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Search Results (729)

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16 pages, 3710 KiB  
Article
Linear Morphometry of Male Genitalia Distinguishes the Ant Genera Monomorium and Syllophopsis (Hymenoptera: Formicidae) in Madagascar
by Nomena F. Rasoarimalala, Tanjona Ramiadantsoa, Jean Claude Rakotonirina and Brian L. Fisher
Insects 2024, 15(8), 605; https://doi.org/10.3390/insects15080605 (registering DOI) - 11 Aug 2024
Viewed by 134
Abstract
Morphometric analyses of male genitalia are routinely used to distinguish genera and species in beetles, butterflies, and flies, but are rarely used in ants, where most morphometric analyses focus on the external morphology of the worker caste. In this work, we performed linear [...] Read more.
Morphometric analyses of male genitalia are routinely used to distinguish genera and species in beetles, butterflies, and flies, but are rarely used in ants, where most morphometric analyses focus on the external morphology of the worker caste. In this work, we performed linear morphometric analysis of the male genitalia to distinguish Monomorium and Syllophopsis in Madagascar. For 80 specimens, we measured 10 morphometric characters, especially on the paramere, volsella, and penisvalvae. Three datasets were made from linear measurements: mean (raw data), the ratios of characters (ratio data), and the Removal of Allometric Variance (RAV data). The following quantitative methods were applied to these datasets: hierarchical clustering (Ward’s method), unconstrained ordination methods including Principal Component Analysis (PCA), Non-Metric Multidimensional Scaling analyses (NMDS), Linear Discriminant Analysis (LDA), and Conditional Inference Trees (CITs). The results from statistical analysis show that the ratios proved to be the most effective approach for genus-level differentiation. However, the RAV method exhibited overlap between the genera. Meanwhile, the raw data facilitated more nuanced distinctions at the species level compared with the ratios and RAV approaches. The CITs revealed that the ratios of denticle length of the valviceps (SeL) to the paramere height (PaH) effectively distinguished between genera and identified key variables for species-level differentiation. Overall, this study shows that linear morphometric analysis of male genitalia is a useful data source for taxonomic delimitation. Full article
(This article belongs to the Section Insect Systematics, Phylogeny and Evolution)
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Figure 1

Figure 1
<p>Illustration of the linear measurements applied to the (<b>a</b>) paramere, (<b>b</b>) volsella, and (<b>c</b>) penisvalvae taken from <span class="html-italic">Monomorium madecassum</span>. Illustrations by the author.</p>
Full article ">Figure 2
<p>Classification at the genus and species levels based on the raw data using (<b>a</b>) Ward’s method, (<b>b</b>) Principal Component Analysis, (<b>c</b>) Non-Metric Multidimensional Scaling, and (<b>d</b>) Linear Discriminant Analysis. (<b>a</b>) <span class="html-italic">Monomorium</span> is depicted in blue, and <span class="html-italic">Syllophopsis</span> in red. In (<b>b</b>–<b>d</b>), squares and diamonds represent valid species, and round shapes represent morphospecies that are similar to valid species. Crosses and asterisks represent morphospecies distinct from known species.</p>
Full article ">Figure 3
<p>Classification at the genus and species level based on the ratio data using (<b>a</b>) Ward’s method, (<b>b</b>) Principal Component Analysis, (<b>c</b>) Non-Metric Multidimensional Scaling, and (<b>d</b>) Linear Discriminant Analysis. (<b>a</b>) <span class="html-italic">Monomorium</span> is depicted in blue, and <span class="html-italic">Syllophopsis</span> in red. In (<b>b</b>–<b>d</b>), squares and diamonds represent valid species, and round shapes represent morphospecies that are similar to valid species. Crosses and asterisks represent morphospecies distinct from known species.</p>
Full article ">Figure 4
<p>Classification at the genus and species level after the effect of allometric variance was removed (RAV data) using (<b>a</b>) Ward’s method, (<b>b</b>) Principal Component Analysis, (<b>c</b>) Non-Metric Multidimensional Scaling, and (<b>d</b>) Linear Discriminant Analysis. (<b>a</b>) <span class="html-italic">Monomorium</span> is depicted in blue, and <span class="html-italic">Syllophopsis</span> in red. In (<b>b</b>–<b>d</b>), squares and diamonds represent valid species, and round shapes represent morphospecies that are similar to valid species. Crosses and asterisks represent morphospecies distinct from known species.</p>
Full article ">Figure 5
<p>Conditional Inference Trees based on (<b>a</b>) raw data, (<b>b</b>) ratio data, and (<b>c</b>) RAV data were calculated. <span class="html-italic">Monomorium</span> is in light gray, and <span class="html-italic">Syllophopsis</span> is in dark gray. Each node represents a morphometric trait used for classification. Terminal nodes display the proportion of specimens classified into each group, with sample sizes (N) provided.</p>
Full article ">Figure 6
<p>Classification tree from the conditional inference trees (CITs) model (raw data). Each node represents a morphometric trait used for classification. Terminal nodes display the proportion of specimens classified into each species, with sample sizes (N) provided.</p>
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<p>Classification tree from the conditional inference trees (CITs) model (ratio data). Each node represents a morphometric trait used for classification. Terminal nodes display the proportion of specimens classified into each species, with sample sizes (N) provided.</p>
Full article ">Figure 8
<p>Classification tree from the conditional inference trees (CITs) model (RAV data). Each node represents a morphometric trait used for classification. Terminal nodes display the proportion of specimens classified into each species, with sample sizes (N) provided.</p>
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16 pages, 8021 KiB  
Article
On the Trail of Morphological Traits: Morphometry Helps to Clarify Morphological Variation in Section Viperella (Sisyrinchium)
by Julia Gabriele Dani, Camila Dellanhese Inácio and Tatiana T. Souza-Chies
Plants 2024, 13(16), 2183; https://doi.org/10.3390/plants13162183 - 7 Aug 2024
Viewed by 272
Abstract
Sisyrinchium, a large genus of the Iridaceae family, is divided into ten sections and defined by genetic, morphological and phylogenetic traits. The section Viperella, though monophyletic, encounters taxonomic hurdles, particularly within the Sisyrinchium palmifolium L. and Sisyrinchium vaginatum Spreng complexes, resulting [...] Read more.
Sisyrinchium, a large genus of the Iridaceae family, is divided into ten sections and defined by genetic, morphological and phylogenetic traits. The section Viperella, though monophyletic, encounters taxonomic hurdles, particularly within the Sisyrinchium palmifolium L. and Sisyrinchium vaginatum Spreng complexes, resulting in numerous misidentifications. The taxonomic confusion in the group may stem from various factors, emphasizing extensive morphological variations, leading to overlapping characteristics. We used morphometric approaches to better characterize the species belonging to two complexes, assess their variation and identify diagnostic traits for taxonomy enhancement. We assessed 16 quantitative traits for the S. palmifolium complex and 15 for the S. vaginatum complex, totaling 652 specimens recorded across 15 herbaria covering the entire species’ distribution area. In the S. vaginatum complex, 66.5% of the variations were accounted for in the first two axes, while in the S. palmifolium complex, the first two axes explained 55.3%. Our findings revealed that both complexes exhibited many morphological variations, leading to a characteristic overlap. These characteristics may have arisen due to recent diversifications of the group and niche overlaps. Additionally, we identified some morphological characteristics that are useful for distinguishing species. Finally, we compiled a section gathering all useful characteristics for species delimitation within the group, aiming to facilitate non-experts in deciphering this species complex. Full article
(This article belongs to the Special Issue Systematics, Taxonomy and Floristics of Angiosperms)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Representatives of the section <span class="html-italic">Viperella</span>. 1. Flower and leaves of <span class="html-italic">Sisyrinchium marchio</span> (Vell.) Steud. 2. Leaves of <span class="html-italic">Sisyrinchium marchioides</span> Ravenna. 3. <span class="html-italic">Sisyrinchium vaginatum</span> Spreng. 4. Leaves and inflorescence of <span class="html-italic">Sisyrinchium coalitum</span> Ravenna. 5. Leaves and flowers of <span class="html-italic">Sisyrinchium palmifolium</span> L. 6. Inflorescence and leaves (background) of <span class="html-italic">Sisyrinchium bromelioides</span> R. C. Foster. Source: Prepared by the authors.</p>
Full article ">Figure 2
<p>Ordination resulting from PCA based on morphometric data of the <span class="html-italic">Sisyrinchium palmifolium</span> L. complex. The graphic shows the distribution of the individuals in a multivariate space. Each color represents a species and the first two axes together explained 55.3% of variations.</p>
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<p>PCA with ellipses for <span class="html-italic">Sisyrinchium palmifolium</span> L. complex: each color represents a species. Some species, such as <span class="html-italic">Sisyrinchium bromelioides</span> R. C. Foster (grey), showed better delimitation compared to other species, which exhibited significant overlap.</p>
Full article ">Figure 4
<p>Loading plots for <span class="html-italic">Sisyrinchium palmifolium</span> L. complex. In yellow are the characteristics that provided the highest contribution, in purple those that provided a medium contribution and in pink those that provided the lowest contribution.</p>
Full article ">Figure 5
<p>Box plots representing different characteristics that best explained the variations according to the PCA for the <span class="html-italic">Sisyrinchium palmifolium</span> L. complex. The black central line represents the median value for each species and the dots represent outliers. Each color represents a species.</p>
Full article ">Figure 6
<p>Ordination resulted from PCA of morphometric data of the <span class="html-italic">Sisyrinchium vaginatum</span> Spreng complex. The graphic shows the distribution of the individuals in a multivariate space. Each color represents a species and the first two axes together explained 66.5% of the variations in the group.</p>
Full article ">Figure 7
<p>PCA with ellipses: each color represents a species. Some species, such as <span class="html-italic">Sisyrinchium restioides</span> Spreng (pink), showed better delimitation compared to other species, which exhibited significant overlap, particularly <span class="html-italic">Sisyrinchium vaginatum</span> Spreng., <span class="html-italic">Sisyrinchium marchioides</span> Ravenna and <span class="html-italic">Sisyrinchium weirii</span> Baker.</p>
Full article ">Figure 8
<p>Loading plot for <span class="html-italic">Sisyrinchium palmifolium</span> L. complex. In yellow are the characters that provided the highest contribution, in green those that provided a medium contribution and in blue those that provided the lowest contribution.</p>
Full article ">Figure 9
<p>Box plots represent different characteristics that best explained the variations according to the PCA for the <span class="html-italic">Sisyrinchium vaginatum</span> Spreng complex. The black central line represents the median value for each species and the dots represent outliers. Each color represents a different species.</p>
Full article ">Figure 10
<p>Leaves and stems of some species of the <span class="html-italic">Sisyrinchium vaginatum</span> Spreng complex: (<b>A</b>) leaves of <span class="html-italic">Sisyrinchium marchioides</span> Ravenna shortest angle in relation to the stem; (<b>B</b>) <span class="html-italic">Sisyrinchium alatum</span> Hook. larger leaves in relation to <span class="html-italic">S. marchioides</span> and angle of the leaves in relation to the larger stem; (<b>C</b>) plicated leaves of <span class="html-italic">Sisyrinchium plicatulum</span> Ravenna; (<b>D</b>) falciform leaves adhered to the stem of <span class="html-italic">S. vaginatum</span>; (<b>E</b>) linear sheets of <span class="html-italic">Sisyrinchium restioides</span> Spreng; (<b>F</b>) papillae on leaves of <span class="html-italic">Sisyrinchium wettsteinii</span> Hand.-Mazz.</p>
Full article ">Figure 11
<p>Details of inflorescence of some species of the <span class="html-italic">Sisyrinchium palmifolium</span> L. complex. (<b>A</b>) Pseudolateral corymbiform synflorescences of <span class="html-italic">S. palmifolium</span>; (<b>B</b>) pseudolateral paniculiform of <span class="html-italic">Sisyrinchium plicatulum</span> Ravenna; (<b>C</b>) pseudolateral congested synflorescence of <span class="html-italic">Sisyrinchium congestum</span> Klatt; (<b>D</b>) membranous bracteoles of <span class="html-italic">Sisyrinchium coalitum</span> Ravenna; (<b>E</b>) branched paniculate or elongated spiciform synflorescence of <span class="html-italic">Sisyrinchium bromelioides</span> R. C. Foster; (<b>F</b>) congested synflorescences of <span class="html-italic">Sisyrinchium marginatum</span> Klatt.</p>
Full article ">Figure 12
<p>Scheme exemplifying how the measurements of morphological characteristics were obtained. (<b>A</b>) <span class="html-italic">Sisyrinchium alatum</span> Hook. illustrating the measurements of <span class="html-italic">Sisyrinchium vaginatum</span> Spreng complex; (<b>B</b>) <span class="html-italic">Sisyrinchium plicatulum</span> Ravenna illustrating the measurements of floral characters of <span class="html-italic">Sisyrinchium palmifolium</span> L. complex and (<b>C</b>) Image of the leaves indicating the leaf veins present in <span class="html-italic">S. palmifolium</span> complex.</p>
Full article ">
13 pages, 1162 KiB  
Article
Unveiling the Acoustic Signature of Collichthys lucidus: Insights from X-ray Morphometry-Informed Acoustic Modeling and Empirical Analysis
by Shuo Lyu, Chuhan Qiu, Minghua Xue, Zhenhong Zhu, Yue Qiu and Jianfeng Tong
Fishes 2024, 9(8), 304; https://doi.org/10.3390/fishes9080304 - 2 Aug 2024
Viewed by 278
Abstract
Collichthys lucidus is an important small-scale economic fish species in the Yangtze River Estuary. To improve the accuracy of acoustic stock assessments for C. lucidus, it is necessary to accurately measure its target strength (TS). This study obtained precise morphological parameters of [...] Read more.
Collichthys lucidus is an important small-scale economic fish species in the Yangtze River Estuary. To improve the accuracy of acoustic stock assessments for C. lucidus, it is necessary to accurately measure its target strength (TS). This study obtained precise morphological parameters of C. lucidus through X-ray scanning and established a Kirchhoff ray mode (KRM) model to simulate the changes in TS of the fish body and swimbladder at different acoustic frequencies and pitch angles. At the same time, the TS was measured using the tethered method to analyze and compare the broadband scattering characteristics obtained from both methods. An empirical formula of C. lucidus relating TS to body length at two conventional frequencies was established using the least squares method. The results show that the C. lucidus TS changes, with body length ranging from 10.91 to 16.61 cm, are significantly influenced by the pitch angle at 70 kHz and 200 kHz frequencies, and the fluctuation of TS for both the fish body and swimbladder increases with the rise in frequency. The broadband TS values estimated by the KRM model and measured by the tethered method fluctuate within in the ranges from −45 dB to −55 dB and −40 dB to −55 dB, respectively. The TS of C. lucidus tends to increase with the increase in swimbladder length. When the probability density function of the pitch angle is N(−5°, 15°), the b20 measured by the KRM and the tethered method at 70 kHz are −71.94 dB and −69.21 dB, respectively, while at 200 kHz they are −72.58 dB and −70.55 dB. This study provides a scientific basis for future acoustic target discrimination and stock assessment of C. lucidus in the Yangtze River Estuary. Full article
(This article belongs to the Special Issue Technology for Fish and Fishery Monitoring)
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Figure 1

Figure 1
<p>Dorsal and lateral X-ray images of <span class="html-italic">C. lucidus</span>, along with morphological parameters. The brighter ellipsoid part within the fish body is the swimbladder.</p>
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<p>Schematic diagram of TS measurement using the tethered method for <span class="html-italic">C. lucidus</span>.</p>
Full article ">Figure 3
<p>TS changes with posture pitch angles for <span class="html-italic">C. lucidus</span> No. 1, estimated by KRM at different frequencies.</p>
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<p>Broadband scattering characteristics of <span class="html-italic">C. lucidus</span> no. 1 with pitch angle variation, as measured by the KRM model and the tethered method.</p>
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<p>Broadband scattering spectra of <span class="html-italic">C. lucidus</span> with different swimbladder lengths, as obtained from the (<b>a</b>) KRM model and (<b>b</b>) tethered method measurements.</p>
Full article ">Figure 6
<p>Relationship between body length and TS of <span class="html-italic">C. lucidus</span>: (<b>a</b>) 70 kHz KRM; (<b>b</b>) 200 kHz KRM; (<b>c</b>) 70 kHz tethered method; (<b>d</b>) 200 kHz tethered method.</p>
Full article ">
28 pages, 3802 KiB  
Article
Effect of Probiotic and β-Mannanase Supplementation on the Productive Performance and Intestinal Health of Broiler Chickens Challenged by Eimeria maxima and Clostridium perfringens
by Larissa Pereira Maria, Rony Riveros Lizana, Rosiane de Souza Camargos, Bruno Balbino Leme, Bárbara Vitória Marçal, Nilva Kazue Sakomura and Marcos Kipper
Poultry 2024, 3(3), 239-266; https://doi.org/10.3390/poultry3030019 - 1 Aug 2024
Viewed by 366
Abstract
The use of antibiotics in poultry farming has been associated with bacterial resistance in humans, leading to a ban on their inclusion in chicken diets. Therefore, the objective was to evaluate the effects of probiotics and β-mannanase on the growth performance and intestinal [...] Read more.
The use of antibiotics in poultry farming has been associated with bacterial resistance in humans, leading to a ban on their inclusion in chicken diets. Therefore, the objective was to evaluate the effects of probiotics and β-mannanase on the growth performance and intestinal health of broiler chickens challenged by Eimeria maxima and Clostridium perfringens. For this, 2100 one-day-old male Ross 308 chicks were used. The treatments were as follows: T1—Negative control (NC) unchallenged birds; T2—Positive control (PC) challenged with E. maxima + C. perfringens; T3—PC + Antibiotic (Enramycin 8%-125 g/ton); T4—PC + β-mannanase (HemicellHT; 300 g/ton); T5—PC + probiotic (ProtexinTM; 150 g/ton); T6—PC + β-mannanase + probiotic. Significant differences (p < 0.05) were observed from 1 to 42 days in the variables body weight, body weight gain and feed intake, and the NC treatment presented higher values compared to the PC and PC + probiotic groups. The villus/crypt ratio in the duodenum increased in the PC + β-man + prob treatment, differing from the NC, PC and PC + probiotic (p < 0.05) treatments. The use of β-mannanase, probiotics or both together is effective to mitigate the effects of production challenges, through the maintenance of the intestine by modulating action on the cecum microbiome and intestinal morphometry. Full article
(This article belongs to the Special Issue Feature Papers of Poultry)
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Figure 1

Figure 1
<p>Boxplot of oocyst count (oocyts/g of feces) of 20-day-old broilers fed diets supplemented or not with β-mannanase, Probiotic, Antibiotic and challenged or not with oocysts of <span class="html-italic">Eimeria maxima</span> and <span class="html-italic">Clostridium perfringens</span>. <sup>abc</sup> Different letters represent statistical difference by a non-parametric Kruskal–Wallis test. Negative control (NC) (birds without challenge); Positive control (PC) (birds challenged with <span class="html-italic">Eimeria maxima</span> + <span class="html-italic">Clostridium perfringens</span>); PC + Antibiotic; PC + β-mannanase; PC + probiotic; PC + β-mannanase + probiotic.</p>
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<p>Alpha diversity estimated by Chao1 parameters (<b>A</b>), observed OTUs (<b>B</b>), Fisher test (<b>C</b>), Simpson index (<b>D</b>), Shannon Entropy (<b>E</b>) and Evenness Pielou (<b>F</b>). Statistical comparison between groups was performed using the non-parametric Kruskal–Wallis and Post hoc Dunn tests. Statistical results below 0.05 were accepted as statistically significant. The treatments were: T1—Negative control (NC) (birds without challenge); T2—Positive control (PC) (birds challenged with <span class="html-italic">Eimeria maxima</span> + <span class="html-italic">Clostridium perfringens</span>); T3—PC + Antibiotic; T4—PC + β-mannanase; T5—PC + probiotic; T6—PC + β-mannanase + probiotic.</p>
Full article ">Figure 3
<p>Beta diversity estimated by Bray–Curtis parameters (<b>A</b>). Jaccard (<b>B</b>). UniFrac (<b>C</b>) and weighted Unifrac (<b>D</b>). Colored ellipses were automatically added via the ggforce library in R. The treatments were as follows: T1—Negative control (NC) (birds without challenge); T2—Positive control (PC) (birds challenged with <span class="html-italic">Eimeria maxima</span> + <span class="html-italic">Clostridium perfringens</span>); T3—PC + Antibiotic); T4—PC + β-mannanase; T5—PC + probiotic; T6—PC + β-mannanase + probiotic.</p>
Full article ">Figure 4
<p>The bar graph shows the ratio between Firmicutes and Bacteroidota taxa in the tested groups. Differences with <span class="html-italic">p</span> value below 0.05 were considered statistically significant. The treatments were as follows: T1—Negative control (NC) (birds without challenge); T2—Positive control (PC) (birds challenged with <span class="html-italic">Eimeria maxima</span> + <span class="html-italic">Clostridium perfringens</span>); T3—PC + Antibiotic; T4—PC + β-mannanase; T5—PC + probiotic; T6—PC + β-mannanase + probiotic.</p>
Full article ">Figure 5
<p>Differential abundance of the Acutalibacteraceae family (<b>A</b>), Bacteroidaceae (<b>B</b>), Lactobacillaceae (<b>C</b>), Oscillospiraceae (<b>D</b>), Butyricicoccaceae (<b>E</b>), Lachnospiraceae (<b>F</b>), Rikenellaceae (<b>G</b>) and Ruminococcaceae (<b>H</b>). Statistical comparison between groups was performed using the non-parametric Kruskal–Wallis and Post hoc Dunn tests. Statistical results below 0.05 were accepted as statistically significant. The treatments were: T1—Negative control (NC) (birds without challenge); T2—Positive control (PC) (birds challenged with <span class="html-italic">Eimeria maxima</span> + <span class="html-italic">Clostridium perfringens</span>); T3—PC + Antibiotic; T4—PC + β-mannanase; T5—PC + probiotic; T6—PC + β-mannanase + probiotic.</p>
Full article ">Figure 6
<p>Differential abundance of <span class="html-italic">Agathobaculum</span> generum (<b>A</b>), <span class="html-italic">Alistipes</span> (<b>B</b>), <span class="html-italic">Lactobacillus</span> (<b>C</b>), <span class="html-italic">Mediterraneibacter</span> (<b>D</b>), <span class="html-italic">Faecalibacterium</span> (<b>E</b>), <span class="html-italic">Gemmiger</span> (<b>F</b>), <span class="html-italic">Prevotellamassilia</span> (<b>G</b>) and <span class="html-italic">Tidjanibacter</span> (<b>H</b>). Statistical comparison between groups was performed using the non-parametric Kruskal–Wallis and Post hoc Dunn tests. Statistical results below 0.05 were accepted as statistically significant. The treatments were: T1—Negative control (NC) (birds without challenge); T2—Positive control (PC) (birds challenged with <span class="html-italic">Eimeria maxima</span> + <span class="html-italic">Clostridium perfringens</span>); T3—PC + Antibiotic; T4—PC + β-mannanase; T5—PC + probiotic; T6—PC + β-mannanase + probiotic.</p>
Full article ">Figure 7
<p>The graph shows that through the analysis of intestinal integrity (HTSi), there was a significant difference between treatments in broilers challenged or not by <span class="html-italic">Eimeria maxima</span> and <span class="html-italic">Clostridium perfringens</span>. <sup>abc</sup> Different letters in the same column represent statistical difference by the Tukey test (<span class="html-italic">p</span>-value &lt; 0.05 was considered statistically different). Means that do not follow a letter are significantly different. Negative control (NC) (birds without challenge); Positive control (PC) (birds challenged with <span class="html-italic">Eimeria maxima</span> + <span class="html-italic">Clostridium perfringens</span>); PC + Antibiotic; PC + β-mannanase; PC + probiotic; PC + β-mannanase + probiotic.</p>
Full article ">
20 pages, 768 KiB  
Article
Structural Magnetic Resonance Imaging-Based Surface Morphometry Analysis of Pediatric Down Syndrome
by Jacob Levman, Bernadette McCann, Nicole Baumer, Melanie Y. Lam, Tadashi Shiohama, Liam Cogger, Allissa MacDonald and Emi Takahashi
Biology 2024, 13(8), 575; https://doi.org/10.3390/biology13080575 - 30 Jul 2024
Viewed by 288
Abstract
Down syndrome (DS) is a genetic disorder characterized by intellectual disability whose etiology includes an additional partial or full copy of chromosome 21. Brain surface morphometry analyses can potentially assist in providing a better understanding of structural brain differences, and may help characterize [...] Read more.
Down syndrome (DS) is a genetic disorder characterized by intellectual disability whose etiology includes an additional partial or full copy of chromosome 21. Brain surface morphometry analyses can potentially assist in providing a better understanding of structural brain differences, and may help characterize DS-specific neurodevelopment. We performed a retrospective surface morphometry study of 73 magnetic resonance imaging (MRI) examinations of DS patients (aged 1 day to 22 years) and compared them to a large cohort of 993 brain MRI examinations of neurotypical participants, aged 1 day to 32 years. Surface curvature measurements, absolute surface area measurements, and surface areas as a percentage of total brain surface area (%TBSA) were extracted from each brain region in each examination. Results demonstrate broad reductions in surface area and abnormalities of surface curvature measurements across the brain in DS. After adjusting our regional surface area measurements as %TBSA, abnormally increased presentation in DS relative to neurotypical controls was observed in the left precentral, bilateral entorhinal, left parahippocampal, and bilateral perirhinal cortices, as well as Brodmann’s area 44 (left), and the right temporal pole. Findings suggest the presence of developmental abnormalities of regional %TBSA in DS that can be characterized from clinical MRI examinations. Full article
(This article belongs to the Section Neuroscience)
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Figure 1
<p>Scatter plots of the leading findings presented in <a href="#biology-13-00575-t004" class="html-table">Table 4</a> and <a href="#biology-13-00575-t005" class="html-table">Table 5</a>, representing surface area abnormalities identified in DS as a percentage of total brain surface area (%TBSA). Green samples represent neurotypical participants, red samples represent DS participants. X represents a male, O a female.</p>
Full article ">
19 pages, 1569 KiB  
Article
In Vitro Gene Conservation Status and the Quality of the Genetic Resources of Native Hungarian Sheep Breeds
by Malam Abulbashar Mujitaba, Alexandra Tokár, Eszter Erika Balogh, Viktória Johanna Debnár, Ariuntungalag Javkhlan, Panka Boglárka Vásárhelyi, István Egerszegi, Szabolcs Tamás Nagy and Gabriella Kútvölgyi
Vet. Sci. 2024, 11(8), 337; https://doi.org/10.3390/vetsci11080337 - 25 Jul 2024
Viewed by 795
Abstract
Studies revealed a global loss of genetic resources for local sheep breeds. Therefore, the current study aimed to introduce and highlight the progress made on Hungary’s existing gene conservation program (small Gene Bank). Furthermore, we evaluated breed (Tsigai, Cikta, and Racka), season, and [...] Read more.
Studies revealed a global loss of genetic resources for local sheep breeds. Therefore, the current study aimed to introduce and highlight the progress made on Hungary’s existing gene conservation program (small Gene Bank). Furthermore, we evaluated breed (Tsigai, Cikta, and Racka), season, and individual variabilities (n = 24) of the pre-freeze and post-thaw semen stored in the Gene Bank to enhance the gene conservation of the breeds. The samples were cryopreserved manually, and post-thaw spermatozoa were analyzed for motility (CASA), viability, chromatin structure, and morphometry of the sperm nuclei. Ejaculate volume, spermatozoa concentration, subjective motility and standard motility, kinematic parameters, and spermatozoa’s head area standard deviation of the post-thaw samples differed significantly among breeds (p < 0.05). Season affected ejaculate volume, total spermatozoa number/ejaculate, STR, BCF, and ALH. We observed a significant (p < 0.001; 0.05) breed and season interaction on concentration, total spermatozoa number/ejaculate, VCL, LIN, WOB, spermatozoa’s head average perimeter and nucleus length (Tsigai and Cikta differed but were statistically the same as Racka). Similarly, season significantly (p < 0.05) affected the proportion of ejaculate suitable for freezing. There was a significant (p < 0.05) difference in kinematic parameters and viability among the rams across the breeds. The spermatozoa’s head morphometry of the Tsigai and Cikta breeds differed significantly (p < 0.05) among the rams. There were individual and breed differences in many spermatozoa quality parameters. The stored samples are of good quality, with more than 40% having intact membranes and low abnormal chromatin condensation. Full article
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<p>Different post-thaw ram spermatozoa categories stained with the modified Kovács–Foote staining technique (magnification ×400, brightfield optics). (a) Intact head, intact tail, and acrosome membrane (intact: IHITIA). (b) Intact with a bent tail (IBT). (c) Damaged head with intact tail (DHIT). (d) Intact head, damaged tail (IHDT). (e) Damaged head, damaged tail, and damaged acrosome (DHDTDA). (f) Damaged head, damaged tail, and intact acrosome.</p>
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<p>Feulgen-stained ram spermatozoa with intact chromatin structure. Phase contrast optics.</p>
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17 pages, 2965 KiB  
Article
Image Processing Analysis of Plant Morphometry with Examples from the Genus Sedum (Crassulaceae)
by Mădălina Borcă, Alexandru Borcă, Alin Ciobica, Gabriela Halitchi and Andrei Stoie
Methods Protoc. 2024, 7(4), 56; https://doi.org/10.3390/mps7040056 - 24 Jul 2024
Viewed by 513
Abstract
The complex systematics of the genus Sedum, the difficulties of its classification and the ambiguity of the concrete identification of the taxa brought about the need to implement a measurement system adaptable to field conditions, so as to facilitate the accuracy of [...] Read more.
The complex systematics of the genus Sedum, the difficulties of its classification and the ambiguity of the concrete identification of the taxa brought about the need to implement a measurement system adaptable to field conditions, so as to facilitate the accuracy of data collection, avoiding the etiolation of samples and, therefore, the deterioration of the morphological structures subject to analysis. Thus, our study describes a digitization of the classic method of making measurements using millimeter paper, thus facilitating the subsequent statistical processing of quantifiable values. Depending on the number of pixels in the photos taken and the pixel/millimeter ratio, a variable measurement scale can be created depending on the size of the analyzed taxomes. The method used adds to the classic taxonomy, which is based on the analysis of morphological characteristics to determine the species of these succulent plants. The applicability of our method is shown by means of the example of an analysis performed on the flowers of the native species of the genus Sedum in the territory of Romania. Full article
(This article belongs to the Special Issue Plant Tissue Culture for Crop Improvement)
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<p>Graphic representation of the importance of the angle in the context of taking photos.</p>
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<p>Taking the photographs.</p>
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<p>The steps that need to be executed in order to carry out measurements using ImageJ.</p>
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<p>An example of measuring flower elements.</p>
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<p>Comparative analysis of the morphology of floral elements: petals.</p>
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<p>Comparative analysis of the morphology of floral elements: sepal.</p>
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<p>Comparative analysis of the morphology of floral elements: carpel.</p>
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<p>Comparative analysis of the morphology of floral elements: stamen.</p>
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12 pages, 1190 KiB  
Article
Fish of Low Commercial Value in Lakes of Different Trophic Status (Poland)
by Krystyna Kalinowska, Dariusz Ulikowski, Michał Kozłowski, Piotr Traczuk, Maciej Szkudlarek, Konrad Stawecki and Andrzej Kapusta
Diversity 2024, 16(8), 437; https://doi.org/10.3390/d16080437 - 24 Jul 2024
Viewed by 344
Abstract
In a commercial fishery, some fish are classified as low-value, but their classification varies in different countries. The aim of this study was to determine the abundance, contribution, and dominance of low-value fish species, such as Abramis brama < 1000 g, Alburnus alburnus [...] Read more.
In a commercial fishery, some fish are classified as low-value, but their classification varies in different countries. The aim of this study was to determine the abundance, contribution, and dominance of low-value fish species, such as Abramis brama < 1000 g, Alburnus alburnus, Blicca bjoerkna, Gymnocephalus cernua, Perca fluviatilis < 100 g, Rutilus rutilus < 200 g, and Scardinius erythrophthalmus < 200 g, in 145 Polish lakes of different areas, depths, and trophic statuses situated in the northern and central parts of Poland in 2021. Perca fluviatilis and R. rutilus were the most frequent low-value species (100% and 99%, respectively). The contribution of all low-value fish to the total biomass of caught fish was relatively high, ranging from 37% in the mesotrophic lake to 100% in the eutrophic lake (mean of 77 ± 14%). Lakes in which the contribution of low-value species exceeded 90% were relatively numerous (24 lakes, 17% of the studied lakes). Among a total of about 437.5 thousand low-value fish, 261 thousand specimens (60%) had a body weight of below 10 g. All low-value fish species, except for P. fluviatilis and S. erythrophthalmus, were related to the studied environmental variables. The relative biomass of these species increased with increasing lake productivity, while it decreased with the increasing maximum and mean depth of the studied lakes. The high contribution of low-value fish to the total biomass in many lakes indicates the need for the constant monitoring of the abundance and structure of fish communities and the use of appropriate actions (biomanipulation and stocking with piscivorous fish species) to improve the ecological condition of lakes. Full article
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<p>Map of Poland showing the geographical distribution of the 145 lakes (black dots) sampled during the study.</p>
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<p>Contribution of low-value fish species to the total biomass of caught fish in 145 lakes (mean values ± standard deviations and ranges).</p>
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<p>Contribution of individual low-value fish species to the total biomass of low-value fish species in the studied lakes (mean values).</p>
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<p>Redundancy diagram (RDA) showing the relationships between morphometric (area, maximum and mean depth), chemical (oxygen layer), trophic (TSI), and ecological (EQR) parameters of lakes and the relative biomass (WPUE) of individual low-value fish species and the total biomass of this group (Total) in the studied lakes. The cumulative explained variation for the two first axes is 16.5% (13.7 and 2.8%, respectively).</p>
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12 pages, 3395 KiB  
Article
Radiological Assessment of Coronal Plane Alignment of the Knee Phenotypes in the Romanian Population
by Serban Dragosloveanu, Bogdan-Sorin Capitanu, Radu Josanu, Diana Vulpe, Romica Cergan and Cristian Scheau
J. Clin. Med. 2024, 13(14), 4223; https://doi.org/10.3390/jcm13144223 - 19 Jul 2024
Viewed by 465
Abstract
Background: The Coronal Plane Alignment of the Knee (CPAK) classification system has been developed as a comprehensive framework delineating nine coronal plane phenotypes, based on arithmetic hip–knee angle (aHKA) and joint line obliquity (JLO). Our study aimed to assess the prevalence of [...] Read more.
Background: The Coronal Plane Alignment of the Knee (CPAK) classification system has been developed as a comprehensive framework delineating nine coronal plane phenotypes, based on arithmetic hip–knee angle (aHKA) and joint line obliquity (JLO). Our study aimed to assess the prevalence of knee phenotypes in the Romanian population using the CPAK classification, encompassing both osteoarthritic and healthy cohorts. Methods: We conducted an observational cross-sectional study, analyzing data from 500 knees with osteoarthritis and 500 healthy knees that met the inclusion criteria. Demographic data were collected, and radiological parameters including lateral distal femoral angle (LDFA), medial proximal tibial angle (MPTA), aHKA, and JLO were measured. Knee phenotypes were categorized using the CPAK classification. Results: In the osteoarthritic cohort, the most prevalent CPAK phenotype was type I (42.4%), characterized by varus alignment and an apex distal joint. Conversely, in the healthy population, CPAK type II, indicating neutral alignment and an apex distal joint, was the most prevalent phenotype (39.0%). CPAK types VII, VIII, and IX were rare. Conclusions: Our findings demonstrate similarities in knee phenotypes compared to other populations, with some minor differences and particularities. The CPAK classification proves to be a valuable tool in assessing knee tyalignment. Full article
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<p>Method of measurement for the radiological parameters of the study. (<b>A</b>) Physiological axes of the lower limb; teal line=mechanical tibial axis, green line=mechanical femoral axis, red line=lower limb mechanical axis; (<b>B</b>) mLDFA (mechanical lateral distal femoral angle) and mMPTA (mechanical medial proximal tibial angle).</p>
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<p>Kellgren–Lawrence classification exemplified on 5 patients from the patient cohorts [<a href="#B16-jcm-13-04223" class="html-bibr">16</a>].</p>
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<p>Comparative graphical view of the differences and distributions of the measured angles and distances in the two study cohorts; circle=outlier; asterisk=extreme outlier.</p>
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<p>CPAK phenotype distribution in the osteoarthritic cohort.</p>
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<p>CPAK phenotype distribution in the healthy cohort.</p>
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13 pages, 1946 KiB  
Article
Hyperacusis in Tinnitus Individuals Is Associated with Smaller Gray Matter Volumes in the Supplementary Motor Area Regardless of Hearing Levels
by Punitkumar Makani, Marc Thioux, Elouise A. Koops, Sonja J. Pyott and Pim van Dijk
Brain Sci. 2024, 14(7), 726; https://doi.org/10.3390/brainsci14070726 - 19 Jul 2024
Viewed by 639
Abstract
Recent evidence suggests a connection between hyperacusis and the motor system of the brain. For instance, our recent study reported that hyperacusis in participants with tinnitus and hearing loss is associated with smaller gray matter volumes in the supplementary motor area (SMA). Given [...] Read more.
Recent evidence suggests a connection between hyperacusis and the motor system of the brain. For instance, our recent study reported that hyperacusis in participants with tinnitus and hearing loss is associated with smaller gray matter volumes in the supplementary motor area (SMA). Given that hearing loss can affect gray matter changes in tinnitus, this study aimed to determine if the changes reported in our previous findings of smaller SMA gray matter volumes in hyperacusis persist in the absence of hearing loss. Data for this study were gathered from four prior studies conducted between 2004 and 2019 at the University Medical Centre Groningen (UMCG). A total of 101 participants with tinnitus and either clinically normal hearing (normal hearing with tinnitus or NHT, n = 35) or bilateral sensorineural hearing loss (hearing loss with tinnitus or HLT, n = 66) were included across four studies. Hyperacusis was determined by a score of ≥22 on the Hyperacusis Questionnaire (HQ). In the NHT group, 22 (63%) participants scored ≥22 on the HQ (NHT with hyperacusis: mean age 44.1 years, 12 females), while in the HLT group, 25 (38%) participants scored ≥22 on the HQ (HLT with hyperacusis: mean age 59.5 years, 10 females). The 2 × 2 between-group ANOVAs revealed that hyperacusis is associated with smaller SMA gray matter volumes, regardless of hearing levels. Notably, the smaller SMA gray matter volumes in hyperacusis were primarily influenced by the attentional subscales of the HQ. The association between hyperacusis and the motor system may indicate a constant alertness to sounds and a readiness for motor action. Full article
(This article belongs to the Special Issue Novel Developments in Tinnitus and Heterogeneity)
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<p>Flowchart of participant inclusion criteria for the four participant groups. For all participants, pure tone air-conduction audiometry was utilized to assess hearing thresholds across octave frequencies ranging from 0.25 to 8 kHz. Hearing loss was defined as an average hearing threshold (or pure tone average—PTA) of ≥25 dB HL across all tested frequencies (0.25, 0.5, 1, 2, 4, and 8 kHz) for both ears. A cut-off score of ≥22 on the Hyperacusis Questionnaire (HQ) was used to distinguish the presence or absence of hyperacusis.</p>
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<p>Box plots showing the hearing thresholds for the four participant groups. Participants with hearing loss (the HLT group either with or without hyperacusis) had worse hearing thresholds than those with clinically normal hearing (the NHT group either with or without hyperacusis) [<span class="html-italic">X</span><sup>2</sup>(3) = 30.0, <span class="html-italic">p</span> &lt; 0.001]. The crosses added to the box plots represent the mean values. HLT, hearing loss and tinnitus; NHT, normal hearing and tinnitus.</p>
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<p>The SMA VOIs were derived from the Human Motor Area Template (HMAT) atlas (upper panels). The 2 × 2 between-group ANOVAs (corrected for age, handedness scores, and total intracranial volume) revealed that hyperacusis has a significant negative main effect on the right supplementary motor area (SMA) gray matter volumes [SMA right: F(1,94) = 21.0, <span class="html-italic">p</span> &lt; 0.001]. There was no significant main effect of hearing loss, nor any interaction between the effects of hyperacusis and hearing loss, on the bilateral SMA gray matter volumes. The presence of hyperacusis was defined by a cut-off score of ≥22 on the 14-item HQ. The graphs show the mean and 95% confidence interval (CI). HLT, hearing loss and tinnitus; NHT, normal hearing and tinnitus.</p>
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<p>The SMA VOIs were derived from the Human Brainnetome (HBN) atlas (upper panels). The 2 × 2 between-group ANOVAs (corrected for age, handedness scores, and total intracranial volume) revealed that hyperacusis has a significant negative main effect on the right anterior (A6a) SMA gray matter volumes [SMA_A6a right: F(1,94) = 21.0, <span class="html-italic">p</span> &lt; 0.001] and the bilateral posterior (A4ll) SMA) gray matter volumes [SMA_A4ll left: F(1,94) = 10.5, <span class="html-italic">p</span> &lt; 0.001; SMA_A4ll right: F(1,94) = 14.1, <span class="html-italic">p</span> &lt; 0.001]. There was no significant main effect of hearing loss nor any interaction between the effects of hyperacusis and hearing loss on the bilateral anterior/posterior SMA gray matter volumes. The presence of hyperacusis was defined by a cut-off score of ≥22 on the 14-item HQ. The graphs show the mean and 95% confidence interval (CI). HLT, hearing loss and tinnitus; NHT, normal hearing and tinnitus.</p>
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15 pages, 6221 KiB  
Article
Comparison of Skull Morphometric Characteristics of Simmental and Holstein Cattle Breeds
by Buket Çakar, Faruk Tandir, Barış Can Güzel, Caner Bakıcı, Burak Ünal, Sokol Duro, Tomaz Szara, Constantin Spataru, Mihaela-Claudia Spataru and Ozan Gündemir
Animals 2024, 14(14), 2085; https://doi.org/10.3390/ani14142085 - 17 Jul 2024
Viewed by 376
Abstract
This study aimed to reveal the morphological characteristics of pure Holstein and Simmental skulls and to obtain reference values for morphometric analysis. Moreover, 54 skulls from 12- to 14-month-old male Holstein (n = 25) and Simmental (n = 29) cattle were [...] Read more.
This study aimed to reveal the morphological characteristics of pure Holstein and Simmental skulls and to obtain reference values for morphometric analysis. Moreover, 54 skulls from 12- to 14-month-old male Holstein (n = 25) and Simmental (n = 29) cattle were collected from Turkey’s Southeastern Anatolia Region between 2023 and 2024. Linear measurements indicated that Holsteins had longer skulls compared to Simmentals. Holsteins exhibited significantly higher values for the greatest length of nasals and the shortest skull length. The facial breadth was wider in Holsteins and statistically distinctive between the breeds. Holsteins had a more oval orbital bony roof, while Simmentals exhibited a wider orbital structure. The orbital index was higher in Holsteins, distinguishing between the two breeds. It was observed that Simmental cattle had a wider occipital region. This difference is likely due to the larger lateral appearance of the Simmental skull, which has more body weight and provides a larger surface area for muscle attachment. These differences not only aid in breed identification but also offer insights into the functional adaptations of each breed. Future research should explore the genetic and environmental factors contributing to these morphological traits, further enriching our knowledge of cattle morphology and its implications for breeding and conservation efforts. Full article
(This article belongs to the Special Issue Mammal Evolution Explained through Molecular and Morphological Data)
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<p>Dorsal view of the cattle skull. P1–P10: Total Length (TL): Acrocranion-Prosthion; P1–P17: Condylobasal Length (CBL): Aboral Border of the Occipital Condyles-prosthion; P7–P10: Median Frontal Length (MFL): Acrocranion-Nasion; P3–P7: Greatest Length of The Nasals (GLN): Nasion-Rhinion; P1–P8: Lateral Facial Length (LFL): Ectorbitale-Prosthion; P9–P9’: Least Frontal Breadth (LFB): Breadth of The Narrowest Part of The Frontal Aboral of The Orbits; P8–P8’: Greatest Breadth of the Skull (GBS): Ectorbitale-Ectorbitale; P6–P6’: Least Breadth Between The Orbits (LBO): entorbitale-Entorbitale; P5–P5’: Facial Breadth (FB): Across The Facial Tuberosities; P2–P2’: Breadth Across The Premaxillae on The Oral Protuberances (BPOP). The explanation for numbers for <a href="#animals-14-02085-f001" class="html-fig">Figure 1</a>: P1—Prosthion—Fissure Interincisivum; P2—Most Lateral Margin of Incisive Body; P3—Rostral End of Nasal Bones; P4—Nasolacrimal Fissure; P5—Facial Tuberosity; P6—Most Medial Margin of Orbits; P7—Midpoint of Nasofrontal Suture; P8—Most Caudolateral Margin of Orbits; P9—Most Medial Point of The Temporal Line; P10—Intercornual Protuberance.</p>
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<p>Lateral view of the cattle skull. P1–P4: Lateral Length of The Premaxilla (LLP): Nasointermaxillare-Prosthion; P6–P8: Greatest Inner Length of The Orbit (GILO): Ectorbitale-Entorbitale; P11–P12: Greatest Inner Height of The Orbit (GIHO). The explanation for numbers for <a href="#animals-14-02085-f002" class="html-fig">Figure 2</a>: P1—rostral margin of incisive bone; P3—rostral end of the nasal bone; P4—nasolacrimal fissure; P5—facial tuberosity; P6—most medial margin of the orbit; P8—most caudal margin of the orbit; P10—intercornual protuberance; P11—most ventral margin of orbits; P12—most dorsal margin of orbits.</p>
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<p>Caudal view of the cattle skull. P22–P22’: Greatest Mastoid Breadth (GMB): Otion-Otion; P20–P20’: Greatest Breadth of The Occipital Condyles (GBOC); P21–P21’: Greatest Breadth at The Bases of The Paraoccipital Processes (GBPP); P19–P19’: Greatest Breadth of The Foramen Magnum (GBFM); P16–P18: Height of The Foramen Magnum (HFM): Basion-Opisthion; P23–P23’: Least Occipital Breadth (LOB): Distance Between The Most Medial Points of The Caudal Borders of The Temporal Grooves; P10–P16: Greatest Height of The Occipital Region (GHOR): Basion-Highest Point of The Intercornual Protuberance; P10–P18: Least Height of The Occipital Region (LHOR): Opisthion-Highest Point of The Intercornual Protuberance. The explanation for numbers for <a href="#animals-14-02085-f003" class="html-fig">Figure 3</a>: P10—nuchal crest; P16—dorsal magin of the foramen magnum (Basion); P18—dorsal margin of foramen magnum (Opisthion); P19—latral margin of foramen magnum; P20—most lateral base of occipital condyle; P21—most lateral base of paracondylar process; P22—external acoustic meatus; P23—caudal border of temporal fossa.</p>
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<p>Ventral view of the cattle skull. P13–P16: Short Skull Length (SSL): Basion-Premolare; P1–P13: Premolare-Prosthion (PP); P1–P15: Dental Length (DL): Postdentale-Prosthion; P14–P14’: Greatest Palatal Breadth (GPB): Measured Across the Outer Borders of The Alveoli. The explanation for numbers for <a href="#animals-14-02085-f004" class="html-fig">Figure 4</a>: P1—Prosthion; P13—midpoint of the interpalatine suture at the first premolar level; P14—lateral margin of the third molar; P15—most caudal point of the interpalatine suture; P16—Basion; P17—ventromedial margin of occipital condyle.</p>
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<p>Principal component analysis scatter plot for skulls. Holstein: blue; Simmental: red.</p>
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<p>Loading plot of linear morphometric characteristics for linear measurements with the largest contributions to each dimension of the PC2 observed in skulls.</p>
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19 pages, 7043 KiB  
Article
Causal Roles of Ventral and Dorsal Neural Systems for Automatic and Control Self-Reference Processing: A Function Lesion Mapping Study
by Jie Sui, Pia Rotshtein, Zhuoen Lu and Magdalena Chechlacz
J. Clin. Med. 2024, 13(14), 4170; https://doi.org/10.3390/jcm13144170 - 16 Jul 2024
Viewed by 506
Abstract
Background: Humans perceive and interpret the world through the lens of self-reference processes, typically facilitating enhanced performance for the task at hand. However, this research has predominantly emphasized the automatic facet of self-reference processing, overlooking how it interacts with control processes affecting [...] Read more.
Background: Humans perceive and interpret the world through the lens of self-reference processes, typically facilitating enhanced performance for the task at hand. However, this research has predominantly emphasized the automatic facet of self-reference processing, overlooking how it interacts with control processes affecting everyday situations. Methods: We investigated this relationship between automatic and control self-reference processing in neuropsychological patients performing self-face perception tasks and the Birmingham frontal task measuring executive functions. Results: Principal component analysis across tasks revealed two components: one loaded on familiarity/orientation judgments reflecting automatic self-reference processing, and the other linked to the cross task and executive function indicating control processing requirements. Voxel-based morphometry and track-wise lesion-mapping analyses showed that impairments in automatic self-reference were associated with reduced grey matter in the ventromedial prefrontal cortex and right inferior temporal gyrus, and white matter damage in the right inferior fronto-occipital fasciculus. Deficits in executive control were linked to reduced grey matter in the bilateral inferior parietal lobule and left anterior insula, and white matter disconnections in the left superior longitudinal fasciculus and arcuate fasciculus. Conclusions: The causal evidence suggests that automatic and control facets of self-reference processes are subserved by distinct yet integrated ventral prefrontal–temporal and dorsal frontal–parietal networks, respectively. Full article
(This article belongs to the Special Issue Advances in Geriatric Diseases)
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<p>Lesion overlap map representing the spatial distribution of lesions among all 30 patients included in the current study. Lesion maps from individual patients were reconstructed based on [<a href="#B83-jcm-13-04170" class="html-bibr">83</a>]; see the <a href="#sec2-jcm-13-04170" class="html-sec">Section 2</a>—Materials and Methods for details. The lesion overlap map is shown for ten axial slices in standard MNI space with given MNI Z-coordinates of the presented axial sections. The color bar shows the number of patients with a lesion within a particular voxel (range 1–30).</p>
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<p><b>Neuropsychological assessments.</b> (<b>a</b>) Experimental stimuli and protocols in the face tasks. Participants display their own face, the face of a friend, or the face of a stranger. They have to judge the orientation of the face in the face orientation task and categorize faces into the familiar (self and friend) or unfamiliar category in the categorization task. In the cross task, a cross appears on the top of the face, where participants are required to judge which horizontal or vertical element of the cross is longer while ignoring the face in the background. (<b>b</b>) In the rule-finding and -switching task in the Birmingham frontal task, participants are asked to predict the next movement of the black dot. (<b>c</b>) Principal component analysis identifies two components among the four assessments and the loadings of the four assessments for the automatic self-reference and control processing components. (<b>d</b>) No significant correlation between the two components demonstrates their separate functions of the four assessments (the distribution of participants’ loading scores in the two components).</p>
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<p><b>Voxel-based morphometry analysis</b>: grey matter substrates of the two components identified in the principal component analysis for (<b>a</b>) automatic self-reference processing and (<b>b</b>) control processing. The areas of damage associated with both components of deficits are colored according to the level of significance in the VBM analysis, where brighter colors represent higher t-values. The numbers in brackets indicate peak MNI coordinates.</p>
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<p><b>Tract-wise lesion deficits:</b> (<b>a</b>). Percentage of patients with disconnection in the eight examined association, commissural, and projection white matter pathways within the left versus right hemisphere, plotted across the entire group of patients. (<b>b</b>). Percentage of patients with disconnection in the eight examined association, commissural, and projection white matter pathways within the left versus right hemisphere, calculated for groups with and without deficits in automatic self-reference and control processing (classified based on norms from healthy control participants. Note: We cannot directly classify patients with or without deficits based on the scores for the two components derived from PCA analysis). As indicated in the Methods section, the tract-wise lesion deficits include eight pathways within both the left and the right hemisphere (cingulum; arcuate; SLFI, II, III, 3 branches of the superior longitudinal fasciculus; uncinate; ILF, inferior longitudinal fasciculus; IFOF, inferior frontal occipital fasciculus).</p>
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<p><b>Tract-wise lesion deficits:</b> the trajectories of white matter pathways (blue) presented in relation to cortical substrates for automatic self-reference (<b>a</b>) and control components (<b>b</b>), as identified in VBM analysis (red). The white matter pathways (IFOF, inferior frontal occipital fasciculus; SLF II, III, second and third branch of the superior longitudinal fasciculus; arcuate) are plotted as thresholded (50%) binary maps from the DTI tractography atlas of human white matter tracts [<a href="#B101-jcm-13-04170" class="html-bibr">101</a>,<a href="#B102-jcm-13-04170" class="html-bibr">102</a>], and the VBM results are presented as binary statistical maps thresholded at the significance level of <span class="html-italic">p</span> &lt; 0.005.</p>
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19 pages, 4687 KiB  
Article
Ommastrephes caroli (Cephalopoda: Ommastrephidae) from the Adriatic Sea: Morphometry, Age, and Genetic Characterization
by Mirela Petrić, Marija Dadić, Damir Roje, David Udovičić, Rino Stanić and Željka Trumbić
J. Mar. Sci. Eng. 2024, 12(7), 1182; https://doi.org/10.3390/jmse12071182 - 14 Jul 2024
Viewed by 388
Abstract
This study gives the first data on the body and beak morphometric characteristics, age, and genetic structure of neon flying squid, a rarely caught cephalopod in the Adriatic Sea. We identified specimens as recently resurrected Ommastrephes caroli species using two mitochondrial markers, 16S ribosomal [...] Read more.
This study gives the first data on the body and beak morphometric characteristics, age, and genetic structure of neon flying squid, a rarely caught cephalopod in the Adriatic Sea. We identified specimens as recently resurrected Ommastrephes caroli species using two mitochondrial markers, 16S ribosomal RNA gene and cytochrome c oxidase subunit I gene. Overall, 23 juveniles (3 females, 3 males, and 17 unsexed), with a dorsal mantle range of 65–152 mm, were caught in September 2020 in the waters of the Korčula Channel, island of Palagruža, and island of Jabuka, thus providing the most abundant sample of this species in the Mediterranean waters. The length–weight relationship showed an isometric growth. The results of the beak/length regressions suggest hood length is a useful characteristic for biomass estimation studies, as it showed a good linear fit to the dorsal mantle length. Statolith growth increments were easily visible and statolith microstructure analysis was successfully used to determine the age of 22 individuals. The estimated age ranged from 36 to 64 days (mean = 48 days). The back-calculation analysis showed that the squid hatched during July and August 2020, indicating that O. caroli spawns during the warmer, summertime period. Considering the size and age of the caught individuals, the Adriatic Sea could represent a potential feeding ground for this species. The genetic structure analyses indicate the existence of separate Atlantic and Mediterranean/Adriatic subclusters; however, this warrants further investigation. Full article
(This article belongs to the Section Marine Biology)
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<p>Map of the Adriatic Sea showing the sampling locations of <span class="html-italic">Ommastrephes caroli</span> in September 2020. The maps were produced using the ggmap package v4.0.0 [<a href="#B23-jmse-12-01182" class="html-bibr">23</a>] for R and tiles by © Stadia Maps (<a href="https://stadiamaps.com/" target="_blank">https://stadiamaps.com/</a>, 28 May 2024) © Stamen Design (<a href="https://stamen.com/" target="_blank">https://stamen.com/</a>, 28 May 2024) © OpenMapTiles (<a href="https://openmaptiles.org/" target="_blank">https://openmaptiles.org/</a>, 28 May 2024) © OpenStreetMap (<a href="https://www.openstreetmap.org/#map=5/39.723/19.314" target="_blank">https://www.openstreetmap.org/#map=5/39.723/19.314</a>, 28 May 2024) contributors. This figure is openly licensed via <a href="https://creativecommons.org/licenses/by-nc-nd/4.0/" target="_blank">CC BY-NC-ND</a>.</p>
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<p><span class="html-italic">Ommastrephes caroli</span> statolith: main regions (dk—dorsal dome, lk—lateral dome, k—wing, r—rostrum) and total statolith length (TSL).</p>
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<p><span class="html-italic">Ommastrephes caroli</span> collected in the Adriatic Sea: ID 8—dorsal view (<b>left</b>) and ID 10—ventral view (<b>right</b>).</p>
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<p><span class="html-italic">Ommastrephes caroli</span>: upper (<b>left</b>) and lower (<b>right</b>) beak of individual ID 3 (145 mm DML).</p>
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<p>The relationship between dorsal mantle length (DML) and beak morphological variables of <span class="html-italic">Ommastrephes caroli</span> collected in the Adriatic Sea in 2020 (N = 23). Linear, exponential, power, and logarithmic models were fitted and compared for each variable. Best chosen models according to AICc criterion are shown. For details on model fitting and beak abbreviations see M and M section.</p>
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<p>Phylogenetic tree of the genus <span class="html-italic">Ommastrephes</span> based on Bayesian inference (BI) of the mitochondrial 16S ribosomal RNA gene. The node values show the posterior probabilities (%) of BI analyses. Represented sequences are from this study (PP839008-PP839028) and those available from GenBank. Clade highlighted in pink represents <span class="html-italic">O. caroli</span>, in yellow <span class="html-italic">O. bartramii</span>, in green <span class="html-italic">O. brevimanus,</span> and blue <span class="html-italic">O. cylindraceus</span>. Abbreviations: ADR—Adriatic Sea, CW MED—Central Western Mediterranean, NE ATL—Northeast Atlantic, S ATL—South Atlantic, SW—Southwest Atlantic, ET ATL—Eastern Tropical Atlantic, SW IND—Southwest Indian Ocean, N PAC—North Pacific, CN—Central North Pacific, SC PAC—South Central Pacific, SW PAC—Southwest Pacific. Scale bar indicates number of nucleotide substitutions per site.</p>
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<p>Phylogenetic tree of the genus <span class="html-italic">Ommastrephes</span> based on Bayesian inference (BI) of the mitochondrial COI gene. The node values show the posterior probabilities (%) of BI analyses. Represented sequences are from this study (PP839030-PP839051) and those available from GenBank. Clade highlighted in pink represents <span class="html-italic">O. caroli</span>, in yellow <span class="html-italic">O. bartramii</span>, in green <span class="html-italic">O. brevimanus,</span> and blue <span class="html-italic">O. cylindraceus</span>. Abbreviations: ADR—Adriatic Sea, CW MED—Central Western Mediterranean, NE ATL—Northeast Atlantic, NW—Northwest Atlantic, SW—Southwest Atlantic, SW IND—Southwest Indian Ocean, NW PAC—Northwest Pacific, CN PAC—Central North Pacific, SE PAC—Southeast Pacific, SW PAC—Southwest Pacific. Scale bar indicates number of nucleotide substitutions per site.</p>
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<p>Median-joining haplotype networks of <span class="html-italic">Ommastrephes caroli</span> 16S rRNA (<b>A</b>) and COI (<b>B</b>) sequences from the present study and GenBank. The network displays the geographical distribution and frequency of individual gene haplotypes. The size of the circles corresponds to the number of sequences (individuals) belonging to a particular haplotype. Transverse bars on branches indicate the number of mutations. The colors of the circles represent the population from which a specific sample was isolated: red—Northeast Atlantic (NE ATL), green—Central Western Mediterranean (CW MED), and purple—Adriatic (ADR).</p>
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18 pages, 340 KiB  
Article
Insect Larvae as an Alternate Protein Source in Poultry Feed Improve the Performance and Meat Quality of Broilers
by Muhammad Sajjad, Asif Sajjad, Ghazanfar Ali Chishti, Ehsaan Ullah Khan, Raimondas Mozūraitis and Muhammad Binyameen
Animals 2024, 14(14), 2053; https://doi.org/10.3390/ani14142053 - 12 Jul 2024
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Abstract
The primary challenge facing the global animal industry is the scarcity of protein feed resources. Various insects are gaining prominence as innovative feed sources due to their economic, environmentally friendly, and nutritious attributes. The purpose of the present study was to determine the [...] Read more.
The primary challenge facing the global animal industry is the scarcity of protein feed resources. Various insects are gaining prominence as innovative feed sources due to their economic, environmentally friendly, and nutritious attributes. The purpose of the present study was to determine the effects of a partial replacement of soybean meal with fall armyworm Spodoptera frugiperda (Lepidoptera: Noctuidae) and black soldier fly Hermetia illucens (Diptera: Stratiomyidae) on the growth performances, blood parameters, gut histology, and meat quality of broilers. A total of 350 1-day-old (40 ± 0.15 g) male chicks (Ross 308) were randomly assigned to seven experimental meals. Each treatment was repeated five times with 50 birds per dietary treatment. The seven dietary treatments included 4, 8, and 12% replacements of SBM with larvae of S. frugiperda and H. illucens. SBM was the basal diet considered the control. The data showed that broilers fed 12% S. frugiperda or H. illucens exhibited a significantly higher (p < 0.05) live weight, average daily weight gain, and improved the feed conversion ratio. Meals with 12% S. frugiperda or H. illucens significantly enhanced (p < 0.05) haematological and gut histological parameters, including villus height, crypt depth, villus width, and villus height/crypt depth ratios. The meat of broilers fed the 12% S. frugiperda diet showed significantly higher (p < 0.05) lightness and yellowness. Replacing soybean meal up to 12% with either S. frugiperda or H. illucens larvae improves the growth performance, blood haematology, gut morphometry, and meat quality traits of broilers. Full article
(This article belongs to the Section Poultry)
15 pages, 3981 KiB  
Article
A Standardized Porcine Model for Partial-Thickness Wound Healing Studies: Design, Characterization, Model Validation, and Histological Insights
by Alexandru-Cristian Tuca, Ives Bernardelli de Mattos, Martin Funk, Danijel Markovic, Raimund Winter, Thomas Lemarchand, Daniela Kniepeiss, Stephan Spendel, Bernd Hartmann, Christian Ottoman and Lars-Peter Kamolz
Int. J. Mol. Sci. 2024, 25(14), 7658; https://doi.org/10.3390/ijms25147658 - 12 Jul 2024
Viewed by 574
Abstract
Wound healing is a complex process that is still not fully understood despite extensive research. To address this, we aimed to design and characterize a standardized porcine model for the evaluation of wound healing, dressings, cell therapies, and pharmaceutical agents. Using a standardized [...] Read more.
Wound healing is a complex process that is still not fully understood despite extensive research. To address this, we aimed to design and characterize a standardized porcine model for the evaluation of wound healing, dressings, cell therapies, and pharmaceutical agents. Using a standardized approach, we examined the wound healing process in 1.2 mm-deep dermatome wounds at defined positions in 11 female pigs. Unlike previous studies that have only described/analyzed selected punch biopsies, we performed and described histological analyses along the complete wound length using quantitative morphometric methods. All animals remained fully healthy following surgery and showed no signs of infection. Our histopathological evaluation using a predetermined grading score and quantitative manual morphometry demonstrated the impact of different tissue sampling methods, sampling sites, and residual dermis thickness on wound healing. Our study presents a reproducible model for wound healing evaluation and demonstrates the usefulness of porcine models for assessing dermal and epidermal wound healing. The use of histological analyses over the complete wound length provides advantages over previous studies, leading to the possibility of a deeper understanding of the wound healing process. This model could potentially facilitate future research on novel wound dressings and local wound healing therapies. Full article
(This article belongs to the Special Issue Recent Advances in Wound Healing)
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Figure 1
<p>Histological cuts. (<b>A</b>) Schematic representation of how the subjective analysis was performed in the area of the wound border (Wb). (<b>B</b>) Hematoxylin and eosin (H&amp;E) staining of the epithelial tissue showing how the wound length was estimated. (<b>C</b>) Example of H&amp;E staining showing how the new dermal tissue area was manually outlined and estimated. (<b>D</b>) H&amp;E staining of a tissue section showing the new epidermis area and the approximative distance.</p>
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<p>Dermatome samples. (<b>A</b>) Hematoxylin and eosin staining of representative cross-sections of dermatome samples generated from each wound. (<b>B</b>) Bar diagram of the dermatome area in pixels obtained from the histological samples (results presented as mean and SD).</p>
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<p>Effects of dressing removal on re-epithelialization results. (<b>A</b>) Schematic illustration showing the tissue preparation process. (<b>B</b>) Percentage of re-epithelialization obtained for each section analyzed (results presented as mean and standard deviation).</p>
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<p>Consistency of the healing process for the same wound bed. (<b>A</b>) Macroscopic observation of three different wound sites in the same animal model using the same sampling strategy to analyze healing process variation. (<b>B</b>) Schematic illustration indicating the histopathology scoring grade provided for each histological cut. (<b>C</b>) Scatter plot showing the percentage of re-epithelialization obtained for each analyzed wound. (<b>D</b>) Scatter plot showing the standardized epithelial thickness in µm. (<b>E</b>) Scatter plot showing the standardized new dermal thickness in µm. In graphs (<b>C</b>–<b>E</b>), the lines indicate the mean value, and the red circles, squares, and crosses indicate the results obtained for sample A at the wound center.</p>
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<p>Map indicating the thickness of the dermal tissue measured under the unwounded area (NA = not applicable). (<b>A</b>) This table shows the mean value for the measured dermal tissue thickness under the unwound epidermis in µm for each position on the dorsal area (left and right sides) of the 11 animals tested The scheme indicates the position where the wounds were applied. (<b>B</b>) The schematic shows that the color system varies from red (lowest) to green (highest), with yellow in between (intermediate), indicating the relative thickness of the dermis for each position on the dorsal area of the animal.</p>
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<p>Correlation the dermal thickness under wound bed. (<b>A</b>) Graph indicating the correlation between residual dermis thickness and the percentage of re-epithelialization for each analyzed histological cut (DUW = dermis under the wound). (<b>B</b>) Graph showing the correlation between residual dermis thickness and new dermal thickness for each analyzed histological cut. Simple linear regression was calculated and plotted as a guide to help observe the tendencies of the scatter plots, with no statistical importance discovered.</p>
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<p>Alignment and wound setting. (<b>A</b>) Schematic dorsal position of the wounds. (<b>B</b>) Dorsal position of the wounds in vivo. (<b>C</b>) Macroscopic observation of six representative wound beds showing successful excision of epidermis and presence of a residual dermis.</p>
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<p>Histological cuts. Schematic sampling strategy used to analyze healing process variation.</p>
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