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19 pages, 2345 KiB  
Article
Effects of Green-Synthesised Copper Oxide–Zinc Oxide Hybrid Nanoparticles on Antifungal Activity and Phytotoxicity of Aflatoxin B1 in Maize (Zea mays L.) Seed Germination
by Simangele C. Ngwenya, Nkanyiso J. Sithole, Doctor M. N. Mthiyane, Martha C. Jobe, Olubukola O. Babalola, Ayansina S. Ayangbenro, Mulunda Mwanza, Damian C. Onwudiwe and Khosi Ramachela
Agronomy 2025, 15(2), 313; https://doi.org/10.3390/agronomy15020313 (registering DOI) - 26 Jan 2025
Abstract
Maize contamination with aflatoxin B1 (AFB1) is of significance on a global scale due to its major contribution to food security. It is very probable that substantial amounts of AFB1 may be absorbed by germinating seeds grown in contaminated soil and cause deleterious [...] Read more.
Maize contamination with aflatoxin B1 (AFB1) is of significance on a global scale due to its major contribution to food security. It is very probable that substantial amounts of AFB1 may be absorbed by germinating seeds grown in contaminated soil and cause deleterious effects on the growth and development of maize. In this study, the effect of green-synthesised ZnO-CuO hybrid nanoparticles (NPs) on antifungal activity and reducing the toxic effects of AFB1 on seed germination was examined. A notable inhibitory effect of green-synthesised ZnO-CuO nanoparticles (NPs) on A. flavus was observed at a concentration of 0.5 ppm, resulting in 13.1% inhibition, which was more effective than the higher concentration of 1.0 ppm and the control. The results showed that the final germination percentage of the seeds that were inoculated with 320 ppb was significantly increased by the treatment with 125 mg/mL of green ZnO-CuO hybrid NPs. This study indicated the potential of green-synthesised ZnO-CuO hybrid NPs as alternative antifungal agents to control aflatoxin production in maize to improve food security and safety by supressing the threat posed by AFB1. Full article
(This article belongs to the Section Plant-Crop Biology and Biochemistry)
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28 pages, 24222 KiB  
Article
TLSynth: A Novel Blender Add-On for Real-Time Point Cloud Generation from 3D Models
by Emiliano Pérez, Adolfo Sánchez-Hermosell and Pilar Merchán
Remote Sens. 2025, 17(3), 421; https://doi.org/10.3390/rs17030421 (registering DOI) - 26 Jan 2025
Abstract
Point clouds are a crucial element in the process of scanning and reconstructing 3D environments, such as buildings or heritage sites. They allow for the creation of 3D models that can be used in a wide range of applications. In some cases, however, [...] Read more.
Point clouds are a crucial element in the process of scanning and reconstructing 3D environments, such as buildings or heritage sites. They allow for the creation of 3D models that can be used in a wide range of applications. In some cases, however, only the 3D model of an environment is available, and it is necessary to obtain point clouds with the same characteristics as those captured by a laser scanner. For instance, point clouds may be required for surveys, performance optimization, site scan planning, or validation of point cloud processing algorithms. This paper presents a new terrestrial laser scanner (TLS) simulator, designed as a Blender add-on, that produces synthetic point clouds from 3D models in real time. The simulator allows users to adjust a set of parameters to replicate real-world scanning conditions, such as noise generation, ensuring the synthetic point clouds closely mirror those produced by actual laser scanners. The target meshes may be derived from either a real-world scan or 3D designs created using design software. By replicating the spatial distributions and attributes of real laser scanner outputs and supporting real-time generation, the simulator serves as a valuable tool for scan planning and the development of synthetic point cloud repositories, advancing research and practical applications in 3D computer vision. Full article
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11 pages, 1442 KiB  
Article
Obesity Prevalence and Trend Among Mississippi High-School Students: Youth Risk Behavior Surveillance System (YRBSS) 2001–2021
by Zhen Zhang, Xiaoshan Z. Gordy and Lei Zhang
Obesities 2025, 5(1), 6; https://doi.org/10.3390/obesities5010006 (registering DOI) - 26 Jan 2025
Abstract
Obesity has become the most consequential threat to the health of Mississippians, as it is known to be associated with major chronic diseases such as type II diabetes, heart disease, and strokes. Obesity prevalence among Mississippi adolescents has been among the highest in [...] Read more.
Obesity has become the most consequential threat to the health of Mississippians, as it is known to be associated with major chronic diseases such as type II diabetes, heart disease, and strokes. Obesity prevalence among Mississippi adolescents has been among the highest in the nation. In this study, data from Mississippi Youth Risk Behavior Surveillance System (YRBSS) 2001–2021 were obtained from the Centers for Disease Control and Prevention (CDC). YRBSS is a survey using a self-administered questionnaire to track the risk behaviors of students in grades 9 to 12. The survey packages in R were utilized for summary statistics to account for the YRBSS complex sampling design that includes stratification, clustering, and unequal probabilities of selection. Logistic regression models and Joinpoint software 5.3.0 were used for trend analysis. Obesity prevalence in Mississippi high-school students demonstrated a significant increasing trend from 2001 to 2021, as a whole or stratified by gender or race. Furthermore, Mississippi obesity prevalence among high-school students has been increasing at a greater pace compared to that of the United States. The increasing trend in obesity prevalence among Mississippi high-school students warrants urgent attention at the government, community, school, family, and personal levels. Concerted efforts must be made to fight and eventually reverse this epidemic. Full article
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15 pages, 507 KiB  
Article
The Societal Cost of Behaviors of Concern Among Individuals with Intellectual and Developmental Disabilities Residing in Small Residential Group Homes
by Tricia J. Johnson, Hugh Vondracek, Teresa Moro, Cameron D. White and Sarah H. Ailey
Int. J. Environ. Res. Public Health 2025, 22(2), 168; https://doi.org/10.3390/ijerph22020168 (registering DOI) - 26 Jan 2025
Abstract
Engagement in behaviors of concern (BoCs) by adults with intellectual and developmental disabilities (IDDs) living in small residential group homes can negatively impact the health, safety, and quality of life of the individuals themselves and others living and working in the home. Little [...] Read more.
Engagement in behaviors of concern (BoCs) by adults with intellectual and developmental disabilities (IDDs) living in small residential group homes can negatively impact the health, safety, and quality of life of the individuals themselves and others living and working in the home. Little is known about the societal cost of BoCs. The objective of this study was to quantify the cost of BoCs for residents, residential group homes, and public and healthcare services in terms of different behaviors. This descriptive study used incident and monthly behavior-tracking reports collected from small residential group homes for six months prior to implementing a social problem-solving intervention aimed at decreasing BoCs. The mean cost per BoC incident per resident was USD 80 ± 601. Health and safety incidents had the highest cost, followed by begging. BoCs impose costs on small residential group homes, public and healthcare services, and residents themselves. Full article
(This article belongs to the Section Health Care Sciences)
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27 pages, 18737 KiB  
Article
Generative Adversarial Network for Synthesizing Multivariate Time-Series Data in Electric Vehicle Driving Scenarios
by Shyr-Long Jeng
Sensors 2025, 25(3), 749; https://doi.org/10.3390/s25030749 (registering DOI) - 26 Jan 2025
Abstract
This paper presents a time-series point-to-point generative adversarial network (TS-p2pGAN) for synthesizing realistic electric vehicle (EV) driving data. The model accurately generates four critical operational parameters—battery state of charge (SOC), battery voltage, mechanical acceleration, and vehicle torque—as multivariate time-series data. Evaluation on 70 [...] Read more.
This paper presents a time-series point-to-point generative adversarial network (TS-p2pGAN) for synthesizing realistic electric vehicle (EV) driving data. The model accurately generates four critical operational parameters—battery state of charge (SOC), battery voltage, mechanical acceleration, and vehicle torque—as multivariate time-series data. Evaluation on 70 real-world driving trips from an open battery dataset reveals the model’s exceptional accuracy in estimating SOC values, particularly under complex stop-and-restart scenarios and across diverse initial SOC levels. The model delivers high accuracy, with root mean square error (RMSE), mean absolute error (MAE), and dynamic time warping (DTW) consistently below 3%, 1.5%, and 2.0%, respectively. Qualitative analysis using principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) demonstrates the model’s ability to preserve both feature distributions and temporal dynamics of the original data. This data augmentation framework offers significant potential for advancing EV technology, digital energy management of lithium-ion batteries (LIBs), and autonomous vehicle comfort system development. Full article
(This article belongs to the Section Vehicular Sensing)
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10 pages, 242 KiB  
Article
Macrovascular Function in People with HIV After Recent SARS-CoV-2 Infection
by Ana S. Salazar, Louis Vincent, Bertrand Ebner, Nicholas Fonseca Nogueira, Leah Krauss, Madison S. Meyer, Jelani Grant, Natalie Aguilar, Mollie S. Pester, Meela Parker, Alex Gonzalez, Armando Mendez, Adam Carrico, Barry E. Hurwitz, Maria L. Alcaide and Claudia Martinez
J. Vasc. Dis. 2025, 4(1), 4; https://doi.org/10.3390/jvd4010004 (registering DOI) - 26 Jan 2025
Abstract
Background: People with HIV (PWH) are at increased risk of vascular dysfunction and cardiovascular disease (CVD). SARS-CoV-2 infection has been associated with acute CVD complications. The aim of the study was to as-sess macrovascular function as an early indicator of CVD risk in [...] Read more.
Background: People with HIV (PWH) are at increased risk of vascular dysfunction and cardiovascular disease (CVD). SARS-CoV-2 infection has been associated with acute CVD complications. The aim of the study was to as-sess macrovascular function as an early indicator of CVD risk in PWH after mild SARS-CoV-2 infection. Methods: PWH aged 20–60 years, with undetectable viral load (RNA < 20 copies/mL), on stable anti-retroviral therapy (≥6 months) and history of mild COVID-19 (≥30 days) without any CVD manifestations prior to enrollment were recruited. Participants were excluded if they had history of diabetes mellitus, end-stage renal disease, heart or respiratory disease. Participants were matched 1:1 to pre-pandemic PWH. A health survey, surrogate measures of CVD risk, and macrovascular function (brachial artery flow-mediated vasodilation and arterial stiffness assessments via applanation tonometry) were compared between group. Results: A total of 17 PWH and history of COVID-19 (PWH/COV+) were matched with 17 PWH without COVID-19 (PWH/COV−) pre-pandemic. Mean age (45.5 years), sex (76.5% male), body mass index (27.3), and duration of HIV infection (12.2 years) were not different between groups. Both groups had comparable CVD risk factors (total cholesterol, LDL, HDL, systolic and diastolic blood pressure). There were no differences in measures of flow mediated arterial dilatation or arterial stiffness after 30 days of SARS-CoV-2 infection. Conclusions: After recent SARS-CoV-2 infection, PWH did not demonstrate evidence of macrovascular dysfunction and increased CVD risk. Results suggest that CVD risk may not be increased in people with well-controlled HIV who did not manifest CVD complications SARS-CoV-2 infection. Full article
(This article belongs to the Section Peripheral Vascular Diseases)
17 pages, 2985 KiB  
Article
Buckling Analysis of Functionally Graded GPL-Reinforced Composite Plates Under Combined Thermal and Mechanical Loads
by Jin-Rae Cho
Materials 2025, 18(3), 567; https://doi.org/10.3390/ma18030567 (registering DOI) - 26 Jan 2025
Abstract
The buckling-like mechanical behavior of functionally graded graphene platelet-reinforced composite (FG-GPLRC) structures is increasingly attracting research attention. However, buckling behavior has previously been studied separately as thermal buckling and mechanical buckling. In this context, this study investigates the buckling behavior of FG-GPLRC plates [...] Read more.
The buckling-like mechanical behavior of functionally graded graphene platelet-reinforced composite (FG-GPLRC) structures is increasingly attracting research attention. However, buckling behavior has previously been studied separately as thermal buckling and mechanical buckling. In this context, this study investigates the buckling behavior of FG-GPLRC plates under combined thermal and mechanical loads. The coupled buckling problem is formulated according to the minimum potential energy theorem using first-order shear deformation theory (FSDT). In addition, the problem is approximated by the 2-D natural element method (NEM), and the resulting coupled eigen matrix equations are derived to compute the critical buckling temperature rise (CBTR) and the mechanical buckling load. The developed numerical method can solve thermal, mechanical, and coupled thermo-mechanical buckling problems, and its reliability is examined through convergence and benchmark tests. Using the developed numerical method, the buckling behavior of FG-GPLRC plates under thermal and mechanical buckling loads is examined in depth with respect to the key parameters. In addition, a comparison with functionally graded CNT-reinforced composite (FG-CNTRC) plates is also presented. Full article
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14 pages, 4345 KiB  
Article
Heat-Responsive PLA/PU/MXene Shape Memory Polymer Blend Nanocomposite: Mechanical, Thermal, and Shape Memory Properties
by Rajita Sanaka, Santosh Kumar Sahu, P. S. Rama Sreekanth, Jayant Giri, Faruq Mohammad, Hamad A. Al-Lohedan, Mohd Shahneel Saharudin and Quanjin Ma
Polymers 2025, 17(3), 338; https://doi.org/10.3390/polym17030338 (registering DOI) - 26 Jan 2025
Abstract
This study investigates the fabrication and characterization of heat-responsive PLA/PU/MXene shape memory polymer blend nanocomposites with varying PLA content (10, 20, 30, and 50%) and a fixed MXene content of 0.5 wt.%. The results indicate significant improvements in mechanical properties, with the 50% [...] Read more.
This study investigates the fabrication and characterization of heat-responsive PLA/PU/MXene shape memory polymer blend nanocomposites with varying PLA content (10, 20, 30, and 50%) and a fixed MXene content of 0.5 wt.%. The results indicate significant improvements in mechanical properties, with the 50% PLA/PU/MXene blend showing a 300% increase in ultimate tensile strength and a 90% decrease in % elongation compared to pure PU. Additionally, the 50% blend exhibited a 400% increase in flexural strength. Microstructural analysis revealed dispersed pores and sea–island morphology in pure PU and the 50% PLA/PU/MXene blend. Thermal analysis using DSC showed an increase in crystallinity from 33% (pure PU) to 45% for the 50% PLA/PU/MXene blend, indicating enhanced crystalline domains due to the semi-crystalline nature of PLA and MXene’s influence on molecular ordering. TGA demonstrated a significant improvement in thermal stability, with the onset temperature rising from 185 °C (pure PU) to 212 °C and the degradation temperature increasing from 370 °C to 425 °C for the 50% blend, attributed to the rigid structure of PLA and MXene’s stabilizing effect. Shape memory testing revealed that the 30% PLA/PU/MXene blend achieved the best shape fixity and recovery with optimal performance, whereas higher PLA content diminished shape memory behavior. Full article
(This article belongs to the Special Issue Shape Memory Polymer Materials)
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19 pages, 11601 KiB  
Article
Micro-Size Layers Evaluation of CIGSe Solar Cells on Flexible Substrates by Two-Segment Process Improved for Overall Efficiencies
by Jiajer Ho, Da-Ming Yu, Jen-Chuan Chang and Jyh-Jier Ho
Molecules 2025, 30(3), 562; https://doi.org/10.3390/molecules30030562 (registering DOI) - 26 Jan 2025
Abstract
This paper details the enhancement of the optoelectronic properties of Cu-(In, Ga)-Se2 (CIGSe) solar cells through a two-segment process in the ultraviolet (UV)–visible spectral range. These include fine-tuning the DC sputtering power of the absorber layer (ranging from 20 to 40 W [...] Read more.
This paper details the enhancement of the optoelectronic properties of Cu-(In, Ga)-Se2 (CIGSe) solar cells through a two-segment process in the ultraviolet (UV)–visible spectral range. These include fine-tuning the DC sputtering power of the absorber layer (ranging from 20 to 40 W at segment I) and thoroughly checking the trace micro-chemistry composition of the absorber layer (CdS, ZnO/CdS, ZnMgO/CdS, and ZnMgO at segment II). After segment I of treatment, the optimal 30 W CIGSe absorber layer (i.e., with a 0.95 CGI ratio) can be obtained, it can be seen that the Cu-rich film exhibits the ability to significantly promote grain growth and can effectively reduce its trap state density. After the segment II process aimed at replacing toxic CdS, the optimal metal alloy (Zn0.9Mg0.1O) composition (buffer layer) achieved the highest conversion efficiency (η) of 8.70%, also emphasizing its role in environmental protection. Especially within the tunable bandgap range (2.48–3.62 eV), the developed overall internal and external quantum efficiency (IQE/EQE) is significantly improved by 13.15% at shorter wavelengths. A photovoltaic (PV) module designed with nine optimal CIGSe cells demonstrated commendable stability. Variation remained within ±5% throughout the 60-day experiment. The PV modules in this study represent a breakthrough benchmark toward a significant advance in the scientific understanding of renewable energy. Furthermore, this research clearly promotes the practical application of PV modules, harmonizes with sustainable goals, and actively contributes to the creation of eco-friendly communities. Full article
(This article belongs to the Section Nanochemistry)
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17 pages, 2685 KiB  
Article
Beyond Soil Health: The Microbial Implications of Conservation Agriculture
by Kassandra Santellanez-Arreola, Miguel Ángel Martínez-Gamiño, Vicenta Constante-García, Jesús Arreola-Ávila, Cristina García-De la Peña, Quetzaly Karmy Siller-Rodríguez, Ricardo Trejo-Calzada and Erika Nava-Reyna
Diversity 2025, 17(2), 90; https://doi.org/10.3390/d17020090 (registering DOI) - 26 Jan 2025
Abstract
Conservation agriculture (CA) is a sustainable land management approach to improve soil quality while mitigating degradation. Although extensive information regarding the effect of CA on soil properties and microbiome is available, complete studies on the cumulative effect on specific interactions between soil parameters, [...] Read more.
Conservation agriculture (CA) is a sustainable land management approach to improve soil quality while mitigating degradation. Although extensive information regarding the effect of CA on soil properties and microbiome is available, complete studies on the cumulative effect on specific interactions between soil parameters, crop productivity, and microbial communities over time are still lacking, mainly in arid regions. Thus, this study aimed to investigate the effects of no-tillage and residue retention over long- and short-term (24 and 3 years, respectively) periods. Six treatments were established in a maize–oat–triticale system from 1995 in a semiarid region: P + H—plow + harrow; H—harrow; MP—multi-plow (short-term); NT—no-tillage; NT33—NT + 33% residue surface cover (long-term); NT66—NT + 66% residue surface cover. Results indicated that CA improved soil quality by increasing soil organic matter (SOM), total carbon, and glomalin; it also enhanced microbial abundance, particularly fungi, and β-galactosidase activity. Nevertheless, conventional tillage practices led to SOM degradation and reduced crop yields. Principal component analysis revealed distinct groupings of treatments based on soil properties and microbial communities. Furthermore, changes could be detected from the short term. These findings highlight the importance of adopting sustainable agricultural practices to maintain soil health and ensure agricultural productivity in semi-arid regions. Full article
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15 pages, 2580 KiB  
Article
Effect of Different Enzyme Treatments on Juice Yield, Physicochemical Properties, and Bioactive Compound of Several Hybrid Grape Varieties
by Muhamad Alfiyan Zubaidi, Marta Czaplicka, Joanna Kolniak-Ostek and Agnieszka Nawirska-Olszańska
Molecules 2025, 30(3), 556; https://doi.org/10.3390/molecules30030556 (registering DOI) - 26 Jan 2025
Abstract
This study investigates the effects of four enzymatic treatments on the yield, physicochemical properties, and bioactive compounds of grape juices from two red (Golubok, Regent) and two white (Muscaris, Aurora) hybrid grape varieties. A total of 20 samples were prepared using four commercial [...] Read more.
This study investigates the effects of four enzymatic treatments on the yield, physicochemical properties, and bioactive compounds of grape juices from two red (Golubok, Regent) and two white (Muscaris, Aurora) hybrid grape varieties. A total of 20 samples were prepared using four commercial enzyme formulations (Pectinex Ultra, Safizym Clear Plus, Safizym Press, and Rapidase color) applied at a concentration of 0.02% (w/w). The juices were evaluated for yield, total phenolic content, antioxidant capacities (ABTS, DPPH, FRAP), titratable acidity, turbidity, total soluble solids, and phenolic profile. The addition of enzymes significantly improved juice yield by 10% to 20%, with the effect varying depending on the type of enzyme and the variety of grapes. Pectinex Ultra was the most effective enzyme in reducing turbidity, while enzyme treatments had minimal impact on Brix levels and sugar concentration, which were primarily determined by the characteristics of each grape variety. The enzyme addition showed a minor influence on the titratable acidity of the juices, with slight increases observed in Muscaris, but the grape variety played a major role in determining the titratable acidity levels. Color parameters revealed that white grape juices (Muscaris and Aurora) were brighter than red varieties (Golubok and Regent). Additionally, enzyme treatments influenced the color, enhancing the red hues in red grape juices. Enzyme treatments also improved the antioxidant capacity of grape juices, especially in Aurora and Muscaris, although the effect on polyphenol content was more dependent on the variety of grapes, with red varieties showing higher levels of polyphenols than white varieties. These findings highlight the significant role of both enzyme treatments and grape variety in determining the quality and health-promoting properties of grape juice. Full article
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12 pages, 991 KiB  
Article
Innovative Fluorinated Polyimides with Superior Thermal, Mechanical, and Dielectric Properties for Advanced Soft Electronics
by Yuwei Chen, Yidong Liu and Yonggang Min
Polymers 2025, 17(3), 339; https://doi.org/10.3390/polym17030339 (registering DOI) - 26 Jan 2025
Abstract
This study addresses the limitations of traditional polyimides (PIs) in high-frequency and high-temperature soft electronic applications, and then introducing trifluoromethylbenzene (TFMB) into the molecular structure and employing various diamines as connecting components to solve the bottleneck. The innovative molecular design enhances thermal, mechanical, [...] Read more.
This study addresses the limitations of traditional polyimides (PIs) in high-frequency and high-temperature soft electronic applications, and then introducing trifluoromethylbenzene (TFMB) into the molecular structure and employing various diamines as connecting components to solve the bottleneck. The innovative molecular design enhances thermal, mechanical, and dielectric properties, overcoming challenges in balancing these performances. The optimized fluorinated PI (TPPI50) exhibits exceptional properties, including a glass transition temperature of 402 °C, thermal decomposition temperature of 563 °C, tensile strength of 232.73 MPa, elongation at break of 26.26%, and dielectric constant of 2.312 at 1 MHz with a dielectric loss as low as 0.00676. These improvements are attributed to the unique synergy between TFMB’s fluorinated groups, which reduce molecular polarization, and the biphenyl structure, which reinforces chain stability. Compared to conventional PIs, TPPI50 demonstrates superior comprehensive performance, making it highly suitable for soft circuits, high-frequency signal transmission, and advanced applications such as wearable devices and biosensors. This study provides a robust framework for industrial applications, offering a path to next-generation soft electronics with enhanced reliability and performance. Full article
(This article belongs to the Special Issue Smart Polymeric Materials for Soft Electronics)
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17 pages, 3858 KiB  
Article
Predicting the Zinc Content in Rice from Farmland Using Machine Learning Models: Insights from Universal Geochemical Parameters
by Wenda Geng, Tingting Li, Xin Zhu, Lei Dou, Zijia Liu, Kun Qian, Guiqi Ye, Kun Lin, Bo Li, Xudong Ma, Qingye Hou, Tao Yu and Zhongfang Yang
Appl. Sci. 2025, 15(3), 1273; https://doi.org/10.3390/app15031273 (registering DOI) - 26 Jan 2025
Abstract
Zinc (Zn) is an essential nutrient for the human body and is prone to deficiency. Supplementing Zn through zinc-enriched cereals is of great significance in addressing the widespread issue of zinc deficiency. However, there is no simple linear correlation between the soil zinc [...] Read more.
Zinc (Zn) is an essential nutrient for the human body and is prone to deficiency. Supplementing Zn through zinc-enriched cereals is of great significance in addressing the widespread issue of zinc deficiency. However, there is no simple linear correlation between the soil zinc content and rice grain zinc content, which poses challenges for zoning zinc-enriched rice cultivation based on the soil Zn content. Therefore, accurately predicting the zinc content in rice grains is of great importance. To verify the robustness of the prediction model and expand its applicability, this study established a prediction model using 371 sets of previously collected and tested rice grain and root zone soil samples from the Pearl River Delta and Heyuan regions in Guangdong. The model was validated using the data from 65 sets of rice and root zone soil samples collected and analyzed in Zijin and Dongyuan counties, Heyuan, in 2023. The results show that zinc absorption by rice grains is controlled by multiple factors, primarily related to the soil S, P, CaO, Mn, TFe2O3, TOC, and SiO2/Al2O3 ratio. Both the artificial neural network model and random forest model demonstrated a good predictive performance across large regions. However, in the Heyuan region, the random forest model outperformed the artificial neural network model, with an R2 of 0.79 and an RMSE of 0.05 when the predicted data were compared against the measured BAFZn of the rice. This suggests that predicting the zinc content in rice grains based on the soil macro-elements (including oxides) and TOC is feasible, and, within certain regional boundaries, the prediction model is robust and widely applicable. This study provides valuable insights into the rational development of zinc-enriched rice in the Heyuan region and offers a useful reference for establishing prediction models of the beneficial element content in rice grains in areas with limited data. Full article
(This article belongs to the Special Issue New Advances, Challenges, and Illustrations in Applied Geochemistry)
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20 pages, 2932 KiB  
Article
Characterization of the SWEET Gene Family in Blueberry (Vaccinium corymbosum L.) and the Role of VcSWEET6 Related to Sugar Accumulation in Fruit Development
by Jiaxin Liu, Xuxin Jiang, Lei Yang, Dongshuang Zhao, Yifei Wang, Yali Zhang, Haiyue Sun, Li Chen and Yadong Li
Int. J. Mol. Sci. 2025, 26(3), 1055; https://doi.org/10.3390/ijms26031055 (registering DOI) - 26 Jan 2025
Abstract
Sugars will eventually be exported transporters (SWEETs) are essential transmembrane proteins involved in plant growth, stress responses, and plant–pathogen interactions. Despite their importance, systematic studies on SWEETs in blueberries (Vaccinium corymbosum L.) are limited. Blueberries are recognized for their rapid growth and [...] Read more.
Sugars will eventually be exported transporters (SWEETs) are essential transmembrane proteins involved in plant growth, stress responses, and plant–pathogen interactions. Despite their importance, systematic studies on SWEETs in blueberries (Vaccinium corymbosum L.) are limited. Blueberries are recognized for their rapid growth and the significant impact of sugar content on fruit flavor, yet the role of the SWEET gene family in sugar accumulation during fruit development remains unclear. In this study, 23 SWEET genes were identified in blueberry, and their phylogenetic relationships, duplication events, gene structures, cis-regulatory elements, and expression profiles were systematically analyzed. The VcSWEET gene family was classified into four clades. Structural and motif analysis revealed conserved exon–intron organization within each clade. RT-qPCR analysis showed widespread expression of VcSWEETs across various tissues and developmental stages, correlating with promoter cis-elements. VcSWEET6a, in particular, was specifically expressed in fruit and showed reduced expression during fruit maturation. Subcellular localization indicated that VcSWEET6a is located in the endoplasmic reticulum. Functional assays in yeast confirmed its role in glucose and fructose uptake, with transport activity inhibited at higher sugar concentrations. Overexpression of VcSWEET6a in blueberries resulted in reduced sugar accumulation. These findings offer valuable insights into the role of VcSWEETs in blueberry sugar metabolism. Full article
17 pages, 2123 KiB  
Article
Clinical Data Mega-Collection of Obesity and Obesity-Related Trials: Primary Inclusion Criteria from All Studies and Highlights of Clinical Efficacy Analysis of GLP-1 Drugs
by Trung Tin Nguyen and David R. Elmaleh
J. Clin. Med. 2025, 14(3), 812; https://doi.org/10.3390/jcm14030812 (registering DOI) - 26 Jan 2025
Abstract
Background/Objectives: Obesity is heterogeneous and considered a chronic epidemic with significant un-met needs for management, treatment, and prevention. Methods: In this study, we used LizAI’s software TAITAN (alpha version) for the mega-collection and analysis of clinical data from 10,407 trials addressing obesity and [...] Read more.
Background/Objectives: Obesity is heterogeneous and considered a chronic epidemic with significant un-met needs for management, treatment, and prevention. Methods: In this study, we used LizAI’s software TAITAN (alpha version) for the mega-collection and analysis of clinical data from 10,407 trials addressing obesity and obesity-related diseases and their associated publications, mainly on PubMed. Results: We report an intensive growth of clinical trials until the end of 2024 and highlight the use of the body mass index (BMI) as a critical criterion in clinical participant selection despite its limitations. The significant disparities in races, regions, and the sites of trials across all studies have not been addressed, posing the possibility of research in the far future on the applications of precision medicine in weight management. In the latter parts of this paper, we analyze and discuss the clinical efficacy, mainly focusing on the primary endpoints and benchmarks of the recently FDA-approved once-weekly injectable glucagon-like peptide-1 receptor agonist (GLP-1 RA) drugs, including semaglutide and tirzepatide. Both drugs have functioned comparably when considering the 5% weight loss FDA threshold. Tirzepatide outperforms semaglutide and impacts fewer participants as the weight loss level increases from 5 to 20% and has greater effects in different populations, especially in people with type 2 diabetes (T2D). Conclusions: We would, however, like to highlight that (i) the weight loss level should be dependent on the clinically relevant needs of patients, and faster and greater weight loss might not be a win, and (ii) the clinical benefits, safety, and quality of life of patients should be carefully assessed when the weight loss is significant in a short period. In our search, we found that the specificities and impacts of weight loss therapies on organs like the kidneys and heart, different muscle types, bones, and fat accumulation in different parts of body were not investigated or disclosed during the clinical study period and longer term monitoring. In light of scientific needs and remarkable public interest in weight loss, our report provides findings on the buzz around losing weight in clinical trials, and our TAITAN software continues to collect data in real time and enrich its knowledge for future updates. Full article
(This article belongs to the Special Issue Clinical Advances in the Management and Treatment of Obesity)
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38 pages, 4477 KiB  
Article
The Effect of Sulphur Atoms on the Structure of Biomolecule 2-Thiocytosine in the Gas-Phase, Solid-State, and Hydrated Forms and in DNA–DNA Microhelices as Compared to Canonical Ones
by Mauricio Alcolea Palafox, Valentin Alba Aparicio, Sergio Toninelli Rodriguez, Josefa Isasi Marín, Jitendra Kumar Vats and Vinod Kumar Rastogi
Molecules 2025, 30(3), 559; https://doi.org/10.3390/molecules30030559 (registering DOI) - 26 Jan 2025
Abstract
This study is focused on the effects of the sulphur atom in position 2 of the cytosine molecule, 2-thiocytosine (2TC), on the molecular structural parameters in the isolated state, as well as in the hydration, solid state arrangement, Watson–Crick pairs, and DNA–DNA microhelices, [...] Read more.
This study is focused on the effects of the sulphur atom in position 2 of the cytosine molecule, 2-thiocytosine (2TC), on the molecular structural parameters in the isolated state, as well as in the hydration, solid state arrangement, Watson–Crick pairs, and DNA–DNA microhelices, as compared to the canonical form. The main six tautomers were optimised at the MP2 and CCSD levels, and the sulphur atom does not show any effect on the stability trend of cytosine. The energy difference between T2b and T2a tautomers is twice as low in 2TC (1.15 kJ/mol) than in cytosine (2.69 kJ/mol). The IR and laser Raman spectra of 2TC were accurately assigned using DFT computations and solid-state simulations of the crystal unit cell through several tetramer forms. The results notably improve those previously published by other authors. The effect of explicit water molecules surrounding 2TC up to 30, corresponding to the first and second hydration shells, on geometries and tautomerism was analysed. The Watson–Crick base pairs’ stability (ΔECP = −97.458 kJ/mol) was found to be less than with cytosine (−105.930 kJ/mol). The calculated dipole moment was also lower (4.205 D) than with cytosine (5.793 D). The effect of 2TC on the 5′-dG-dC-dG-3′ and 5′-dA-dC-dA-3′ DNA–DNA optimised microhelices was evaluated through their calculated helical parameters, which indicates a clear deformation of the helix formation. The radius (R) with 2TC appears considerably shorter (6.200 Å) in the 5′-dA-dC-dA-3′ microhelix than that with cytosine (7.050 Å). Because of the special characteristics of the 2TC molecule, it can be used as an anticancer drug. Full article
12 pages, 2964 KiB  
Article
Decline in Water Treatment Efficiency of an Estuarine Constructed Wetland over Its Operating Years
by Huaqing Li, Qian Xu, Shiyi Jiang, Yanping Liu, Ronghui Wang, Yong Xu, Jimeng Feng, Jian Shen and Xinze Wang
Water 2025, 17(3), 352; https://doi.org/10.3390/w17030352 (registering DOI) - 26 Jan 2025
Abstract
Estuarine constructed wetlands (ECWs) play a role as ecological barriers in the control of external pollution in lakes. Usually, ECWs show reduced water treatment efficiency after many years of operation compared to their initial performance. However, it is unclear how the water purification [...] Read more.
Estuarine constructed wetlands (ECWs) play a role as ecological barriers in the control of external pollution in lakes. Usually, ECWs show reduced water treatment efficiency after many years of operation compared to their initial performance. However, it is unclear how the water purification efficiency of an ECW changes over time. After over a decade of tracking analysis on an ECW, this study found that it indeed played a significant role in achieving water quality improvement effects. The average removal rates for total nitrogen (TN) and total phosphorus (TP) and the permanganate index (CODMn) were 36.2%, 26.7%, and 30.7%, respectively, with annual reductions of 1.6 t/a, 20.8 t/a, and 44.6 t/a. The surface hydraulic load is a critical indicator for the design and operational management of ECWs. The reduction loads of TP, TN, and CODMn increased with the rise in surface hydraulic load, indicating that this ECW project had certain advantages in treating large-volume water bodies. However, when strict CODMn treatment is needed, the surface hydraulic load should be reduced. During the high-efficiency period (2010–2015), the treatment effects on TN and TP were more than twice those during the degradation period (2016–2021), and the effect on CODMn was about 1.5 times greater. With increased operation years, the TN removal rate declined most rapidly due to pollutant accumulation and sediment release. Full article
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22 pages, 4765 KiB  
Article
Mathematical Model-Based Optimization of Trace Metal Dosage in Anaerobic Batch Bioreactors
by Tina Kegl, Balasubramanian Paramasivan and Bikash Chandra Maharaj
Bioengineering 2025, 12(2), 117; https://doi.org/10.3390/bioengineering12020117 (registering DOI) - 26 Jan 2025
Abstract
Anaerobic digestion (AD) is a promising and yet a complex waste-to-energy technology. To optimize such a process, precise modeling is essential. Developing complex, mechanistically inspired AD models can result in an overwhelming number of parameters that require calibration. This study presents a novel [...] Read more.
Anaerobic digestion (AD) is a promising and yet a complex waste-to-energy technology. To optimize such a process, precise modeling is essential. Developing complex, mechanistically inspired AD models can result in an overwhelming number of parameters that require calibration. This study presents a novel approach that considers the role of trace metals (Ca, K, Mg, Na, Co, Cr, Cu, Fe, Ni, Pb, and Zn) in the modeling, numerical simulation, and optimization of the AD process in a batch bioreactor. In this context, BioModel is enhanced by incorporating the influence of metal activities on chemical, biochemical, and physicochemical processes. Trace metal-related parameters are also included in the calibration of all model parameters. The model’s reliability is rigorously validated by comparing simulation results with experimental data. The study reveals that perturbations of 5% in model parameter values significantly increase the discrepancy between simulated and experimental results up to threefold. Additionally, the study highlights how precise optimization of metal additives can enhance both the quantity and quality of biogas production. The optimal concentrations of trace metals increased biogas and CH4 production by 5.4% and 13.5%, respectively, while H2, H2S, and NH3 decreased by 28.2%, 43.6%, and 42.5%, respectively. Full article
(This article belongs to the Special Issue Anaerobic Digestion Advances in Biomass and Waste Treatment)
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24 pages, 1767 KiB  
Review
The Small Key to the Treasure Chest: Endogenous Plant Peptides Involved in Symbiotic Interactions
by Anna Mamaeva, Arina Makeeva and Daria Ganaeva
Plants 2025, 14(3), 378; https://doi.org/10.3390/plants14030378 (registering DOI) - 26 Jan 2025
Abstract
Plant growth and development are inextricably connected with rhizosphere organisms. Plants have to balance between strong defenses against pathogens while modulating their immune responses to recruit beneficial organisms such as bacteria and fungi. In recent years, there has been increasing evidence that regulatory [...] Read more.
Plant growth and development are inextricably connected with rhizosphere organisms. Plants have to balance between strong defenses against pathogens while modulating their immune responses to recruit beneficial organisms such as bacteria and fungi. In recent years, there has been increasing evidence that regulatory peptides are essential in establishing these symbiotic relationships, orchestrating processes that include nutrient acquisition, root architecture modification, and immune modulation. In this review, we provide a comprehensive summary of the peptide families that facilitate beneficial relationships between plants and rhizosphere organisms. Full article
(This article belongs to the Section Plant Molecular Biology)
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17 pages, 3144 KiB  
Review
A Review of Diagnostic Methods for Yaw Errors in Horizontal Axis Wind Turbines
by Qian Li, Danyang Chen, Hangbing Lin and Xiaolei Yang
Energies 2025, 18(3), 588; https://doi.org/10.3390/en18030588 (registering DOI) - 26 Jan 2025
Abstract
Yaw errors occur in wind turbines either during the installation stage or because of the aging of devices. It reduces the wind speed in the rotor axial direction and increases the structural loads in the lateral direction. Diagnosing yaw error rapidly and accurately [...] Read more.
Yaw errors occur in wind turbines either during the installation stage or because of the aging of devices. It reduces the wind speed in the rotor axial direction and increases the structural loads in the lateral direction. Diagnosing yaw error rapidly and accurately is crucial for avoiding the introduced under-performance. In this review paper, we first introduce the fundamental concepts and principles of wind turbine yaw control strategies, and we discuss two types of yaw errors (i.e., the static yaw error and the dynamic yaw error) with their corresponding causes. Subsequently, we outline the existing yaw error diagnostic methods, which are based on the LiDAR (light detection and ranging) data, the SCADA (supervisory control and data acquisition) data, or a combination of the two, and we discuss the advantages and disadvantages of various methods. At last, we emphasize that the diagnostic performance can be improved via the combination of the LiDAR data and the SCADA data, and it benefits from an in-depth understanding of the salient features and influential factors associated with the yaw error. Meanwhile, the potential of intelligent clusters and digital twins for detecting yaw errors is discussed. Full article
(This article belongs to the Section A3: Wind, Wave and Tidal Energy)
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18 pages, 5126 KiB  
Article
Critical Filling Height of Embankment over Soft Soil: A Three-Dimensional Upper-Bound Limit Analysis
by Xijun Liu, Bokai Song, Zhuanqin Sun and Wenxiu Jiao
Buildings 2025, 15(3), 395; https://doi.org/10.3390/buildings15030395 (registering DOI) - 26 Jan 2025
Abstract
This paper investigates the critical filling height of embankments over soft soil using three-dimensional (3D) upper-bound limit analysis based on a rotational log-spiral failure mechanism. Soft soils are characterized by low shear strength and high compressibility, making the accurate determination of critical filling [...] Read more.
This paper investigates the critical filling height of embankments over soft soil using three-dimensional (3D) upper-bound limit analysis based on a rotational log-spiral failure mechanism. Soft soils are characterized by low shear strength and high compressibility, making the accurate determination of critical filling height essential for evaluating embankment stability. Unlike conventional two-dimensional (2D) analyses, the proposed 3D method captures the true failure mechanism of embankments, providing more realistic and reliable results. The upper-bound analysis equations are derived using the principle of virtual work and solved efficiently through the genetic algorithm (GA), which avoids the limitations of traditional loop and random searching algorithms. The proposed solution is validated by comparing it with existing studies on slope stability and demonstrates higher accuracy and computational efficiency. Parametric studies are conducted to evaluate the influence of the depth–height ratio (the ratio of soft soil depth to embankment height) on the failure width of the embankment, the critical failure surface, and the critical filling height. Results show that the critical failure surface is tangential to the bottom of the soft soil layer and the critical filling height increases as the depth–height ratio decreases. The findings provide a set of critical filling heights calculated under various soft soil depths, strength parameters, and embankment geometries, offering practical guidance for embankment design. Full article
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25 pages, 11027 KiB  
Article
A Novel Approach for the Counting of Wood Logs Using cGANs and Image Processing Techniques
by João V. C. Mazzochin, Giovani Bernardes Vitor, Gustavo Tiecker, Elioenai M. F. Diniz, Gilson A. Oliveira, Marcelo Trentin and Érick O. Rodrigues
Forests 2025, 16(2), 237; https://doi.org/10.3390/f16020237 (registering DOI) - 26 Jan 2025
Abstract
This study tackles the challenge of precise wood log counting, where applications of the proposed methodology can span from automated approaches for materials management, surveillance, and safety science to wood traffic monitoring, wood volume estimation, and others. We introduce an approach leveraging Conditional [...] Read more.
This study tackles the challenge of precise wood log counting, where applications of the proposed methodology can span from automated approaches for materials management, surveillance, and safety science to wood traffic monitoring, wood volume estimation, and others. We introduce an approach leveraging Conditional Generative Adversarial Networks (cGANs) for eucalyptus log segmentation in images, incorporating specialized image processing techniques to handle noise and intersections, coupled with the Connected Components Algorithm for efficient counting. To support this research, we created and made publicly available a comprehensive database of 466 images containing approximately 13,048 eucalyptus logs, which served for both training and validation purposes. Our method demonstrated robust performance, achieving an average Accuracypixel of 96.4% and Accuracylogs of 92.3%, with additional measures such as F1 scores ranging from 0.879 to 0.933 and IoU values between 0.784 and 0.875, further validating its effectiveness. The implementation proves to be efficient with an average processing time of 0.713 s per image on an NVIDIA T4 GPU, making it suitable for real-time applications. The practical implications of this method are significant for operational forestry, enabling more accurate inventory management, reducing human errors in manual counting, and optimizing resource allocation. Furthermore, the segmentation capabilities of the model provide a foundation for advanced applications such as eucalyptus stack volume estimation, contributing to a more comprehensive and refined analysis of forestry operations. The methodology’s success in handling complex scenarios, including intersecting logs and varying environmental conditions, positions it as a valuable tool for practical applications across related industrial sectors. Full article
(This article belongs to the Special Issue Applications of Artificial Intelligence in Forestry: 2nd Edition)
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21 pages, 289 KiB  
Article
The Radicalness of Innovation in Nonprofit Community Sport Organizations
by Alison Doherty, Larena Hoeber, Orland Hoeber, Kristen A. Morrison and Richard Wolfe
Adm. Sci. 2025, 15(2), 37; https://doi.org/10.3390/admsci15020037 (registering DOI) - 26 Jan 2025
Abstract
Our study examined and compared the type, process, conditions, and consequences of radical and incremental innovations in community sport organizations (CSOs), which are a type of nonprofit membership association. Interviews were conducted with the president (or representative) of 14 CSOs engaged with both [...] Read more.
Our study examined and compared the type, process, conditions, and consequences of radical and incremental innovations in community sport organizations (CSOs), which are a type of nonprofit membership association. Interviews were conducted with the president (or representative) of 14 CSOs engaged with both radical and incremental innovations. Radical innovations were reported to be mostly technical (but also administrative), undertaken with the goal of club growth and enhancing club management, adopted and further adapted from outside the organization, influenced by the culture and expertise of the board and the culture and capacity of the CSO at large, and informed by market opportunity and best practices. The radical innovations were reported to be successful in reaching their intended goals, and a wide variety of unanticipated (positive) consequences was also realized. The findings have implications for the management of radical (and incremental) innovation in the focal nonprofit context and contribute to theorizing about the radicalness of organizational innovation. Full article
21 pages, 8517 KiB  
Article
Investigation of Thermal Deformation Behavior in Boron Nitride-Reinforced Magnesium Alloy Using Constitutive and Machine Learning Models
by Ayoub Elajjani, Yinghao Feng, Wangxi Ni, Sinuo Xu, Chaoyang Sun and Shaochuan Feng
Nanomaterials 2025, 15(3), 195; https://doi.org/10.3390/nano15030195 (registering DOI) - 26 Jan 2025
Abstract
Accurate flow stress prediction is vital for optimizing the manufacturing of lightweight materials under high-temperature conditions. In this study, a boron nitride (BN)-reinforced AZ80 magnesium composite was subjected to hot compression tests at temperatures of 300–400 °C and strain rates ranging from 0.01 [...] Read more.
Accurate flow stress prediction is vital for optimizing the manufacturing of lightweight materials under high-temperature conditions. In this study, a boron nitride (BN)-reinforced AZ80 magnesium composite was subjected to hot compression tests at temperatures of 300–400 °C and strain rates ranging from 0.01 to 10 s−1. A data-driven Support Vector Regression (SVR) model was developed to predict flow stress based on temperature, strain rate, and strain. Trained on experimental data, the SVR model demonstrated high predictive accuracy, as evidenced by a low mean squared error (MSE), a coefficient of determination (R2) close to unity, and a minimal average absolute relative error (AARE). Sensitivity analysis revealed that strain rate and temperature exerted the greatest influence on flow stress. By integrating machine learning with experimental observations, this framework enables efficient optimization of thermal deformation, supporting data-driven decision-making in forming processes. The results underscore the potential of combining advanced computational models with real-time experimental data to enhance manufacturing efficiency and improve process control in next-generation lightweight alloys. Full article
(This article belongs to the Section Theory and Simulation of Nanostructures)
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17 pages, 3270 KiB  
Article
Antioxidant Peptides from Hizikia fusiformis: A Study of the Preparation, Identification, Molecular Docking, and Cytoprotective Function of H2O2-Damaged A549 Cells by Regulating the Keap1/Nrf2 Pathway
by Shang Lv, Bin Hu, Su-Zhen Ran, Min Zhang, Chang-Feng Chi and Bin Wang
Foods 2025, 14(3), 400; https://doi.org/10.3390/foods14030400 (registering DOI) - 26 Jan 2025
Abstract
Hijiki (Hizikia fusiformis) is a seaweed native to warm-temperate and subtropical regions that has a high edible value and economic value, with a production of about 2 × 105 tons/year. Current research has clearly shown that the pharmacological activities of [...] Read more.
Hijiki (Hizikia fusiformis) is a seaweed native to warm-temperate and subtropical regions that has a high edible value and economic value, with a production of about 2 × 105 tons/year. Current research has clearly shown that the pharmacological activities of active ingredients from hijiki have covered a broad spectrum of areas, including antioxidant, hypoglycemic, antiviral, anticoagulant, anti-inflammatory, intestinal flora modulation, anti-aging, antineoplastic and antibacterial, and anti-Alzheimer’s disease areas. However, no studies have reported on the production of antioxidant peptides from hijiki proteins. The objectives of this study were to optimize the preparation process and explore the cytoprotective function and mechanisms of antioxidant peptides from hijiki protein. The results indicated that papain is more suitable for hydrolyzing hijiki protein than pepsin, trypsin, alkaline protease, and neutral protease. Under the optimized parameters of an enzyme dosage of 3%, a material–liquid ratio of 1:30, and an enzyme digestion time of 5 h, hijiki hydrolysate with a high radical scavenging activity was generated. Using ultrafiltration and serial chromatographic methods, ten antioxidant oligopeptides were purified from the papain-prepared hydrolysate and identified as DGPD, TIPEE, TYRPG, YTPAP, MPW, YPSKPT, YGALT, YTLLQ, FGYGP, and FGYPA with molecular weights of 402.35, 587.61, 592.64, 547.60, 532.53, 691.77, 523.57, 636.73, 539.58, and 553.60 Da, respectively. Among them, tripeptide MPW could regulate the Keap1/Nrf2 pathway to significantly ameliorate H2O2-induced oxidative damage of A549 cells by increasing cell viability and antioxidant enzyme (SOD, CAT, and GSH-Px) activity, decreasing ROS and MDA levels, and reducing the apoptosis rate. Molecular docking experiments show that HFP5 (MPW) exerts its inhibitory effect mainly through hydrogen bonds and hydrophobic interactions with the Kelch domain of the Keap1 protein, eventually facilitating the translocation of Nrf2 to the nucleus. Therefore, antioxidant peptides from hijiki can be applied to develop algae-derived health foods for treating diseases associated with oxidative stress. Full article
12 pages, 1358 KiB  
Communication
Pharmacological Inhibition of MDM2 Induces Apoptosis in p53-Mutated Triple-Negative Breast Cancer
by Jasmin Linh On, Sahel Ghaderi, Carina Rittmann, Greta Hoffmann, Franziska Gier, Vitalij Woloschin, Jia-Wey Tu, Sanil Bhatia, Andrea Kulik, Dieter Niederacher, Hans Neubauer, Thomas Kurz, Tanja Fehm and Knud Esser
Int. J. Mol. Sci. 2025, 26(3), 1078; https://doi.org/10.3390/ijms26031078 (registering DOI) - 26 Jan 2025
Abstract
Triple-negative breast cancer (TNBC) represents the most aggressive breast carcinoma subtype lacking efficient therapeutic options. A promising approach in cancer treatment is the pharmacological inhibition of murine double minute 2 (MDM2)-p53 interaction inducing apoptosis in p53 wild-type tumors. However, the role of MDM2 [...] Read more.
Triple-negative breast cancer (TNBC) represents the most aggressive breast carcinoma subtype lacking efficient therapeutic options. A promising approach in cancer treatment is the pharmacological inhibition of murine double minute 2 (MDM2)-p53 interaction inducing apoptosis in p53 wild-type tumors. However, the role of MDM2 in TNBC with primarily mutant p53 is not well understood. We here selected the clinical-stage MDM2 inhibitors Idasanutlin and Milademetan and investigated their anti-tumoral effects in TNBC. When we analyzed anti-tumor activity in the TNBC cell lines MDA-MB-231, MDA-MB-436, and MDA-MB-468, cellular viability was efficiently reduced, with half maximal inhibitory concentration (IC50) values ranging between 2.00 and 7.62 µM being up to 11-fold lower compared to the well-characterized non-clinical-stage MDM2 inhibitor Nutlin-3a. Furthermore, caspase-3/7 activity was efficiently induced. Importantly, the IC50 values for MDM2 inhibition were equally observed in HCT116 p53+/+ or HCT116 p53−/− cells. Finally, the IC50 was significantly higher in non-malignant MCF-10A cells than in TNBC cells. Taken together, Idasanutlin and Milademetan show a potent anti-tumor activity in TNBC cell culture models by efficiently inducing tumor cell death via apoptosis. This effect was observed despite an inactivating p53 mutation and was apparently independent of p53 expression. Our data suggest that MDM2 is a promising target in TNBC and clinical-stage MDM2 inhibitors should be further evaluated for their potential therapeutic application. Full article
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