>3</b>) are the resultant chimeras constructed for -D strain. (<b>B</b>) Subcloning <span class="html-italic">Bam</span>HI/<span class="html-italic">Spe</span>I fragments (<b>top</b>) into mosaic (Mo) strain DNA-B, red line (<b>bottom</b>) represents linearized wild-type mosaic strain. (<b>1</b>–<b>3</b>) are the resultant chimeras for the Mo. The blue and green arrows represent the two ORFs on the DNA-B. The brown arrows point to the subcloning sites. <span class="html-italic">Nde</span>I site (in red) on the <span class="html-italic">Bam</span>HI/<span class="html-italic">Spe</span>I fragments was engineered because of the presence of another site on DNA-B Mo at the BV1 5′ end.</p>
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<p>Characteristic symptoms in inoculated ‘Anaheim’ pepper plants. (<b>A</b>) PepGMV-Mo wild-type inoculated ‘Anaheim’ pepper plant at 15 dpi; (<b>B</b>) PepGMV-Mo strain DNA-A and DNA-B background containing pMoB:DBC1 Prom inoculated pepper plant at 15 dpi; (<b>C</b>) PepGMV-D wild-type inoculated pepper plant at 15 dpi; (<b>D</b>) PepGMV-D strain DNA-A and DNA-B background containing pDB:MoBC1 Prom inoculated pepper plant at 15 dpi.</p>
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<p>Viral DNA accumulation in PepGMV-Mo and PepGMV-D wild-type strains. Total DNA was fractionated by 1% agarose gel electrophoresis blotted onto nitrocellulose membranes and hybridized with PepGMV-Mo as probe. Approximately 5 mg of total DNA were loaded in each lane. (<b>A</b>) PepGMV-Mo strain leaves 1 to 6 and H = virus-free or ‘health’ control; (<b>B</b>) PepGMV-D strain leaves 1 to 6 and H = healthy or virus-free control. OC = open circle, SC = super coiled, and SS = single stranded.</p>
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<p>Fluorescence microscope images showing <span class="html-italic">Pepper golden mosaic virus</span> (PepGMV) wild-type strains (Mo and D) distribution along transverse sections of leaves and roots of pepper infected plants. Figures (<b>A</b>–<b>F</b>) correspond to PepGMV-GFP detection in Mo-inoculated pepper plants. (<b>A</b>) leaf 1; (<b>B</b>) leaf 3; (<b>C</b>) leaf 5; (<b>D</b>) inoculated leaf; (<b>E</b>) root; (<b>F</b>) mock inoculated. Figures (<b>G</b>–<b>L</b>) correspond to PepGMV-GFP detection in D-inoculated pepper plants. (<b>G</b>) leaf 1; (<b>H</b>) leaf 3; (<b>I</b>) leaf 5; (<b>J</b>) inoculated leaf; (<b>K</b>) root; (<b>L</b>) mock inoculated.</p>
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<p>In situ localization of <span class="html-italic">Pepper golden mosaic virus</span> (PepGMV) in pepper plants inoculated with (<b>A</b>) mosaic strain: (<b>B</b>) distortion strain and (<b>C</b>) mock-inoculated, negative control. Pepper plants exhibiting PepGMV-Mo and -D strain-specific symptoms (<b>A</b>,<b>B</b>) and no symptoms (<b>C</b>) were sectioned and hybridized with BC1:Mo- or BC1:D-specific DIG-labeled probes and viewed at the ×100 and ×1000 magnification. Inserts represent ×1000 of boxed areas.</p>
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<p>Northern blot hybridization of total RNA isolated from pepper plants inoculated with <span class="html-italic">Pepper golden mosaic virus</span> (PepGMV) wild-type and chimeric viruses. (<b>A</b>) Loading control (EtBr stain). Approximately 20 mg of total RNA were loaded in each lane. (<b>B</b>) Blots hybridized with 700 nt of BC1 gene as probe. S = symptomatic; R = recovered. Lanes: (1) PepGMV-Mo leaves 1 and 2 symptomatic; (2) PepGMV-Mo leaves 5 and 6 symptomatic; (3) PepGMV-D Leaves 1 and 2 symptomatic; (4) PepGMV-D Leaves 5 and 6 recovered; (5) healthy pepper; (6) PepGMV-Mo with DNA-A and DNA-B background containing pMoB:DBC1 Prom Leaves 1 and 2 mild symptoms; (7) PepGMV-Mo with DNA-A and DNA-B background containing pMoB:DBC1 Prom Leaves 5 and 6 recovered; (8) PepGMV-D with DNA-A and DNA-B background containing pDB:MoBC1 Prom Leaves 1 and 2 symptomatic; (9) PepGMV-D with DNA-A and DNA-B background containing pDB:MoBC1 Prom Leaves 5 and 6 symptomatic; (10) Healthy pepper.</p>
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<p>Northern blot analysis of vsiRNAs from pepper plants inoculated with each PepGMV-Mo and PepGMV-D wild-type strains and chimeras. The low molecular weight (LMW) RNA was fractionated by denaturing polyacrylamide gel electrophoresis and hybridized with the 700 bp probe from the BC1 gene (Movement protein gene). 15 mg of LMW RNA was loaded into each lane. (<b>A</b>) Lane (1) PepGMV-Mo strain symptomatic leaves 1 and 2; Lane (2); PepGMV-Mo strain symptomatic leaves 5 and 6; Lane (3) PepGMV-D strain symptomatic leaves 1 and 2; Lane (4) PepGMV-D strain recovered leaves 5 and 6: Lane (5); Mock inoculated control. (<b>B</b>) Lane (1) PepGMV-Mo with DNA-A and DNA-B background containing pMoB:DBC1 Prom mild symptomatic leaves 1 and 2; Lane (2) PepGMV-Mo with DNA-A and DNA-B containing pMoB:DBC1 Prom-recovered leaves 5 and 6; Lane (3) PepGMV-D with DNA-A and DNA-B containing pDB:MoBC1 Prom-symptomatic leaves 1 and 2; Lane (4) PepGMV-D with DNA-A and DNA-B containing pDB:MoBC1 Prom-symptomatic leaves 5 and 6; Lane (5) Mock inoculated control.</p>
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17 pages, 2875 KiB  
Article
Genetic Regulation of Chlorophyll Biosynthesis in Pepper Fruit: Roles of CaAPRR2 and CaGLK2
by Huagang Sun, Yiyue Zhang, Lingkui Zhang, Xiang Wang, Kang Zhang, Feng Cheng and Shumin Chen
Genes 2025, 16(2), 219; https://doi.org/10.3390/genes16020219 - 13 Feb 2025
Viewed by 274
Abstract
Background: Pepper (Capsicum annuum L.) is a widely cultivated vegetable crop worldwide, with its rich fruit colors providing unique visual traits and economic value. This study investigated the genetic basis of the immature green fruit color by constructing a F2 segregating [...] Read more.
Background: Pepper (Capsicum annuum L.) is a widely cultivated vegetable crop worldwide, with its rich fruit colors providing unique visual traits and economic value. This study investigated the genetic basis of the immature green fruit color by constructing a F2 segregating population derived from a cross between yellow fruit C20 and green fruit C62 parent lines. Methods: Bulked segregant analysis sequencing (BSA-seq) was performed to identify genomic regions associated with fruit color. Candidate genes were pinpointed through functional annotation and genetic variation analysis, supported by SNP markers, genotype analysis, and transcriptome profiling. Results: Two genomic regions associated with fruit color were identified on chromosomes 1 (14.55–20.85 Mb) and 10 (10.15–22.85 Mb), corresponding to previously reported loci pc1 and pc10.1. Two chlorophyll synthesis-related genes, CaAPRR2 and CaGLK2, were identified as candidate regulators of fruit color. Mutations in these genes include a premature stop codon in both CaGLK2 and CaAPRR2. The mutation of CaAPRR2 and CaGLK2 jointly regulate the yellow fruit trait in pepper, with CaGLK2 being the major gene and CaAPRR2 being the minor gene. Transcriptome analysis showed that the expression levels of the two genes increased during the green ripening stage of the parent fruits, with higher expression levels of CaGLK2. Conclusions: This study identifies CaGLK2 and CaAPRR2 as key regulators of immature green fruit color in pepper, with CaGLK2 playing a predominant role. These findings provide a theoretical foundation and data support for elucidating the molecular regulatory mechanisms of fruit color and advancing marker-assisted breeding in pepper. Full article
(This article belongs to the Special Issue Vegetable Genomes and Genetic Breeding)
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Figure 1
<p>Segregation and chlorophyll content analysis in pepper fruits derived from a cross between parental lines C20 and C62. (<b>a</b>) Schematic representation of the cross between the yellow-fruited C20 and the green-fruited C62 parental lines, showing the F₁ generation and the color variation in the F₂ generation fruits (from yellow to green). Scale bar = 30 mm. (<b>b</b>) Chlorophyll content measured in fruits of C20 and C62 at three developmental stages (1, 7, and 21 DAF), showing a significant increase in chlorophyll levels in C62 compared to C20. Statistical significance is indicated (** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001). (<b>c</b>) Distribution of fruit color phenotypes in the F₂ population, with a range of chlorophyll-related color classes from yellow to green.</p>
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<p>Genomic analysis of mutation sites across pepper chromosomes. (<b>a</b>) ΔSNP-index distribution across all 12 chromosomes, showing the relative differences in single nucleotide polymorphisms (SNPs) between two contrasting pepper lines. The x-axis represents chromosome position, while the y-axis shows ΔSNP-index values. The color gradient represents the number of mutation sites within each window, from yellow (lower mutation count) to dark blue (higher mutation count). Horizontal dashed lines indicate the significance threshold, and vertical dashed red lines highlight candidate regions with notable ΔSNP-index peaks. (<b>b</b>) ED<sup>2</sup> distribution across all 12 chromosomes, indicating genetic differentiation between the two pepper lines. The x-axis represents chromosome position, while the y-axis represents ED<sup>2</sup> values. The color gradient follows the same scale as in (<b>a</b>). Horizontal dashed lines represent the significance threshold, while vertical dashed red lines mark candidate regions with significant ED<sup>2</sup> peaks.</p>
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<p>BSA mapping and structural analysis of candidate genes <span class="html-italic">CaAPRR2, CaLOL1</span>, and <span class="html-italic">CaGLK2</span> associated with chlorophyll synthesis in pepper fruit. (<b>a</b>) ΔSNP-index plot of chromosome 1 showing the position of the chlorophyll-related gene <span class="html-italic">CaAPRR2</span> and <span class="html-italic">CaLOL1</span>, marked by a red star. (<b>b</b>) ΔSNP-index plot of chromosome 10 indicating the location of the chlorophyll-related gene <span class="html-italic">CaGLK2</span>, also highlighted with a red star. (<b>c</b>) Structural diagram of <span class="html-italic">CaAPRR2</span> gene, showing a premature stop codon mutation (TGG to TGA) causing truncated protein synthesis. The right panel shows the sequence alignment of <span class="html-italic">CaAPRR2</span> in the C62 (green parent) and C20 (yellow parent) lines, with the mutation site highlighted. Blue boxes represent exons, yellow regions represent untranslated regions (UTRs), and black lines represent introns. The full length of the gene, including both introns and exons, is highlighted by a green line, spanning from the start codon to the stop codon. (<b>d</b>) Structural diagram of <span class="html-italic">CaLOL1</span> gene, highlighting a non-synonymous mutation (TTC to TAC) resulting in an amino acid change from serine (S) to tyrosine (T). (<b>e</b>) Structural diagram of <span class="html-italic">CaGLK2</span> gene, showing a premature stop codon mutation (TCG to TAG) causing truncated protein synthesis. The right panel presents the sequence alignment for <span class="html-italic">CaGLK2</span> in the two parental lines, highlighting the stop-gain mutation. (<b>f</b>) Genetic variation in CaAPRR2, <span class="html-italic">CaLOL1</span>, and <span class="html-italic">CaGLK2</span> in green and yellow accessions. The bar chart displays the genetic variation frequencies for three genes (<span class="html-italic">CaAPRR2</span>, <span class="html-italic">CaLOL1,</span> and <span class="html-italic">CaGLK2</span>) across green and yellow accessions, and heterozygosity is denoted by an asterisk (*). For <span class="html-italic">CaAPRR2</span>, yellow accessions exhibit a frequency of 13(4*)/19 (yellow bar), while green accessions show 2/239 (green bar). The mutation frequency is indicated as 2/239 (white bar for <span class="html-italic">CaLOL1</span>, green accessions have a frequency of 118(41*)/239, and yellow accessions exhibit a frequency of 15(3*)/19). <span class="html-italic">CaGLK2</span> shows no variation in green accessions (0/239), whereas yellow accessions display a frequency of 2(1*)/19. Data are derived from a total of 258 materials.</p>
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<p>Comparative transcriptome and gene ontology enrichment analysis of parental lines C20 (Yellow parent) and C62 (Green parent) across four developmental stages. (<b>a</b>) Developmental stages of pepper fruit from parental lines C20 and C62, including 1, 4, 7, and 21 DAF. Scale bar = 30 mm. (<b>b</b>) Heatmap of transcript per million (TPM) expression values (Z-score) for candidate genes involved in chlorophyll biosynthesis and photosynthesis in C20 and C62 at four developmental stages. Higher expression levels are indicated in red, and lower levels in blue. (<b>c</b>) Gene ontology (GO) enrichment analysis of upregulated genes in C20, highlighting terms related to ADP binding, heme binding, oxidoreductase activity, iron ion binding, and UDP-glycosyltransferase activity. (<b>d</b>) GO enrichment analysis of upregulated genes in C62, with significant enrichment in terms related to photosynthesis, including photosystem I, photosystem II, and the photosystem II oxygen-evolving complex (in red), as well as additional molecular functions and cellular components associated with photosynthesis and cell organization. The size of each circle represents the number of genes in each category, and the color gradient indicates the adjusted p-value of enrichment significance.</p>
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<p>Effect of different genotypic combinations of candidate genes <span class="html-italic">CaAPRR2</span> and <span class="html-italic">CaGLK2</span> on pepper fruit color. Fruit color phenotypes for each genotype combination of <span class="html-italic">CaAPRR2</span> (Y = yellow homozygous, H = heterozygous, G = green homozygous) and <span class="html-italic">CaGLK2</span> (Y = yellow homozygous, H = heterozygous, G = green homozygous) are shown. The horizontal axis represents <span class="html-italic">CaGLK2</span> genotypes, and the vertical axis represents <span class="html-italic">CaAPRR2</span> genotypes. The gradient arrow illustrates the transition in fruit color from yellow to green as the genotypic combination shifts from YY to GG.</p>
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17 pages, 4272 KiB  
Article
Characterization of Volatile Compounds and Odorants in Different Sichuan Pepper Varieties in Tallow Hotpot
by Wenhua Li, Qiaojun Wang, Huilin Huan, Gangcheng Wu, Qingzhe Jin, Youfeng Zhang and Xingguo Wang
Foods 2025, 14(4), 627; https://doi.org/10.3390/foods14040627 - 13 Feb 2025
Viewed by 363
Abstract
Sichuan pepper plays a vital role in enhancing the flavor of hotpot. However, the specific flavor compounds involved are still unclear. In this study, the key aroma components of Sichuan pepper tallow hotpot were explored. Six aroma attributes were evaluated by quantitative descriptive [...] Read more.
Sichuan pepper plays a vital role in enhancing the flavor of hotpot. However, the specific flavor compounds involved are still unclear. In this study, the key aroma components of Sichuan pepper tallow hotpot were explored. Six aroma attributes were evaluated by quantitative descriptive sensory analysis (QDA). Gas chromatography–mass spectrometry (GC-MS) identified 56 compounds. Among them, a total of 27 aroma-active compounds were identified by gas chromatography–olfactometry (GC-O) and aroma extract dilution analysis (AEDA). Sixteen aroma-active compounds were determined using odor activity values (OAVs) ≥ 1. Linalool, linalyl acetate, D-limonene, sabinene, β-myrcene, eucalyptol, α-terpineol, terpinen-4-ol, acetic acid, (E,E)-2,4-decadienal, (E)-2-heptenal, and others were identified as the key aroma compounds. Chemometrics analysis indicated that the aroma of green Sichuan pepper tallow hotpot was green, and the aroma of different red Sichuan pepper tallow hotpots varied significantly. The research results serve as a foundation for the quality control and production of the hotpot industry. Full article
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<p>Radar map for sensory evaluation of flavor of Sichuan pepper tallow hotpot.</p>
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<p>Differences of volatile compounds in six Sichuan pepper tallow hotpots. (<b>A</b>) The relative content percentage of volatile compounds categories. (<b>B</b>) The average relative volatile compounds content in each category.</p>
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<p>PCA and OPLS-DA of volatile compounds from six Sichuan pepper tallow hotpots. (<b>A</b>) PCA. (<b>B</b>) HCA. (<b>C</b>) OPLS-DA. (<b>D</b>) Distribution plot. (<b>E</b>) VIP analysis.</p>
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<p>Volatile compounds in six Sichuan pepper tallow hotpots of heat map analysis.</p>
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<p>Correlation between sensory descriptors and volatile compounds by PLSR.</p>
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21 pages, 4293 KiB  
Article
A Highly Robust Encoder–Decoder Network with Multi-Scale Feature Enhancement and Attention Gate for the Reduction of Mixed Gaussian and Salt-and-Pepper Noise in Digital Images
by Milan Tripathi, Waree Kongprawechnon and Toshiaki Kondo
J. Imaging 2025, 11(2), 51; https://doi.org/10.3390/jimaging11020051 - 10 Feb 2025
Viewed by 365
Abstract
Image denoising is crucial for correcting distortions caused by environmental factors and technical limitations. We propose a novel and highly robust encoder–decoder network (HREDN) for effectively removing mixed salt-and-pepper and Gaussian noise from digital images. HREDN integrates a multi-scale feature enhancement block in [...] Read more.
Image denoising is crucial for correcting distortions caused by environmental factors and technical limitations. We propose a novel and highly robust encoder–decoder network (HREDN) for effectively removing mixed salt-and-pepper and Gaussian noise from digital images. HREDN integrates a multi-scale feature enhancement block in the encoder, allowing the network to capture features at various scales and handle complex noise patterns more effectively. To mitigate information loss during encoding, skip connections transfer essential feature maps from the encoder to the decoder, preserving structural details. However, skip connections can also propagate redundant information. To address this, we incorporate attention gates within the skip connections, ensuring that only relevant features are passed to the decoding layers. We evaluate the robustness of the proposed method across facial, medical, and remote sensing domains. The experimental results demonstrate that HREDN excels in preserving edge details and structural features in denoised images, outperforming state-of-the-art techniques in both qualitative and quantitative measures. Statistical analysis further highlights the model’s ability to effectively remove noise in diverse, complex scenarios with images of varying resolutions across multiple domains. Full article
(This article belongs to the Special Issue Celebrating the 10th Anniversary of the Journal of Imaging)
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<p>Images corrupted by mixed Gaussian (G) and random salt-and-pepper (RSP) noise: (<b>a</b>) G:10 + RSP, (<b>b</b>) G:30 + RSP, (<b>c</b>) G:50 + RSP, (<b>d</b>) G:70 + RSP, (<b>e</b>) G:90 + RSP.</p>
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<p>Architecture of the proposed HREDN.</p>
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<p>Architecture of the multi-scale feature enhancement block.</p>
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<p>In-depth architecture of proposed attention block.</p>
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<p>Visual comparison among eight facial image denoising methods on a single testing image from the FER2013 dataset with noise level (G:30 + RSP).</p>
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<p>Visual comparison results for eight facial image denoising methods on single testing image from CKPLUS dataset with noise level (G:30 + RSP).</p>
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<p>Visual comparison results for eight CT scan image denoising methods on single testing image from Curated COVID CT dataset with noise level (G:30 + RSP).</p>
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<p>Visual comparison results for eight remote sensing image denoising methods on single testing image from NWPU-RESISC45 dataset with noise level (G:30 + RSP).</p>
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15 pages, 4172 KiB  
Article
The Transcription Factor CcMYB330 Regulates Capsaicinoid Biosynthesis in Pepper Fruits
by Hong Cheng, Mingxian Zhang, Guining Fang, Mengjuan Li, Ruihao Zhang, Qiaoli Xie, Shu Han, Junheng Lv and Minghua Deng
Int. J. Mol. Sci. 2025, 26(4), 1438; https://doi.org/10.3390/ijms26041438 - 8 Feb 2025
Viewed by 440
Abstract
Pepper is an important vegetable and economic crop, and the MYB family is one of the most numerous transcription factor families in plants, extensively participating in various biological processes such as plant growth, development, and stress resistance. In this study, CcMYB330 is identified [...] Read more.
Pepper is an important vegetable and economic crop, and the MYB family is one of the most numerous transcription factor families in plants, extensively participating in various biological processes such as plant growth, development, and stress resistance. In this study, CcMYB330 is identified as a differentially expressed gene in the pepper fruit, and CcMYB330 is expressed with higher expression levels in the placenta and pericarp at different development stages of pepper fruit. Analysis of the promoter cis-elements revealed that this gene contains not only core elements but also environmental factor response elements and plant hormone response elements. The silencing of CcMYB330 could reduce the capsaicinoid accumulation in pepper fruit, while the overexpression of CcMYB330 could increase capsaicinoid accumulation. Additionally, silencing or overexpressing CcMYB330 could regulate the expression of structural genes involved in capsaicinoid biosynthesis. In addition, through yeast one-hybrid experiments, we identified an interaction between CcMYB330 and the capsaicinoid biosynthesis structural gene CcPAL. Further evidence from EMSA experiments and dual luciferase assays confirmed that CcMYB330 can bind to the cis-element ACCAACAACCAAA in the CcPAL promoter. These results indicate that CcMYB330 may regulate the synthesis of capsaicinoids by modulating structural genes in the capsaicinoid biosynthesis pathway, providing new insights into the regulatory mechanisms of capsaicinoid synthesis. Full article
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<p>Schematic diagram of the biosynthetic pathway of capsaicin [<a href="#B8-ijms-26-01438" class="html-bibr">8</a>].</p>
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<p>Sequence structure and evolutionary characteristics analysis of <span class="html-italic">CcMYB330</span>. (<b>A</b>) Phylogenetic tree and promoter <span class="html-italic">cis</span>-element analysis of MYB transcription factors. (<b>B</b>) Alignment of <span class="html-italic">MYB330</span> amino acid sequences.</p>
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<p>Analysis of characteristics of <span class="html-italic">CcMYB330</span>. (<b>A</b>) Subcellular localization results of <span class="html-italic">CcMYB330</span>. (<b>B</b>) <span class="html-italic">CcMYB330</span> lacks transcriptional activation activity. pCL1: as a positive control; pGBKT7::00: as a negative control. (<b>C</b>) Prediction of <span class="html-italic">cis</span>-elements in the <span class="html-italic">CcMYB330</span> promoter.</p>
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<p>Expression analysis of <span class="html-italic">CcMYB330</span>. (<b>A</b>) Fruits at different developmental stages. (<b>B</b>) Relative expression levels of <span class="html-italic">CcMYB330</span> in different tissues of the fruit placenta at various stages. The letters above the bars indicate significant differences determined by Student’s <span class="html-italic">t</span>-tests (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effects of <span class="html-italic">CcMYB330</span> gene silencing. (<b>A</b>) Relative expression levels of the <span class="html-italic">CcMYB330</span> gene in silenced fruits and the letters above the column indicate significant differences. pTRV2::00: as a negative control. (<b>B</b>) Contents of capsaicin and dihydrocapsaicin after silencing of the <span class="html-italic">CcMYB330</span> gene. pTRV2::00: as a control group and it represents the transient expression of pTRV1 and the pTRV2 empty vector; pTRV2::<span class="html-italic">CcMYB330</span>: as an experimental group and it represents the transient expression of pTRV1 and the pTRV2-<span class="html-italic">CcMYB330</span>. (<b>C</b>) Relative expression levels of capsaicin biosynthetic genes in the placenta of silenced fruits. The letters above the bars indicate significant differences determined by Student’s <span class="html-italic">t</span>-tests (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effects of transient overexpression of the <span class="html-italic">CcMYB330</span> gene on capsaicin synthesis. (<b>A</b>) GUS staining images of different treatments in the overexpression system. pCambia 1301::00: as a negative control. (<b>B</b>) Relative expression levels of the <span class="html-italic">CcMYB330</span> gene in silenced fruits. (<b>C</b>) Contents of capsaicin and dihydrocapsaicin after transient overexpression of the <span class="html-italic">CcMYB330</span> gene. pCambia 1301::00: as a control group and it represents the transient expression of the pCambia 1301 empty vector; pCambia 1301::<span class="html-italic">CcMYB330</span>: as an experimental group and it represents the transient expression of the pCambia 1301-<span class="html-italic">CcMYB330</span>. (<b>D</b>) Relative expression levels of structural genes for capsaicin synthesis in pepper fruits with transient overexpression of the <span class="html-italic">CcMYB330</span>. The letters above the bars indicate significant differences determined by Student’s <span class="html-italic">t</span>-tests (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Interaction between <span class="html-italic">CcMYB330</span> and the <span class="html-italic">CcPAL</span> promoter. (<b>A</b>) Yeast one-hybrid experiment demonstrating the interaction between <span class="html-italic">CcMYB330</span> and the <span class="html-italic">CcPAL</span> promoter. pLacZi Control Vector + pB42AD Control Vector: as a positive control; pLacZi::<span class="html-italic">CcPAL</span> + pb42AD::00: as a negative control; pLacZi::<span class="html-italic">CcPAL</span> + pb42AD::<span class="html-italic">CcMYB330</span>: as an experimental group. (<b>B</b>) Electrophoretic mobility shift assay showing that the <span class="html-italic">CcMYB330</span> protein can bind to the <span class="html-italic">CcPAL</span> promoter element ACCAACAACCAAA. (<b>C</b>) Schematic diagram of the dual luciferase reporter gene constructs for 0800-LUC::<span class="html-italic">CcPAL</span> and effector gene 62SK::<span class="html-italic">CcMYB330</span>. (<b>D</b>) LUC in vivo imaging shows that <span class="html-italic">CcMYB330</span> activates <span class="html-italic">CcPAL</span> transcription. pGreenII 62SK + pGreenII 0800-LUC: as a negative control; pGreenII 62SK::<span class="html-italic">CcMYB330</span> + pGreenII 0800-LUC::<span class="html-italic">CcPAL</span>:: as an experimental group. (<b>E</b>) The ratio of LUC to REN in the LUC assay indicates activity. The letters above the bars indicate significant differences determined by Student’s <span class="html-italic">t</span>-tests (<span class="html-italic">p</span> &lt; 0.05).</p>
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21 pages, 1399 KiB  
Article
Use of Black Pepper Essential Oil to Produce a Healthier Chicken Pâté
by Sandra S. Q. Rodrigues, Ana Leite, Lia Vasconcelos, Etelvina Pereira, Natália L. Seixas, Leticia Estevinho and Alfredo Teixeira
Appl. Sci. 2025, 15(4), 1733; https://doi.org/10.3390/app15041733 - 8 Feb 2025
Viewed by 719
Abstract
This study aims to explore the effect of using black pepper essential oil (BPEO) to produce a healthier chicken pâté. Four different formulations were produced: a control formulation without back pepper and three with increasing BPEO contents. To test the effect of using [...] Read more.
This study aims to explore the effect of using black pepper essential oil (BPEO) to produce a healthier chicken pâté. Four different formulations were produced: a control formulation without back pepper and three with increasing BPEO contents. To test the effect of using BPEO, physiochemical analyses were performed at two different moments, 8 and 21 days after production. Microbiological analyses were performed 2, 9, 16, and 23 days after production. Sensory analysis to evaluate the pleasantness of the pâtés to consumers was performed 21 days after production. Finally, total phenol and flavonoid content and antioxidant activity were evaluated. Results show no significant physicochemical differences. Pâtés with no BPEO or black garlic were the most pleasant, but 0.3 or 0.5% of BPEO were not significantly less appreciated, while 1% of the EO caused a decrease in taste and global appreciation. The higher the BPEO content, the higher the phenol content, antioxidant (with an increase from 1.58 to 2.27 mg eq. Fe II/g of sample, in the Control at T23 and V3 at T23, respectively), and microbial activity (with total mesophiles count reduction from 5.91 to 5.21 log CFU/g sample in V3 from T9 to T16). The use of 1% of BPEO showed a significant effect on the reduction in mesophile counts for at least two weeks. These results highlight the potential for optimizing BPEO or black garlic content to ensure both consumer acceptance and enhanced functional properties. While further analysis will help pinpoint the best formulation, the current findings are a promising step towards achieving an optimal balance. Full article
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<p>Production process for chicken pâtés.</p>
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<p>Boxplots of the sensory variability of the chicken pâtés.</p>
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25 pages, 5428 KiB  
Article
Research on Fault Diagnosis of Marine Diesel Engines Based on CNN-TCN–ATTENTION
by Ao Ma, Jundong Zhang, Haosheng Shen, Yang Cao, Hongbo Xu and Jiale Liu
Appl. Sci. 2025, 15(3), 1651; https://doi.org/10.3390/app15031651 - 6 Feb 2025
Viewed by 458
Abstract
In response to the typical fault issues encountered during the operation of marine diesel engines, a fault diagnosis method based on a convolutional neural network (CNN), a temporal convolutional network (TCN), and the attention mechanism (ATTENTION) is proposed, referred to as CNN-TCN–ATTENTION. This [...] Read more.
In response to the typical fault issues encountered during the operation of marine diesel engines, a fault diagnosis method based on a convolutional neural network (CNN), a temporal convolutional network (TCN), and the attention mechanism (ATTENTION) is proposed, referred to as CNN-TCN–ATTENTION. This method successfully addresses the issue of insufficient feature extraction in previous fault diagnosis algorithms. The CNN is employed to capture the local features of diesel engine faults; the TCN is employed to explore the correlations and temporal dependencies in sequential data, further obtaining global features; and the attention mechanism is introduced to assign different weights to the features, ultimately achieving intelligent fault diagnosis for marine diesel engines. The results of the experiments demonstrate that the CNN-TCN–ATTENTION-based model achieves an accuracy of 100%, showing superior performance compared to the individual CNN, TCN, and CNN-TCN methods. Compared with commonly used algorithms such as Transformer, long short-term memory (LSTM), Gated Recurrent Unit (GRU), and Deep Belief Network (DBN), the proposed method demonstrates significantly higher accuracy. Furthermore, the model maintains an accuracy of over 90% in noise environments such as random noise, Gaussian noise, and salt-and-pepper noise, demonstrating strong diagnostic performance, generalization capability, and noise robustness. This provides a theoretical basis for its practical application in the fault diagnosis of marine diesel engines. Full article
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<p>Structure of CNN.</p>
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<p>Principle of the convolution operation, with an outline highlighting the region of the dot product.</p>
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<p>Principle of the pooling process, with an outline highlighting the sliding region.</p>
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<p>Architectural principle of TCN.</p>
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<p>Principle of causal convolution.</p>
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<p>Principle of dilated convolution.</p>
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<p>Residual block of TCN.</p>
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<p>Principle of attention.</p>
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<p>Structure of CNN-TCN–ATTENTION.</p>
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<p>Flowchart of CNN-TCN–ATTENTION.</p>
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<p>W6X72DF simulation model.</p>
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<p>Deviation rates of diesel engine parameters at different fault severities.</p>
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<p>Training and validation accuracy and loss rates for different numbers of convolution layers.</p>
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<p>Training and validation accuracy and loss rates for different numbers of convolution layers.</p>
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<p>Confusion matrices of different models: (<b>a</b>) CNN, (<b>b</b>) TCN, (<b>c</b>) CNN-TCN, and (<b>d</b>) CNN-TCN–ATTENTION.</p>
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<p>Confusion matrices of different models: (<b>a</b>) CNN, (<b>b</b>) TCN, (<b>c</b>) CNN-TCN, and (<b>d</b>) CNN-TCN–ATTENTION.</p>
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<p>Test accuracy under different noise conditions.</p>
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<p>Confusion matrices of different models: (<b>a</b>) Transformer model, (<b>b</b>) LSTM model, (<b>c</b>) GRU model, and (<b>d</b>) DBN model.</p>
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<p>Confusion matrices of different models: (<b>a</b>) Transformer model, (<b>b</b>) LSTM model, (<b>c</b>) GRU model, and (<b>d</b>) DBN model.</p>
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20 pages, 10615 KiB  
Article
Dietary Capsaicin Exacerbates Gut Microbiota Dysbiosis and Mental Disorders in Type 1 Diabetes Mice
by Xiaohui Zhang, Houjia Hu, Yue Zhang, Shuting Hu, Jiaqin Lu, Weijie Peng and Dan Luo
Nutrients 2025, 17(3), 593; https://doi.org/10.3390/nu17030593 - 6 Feb 2025
Viewed by 756
Abstract
Background/Objectives: Diabetes mellitus is often accompanied by mental health complications, including anxiety, depression, and cognitive decline. Recent research suggested that capsaicin, the active component of chili peppers, may influence mental health. This study aimed to determine the effect of dietary capsaicin on [...] Read more.
Background/Objectives: Diabetes mellitus is often accompanied by mental health complications, including anxiety, depression, and cognitive decline. Recent research suggested that capsaicin, the active component of chili peppers, may influence mental health. This study aimed to determine the effect of dietary capsaicin on mental disorders in a type 1 diabetes (T1D) mouse model, while also exploring the potential involvement of the microbiota-gut-brain axis. Methods: We induced T1D in mice using streptozotocin (STZ) and administered a diet supplemented with 0.005% capsaicin for five weeks. Behavioral assessments, including the open field test (OFT), tail suspension test (TST), forced swimming test (FST), elevated plus maze (EPM) test, and Morris water maze (MWM) test, were conducted to evaluate depressive and anxiety-like behaviors as well as cognitive function. Targeted and untargeted metabolomics analyses were performed to assess neurotransmitter levels in the hippocampus and serum metabolites, while 16S rRNA sequencing was utilized to analyze gut microbiota composition. Intestinal barriers were determined using western blot detection of the tight junction proteins ZO-1 and occludin. Results: Dietary capsaicin exacerbated anxiety and depressive-like behaviors along with cognitive declines in T1D mice. Capsaicin reduced gut microbiota diversity and levels of beneficial bacteria, while broad-spectrum antibiotic treatment further intensified anxiety and depression behaviors. Metabolomic analysis indicated that capsaicin disrupted metabolic pathways related to tryptophan and phenylalanine, leading to decreased neuroprotective metabolites, such as kynurenic acid, hippurate, and butyric acid. Additionally, capsaicin diminished the expression of ZO-1 and occludin, indicating increased intestinal permeability. Conclusions: Dietary capsaicin aggravates gut microbiota and metabolic disturbances in diabetic mice, thereby worsening anxiety, depression, and cognitive decline. Full article
(This article belongs to the Special Issue Diet, Gut Microbiota and Neuropsychiatric Diseases)
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<p>Effects of dietary capsaicin on the general condition of STZ-induced type 1 diabetes Mice (DM). (<b>A</b>) The schematic representation of the animal experiment. (<b>B</b>) Fasting blood glucose. (<b>C</b>) Body weight. (<b>D</b>) The average daily food intake. Data are presented as mean ± SEM (n = 7–8 mice); one-way ANOVA; post hoc Bonferroni test; * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>(<b>A</b>–<b>D</b>) The representative movement tracks, time spent in the center, traveled distance in the center and entries into the center in the open field test (OFT). (<b>E</b>–<b>H</b>) The representative movement tracks, total distance, distance traveled, and percentage of time spent on the open arms in elevated plus maze test (EPM). (<b>I</b>–<b>L</b>) The total traveled distance in the OFT, the immobility time in the forced swimming test (FST), and the immobility time in the tail suspension test (TST). (<b>M</b>–<b>O</b>) Cognitive Function: The representative movement tracks, learning phase, and 4 day memory retention phase of the Morris water maze test (MWM). All the values are expressed as mean ± SEM (n = 7–8 mice); one-way ANOVA; post hoc Bonferroni test; * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Targeted metabolomics identified the differential neurotransmitters in hippocampus among groups. (<b>A</b>) The heatmap of the differential neurotransmitters in the hippocampus. (<b>B</b>,<b>C</b>) Volcano plot of differential neurotransmitters in hippocampus, Red = up and blue = down. (<b>D</b>) Representative altered neurotransmitters. All the values are expressed as mean ± SEM (n = 6 mice); one-way ANOVA; post hoc Bonferroni test; * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Effect of dietary capsaicin on the gut microbiota in DM mice based on 16S rRNA gene analysis. (<b>A</b>) Partial least squares discriminant analysis (PLSDA) for 16S sequencing data. (<b>B</b>) Box diagram based on unweighted UniFrac beta diversity. (<b>C</b>) The alpha-diversity indices including the Chao1 index, ACE index, Simpson index, and Shannon index. (<b>D</b>) Heatmap of gut microbiota composition at the genus level. (<b>E</b>) Relative abundance of beneficial bacteria (<span class="html-italic">Akkermansia</span>, <span class="html-italic">Streptococcus</span>, <span class="html-italic">Faecalicoccus</span>). (<b>F</b>) Relative abundance of harmful bacteria (<span class="html-italic">Alistipes</span>, <span class="html-italic">Anaerotruncus</span>, <span class="html-italic">Acetatifactor muris</span>). (<b>G</b>) Relative abundance of SCFA–producing bacteria (<span class="html-italic">Allobaculum</span>, <span class="html-italic">Olsenella</span>, <span class="html-italic">Erysipelotrichaceae</span>, <span class="html-italic">Barnesiella intestinihominis</span>, <span class="html-italic">Eubacterium uniforme</span>). All the values are expressed as mean ± SEM (n = 6 mice); Kruskal–Wallis test followed by Dunn’s post hoc test (* <span class="html-italic">p</span>-value &lt; 0.05, ** <span class="html-italic">p</span>-value &lt; 0.01).</p>
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<p>Serum metabolomics detected by untargeted metabolomics. (<b>A</b>) Partial least squares discriminant analysis (PLSDA) for metabolomic data. (<b>B</b>) Volcano plot of differentially expressed metabolites in serum, Red = up and blue = down. (<b>C</b>) Heatmap of the top 25 up- and 25 down- regulated (fold change) serum metabolites between different groups. (<b>D</b>,<b>E</b>) KEGG pathway analysis. (<b>F</b>) Representative transmitters and hormones with significant differences in serum. (<b>G</b>) Levels of butyric acid. (<b>H</b>) Representative metabolites in three pathways of tryptophan metabolism. (<b>I</b>) Representative metabolites in phenylalanine metabolism pathway. All the values are expressed as mean ± SEM (n = 6 mice); Kruskal–Wallis test followed by Dunn’s post hoc test (* <span class="html-italic">p</span>-value &lt; 0.05, ** <span class="html-italic">p</span>-value &lt; 0.01).</p>
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<p>Spearman correlation analysis of gut microbiota, serum metabolites, and hippocampal neurotransmitters. (<b>A</b>) The Spearman’s rank correlation coefficient between gut differential microbiota and serum differential metabolites. (<b>B</b>) The Spearman’s rank correlation coefficient between gut differential microbiota and hippocampal differential neurotransmitters. * <span class="html-italic">p</span> &lt; 0.05, ** <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>Effect of dietary capsaicin on the expression of intestinal tight junction protein ZO-1 and occludin in DM mice. Effect of dietary capsaicin on the expression of intestinal tight junction protein ZO-1 and occludin in DM mice. All the values are expressed as mean ± SEM (n = 3 mice); one-way ANOVA; post hoc Bonferroni test; * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Gut microbiota depletion exacerbates anxiety and depressive-like behaviors in DM mice with capsaicin diet. (<b>A</b>) The time spent in the center and traveled distance in the center in the open field test (OFT). (<b>B</b>) The total traveled distance in OFT. (<b>C</b>) The immobility time in the forced swimming test (FST). All the values are expressed as mean ± SEM (n = 3 mice); one-way ANOVA; post hoc Bonferroni test; * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01.</p>
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15 pages, 1345 KiB  
Article
Indole-2-Carboxamide as an Effective Scaffold for the Design of New TRPV1 Agonists
by Samuele Maramai, Claudia Mugnaini, Marco Paolino, Aniello Schiano Moriello, Luciano De Petrocellis, Federico Corelli, Francesca Aiello and Antonella Brizzi
Molecules 2025, 30(3), 721; https://doi.org/10.3390/molecules30030721 - 5 Feb 2025
Viewed by 452
Abstract
Due to its central role in pain, inflammation, and related disorders, the Transient Receptor Potential (TPR) Vanilloid Type-1 (TRPV1) ion channel represents an attractive target for the development of novel antinociceptive and anti-inflammatory agents. Capsaicin, the natural component of chili peppers, is one [...] Read more.
Due to its central role in pain, inflammation, and related disorders, the Transient Receptor Potential (TPR) Vanilloid Type-1 (TRPV1) ion channel represents an attractive target for the development of novel antinociceptive and anti-inflammatory agents. Capsaicin, the natural component of chili peppers, is one of the most investigated agonists of this receptor. Several modifications of its structure have been attempted, aiming at finding TRPV1 agonists with improved characteristics, but, to date, no capsaicin-derived agents have reached the market. Based on our previous knowledge of the design and synthesis of TRPV1 agonists, in this paper we propose two small series of indole-2-carboxamides as novel and selective agonists for this ion channel. The newly developed compounds have been structurally characterized and tested in vitro for their ability to modulate TRPV1, in terms of efficacy, potency (EC50), and desensitization (IC50) properties. For the most promising derivatives, selectivity over the TRP ankyrin-1 (TRPA1) channel has been reported. From our study, compound 6g arose as a promising candidate for further evaluation, also in correlation with its in silico-predicted drug-like properties. Full article
(This article belongs to the Section Medicinal Chemistry)
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<p>Structure of capsaicin (1) and previously reported TRPV1 agonists exemplified by lead compounds <b>2</b>, <b>3</b>, and <b>4a</b>–<b>d</b>. EC<sub>50</sub>/IC<sub>50</sub> values refer to the potency and desensitization of the compounds on TRPV1, respectively.</p>
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<p>General structures of the title compounds <b>5a</b>–<b>i</b> and <b>6a</b>–<b>j</b>.</p>
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<p>Structure and SwissADME property prediction [<a href="#B33-molecules-30-00721" class="html-bibr">33</a>] for compound <b>6g</b>. The red-colored zone in the spider web diagram is the suitable space for oral bioavailability. LIPO (lipophilicity): −0.7 &lt; XLOGP3 &lt; +5.0; SIZE: 150 g/mol &lt; MW &lt; 500 g/mol; POLAR (polarity): 20 Å<sup>2</sup> &lt; TPSA &lt; 130 Å<sup>2</sup>; INSOLU (insolubility): −6 &lt; Log S (ESOL) &lt; 0; INSATU (insaturation): 0.25 &lt; Fraction Csp3 &lt; 1; FLEX (flexibility): 0 &lt; num. Rotable bonds &lt; 9.</p>
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<p>The synthetic procedure leading to the title compounds <b>5a</b>–<b>i</b> and <b>6a</b>–<b>j</b>. Reagents and conditions: (<b>a</b>) Method A: suitably substituted amine or aniline, EDCI, HOBt, dry DCM (<b>6b</b>–<b>f</b>, <b>6h</b>–<b>i</b>) or HPLC-grade ACN (<b>5a</b>–<b>e</b>, <b>5g</b>–<b>h</b>, <b>6a</b>), rt, 12 h; Method B: suitable amine hydrochloride, HBTU, HOBt, DIPEA, dry DMF, rt, 12 h (<b>5f</b>, <b>5i</b>, <b>6g</b>, <b>6j</b>); (<b>b</b>) DMC, K<sub>2</sub>CO<sub>3</sub>, dry DMF, 150 °C, 6 h; (<b>c</b>) EtOH/aq. NaOH, reflux, 4 h.</p>
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10 pages, 933 KiB  
Article
Radiation Treatment Planning After Minimum Metallic Instrumentation for Patients with Spinal Metastases: A Case Series
by Jan-Niklas Becker, Mirko Fischer, Hans Christiansen, Michael Schwake, Walter Stummer, Christian Ewelt, Niklas Benedikt Pepper, Hans Theodor Eich and Michael Müther
Medicina 2025, 61(2), 269; https://doi.org/10.3390/medicina61020269 - 5 Feb 2025
Viewed by 426
Abstract
Background and Objectives: The utilization of non-metallic pedicle screws and rods has become a favored approach in the management of spinal tumors. An abundance of metal artifacts improves postoperative imaging and allows for precise radiation treatment planning. Under certain conditions, a vertebral [...] Read more.
Background and Objectives: The utilization of non-metallic pedicle screws and rods has become a favored approach in the management of spinal tumors. An abundance of metal artifacts improves postoperative imaging and allows for precise radiation treatment planning. Under certain conditions, a vertebral body replacement (VBR) is necessary in addition to dorsal fixation. For a long time, VBR hardware was available as titanium implants only. Recently, other non-titanium products were introduced into the market. This study compares radiotherapy planning after VBR with titanium and non-titanium materials. Materials and Methods: This is a retrospective cohort study in a single academic center setting. VBR was performed for thoracic spinal metastatic disease. Radiation plan quality was evaluated according to the criteria of the International Commission on Radiation Units and Measurements, based on postoperative CT imaging. Results: Six patients with dorsal fixation and VBR were included, half of which were treated with titanium VBR and the other half with a minimum metallic implant. In addition, patients received different dorsal fixation hardware. No difference was found in terms of radiation plan quality. With non-titanium materials, visual demarcation during radiation planning was superior. Conclusions: This is the first study in the field to comprehensively compare radiation treatment planning after VBR using different materials. With minimum metallic implants, radiotherapy planning is equal in terms of planning but superior in terms of visual demarcation in comparison to standard titanium VBR, potentially enabling more precise radiotherapy approaches. Full article
(This article belongs to the Section Oncology)
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<p>Illustration of dose distribution in volumetric modulated arc therapy radiation planning. Planning after full MMI instrumentation with PEEK VBR and CRF-PEEK dorsal fixation in patient 1 (<b>a</b>). (<b>b</b>) shows case of patient 7 after full titanium VBR and dorsal fixation. Planning target volume is outlined in red Dose is represented with color wash gradient.</p>
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16 pages, 6157 KiB  
Article
The MADS-Box Transcription Factor CaRIN Positively Regulates Chlorophyll Degradation During Pepper (Capsicum annuum L.) Fruit Ripening by Repressing the Expression of CaLhcb-P4
by Yingying Song, Qing Cheng, Xingzhe Li, Shijie Ma, Huolin Shen and Liang Sun
Plants 2025, 14(3), 445; https://doi.org/10.3390/plants14030445 - 3 Feb 2025
Viewed by 667
Abstract
Pepper (Capsicum spp.) is an important global vegetable and spice, with fruit color being a key determinant of its commercial quality. However, the regulatory mechanisms underlying pepper fruit color are still not fully understood. This study focuses on the MADS-RIPENING INHIBITOR (MADS-RIN), [...] Read more.
Pepper (Capsicum spp.) is an important global vegetable and spice, with fruit color being a key determinant of its commercial quality. However, the regulatory mechanisms underlying pepper fruit color are still not fully understood. This study focuses on the MADS-RIPENING INHIBITOR (MADS-RIN), a MADS-box transcription factor that regulates various aspects of fruit ripening, including pigmentation. We identified CaRIN, a homolog of tomato’s SlRIN, whose expression is closely associated with fruit ripening in pepper. Silencing CaRIN through virus-induced gene silencing (VIGS) resulted in increased chlorophyll and chlorophyll a content, reduced carotenoid accumulation, and uneven fruit coloration. Integrative analysis of the RNA-seq and DAP-seq data identified 77 target genes regulated by CaRIN, which was involved in processes such as chlorophyll metabolism and plant hormone signaling. Yeast one-hybrid (Y1H) and dual-luciferase (LUC) assays demonstrated that CaRIN directly bound to the promoter of CaLhcb-P4, repressing its expression. Downregulation of CaLhcb-P4 in pepper fruits via VIGS accelerated chlorophyll degradation. Additionally, CaRIN indirectly regulated multiple genes associated with chlorophyll and carotenoid metabolism, sugar transport, and cell wall degradation. These findings provide novel insights into the regulatory mechanisms of chlorophyll degradation during pepper fruit ripening, offering a foundation for further research and potential genetic improvement strategies. Full article
(This article belongs to the Special Issue Gene Regulation in Flower and Fruit Development)
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<p><span class="html-italic">CaRIN</span> regulates chlorophyll and carotenoid contents in pepper fruit during ripening. (<b>A</b>) A phylogenetic tree of SlRIN and its homologs in other species. (<b>B</b>) The relative expression levels of <span class="html-italic">CaRIN</span> and <span class="html-italic">CaMADS3</span> in the sweet pepper inbred line 16C391 at various developmental stages: IM (immature green, 22 DPA), MG (mature green, 40 DPA), B (breaker, 49 DPA), B5 (breaker + 5, 54 DPA), and RR (red ripe, 63 DPA). (<b>C</b>) A schematic diagram of VIGS using the vacuum infiltration method. pTVR1 + pTRV2-GFP serves as the negative control, while pTVR1 + pTRV2-CaPDS is used as the positive control. (<b>D</b>) Phenotypic observations of <span class="html-italic">CaRIN</span>-silenced seedlings under white light and UV (top left and middle), light bleaching in the <span class="html-italic">CaPDS</span>-silenced fruit at the mature green stage (top right), <span class="html-italic">CaRIN</span>-silenced fruits at the red ripe stage (bottom right and middle), and fruit from the negative control (bottom left). Scale bar = 1.5 cm. (<b>E</b>) The relative expression of <span class="html-italic">CaRIN</span> and levels of chlorophyll and carotenoids in fruits at 64 DPA from the <span class="html-italic">CaRIN</span>-silenced and negative control plants. The data represent the mean ± SE (n = 3). Significant differences were determined using Student’s <span class="html-italic">t</span>-test (* <span class="html-italic">p</span> &lt; 0.05; *** <span class="html-italic">p</span> &lt; 0.001; ns, not significant).</p>
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<p>RNA-seq analysis of the pericarp collected from <span class="html-italic">CaRIN</span>-silenced and negative control fruits. (<b>A</b>) PCA of RNA-seq data. (<b>B</b>) Volcano plots of the DEGs. (<b>C</b>) GO enrichment analysis of DEGs. (<b>D</b>,<b>E</b>) heatmaps of DEGs related to chloroplast metabolism and carotenoid synthesis. #1, #2 and #3 represent three biological replicates.</p>
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<p>The genome-wide identification of CaRIN binding sites via DAP-seq. (<b>A</b>) A Venn diagram of the two biological replicates of DAP-seq. (<b>B</b>) The distribution of CaRIN binding sites relative to the transcription start sites (TSS). (<b>C</b>) The distribution of CaRIN binding sites across the 12 chromosomes. (<b>D</b>) The localization of CaRIN binding sites in relation to cis-regulatory regions. (<b>E</b>) The primary motif bound by CaRIN. (<b>F</b>) The top enriched GO terms associated with CaRIN-bound genes.</p>
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<p>The Identification of <span class="html-italic">CaRIN</span>-regulated target genes. (<b>A</b>) A Venn diagram showing the overlap between <span class="html-italic">CaRIN</span>-bound genes identified by DAP-seq and DEGs from RNA-seq. (<b>B</b>) The top KEGG pathways enriched in the <span class="html-italic">CaRIN</span>-regulated target genes. (<b>C</b>) The relative expression levels of <span class="html-italic">CaUROS</span> and <span class="html-italic">CaLhcb-P4</span> in <span class="html-italic">CaRIN</span>-silenced and negative control fruits (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>The interaction of CaRIN with <span class="html-italic">CaLhcb-P4</span> and the silencing of CaLhcb-P4 in pepper fruit. (<b>A</b>) The binding peaks of CaRIN (Repeats 1 and 2) and the negative control (input) at the promoter regions of <span class="html-italic">CaLhcb-P4</span> and <span class="html-italic">CaUROS</span>, as determined by DAP-seq. Red arrows represent binding peaks. (<b>B</b>) The Y1H assay of CaRIN interaction with the promoters of <span class="html-italic">CaLhcb-P4</span> and <span class="html-italic">CaUROS</span>. Three independent yeast colonies were tested for each treatment, and the results were observed 3 days post-treatment. (<b>C</b>) A schematic representation of the reporter and effector constructs used in the dual-luciferase assay. (<b>D</b>) The LUC imaging assay confirming that CaRIN directly represses the expression of <span class="html-italic">CaLhcb-P4</span>. (<b>E</b>) The LUC/REN ratio analysis for the detection of CaRIN targeting <span class="html-italic">CaLhcb-P4</span>. LUC, firefly luciferase activity; REN, Renilla luciferase activity. The data are presented as mean values ± SD from three independent biological replicates. (<b>F</b>) The typical phenotype of CaLhcb-P4-silenced and control fruits. Red arrows represent silencing position. Scale bar = 1.5 cm. (<b>G</b>) The relative expression of <span class="html-italic">CaLhcb-P4</span> and chlorophyll content in <span class="html-italic">CaLhcb-P4</span>-silenced and the negative control fruits. The data are expressed as the mean ± SE (n = 3). Statistical significance was assessed by Student’s <span class="html-italic">t</span>-test (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; ns, not significant).</p>
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<p>A proposed model for the regulation of fruit ripening by CaRIN in pepper. CaRIN represses <span class="html-italic">CaLhcb-P4</span> expression by binding the <span class="html-italic">CaLhcb-P4</span> promoter, and then, <span class="html-italic">CaLhcb-P4</span> influences chlorophyll metabolism. CaRIN also indirectly regulates multiple genes associated with chlorophyll and carotenoid metabolism, sugar transport, and cell wall degradation.</p>
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21 pages, 4995 KiB  
Review
Dermoscopy of Basal Cell Carcinoma Part 1: Dermoscopic Findings and Diagnostic Accuracy—A Systematic Literature Review
by Irena Wojtowicz and Magdalena Żychowska
Cancers 2025, 17(3), 493; https://doi.org/10.3390/cancers17030493 - 1 Feb 2025
Viewed by 597
Abstract
Introduction: Basal cell carcinoma (BCC) is the most common malignant skin tumor. While rarely fatal, it can cause local tissue damage. Part I of the review summarizes the dermoscopic features of BCC and the diagnostic accuracy of dermoscopy in the diagnosis of BCC. [...] Read more.
Introduction: Basal cell carcinoma (BCC) is the most common malignant skin tumor. While rarely fatal, it can cause local tissue damage. Part I of the review summarizes the dermoscopic features of BCC and the diagnostic accuracy of dermoscopy in the diagnosis of BCC. Methods: A search of the PubMed database was performed for studies reporting on the diagnostic accuracy of dermoscopy or dermoscopic findings in BCC, either pigmented or non-pigmented, located anywhere on the body, of any histopathologic subtype, size and at any age of onset. Results: BCC was found to present with a wide range of dermoscopic features, including white structures (shiny white lines, shiny white areas, rosettes), yellow structures (milia-like cysts, yellow lobular-like structures), multiple aggregated yellow-white globules (MAY globules), blue structures (blue ovoid nests), vascular structures (arborizing vessels, short fine telangiectasias), multiple small erosions/ulcerations, features of regression (pepper-like structures, white scar-like areas) and pigmented structures (spoke-wheel areas, maple leaf-like areas (MLLAs), blue/gray dots). Dermoscopy showed a sensitivity of 67.6–98.6% and a positive predictive value (PPV) of 85.9–97% in identifying BCC. The physician’s experience and training improve the accuracy, however, BCCs on the trunk and extremities, particularly of superficial subtypes, may still constitute a challenge. Conclusions: Dermoscopy, especially when performed by a trained physician, increases the accuracy of early BCC detection. Full article
(This article belongs to the Special Issue Dermoscopy in Skin Cancer)
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<p>PRISMA flow chart showing the screening process (available also: Wojtowicz I et al. [<a href="#B10-cancers-17-00493" class="html-bibr">10</a>]).</p>
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<p>Dermoscopy images of basal cell carcinomas (BCCs) with shiny white lines (blue arrows).</p>
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<p>Dermoscopy images of BCCs with shiny white blotches (yellow arrows).</p>
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<p>Dermoscopy images of BCCs with milia-like cysts (MLCs) (green arrows).</p>
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<p>Dermoscopy images of BCCs with yellow lobular-like structures (red arrows and red circle).</p>
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<p>Dermoscopy images of BCCs with multiple aggregated yellow-white globules (MAY globules) (yellow circles).</p>
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<p>Dermoscopy images of BCCs with arborizing vessels (yellow arrows).</p>
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<p>Dermoscopy images of BCCs with short fine telangiectasias (green arrows and circles).</p>
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<p>Dermoscopy images of BCCs with multiple small erosions/ulcerations (red arrowheads).</p>
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<p>Dermoscopy images of BCCs with bluish features of regression called “blue areas” or “blue hue” (yellow circles) and “pepper-like structures” (green circles).</p>
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<p>Dermoscopy images of BCCs with white/reddish features of regression called “white scar-like areas”, “white areas” or “milky way areas” (red circles).</p>
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<p>Dermoscopy images of BCCs with spoke-wheel areas (yellow arrows).</p>
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<p>Dermoscopy images of BCCs with maple leaf-like areas—MLLAs (blue arrowheads).</p>
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<p>Dermoscopy images of BCCs with blue-gray ovoid nests (blue arrows).</p>
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<p>Dermoscopy images of BCCs with concentric structures (yellow circles).</p>
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<p>Dermoscopy images of BCCs with multiple blue/gray globules (red circles).</p>
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<p>Dermoscopy images of BCCs with multiple in-focus blue/gray dots (green circles).</p>
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<p>Dermoscopy image of BCC with brown homogeneous blotches (BHB) (yellow circles).</p>
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<p>Dermoscopy image of BCC with large blue-gray structureless areas (yellow arrowhead).</p>
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<p>Dermoscopy image of BCC with semitranslucent areas (red circle).</p>
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