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21 pages, 4944 KiB  
Article
Evaluation of the Nutritional Impact of Baobab Leaves (Adansonia digitata L.) as a Dietary Intervention to Combat Nutrient Deficiencies and Poverty-Related Health Problems
by Abdelhakam Esmaeil Mohamed Ahmed, Massimo Mozzon, Abdaljbbar B. A. Dawod, Eltayeb Omaima Awad Mustafa, Shaikh Ayaz Mukarram, Tahra ElObeid, Elshafia Ali Hamid Mohammed and Béla Kovács
Nutrients 2024, 16(24), 4340; https://doi.org/10.3390/nu16244340 - 16 Dec 2024
Viewed by 681
Abstract
Background/Objectives: Baobab (Adansonia digitate L.) is an underutilized species and edible parts (fruits, leaves and seeds) contribute to food security and human health in tropical areas. Although the fruits have attracted greater research interest and have recently been approved for consumption in [...] Read more.
Background/Objectives: Baobab (Adansonia digitate L.) is an underutilized species and edible parts (fruits, leaves and seeds) contribute to food security and human health in tropical areas. Although the fruits have attracted greater research interest and have recently been approved for consumption in EU countries, the leaves are traditionally consumed but they have yet to be studied from an interventional perspective. The aim of this study was to propose a protocol for a dietary intervention using baobab leaves (BLs) to achieve the recommended reference values for proteins and minerals (K, Ca, Mg, Na, Fe, Mn) for different target groups of the Sudanese population. Methods: Dry matter, crude fat, protein and ash content, mineral content (Na, Mg, K, Ca, Fe, Mn), total phenolic, and flavonoid compounds were determined in BLs from six different areas. To assess the health and nutrition status in Sudan, time-series data (2013–2023) from the DataBank Health Nutrition and Population Statistics database were used. The reference values for nutrients recommended by the European Food Safety Authority were used to estimate the amount of baobab leaf intake (BLI, g/day). Results: For each nutrient, the study area with the lowest amount of BLs to be consumed is recommended. Leaves from the area of El Gari (BN3) 18.312 g/day and 30.712 g/day are recommended for K and Ca, which are particularly beneficial for children aged 1–3 years and lactating women. Leaves from Kor Tagat (KR1) are suitable for sodium intake, requiring approximately 13–23 g/day across all age groups. Leaves from Kazgil (KR2) (46–81 g/day), (35–66 g/day), (0.48–0.68 g/day), and (4–6 g/day) are optimal for fulfilling the daily requirements of magnesium, iron, manganese, and protein in this order. Conclusions: The systematic inclusion of BLs in the diet can positively support the nutritional status of various demographics. Moreover, the findings of this study demonstrated the foundation for public health and nutritional policy-makers on how they will tackle malnutrition and food insecurity worldwide by incorporating naturally available diets and nutritious alternatives. Recommendation: Further research should focus on assessing the nutritional composition factors that could affect the absorption of nutrients such as phytates and oxalates and investigating the in vitro bioavailability of the elements. Full article
(This article belongs to the Section Nutrition and Public Health)
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<p>The location of the north Kordofan and Blue Nile regions in Sudan where baobab leaves were sourced. Source, QGIS 3.20.1 software.</p>
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<p>(<b>a</b>) Baobab trees and (<b>b</b>) baobab of (mixed of young and old) fresh leaves from Sudan.</p>
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<p>(<b>a</b>) Current health expenditure as a percentage of gross domestic product (GDP%) vs. prevalence of undernourishment. (<b>b</b>) Out-of-pocket expenditure per capita vs. number of undernourished people.</p>
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<p>(<b>a</b>) Current health expenditure per capita vs. prevalence of anemia among children. (<b>b</b>) Current health expenditure as a percentage of gross domestic product (GDP%) vs. prevalence of hypertension among adults.</p>
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<p>Number of rural population vs. prevalence of undernourishment.</p>
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<p>(<b>a</b>) Dry matter and (<b>b</b>) crude ash content in baobab leaves from six different areas in Sudan. Different letters indicate statistically significant differences (<span class="html-italic">p</span> ≤ 0.05). Study areas: Khor Tagat (KR1), Kazgil (KR2), Jabal Kordofan (KR3), Er Roseires (BN1), Abu Hashim (BN2), and El Gari (BN3).</p>
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<p>(<b>a</b>) Crude fat and (<b>b</b>) crude protein content in baobab leaves from six different areas in Sudan. Different letters indicate statistically significant differences (<span class="html-italic">p</span> ≤ 0.05). Study areas: Khor Tagat (KR1), Kazgil (KR2), Jabal Kordofan (KR3), Er Roseires (BN1), Abu Hashim (BN2), and El Gari (BN3).</p>
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<p>pH values of baobab leaves from six different areas in Sudan. Different letters indicate statistically significant differences (<span class="html-italic">p</span> ≤ 0.05). Study areas: Khor Tagat (KR1), Kazgil (KR2), Jabal Kordofan (KR3), Er Roseires (BN1), Abu Hashim (BN2), and El Gari (BN3).</p>
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<p>(<b>a</b>) Calcium and (<b>b</b>) potassium content in baobab leaves from six different areas in Sudan. Different letters indicate statistically significant differences (<span class="html-italic">p</span> ≤ 0.05). Study areas: Khor Tagat (KR1), Kazgil (KR2), Jabal Kordofan (KR3), Er Roseires (BN1), Abu Hashim (BN2), and El Gari (BN3).</p>
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<p>(<b>a</b>) Magnesium and (<b>b</b>) sodium content in baobab leaves from six different areas in Sudan. Different letters indicate statistically significant differences (<span class="html-italic">p</span> ≤ 0.05). Study areas: Khor Tagat (KR1), Kazgil (KR2), Jabal Kordofan (KR3), Er Roseires (BN1), Abu Hashim (BN2), and El Gari (BN3).</p>
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<p>(<b>a</b>) Iron and (<b>b</b>) manganese content in baobab leaves from six different areas in Sudan. Different letters indicate statistically significant differences (<span class="html-italic">p</span> ≤ 0.05). Study areas: Khor Tagat (KR1), Kazgil (KR2), Jabal Kordofan (KR3), Er Roseires (BN1), Abu Hashim (BN2), and El Gari (BN3).</p>
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<p>(<b>a</b>) TPC (total polyphenols content) and (<b>b</b>) TFC (total flavonoid content) in baobab leaves from six different areas in Sudan. Different letters indicate statistically significant differences (<span class="html-italic">p</span> ≤ 0.05). Study areas: Khor Tagat (KR1), Kazgil (KR2), Jabal Kordofan (KR3), Er Roseires (BN1), Abu Hashim (BN2), and El Gari (BN3).</p>
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<p>Protocol steps for implementing nutritional intervention using baobab leaves (BLs).</p>
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20 pages, 5713 KiB  
Article
A Comparison of the Sensitivity and Cellular Detection Capabilities of Magnetic Particle Imaging and Bioluminescence Imaging
by Sophia Trozzo, Bijita Neupane and Paula J. Foster
Tomography 2024, 10(11), 1846-1866; https://doi.org/10.3390/tomography10110135 - 20 Nov 2024
Viewed by 941
Abstract
Background: Preclinical cell tracking is enhanced with a multimodal imaging approach. Bioluminescence imaging (BLI) is a highly sensitive optical modality that relies on engineering cells to constitutively express a luciferase gene. Magnetic particle imaging (MPI) is a newer imaging modality that directly detects [...] Read more.
Background: Preclinical cell tracking is enhanced with a multimodal imaging approach. Bioluminescence imaging (BLI) is a highly sensitive optical modality that relies on engineering cells to constitutively express a luciferase gene. Magnetic particle imaging (MPI) is a newer imaging modality that directly detects superparamagnetic iron oxide (SPIO) particles used to label cells. Here, we compare BLI and MPI for imaging cells in vitro and in vivo. Methods: Mouse 4T1 breast carcinoma cells were transduced to express firefly luciferase, labeled with SPIO (ProMag), and imaged as cell samples after subcutaneous injection into mice. Results: For cell samples, the BLI and MPI signals were strongly correlated with cell number. Both modalities presented limitations for imaging cells in vivo. For BLI, weak signal penetration, signal attenuation, and scattering prevented the detection of cells for mice with hair and for cells far from the tissue surface. For MPI, background signals obscured the detection of low cell numbers due to the limited dynamic range, and cell numbers could not be accurately quantified from in vivo images. Conclusions: It is important to understand the shortcomings of these imaging modalities to develop strategies to improve cellular detection sensitivity. Full article
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<p>Characterization of 4T1 luc GFP+ cell transduction and ProMag-labeling: (<b>A</b>) A flow cytometry histogram comparing GFP fluorescence for an untransduced 4T1 cell population (grey) and a transduced 4T1 luc GFP+ cell population (blue). A sort gate was created to select the transduced cells based on GFP fluorescent intensity (green). (<b>B</b>) A second flow cytometry histogram showing GFP fluorescence for viable (Sytox blue negative) 4T1 luc GFP+ cells. (<b>C</b>) A fluorescent image of sorted 4T1 luc GFP+ cells in culture visually confirms GFP expression (scale bar = 100 μm). (<b>D</b>) A Perls’ Prussian blue stained image of ProMag-labeled 4T1 luc GFP+ cells shows minimal extracellular iron and high iron-labeling efficiency (scale bar = 100 μm). (<b>E</b>) Representative BLI images on day 1 and day 5 post-iron loading of 4T1 cells in a 24-well plate. (<b>F</b>) The corresponding radiance measurements for each sample revealed no significant differences between labeled and unlabeled cells up to 5 days post iron loading (ns = non-significant).</p>
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<p>Characterization of ProMag: (<b>A</b>) A relaxometry curve generated by normalizing MPI signal (A.U.) to iron mass (μg) to measure ProMag sensitivity. (<b>B</b>) A second relaxometry curve to measure ProMag resolution. MPI signal was normalized to iron mass and maximum MPI signal. (<b>C</b>) A calibration line showing the linear relationship between iron mass and total MPI signal (R<sup>2</sup> = 0.9802, <span class="html-italic">p</span> &lt; 0.0001). (<b>D</b>) Corresponding images of ProMag samples used to generate the calibration line, displayed in full dynamic range. Note the differences in scale.</p>
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<p>In vitro BLI cell detection: (<b>A</b>) Representative images showing detectable BLI signal for all cell samples from 51,200 to 3200 cells and (<b>B</b>) 1600 to 100 cells. (<b>C</b>) A linear regression showing cell number versus radiance measurements for samples from 51,200 to 3200 cells (R<sup>2</sup> = 0.9787). (<b>D</b>) A linear regression showing cell number versus radiance measurements for samples from 1600 to 100 cells (R<sup>2</sup> = 0.9802). Radiance measurements showed a significant linear and positive correlation with increasing cell number for all samples (<span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>In vitro MPI cell detection: (<b>A</b>) Representative 2D and 3D MPI images of all cell samples that could be detected and quantified. A red “x” is placed over the 2D image of 1600 cells that could not be accurately quantified due to image noise. (<b>B</b>) A linear regression comparing cell number versus total 2D MPI signal (A.U.) for samples of 51,200 to 3200 cells. The total 2D MPI signal showed a significant linear and positive correlation with increasing cell number (R<sup>2</sup> = 0.9940, <span class="html-italic">p</span> &lt; 0.0001). (<b>C</b>) Iron content was calculated for each cell sample that could be quantified in 2D. There was a significant positive and linear correlation between cell number and iron content (R<sup>2</sup> = 0.9940, <span class="html-italic">p</span> &lt; 0.0001). (<b>D</b>) Using the iron content measurements for each sample, the cell number was calculated and compared with the actual cell number. There was no significant difference between the mean calculated cell number and the actual cell number for each group of samples as determined by Student’s <span class="html-italic">t</span>-tests (ns = non-significant). (<b>E</b>) A chart was generated to visualize the % differences between the average calculated cell number and the actual cell number for each group of samples. The largest difference was observed for the 12,800-sample group (14.1%), and the smallest difference was observed for the 6400-cell group (4.70%).</p>
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<p>Correlation plot comparing total MPI signal (x-axis) and radiance (y-axis) measurements for cell samples between 51,200 and 3200 cells. Each point represents an individual sample (a total of 15 samples). There is a strong linear correlation between MPI and BLI signals for in vitro samples (R<sup>2</sup> = 0.9904, <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Comparing in vivo cell detection in nu/nu mice: (<b>A</b>) 2D full FOV MPI cannot detect signal from 6400 cells. Note the impeding gastrointestinal signal that is labeled “gut”. (<b>B</b>) A BLI image of the same mouse showing detectable signal from the 6400-cell injection. This image shows BLI signal overlayed with X-ray. (<b>C</b>) 2D full FOV MPI could detect signals from 12,800 cells with impeding gut signals (labeled). (<b>D</b>) BLI signal was detected in the same mouse.</p>
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<p>BLI cell detection in vivo for mice before versus after hair removal: (<b>A</b>) BLI signal is observed in the white mouse with hair. (<b>B</b>) Hair removal reveals an immediate increase in signal. (<b>C</b>) The signal continued to increase after hair removal. (<b>D</b>) Complete signal attenuation was observed for a C57Bl/6 mouse imaged with black hair. (<b>E</b>) BLI signal was observed with hair removal and (<b>F</b>) continued to increase until reaching peak radiance.</p>
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<p>In vivo cell detection and sensitivity with prone and supine imaging for BLI and MPI: (<b>A</b>) In the prone position, signal is detected from 12,800 cells in the nude mouse. (<b>B</b>) This signal is completely attenuated when the mouse is imaged supine (depth of cell injection site = 2.5 cm). A Balb/c mouse containing 12,800 cells had a similar MPI signal when imaged in (<b>C</b>) prone and (<b>D</b>) supine.</p>
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<p>MPI images of triplicate 500,000 cell samples used to calculate the average iron loading per cell.</p>
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<p>MPI image of C57Bl/6 mouse injected with 12,800 cells. The mouse was imaged with a full FOV in the prone position. The MPI signal (181 A.U.), iron content (0.113 μg), and cell number (6962 cells) were quantified for this mouse.</p>
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20 pages, 17929 KiB  
Article
Experimental Identification of a New Secondary Wave Pattern in Transonic Cascades with Porous Walls
by Valeriu Drăgan, Oana Dumitrescu, Mihnea Gall, Emilia Georgiana Prisăcariu and Bogdan Gherman
Aerospace 2024, 11(11), 946; https://doi.org/10.3390/aerospace11110946 - 16 Nov 2024
Viewed by 496
Abstract
Turbomachinery shock wave patterns occur as a natural result of operating at off-design points and are accountable for some of the loss in performance. In some cases, shock wave–boundary layer (SW-BLIs) interactions may even lead to map restrictions. The current paper refers to [...] Read more.
Turbomachinery shock wave patterns occur as a natural result of operating at off-design points and are accountable for some of the loss in performance. In some cases, shock wave–boundary layer (SW-BLIs) interactions may even lead to map restrictions. The current paper refers to experimental findings on a transonic linear cascade specifically designed to mitigate shock waves using porous walls on the blades. Schlieren visualization reveals two phenomena: Firstly, the shock waves were dissipated in all bladed passages, as predicted by the CFD studies. Secondly, a lower-pressure wave pattern was observed upstream of the blades. It is this phenomenon that the paper reports and attempts to describe. Attempts to replicate this pattern using Reynolds-averaged Navier–Stokes (RANS) calculations indicate that the numerical method may be too dissipative to accurately capture it. The experimental campaign demonstrated a 4% increase in flow rate, accompanied by minimal variations in pressure and temperature, highlighting the potential of this approach for enhancing turbomachinery performance. Full article
(This article belongs to the Section Aeronautics)
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<p>Vanes after surface finishing: (<b>a</b>) porous walls; (<b>b</b>) reference case, with no flow control.</p>
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<p>Linear cascade facility overview.</p>
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<p>P&amp;ID diagram for linear cascade facility.</p>
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<p>Schlieren system for flow visualization with knife edge.</p>
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<p>Mesh convergence study.</p>
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<p>Linear cascade computational grid with channel details. (<b>a</b>) test area; (<b>b</b>) zoomed-in view of the second channel.</p>
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<p>Computational grid, with blade details: (<b>a</b>) leading edge; (<b>b</b>) trailing edge.</p>
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<p>Distribution of the dimensionless distance to the wall (y+): (<b>a</b>) vanes surface; (<b>b</b>) perforated plate.</p>
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<p>Computational domain and boundary conditions.</p>
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<p>Schlieren images: (<b>a</b>) no control and no filter, with knife edge [<a href="#B28-aerospace-11-00946" class="html-bibr">28</a>]; (<b>b</b>) passive control and gradual color filter (upper corner, right). Inlet static pressure of 70,000 Pa gauge.</p>
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<p>Schlieren images: (<b>a</b>) no control and no filter, with knife edge [<a href="#B28-aerospace-11-00946" class="html-bibr">28</a>]; (<b>b</b>) passive control and color filter. Inlet static pressure of 80,000 Pa gauge.</p>
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<p>Schlieren images: (<b>a</b>) no control and no filter [<a href="#B28-aerospace-11-00946" class="html-bibr">28</a>]; (<b>b</b>) passive control. Inlet static pressure of 90,000 Pa gauge.</p>
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<p>Pressure distribution in the linear cascade, median plane: (<b>a</b>) no control [<a href="#B28-aerospace-11-00946" class="html-bibr">28</a>]; (<b>b</b>) passive control.</p>
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<p>Density gradient distribution, median plane: (<b>a</b>) no control [<a href="#B28-aerospace-11-00946" class="html-bibr">28</a>]; (<b>b</b>) passive control.</p>
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<p>Velocity vectors in Channel 3 of the linear cascade: (<b>a</b>) Channel 3 top view; (<b>b</b>) perforated plate and cavity detail.</p>
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<p>Reference lines, upstream and downstream of the test area.</p>
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<p>Pressure profile along the mid-height measurement line upstream and downstream of the blades, with a 0.013 m distance.</p>
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<p>Velocity profile along the mid-height measurement line upstream and downstream of the blades, with a 0.013 m distance.</p>
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<p>Effect of passive control on key operating parameters: (<b>a</b>) mass flow rate, (<b>b</b>) total inlet temperature variation, and (<b>c</b>) inlet static pressure variation.</p>
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<p>Influence of porous wall on overall flow rate and flow structure: (<b>a</b>) no control; (<b>b</b>) passive control.</p>
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<p>Impact of passive control on the splitter: (<b>a</b>) first splitter with passive control; (<b>b</b>) second splitter no control.</p>
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<p>Influence of passive control on the main blade: (<b>a</b>) second main blade with passive control; (<b>b</b>) first main blade with no control.</p>
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13 pages, 264 KiB  
Review
Differences in Patient Access to Newly Approved Antibacterial Drugs in EU/EEA Countries
by Anelia Zasheva, Elina Batcheva, Kremena Dimitrova Ivanova and Antoniya Yanakieva
Antibiotics 2024, 13(11), 1077; https://doi.org/10.3390/antibiotics13111077 - 12 Nov 2024
Viewed by 1276
Abstract
The introduction of antibiotics in the beginning of the 20th century was one of the most important scientific breakthroughs in history. However, in recent decades, the growing threat of antimicrobial resistance (AMR) has shown the limitations of the current research and development programs [...] Read more.
The introduction of antibiotics in the beginning of the 20th century was one of the most important scientific breakthroughs in history. However, in recent decades, the growing threat of antimicrobial resistance (AMR) has shown the limitations of the current research and development programs for new antimicrobial drugs. In the last decade, 20 antibiotics, 7 β-lactam/β-lactamase inhibitor (BL/BLI) combinations and 4 non-traditional antibacterial drugs have been launched worldwide. Methods: This study aimed to assess the time to patient access for new antibacterial drugs in countries in the European Union and the European Economic Area (EU/EEA). Time differences in marketing authorization from the U.S. Food and Drug Agency (FDA) and the European Medicines Agency (EMA) were also described, as well as the availability of each drug in the countries in the EU/EEA according to the national competent authorities. Results: Substantial differences between countries were observed, with no or only one new drug available in some countries. Conclusions: Improving pricing and reimbursement timelines and fostering collaboration between national health authorities and market authorization holders can enhance timely and equitable patient access to new antibacterial treatments in Europe. Equitable and sustainable access to antibacterial drugs is a cornerstone in the battle against AMR. Full article
(This article belongs to the Section The Global Need for Effective Antibiotics)
11 pages, 1209 KiB  
Article
Efficacy of Streptococcus salivarius Blis K12 in the Prevention of Upper Respiratory Tract Infections in Physically Active Individuals: A Randomized Controlled Trial
by Alexander Bertuccioli, Marco Cardinali, Matteo Micucci, Marco Bruno Luigi Rocchi, Chiara Maria Palazzi, Giordano Bruno Zonzini, Giosuè Annibalini, Annalisa Belli and Davide Sisti
Microorganisms 2024, 12(11), 2164; https://doi.org/10.3390/microorganisms12112164 - 26 Oct 2024
Viewed by 1866
Abstract
This study investigates the efficacy of Streptococcus salivarius K12 in preventing upper respiratory tract infections (URTIs) in healthy adults. URTIs are a common issue, particularly in physically active individuals, leading to significant disruptions in daily life. Probiotics, such as S. salivarius K12, have [...] Read more.
This study investigates the efficacy of Streptococcus salivarius K12 in preventing upper respiratory tract infections (URTIs) in healthy adults. URTIs are a common issue, particularly in physically active individuals, leading to significant disruptions in daily life. Probiotics, such as S. salivarius K12, have emerged as a potential preventive strategy for these infections. This research was conducted as a randomized, double-blind, placebo-controlled trial involving 112 participants aged between 19 and 25. Participants were randomly divided into two groups: one group received a daily dose of S. salivarius K12, marketed as Bactoblis®, while the other received a placebo. The trial lasted for four months, during which adherence to the treatment protocol was closely monitored. The primary goal was to measure the incidence of URTIs using the Jackson Scale and the Wisconsin Upper Respiratory Symptom Survey (WURSS-11). The results indicated that higher adherence to the S. salivarius K12 treatment was associated with an increased number of days without URTI symptoms. Although the overall severity of symptoms did not differ significantly between the treatment and control groups, those with high adherence to S. salivarius K12 (greater than 90%) reported more days free from illness. In conclusion, S. salivarius K12 demonstrated potential as a preventive measure against URTIs, especially in individuals who adhered strictly to the treatment regimen. However, further research involving larger populations and longer follow-up periods is needed to fully confirm these findings and better understand the role of S. salivarius K12 in preventing respiratory infections. Full article
(This article belongs to the Section Medical Microbiology)
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<p>Flow diagram of the study.</p>
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<p>Violin plot of adherence of experimental groups (control and treated).</p>
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<p>Box plot of URTI-free days of control and treated groups.</p>
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<p>Statistics for the proportion of days free from illness across different adherence levels and treatment conditions.</p>
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12 pages, 1364 KiB  
Article
Protein A-like Peptide Design Based on Diffusion and ESM2 Models
by Long Zhao, Qiang He, Huijia Song, Tianqian Zhou, An Luo, Zhenguo Wen, Teng Wang and Xiaozhu Lin
Molecules 2024, 29(20), 4965; https://doi.org/10.3390/molecules29204965 - 21 Oct 2024
Viewed by 1425
Abstract
Proteins are the foundation of life, and designing functional proteins remains a key challenge in biotechnology. Before the development of AlphaFold2, the focus of design was primarily on structure-centric approaches such as using the well-known open-source software Rosetta3. Following the development of AlphaFold2, [...] Read more.
Proteins are the foundation of life, and designing functional proteins remains a key challenge in biotechnology. Before the development of AlphaFold2, the focus of design was primarily on structure-centric approaches such as using the well-known open-source software Rosetta3. Following the development of AlphaFold2, deep-learning techniques for protein design gained prominence. This study proposes a new method to generate functional proteins using the diffusion model and ESM2 protein language model. Diffusion models, which are widely used in image and natural language generation, are used here for protein design, facilitating the controlled generation of new sequences. The ESM2 model, trained on the basis of large-scale protein sequence data, provides a deep understanding of the context of the sequence, thus improving the model’s ability to generate biologically relevant proteins. In this study, we used the Protein A-like peptide as a model study object, combined the diffusion model and the ESM2 model to generate new peptide sequences from minimal input data, and verified their biological activities through experiments such as the BLI affinity test. In conclusion, we developed a new method for protein design that provides a novel strategy to meet the challenges of generic protein generation. Full article
(This article belongs to the Special Issue Computational Insights into Protein Engineering and Molecular Design)
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<p>Tertiary structure of Protein A (PA) and the newly generated protein sequences Z1–Z4. Z5, Z6, and Z7 are from the ESMIF, proteinMPNN, and RfDiffusion models, respectively. Using AlphaFold2 to predict the tertiary structure of proteins, we display the tertiary structure of the protein using PyMOL for the resulting PDB files and perform alignment operations.</p>
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<p>DDPM model. The image illustrates the forward and reverse processes in a diffusion model. The forward process adds Gaussian noise <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="sans-serif">β</mi> <mi>t</mi> </msub> </mrow> </semantics></math> to the data, the formula describes the diffusion process from <math display="inline"><semantics> <mrow> <msub> <mi>X</mi> <mrow> <mi>t</mi> <mo>−</mo> <mn>1</mn> </mrow> </msub> </mrow> </semantics></math> to reach <math display="inline"><semantics> <mrow> <msub> <mi>X</mi> <mi>t</mi> </msub> </mrow> </semantics></math>, where <math display="inline"><semantics> <mrow> <msub> <mi>X</mi> <mi>t</mi> </msub> </mrow> </semantics></math> is a Gaussian distribution given <math display="inline"><semantics> <mrow> <msub> <mi>X</mi> <mrow> <mi>t</mi> <mo>−</mo> <mn>1</mn> </mrow> </msub> </mrow> </semantics></math>. Its mean is <math display="inline"><semantics> <mrow> <msub> <mi>X</mi> <mrow> <mi>t</mi> <mo>−</mo> <mn>1</mn> </mrow> </msub> </mrow> </semantics></math> multiplied by the coefficient <math display="inline"><semantics> <mrow> <msqrt> <mrow> <mn>1</mn> <mo>−</mo> <msub> <mi mathvariant="sans-serif">β</mi> <mi>t</mi> </msub> </mrow> </msqrt> </mrow> </semantics></math>, and its variance is <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="sans-serif">β</mi> <mi>t</mi> </msub> <mo> </mo> <mi>I</mi> </mrow> </semantics></math>, where <span class="html-italic">I</span> is the identity matrix. The reverse process aims to denoise and reconstruct the original data. The formula at the bottom describes the generation process, that is, from <math display="inline"><semantics> <mrow> <msub> <mi>X</mi> <mi>t</mi> </msub> </mrow> </semantics></math> to <math display="inline"><semantics> <mrow> <msub> <mi>X</mi> <mrow> <mi>t</mi> <mo>−</mo> <mn>1</mn> </mrow> </msub> </mrow> </semantics></math>. <math display="inline"><semantics> <mrow> <msub> <mi>X</mi> <mrow> <mi>t</mi> <mo>−</mo> <mn>1</mn> </mrow> </msub> </mrow> </semantics></math> follows a Gaussian distribution with a mean of <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="sans-serif">μ</mi> <mi mathvariant="sans-serif">θ</mi> </msub> <mfenced> <mrow> <msub> <mi>X</mi> <mi>t</mi> </msub> <mo>,</mo> <mi>t</mi> </mrow> </mfenced> </mrow> </semantics></math> calculated by a neural network (parameter <math display="inline"><semantics> <mi mathvariant="sans-serif">θ</mi> </semantics></math>) and a variance of <math display="inline"><semantics> <mrow> <msubsup> <mi mathvariant="sans-serif">σ</mi> <mi>t</mi> <mn>2</mn> </msubsup> <mo> </mo> </mrow> </semantics></math><span class="html-italic">I</span>.</p>
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<p>The process of encoding a protein into an image. Protein sequences are transformed into grayscale images by representing amino acids with one-hot encoded binary vectors, enabling their use in image-based analysis and machine learning models.</p>
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<p>Methodology model structure. (<b>A</b>) is the VAE structure, and (<b>B</b>) is the Transformer and ESM2 structure. (<b>A</b>) This panel demonstrates a variational autoencoder structure where the input sequence is encoded into a latent space with mean (μ) and standard deviation (σ) parameters, which are then sampled to generate new sequences via the decoder. (<b>B</b>) The bottom left panel showcases a sequence-to-sequence model with attention, where an encoder processes a protein sequence, and a decoder reconstructs the input sequence, leveraging multi-head attention mechanisms to enhance feature extraction.</p>
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17 pages, 6607 KiB  
Article
Evaluation of the Role of Tanshinone I in an In Vitro System of Charcot-Marie-Tooth Disease Type 2N
by Jingjing Zhang, Xinru Meng, Qianni Qin, Yali Liang, Guangpu Yang, Shen Li, Xiaorong Li, Ji-Chang Zhou and Litao Sun
Int. J. Mol. Sci. 2024, 25(20), 11184; https://doi.org/10.3390/ijms252011184 - 17 Oct 2024
Viewed by 1030
Abstract
Charcot-Marie-Tooth disease type 2N (CMT2N) is an inherited nerve disorder caused by mutations in the alanyl-tRNA synthetase (AlaRS) gene, resulting in muscle weakness and sensory issues. Currently, there is no cure for CMT2N. Here, we found that all five AlaRS mutations in the [...] Read more.
Charcot-Marie-Tooth disease type 2N (CMT2N) is an inherited nerve disorder caused by mutations in the alanyl-tRNA synthetase (AlaRS) gene, resulting in muscle weakness and sensory issues. Currently, there is no cure for CMT2N. Here, we found that all five AlaRS mutations in the aminoacylation domain can interact with neuropilin-1 (Nrp1), which is consistent with our previous findings. Interestingly, three of these mutations did not affect alanine activation activity. We then performed a high-throughput screen of 2000 small molecules targeting the prevalent R329H mutant. Using thermal stability assays (TSA), biolayer interferometry (BLI), ATP consumption, and proteolysis assays, we identified Tanshinone I as a compound that binds to and modifies the conformation of the R329H mutant and other CMT-related AlaRS mutants interacting with Nrp1. Molecular docking and dynamic simulation studies further clarified Tanshinone I’s binding mode, indicating its potential against various AlaRS mutants. Furthermore, co-immunoprecipitation (Co-IP) and pull-down assays showed that Tanshinone I significantly reduces the binding of AlaRS mutants to Nrp1. Collectively, these findings suggest that Tanshinone I, by altering the conformation of mutant proteins, disrupts the pathological interaction between AlaRS CMT mutants and Nrp1, potentially restoring normal Nrp1 function. This makes Tanshinone I a promising therapeutic candidate for CMT2N. Full article
(This article belongs to the Section Biochemistry)
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Figure 1

Figure 1
<p>Distribution of CMT-causing mutations on AlaRS and abnormal interactions with Nrp1. (<b>A</b>) Distribution of CMT-causing mutations on AlaRS. Ten CMT2N-associated dominant mutations distributed across all three domains of human cytosolic AlaRS. Structure model of AlaRS generated by Alphafold. CMT mutation sites are indicated by colored balls in the aminoacylation domain and black balls in the editing domain and C-Ala domain. (<b>B</b>) Enzymatic activity of AlaRS proteins measured by ATP assumption assay with purified enzymes, Alanine, and ATP. The reaction was negatively controlled with Alanine and ATP alone (no enzyme). Data are presented as mean ± SD (n = 2). (<b>C</b>) Nrp1-AlaRS interaction was detected by coimmunoprecipitation analysis using anti-HA antibody. AlaRS (WT or CMT2N mutants) was expressed in NSC34 cells with a HA tag detected by an anti-HA antibody. Nrp1 was expressed with a Flag tag detected by an anti-Flag antibody.</p>
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<p>Drug screening based on TSA assay. (<b>A</b>) Screening for molecules binding to aminoacylation domain of AlaRS<sup>R329H</sup> based on the thermal shift assay. A total of four compounds shifted the melting temperature of AlaRS<sup>R329H</sup> by &gt;2.5 °C and were considered positive hits among the 2000 tested compounds. Black points represent negative hits. (<b>B</b>) The interaction analysis of AlaRS<sup>R329H</sup> and four positive compounds by TSA. The Tm of AlaRS<sup>R329H</sup> was approximately 47.5 °C and a shift &gt;2.5 °C was observed in the Tm with Atazanavir sulfate, Tanshinone I, Hederacolchiside A1, and Hexylresorcinol.</p>
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<p>BLI and ATP consumption assays for the four small molecules. Binding sensorgrams for the interaction of Atazanavir sulfate (<b>A</b>), Tanshinone I (<b>B</b>), Hederacolchiside A1 (<b>C</b>), and Hexylresorcinol (<b>D</b>) with immobilized AlaRS<sup>R329H</sup>. Each sensorgram contains five curves generated from 40, 20, 10, 5, and 2.5 μM concentrations. The K<sub>D</sub> values are presented as the mean ± SD and experiments were performed in triplicate. (<b>E</b>) The inhibitory effects of the four positive hits were compared with the DMSO control (n = 3). The average relative enzyme activity calculated from three experiments is labelled above the bar graph. An analysis of variance (ANOVA) was conducted to compare the effects of different compounds on relative enzyme activity, followed by post-hoc analyses (Tukey’s test) to account for differences between the treatment groups. ****: <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Proteolytic digestion assay of AlaRS<sup>R329H</sup> with four small molecules. The AlaRS<sup>R329H</sup> proteins (in the presence and absence of Atazanavir sulfate, Tanshinone I, Hederacolchiside A1, and Hexylresorcinol) were incubated with trypsin at different concentrations for 3 h before the reactions were quenched, and the products were separated by SDS-PAGE. The addition of Tanshinone I resulted in a significant change in the distribution of the bands at the indicated position.</p>
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<p>BLI and proteolytic digestion assay of AlaRS mutants with Tanshinone I. Binding sensorgrams for the interaction of Tanshinone I with immobilized AlaRS<sup>R329H</sup> (<b>A</b>), AlaRS<sup>G102R</sup> (<b>C</b>), AlaRS<sup>R326W</sup> (<b>E</b>), and AlaRS<sup>E337K</sup> (<b>G</b>). Each sensorgram contains five curves generated from five different concentrations. The K<sub>D</sub> values are presented as the mean ± SD and experiments were performed in triplicate. The AlaRS<sup>N71Y</sup> (<b>B</b>), AlaRS<sup>G102R</sup> (<b>D</b>), AlaRS<sup>R326W</sup> (<b>F</b>), and AlaRS<sup>E337K</sup> (<b>H</b>) proteins (in the presence and absence of Tanshinone I) were incubated with trypsin at different concentrations for three hours before the reactions were quenched, and the products were separated by SDS-PAGE.</p>
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<p>Molecular docking and dynamic simulations of Tanshinone I with AlaRS Mutants. (<b>A</b>) The molecular docking model of AlaRS mutants and Tanshinone I was generated by Autodock Vina v.1.2.2. The two-dimensional images were generated and adjusted using Schrödinger’s LigPrep module (Release 2019-2, Schrödinger LLC, New York, NY, USA, 2019) [<a href="#B23-ijms-25-11184" class="html-bibr">23</a>]. (<b>B</b>) Molecular dynamics (MD) simulations of the AlaRS mutant/Tanshinone I complex were conducted for 100 ns, followed by root-mean-square deviation (RMSD) analysis. (<b>C</b>) The MD simulation (RMSF analysis) of the AlaRS mutant/Tanshinone I complex for 100 ns.</p>
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<p>The impact of Tanshinone I on the interaction between AlaRS mutants and Nrp1. (<b>A</b>) Co-IP assays were conducted to assess the binding between HA-AlaRS mutants and Nrp1, both with and without treatment with 20 µM Tanshinone I for 24 h. (<b>B</b>) Relative quantification of the AlaRS mutants immunoprecipitated from the Co-IP experiments post-Tanshinone I treatment was performed using ImageJ, with the averages from three experimental repeats displayed in the figure. (<b>C</b>) Pull down assay was performed to detect the binding between AlaRS mutants and GST-Nrp1 b1 with or without 20 µM Tanshinone I. (<b>D</b>) Relative quantification statistics of the AlaRS mutants pulled down from the GST pull down experiments after Tanshinone I treatment were performed using ImageJ. The averages of the three experimental repeats are presented in the figure. (<b>E</b>) The cell viability of 293T and NSC34 cells treated with different concentrations of Tanshinone I was assessed using the CCK-8 assay over a 24 h period.</p>
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<p>Tanshinone I as a therapeutic candidate for CMT2N via the targeting of AlaRS CMT mutant proteins. The abnormal binding between AlaRS CMT mutants and Nrp1 inhibits the interaction between Nrp1 and its receptor, thereby suppressing the subsequent signaling response. Our screened compound, Tanshinone I, binds to AlaRS CMT mutants, alters their conformation, and inhibits the abnormal binding to Nrp1, thereby allowing Nrp1 to perform its function.</p>
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23 pages, 3476 KiB  
Article
Exploring a Potential Optimization Route for Peptide Ligands of the Sam Domain from the Lipid Phosphatase Ship2
by Marian Vincenzi, Flavia Anna Mercurio, Sara La Manna, Rosanna Palumbo, Luciano Pirone, Daniela Marasco, Emilia Maria Pedone and Marilisa Leone
Int. J. Mol. Sci. 2024, 25(19), 10616; https://doi.org/10.3390/ijms251910616 - 2 Oct 2024
Viewed by 729
Abstract
The Sam (Sterile alpha motif) domain of the lipid phosphatase Ship2 (Ship2-Sam) is engaged by the Sam domain of the receptor tyrosine kinase EphA2 (EphA2-Sam) and, this interaction is principally linked to procancer effects. Peptides able to hinder the formation of the EphA2-Sam/Ship2-Sam [...] Read more.
The Sam (Sterile alpha motif) domain of the lipid phosphatase Ship2 (Ship2-Sam) is engaged by the Sam domain of the receptor tyrosine kinase EphA2 (EphA2-Sam) and, this interaction is principally linked to procancer effects. Peptides able to hinder the formation of the EphA2-Sam/Ship2-Sam complex could possess therapeutic potential. Herein, by employing the FoldX software suite, we set up an in silico approach to improve the peptide targeting of the so-called Mid Loop interface of Ship2-Sam, representing the EphA2-Sam binding site. Starting from a formerly identified peptide antagonist of the EphA2-Sam/Ship2-Sam association, first, the most stabilizing mutations that could be inserted in each peptide position were predicted. Then, they were combined, producing a list of potentially enhanced Ship2-Sam ligands. A few of the in silico generated peptides were experimentally evaluated. Interaction assays with Ship2-Sam were performed using NMR and BLI (BioLayer Interferometry). In vitro assays were conducted as well to check for cytotoxic effects against both cancerous and healthy cells, and also to assess the capacity to regulate EphA2 degradation. This study undoubtedly enlarges our knowledge on how to properly target EphA2-Sam/Ship2-Sam associations with peptide-based tools and provides a promising strategy that can be used to target any protein–protein interaction. Full article
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<p>(<b>a</b>) The EphA2-Sam (gray)/Ship2-Sam (magenta) hetero-dimer. The EphA2-Sam EH interface (regions P58-Y66 and I22-M24 from the chain A of the PDB entry code 2KSO [<a href="#B9-ijms-25-10616" class="html-bibr">9</a>]) and the Ship2-Sam ML interface (segment H47-E66 from the chain B of the PDB entry code 2KSO) are colored orange and white, respectively. The side chains of aromatic, positively, and negatively charged residues present at the Sam–Sam EH/ML interface are shown in dark green, blue, and red, respectively. Residues G59 (EphA2-Sam) and N48 (Ship2-Sam) involved in the Sam–Sam characteristic H-bond (G59 <sub>N</sub>H/N48 O [<a href="#B14-ijms-25-10616" class="html-bibr">14</a>]) are colored in cyan and highlighted by a connecting dashed line. The inset shows the position of the KRIAY motif (green) within the EH interface of EphA2-Sam. (<b>b</b>) The docking model of the Ship2-Sam/KRI3 peptide complex [<a href="#B32-ijms-25-10616" class="html-bibr">32</a>]. The color code used for Ship2-Sam, aromatic, positively charged, and negatively charged residues is the same as that in panel (<b>a</b>). KRI3 is shown in a light green ribbon representation, with the side chains of Lys (blue), Arg (blue), and Tyr (dark green) reported in a neon representation.</p>
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<p>In silico design of peptide sequences through the different macros of FoldX (v. 5) [<a href="#B29-ijms-25-10616" class="html-bibr">29</a>]; the peptide selection strategy and the experimental in vitro evaluation protocol are also indicated.</p>
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<p>NMR solution structures in PBS/TFE (50/50—<span class="html-italic">v</span>/<span class="html-italic">v</span>) of (<b>a</b>) PSscan255; (<b>b</b>) PSscan258; and (<b>c</b>) PSscan266 peptides. (<b>a</b>–<b>c</b>) Representative NMR conformers are reported in the left panels in ribbon drawings, whereas superpositions on the backbone atoms of twenty structures are shown in the right panels. In the left panels, diverse charged and aromatic residues are evidenced in a neon representation with only heavy atoms. (<b>a</b>) PSscan255 conformers were calculated from 175 distance restraints (52 intra-residue, 53 short-, 70 medium-, and 0 long-range) and 81 angle constraints; (<b>b</b>) regarding PSscan258, 159 distance restraints (50 intra-residue, 57 short-, 52 medium-, and 0 long-range) along with 83 angle constraints were employed to derive the NMR structure; (<b>c</b>) the PSscan266 structure was calculated based on 177 distance restraints (74 intra-residue, 54 short-, 49 medium-, and 0 long-range) and 81 angle constraints.</p>
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<p>(<b>a</b>) Screening by 1D [<sup>1</sup>H] NMR. The expansion of aliphatic regions of 1D [<sup>1</sup>H] NMR spectra of Ship2-Sam in the apo form (27 µM concentration) (red) and in the presence of the different peptides (273 µM each). (<b>b</b>) Comparison of [<sup>1</sup>H-<sup>15</sup>N] HSQC spectra of Ship2-Sam (20 μM concentration) alone (red) and after the addition of the PSscan255 peptide (200 μM concentration) (blue). (<b>c</b>) Histogram showing chemical shift perturbations (CSPs) (i.e., Δδ = [(ΔH<sub>N</sub>)<sup>2</sup> + (0.17 × Δ<sup>15</sup>N<sub>H</sub>)<sup>2</sup>]<sup>1/2</sup>) [<a href="#B49-ijms-25-10616" class="html-bibr">49</a>] versus residue numbers for the interaction between Ship2-Sam and PSScan255. The Δδ value was set to be equal to zero for P72 as well as I36 and L53 as their peaks disappear in the spectrum of the peptide/protein complex (See “<span style="color:red">#</span>”). (<b>d</b>) Residues associated with the largest perturbations in chemical shifts (Δδ ≥ 0.025 ppm) or peak intensities (i.e., W32 (NHε1), L33, I36, E39, V46, H47, D51, L53, T60, T81) are highlighted in blue in the 3D solution structure of Ship2-Sam (conformer number 1, PDB entry code 2K4P [<a href="#B8-ijms-25-10616" class="html-bibr">8</a>]), which is displayed in the ribbon with a transparent surface drawing. (<b>e</b>) Average CSP (Δδ<sub>ave</sub>) values for control (CTRL) and PSscan255 peptides, which were evaluated for the entire Ship2-Sam sequence (“◊” residue range L24-K86), the ML interface (“□” protein segment H47-E66), and the region outside the ML (“○” residues L24-V46 and A67-K86). Peaks corresponding to backbone NH and side-chain NHε1 groups of W32 and W50 were included in the CSP evaluation.</p>
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<p>The 1D [<sup>1</sup>H] spectrum (HN/aromatic protons regions) of PSscan266 (100 µM concentration) in PBS/D<sub>2</sub>O (33/67—<span class="html-italic">v</span>/<span class="html-italic">v</span>) (black) is shown on the top. The overlay of 1D [<sup>1</sup>H] NMR spectra, recorded in PBS/D<sub>2</sub>O (90/10—<span class="html-italic">v</span>/<span class="html-italic">v</span>) of PSscan266 peptide at 50 µM (red) and 300 µM (blue) concentrations, is shown on the bottom. An expansion containing only peaks arising from aromatic protons is reported in the left inset. Peak intensities were adjusted to reach the same level in each spectrum.</p>
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<p>Docking results for the Ship2-Sam/PSscan255 peptide complex. In each panel, a different docking solution among the best 10—in terms of Haddock scores [<a href="#B50-ijms-25-10616" class="html-bibr">50</a>]—is shown. (<b>a</b>) 1st best model; (<b>b</b>) 3rd best model; (<b>c</b>) 5th best model; (<b>d</b>) 6th best model; (<b>e</b>) 10th best model. Each structure is reported in a ribbon representation: the ML region in Ship2-Sam (magenta) is colored white. The residues most affected by the binding of the peptide according to the NMR studies (i.e., W32 (NHε1), L33, I36, E39, V46, H47, D51, L53, T60, T81) are highlighted in black on the Ship2-Sam surface. The PSscan255 peptide is shown in an orange ribbon drawing. Different helices in Ship2-Sam are labeled.</p>
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<p>(<b>a</b>) The cytotoxic effect of PSscan255 peptide on PC-3 and NHDF cells was assessed through the crystal violet assay. Cells were treated with TAT-PSscan255 (50 μM and 100 μM concentrations for 4 h), and values were expressed as percentages relative to untreated cells. Each value represents an average ± SEM (Standard Error of Mean) of three separate experiments performed in quadruplicate. (<b>b</b>) EphA2 degradation in the prostatic cancer cell line. (Top) PC-3 cells were treated either with TAT-PSscan255 (50 μM for 4 h) and/or ephrinA1-Fc (1 μg/mL for 2 h). The β-actin antibody was employed for the comparison of protein loads. Characteristic data are presented (bottom). EphA2/β-actin ratios were normalized, assuming the EphA2 expression under the untreated condition as 1. Mean ± SEM, n = 3. One-way analysis of variance (ANOVA) using Dunnett’s post-test analysis was performed; ** <span class="html-italic">p</span>&lt; 0.01; *** <span class="html-italic">p</span>&lt; 0.001.</p>
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14 pages, 12752 KiB  
Article
Establishment of Translational Luciferase-Based Cancer Models to Evaluate Antitumoral Therapies
by Martin R. Ramos-Gonzalez, Nagabhishek Sirpu Natesh, Satyanarayana Rachagani, James Amos-Landgraf, Haval Shirwan, Esma S. Yolcu and Jorge G. Gomez-Gutierrez
Int. J. Mol. Sci. 2024, 25(19), 10418; https://doi.org/10.3390/ijms251910418 - 27 Sep 2024
Cited by 1 | Viewed by 1160
Abstract
Luciferase (luc) bioluminescence (BL) is the most used light-emitting protein that has been engineered to be expressed in multiple cancer cell lines, allowing for the detection of tumor nodules in vivo as it can penetrate most tissues. The goal of this study was [...] Read more.
Luciferase (luc) bioluminescence (BL) is the most used light-emitting protein that has been engineered to be expressed in multiple cancer cell lines, allowing for the detection of tumor nodules in vivo as it can penetrate most tissues. The goal of this study was to develop an oncolytic adenovirus (OAd)-resistant human triple-negative breast cancer (TNBC) that could express luciferase. Thus, when combining an OAd with chemotherapies or targeted therapies, we would be able to monitor the ability of these compounds to enhance OAd antitumor efficacy using BL in real time. The TNBC cell line HCC1937 was stably transfected with the plasmid pGL4.50[luc2/CMV/Hygro] (HCC1937/luc2). Once established, HCC1937/luc2 was orthotopically implanted in the 4th mammary gland fat pad of NSG (non-obese diabetic severe combined immunodeficiency disease gamma) female mice. Bioluminescence imaging (BLI) revealed that the HCC1937/luc2 cell line developed orthotopic breast tumor and lung metastasis over time. However, the integration of luc plasmid modified the HCC1937 phenotype, making HCC1937/luc2 more sensitive to OAdmCherry compared to the parental cell line and blunting the interferon (IFN) antiviral response. Testing two additional luc cell lines revealed that this was not a universal response; however, proper controls would need to be evaluated, as the integration of luciferase could affect the cells’ response to different treatments. Full article
(This article belongs to the Special Issue Advances in Luciferase)
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<p>HCC1937/luc2 TNBC tumors and metastatic nodules detected by BLI in vivo imaging. Images showing the intensity of BLI from tumors corresponding to 7 (<b>A</b>) and 14 days (<b>B</b>) post-inoculation. Photography and x-ray. (<b>C</b>) BLI quantification allows for an accurate tumor size comparison. (<b>D</b>) Detection of BLI from lung metastases in vivo and ex vivo (<b>E</b>) and their signal quantification confirming a positive correlation of the intensity observed (<b>F</b>). The graphs show 3 independent experiments (Mean ± SD, * <span class="html-italic">p</span> &lt; 0.05) for linear regression (r = Pearson correlation coefficient).</p>
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<p>Incorporation of the luciferase expression system increases the infectivity and killing effect of OAdmCherry in the TNBC HCC1937/luc2 cell line. (<b>A</b>) Infectivity by AdGFP (top) and replication by OAdmCherry (bottom) are increased in the HCC1937/luc2 cell line at 48 h. (<b>B</b>) Viability is decreased at 72 h in the OAdmCherry infected HCC1937/luc2. (<b>C</b>) The number of Adenovirus DNA copies by qPCR (<b>D</b>) and expression of the E1A adenovirus replication marker is increased in the HCC1937/luc2 cells after 24 h of infection. The graphs show 3 independent experiments (Mean ± SD, * <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).</p>
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<p>The antiviral response is further downregulated after OAdmCherry infection in the HCC1937/luc2 cell line. WB shows the main proteins of the interferon-activated immunity. Infection with OAdmCherry decreases the production of these proteins in a dose–response manner.</p>
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<p>Evaluation of the TNBC 4T1/luc orthotopic model. Monitoring of the tumor growth at day 7 (<b>A</b>) and day 14 (<b>B</b>), as well as the identification of metastatic nodules in organs (<b>C</b>) by BLI imaging. (<b>D</b>) The normal tissues and tumor tissues recovered from the lungs demonstrate the presence of metastatic infiltrates. (<b>E</b>) Viability assay after 72 h of OAd infection in both 4T1 and 4T1/luc cell lines. The graphs show 3 independent experiments (Mean ± SD, no significance NS).</p>
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<p>Monitoring by the BLI of an orthotopic TC-1/luc lung cancer model. (<b>A</b>) Subcutaneous tumors confirm the emission of BLI from the TC-1/luc cell line. (<b>B</b>) The detection of orthotopic lung tumors in vivo BLI imaging, and (<b>C</b>) the corresponding ex vivo lungs showing the presence of several tumoral nodules. (<b>D</b>) H&amp;E and IHC staining confirmed the presence of tumor infiltrates and increased proliferation in the lungs. (<b>E</b>) Viability comparison between TC-1 and TC-1/luc after 72 h infection with OAds. The graphs show 3 independent experiments (Mean ± SD, *** <span class="html-italic">p</span> &lt; 0.001).</p>
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13 pages, 3203 KiB  
Article
Brevetoxin Aptamer Selection and Biolayer Interferometry Biosensor Application
by Bo Hu, Sheng-Qun Ouyang, Yu-Ping Zhu, Xiao-Ling Lu, Zhe Ning, Bing-Hua Jiao, Liang-Hua Wang, Hao-Bing Yu and Xiao-Yu Liu
Toxins 2024, 16(10), 411; https://doi.org/10.3390/toxins16100411 - 24 Sep 2024
Viewed by 1026
Abstract
Brevetoxins (PbTxs) are very potent marine neurotoxins that can cause an illness clinically described as neurologic shellfish poisoning (NSP). These toxins are cyclic polyether in chemistry and have increased their geographical distribution in the past 2 decades. However, the ethical problems as well [...] Read more.
Brevetoxins (PbTxs) are very potent marine neurotoxins that can cause an illness clinically described as neurologic shellfish poisoning (NSP). These toxins are cyclic polyether in chemistry and have increased their geographical distribution in the past 2 decades. However, the ethical problems as well as technical difficulties associated with currently employed analysis methods for marine toxins have spurred the quest for suitable alternatives to be applied in a regulatory monitoring regime. In this work, we reported the first instance of concurrent aptamer selection of Brevetoxin-1 (PbTx-1) and Brevetoxin-2 (PbTx-2) and constructed a biolayer interferometry (BLI) biosensor utilizing PbTx-1 aptamer as a specific recognition element. Through an in vitro selection process, we have, for the first time, successfully selected DNA aptamers with high affinity and specificity to PbTx-1 and PbTx-2 from a vast pool of random sequences. Among the selected aptamers, aptamer A5 exhibited the strongest binding affinity to PbTx-1, with an equilibrium dissociation constant (KD) of 2.56 μM. Subsequently, we optimized aptamer A5 by truncation to obtain the core sequence (A5-S3). Further refinement was achieved through mutations based on the predictions of a QGRS mapper, resulting in aptamer A5-S3G, which showed a significant increase in the KD value by approximately 100-fold. Utilizing aptamer A5-S3G, we fabricated a label-free, real-time optical BLI aptasensor for the detection of PbTx-1. This aptasensor displayed a broad detection range from 100 nM to 4000 nM PbTx-1, with a linear range between 100 nM and 2000 nM, and a limit of detection (LOD) as low as 4.5 nM. Importantly, the aptasensor showed no cross-reactivity to PbTx-2 or other marine toxins, indicating a high level of specificity for PbTx-1. Moreover, the aptasensor exhibited excellent reproducibility and stability when applied for the detection of PbTx-1 in spiked shellfish samples. We strongly believe that this innovative aptasensor offers a promising alternative to traditional immunological methods for the specific and reliable detection of PbTx-1. Full article
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<p>(<b>A</b>) Chemical structures of PbTx-1, PbTx-7, and PbTx-10. (<b>B</b>) Chemical structures of PbTx-2, PbTx-3, PbTx-5, PbTx-6, PbTx-8, and PbTx-9. *Denotes likely chemical artifact from extraction.</p>
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<p>(<b>A</b>) Process of MB-SELEX. (<b>B</b>) Recovery ratio of ssDNA during MB-SELEX. The yellow columns represent the recovery ratio of ssDNA bound to PbTx-1 and PbTx-2. The pink columns represent the recovery ratio of ssDNA bound to PbTx-1. The purple columns represent the recovery ratio of ssDNA bound to PbTx-2. CS: Counter Selection.</p>
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<p>(<b>A</b>) Binding saturation curve of potential aptamer A5 to PbTx. (<b>B</b>) Binding saturation curve of potential aptamer B2 to PbTx. (<b>C</b>) Binding saturation curve of potential aptamer B17 to PbTx. (<b>D</b>) Binding saturation curve of the random sequence to PbTx.</p>
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<p>(<b>A</b>) Secondary structure of aptamer A5. (<b>B</b>) Secondary structure of aptamer A5-S1. (<b>C</b>) Secondary structure of aptamer A5-S2. (<b>D</b>) Secondary structure of aptamer A5-S3. (<b>E</b>) Secondary structure of aptamer A5-S3G. (<b>F</b>) Secondary structure of aptamer B2. (<b>G</b>) Secondary structure of aptamer B2-S1. (<b>H</b>) Secondary structure of aptamer B2-S2. (<b>I</b>) Secondary structure of aptamer B2-S1G.</p>
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<p>(<b>A</b>) Characterization of aptamer A5-S3G. (<b>B</b>) Principle of BLI aptasensor. (<b>C</b>) Working procedure of BLI aptasensor.</p>
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<p>(<b>A</b>) The BLI aptasensor’s response to PbTx-1 at increased concentrations (100–4000 nM). (<b>B</b>) The calibration curve of the BLI aptasensor’s response to PbTx-1 at different concentrations (100–4000 nM). The error bars display standard deviations. (<b>C</b>) The linear range of the calibration curve for PbTx-1. The error bars display standard deviations. (<b>D</b>) The specificity of the aptasensor. The error bars display standard deviations. *** <span class="html-italic">p</span> &lt; 0.001, vs. PbTx-1 (control).</p>
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21 pages, 6192 KiB  
Article
Optimizing the Landing Stability of Blended-Wing-Body Aircraft with Distributed Electric Boundary-Layer Ingestion Propulsors through a Novel Thrust Control Configuration
by Mingxing Yu, Zhi Tao, Haiwang Li and Peng Tang
Appl. Sci. 2024, 14(18), 8546; https://doi.org/10.3390/app14188546 - 23 Sep 2024
Viewed by 1104
Abstract
The imperative for energy conservation and environmental protection has led to the development of innovative aircraft designs. This study explored a novel thrust control configuration for blended-wing-body (BWB) aircraft with distributed electric boundary-layer ingestion (BLI) propulsors, addressing the issues of sagging and altitude [...] Read more.
The imperative for energy conservation and environmental protection has led to the development of innovative aircraft designs. This study explored a novel thrust control configuration for blended-wing-body (BWB) aircraft with distributed electric boundary-layer ingestion (BLI) propulsors, addressing the issues of sagging and altitude loss during landing. The research focused on a small-scale BWB demonstrator equipped with six BLI fans, each with a 90 mm diameter. Various thrust control configurations were evaluated to achieve significant thrust reduction while maintaining lift, including dual-layer sleeve, separate flap-type, single-stage linkage flap-type, and dual-stage linkage flap-type configurations. The separate flap-type configuration was tested through ground experiments. Control experiments were conducted under three different experimental conditions as follows: deflection of the upper cascades only, deflection of the lower cascades only, and symmetrical deflection of both cascades. For each condition, the deflection angles tested were 0°, 10°, 20°, 30°, 40°, 50°, and 60°. The thrust reductions observed for these three conditions were 0%, 37.5%, and 27.5% of the maximum thrust, respectively, without additional changes in the pitch moment. A combined thrust adjustment method maintaining a zero pitch moment demonstrated a linear thrust reduction to 20% of its initial value. The experiment concluded that the novel thrust control configuration effectively adjusted thrust without altering the BLI fans’ rotation speed, solving the coupled lift–thrust problem and enhancing BWB landing stability. Full article
(This article belongs to the Section Aerospace Science and Engineering)
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<p>Sagging problem of BWB aircraft caused by short lever arms.</p>
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<p>Schematic of BWB aircraft with distributed electric BLI propulsors.</p>
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<p>Schematic diagram of a dual-layer sleeve thrust control configuration: (<b>a</b>) normal thrust and (<b>b</b>) reverse thrust.</p>
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<p>Components and motion of a dual-layer sleeve thrust control configuration.</p>
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<p>Schematic diagram of a separate flap-type thrust control configuration.</p>
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<p>Components and motion of a separate flap-type thrust control configuration: (<b>a</b>) normal thrust and (<b>b</b>) reverse thrust.</p>
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<p>Schematic diagram of a single-stage linkage flap-type thrust control configuration.</p>
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<p>Components and motion of a single-stage linkage flap-type thrust control configuration.</p>
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<p>Schematic diagram of a dual-stage linkage flap-type thrust control configuration.</p>
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<p>Components and motion of a dual-stage linkage flap-type thrust control configuration.</p>
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<p>Schematic diagram of BWB aircraft with novel thrust control configuration.</p>
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<p>Force model of BWB aircraft.</p>
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<p>Schematic diagram of the experimental setup for BWB aircraft with novel thrust control configuration.</p>
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<p><span class="html-italic">C<sub>L</sub></span> variation with deflection angles in symmetrical cascade deflection.</p>
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<p><span class="html-italic">C<sub>M</sub></span> variation with deflection angles in symmetrical cascade deflection.</p>
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<p><span class="html-italic">T</span> variation with deflection angles in symmetrical cascade deflection.</p>
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<p><span class="html-italic">C<sub>L</sub></span> variation with deflection angles in upper cascade deflection.</p>
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<p><span class="html-italic">C<sub>M</sub></span> variation with deflection angles in upper cascade deflection.</p>
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<p><span class="html-italic">T</span> variation with deflection angles in upper cascade deflection.</p>
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<p><span class="html-italic">C<sub>L</sub></span> variation with deflection angles in lower cascade deflection.</p>
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<p>C<sub>M</sub> variation with deflection angles in lower cascade deflection.</p>
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<p><span class="html-italic">T</span> variation with deflection angles in lower cascade deflection.</p>
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<p>Deflection angle combinations for zero pitch moment (<span class="html-italic">C<sub>M</sub></span> = 0) in both cascades.</p>
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<p>Variation in <span class="html-italic">C<sub>L</sub></span> and <span class="html-italic">T</span> with deflection angles under constant-pitch-moment conditions.</p>
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15 pages, 2776 KiB  
Article
Development of Biolayer Interferometry (BLI)-Based Double-Stranded RNA Detection Method with Application in mRNA-Based Therapeutics and Vaccines
by Dharia Sara Silas, Bindiya Juneja, Keerat Kaur, Muralikrishna Narayanareddy Gari, Yingjian You, Youmi Moon, Yizhuo Chen, Srishti Arora, Johanna Hansen, Kathir Muthusamy, Yue Fu, Nisha Palackal and Erica A. Pyles
Pharmaceutics 2024, 16(9), 1227; https://doi.org/10.3390/pharmaceutics16091227 - 19 Sep 2024
Viewed by 1953
Abstract
Background: In vitro-transcribed (IVT) mRNA has been established as a promising platform for therapeutics and vaccine development. Double-stranded RNA (dsRNA) is a major impurity of IVT mRNA and can trigger unfavored immune responses, potentially causing adverse events in patients. Existing dsRNA detection and [...] Read more.
Background: In vitro-transcribed (IVT) mRNA has been established as a promising platform for therapeutics and vaccine development. Double-stranded RNA (dsRNA) is a major impurity of IVT mRNA and can trigger unfavored immune responses, potentially causing adverse events in patients. Existing dsRNA detection and quantitation methods, such as gel electrophoresis, ELISA, or homogeneous time-resolved fluorescence (HTRF), have low sensitivity or are time-consuming. A recently published lateral flow immunoassay (LFSA) was shown to be fast, but it lacks the sensitivity for dsRNA with uridine modifications. Methods: In this study, we provided a possible explanation for the reduced sensitivity of existing quantitation methods for dsRNA with modified uridines by characterizing the binding affinities of commonly used anti-dsRNA antibodies. Then, a rapid and sensitive biolayer interferometry (BLI) dsRNA detection assay utilizing Flock House Virus (FHV) B2 protein was developed to overcome the challenges in dsRNA detection and the reduced sensitivity. Results: This assay allows the detection of dsRNA with different uridine modifications (ψ, m1ψ, 5 moU) with similar sensitivity as dsRNA without modification. Furthermore, we demonstrated this method can be used to quantify both short and long dsRNA, as well as hairpin-structured dsRNA, providing a more comprehensive detection for dsRNA impurities. Moreover, we applied this assay to monitor dsRNA removal through a purification process. Conclusions: Taken together, this BLI method could enable real-time monitoring of impurities in IVT mRNA production to prevent immunogenicity stemming from dsRNA. Full article
(This article belongs to the Special Issue State-of-Art in mRNA Therapeutics and Gene Delivery)
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<p>Determination of B2 binding affinity for dsRNA with different modifications. Binding sensorgrams and binding affinity determination of B2 for 700 bp dsRNA with different uridine modifications. (<b>Top</b>) (from left to right): representative binding sensorgrams of B2 with 700 bp-U, 700 bp-ψ, 700 bp-m1ψ or 700 bp-5 moU dsRNA. (<b>Bottom</b>): corresponding steady-state analysis using binding sensorgrams on the top (BLI signal plotted against B2 concentration) was utilized to determine B2 to dsRNA binding affinity (K<sub>D</sub>). All experiments were performed in triplicate.</p>
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<p>Illustration of BLI dsRNA detection assay. BLI dsRNA detection assay with representative sensorgrams with dotted line separating each step. Step (1) establish baseline in assay buffer; (2) immobilize B2-Biotin on SA sensors; (3) wash to remove unbound B2-Biotin; (4) serially diluted dsRNA binding to B2 surface.</p>
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<p>BLI dsRNA detection assay validation with HTRF assay. dsRNA detection by BLI dsRNA detection assay showed a similar trend as HTRF dsRNA assay for three IVT mRNA samples: (<b>Left</b>), BLI assay responses for mRNA-1 to mRNA-3 (with blank signal subtracted). (<b>Right</b>), HTRF signal (ratio) measured for mRNA-1 to mRNA-3 (with blank signal subtracted). All IVT mRNA samples were tested at 5 µg/mL in triplicates (BLI) and duplicates (HTRF).</p>
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<p>BLI dsRNA detection assay specificity and interference testing. Testing specificity and interference using chemically similar nucleic acids on BLI dsRNA detection assay: (<b>A</b>) Specificity testing: BLI signal is shown for 700 bp-U, 700 bp-m1ψ, ssRNA (100-fold), dsDNA (100-fold), 142 bp dsRNA, and Poly(I:C). (<b>B</b>) Interference testing: BLI signal of 700 bp-U compared against 700 bp-U in the presence of 100-fold or 200-fold excess of ssRNA or dsDNA. (<b>C</b>) Interference testing: BLI signal of 700 bp-U was compared against 700 bp-m1ψ in the presence of 100-fold or 200-fold excess of ssRNA or dsDNA. All experiments were performed in triplicate.</p>
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<p>Comparison of impact of uridine modifications on standard curves for BLI, HTRF, and ELISA method for dsRNA quantitation. Comparison of impact of uridine modifications on standard curves for BLI, HTRF, and ELISA methods. From top to bottom, overlay of 700 bp dsRNA standards with different modifications for (<b>A</b>) BLI dsRNA detection assay; (<b>B</b>) dsRNA quantitation HTRF assay; (<b>C</b>) dsRNA quantitation J2 ELISA.</p>
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<p>Comparison of dsRNA standards of different lengths on BLI, HTRF, and ELISA methods. Comparison of dsRNA standards of different lengths using BLI, HTRF, and ELISA methods. From top to bottom, overlay of dsRNA standards of different lengths for (<b>A</b>) BLI dsRNA detection assay; (<b>B</b>) dsRNA quantitation HTRF assay; (<b>C</b>) dsRNA quantitation J2 ELISA.</p>
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<p>BLI dsRNA assay can monitor dsRNA reduction through purification process. BLI dsRNA detection assay utilized to monitor dsRNA level through purification process. Two IVT mRNA transcripts (mRNA-4 and mRNA-5) were purified using ion pair reverse-phase (IPRP) chromatography. Before: IVT mRNA before IPRP purification. After: IVT mRNA purified by IPRP. (<b>Top</b>) panel: BLI response of mRNA-4 and mRNA-5 tested at 20 µg/mL in triplicates (with blank subtracted). (<b>Bottom</b>) panel: HTRF signal of mRNA-4 and mRNA-5 tested at 10 µg/mL in triplicates (with blank subtracted).</p>
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15 pages, 2922 KiB  
Article
Specific Synbiotic Sugars Stimulate Streptococcus salivarius BLIS K12 and BLIS M18 Lantibiotic Production to Expand Bacterial Inhibition Range and Potency
by Liam K. Harold, Nicola C. Jones, Sarah L. Barber, Abigail L. Voss, Rohit Jain, John R. Tagg and John D. F. Hale
Appl. Microbiol. 2024, 4(3), 1320-1334; https://doi.org/10.3390/applmicrobiol4030091 - 16 Sep 2024
Viewed by 1003
Abstract
Synbiotics are mixtures of prebiotics and probiotics that enhance the activity of probiotic bacteria when co-administered to provide greater benefits to the host. Traditionally, the synbiotics that have been discovered enhance gut probiotic strains and are nutritionally complex molecules that survive digestive breakdown [...] Read more.
Synbiotics are mixtures of prebiotics and probiotics that enhance the activity of probiotic bacteria when co-administered to provide greater benefits to the host. Traditionally, the synbiotics that have been discovered enhance gut probiotic strains and are nutritionally complex molecules that survive digestive breakdown until they reach the later stages of the intestinal tract. Here, we screened and identified sugars or sugar substitutes as synbiotics for the oral probiotic strains Streptococcus salivarius BLIS K12 and BLIS M18. Using a modified deferred antagonism assay, we found that 0.5% (w/v) galactose and 2.5% (w/v) raffinose were the best candidates for use as synbiotics with BLIS K12 and M18, as they trigger enhanced antimicrobial activity against a range of bacteria representing species from the mouth, gut, and skin. Using reverse transcriptase quantitative PCR, we found that this enhanced antimicrobial activity was caused by the upregulation of the lantibiotic genes salA, salB, and sal9 in either K12 or M18. This led to the conclusion that either 2.5% (w/v) raffinose or 0.5% (w/v) galactose, respectively, are suitable synbiotics for use in conjunction with BLIS K12 and M18 to enhance probiotic performance. Full article
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<p>(<b>A</b>) Sum of the mean zones of inhibition for different sugars (left Y-axes, Bars) and the number of species inhibited (right Y-axes, square points) for BLIS K12 and BLIS M18 at both 2.5% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) and 0.5% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) of different sugars (Data points are mean (n = 3, ±SD). For the sum of the average mean zones of inhibition, a two-way ANOVA with Dunnett’s multiple comparisons tests compared raffinose in the 2.5% samples and galactose in 0.5% to the other sugars was completed. * = <span class="html-italic">p</span> &lt; 0.05 for all sugars, # = <span class="html-italic">p</span> &lt; 0.05 for all sugars except lactulose and lactose and ^ = <span class="html-italic">p</span> &lt; 0.05 for all sugar except raffinose. (<b>B</b>) Mean growth of BLIS K12 and BLIS M18 in M17 media supplemented with different types and concentrations of sugars after 18 h. (n = 3, ±SD). (<b>C</b>) Dose response of raffinose and galactose at different concentrations measuring the mean increase in zones of inhibition and number of species of bacteria inhibited compared to a non-sugar control across <span class="html-italic">S. constellatus</span> T29, <span class="html-italic">S. salivarius</span> K34b, <span class="html-italic">S. pyogenes</span> 71-698, <span class="html-italic">S. mutans</span> OMZ175, <span class="html-italic">S. pneumoniae</span> D39, <span class="html-italic">S. saprophyticus</span> ATCC 13505, <span class="html-italic">S. aureus</span> A222, <span class="html-italic">S. sobrinus</span> OMZ176. Lines with dots represent the mean increase in the size of the inhibition zone with a line of non-linear fit (left Y axes) and bars represent the number of species inhibited (right Y axes).</p>
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<p>Size of the inhibition zone for BLIS K12 and BLIS M18 on CABCa agar plates, containing 2.5% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) raffinose or 0.5% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) galactose or no sugar, across a range of bacterial species and strains associated with (<b>A</b>) pharyngitis, otitis media, pneumonia, and neonatal sepsis infections. (<b>B</b>) Teeth (<b>C</b>) periodontitis, halitosis, and gut (<b>D</b>) skin. Bars are means of biological replicates (n = 3, ±SD). (<b>A</b>–<b>D</b>) A two-way ANOVA with Dunnett’s multiple comparisons tests compared raffinose and galactose to the no sugar control. *, <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, ****, <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Mean expression levels of (<b>A</b>) <span class="html-italic">salA</span> (<b>B</b>) <span class="html-italic">salB</span> in BLIS K12 and (<b>C</b>) <span class="html-italic">salA</span> (<b>D</b>) <span class="html-italic">sal9</span> in BLIS M18, when grown on CABCa agar medium supplemented with different sugars relative to a no sugar control. Bars represent mean values with individual values shown as symbols (n = 3, ±SD).</p>
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<p>Illustrates the potential mechanisms by which the synbiotic sugars, raffinose and galactose enhance the probiotic performance of BLIS K12 and BLIS M18. Created with Created in BioRender. Hale, J. (2024) <a href="http://BioRender.com/g80w234" target="_blank">BioRender.com/g80w234</a> (accessed on 13 September 2024).</p>
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9 pages, 620 KiB  
Brief Report
Utilization of Assisted Reproductive Technologies in Breeding Auliekol Cattle: A Comparative Study
by Altyn Kulpiisova, Kairly Yessengaliyev, Gulsara Kassimova, Ainat Kozhakhmetova, Bakytkanym Kadraliyeva, Abeldinov Rustem, Alma Temirzhanova, Nadezhda Burambayeva, Salbak Chylbak-ool, Elena Pakhomova, Nurzhan Abekeshev, Gulnara Baikadamova, Zhomart Kemeshev, Alexandra Tegza, Arman Issimov and Peter White
Life 2024, 14(9), 1167; https://doi.org/10.3390/life14091167 - 15 Sep 2024
Viewed by 1077
Abstract
This study evaluates the utilization of in vitro embryo production (IVEP) technology for the conservation and breeding of the Auliekol cattle breed, a primary beef breed in Kazakhstan facing population decline due to the cessation of breeding programs and the incursion of transboundary [...] Read more.
This study evaluates the utilization of in vitro embryo production (IVEP) technology for the conservation and breeding of the Auliekol cattle breed, a primary beef breed in Kazakhstan facing population decline due to the cessation of breeding programs and the incursion of transboundary diseases. We assessed the effect of consecutive ovum pick-up (OPU) procedures on oocyte yield and embryo production in Auliekol and Aberdeen Angus cows. A total of 2232 and 3659 oocytes were aspirated from Auliekol and Aberdeen Angus donors, respectively, with significantly higher yields and embryo production observed in Aberdeen Angus cows. The application of a meiotic block using Butyrolactone I (BLI) and subsequent in vitro fertilization (IVF) protocols was employed, with embryo development monitored up to the morula/blastocyst stage. Results indicated that Auliekol cows exhibited lower oocyte recovery, cleavage, and blastocyst rates compared to Aberdeen Angus cows, likely due to genetic characteristics. Despite the challenges, IVEP presents a valuable tool for the preservation and future propagation of the Auliekol breed, highlighting the need for further research to enhance reproductive outcomes and conservation strategies. Full article
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<p>Inverted microscopic picture of Blastocysts produced in vitro on the seventh day of development. DIC magnification ×100.</p>
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20 pages, 2618 KiB  
Article
Enhanced Tailings Dam Beach Line Indicator Observation and Stability Numerical Analysis: An Approach Integrating UAV Photogrammetry and CNNs
by Kun Wang, Zheng Zhang, Xiuzhi Yang, Di Wang, Liyi Zhu and Shuai Yuan
Remote Sens. 2024, 16(17), 3264; https://doi.org/10.3390/rs16173264 - 3 Sep 2024
Viewed by 950
Abstract
Tailings ponds are recognized as significant sources of potential man-made debris flow and major environmental disasters. Recent frequent tailings dam failures and growing trends in fine tailings outputs underscore the critical need for innovative monitoring and safety management techniques. Here, we propose an [...] Read more.
Tailings ponds are recognized as significant sources of potential man-made debris flow and major environmental disasters. Recent frequent tailings dam failures and growing trends in fine tailings outputs underscore the critical need for innovative monitoring and safety management techniques. Here, we propose an approach that integrates UAV photogrammetry with convolutional neural networks (CNNs) to extract beach line indicators (BLIs) and conduct enhanced dam safety evaluations. The significance of real 3D geometry construction in numerical analysis is investigated. The results demonstrate that the optimized You Only Look At CoefficienTs (YOLACT) model outperforms in recognizing the beach boundary line, achieving a mean Intersection over Union (mIoU) of 72.63% and a mean Pixel Accuracy (mPA) of 76.2%. This approach shows promise for future integration with autonomously charging UAVs, enabling comprehensive coverage and automated monitoring of BLIs. Additionally, the anti-slide and seepage stability evaluations are impacted by the geometry shape and water condition configuration. The proposed approach provides more conservative seepage calculations, suggesting that simplified 2D modeling may underestimate tailings dam stability, potentially affecting dam designs and regulatory decisions. Multiple numerical methods are suggested for cross-validation. This approach is crucial for balancing safety regulations with economic feasibility, helping to prevent excessive and unsustainable burdens on enterprises and advancing towards the goal of zero harm to people and the environment in tailings management. Full article
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<p>Diagram illustrating common BLIs monitoring methods. (<b>a</b>) Equidistant beach width sign placed along the beach section used for the visual identification method. (<b>b</b>) The radar level gauge method, illustrating its setup and data collection technique. (<b>c</b>) The laser ranging method, illustrating the device setup at the dam crest, the measurement of the irradiated laser beam angle <math display="inline"><semantics> <mi>α</mi> </semantics></math>, and the distance <span class="html-italic">l</span> to the decant pond boundary. (<b>d</b>) The seepage backcalculation method, illustrating the placement of piezometers and the principle for calculating the BLIs. (<b>e</b>) Arrangement layout of the tailings pond BLIs monitoring devices.</p>
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<p>Optimized YOLACT model workflow. Here, “+” denotes elementwise addition, “2×” indicates twice linear upsampling,“DWconv” stands for depthwise convolution, and “BN” refers to batch normalization.</p>
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<p>Optimized DeepLabV3+ model workflow.</p>
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<p>Information and UAV aerial survey results of the tailings pond in the case study. (<b>a</b>) Geographical location. (<b>b</b>) Structural composition. (<b>c</b>,<b>d</b>) UAV aerial survey Digital Orthophoto Map (DOM) texture and Digital Surface Model (DSM) topographic results.</p>
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<p>Computational models of tailings dam stability analyses. (<b>a</b>) Two-dimensional (2D) model. (<b>b</b>) Pseudo-three-dimensional (P-3D) model that extends the 2D profiles fitting with water level conditions. (<b>c</b>) Real three-dimensional (R-3D) model that incorporates actual BLIs conditions identified from the proposed approach.</p>
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<p>Comparison of automated recognition results. (<b>a1</b>∼<b>a4</b>) Original images. (<b>b1</b>∼<b>b4</b>) Manually annotated results. (<b>c1</b>∼<b>c4</b>) Recognition results of optimized DeepLabV3+. (<b>d1</b>∼<b>d4</b>) Recognition results of optimized YOLACT.</p>
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<p>The extracted contours delineating the beach interface and the boundary edge of the decant pond using the optimized YOLACT model.</p>
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<p>Beach slope observation results. (<b>a</b>) Equidistant beach slope calculation sections. (<b>b</b>–<b>g</b>): Beach slope values extracted from DSM from section I to section VI plotted against the distance from the embankment crest.</p>
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<p>Results of dam stability evaluation. (<b>a</b>) 2D model, dam stability coefficient 2.096 (simplified Bishop method). (<b>b</b>) 2D model, dam stability coefficient 3.10 (SRM method). (<b>c</b>) P-3D model that extended the 2D profiles fitting with the minimum beach width condition, dam stability coefficient 3.86 (SRM method). (<b>d</b>) R-3D model based on actual BLIs condition extracted from the proposed approach, dam stability coefficient 4.00 (SRM method).</p>
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<p>Results of the tailings pond seepage analyses. (<b>a</b>) Model A, with water levels set at the minimum beach width condition. (<b>b</b>) Model B, with water levels set at the actual beach boundary line condition and extracted using the optimized YOLACT. (<b>c</b>) Comparison of the simulated seepage phreatic lines for Models A and B under various rainfall scenarios.</p>
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