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16 pages, 2411 KiB  
Article
Research on Gas Emission Prediction Based on KPCA-ICSA-SVR
by Li Liu, Linchao Dai, Xinyi Mao, Yutao Chen and Yongheng Jing
Processes 2024, 12(12), 2655; https://doi.org/10.3390/pr12122655 (registering DOI) - 25 Nov 2024
Abstract
In the context of deep mining, the uncertainty of gas emission levels presents significant safety challenges for mines. This study proposes a gas emission prediction model based on Kernel Principal Component Analysis (KPCA), an Improved Crow Search Algorithm (ICSA) incorporating adaptive neighborhood search, [...] Read more.
In the context of deep mining, the uncertainty of gas emission levels presents significant safety challenges for mines. This study proposes a gas emission prediction model based on Kernel Principal Component Analysis (KPCA), an Improved Crow Search Algorithm (ICSA) incorporating adaptive neighborhood search, and Support Vector Regression (SVR). Initially, data preprocessing is conducted to ensure a clean and complete dataset. Subsequently, KPCA is applied to reduce dimensionality by extracting key nonlinear features from the gas emission influencing factors, thereby enhancing computational efficiency. The ICSA is then employed to optimize SVR hyperparameters, improving the model’s optimization capabilities and generalization performance, leading to the development of a robust KPCA-ICSA-SVR prediction model. The results indicate that the KPCA-ICSA-SVR model achieves the best performance, with RMSE values of 0.17898 and 0.3071 for the training and testing sets, respectively, demonstrating superior robustness and generalization capability. Full article
(This article belongs to the Special Issue Advances in Coal Processing, Utilization, and Process Safety)
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<p>Schematic diagram of KPCA.</p>
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<p>Schematic diagram of the ICSA.</p>
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<p>Schematic diagram of SVR.</p>
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<p>RMSE of different estimators.</p>
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<p>Kernel matrix heatmap.</p>
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<p>Variance explanation.</p>
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<p>Optimization capabilities of the algorithm: (<b>a</b>) unimodal function; (<b>b</b>) multimodal function.</p>
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<p>Training set prediction results.</p>
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<p>Test set prediction results</p>
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14 pages, 1483 KiB  
Article
Unveiling the Dynamics of Antimicrobial Resistance: A Year-Long Surveillance (2023) at the Largest Infectious Disease Profile Hospital in Western Romania
by Sorina Maria Denisa Laitin, Luminita Mirela Baditoiu, Ruxandra Laza, Irina-Maria Stefan, Razvan Sebastian Besliu, Septimiu Radu Susa, Cristian Oancea, Emil Robert Stoicescu, Diana Manolescu and Corneluta Fira-Mladinescu
Antibiotics 2024, 13(12), 1130; https://doi.org/10.3390/antibiotics13121130 (registering DOI) - 25 Nov 2024
Abstract
Background/Objectives: Antimicrobial resistance (AMR) is a critical global health threat, leading to increased morbidity, mortality, and healthcare costs. This study aimed to identify the most common bacterial pathogens and their resistance profiles from 2179 positive clinical cultures from inpatients at “Victor Babes” [...] Read more.
Background/Objectives: Antimicrobial resistance (AMR) is a critical global health threat, leading to increased morbidity, mortality, and healthcare costs. This study aimed to identify the most common bacterial pathogens and their resistance profiles from 2179 positive clinical cultures from inpatients at “Victor Babes” Hospital of Infectious Disease and Pneumoftiziology Timisoara in 2023. Methods: Samples were collected from sputum, bronchial aspiration, hemoculture, urine, wound secretions, catheter samples, and other clinical specimens. Results: Key pathogens identified included Klebsiella pneumoniae, Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and Acinetobacter baumannii, with notable resistance patterns, observed K. pneumoniae exhibited high resistance rates, notably 41.41% in Quarter 1, while E. coli showed 35.93% resistance in the same period. S. aureus, particularly MRSA, remained a persistent challenge, with 169 cases recorded over the year. A. baumannii and P. aeruginosa displayed alarming levels of multi-drug resistance, especially in Quarter 3 (88.24% and 22.02%, respectively). Although there was a general decline in resistance rates by Quarter 4, critical pathogens such as S. aureus and K. pneumoniae continued to exhibit significant resistance (81.25% and 21.74%, respectively). Conclusions: The study’s findings align with the broader antimicrobial resistance trends observed in Romania, where high resistance rates in K. pneumoniae, E. coli, S. aureus (MRSA), Acinetobacter, and Pseudomonas species have been widely reported, reflecting the country’s ongoing struggle with multi-drug-resistant infections. Despite some reductions in resistance rates across quarters, the persistent presence of these resistant strains underscores the critical need for strengthened antimicrobial stewardship, infection control measures, and continuous surveillance to combat the growing threat of AMR in Romania and similar healthcare settings. Full article
(This article belongs to the Special Issue Antimicrobial Resistance Genes: Spread and Evolution)
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<p>The distribution’s histogram during quarters in 2023.</p>
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<p>Number and percentage of isolates (%) over the surveillance period (Timisoara Hospital, 2023) by specimen type.</p>
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<p>Number (n) and percentage (%) of bacterial infections during the surveillance period (2023) by organism and resistance phenotype.</p>
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<p>%MRSA and %MRSE trends across the quarters in 2023.</p>
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17 pages, 2361 KiB  
Article
Net Promoter Score Model for Evaluating Paediatric Medicine Acceptability: Validation and Feasibility Study
by Okhee Yoo, Demi Stanford, Britta S. von Ungern-Sternberg and Lee Yong Lim
Pharmaceutics 2024, 16(12), 1513; https://doi.org/10.3390/pharmaceutics16121513 (registering DOI) - 25 Nov 2024
Abstract
Background/Objectives: Medicine acceptability is crucial for paediatric drug development, yet its assessment remains challenging due to the multifaceted nature of sensory attributes like taste, smell, and mouthfeel. Traditional methods of acceptability evaluation often involve complex questionnaires and lack standardisation, leading to difficulties [...] Read more.
Background/Objectives: Medicine acceptability is crucial for paediatric drug development, yet its assessment remains challenging due to the multifaceted nature of sensory attributes like taste, smell, and mouthfeel. Traditional methods of acceptability evaluation often involve complex questionnaires and lack standardisation, leading to difficulties in a comparative analysis across studies. This study aimed to develop a simplified, standardised approach for assessing medicine acceptability introducing the Net Promoter Score (NPS) framework to derive a Medicine Acceptability Score (MAS). Methods: A retrospective analysis was conducted using taste assessment data from nine paediatric formulations across four studies. The MAS was calculated by identifying an optimal range for categorising participant responses, which encapsulated diverse sensory attributes into a single metric. Validation was performed across various age groups and different formulations to test the reliability and discriminatory power of MAS. Results: The MAS effectively discriminated between acceptable and unacceptable formulations, providing a practical tool for formulation development. Conclusions: The MAS offers a novel, standardised metric for evaluating paediatric medicine acceptability, addressing key limitations of traditional methods. Future studies are recommended to refine the MAS model through the establishment of benchmark scores for chronic and acute medications, thereby standardising acceptability assessment of medicines across the pharmaceutical industry. Full article
(This article belongs to the Special Issue Customized Pharmaceutics: Innovations for Diverse Populations)
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<p>An illustration of how the Net Promoter Score (NPS) is calculated. The NPS ranges from −100 to +100 and is calculated by subtracting the percentage of detractors (customers who give a score of 0–6) from the percentage of promoters (customers who give a score of 9–10).</p>
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<p>Chewable flucloxacillin taste-masked tablets equivalent to 62.5 mg flucloxacillin and with (<b>a</b>) dark chocolate as carrier (FLX TMT1) and (<b>b</b>) white chocolate as carrier (FLX TMT2).</p>
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<p>The 11-point rating scales used by the participants in Study 4 to assess each prednisolone sodium phosphate formulation for (<b>a</b>) their liking of the taste and (<b>b</b>) their willingness to take the formulation again.</p>
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<p>A schematic diagram illustrating how the MAS was calculated using data from a 5-Point Hedonic Taste Score and assigning the passives scores to be (<b>a</b>) 2–4; and (<b>b</b>) 3 alone, as well as the calculation of the Willingness to Take Medicine Score (WTMS) (<b>c</b>). Both MAS and WTMS were calculated using data obtained from a paediatric clinical trial on the tramadol taste-masked tablet (<span class="html-italic">n</span> = 68).</p>
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<p>Box plots showing the taste scores obtained via 5-point hedonic scales for medicinal formulations evaluated in Studies 1–3. The upper limit of each box represents the 75th percentile, the lower limit represents the 25th percentile, and the line within the box indicates the median value. Whiskers above and below the boxes represent the 90th and 10th percentiles, respectively. Individual data points are depicted as solitary circles. Tramadol = TRM; Midazolam = MDZ; Flucloxacillin = FLX; Taste-masked tablets = TMTs; LQD = oral liquid comparator. Two flucloxacillin taste-masked tablets, FLX TMT1 and FLX TMT2, were evaluated.</p>
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<p>Percentages of promoters, passives, and detractors for TRM TMT when different score ranges were defined for the passives category. Participants were categorised into promoters, passives, or detractors based on the taste scores they provided for TRM TMT using a 5-point hedonic scale.</p>
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<p>(<b>a</b>) The bar graph depicts the correlation between mean taste scores with a passives range of 3 and Medicine Acceptance Scores (MAS) for 7 medicinal formulations evaluated in Studies 1–3. Formulations with positive MAS values are grouped on the left, indicating higher acceptance, while those with negative MAS values are on the right, indicating lower acceptance. The data illustrate how MAS can differentiate acceptance levels that are not apparent from comparing taste scores alone. (<b>b</b>) The percentages of promoters, passives, and detractors for the different formulations. Participants were categorised as promoters, passives, or detractors based on their taste scores using a 5-point hedonic scale, with a score of 3 indicating a passive response. Tramadol = TRM; Midazolam = MDZ; Flucloxacillin = FLX; Taste-masked tablets = TMTs; LQD = oral liquid comparator.</p>
Full article ">Figure 7 Cont.
<p>(<b>a</b>) The bar graph depicts the correlation between mean taste scores with a passives range of 3 and Medicine Acceptance Scores (MAS) for 7 medicinal formulations evaluated in Studies 1–3. Formulations with positive MAS values are grouped on the left, indicating higher acceptance, while those with negative MAS values are on the right, indicating lower acceptance. The data illustrate how MAS can differentiate acceptance levels that are not apparent from comparing taste scores alone. (<b>b</b>) The percentages of promoters, passives, and detractors for the different formulations. Participants were categorised as promoters, passives, or detractors based on their taste scores using a 5-point hedonic scale, with a score of 3 indicating a passive response. Tramadol = TRM; Midazolam = MDZ; Flucloxacillin = FLX; Taste-masked tablets = TMTs; LQD = oral liquid comparator.</p>
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<p>Box plots showing the scores obtained via 11-point scales for (<b>a</b>) taste; and (<b>b</b>) willingness to take the formulation again when unwell for two prednisolone sodium phosphate formulations in Study 4. The upper limit of each box represents the 75th percentile, the lower limit represents the 25th percentile, and the line within the box indicates the median value. Whiskers above and below the boxes represent the 90th and 10th percentiles, respectively. Individual data points are depicted as solitary circles. Prednisolone sodium phosphate = PSP; Taste-masked tablet = TMT; LQD = oral liquid comparator.</p>
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39 pages, 6564 KiB  
Article
Thermal Conversion of Coal Bottom Ash and Its Recovery Potential for High-Value Products Generation: Kinetic and Thermodynamic Analysis with Adiabatic TD24 Predictions
by Bojan Janković, Marija Janković, Ana Mraković, Jelena Krneta Nikolić, Milica Rajačić, Ivana Vukanac, Nataša Sarap and Nebojša Manić
Materials 2024, 17(23), 5759; https://doi.org/10.3390/ma17235759 (registering DOI) - 25 Nov 2024
Abstract
Thermal decomposition (pyrolysis) of coal bottom ash (collected after lignite combustion in coal-fired power plant TEKO-B, Republic of Serbia) was investigated, using the simultaneous TG-DTG techniques in an inert atmosphere, at various heating rates. By using the XRD technique, it was found that [...] Read more.
Thermal decomposition (pyrolysis) of coal bottom ash (collected after lignite combustion in coal-fired power plant TEKO-B, Republic of Serbia) was investigated, using the simultaneous TG-DTG techniques in an inert atmosphere, at various heating rates. By using the XRD technique, it was found that the sample (CBA-TB) contains a large amount of anorthite, muscovite, and silica, as well as periclase and hematite, but in a smaller amount. Using a model-free kinetic approach, the complex nature of the process was successfully resolved. Thermodynamic analysis showed that the sample is characterized by dissociation reactions, which are endothermic with positive activation entropy changes, where spontaneity is achieved at high reaction temperatures. The model-based method showed the existence of a complex reaction scheme that includes two consecutive reaction steps and one single-step reaction, described by a variety of reaction models as nucleation/growth phase boundary-controlled, the second/n-th order chemical, and autocatalytic mechanisms. It was established that an anorthite I1 phase breakdown reaction into the incongruent melting product (CaO·Al2O3·2SiO2) represents the rate-controlling step. Autocatalytic behavior is reflected through chromium-incorporated SiO2 catalyst reaction, which leads to the formation of chromium(II) oxo-species. These catalytic centers are important in ethylene polymerization for converting light olefin gases into hydrocarbons. Adiabatic TD24 prediction simulations of the process were also carried out. Based on safety analysis through validated kinetic parameters, it was concluded that the tested sample exhibits high thermal stability. Applied thermal treatment was successful in promoting positive changes in the physicochemical characteristics of starting material, enabling beneficial end-use of final products and reduction of potential environmental risks. Full article
(This article belongs to the Section Advanced Materials Characterization)
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Figure 1
<p>TG (<b>a</b>) and DTG (<b>b</b>) curves at the heating rate of <span class="html-italic">β</span> = 10.3 K/min for thermal decomposition of CBA-TB.</p>
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<p>The conversion rate (absolute) (%/min) curves vs. temperature at various heating rates for thermal decomposition of CBA-TB (the specific decomposition zones are also designated at the same graph, as “I, II and III”; the corresponding “shoulder” reaction peak inside the main decomposition region (“II”) is clearly marked).</p>
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<p>ASTM E2890 plots were obtained for considered reaction regions (I, II, and III) in thermal decomposition of CBA-TB sample (Adj. R-Square values (R<sup>2</sup>) and the 95% confidential (mean) ellipses are provided).</p>
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<p>Variation of activation energy (<span class="html-italic">E<sub>a</sub></span>) (<b>a</b>) and the logarithm of the pre-exponential factor (<span class="html-italic">logA</span>) (<b>b</b>) with conversion (α), calculated by means of FR, KAS, OFW, and VY model-free methods for non-isothermal decomposition process of CBA-TB.</p>
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<p>(<b>a</b>) Experimental <span class="html-italic">ddf</span> (the full open circles) and the LogNormal <span class="html-italic">ddf</span> fit (Equation (1): solid red line curve) with the indicated <span class="html-italic">E<sub>a</sub></span><sub>,<span class="html-italic">c</span></sub> valu, and (<b>b</b>) Extracted LogNormal distribution function without short—and long–tails, with the main part of the distribution (enlarged), where the central peak is found (the values of median, mean, and variance were compared) (baseline of <span class="html-italic">ddf</span> is represented by the dashed red-colored line).</p>
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<p>Conversion fit optimization of CBA-TB thermal decomposition process through TG-signals, using modified Friedman’s model data (<span class="html-italic">colored symbols</span>: experimental TG-data points; <span class="html-italic">colored solid lines</span>: optimized results—calculated (fit) TG-curves (<a href="#app1-materials-17-05759" class="html-app">Supplementary Materials, Equations (S8)–(S9)</a>) (NETZSCH Kinetics Neo software image extracted (Product version 2.7.3.15, Build date 6 November 2024))).</p>
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<p>Compensatory behavior of the kinetic parameters, <span class="html-italic">logA</span> and <span class="html-italic">E<sub>a</sub></span>, expressed through the KCE relationships as <span class="html-italic">logA</span><sub>(conversion (α))</sub> = <span class="html-italic">a</span> + <span class="html-italic">b</span>·<span class="html-italic">E<sub>a</sub></span><sub>(conversion (α))</sub> for the thermal decomposition process of CBA-TB sample, with indicated Adj. R-Square (R<sup>2</sup>) values for each KCE branch (Region I: Δα = 0.01–014; Region II: Δα = 0.15–0.54; Transition*: Δα = 0.55–0.73; Region III: Δα = 0.74–0.99).</p>
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<p>Model-based TG-signal fits to experimental data, based on the proposed p:, model scheme, at the various heating rates, for thermal decomposition of CBA-TB (<span class="html-italic">colored symbols</span>: experimental data points; <span class="html-italic">colored solid lines</span>: model-based results (R<sup>2</sup> = 0.99968)) (NETZSCH Kinetics Neo software image extracted (Product version 2.7.3.15, Build date 6 November 2024)).</p>
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<p>Normalized concentration species evolution with the temperature, for every reaction step in the proposed p:, model scheme at the heating rates of 10.3 K/min, 20.9 K/min and 32.1 K/min (NETZSCH Kinetics Neo software image extracted (Product version 2.7.3.15, Build date: 6 November 2024)).</p>
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<p>Reaction rate curves (1/s) vs. the temperature (°C) for all CBA-TB decomposition steps described by p, model scheme, which is determined using the model-based kinetic approach at the different heating rates (NETZSCH Kinetics Neo software image extracted (Product version 2.7.3.15, Build date 6 November 2024)).</p>
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<p>α = α(<span class="html-italic">t</span>) adiabatic conversion curves for CBA-TB thermal decomposition after 24 h, obtained for: (<b>a</b>) Friedman, (<b>b</b>) Numerical, and (<b>c</b>) p:, models, respectively (<span class="html-italic">full colored line</span>—calorimeter measurement/experimental signal; <span class="html-italic">dash colored line</span>—simulated signal to time to the maximum reaction rate, e.g., 24 h) (NETZSCH Kinetics Neo software images extracted (Product version 2.7.3.15, Build date 6 November 2024)).</p>
Full article ">Figure 11 Cont.
<p>α = α(<span class="html-italic">t</span>) adiabatic conversion curves for CBA-TB thermal decomposition after 24 h, obtained for: (<b>a</b>) Friedman, (<b>b</b>) Numerical, and (<b>c</b>) p:, models, respectively (<span class="html-italic">full colored line</span>—calorimeter measurement/experimental signal; <span class="html-italic">dash colored line</span>—simulated signal to time to the maximum reaction rate, e.g., 24 h) (NETZSCH Kinetics Neo software images extracted (Product version 2.7.3.15, Build date 6 November 2024)).</p>
Full article ">Figure 11 Cont.
<p>α = α(<span class="html-italic">t</span>) adiabatic conversion curves for CBA-TB thermal decomposition after 24 h, obtained for: (<b>a</b>) Friedman, (<b>b</b>) Numerical, and (<b>c</b>) p:, models, respectively (<span class="html-italic">full colored line</span>—calorimeter measurement/experimental signal; <span class="html-italic">dash colored line</span>—simulated signal to time to the maximum reaction rate, e.g., 24 h) (NETZSCH Kinetics Neo software images extracted (Product version 2.7.3.15, Build date 6 November 2024)).</p>
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11 pages, 950 KiB  
Article
Analysis of Copper and Lead in Aerosols with Laser-Induced Breakdown Spectroscopy
by Daniel Diaz, Alejandra Carreon and David W. Hahn
Photonics 2024, 11(12), 1112; https://doi.org/10.3390/photonics11121112 (registering DOI) - 25 Nov 2024
Abstract
Laser-induced breakdown spectroscopy (LIBS) was applied to the analysis of aerosolized Cu- and Pb-bearing particles generated from aqueous solutions. A nitrogen-driven nebulizer was utilized to aerosolize Cu- and Pb-spiked solutions. The liquid matrix of the aqueous droplets was evaporated before the LIBS analysis, [...] Read more.
Laser-induced breakdown spectroscopy (LIBS) was applied to the analysis of aerosolized Cu- and Pb-bearing particles generated from aqueous solutions. A nitrogen-driven nebulizer was utilized to aerosolize Cu- and Pb-spiked solutions. The liquid matrix of the aqueous droplets was evaporated before the LIBS analysis, and the remaining gas-phase analyte-rich aerosols were analyzed in a LIBS system that featured a 1064 nm Nd:YAG laser, a Czerny–Turner spectrometer, and an ICCD camera. The Cu and Pb concentrations in the aerosol streams were 0.26–1.29 ppm and 0.40–1.19 ppm, respectively. Laser diffraction and the particle size distributions of the aqueous aerosols were obtained to indirectly demonstrate the evaporation of the liquid matrix. Highly linear calibration curves (R2 = 0.995 for Cu and R2 = 0.987 for Pb) and acceptable limits of detection (2 ppb for Cu and 9 ppb for Pb) and quantification (5 ppb and 28 ppb) were obtained. The applications of the presented methodology include the near-real-time and in situ analysis of wastewater and gas-phase aerosols contaminated with heavy metals. Full article
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<p>Scheme of LIBS and aerosol generation systems. L1 and L2: plano-convex lenses; PM: pierced mirror.</p>
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<p>Particle size distribution of water aerosols obtained at the outlet of the nebulizer (dots, continuous line) and at the outlet of the generator (squares, dashed line).</p>
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<p>Spectral and calibration curves. (<b>a</b>) Cu I emission line for various concentrations; (<b>b</b>) Cu calibration curve (dashed dot) and confidence bands (dashed line); (<b>c</b>) Pb I emission line for various concentrations; (<b>d</b>) Pb calibration curve (dashed dot) and confidence bands (dashed line). Error bars represent one standard deviation.</p>
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23 pages, 9398 KiB  
Article
Analysis of the Effect of Structural Parameters on the Internal Flow Field of Composite Curved Inlet Body Hydrocyclone
by Yanchao Wang, Hu Han, Zhitao Liang, Huanbo Yang, Feng Li, Wen Zhang and Yanrui Zhao
Processes 2024, 12(12), 2654; https://doi.org/10.3390/pr12122654 (registering DOI) - 25 Nov 2024
Abstract
To enhance the classification efficiency of hydrocyclones, this study introduces a novel hydrocyclone design featuring a composite curved-inlet-body structure. Through numerical simulations, the internal flow field characteristics of this structure are thoroughly investigated. The results reveal several key findings: when the diameter of [...] Read more.
To enhance the classification efficiency of hydrocyclones, this study introduces a novel hydrocyclone design featuring a composite curved-inlet-body structure. Through numerical simulations, the internal flow field characteristics of this structure are thoroughly investigated. The results reveal several key findings: when the diameter of the overflow tube is reduced below a critical threshold, the axial velocity exhibits predominantly downward movement within the outer cyclone, accompanied by substantial recirculation, leading to a loss of effective separation. Moreover, both static pressure and tangential velocity are largely independent of the insertion depth of the overflow tube. In contrast, the diameter of the bottom flow opening plays a crucial role in determining flow dynamics within the hydrocyclone. An excessively large or small bottom opening leads to flow instabilities, causing fluctuations that disrupt the uniformity of the flow field. Additionally, a small height-to-diameter ratio exacerbates flow instability, increasing turbulence intensity and resulting in irregular fluctuations in the LZVV. These findings provide important theoretical insights for the design of more efficient hydrocyclone separation structures. Full article
(This article belongs to the Special Issue Fault Diagnosis Process and Evaluation in Systems Engineering)
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<p>Hydrohydrocyclone 3D structure (<b>a</b>) and meshing (<b>b</b>).</p>
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<p>Verification of mesh independence.</p>
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<p>Validation of the numerical simulation for the flow field. Z = 120 mm.</p>
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<p>Variation in static pressure with the vortex finder diameters. (<b>a</b>) Z = 80 mm; (<b>b</b>) Z = 120 mm; (<b>c</b>) Z = 180 mm; (<b>d</b>) Z = 220 mm.</p>
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<p>Variation in pressure drop and split ratio with vortex finder diameter.</p>
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<p>Variation in pressure efficiency with vortex finder diameter.</p>
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<p>Variation in tangential velocity with different vortex finder diameters. (<b>a</b>) Z = 80 mm; (<b>b</b>) Z = 120 mm; (<b>c</b>) Z = 180 mm; (<b>d</b>) Z = 220 mm.</p>
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<p>Variation in tangential velocity with different vortex finder diameters. (<b>a</b>) Z = 80 mm; (<b>b</b>) Z = 120 mm; (<b>c</b>) Z = 180 mm; (<b>d</b>) Z = 220 mm.</p>
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<p>Variation in axial velocity with different vortex finder diameters. (<b>a</b>) Z = 80 mm; (<b>b</b>) Z = 120 mm; (<b>c</b>) Z = 180 mm; (<b>d</b>) Z = 220 mm.</p>
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<p>LZVV under different vortex finder diameters.</p>
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<p>Effect of vortex finder diameter on turbulent kinetic energy.</p>
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<p>Variation in static pressure with different insertion depths of vortex finder. (<b>a</b>) Z = 80 mm; (<b>b</b>) Z = 120 mm; (<b>c</b>) Z = 180 mm; (<b>d</b>) Z = 220 mm.</p>
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<p>Variation in pressure drop and split ratio.</p>
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<p>Variation in pressure efficiency.</p>
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<p>Variation in tangential velocity with insertion depth of vortex finder. (<b>a</b>) Z = 80 mm; (<b>b</b>) Z = 120 mm; (<b>c</b>) Z = 180 mm; (<b>d</b>) Z = 220 mm.</p>
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<p>Variation in axial velocity with insertion depth of vortex finder. (<b>a</b>) Z = 80 mm; (<b>b</b>) Z = 120 mm; (<b>c</b>) Z = 180 mm; (<b>d</b>) Z = 220 mm.</p>
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<p>Variation in LZVV with the different insertion depths of vortex finder.</p>
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<p>Variation in turbulent kinetic energy with insertion depth of vortex finder.</p>
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<p>Variation in static pressure with apex diameter. (<b>a</b>) Z = 80 mm; (<b>b</b>) Z = 120 mm; (<b>c</b>) Z = 180 mm; (<b>d</b>) Z = 220 mm.</p>
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<p>Variation in pressure drop and split ratio with apex diameter.</p>
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<p>Variation in pressure efficiency with apex diameter.</p>
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<p>Variation in tangential velocity with apex diameter. (<b>a</b>) Z = 80 mm; (<b>b</b>) Z = 120 mm; (<b>c</b>) Z = 180 mm; (<b>d</b>) Z = 220 mm.</p>
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<p>Variation in axial velocity with apex diameter. (<b>a</b>) Z = 80 mm; (<b>b</b>) Z = 120 mm; (<b>c</b>) Z = 180 mm; (<b>d</b>) Z = 220 mm.</p>
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<p>Variation in LZVV under different apex diameters.</p>
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<p>Variation in outlet velocity change rate with apex diameter.</p>
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<p>Variation in static pressure with aspect ratio. (<b>a</b>) Z = 80 mm; (<b>b</b>) Z = 120 mm; (<b>c</b>) Z = 180 mm; (<b>d</b>) Z = 220 mm.</p>
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<p>Variation in pressure drop and split ratio with aspect ratio.</p>
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<p>Variation in pressure efficiency with aspect ratio.</p>
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<p>Variation in tangential velocity with aspect ratio. (<b>a</b>) Z = 80 mm; (<b>b</b>) Z = 120 mm; (<b>c</b>) Z = 180 mm; (<b>d</b>) Z = 220 mm.</p>
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<p>Variation in axial velocity with aspect ratio. (<b>a</b>) Z = 80 mm; (<b>b</b>) Z = 120 mm; (<b>c</b>) Z = 180 mm; (<b>d</b>) Z = 220 mm.</p>
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<p>Variation in LZVV under different aspect ratios.</p>
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<p>Variation in turbulent kinetic energy with aspect ratio.</p>
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17 pages, 39615 KiB  
Review
The Need for Standards in Evaluating the Quality of Electronic Health Records and Dental Records: A Narrative Review
by Varadraj P. Gurupur, Giang Vu, Veena Mayya and Christian King
Big Data Cogn. Comput. 2024, 8(12), 168; https://doi.org/10.3390/bdcc8120168 (registering DOI) - 25 Nov 2024
Abstract
Over the past two decades, there has been an enormous growth in the utilization of electronic health records (EHRs). However, the adoption and use of EHRs vary widely across countries, healthcare systems, and individual facilities. This variance poses several challenges for seamless communication [...] Read more.
Over the past two decades, there has been an enormous growth in the utilization of electronic health records (EHRs). However, the adoption and use of EHRs vary widely across countries, healthcare systems, and individual facilities. This variance poses several challenges for seamless communication between systems, leading to unintended consequences. In this article, we outline the primary factors and issues arising from the absence of standards in EHRs and dental record implementation, underscoring the need for global standards in this area. We delve into various scenarios and concepts that emphasize the necessity of global standards for healthcare systems. Additionally, we explore the adverse outcomes stemming from the absence of standards, as well as the missed opportunities within the healthcare ecosystem. Our discussions provide key insights on the impacts of the lack of standardization. Full article
(This article belongs to the Special Issue Applied Data Science for Social Good)
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<p>A schematic representation of a standard EHR.</p>
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<p>A schematic representation of common dimensions of data quality in EHRs [<a href="#B4-BDCC-08-00168" class="html-bibr">4</a>,<a href="#B5-BDCC-08-00168" class="html-bibr">5</a>].</p>
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<p>A conceptual model for ensuring data completeness in EHRs [<a href="#B6-BDCC-08-00168" class="html-bibr">6</a>].</p>
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<p>A schematic representation of features of a successful learning healthcare system.</p>
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<p>Percentage of missing values in the eICU research database [<a href="#B55-BDCC-08-00168" class="html-bibr">55</a>].</p>
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10 pages, 6222 KiB  
Article
Waste Polyethylene Terephthalate (PET) as a Partial Replacement of Aggregates in Sustainable Concrete
by Lukman Abubakar, Nusrat Yeasmin and Arjak Bhattacharjee
Constr. Mater. 2024, 4(4), 738-747; https://doi.org/10.3390/constrmater4040040 (registering DOI) - 25 Nov 2024
Abstract
Concrete use is enhanced daily due to infrastructure development, but it has adverse impacts on the environment. Modern lifestyles have led to the increased use of plastic, and, for households, polyethylene terephthalate (PET) plastics are used. However, PET is non-biodegradable and causes adverse [...] Read more.
Concrete use is enhanced daily due to infrastructure development, but it has adverse impacts on the environment. Modern lifestyles have led to the increased use of plastic, and, for households, polyethylene terephthalate (PET) plastics are used. However, PET is non-biodegradable and causes adverse impacts on the environment and marine health. So, there is a need to minimize the amount of plastic waste by finding an alternative use for the waste. Our study focuses on creating sustainable concrete by utilizing PET-based plastic waste as a partial substitution for aggregates, aiming to use this concrete for various low-load-bearing construction applications. From our phase analysis study, no adverse effects were found on cement phase formation. We also found that up to 10 wt.% PET incorporation leads to acceptable compressive strength reduction as per ASTM guidelines. To enhance adhesion, the PET was roughened, and, from FESEM, we found effective adhesion of PET waste into the cement matrix. We believe that this sustainable concrete will not only contribute to waste reduction but also promote eco-friendly construction material development. Full article
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<p>(<b>a</b>) PET waste after shredding. (<b>b</b>) concrete sample preparation with PET as a partial.</p>
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<p>Process schematic of partially PET substituted concrete sample preparation followed by compressive strength assessment.</p>
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<p>(<b>a</b>) Density plot of concrete samples, (<b>b</b>) Compressive strength plot of concrete samples, (<b>c</b>,<b>d</b>) image of concrete sample before and after failure during compression test.</p>
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<p>(<b>a</b>) FTIR Plot of Concrete and Concrete + PET, (<b>b</b>) XRD plot of concrete and concrete + PET.</p>
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<p>(<b>a</b>,<b>b</b>) SEM images showing PET aggregate in concrete matrix.</p>
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13 pages, 2353 KiB  
Article
OsFBN6 Enhances Brown Spot Disease Resistance in Rice
by Fang-Yuan Cao, Yuting Zeng, Ah-Rim Lee, Backki Kim, Dongryung Lee, Sun-Tae Kim and Soon-Wook Kwon
Plants 2024, 13(23), 3302; https://doi.org/10.3390/plants13233302 (registering DOI) - 25 Nov 2024
Abstract
Brown spot (BS) is caused by necrotrophs fungi Cochliobolus miyabeanus (C. miyabeanus) which affects rainfed and upland production in rice, resulting in significant losses in yield and grain quality. Here, we explored the meJA treatment that leads to rice resistance to [...] Read more.
Brown spot (BS) is caused by necrotrophs fungi Cochliobolus miyabeanus (C. miyabeanus) which affects rainfed and upland production in rice, resulting in significant losses in yield and grain quality. Here, we explored the meJA treatment that leads to rice resistance to BS. Fibrillins (FBNs) family are constituents of plastoglobules in chloroplast response to biotic and abiotic stress, many research revealed that OsFBN1 and OsFBN5 are not only associated with the rice against disease but also with the JA pathway. The function of FBN6 was only researched in the Arabidopsis. We revealed gene expression levels of OsFBN1, OsFBN5, OsFBN6 and the JA pathway synthesis first specific enzyme OsAOS2 following infection with C. miyabeanus, OsAOS2 gene expression showed great regulation after C. miyabeanus and meJA treatment, indicating JA pathway response to BS resistance in rice. Three FBN gene expressions showed different significantly regulated modes in C. miyabeanus and meJA treatment. The haplotype analysis results showed OsFBN1 and OsFBN5 the diverse Haps significant with BS infection score, and the OsFBN6 showed stronger significance (**** p < 0.0001). Hence, we constructed OsFBN6 overexpression lines, which showed more resistance to BS compared to the wild type, revealing OsFBN6 positively regulated rice resistance to BS. We developed OsFBN6 genetic markers by haplotype analysis from 130 rice varieties according to whole-genome sequencing results, haplotype analysis, and marker development to facilitate the screening of BS-resistant varieties in rice breeding. The Caps marker developed by Chr4_30690229 can be directly applied to the breeding application of screening rice BS-resistant varieties. Full article
(This article belongs to the Special Issue Disease Resistance Breeding of Field Crops)
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<p>(<b>A</b>) The structure of <span class="html-italic">C. miyabeanus 36</span> conidia. (<b>B</b>) The phenotype of R and S lines inoculated with <span class="html-italic">C. miyabeanus</span> and meJA. (<b>C</b>–<b>F</b>) Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) measurements of <span class="html-italic">OsFBN6</span>, <span class="html-italic">OsFBN1</span>, <span class="html-italic">OsFBN5</span>, and <span class="html-italic">OsAOS2</span> in rice leaves infected with <span class="html-italic">C. miyabeanus</span> and meJA. CK, control group; (<span class="html-italic">n</span> = 3, Student’s <span class="html-italic">t</span>-test; *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Haplotype analysis. (<b>A</b>) Schematic of gene structure and positions of SNPs in <span class="html-italic">OsFBN6</span>. Red arrows indicate SNP sites in the gene region. The average indicates the mean of BS infection scores of all varieties in each haplotype. The subset for α = 0.01 represents a very significant level of difference average of infection in each group. The blue squares represent mutant SNPS in each haplotype. (<b>B</b>) Haplotype network analysis in <span class="html-italic">OsFBN6</span>. Different colors indicate each rice subspecies, and the circle size represents the number of varieties in each haplotype. (<b>C</b>–<b>E</b>) The violin plot of BS infection score distribution for all varieties in each haplotype in <span class="html-italic">OsFBN6</span>, <span class="html-italic">OsFBN1</span> and <span class="html-italic">OsFBN5</span>. The dashed line represents the median, and n = the number of varieties in each haplotype. Statistical analysis finished by ANOVA and Duncan’s test, the asterisk represents the significant level at; **, <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>Marker designing. (<b>A</b>) Each haplotype has a different allele between wild and mutant lines in three SNP positions. Mutant alleles are color-coded. (<b>B</b>) The primer list of the markers: Arms primer has two pairs, and Caps primer has 1 pair with an SspI-cutting site.</p>
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<p>Results of agarose gel electrophoresis. (<b>A</b>) The DNA fragments were amplified using Arms primers. (<b>B</b>) The DNA fragments were amplified using Caps primers. Mutant alleles are bold numbers.</p>
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<p>Functional identification of the <span class="html-italic">OsFBN6</span> overexpression lines. (<b>A</b>) Structure and schematic diagram of the plasmid. (<b>B</b>) WT and OE line phenotypes infected with <span class="html-italic">C. miyabeanus</span>. (<b>C</b>) The reverse transcription-quantitative polymerase chain reaction (RT-qPCR) measurements of the WT and OE line gene expressions in rice leaves infected with <span class="html-italic">C. miyabeanus.</span> (<b>D</b>) Lesion-relative area and amounts of WT and OE lines inoculated with <span class="html-italic">C. miyabeanus</span>. The value of the red dot represents the relative proportion of the leaf area of each spot; the number represents the number of spots, and the bars represent the average of all spots. Statistical analysis finished by ANOVA and Duncan’s test, the asterisk represents the significant level at *, <span class="html-italic">p</span> &lt; 0.05. (<b>E</b>) The total lesion relative area of infection with <span class="html-italic">C. miyabeanus</span> (<span class="html-italic">n</span> = 3, Student’s <span class="html-italic">t</span>-test; *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01).</p>
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30 pages, 3560 KiB  
Review
Resistance to Tyrosine Kinase Inhibitors in Hepatocellular Carcinoma (HCC): Clinical Implications and Potential Strategies to Overcome the Resistance
by Ali Gawi Ermi and Devanand Sarkar
Cancers 2024, 16(23), 3944; https://doi.org/10.3390/cancers16233944 (registering DOI) - 25 Nov 2024
Abstract
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide, and the development of effective treatment strategies remains a significant challenge in the management of advanced HCC patients. The emergence of tyrosine kinase inhibitors (TKIs) has been a significant advancement in the [...] Read more.
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide, and the development of effective treatment strategies remains a significant challenge in the management of advanced HCC patients. The emergence of tyrosine kinase inhibitors (TKIs) has been a significant advancement in the treatment of HCC, as these targeted therapies have shown promise in prolonging the survival of patients with advanced disease. Although immunotherapy is currently considered as the first line of treatment for advanced HCC patients, many such patients do not meet the clinical criteria to be eligible for immunotherapy, and in many parts of the world there is still lack of accessibility to immunotherapy. As such, TKIs still serve as the first line of treatment and play a major role in the treatment repertoire for advanced HCC patients. However, the development of resistance to these agents is a major obstacle that must be overcome. In this review, we explore the underlying mechanisms of resistance to TKIs in HCC, the clinical implications of this resistance, and the potential strategies to overcome or prevent the emergence of resistance. Full article
(This article belongs to the Special Issue Liver Cancer: Improving Standard Diagnosis and Therapy: 2nd Edition)
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<p>Mechanism of receptor tyrosine kinase (RTK) activation. Created in <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p>Cartoon showing common tyrosine kinase receptors and their downstream signaling pathways. Created in <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p>Chemical structures of commonly used TKIs approved by the FDA for treatment of HCC. Created in <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p>Schematic of m6A RNA modification and its contribution to resistance to TKIs. See text for details. Created in <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p>Schematic of metabolic changes contributing to resistance to TKIs. See text for details. Created in <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p>Important mechanisms of TKI resistance and strategies to overcome them. Please see text for details. Created in <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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19 pages, 3626 KiB  
Article
Unravelling the Signature Follicular Fluid Metabolites in Dairy Cattle Follicles Growing Under Negative Energy Balance: An In Vitro Approach
by Muhammad Shahzad, Jianhua Cao, Hubdar Ali Kolachi, Jesse Oluwaseun Ayantoye, Zhou Yu, Yifan Niu, Pengcheng Wan and Xueming Zhao
Int. J. Mol. Sci. 2024, 25(23), 12629; https://doi.org/10.3390/ijms252312629 (registering DOI) - 25 Nov 2024
Abstract
The astringent selection criteria for milk-oriented traits in dairy cattle have rendered these animals prone to various metabolic disorders. Postpartum lactational peak and reduced feed intake lead to negative energy balance in cattle. As a compensatory mechanism, cattle start mobilizing fat reserves to [...] Read more.
The astringent selection criteria for milk-oriented traits in dairy cattle have rendered these animals prone to various metabolic disorders. Postpartum lactational peak and reduced feed intake lead to negative energy balance in cattle. As a compensatory mechanism, cattle start mobilizing fat reserves to meet the energy demand for vital body functions. Consequently, diminished glucose concentrations and elevated ketone body levels lead to poor ovarian function. The impaired follicular development and subpar oocyte quality diminish the conception rates, which poses significant economic repercussions. Follicular fluid is integral to the processes of follicular growth and oocyte development. Hence, the present study was performed to identify potential alterations in metabolites in the follicular fluid under in vitro culture conditions mimicking negative energy balance. Our results revealed nine distinct metabolites exhibiting differential expression in follicular fluid under negative energy balance. The differentially expressed metabolites were predominantly associated with pathways related to amino acid metabolism, lipid metabolism, signal transduction mechanisms, and membrane transport, alongside other biological processes. The identified signature metabolites may be further validated to determine oocyte fitness subjected to in vitro fertilization or embryo production from slaughterhouse source ovaries. Full article
(This article belongs to the Section Molecular Endocrinology and Metabolism)
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<p>Chromatogram illustrates the total ion current (TIC) with respect to the retention time of metabolite in QC samples both in positive/+ (<b>A</b>) and negative (<b>B</b>) ions of electrospray ionization (ESI) modes. The signal intensity is displayed on the <span class="html-italic">y</span>-axis in million counts, and the retention time is displayed on the <span class="html-italic">x</span>-axis in min. The QC1, QC2, and QC3 are represented by the colors blue, pink, and red in the spectrum, respectively.</p>
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<p>PCA of differential metabolites in follicular fluid from dairy cows under different metabolic states. (<b>A</b>) PCA plot illustrates metabolite distribution in positive ion samples. (<b>B</b>) PCA plot displaying metabolite profiles from negative ion metabolites. Green squares represent NEB metabolites, blue circles represent PEB metabolites, and pink triangles represent QC. The <span class="html-italic">x</span> and <span class="html-italic">y</span> axis show the first two principal components (PC1 and PC2) which explain the greatest variance in the data. The label “t[1]” on the <span class="html-italic">x</span>-axis represents the first principal component (PC1) of the Principal Component Analysis (PCA).</p>
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<p>The figure shows correlation profiles of QC samples in metabolomic analysis of FF from dairy cows. (<b>A</b>) Correlation matrix for positive ion mode QC samples. (<b>B</b>) Correlation matrix for negative ion mode QC samples. Each subplot represents pairwise comparisons between three QC samples (QC-1, QC-2, QC-3), with correlation coefficients shown in blue. The high correlation coefficients (≥0.998) indicate strong reproducibility and stability of the metabolomic measurements across both ionization modes.</p>
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<p>Distribution of metabolite classes (colors) identified in FF of dairy cows. The pie chart illustrates the relative proportions of various metabolite classes, expressed as percentages (%).</p>
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<p>Volcano plots show the differential metabolite expression in FF under NEB and PEB. (<b>A</b>) Positive ion mode and (<b>B</b>) negative ion mode metabolite profiles. The <span class="html-italic">x</span>-axis represents log2 FC. The <span class="html-italic">y</span>-axis shows −log10 of <span class="html-italic">p</span>-value. Different color dots represent metabolites that were significantly upregulated (red), significantly downregulated (blue), and with no significant change (grey). The fold change (FC) threshold is represented by vertical dotted lines, whereas the significance threshold is represented by the horizontal dotted line (<span class="html-italic">p</span>-value).</p>
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<p>Heatmap showing hierarchical clustering of differentially expressed metabolites in FF NEB and PEB groups. (<b>A</b>) Metabolites detected in positive ion mode. (<b>B</b>) Metabolites detected in negative ion mode. The color scale denotes the relative abundance of metabolites, with red indicating higher levels and blue indicating lower levels. Each horizontal row represents a distinct metabolite, and each vertical column represents a sample (NEB-A, NEB-B, NEB-C, PEB-A, PEB-B, PEB-C). The dendrograms on the left-hand side represent the hierarchical clustering of metabolites based on their expression patterns.</p>
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<p>KEGG pathway enrichment analysis of differentially expressed metabolites in FF of dairy cattle under varying energy balance conditions. (<b>A</b>) The bubble plot represents the enriched pathways. The <span class="html-italic">x</span>-axis gauges the rich factor (ratio of differentially expressed metabolites in a pathway to the total metabolites in that pathway). The <span class="html-italic">y</span>-axis enlists the enriched KEGG pathways. The bubble size indicates the number of metabolites, and the color represents the significance level (−log10 (<span class="html-italic">p</span>-value)). (<b>B</b>) Bar plot of the same enriched pathways, where the <span class="html-italic">x</span>-axis shows the number of compounds involved in each pathway, and bars are colored according to <span class="html-italic">p</span>-value significance.</p>
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<p>Schematic diagram of the experiment illustrating follicle enucleation, diameter measurement, culturing, FF collection, and metabolite analysis.</p>
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19 pages, 4936 KiB  
Review
Progress in Flexible and Wearable Lead-Free Polymer Composites for Radiation Protection
by Shouying Wu, Wei Zhang and Yumin Yang
Polymers 2024, 16(23), 3274; https://doi.org/10.3390/polym16233274 (registering DOI) - 25 Nov 2024
Abstract
The rapid development of nuclear technology has brought convenience to medical, industrial, and military fields. However, long-term exposure to a radiation environment with high energy will result in irreversible damage, especially to human health. Traditional lead-based radiation protection materials are heavy, inflexible, inconvenient [...] Read more.
The rapid development of nuclear technology has brought convenience to medical, industrial, and military fields. However, long-term exposure to a radiation environment with high energy will result in irreversible damage, especially to human health. Traditional lead-based radiation protection materials are heavy, inflexible, inconvenient for applications, and could lead to toxicity hazards and environmental problems. Therefore, it has become a mainstream topic to produce high-performance shielding materials that are lightweight, flexible, and wearable. Polymer composites are less dense and have excellent flexibility and processability, drawing great interest from researchers worldwide. Many attempts have been made to blend functional particles and polymeric matrix to produce flexible and wearable protection composites. This paper presents an extensive overview of the current status of studies on lead-free polymer composites as flexible and wearable protection materials. First, novel functional particles and polymer matrices are discussed, and recent results with potential applications are summarised. In addition, novel strategies for preparing polymeric shielding materials and their respective radiation shielding properties are analyzed. Finally, directions for developing lead-free polymeric shielding materials are indicated, and it is beneficial to provide additional references for obtaining flexible, lightweight, and high-performance wearable shielding materials. Full article
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<p>(<b>A</b>) Structure of NL. (<b>B</b>) Fabrication of Bi/Ce-NL. (<b>C</b>) Attenuation efficiency of the Bi/Ce-NL. (<b>A</b>–<b>C</b>) Reprinted with permission from Ref. [<a href="#B33-polymers-16-03274" class="html-bibr">33</a>]. Copyright 2020, Elsevier. (<b>D</b>) Structure design of Bi<sub>2</sub>O<sub>3</sub>/Gd<sub>2</sub>O<sub>3</sub> janus nanofiber membranes. (<b>E</b>) Shielding efficiency of Bi<sub>2</sub>O<sub>3</sub>/Gd<sub>2</sub>O<sub>3</sub> janus nanofiber membranes. (<b>D</b>,<b>E</b>) Reprinted with permission from Ref. [<a href="#B56-polymers-16-03274" class="html-bibr">56</a>]. Copyright 2023, John Wiley and Sons.</p>
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<p>(<b>A</b>) Schematic illustration of fabricating BCMBG aerogels. (<b>B</b>) Shielding mechanism. (<b>A</b>,<b>B</b>) Reprinted with permission from Ref. [<a href="#B70-polymers-16-03274" class="html-bibr">70</a>]. Copyright 2024, Elsevier.</p>
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<p>(<b>A</b>) Schematic image of BTO. (<b>B</b>) The interaction between X-rays and BTO-ER materials. (<b>C</b>) Mass attenuation coefficient. (<b>D</b>) Comparison of X-ray transmission between pure Pb Film and BTO-ER. (<b>A</b>–<b>D</b>) Reprinted with permission from Ref. [<a href="#B32-polymers-16-03274" class="html-bibr">32</a>]. Copyright 2021, American Chemical Society.</p>
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<p>(<b>A</b>) The preparation of the BiINP-LM. (<b>B</b>) SEM of BiINP-LM. (<b>C</b>) Mass attenuation coefficients of BiINP-LM, and shallow circles were 0.25 mm Pb lead apron. (<b>D</b>) X-ray shielding performances (orange was 1.00 mm BiINP-LM, gray and blue were lead plate and lead apron, respectively). (<b>A</b>–<b>D</b>) Reprinted with permission from Ref. [<a href="#B91-polymers-16-03274" class="html-bibr">91</a>]. Copyright 2020, American Chemical Society.</p>
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<p>Preparation and shielding mechanism of BSCM. Reprinted with permission from Ref. [<a href="#B35-polymers-16-03274" class="html-bibr">35</a>] Copyright 2019, Elsevier.</p>
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<p>(<b>A</b>) Schematic illustration of sandwiched Pb-free radiation protection fabric. (<b>B</b>) Thickness of SL-PES-PDMS/BTO. (<b>C</b>) Flexibility of SL-PES-PDMS/BTO (<b>D</b>) Mass attenuation coefficients of SL-PES-PDMS/BTO. (<b>A</b>–<b>D</b>) Reprinted with permission from Ref. [<a href="#B104-polymers-16-03274" class="html-bibr">104</a>]. Copyright 2022, Elsevier.</p>
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<p>Digital photos and SEM images of W-PU composite nanofiber mats. Reprinted with permission from Ref. [<a href="#B113-polymers-16-03274" class="html-bibr">113</a>]. Copyright 2021, John Wiley and Sons.</p>
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<p>(<b>A</b>) Morphologies of BGAs. (<b>B</b>) X-ray shielding process of BGAs. (<b>C</b>) Fabrication process of the BGAs. (<b>D</b>) BGAs standing on a dandelion. (<b>A</b>–<b>D</b>) Reprinted with permission from Ref. [<a href="#B118-polymers-16-03274" class="html-bibr">118</a>]. Copyright 2023, American Chemical Society.</p>
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27 pages, 1792 KiB  
Article
Integrating Digitalization and Asset Health Index for Strategic Life Cycle Cost Analysis of Power Converters
by Vicente González-Prida, Antonio de la Fuente Carmona, Antonio J. Guillén López, Juan F. Gómez Fernández and Adolfo Crespo Márquez
Information 2024, 15(12), 749; https://doi.org/10.3390/info15120749 (registering DOI) - 25 Nov 2024
Abstract
In the context of energy storage systems, optimizing the life cycle of power converters is crucial for reducing costs, making informed decisions, and ensuring sustainability. This study presents a comprehensive methodology for calculating the life cycle cost (LCC) of power converters, employing a [...] Read more.
In the context of energy storage systems, optimizing the life cycle of power converters is crucial for reducing costs, making informed decisions, and ensuring sustainability. This study presents a comprehensive methodology for calculating the life cycle cost (LCC) of power converters, employing a nine-step process that integrates digitalization, Internet of Things (IoT) technologies, and the Asset Health Index (AHI). The methodology adapts the Woodward model to provide a detailed cost analysis, encompassing the acquisition, operation, maintenance, and end-of-life phases. Our findings reveal significant insights into asset management, highlighting the importance of preventive and major maintenance in controlling failure rates and extending asset life. This study concludes that adopting sustainable business models and leveraging advanced technologies can enhance the reliability and maintainability of power converters, ultimately leading to more competitive and environmentally friendly energy storage solutions. Full article
(This article belongs to the Special Issue New Applications in Multiple Criteria Decision Analysis II)
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<p>Maintenance management process model [<a href="#B2-information-15-00749" class="html-bibr">2</a>].</p>
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<p>Outline of the proposed procedure.</p>
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<p>Cost estimation scheme according to the timing of the study.</p>
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<p>Process for obtaining the health index.</p>
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<p>Costs breakdown evolution.</p>
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23 pages, 4959 KiB  
Article
Microtubule Association of EML4–ALK V3 Is Key for the Elongated Cell Morphology and Enhanced Migration Observed in V3 Cells
by Savvas Papageorgiou, Sarah L. Pashley, Laura O’Regan, Kees R. Straatman and Andrew M. Fry
Cells 2024, 13(23), 1954; https://doi.org/10.3390/cells13231954 (registering DOI) - 25 Nov 2024
Abstract
The EML4–ALK oncogene drives tumour progression in approximately 5% of cases of non-small-cell lung cancers. At least 15 EML4–ALK variants have been identified, which elicit differential responses to conventional ALK inhibitors. Unfortunately, most, if not all, patients eventually acquire resistance to these inhibitors [...] Read more.
The EML4–ALK oncogene drives tumour progression in approximately 5% of cases of non-small-cell lung cancers. At least 15 EML4–ALK variants have been identified, which elicit differential responses to conventional ALK inhibitors. Unfortunately, most, if not all, patients eventually acquire resistance to these inhibitors and succumb to the disease, which warrants the need for alternative targets to be identified. The most aggressive variant, EML4–ALK variant 3 (V3), assembles into a complex on interphase microtubules together with the NEK9 and NEK7 kinases, which leads to the downstream phosphorylation of NEK7 substrates. Overall, this promotes an elongated cell morphology and an enhanced migratory phenotype, which likely contributes to the increased metastasis often seen in V3 patients. Here, using two separate approaches to displace V3 from microtubules and a variety of in vitro assays, we show that microtubule association of EML4–ALK V3 is required for both V3 phenotypes, as removal of the oncogenic fusion protein from microtubules led to the dissociation of the V3–NEK9–NEK7 complex and the reversal of both phenotypic changes. Overall, we propose that targeting the interaction between EML4–ALK V3 and microtubules might offer a novel therapeutic option, independent of ALK activity, for V3+ NSCLC patients with acquired resistance to ALK inhibitors. Full article
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Figure 1

Figure 1
<p><b>Generation and characterisation of the “knocksideways” FKBP:EML4–ALK V3.</b> (<b>A</b>) Beas2B parental cells were transfected with the template bicistronic and the FKBP:EML4–ALK V3 (FKBP–V3) plasmids before being fixed and stained with antibodies against FKBP (green), mCherry (red) and MTC02 (green). Unpaired <span class="html-italic">t</span>-tests were performed to measure Manders’ co-localization (MC) coefficient (±SEM) between (<b>B</b>) FKBP and mCherry–FRB or (<b>C</b>) mCherry–FRB and MTC02. Each graph shows three replicates, and each replicate is colour-coded (n = 30 cells in total per sample population). Temp = template plasmid and ns = not significant. (<b>D</b>,<b>E</b>) Lysates were prepared for Western blot analyses with antibodies against ALK, mCherry, FKBP, EML4-NTD and GAPDH. Molecular weights (kDa) are indicated on the left. Blots are representative of three biological replicates (n = 3). Uncropped blots are indicated in the <a href="#app1-cells-13-01954" class="html-app">Supplementary Data</a>. (<b>F</b>) Beas2B parental cells were transfected with the FKBP–V3 plasmid and either left untreated or treated with 200 nM of rapamycin for 10 s, 30 s, 1 min or 5 min before being fixed and stained with antibodies against ALK (green) and mCherry (red). The experiment was performed in triplicate (n = 3), and the images shown are representative of all three replicates. (<b>A</b>–<b>F</b>). Scale = 5 μm.</p>
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<p><b>Microtubule recruitment of EML4–ALK V3 drives the development of a mesenchymal-like cell morphology.</b> (<b>A</b>) Beas2B parental cells were transfected with the “knocksideways” FKBP–V3 construct and treated with 200 nM of rapamycin for 5 min before being fixed and stained for ALK (green) and α-tubulin (purple) or mCherry (red). Scale = 5 μm. Unpaired <span class="html-italic">t</span>-tests were performed to compare Manders’ co-localization (MC) coefficients (±SEM) between (<b>B</b>) ALK and α-tubulin or (<b>C</b>) mCherry–FRB in untreated versus treated cells. The experiment was performed in triplicate, and 10 measurements were taken from each replicate (colour-coded) (n = 30 cells in total per sample population). (<b>D</b>) Transfected cells were treated with rapamycin as above before being fixed and stained for either α-tubulin (purple), ALK (yellow) or both. Scale = 50 μm. (<b>E</b>) The protrusion (μm ± SEM) and (<b>F</b>) total cell lengths (μm ± SEM) were measured, and one-way ANOVA with Tukey’s multiple comparisons tests were performed. **** <span class="html-italic">p</span> &lt; 0.0001 and ns = not significant. All experiments were performed in triplicate (n = 29 cells in total per sample population), and replicates are colour-coded. All images are representative of all replicates.</p>
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<p><b>Microtubule recruitment of EML4–ALK V3 is required for enhanced cell migration.</b> (<b>A</b>) Beas2B parental cells were transfected with the “knocksideways” FKBP–V3 construct and treated with 200 nM of rapamycin for 5 min before being subjected to live-cell imaging for 6 h. Scale = 50 μm. A single-cell tracking analysis was performed, and the (<b>B</b>) total distance covered (μm ± SEM) and (<b>C</b>) average velocity (μm/min ± SEM) were measured. One-way ANOVA with Tukey’s multiple comparisons tests were performed. The experiment was performed in triplicate (n = 30–40 cells in total per sample population), and measurements were taken from at least 10 cells per replicate (colour coded). (<b>D</b>) U2OS parental and U2OS:FKBP–V3 cells were allowed to reach 90–100% confluency before a wound was generated at the centre of the well. Cells were also treated with 200 nM of rapamycin for 2 h where appropriate before live-cell imaging for 12 h was undertaken. Scale = 150 μm. (<b>E</b>) One-way ANOVA with Tukey’s multiple comparisons tests were also performed to compare the cell-free area (μm<sup>2</sup> ± SEM) at t = 6 and t = 12 relative to the t = 0 of U2OS parental cells. (<b>F</b>) Non-linear regression lines were drawn to determine the rate of migration, and one-way ANOVA with Tukey’s multiple comparisons tests were performed to compare the rates. The comparisons shown are against the untreated sample. The experiment was performed in triplicate (n = 30 regions in total per sample population), and each replicate is colour-coded. (<b>G</b>) U2OS parental and U2OS:FKBP–V3 cells were allowed to form spheroids in ultra-low attachment plates before embedding in Matrigel and live-cell imaging, which was performed for 72 h. Cells were also treated with 200 nM of rapamycin for 2 h where appropriate prior to embedding in 2.5 mg/mL of Matrigel. Scale = 100 μm. (<b>H</b>) At 0 and 72 h post-embedding in Matrigel, the length of 8–10 invasive strands in 5 individual spheroids per condition (n = 3 experiments) was measured (μm ± SEM) and compared between untreated and rapamycin-treated cells using unpaired <span class="html-italic">t</span>-tests. **** <span class="html-italic">p</span> &lt; 0.0001 and * <span class="html-italic">p</span> = 0.0218. All images shown are representative of all replicates.</p>
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<p><b>Relocation of V3 away from microtubules results in the dissociation of the EML4–ALK V3–NEK9–NEK7 complex.</b> (<b>A</b>) Beas2B parental cells were transfected with the FKBP–V3 construct and treated with 200 nM of rapamycin for 5 min before being fixed and co-stained with antibodies against NEK9 (yellow) or NEK7 (yellow) and α-tubulin (purple). (<b>B</b>,<b>C</b>) One-way ANOVA with Tukey’s multiple comparisons tests were performed for comparing Manders’ co-localization (MC) coefficient (± SEM). (<b>D</b>) Beas2B cells, transfected as before, were fixed and co-stained for NEK9 (yellow) or NEK7 (yellow) and ALK (purple). (<b>A</b>,<b>D</b>) Scale = 5 μm. (<b>E</b>,<b>F</b>) Unpaired <span class="html-italic">t</span>-tests were performed for comparing the MC coefficients (± SEM). *** <span class="html-italic">p</span> = 0.0003 and **** <span class="html-italic">p</span> &lt; 0.0001. Experiments were performed in triplicate (n = 30 cells in total per sample population), and each replicate is colour-coded. (<b>G</b>) Beas2B cells, transfected as before, were fixed and stained for NEK7 (green) only. Scale = 10 μm. (<b>H</b>) Lysates were also collected and prepared for immunoprecipitation using anti-ALK and anti-IgG antibodies. Immunoprecipitates were analysed by Western blotting with antibodies against FKBP and NEK9. Molecular weights (kDa) are indicated on the left. Three biological replicates (n = 3) were performed, and all images and blots are representative of all replicates. Uncropped blots are indicated in the <a href="#app1-cells-13-01954" class="html-app">Supplementary Data</a>.</p>
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<p><b>Removal of EML4–ALK V3 from microtubules likely prevents the phosphorylation of Eg5 by NEK7.</b> (<b>A</b>) HeLa:aNEK7 or NEK7 KD cells were induced with 1 μg/mL of doxycycline for 72 h and transfected with the WT or TM (S134D/S144D/S146D) V3 constructs before being fixed and stained with α-tubulin or ALK (green). Scale = 25 μm. (<b>B</b>–<b>E</b>) One-way ANOVA with Tukey’s multiple comparisons tests were performed to compare protrusion lengths (μm ± SEM) and total cell lengths (μm ± SEM). (<b>F</b>) Beas2B parental cells were transfected with the FKBP–V3 construct and treated with 200 nM of rapamycin for 5 min before being fixed and co-stained with antibodies against Eg5 (yellow) and α-tubulin (purple). (<b>G</b>) One-way ANOVA with Tukey’s multiple comparisons tests were performed for comparing Manders’ co-localization (MC) coefficients (±SEM). (<b>H</b>) Beas2B parental cells were transfected with the FKBP–V3 construct and treated with rapamycin as above before being fixed and co-stained with antibodies against Eg5 (yellow) and ALK (purple). (<b>G</b>,<b>H</b>) Scale = 5 μm. (<b>I</b>) Unpaired <span class="html-italic">t</span>-tests were performed for comparing MC coefficients (±SEM). ** <span class="html-italic">p</span> = 0.0054, **** <span class="html-italic">p</span> &lt; 0.0001, ns = not significant. All experiments were repeated in triplicate (n = 30–40 cells in total per sample population), and a minimum of 10 measurements were taken per replicate (colour-coded). All images are representative of all replicates.</p>
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<p><b>Working models for the effects of microtubule recruitment of the EML4–ALK V3 protein on the V3–NEK9–NEK7 pathway</b>. (<b>A</b>) A schematic illustration demonstrating that recruitment of the V3–NEK9–NEK7 complex to microtubules leads to the phosphorylation of Eg5. Overall, this promotes a mesenchymal-like cell morphology while also enhancing the migratory potential of these cells. The addition of rapamycin leads to the relocation of V3 and NEK7 to mitochondria but not NEK9 or Eg5. This likely prevents NEK7 activation and the subsequent phosphorylation of Eg5 by NEK7, which leads to a reversal of both phenotypic changes. (<b>B</b>) A cartoon of a possible mechanism under the “knocksideways” conditions, where an interaction of EML4–ALK V3 with microtubules allows the unstructured regions between the EML4 basic region and EML4–ALK junction point to become structured, revealing a binding region for NEK9. The relocation of V3 to mitochondria following the addition of rapamycin causes that region to become unstructured again, which prevents NEK9 from binding to EML4–ALK V3.</p>
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18 pages, 4306 KiB  
Article
The Synergic Immunomodulatory Effect of Vitamin D and Chickpea Protein Hydrolysate in THP-1 Cells: An In Vitro Approach
by Ángela Alcalá-Santiago, Rocío Toscano-Sánchez, José Carlos Márquez-López, José Antonio González-Jurado, María-Soledad Fernández-Pachón, Belén García-Villanova, Justo Pedroche and Noelia María Rodríguez-Martín
Int. J. Mol. Sci. 2024, 25(23), 12628; https://doi.org/10.3390/ijms252312628 (registering DOI) - 25 Nov 2024
Abstract
Vitamin D (VD), a crucial micronutrient, regulates bone health and immune responses. Recent studies suggest that VD may confer protective effects against chronic inflammatory diseases. Additionally, plant-based peptides can show biological activities. Furthermore, the supplementation of protein hydrolysates with VD could potentially enhance [...] Read more.
Vitamin D (VD), a crucial micronutrient, regulates bone health and immune responses. Recent studies suggest that VD may confer protective effects against chronic inflammatory diseases. Additionally, plant-based peptides can show biological activities. Furthermore, the supplementation of protein hydrolysates with VD could potentially enhance the bioactivity of peptides, leading to synergistic effects. In this study, THP-1 cells were exposed to low concentrations of Lipopolysaccharide (LPS) to induce inflammation, followed by treatment with vitamin D at different concentrations (10, 25, or 50 nM) or a chickpea protein hydrolysate (“H30BIO”) supplemented with VD. The cytotoxicity of VD was evaluated using viability assay to confirm its safety. The cytokine secretion of TNF-α, IL-1β, and IL6 was assessed in the cell supernatant, and the gene expression of TNF-α, IL-1β, IL6, IL8, CASP-1, COX2, NRF2, NF-ĸB, NLRP3, CCL2, CCR2, IP10, IL10, and RANTES was quantified by qRT-PCR. Treatment with VD alone significantly decreased the expression of the pro-inflammatory genes TNF-α and IL6, as well as their corresponding cytokine levels in the supernatants. While IL-1β gene expression remained unchanged, a reduction in its cytokine release was observed upon VD treatment. No dose-dependent effects were observed. Interestingly, the combination of VD with H30BIO led to an increase in TNF-α expression and secretion in contrast with the LPS control, coupled with a decrease in IL-1β levels. Additionally, genes such as IP10, NF-κB, CCL2, COX2, NRF2, and CASP-1 exhibited notable modulation, suggesting that the combination treatment primarily downregulates NF-κB-related gene activity. This study demonstrates a synergistic interaction between VD and H30BIO, suggesting that this combination may enhance pathways involving TNF-α, potentially aiding in the resolution and modulation of inflammation through adaptive processes. These findings open new avenues for research into the therapeutic applications of enriched protein hydrolysates with VD to manage low-grade inflammatory-related conditions. Full article
(This article belongs to the Special Issue The Role of Micronutrients in Metabolic and Infectious Diseases)
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Figure 1
<p>Cell viability analysis of THP-1 cells treated with different compounds at 24 and 48 h. The graph shows the 24 h viability of THP-1 cells treated with various concentrations of VD (1–50 nM) (<b>A</b>) and 48 h viability at the same concentrations for VD (<b>B</b>). Data are expressed as the mean (percentage of absorbance compared with that obtained in the control (non-treated cells)) ± SD, and different letters (a,b) were assigned in the multiple comparison test across all groups, indicating significant differences in a <span class="html-italic">p</span> value &lt; 0.05, <span class="html-italic">n</span> ≥ 4. DC corresponds to the dead cells control and LC to the live cells control.</p>
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<p>Pro-inflammatory cytokines and genes in LPS-induced inflammation THP-1 cells treated with VD. The figure shows the mRNA of <span class="html-italic">Tumor Necrotic Factor-α</span> (<span class="html-italic">TNF-α</span>) levels (<b>A</b>), as well as the content of TNF-α in the supernatant of the treated cells described below (<b>B</b>). In (<b>C</b>), the figure shows the expression levels of <span class="html-italic">Interleukin-1β</span> (<span class="html-italic">IL-1β</span>) and the release of the IL-1β in cellular supernatants after the treatments (<b>D</b>). (<b>E</b>,<b>F</b>) show mRNA levels and content in the supernatant of Interleukin 6 (IL6), respectively. Data are expressed as the mean ± SD, and different letters (a–c) indicate statistical differences in the multiple comparison test across all groups using a <span class="html-italic">p</span> value &lt; 0.05, <span class="html-italic">n</span> = 6. Treatments conducted were C: without reactive; C+: Lipopolysaccharide (LPS) (50 ng/mL); T1: LPS (50 ng/mL) + vitamin D (VD) (10 nM); T2: LPS (50 ng/mL) + VD (25 nM); T3: LPS (50 ng/mL) + VD (50 nM).</p>
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<p>Pro-inflammatory cytokines and genes in LPS-induced inflammation THP-1 cells treated with H30BIO, alone and supplemented with vitamin D. The figure shows the mRNA of <span class="html-italic">Tumor Necrotic Factor-α</span> (<span class="html-italic">TNF-α</span>) levels (<b>A</b>), as well as the content of TNF-α in the supernatant of the treated cells described below (<b>B</b>). In (<b>C</b>), the figure shows the expression levels of <span class="html-italic">Interleukin-1β</span> (<span class="html-italic">IL-1β</span>) and the release of the IL-1β in cellular supernatants after the treatments (<b>D</b>). (<b>E</b>,<b>F</b>) show mRNA levels and content in the supernatant of <span class="html-italic">Interleukin-6 (IL-6)</span>, respectively. Data are expressed as the mean ± SD, and different letters (a–c) indicates statistical differences in the multiple comparison test across all groups using a <span class="html-italic">p</span> value &lt; 0.05, <span class="html-italic">n</span> = 6. Treatments conducted were C: without reactive; C++: Lipopolysaccharide (LPS) (100 ng/mL); T4: LPS (100 ng/mL) + H30BIO (250 µg/mL); T5: LPS (100 ng/mL) + vitamin D (10 nM) + H30BIO (250 µg/mL).</p>
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<p>Gene transcription levels of NF-κB pathway in LPS-induced inflammation THP-1 cells treated with vitamin D. The figure shows the relative levels of gene expression of <span class="html-italic">Nuclear Factor Kappa B Subunit 1</span> (<span class="html-italic">NF-κB</span>) (<b>A</b>), <span class="html-italic">Nuclear Factor Erythroid 2-related Factor 2</span> (<span class="html-italic">NRF2</span>) (<b>B</b>), <span class="html-italic">Caspase-1</span> (<span class="html-italic">CASP-1</span>) (<b>C</b>), <span class="html-italic">C-C Motif Chemokine Receptor 2</span> (<span class="html-italic">CCR2</span>) (<b>D</b>), <span class="html-italic">C-C Motif Chemokine Ligand 2</span> (<span class="html-italic">CCL2</span>) (<b>E</b>), <span class="html-italic">Interleukin 8</span> (<span class="html-italic">IL8</span>) (<b>F</b>), <span class="html-italic">Cyclooxygenase-2</span> (<span class="html-italic">COX2</span>) (<b>G</b>), <span class="html-italic">Interleukin 10</span> (<span class="html-italic">IL10</span>) (<b>H</b>), and <span class="html-italic">C-X-C motif chemokine ligand 10</span> (<span class="html-italic">CXCL10</span>, <span class="html-italic">IP10</span>) (<b>I</b>). Data are expressed as the mean ± SD, and different letters (a–c) were assigned in the multiple comparison test across all groups, indicating significant differences at a <span class="html-italic">p</span> value &lt; 0.05; and ‘ns’ indicates non-statistical differences in the multiple comparison test, <span class="html-italic">n</span> = 6. Treatments conducted were C: without reactive; C+: Lipopolysaccharide (LPS) (50 ng/mL); T1: LPS (50 ng/mL) + vitamin D (VD) (10 nM); T2: LPS (50 ng/mL) + VD (25 nM); T3: LPS (50 ng/mL) + VD (50 nM).</p>
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<p>Gene transcription levels of NF-κB pathway in LPS-induced inflammation in THP-1 cells treated with H30BIO alone and supplemented with vitamin D. The figure shows the relative levels of gene expression of <span class="html-italic">Nuclear Factor Kappa B Subunit 1</span> (<span class="html-italic">NF-κB</span>) (<b>A</b>), <span class="html-italic">Nuclear Factor Erythroid 2-related Factor 2</span> (<span class="html-italic">NRF2</span>) (<b>B</b>), <span class="html-italic">Caspase-1</span> (<span class="html-italic">CASP-1</span>) (<b>C</b>), <span class="html-italic">C-C Motif Chemokine Receptor 2</span> (<span class="html-italic">CCR2</span>) (<b>D</b>), <span class="html-italic">C-C Motif Chemokine Ligand 2</span> (<span class="html-italic">CCL2</span>) (<b>E</b>), <span class="html-italic">Interleukin 8</span> (<span class="html-italic">IL8</span>) (<b>F</b>), <span class="html-italic">Cyclooxygenase-2</span> (<span class="html-italic">COX2</span>) (<b>G</b>), <span class="html-italic">Interleukin 10</span> (<span class="html-italic">IL10</span>) (<b>H</b>), and <span class="html-italic">C-X-C motif chemokine ligand 10</span> (<span class="html-italic">CXCL10</span>, <span class="html-italic">IP10</span>) (<b>I</b>). Data are expressed as the mean ± SD, and different letters (a–c) were assigned in the multiple comparison test across all groups, indicating significant differences at a <span class="html-italic">p</span> value &lt; 0.05, <span class="html-italic">n</span> = 6. Treatments conducted were C: without reactive; C++: Lipopolysaccharide (LPS) (100 ng/mL); T4: LPS (100 ng/mL) + H30BIO (250 µg/mL); T5: LPS (100 ng/mL) + VD (10 nM) + H30BIO (250 µg/mL).</p>
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<p>Heat map of gene expression in LPS-induced inflammation THP-1 cells treated with vitamin D and/or H30BIO. The heat map represents gene expression normalized to the overstimulated control (C+ (<b>A</b>) or C++ (<b>B</b>)), with a color scale ranging from 0% (minimal expression, blue) to 150% (expression 50% higher than the C+ or C++ controls, red), <span class="html-italic">n</span> = 6. More intense red indicates higher levels of relative expression, while more light blue indicates lower levels. Treatments conducted were C: without reactive; C+: Lipopolysaccharide (LPS) (50 ng/mL); T1: LPS (50 ng/mL) + VD (10 nM); T2: LPS (50 ng/mL) + VD (25 nM); T3: LPS (50 ng/mL) + vitamin D (VD) (50 nM); C++: Lipopolysaccharide (LPS) (100 ng/mL); T4: LPS (100 ng/mL) + H30BIO (250 µg/mL); T5: LPS (100 ng/mL) + VD (10 nM) + H30BIO (250 µg/mL).</p>
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<p>Enrichment analysis using Biocarta (<b>A</b>), Hallmark (<b>B</b>), and KEGG (<b>C</b>) databases. Enrichment adjusted log-transformed <span class="html-italic">p</span>-values and proportions of overlapping genes are displayed alongside corresponding pathway names. Key pathways include cytokine signaling, NF-κB activation, inflammatory response, and apoptosis. The results provide insights into the molecular and cellular processes associated with the analyzed gene set.</p>
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