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Search Results (1,301)

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Keywords = DH_32

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19 pages, 4526 KiB  
Article
Discovery of Coumarins from Zanthoxylum dimorphophyllum var. spinifoliumas and Their Potential against Rheumatoid Arthritis
by Caixia Du, Xingyu Li, Junlei Chen, Lili Luo, Chunmao Yuan, Jue Yang, Xiaojiang Hao and Wei Gu
Molecules 2024, 29(18), 4395; https://doi.org/10.3390/molecules29184395 - 16 Sep 2024
Viewed by 249
Abstract
In the present study, a series of coumarins, including eight undescribed bis-isoprenylated ones Spinifoliumin A-H, were isolated and identified from the aerial parts of Zanthoxylum dimorphophyllum var. spinifolium (ZDS), a plant revered in traditional Chinese medicine, particularly for treating rheumatoid arthritis (RA). The structures [...] Read more.
In the present study, a series of coumarins, including eight undescribed bis-isoprenylated ones Spinifoliumin A-H, were isolated and identified from the aerial parts of Zanthoxylum dimorphophyllum var. spinifolium (ZDS), a plant revered in traditional Chinese medicine, particularly for treating rheumatoid arthritis (RA). The structures of the compounds were elucidated using 1D and 2D NMR spectroscopy, complemented by ECD, [Rh2(OCOCF3)4]-induced ECD, Mo2(OAc)4 induced ECD, IR, and HR-ESI-MS mass spectrometry. A network pharmacology approach allowed for predicting their anti-RA mechanisms and identifying the MAPK and PI3K-Akt signaling pathways, with EGFR as a critical gene target. A CCK-8 method was used to evaluate the inhibition activities on HFLS-RA cells of these compounds. The results demonstrated that Spinifoliumin A, B, and D-H are effective at preventing the abnormal proliferation of LPS-induced HFLS-RA cells. The results showed that compounds Spinifoliumin A, D, and G can significantly suppress the levels of IL-1β, IL-6, and TNF-α. Moreover, molecular docking methods were utilized to confirm the high affinity between Spinifoliumin A, D, and G and EGFR, SRC, and JUN, which were consistent with the results of network pharmacology. This study provides basic scientific evidence to support ZDS’s traditional use and potential clinical application. Full article
(This article belongs to the Section Natural Products Chemistry)
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Figure 1

Figure 1
<p>Chemical structures of compounds <b>1</b>–<b>30</b>.</p>
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<p>The key HMBC and <sup>1</sup>H-<sup>1</sup>H COSY correlations of compounds <b>1</b>–<b>8</b>.</p>
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<p>ECD curve of the Rh<sub>2</sub>(OCOCF<sub>3</sub>)<sub>4</sub> complex of compound <b>1</b>.</p>
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<p>NOESY correlations of compound <b>7</b>.</p>
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<p>CD spectrum of <b>7</b> in DMSO containing Mo<sub>2</sub>(OAc)<sub>4</sub> with the inherent CDs subtracted.</p>
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<p>Experimental and calculated ECD spectra of compounds <b>7</b> and <b>8</b>.</p>
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<p>(<b>A</b>) Venn diagram showing the common target genes between ZDS and RA. (<b>B</b>,<b>C</b>) Overall PPI network and (<b>D</b>) the top 10 targets in order of degree value. (<b>E</b>) The top 30 KEGG pathways of hub genes and (<b>F</b>) the compound target pathway network.</p>
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<p>Cell viability of compounds <b>1</b>, <b>2</b>, and <b>4</b>–<b>8</b> of HFLS-RA. Data are expressed as mean ± SD (n = 3), vs. the control group, ns means non-significant and *** means <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Effect of compounds <b>1</b>, <b>2</b>, and <b>4</b>–<b>8</b> on the proliferation viability of LPS (1 μg/mL)-induced HFLS-RA cells. Data are expressed as mean ± SD (n = 3), vs. the untreated group (Normol), ###, <span class="html-italic">p</span> &lt; 0.001 vs. LPS-induced group, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Effects of compounds <b>1</b>, <b>5</b>, and <b>7</b> on the levels of pro-inflammatory cytokines IL-1β, IL-6, and TNF-α in the LPS (1 μg/mL)-induced HFLS-RA cells. Data are expressed as mean ± SD (n = 3), vs. untreated group, ###, <span class="html-italic">p</span> &lt; 0.001, vs. LPS-induced group, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Docking results of the three active compounds of ZDS and the key RA-associated targets. (<b>A</b>) compound <b>1</b> and EGFR; (<b>B</b>) compound <b>5</b> and EGFR; (<b>C</b>) compound <b>5</b> and SRC; (<b>D</b>) compound <b>7</b> and EGFR; (<b>E</b>) compound <b>7</b> and SRC; (<b>F</b>) compound <b>7</b> and JUN.</p>
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12 pages, 1292 KiB  
Article
Clinical Investigation of Bioelectric Toothbrush for Dentin Hypersensitivity Management: A Randomized Double-Blind Study
by Hyun-Kyung Kang, Yu-Rin Kim, Ji-Young Lee, Da-Jeong Kim and Young-Wook Kim
Bioengineering 2024, 11(9), 923; https://doi.org/10.3390/bioengineering11090923 (registering DOI) - 14 Sep 2024
Viewed by 242
Abstract
Background: The objective of this study was to evaluate how effectively the bioelectric toothbrush can alleviate dentin hypersensitivity (DHS) by using electrostatic forces to remove biofilm from the tooth surface. Methods: This study divided inpatients of a preventative dental clinic between March and [...] Read more.
Background: The objective of this study was to evaluate how effectively the bioelectric toothbrush can alleviate dentin hypersensitivity (DHS) by using electrostatic forces to remove biofilm from the tooth surface. Methods: This study divided inpatients of a preventative dental clinic between March and October 2023 into the following two groups: a bioelectric toothbrush group (BET, n = 25) and a non-bioelectric toothbrush group (NBET, n = 18) as a control group. This was a randomized double-blind, placebo-controlled trial study. A survey, the number of hypersensitive teeth, the O’Leary index, the visual analogue scale (VAS), and the Schiff Cold Air Sensitivity Scale (SCASS) were also investigated. Results: When fluoride toothpaste was applied with a bioelectric toothbrush, the subjects’ VAS and SCASS scores reflecting symptoms of hyperesthesia significantly decreased over time, as did the number of hypersensitive teeth and the O’Leary index. Moreover, the bioelectric toothbrush was confirmed to be effective in removing dental plaque. Conclusions: Dental clinics must actively promote bioelectric toothbrushes and fluoride toothpaste for patients suffering from hyperesthesia and pain. Furthermore, these items can be suggested as preventative oral care products to patients with potential hyperesthesia. Full article
(This article belongs to the Section Biomedical Engineering and Biomaterials)
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Figure 1
<p>Schematics of the BE and non-BE toothbrush (ProxiHealthcare, Seoul, Republic of Korea).</p>
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<p>Flowchart of participants.</p>
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<p>Flowchart of study method.</p>
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11 pages, 269 KiB  
Article
Anti TNF-Alpha Treatment Improves Microvascular Endothelial Dysfunction in Rheumatoid Arthritis Patients
by Alexandru Caraba, Oana Stancu, Viorica Crișan and Doina Georgescu
Int. J. Mol. Sci. 2024, 25(18), 9925; https://doi.org/10.3390/ijms25189925 (registering DOI) - 14 Sep 2024
Viewed by 216
Abstract
Nailfold capillaroscopy is a non-invasive investigation, which allows for the study of the microvasculature (anatomical and functional). Rheumatoid arthritis (RA) is associated with a high risk of cardiovascular atherosclerotic diseases, with endothelial dysfunction (macrovascular and microvascular) representing the first step in atherosclerosis development. [...] Read more.
Nailfold capillaroscopy is a non-invasive investigation, which allows for the study of the microvasculature (anatomical and functional). Rheumatoid arthritis (RA) is associated with a high risk of cardiovascular atherosclerotic diseases, with endothelial dysfunction (macrovascular and microvascular) representing the first step in atherosclerosis development. The aim of this study is represented by the assessment of microvascular endothelial dysfunction in RA patients by means of nailfold capillaroscopy and to assess its evolution after a period of 12 months of anti TNF-alpha treatment. The study included 70 consecutive patients with RA and 70 healthy subjects, matched for age and gender, as the control group. Rheumatoid factor, anti-cyclic citrullinated peptide antibodies, serum TNF-α, C reactive protein, and erythrocytes sedimentation rate were evaluated in all patients, but in controls, only rheumatoid factor, serum TNF-α, C reactive protein, and erythrocytes sedimentation rate were measured. The RA activity was measured by DAS28. Nailfold capillaroscopy was carried out in all patients and controls, determining the baseline nailfold capillary density (Db), nailfold capillary density during reactive hyperemia (Dh), and nailfold capillary density after venous congestion (Dc). Data were presented as mean ± standard deviation. Statistical analysis was performed using ANOVA and Pearson’s correlation, with p < 0.05 being statistically significant. Db, Dh, and Dc were lower in RA patients than in controls (p < 0.0001), correlating with RA activity and TNF-α (p < 0.05). After 12 months of anti TNF-α treatment, microvascular endothelial dysfunction improved (p < 0.0001). Microvascular endothelial dysfunction can be assessed by nailfold capillaroscopy, with anti TNF-α medication contributing to its improvement. Full article
25 pages, 22684 KiB  
Article
Hydrodynamic Modelling in a Mediterranean Coastal Lagoon—The Case of the Stagnone Lagoon, Marsala
by Emanuele Ingrassia, Carmelo Nasello and Giuseppe Ciraolo
Water 2024, 16(18), 2602; https://doi.org/10.3390/w16182602 - 14 Sep 2024
Viewed by 223
Abstract
Coastal lagoons are important wetland sites for migratory species and the local flora and fauna population. The Stagnone Lagoon is a coastal lagoon located on the west edge of Sicily between the towns of Marsala and Trapani. The area is characterized by salt-harvesting [...] Read more.
Coastal lagoons are important wetland sites for migratory species and the local flora and fauna population. The Stagnone Lagoon is a coastal lagoon located on the west edge of Sicily between the towns of Marsala and Trapani. The area is characterized by salt-harvesting plants and several archaeological sites and is affected by microtidal excursion. Two mouths allow exchange with the open sea: one smaller and shallower in the north and one larger and deeper in the south. This study aims to understand the lagoon’s hydrodynamics, in terms of circulation and involved forces. The circulation process appears to be dominated mainly by tide excursions and wind forces. Wind velocity, water levels, and water velocity were recorded during different field campaigns in order to obtain a benchmark value. The hydrodynamic circulation has been studied with a 2DH (two-dimensional in the horizontal plane) unstructured mesh model, calibrated with data collected during the 2006 field campaign and validated with the data of the 2007 campaign. Rapid changes in averaged velocity have been found both in Vx and Vy components, showing the strong dependence on seiches. This study tries to identify the main factor that domains the evolution of the water circulation. Sensitivity analyses were conducted to estimate the correct energy transfer between the forcing factors and dissipating ones. A Gauckler–Strickler roughness coefficient between 20 and 25 m1/3/s is found to be the most representative in the lagoon. To enhance the knowledge of this peculiar lagoon, the MIKE 21 model has been used, reproducing all the external factors involved in the circulation process. Nash–Sutcliffe coefficient of efficiency (NSE) values up to 0.92 and 0.79 are reached with a Gauckler–Strickler coefficient equal to 20 m1/3/s related to water depth and the Vy velocity component. The Vx velocity component NSE has never been satisfying, showing the limits of the 2D approach in reproducing the currents induced by local morphological peculiarities. Comparing the NSE value of water depth, there is a loss of up to 70% in model predictivity capability between the southern and the northern lagoon areas. This study aims to support the local decision-makers to improve the management of the lagoon itself. Full article
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Figure 1
<p>Study area.</p>
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<p>(<b>a</b>) Unstructured mesh used for the numerical simulations and (<b>b</b>) bathymetry recorded during the 1999 survey.</p>
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<p>Localization scheme during the 2006 and 2007 field campaigns. Colours indicate the instrument type.</p>
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<p>Comparison between filtered and raw signals in vertical (<b>a</b>), northward (<b>b</b>), and eastward (<b>c</b>) velocity components of ADV_07 (20 s sketch).</p>
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<p>Comparison between filtered and raw signals in vertical (<b>a</b>), northward (<b>b</b>), and eastward (<b>c</b>) velocity components of ADV_07 (20 s sketch).</p>
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<p>Water depth (<b>a</b>) and horizontal velocities northward and eastward, (<b>b</b>) and (<b>c</b>) respectively, recorded in 24 h at 1 Hz by Vec_07.</p>
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<p>Water depth (<b>a</b>) and horizontal velocities northward and eastward, (<b>b</b>) and (<b>c</b>) respectively, recorded in 24 h at 1 Hz by Vec_07.</p>
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<p>Evolution of water levels recorded in both mouths.</p>
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<p>Decoupling of recorded and simulated data on Vec_06, related to water depth (<b>a</b>) and horizontal velocities northward and eastward, (<b>b</b>) and (<b>c</b>) respectively.</p>
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<p>Behaviour of the Vy and Vx velocity components recorded and simulated in Adv_06, related to horizontal velocities northward and eastward, (<b>a</b>) and (<b>b</b>) respectively.</p>
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<p>Behaviour of simulated variables against the recorded data of Val_06, related to water depth (<b>a</b>) and horizontal velocities northward and eastward, (<b>b</b>) and (<b>c</b>) respectively.</p>
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<p>Graphical maps of hydrodynamic circulation. A whole tidal cycle is reported. A strong Venturi effect can be observed in when the flow is outgoing (<b>a</b>,<b>b</b>,<b>d</b>), caused by the falling tide. A modest eddy is simulated in (<b>c</b>). Is also possible to appreciate (<b>d</b>–<b>f</b>) the tide evolution with 6 h period.</p>
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<p>Hydrodynamic circulation in the lagoon’s southern region. Is possible to appreciate how the circulation follows the tides (<b>a</b>,<b>c</b>,<b>f</b>). Lower hydrodynamism is simulated in the coastal part of the lagoon (<b>b</b>,<b>d</b>). Is possible to appreciate the 6 h tide evolution (<b>e</b>,<b>f</b>).</p>
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<p>NSE values obtained by the comparison of Vec_06 (<b>a</b>), Adv_06 (<b>b</b>), Val_06 (<b>c</b>), and simulated ones, depending on bed roughness. All the Ks values are in m<sup>1/3</sup>/s.</p>
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<p>NSE values obtained by the comparison of Vec_06 (<b>a</b>), Adv_06 (<b>b</b>), and Val_06 (<b>c</b>) recorded values and simulated ones, depending on the friction factor f.</p>
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<p>Behaviour of simulated variables (water level, Vy, and Vx velocity components, respectively, in (<b>a</b>–<b>c</b>)) against the recorded data of Vec_07.</p>
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<p>Behaviour of the Vy and Vx velocity components recorded and simulated in Adv_07, related to horizontal velocities northward and eastward, (<b>a</b>) and (<b>b</b>) respectively.</p>
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<p>Behaviour of simulated variables (water level, Vy, and Vx velocity components, respectively, in (<b>a</b>–<b>c</b>)) against the recorded data of Val_07. In (<b>d</b>), the evolution of the wind blowing during 2007 campaign is reported.</p>
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<p>NSE values obtained by the comparison of Vec_07 (<b>a</b>), Adv_07 (<b>b</b>), Val_07 (<b>c</b>), and simulated ones, depending on bed roughness. All the Ks values are in m<sup>1/3</sup>/s.</p>
Full article ">Figure A1
<p>Scatter plots of the recorded and simulated values. All the water (<b>a</b>,<b>d</b>,<b>e</b>,<b>h</b>) level graphs look return an agreement between the variables, even if in both years simulated values of Valeport station returned a sort of delay effect (<b>d</b>,<b>h</b>). Is possible to appreciate the increasing NSE value from Vec_06 to Vec_07 (<b>b</b>,<b>f</b>). The agreement of Vy velocity component looks high scattered (<b>c</b>). The Vy velocity component looks better in 2007 (<b>f</b>,<b>g</b>) than in 2006 (<b>b</b>,<b>c</b>).</p>
Full article ">Figure A1 Cont.
<p>Scatter plots of the recorded and simulated values. All the water (<b>a</b>,<b>d</b>,<b>e</b>,<b>h</b>) level graphs look return an agreement between the variables, even if in both years simulated values of Valeport station returned a sort of delay effect (<b>d</b>,<b>h</b>). Is possible to appreciate the increasing NSE value from Vec_06 to Vec_07 (<b>b</b>,<b>f</b>). The agreement of Vy velocity component looks high scattered (<b>c</b>). The Vy velocity component looks better in 2007 (<b>f</b>,<b>g</b>) than in 2006 (<b>b</b>,<b>c</b>).</p>
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7 pages, 2353 KiB  
Communication
Antibiotic-Loaded Dendrimer Hydrogels in Periodontal Bone Regeneration: An In Vitro Release Feasibility Study
by Nicholas Yesbeck, Da Huang, Caroline Carrico, Parthasarathy Madurantakam and Hu Yang
Gels 2024, 10(9), 593; https://doi.org/10.3390/gels10090593 - 14 Sep 2024
Viewed by 249
Abstract
The prescription of a course of oral antibiotics following bone grafting procedures is a common practice in clinical periodontics to reduce surgical site infections. The goal of this study is to characterize the release profile of antibiotics via local delivery using dendrimer hydrogels [...] Read more.
The prescription of a course of oral antibiotics following bone grafting procedures is a common practice in clinical periodontics to reduce surgical site infections. The goal of this study is to characterize the release profile of antibiotics via local delivery using dendrimer hydrogels (DH) and to analyze the effect of two different particulate bone allografts on the release of the antibiotics in vitro. DH were synthesized from polyamidoamine (PAMAM) dendrimer G5 and polyethylene glycol diacrylate, and cefazolin was chosen as the antibiotic. The antibiotic-loaded samples were bathed in PBS and incubated at 37 °C; aliquots were taken (1 h, 2 h, 3 h, 4 h, 5 h, 6 h, 12 h, 24 h, 48 h, 72 h) and analyzed using HPLC to determine the amounts of released cefazolin. In samples with DH, the estimated maximum concentration of cefazolin was 36.97 ± 2.39 μg/mL (95% CI: 34.58–39.36) with 50% released in 4.17 h (95%: 3.26–5.07) and an estimated growth rate of 0.27 (95% CI: 0.17–0.37). For samples without DH, the estimated maximum concentration of cefazolin was 167.4 ± 7.0 μg/mL (95% CI: 160.4–174.4) with 50% released in 2.36 h (95% CI: 2.05–2.67) and an estimated growth rate of 0.70 (95% CI: 0.54–0.87). We conclude that DH are a promising platform for sustained antibiotic release and that the presence of bone grafts did not significantly affect their release. Full article
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Figure 1
<p>Schematic illustration of the preparation of cefazolin-loaded dendrimer hydrogels (DH) with allograft and their application in periodontal bone regeneration.</p>
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<p>Restricted cubic spline model for cefazolin concentration by time, bone graft material, and presence of DH.</p>
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<p>Logistic growth curves for cefazolin concentration with and without DH.</p>
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<p>Cumulative release of cefazolin. The curve indicates that without DH, cephazolin is released fast and early, while all formulations containing DH demonstrate a sustained steady release.</p>
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<p>Schematic illustration of proposed mechanism of cefazolin binding/release from DH.</p>
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15 pages, 2602 KiB  
Article
A Novel Approach for the Synthesis of Responsive Core–Shell Nanogels with a Poly(N-Isopropylacrylamide) Core and a Controlled Polyamine Shell
by Anna Harsányi, Attila Kardos, Pinchu Xavier, Richard A. Campbell and Imre Varga
Polymers 2024, 16(18), 2584; https://doi.org/10.3390/polym16182584 - 13 Sep 2024
Viewed by 207
Abstract
Microgel particles can play a key role, e.g., in drug delivery systems, tissue engineering, advanced (bio)sensors or (bio)catalysis. Amine-functionalized microgels are particularly interesting in many applications since they can provide pH responsiveness, chemical functionalities for, e.g., bioconjugation, unique binding characteristics for pollutants and [...] Read more.
Microgel particles can play a key role, e.g., in drug delivery systems, tissue engineering, advanced (bio)sensors or (bio)catalysis. Amine-functionalized microgels are particularly interesting in many applications since they can provide pH responsiveness, chemical functionalities for, e.g., bioconjugation, unique binding characteristics for pollutants and interactions with cell surfaces. Since the incorporation of amine functionalities in controlled amounts with predefined architectures is still a challenge, here, we present a novel method for the synthesis of responsive core–shell nanogels (dh < 100 nm) with a poly(N-isopropylacrylamide) (pNIPAm) core and a polyamine shell. To achieve this goal, a surface-functionalized pNIPAm nanogel was first prepared in a semi-batch precipitation polymerization reaction. Surface functionalization was achieved by adding acrylic acid to the reaction mixture in the final stage of the precipitation polymerization. Under these conditions, the carboxyl functionalities were confined to the outer shell of the nanogel particles, preserving the core’s temperature-responsive behavior and providing reactive functionalities on the nanogel surface. The polyamine shell was prepared by the chemical coupling of polyethyleneimine to the nanogel’s carboxyl functionalities using a water-soluble carbodiimide (EDC) to facilitate the coupling reaction. The efficiency of the coupling was assessed by varying the EDC concentration and reaction temperature. The molecular weight of PEI was also varied in a wide range (Mw = 0.6 to 750 kDa), and we found that it had a profound effect on how many polyamine repeat units could be immobilized in the nanogel shell. The swelling and the electrophoretic mobility of the prepared core–shell nanogels were also studied as a function of pH and temperature, demonstrating the successful formation of the polyamine shell on the nanogel core and its effect on the nanogel characteristics. This study provides a general framework for the controlled synthesis of core–shell nanogels with tunable surface properties, which can be applied in many potential applications. Full article
(This article belongs to the Special Issue Smart and Bio-Medical Polymers)
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Graphical abstract

Graphical abstract
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<p>The hydrodynamic size of (<b>a</b>) the carboxyl-functionalized pNIPAm nanogels and (<b>b</b>) a non-functionalized pNIPAm microgel in 10 mM HCl (pH = 2) and in 10 mM NaCl (pH = 7) as a function of temperature. Lines are only visual guides.</p>
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<p>(<b>a</b>) The electrophoretic mobility and (<b>b</b>) the hydrodynamic size of the carboxyl-functionalized pNIPAm nanogels as a function of pH at constant ionic strength (I = 10 mM). Lines are only visual guides.</p>
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<p>The variation in the microgel-bound PEI as a function of EDC excess used in the coupling reaction. The amount of microgel-bound PEI is given as a percentage of the total amount of PEI added to the reaction mixture. The lines are only visual guides.</p>
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<p>(<b>a</b>) The electrophoretic mobility and (<b>b</b>) the hydrodynamic size of the core–shell nanogels prepared with coupling low-molecular-weight PEI (<span class="html-italic">M<sub>w</sub></span> = 0.6 kDa) with a stoichiometric amount of EDC (in green) and using an EDC excess of ten times (in red). As a reference, data determined for the pNIPAm core are also plotted (in blue). Lines are only visual guides.</p>
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<p>The microgel-bound PEI as a function of the PEI molecular weight used in the coupling reaction. The amount of microgel-bound PEI is given as a percentage of the total amount of PEI added to the reaction mixture. The line is only a visual guide.</p>
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<p>The electrophoretic mobility of the core–shell nanogels prepared with coupling of PEIs with different molecular weights. As a reference, the electrophoretic mobility data determined for the pNIPAm core was also plotted (in blue). Lines are only visual guides.</p>
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<p>The hydrodynamic size of the core–shell pNIPAm nanogels prepared by coupling 10 kDa PEI as a function of temperature, measured in 10 mM HCl or in 10 mM NaOH. Lines are only visual guides.</p>
Full article ">Scheme 1
<p>A schematic representation of the synthesis protocol proposed to prepare pNIPAm nanogels with a polyamine shell. In the first step of the procedure, the precipitation polymerization of the nanogel beads is initiated at <span class="html-italic">t</span><sub>0</sub> with the addition of APS, and then after time <span class="html-italic">t</span><sub>1</sub> (when most of the monomers are already reacted), a second batch of monomers, including acrylic acid (AAc), is added to the reaction mixture to form the carboxyl-functionalized outer shell. These surface-functionalized nanogel beads are used to graft polyamine molecules to the carboxyl functionalities using EDC coupling to facilitate the formation of the polyamine shell in the second step of the protocol. (The yellow/green transition of the pNIPAm core indicates its decreasing crosslink density towards its surface; the blue shell depicts the acrylic-acid-functionalized outer shell of the nanogel core particles; the red shell represents the polyamine shell formed in the final coupling reaction.)</p>
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17 pages, 3803 KiB  
Article
Metabolic and Pharmacokinetic Profiling Studies of N, N-Dimethylaniline-Heliamine in Rats by UHPLC-Q-Orbitrap MS/MS
by Ruqi Xi, Rahima Abdulla, Jurakulov Sherzod, Vinogradova Valentina Ivanovna, Maidina Habasi and Yongqiang Liu
Molecules 2024, 29(18), 4324; https://doi.org/10.3390/molecules29184324 - 12 Sep 2024
Viewed by 214
Abstract
Cardiovascular disease is the first cause of death worldwide and kills more people each year than any other cause of death. N, N-dimethylaniline-heliamine (DH), a synthetic tetrahydroisoquinoline alkaloid, has shown notable antiarrhythmic activity. However, the metabolic processes and pharmacokinetic characteristics of DH in [...] Read more.
Cardiovascular disease is the first cause of death worldwide and kills more people each year than any other cause of death. N, N-dimethylaniline-heliamine (DH), a synthetic tetrahydroisoquinoline alkaloid, has shown notable antiarrhythmic activity. However, the metabolic processes and pharmacokinetic characteristics of DH in rats have not been studied. This study aims to identify its metabolites, as well as develop and validate a rapid and efficient bioanalytical method for quantifying DH in rat plasma over a wide range of concentrations. Its metabolites were characterized in silico, in vitro, and in vivo. A series of 16 metabolites were identified, of which 12 were phase I metabolites and 4 were phase II metabolites. A low probability of DH binding to DNA, protein, and glutathione is predicted by the in silico model. The main metabolic processes of DH were demethylation, dehydrogenation, glucuronidation, and sulfation. Concentration–time profiles were generated by analyzing the plasma, and the outcomes were analyzed via non-compartmental analysis to identify the pharmacokinetic parameters. Among the detected parameters were the volume of distribution, estimated at 126,728.09 ± 56,867.09 mL/kg, clearance at 30,148.65 ± 15,354.27 mL/h/kg, and absolute oral bioavailability at 16.11%. The plasma distribution volume of DH was substantially higher than the overall plasma volume of rats, which suggests that DH has a specific tissue distribution in rats. This study suggests that DH is appropriately bioavailable and excreted via a variety of routes and has low toxicity. Full article
(This article belongs to the Section Analytical Chemistry)
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Figure 1
<p>Chemical structures of DH and colchicine (IS).</p>
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<p>Schematic diagram of metabolites identification of DH.</p>
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<p>In silico prediction of phase I site (stable oxygenation, unstable oxygenation, dehydrogenation, hydrolysis, and reduction); site of reactivity (glutathione, protein, and DNA); site of quinonation, epoxidation, and N-dealkylation; site of glucuronidation in DH. Potential sites of metabolism are highlighted by a color gradient, distributed throughout a range of 0 (no color, minimal probability) to 1 (color, maximal probability).</p>
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<p>The characteristic fragments of the MS spectrum of DH.</p>
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<p>The total ion chromatograms of DH and its metabolites in pooled urine samples (<b>A</b>), blank urine samples (<b>B</b>), pooled feces samples (<b>C</b>), blank feces samples (<b>D</b>), pooled plasma samples (<b>E</b>), and blank plasma samples (<b>F</b>).</p>
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<p>The total ion chromatograms of DH and its metabolites in pooled liver microsome phase I samples (<b>A</b>), blank liver microsome phase I samples (<b>B</b>), pooled liver microsome phase II samples (<b>C</b>), and blank liver microsome phase II samples (<b>D</b>).</p>
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<p>The MS/MS spectra of M4–A/M4–B (<b>A</b>), M4–C (<b>B</b>), and M1–A/M1–B (<b>C</b>).</p>
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<p>The proposed metabolic pathways of DH in rats.</p>
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<p>The PRM extracted ion chromatogram of DH and IS in rat plasma: blank rat plasma (<b>A</b>); blank rat plasma spiked with 100 ng/mL and IS (<b>B</b>); an incurred sample after oral administration of DH at 1.5 h (<b>C</b>); an incurred sample after intravenous administration of DH at 1.0 h (<b>D</b>).</p>
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<p>The PRM extracted ion chromatogram of DH and IS in rat plasma: blank rat plasma (<b>A</b>); blank rat plasma spiked with 100 ng/mL and IS (<b>B</b>); an incurred sample after oral administration of DH at 1.5 h (<b>C</b>); an incurred sample after intravenous administration of DH at 1.0 h (<b>D</b>).</p>
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<p>Mean plasma concentration time curves of DH in rats after oral 19.2 mg/kg (n = 6, mean ± SD) and intravenous administration 1.9 mg/kg (n = 6, mean ± SD), respectively.</p>
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14 pages, 2352 KiB  
Article
Bisphenol S Promotes the Transfer of Antibiotic Resistance Genes via Transformation
by Jiayi Zhang, Shuyao Zhu, Jingyi Sun and Yuan Liu
Int. J. Mol. Sci. 2024, 25(18), 9819; https://doi.org/10.3390/ijms25189819 - 11 Sep 2024
Viewed by 346
Abstract
The antibiotic resistance crisis has seriously jeopardized public health and human safety. As one of the ways of horizontal transfer, transformation enables bacteria to acquire exogenous genes naturally. Bisphenol compounds are now widely used in plastics, food, and beverage packaging, and have become [...] Read more.
The antibiotic resistance crisis has seriously jeopardized public health and human safety. As one of the ways of horizontal transfer, transformation enables bacteria to acquire exogenous genes naturally. Bisphenol compounds are now widely used in plastics, food, and beverage packaging, and have become a new environmental pollutant. However, their potential relationship with the spread of antibiotic resistance genes (ARGs) in the environment remains largely unexplored. In this study, we aimed to assess whether the ubiquitous bisphenol S (BPS) could promote the transformation of plasmid-borne ARGs. Using plasmid pUC19 carrying the ampicillin resistance gene as an extracellular ARG and model microorganism E. coli DH5α as the recipient, we established a transformation system. Transformation assays revealed that environmentally relevant concentrations of BPS (0.1–10 μg/mL) markedly enhanced the transformation frequency of plasmid-borne ARGs into E. coli DH5α up to 2.02-fold. Fluorescent probes and transcript-level analyses suggest that BPS stimulated increased reactive oxygen species (ROS) production, activated the SOS response, induced membrane damage, and increased membrane fluidity, which weakened the barrier for plasmid transfer, allowing foreign DNA to be more easily absorbed. Moreover, BPS stimulates ATP supply by activating the tricarboxylic acid (TCA) cycle, which promotes flagellar motility and expands the search for foreign DNA. Overall, these findings provide important insight into the role of bisphenol compounds in facilitating the horizontal spread of ARGs and emphasize the need to monitor the residues of these environmental contaminants. Full article
(This article belongs to the Section Molecular Microbiology)
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<p>BPS promotes the transformation of ARGs into <span class="html-italic">E. coli</span> DH5α. (<b>A</b>) Growth curves of the recipient bacterium (<span class="html-italic">E. coli</span> DH5α) in the presence of different concentrations of the BPS (0.1–10 μg/mL). (<b>B</b>) Effects of different concentrations of the BPS on the frequency of transformation of pUC19 plasmid into <span class="html-italic">E. coli</span> DH5α. Statistically significant differences were determined using one-way ANOVA at * <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, respectively. NS, not significant. (<b>C</b>) Gel electropherograms of pUC19 plasmid, recipient bacteria, and transformants at different concentrations of BPS. (<b>D</b>) MIC values of recipient bacteria and transformants.</p>
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<p>BPS stimulates the production of ROS and enhances membrane permeability in the recipient bacteria. (<b>A</b>) Effects of different concentrations of BPS on ROS production by recipient bacteria. (<b>B</b>) Heat map of increased expression levels of genes related to the oxidative stress system and SOS response system of bacteria after BPS treatment. (<b>C</b>) Changes in outer membrane permeability of recipient bacteria following BPS pressure. (<b>D</b>) Changes in inner membrane permeability in response to BPS treatment. (<b>E</b>) Effect of BPS on membrane fluidity. Statistically significant differences were determined using one-way ANOVA at * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 and **** <span class="html-italic">p</span> &lt; 0.0001, respectively. NS, not significant. (<b>F</b>) Heatmap of the increased expression levels of genes related to bacterial membrane permeability after BPS treatment. (<b>G</b>) SEM images of <span class="html-italic">E. coli</span> DH5α bacterial cells exposed to 0.5 μg/mL BPS for 4 h. Cell membrane damage is indicated by red arrows.</p>
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<p>BPS enhances bacterial metabolism by accelerating the TCA cycle. (<b>A</b>) Bacterial respiration levels of <span class="html-italic">E. coli</span> DH5α were unchanged or even decreased under the pressure of BPS. (<b>B</b>) Heatmap of the expression levels of genes related to bacterial electron transport chain in response to BPS treatment. (<b>C</b>) Heatmap of TCA cycle-related gene expression levels in response to BPS. Bacterial (<b>D</b>) NAD<sup>+</sup>/NADH ratio, (<b>E</b>) NAD<sup>+</sup> content, and (<b>F</b>) NADH content under BPS treatment. Statistically significant differences were determined using one-way ANOVA at ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 and **** <span class="html-italic">p</span> &lt; 0.0001, respectively. NS, not significant.</p>
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<p>BPS stimulates ATP synthesis and flagellar motility. (<b>A</b>) ΔpH changes of recipient bacteria in response to BPS treatment, measured using BCECF. (<b>B</b>) Membrane potential of recipient bacteria in response to BPS stress, monitored using DiSC<sub>3</sub>(5). (<b>C</b>) Bacterial ATP synthesis after exposure to BPS. (<b>D</b>) Heat map of the expression level of bacterial ATP synthase-related genes under BPS stress. (<b>E</b>) Heatmap of the expression level of bacterial flagellum-related genes after BPS treatment. (<b>F</b>) Swimming motility test of <span class="html-italic">E. coli</span> DH5α under BPS stress, scale bar, 0.5 cm. Statistically significant differences were determined using one-way ANOVA at **** <span class="html-italic">p</span> &lt; 0.0001. NS, not significant.</p>
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<p>Schematic diagram of the mechanism of increased transformation by BPS treatment. The frequency of transformation of antibiotic-resistant plasmids was significantly increased under the stress of low concentrations of BPS. Potential mechanisms include a dramatic increase in ROS production and activation of the SOS response, which increases membrane permeability and fluidity. In addition, the accelerated TCA cycle generates a large amount of ATP, and flagellar motility was also enhanced. These actions are favorable for plasmid uptake, facilitation, and integration.</p>
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17 pages, 502 KiB  
Article
Effect of the Nitrification Inhibitor DMPP on Blueberry Planted in Neutral Soil
by Yiru Yang, Qilong Zeng, Hong Yu, Jiguang Wei, Jiafeng Jiang and Liangliang Tian
Agronomy 2024, 14(9), 2029; https://doi.org/10.3390/agronomy14092029 - 5 Sep 2024
Viewed by 325
Abstract
In order to increase nutrient input and alleviate the poor growth of blueberry (Vaccinium corymbosum L.) in neutral soil with strong nitrification, the application of nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP) as an enhanced efficiency fertilizer is a strategy to reduce nitrogen (N) [...] Read more.
In order to increase nutrient input and alleviate the poor growth of blueberry (Vaccinium corymbosum L.) in neutral soil with strong nitrification, the application of nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP) as an enhanced efficiency fertilizer is a strategy to reduce nitrogen (N) loss and improve N supply. However, few studies have systematically investigated the effect of DMPP application on blueberry and its soil condition in detail so far. In this study, a pot experiment was conducted to elucidate the effect of DMPP at four gradient levels including 0.5% (w/w applied-N) DMPP (DL), 1% DMPP (DM), 2% DMPP (DH), and no DMPP (CK) on the dynamics of soil mineral N (NH4+-N and NO3-N), soil chemical properties, as well as the agronomic characteristics and physiological indexes of blueberry plants in the neutral soil–blueberry system. The addition of DMPP significantly increased the retention of soil ammonium nitrogen and the content of total mineral nitrogen. qPCR analysis showed that DMPP inhibited the ammoxidation process mainly by reducing the abundance of the ammonia-oxidizing bacteria (AOB) amoA gene rather than the ammonia-oxidizing archaea (AOA) amoA gene. No significant inhibitory effect of DMPP was observed for the nitrite dehydrogenase gene nxrA and nitrite reductase gene nirS. Soil NH4+-N and available phosphorus content were both enhanced with the DMPP application rates both in bulk and rhizosphere soil. Applying 1% DMPP to the neutral soil for blueberry was sufficient to safely inhibit soil nitrification, not only increasing ammonium nitrogen content by 10.42% and 26.79%, but also enhancing available phosphorus content by 9.19% and 22.41% compared with CK in bulk and rhizosphere soil, respectively. Moreover, 1% DMPP addition increased the nitrogen and phosphorus concentration of blueberry leaves by 12.17% and 26.42%, respectively, compared with CK. The total branch length and the dry weight of blueberry plant were also increased by 16.8% and 33.1%, respectively. These results provide valuable agronomic information for the application of DMPP in blueberry cultivation. Fertilization applied with 1% DMPP has great economic potential to improve both nitrogen and phosphorus absorption of blueberry so as to promote the vegetative growth of blueberry. Full article
(This article belongs to the Section Horticultural and Floricultural Crops)
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<p>Dynamic changes of ammonium nitrogen, nitrate nitrogen, and total mineral nitrogen content in the soil planted with blueberry as affected by different 3,4-dimethylpyrazole phosphate (DMPP) levels through time. The value represents the mean of three samples, and the error bars indicate the standard deviation of the mean (n = 3). Down arrow ↓ indicates the time of fertilization and DMPP addition. CK = control with no DMPP; DL, DM, and DH = treatments applied with 0.5%, 1%, and 2% DMPP, respectively.</p>
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19 pages, 1923 KiB  
Article
Results of a Pilot Trial Assessing the Effects of Proper Oral Hygiene and a Probiotic Dietary Supplement on Oral Health in Volunteers with Oral Malodor
by Elena Y. Enioutina, R. James Keddington, Kurtis G. Hauck, Amarina Chavez, Jeffrey J. Clifford, Thy (April) Cao, Bryce Smith, Kathleen M. Job and Alfred Balch
Microorganisms 2024, 12(9), 1821; https://doi.org/10.3390/microorganisms12091821 - 3 Sep 2024
Viewed by 648
Abstract
Persistent malodor affects many people worldwide and is usually associated with poor dental hygiene. This pilot trial aimed to determine whether proper dental hygiene (DH) and a probiotic dietary supplement support oral health in volunteers with persistent malodor. Volunteers (n = 35) [...] Read more.
Persistent malodor affects many people worldwide and is usually associated with poor dental hygiene. This pilot trial aimed to determine whether proper dental hygiene (DH) and a probiotic dietary supplement support oral health in volunteers with persistent malodor. Volunteers (n = 35) were randomly assigned to the probiotic or placebo cohort. The probiotic cohort (n = 20) brushed and flossed their teeth twice daily and used probiotics for 30 days; the placebo cohort (n = 15) followed the same hygiene practices and used the placebo. The intervention phase was followed by a 30-day follow-up period. Measured outcomes were malodor and tongue-coating scores, probiotic DNA levels, salivary cytokines, and salivary pH. DH and probiotics significantly decreased malodor (~50% during intervention) and tongue coating scores (~45% during intervention). These changes remained through the course of the trial. The probiotic DNA levels increased in the probiotic cohort and dropped in the placebo cohort after the intervention started. The malodor moderately correlated with the tongue coating P. acidilactici level. The addition of probiotics increased IL-10 levels during the intervention and decreased IL-8, TNF-α, and IL-6 by the end of the study. People with malodor may benefit from using DH and probiotics. Additional trials are needed to definitively establish the benefits of probiotic dietary supplements. Full article
(This article belongs to the Special Issue Interactions between Probiotics and Host)
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<p>In-between teeth positions at which participants evaluated the intensity of malodor. Modified from <a href="https://en.wikipedia.org/wiki/Universal_Numbering_System" target="_blank">https://en.wikipedia.org/wiki/Universal_Numbering_System</a> (accessed on 20 May 2024). The Universal Numbering System image was created by Kaligula (<a href="http://commons.wikimedia.org/wiki/User:Kaligula" target="_blank">http://commons.wikimedia.org/wiki/User:Kaligula</a>) accessed on 11 May 2013.</p>
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<p>Tongue division into six areas for tongue coating evaluation. A–F tongue areas where the coating scores were evaluated.</p>
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<p>CONSORT flow diagram of participants who participated in the study, according to the CONSORT 2010 Statement.</p>
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<p>Malodor score changes. (<b>A</b>)—the measurements were performed by participants during office visits; *—the differences between the baseline measurements and visit 2 measurements in the probiotic cohort were statistically significant (<span class="html-italic">p</span> &lt; 0.0001); †—the differences between the baseline measurements and visit 2 measurements in the placebo cohort were statistically significant (<span class="html-italic">p</span> &lt; 0.0001); there were no statistically significant differences in the malodor reduction between the placebo and probiotic cohorts. (<b>B</b>)—The measurements were taken by participants at home.</p>
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<p>The probability of having a malodor score depends on the levels of <span class="html-italic">P. acidilactici</span> in the tongue coating. (<b>A</b>)—Malodor score of 0; (<b>B</b>)—malodor score of 1; (<b>C</b>)—malodor score of 2; (<b>D</b>)—malodor score of 3.</p>
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15 pages, 6877 KiB  
Article
Finger Multi-Joint Trajectory Measurement and Kinematics Analysis Based on Machine Vision
by Shiqing Lu, Chaofu Luo, Hui Jin, Yutao Chen, Yiqing Xie, Peng Yang and Xia Huang
Actuators 2024, 13(9), 332; https://doi.org/10.3390/act13090332 - 2 Sep 2024
Viewed by 308
Abstract
A method for measuring multi-joint finger trajectories is proposed using MediaPipe. In this method, a high-speed camera is used to record finger movements. Subsequently, the recorded finger movement data are input into MediaPipe, where the system automatically extracts the coordinate data of the [...] Read more.
A method for measuring multi-joint finger trajectories is proposed using MediaPipe. In this method, a high-speed camera is used to record finger movements. Subsequently, the recorded finger movement data are input into MediaPipe, where the system automatically extracts the coordinate data of the key points in the finger movements. From this, we obtain data pertaining to the trajectory of the finger movements. In order to verify the accuracy and effectiveness of this experimental method, we compared it with the DH method and the Artificial keypoint alignment method in terms of metrics such as MAPE (Mean Absolute Percentage Error), maximum distance error, and the time taken to process 500 images. The results demonstrated that our method can detect multiple finger joints in a natural, efficient, and accurate manner. Then, we measured posture for three selected hand movements. We determined the position coordinates of the joints and calculated the angular acceleration of the joint rotation. We observed that the angular acceleration can fluctuate significantly over a very short period of time (less than 100 ms), in some cases increasing to more than ten times the initial acceleration. This finding underscores the complexity of finger joint movements. This study can provide support and reference for the design of finger rehabilitation robots and dexterous hands. Full article
(This article belongs to the Section Actuators for Robotics)
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<p>Schematic diagram of the physiological structure of the finger.</p>
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<p>Statistical values of finger bone length ranges.</p>
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<p>Experimental flow chart of the trajectory measurement based on the MediaPipe method.</p>
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<p>Hand fixed platform and gesture locator.</p>
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<p>Experimental operating platform.</p>
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<p>The process of three gestures. (<b>a</b>) The palmar grasp simulates the natural state of the hand when grasping an object. While exercising the coordination of finger muscles, it also involves the flexibility of the MCP joints; (<b>b</b>) the pincer grasp gesture helps to increase the strength and flexibility of the fingers. In particular, it exercises the backward drive of the MCP joints and the coordinated control of the PIP and DIP joints; (<b>c</b>) the posture of straight exercises the upward drive movement of the MCP joints, and can fully exercise the DIP joints. It is very beneficial for the recovery of pushing, grasping, and other movements.</p>
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<p>System test drawing and actual effect test drawing. (<b>a</b>) Illustration of 21 Key points in the MediaPipe system; (<b>b</b>) proof of alignment between the actual image and the MediaPipe system.</p>
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<p>Motion trajectory fitting diagrams for the three joints of the palmar grasp. (<b>a</b>) The curve fitting the PIP joint motion trajectory; (<b>b</b>) the curve fitting the DIP joint motion trajectory; (<b>c</b>) the curve fitting the fingertip joint motion trajectory.</p>
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<p>Coordinate system of index finger DH method.</p>
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<p>MediaPipe system identification point, identification icon center point and index finger node coincidence image.</p>
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<p>Summary diagram of trajectories obtained by three measurement methods.</p>
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<p>Palmar Grasp of joint motion trajectory.</p>
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<p>Palmar grasp of joint bending angle data. (<b>a</b>) Curve of angular acceleration variation; (<b>b</b>) MCP angle and angular acceleration curve; (<b>c</b>) PIP angle and angular acceleration curve; (<b>d</b>) DIP angle and angular acceleration curve.</p>
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<p>Pincer Grasp of joint motion trajectory.</p>
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<p>Pincer grasp of joint bending angle data. (<b>a</b>) Curve of angular acceleration variation; (<b>b</b>) MCP angle and angular acceleration curve; (<b>c</b>) PIP angle and angular acceleration curve; (d) DIP angle and angular acceleration curve.</p>
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<p>The straightening posture of joint motion trajectory.</p>
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<p>The straightening posture of joint bending angle data. (<b>a</b>) Curve of angular acceleration variation; (<b>b</b>) MCP angle and angular acceleration curve; (<b>c</b>) PIP angle and angular acceleration curve; (<b>d</b>) DIP angle and angular acceleration curve.</p>
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11 pages, 465 KiB  
Article
Evaluating the Impact of Nutritional Risk on Stress-Induced Hyperglycemia and Trauma Patient Outcomes
by Ching-Ya Huang, Yuan-Hao Yen, Ting-Min Hsieh, Ching-Hua Tsai, Shiun-Yuan Hsu and Ching-Hua Hsieh
Healthcare 2024, 12(17), 1746; https://doi.org/10.3390/healthcare12171746 - 2 Sep 2024
Viewed by 321
Abstract
Introduction: Stress-induced hyperglycemia (SIH) and malnutrition are common in trauma patients and are linked to worse outcomes. This study examined the influence of nutritional status, determined by the Geriatric Nutritional Risk Index (GNRI), on the incidence of SIH in trauma patients. Methods: A [...] Read more.
Introduction: Stress-induced hyperglycemia (SIH) and malnutrition are common in trauma patients and are linked to worse outcomes. This study examined the influence of nutritional status, determined by the Geriatric Nutritional Risk Index (GNRI), on the incidence of SIH in trauma patients. Methods: A retrospective analysis was conducted on adult trauma patients admitted to a Level I trauma center from 1 January 2009 to December 31, 2021. Patients were categorized into four groups: SIH, diabetic hyperglycemia (DH), diabetic normoglycemia (DN), and non-diabetic normoglycemia (NDN). Nutritional status was assessed using GNRI: high risk (GNRI < 82), moderate risk (82 ≤ GNRI < 92), low risk (92 ≤ GNRI ≤ 98), and no risk (GNRI > 98). Incidence of SIH and outcomes were analyzed across GNRI groups. Results: SIH was associated with higher mortality across all GNRI groups compared to NDN, with the highest rate (45.7%) in the high-risk group. Mortality decreased as GNRI increased in all glucose groups. NDN patients had the lowest mortality rates across GNRI groups. There was no correlation between GNRI and SIH incidence (p = 0.259). Conclusion: SIH significantly influenced mortality across all nutritional status groups, with the highest impact in malnourished patients. Although malnutrition did not affect SIH incidence, both SIH and poor nutritional status independently contributed to worse trauma outcomes. Targeted management of hyperglycemia and nutritional deficiencies is crucial for improving survival. Full article
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<p>Enrollment and grouping of the patients. Geriatric Nutritional Risk Index (GNRI); SIH = stress-induced hyperglycemia; DN = diabetic normoglycemia; DH = diabetic hyperglycemia; NDN = non-diabetic normoglycemia.</p>
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22 pages, 6668 KiB  
Article
Multi-Omics Reveals the Role of Arachidonic Acid Metabolism in the Gut–Follicle Axis for the Antral Follicular Development of Holstein Cows
by Yajun Guo, Shiwei Wang, Xuan Wu, Rong Zhao, Siyu Chang, Chen Ma, Shuang Song and Shenming Zeng
Int. J. Mol. Sci. 2024, 25(17), 9521; https://doi.org/10.3390/ijms25179521 - 1 Sep 2024
Viewed by 582
Abstract
In vitro embryonic technology is crucial for improving farm animal reproduction but is hampered by the poor quality of oocytes and insufficient development potential. This study investigated the relationships among changes in the gut microbiota and metabolism, serum features, and the follicular fluid [...] Read more.
In vitro embryonic technology is crucial for improving farm animal reproduction but is hampered by the poor quality of oocytes and insufficient development potential. This study investigated the relationships among changes in the gut microbiota and metabolism, serum features, and the follicular fluid metabolome atlas. Correlation network maps were constructed to reveal how the metabolites affect follicular development by regulating gene expression in granulosa cells. The superovulation synchronization results showed that the number of follicle diameters from 4 to 8 mm, qualified oocyte number, cleavage, and blastocyst rates were improved in the dairy heifers (DH) compared with the non-lactating multiparous dairy cows (NDC) groups. The gut microbiota was decreased in Rikenellaceae_RC9_gut_group, Alistipes, and Bifidobacterium, but increased in Firmicutes, Cyanobacteria, Fibrobacterota, Desulfobacterota, and Verrucomicrobiota in the NDC group, which was highly associated with phospholipid-related metabolites of gut microbiota and serum. Metabolomic profiling of the gut microbiota, serum, and follicular fluid further demonstrated that the co-metabolites were phosphocholine and linoleic acid. Moreover, the expression of genes related to arachidonic acid metabolism in granulosa cells was significantly correlated with phosphocholine and linoleic acid. The results in granulosa cells showed that the levels of PLCB1 and COX2, participating in arachidonic acid metabolism, were increased in the DH group, which improved the concentrations of PGD2 and PGF in the follicular fluid. Finally, the expression levels of apoptosis-related proteins, cytokines, and steroidogenesis-related genes in granulosa cells and the concentrations of steroid hormones in follicular fluid were determinants of follicular development. According to our results, gut microbiota-related phosphocholine and linoleic acid participate in arachidonic acid metabolism in granulosa cells through the gut–follicle axis, which regulates follicular development. These findings hold promise for enhancing follicular development and optimizing oocyte quality in subfertile dairy cows. Full article
(This article belongs to the Section Molecular Endocrinology and Metabolism)
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<p>Serum concentrations of key biochemicals and reproductive hormones and antral follicle numbers at OPU in the DH and NDC groups. (<b>A</b>) Serum levels of alanine transaminase (ALT) and aspartate aminotransferase (AST) on D0 of OPU in the DH and NDC groups (<span class="html-italic">n</span> = 3 per group). (<b>B</b>) Serum cortisol (COR) levels on D0 of OPU in the DH and NDC groups (<span class="html-italic">n</span> = 3 per group). (<b>C</b>) Serum levels of triglycerides (TG), glucose (GLU), cholesterol (CHOL), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) on D0 of OPU in the DH and NDC groups (<span class="html-italic">n</span> = 3 per group). (<b>D</b>) Serum levels of follicle-stimulating hormone (FSH), luteinizing hormone (LH), estrogen (E<sub>2</sub>), and progesterone (P<sub>4</sub>) on D0 of OPU in the DH and NDC groups (<span class="html-italic">n</span> = 3 per group). (<b>E</b>) Serum levels of FSH, LH, E<sub>2,</sub> and P<sub>4</sub> on D5 of OPU in the DH and NDC groups (<span class="html-italic">n</span> = 3 per group). (<b>F</b>) Ultrasound images of follicular development on D5 of OPU in the DH and NDC groups. The white dashed box indicates the ovary and the red pentagonal star indicates the follicle. Bar scale 8 mm. Data are presented as mean ± SD. Student’s <span class="html-italic">t</span>-test (two-tailed) was used for statistical analysis. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. ns: not significant. DH: dairy heifers, NDC: non-lactating multiparous dairy cows.</p>
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<p>Composition of the gut microbiota in the DH and NDC groups. (<b>A</b>) Taxonomic annotation of gut microbiota for DH and NDC samples. (<b>B</b>) Relative abundance of gut microbiota at the phylum level in the DH and NDC samples. (<b>C</b>) Relative abundance of gut microbiota at the genus level in the DH and NDC samples. (<b>D</b>) Alpha diversity evaluation of gut microbiota richness and evenness by measuring Chao and Shannon diversity indexes. <span class="html-italic">p</span> &lt; 0.05 significant difference, <span class="html-italic">p</span> &lt; 0.01 highly significant difference, <span class="html-italic">p</span> ≥ 0.05 insignificant difference. (<b>E</b>) Rarefaction curves of gut microbiota for DH and NDC groups. (<b>F</b>) Bray-Curtis Principal coordinate analysis plot of gut microbiota based on the operational taxonomic unit metrics of the samples in the DH and NDC groups. (<b>G</b>) Unweighted pair-group method with arithmetic mean (UPGMA) analysis at the phylum level for DH and NDC samples. (<b>H</b>) UPGMA analysis at the genus level for DH and NDC samples. <span class="html-italic">n</span> = 8 per group.</p>
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<p>Identification of key differential gut microbiota in the DH and NDC groups. (<b>A</b>) Principal coordinates analysis (PCoA) for the DH and NDC groups. (<b>B</b>,<b>C</b>) Linear discriminant analysis effect size (LEfSe) was performed to identify the differential microbiota in the DH and NDC groups. (<b>D</b>) Heatmap showing the differences in gut microbiota abundance at the phylum level between the DH and NDC groups. (<b>E</b>) The random forest analysis demonstrated the importance ranking of differential gut microbes at the phylum level between the DH and NDC groups. (<b>F</b>) Heatmap showing the difference in gut microbiota abundance at the genus level between the DH and NDC groups. (<b>G</b>) The random forest analysis demonstrated the importance ranking of differential gut microbes at the genus level in the two groups. <span class="html-italic">n</span> = 8 per group.</p>
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<p>The composition and different metabolites of gut microbiota and correlation with gut microbiota between the DH and NDC groups. (<b>A</b>,<b>B</b>) Heatmap showing the relative abundance of key identified metabolites (VIP &gt; 1, <span class="html-italic">p</span> &lt; 0.05). (<b>C</b>) KEGG enrichment analysis of differential metabolites. (<b>D</b>) Relative levels of differential metabolites of ABC transporters. (<b>E</b>) Relative levels of the differential metabolites of steroid hormone biosynthesis. (<b>F</b>) Spearman’s correlation analysis of different gut microbiota and metabolites. Blue indicates a positive correlation and red indicates a negative correlation. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Composition and differences in serum metabolites between the DH and NDC groups. (<b>A</b>,<b>B</b>) Heatmap showing the relative abundance of the key identified metabolites (VIP &gt;1, <span class="html-italic">p</span> &lt; 0.05. <span class="html-italic">n</span> = 6 per group). (<b>C</b>) KEGG enrichment analysis of differential metabolites. (<b>D</b>) Correlation analysis of gut microbiota and serum metabolites. Blue indicates a positive correlation and red indicates a negative correlation. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. <span class="html-italic">n</span> = 6 per group.</p>
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<p>Composition and different metabolites in the follicular fluid between the DH and NDC groups. (<b>A</b>,<b>B</b>) Heatmap showing the relative abundance of the key identified metabolites (VIP &gt; 1, <span class="html-italic">p</span> &lt; 0.05). (<b>C</b>) KEGG enrichment analysis of different metabolites. (<b>D</b>) Relative levels of different metabolites of protein digestion and absorption. (<b>E</b>) Relative levels of different metabolites of ABC transporters. (<b>F</b>) Relative levels of the differential metabolites of cholesterol metabolism. (<b>G</b>) Relative levels of different biosynthesis of amino acids metabolites. <span class="html-italic">n</span> = 6 per group.</p>
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<p>The different expression of genes in granulosa cells between the DH and NDC groups. (<b>A</b>) PCA analysis. (<b>B</b>) Volcano plot showing the changes in gene expression. (<b>C</b>) Heatmap of differentially expressed genes (DEGs). (<b>D</b>) GO enrichment analysis of DEGs. (<b>E</b>) KEGG pathway enrichment analysis of up-regulation DEGs. (<b>F</b>) KEGG pathway enrichment analysis of down-regulation DEGs. (<b>G</b>) Heatmap illustrating the expression of genes related to apoptosis and programmed cell death in the two groups. (<b>H</b>) Heatmap illustrating the expression of genes related to arachidonic acid metabolism in DH and NDC groups. (<b>I</b>) The heatmap illustrates the expression of genes related to steroid hormone metabolism in the two groups. (<b>J</b>) Heatmap illustrating the expression of genes related to growth factors in the two groups. <span class="html-italic">n</span> = 4 per group.</p>
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<p>Screening for shared metabolites among gut microbiota, serum, and follicular fluid to construct their regulatory network in granulosa cells. (<b>A</b>–<b>C</b>) The important metabolites in gut microbiome (<b>A</b>), serum (<b>B</b>), and follicular fluid (<b>C</b>) by the random forest analysis. (<b>D</b>–<b>F</b>) Expression of metabolites related to membrane phospholipids in rectal feces (<b>D</b>), serum (<b>E</b>), and follicular fluid (<b>F</b>). (<b>G</b>) The network maps in linoleic acid and arachidonic acid metabolism pathways. The red line showed a positive correlation and the green line indicates a negative correlation (|R| &gt; 0.8 and <span class="html-italic">p</span> &lt; 0.01). * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Metabolite levels in follicular fluid related to arachidonic acid and steroid hormones, and gene expression in granulosa cells related to both pathways. (<b>A</b>) Levels of arachidonic acid metabolites in follicular fluid (<span class="html-italic">n</span> = 3 per group). (<b>B</b>,<b>C</b>) The levels of PTGS2, ALOX5, and PLCB1 in granulosa cells. (<b>D</b>) The mRNA expression levels of genes related to apoptosis, arachidonic acid metabolism, steroid hormones synthesis, and inflammation in granulosa cells. (<b>E</b>,<b>F</b>) The levels of steroid hormones metabolites in follicular fluid (<span class="html-italic">n</span> = 3 per group). (<b>G</b>) Correlation between metabolites in the arachidonic acid metabolism and steroid hormones synthesis. (<b>H</b>,<b>I</b>) The levels of HIF-1α, SOD1, ERK1/2, P-ERK1/2, and p38MAPK in granulosa cells. (<b>J</b>,<b>K</b>) The levels of apoptosis-related proteins (BCL2, BAX, CASP3, and P53), and programmed cell death-related proteins in granulosa cells (IRF1, RIPK1, GSDMD, IL-1B, and MIF). (<b>L</b>) Comparison of COX2, PLCB1, and ALOX5 expression between healthy (HF) and atresia (AF) follicles by immunofluorescence staining. COX2, PLCB1, and ALOX5 were stained green. DNA was stained blue. White dashed line indicates follicular basement membrane. Scale bar, 20μm. Data are presented as mean ± SD. Student’s <span class="html-italic">t</span>-test (two-tailed) was used for statistical analysis. * <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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19 pages, 7761 KiB  
Article
Forecasting of Daily Heat Production in a District Heating Plant Using a Neural Network
by Adam Maryniak, Marian Banaś, Piotr Michalak and Jakub Szymiczek
Energies 2024, 17(17), 4369; https://doi.org/10.3390/en17174369 - 1 Sep 2024
Viewed by 507
Abstract
Artificial neural networks (ANNs) can be used for accurate heat load forecasting in district heating systems (DHSs). This paper presents an application of a shallow ANN with two hidden layers in the case of a local DHS. The developed model was used to [...] Read more.
Artificial neural networks (ANNs) can be used for accurate heat load forecasting in district heating systems (DHSs). This paper presents an application of a shallow ANN with two hidden layers in the case of a local DHS. The developed model was used to write a simple application in Python 3.10 that can be used in the operation of a district heating plant to carry out a preliminary analysis of heat demand, taking into account the ambient temperature on a given day. The model was trained using the real data from the period 2019–2022. The training was sufficient for the number of 150 epochs. The prediction effectiveness indicator was proposed. In the considered case, the effectiveness of the trained network was 85% and was better in comparison to five different regression models. The developed tool was based on an open-source programming environment and proved its ability to predict heating load. Full article
(This article belongs to the Collection Energy Efficiency and Environmental Issues)
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<p>The research algorithm.</p>
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<p>Ambient temperature and heat production.</p>
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<p>Heating energy and ambient temperature.</p>
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<p>Daily duration curves of heating power in 2019, 2020 and 2021.</p>
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<p>The Pearson correlation coefficient matrix plot for the heat load and influencing factors.</p>
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<p>Graphs showing correlations between individual parameters. Part 1.</p>
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<p>Graphs showing correlations between individual parameters. Part 2.</p>
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<p>Graphs showing correlations between individual parameters. Part 3.</p>
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<p>Graphs showing correlations between individual parameters. Part 4.</p>
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<p>Algorithm of source code operation.</p>
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<p>Structure of the artificial network.</p>
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<p>Flow chart of the k-method—cross-validation.</p>
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<p>Algorithm of forecast tool operation.</p>
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<p>Plots of MAE against the number of epochs during training and validation of a network with (<b>a</b>) 8 neurons in each layer; (<b>b</b>) 32 neurons in each layer.</p>
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<p>Plots of MAE against the number of epochs during training and validation of a network with (<b>a</b>) 64 neurons in each layer; (<b>b</b>) 120 neurons in each layer.</p>
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<p>The RMSE training and validation errors for the 64 neurons.</p>
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<p>Real and predicted heating energy.</p>
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16 pages, 2618 KiB  
Article
Quantitative Trait Loci Mapping of Heading Date in Wheat under Phosphorus Stress Conditions
by Bin Yang, Ling Qiao, Xingwei Zheng, Jun Zheng, Bangbang Wu, Xiaohua Li and Jiajia Zhao
Genes 2024, 15(9), 1150; https://doi.org/10.3390/genes15091150 - 31 Aug 2024
Viewed by 496
Abstract
Wheat (Triticum aestivum L.) is a crucial cereal crop, contributing around 20% of global caloric intake. However, challenges such as diminishing arable land, water shortages, and climate change threaten wheat production, making yield enhancement crucial for global food security. The heading date [...] Read more.
Wheat (Triticum aestivum L.) is a crucial cereal crop, contributing around 20% of global caloric intake. However, challenges such as diminishing arable land, water shortages, and climate change threaten wheat production, making yield enhancement crucial for global food security. The heading date (HD) is a critical factor influencing wheat’s growth cycle, harvest timing, climate adaptability, and yield. Understanding the genetic determinants of HD is essential for developing high-yield and stable wheat varieties. This study used a doubled haploid (DH) population from a cross between Jinmai 47 and Jinmai 84. QTL analysis of HD was performed under three phosphorus (P) treatments (low, medium, and normal) across six environments, using Wheat15K high-density SNP technology. The study identified 39 QTLs for HD, distributed across ten chromosomes, accounting for 2.39% to 29.52% of the phenotypic variance. Notably, five stable and major QTLs (Qhd.saw-3A.7, Qhd.saw-3A.8, Qhd.saw-3A.9, Qhd.saw-4A.4, and Qhd.saw-4D.3) were consistently detected across varying P conditions. The additive effects of these major QTLs showed that favorable alleles significantly delayed HD. There was a clear trend of increasing HD delay as the number of favorable alleles increased. Among them, Qhd.saw-3A.8, Qhd.saw-3A.9, and Qhd.saw-4D.3 were identified as novel QTLs with no prior reports of HD QTLs/genes in their respective intervals. Candidate gene analysis highlighted seven highly expressed genes related to Ca2+ transport, hormone signaling, glycosylation, and zinc finger proteins, likely involved in HD regulation. This research elucidates the genetic basis of wheat HD under P stress, providing critical insights for breeding high-yield, stable wheat varieties suited to low-P environments. Full article
(This article belongs to the Special Issue Advances in Breeding and Genetics of Wheat)
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<p>Phenotypic analysis of heading date (HD) in the DH population under different phosphorus (P) levels. (<b>A</b>) Distribution of HD in the DH population across varying P levels. Arrows indicate the positions of the parental lines Jinmai 47 and Jinmai 84. The data presented are based on the best linear unbiased prediction (BLUP) values. (<b>B</b>) Pearson correlation coefficients of HD between different P levels (E1 to E6) and BLUP values. Asterisks denote significance levels: *** <span class="html-italic">p</span> &lt; 0.001. (<b>C</b>) Density distribution of HD in the DH population under different P treatments.</p>
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<p>Genomic distribution of SNP markers, map length, and marker density across chromosomes. (<b>A</b>) Number of SNP markers on each chromosome. (<b>B</b>) Length of each chromosome in centiMorgans (cM). (<b>C</b>) Marker density (cM/marker) for each chromosome in the wheat genome.</p>
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<p>Relationship between the number of favorable alleles of major QTLs and heading date (HD) in wheat (BLUP data). Violin plots show the distribution of HD values for different numbers of favorable alleles. The numbers in parentheses indicate the number of lines within each group. Statistical significance is indicated by asterisks (** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>Expression profiles of candidate genes in wheat tissues. A heatmap illustrating the expression levels of candidate genes associated with heading date across various wheat tissues (coleoptile, leaf, shoots, and second leaf). Expression levels are presented on a log2 scale, with colors ranging from low (blue) to high (red) expression.</p>
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