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18 pages, 2512 KiB  
Article
Synergy between BRD9- and IKZF3-Targeting as a Therapeutic Strategy for Multiple Myeloma
by Basudev Chowdhury, Swati Garg, Wei Ni, Martin Sattler, Dana Sanchez, Chengcheng Meng, Taisei Akatsu, Richard Stone, William Forrester, Edmund Harrington, Sara J. Buhrlage, James D. Griffin and Ellen Weisberg
Cancers 2024, 16(7), 1319; https://doi.org/10.3390/cancers16071319 (registering DOI) - 28 Mar 2024
Abstract
Progress in the treatment of multiple myeloma (MM) has resulted in improvement in the survival rate for younger patients but not for patients >65. Thus, there is a need for more efficacious therapies. We and others have shown that bromodomain-containing protein 9 (BRD9), [...] Read more.
Progress in the treatment of multiple myeloma (MM) has resulted in improvement in the survival rate for younger patients but not for patients >65. Thus, there is a need for more efficacious therapies. We and others have shown that bromodomain-containing protein 9 (BRD9), a member of the non-canonical SWI/SNF chromatin remodeling complex, plays a role in MM cell survival, and targeting BRD9 selectively blocks MM cell proliferation and synergizes with IMiDs. We found that synergy in vitro is associated with the downregulation of MYC and Ikaros proteins, including IKZF3, and overexpression of IKZF3 or MYC could partially reverse synergy. RNA-seq analysis revealed synergy to be associated with the suppression of pathways associated with MYC and E2F target genes and pathways, including cell cycle, cell division, and DNA replication. Stimulated pathways included cell adhesion and immune and inflammatory response. Importantly, combining IMiD treatment and BRD9 targeting, which leads to the downregulation of MYC protein and upregulation of CRBN protein, was able to override IMiD resistance of cells exposed to iberdomide in long-term culture. Taken together, our results support the notion that combination therapy based on agents targeting BRD9 and IKZF3, two established dependencies in MM, represents a promising novel therapeutic strategy for MM and IMiD-resistant disease. Full article
(This article belongs to the Special Issue Signaling Pathways in Multiple Myeloma)
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23 pages, 10525 KiB  
Article
Ocean Satellite Data Fusion for High-Resolution Surface Current Maps
by Alisa Kugusheva, Hannah Bull, Evangelos Moschos, Artemis Ioannou, Briac Le Vu and Alexandre Stegner
Remote Sens. 2024, 16(7), 1182; https://doi.org/10.3390/rs16071182 (registering DOI) - 28 Mar 2024
Abstract
Real-time reconstruction of ocean surface currents is a challenge due to the complex, non-linear dynamics of the ocean, the small number of in situ measurements, and the spatio-temporal heterogeneity of satellite altimetry observations. To address this challenge, we introduce HIRES-CURRENTS-Net, an operational real-time [...] Read more.
Real-time reconstruction of ocean surface currents is a challenge due to the complex, non-linear dynamics of the ocean, the small number of in situ measurements, and the spatio-temporal heterogeneity of satellite altimetry observations. To address this challenge, we introduce HIRES-CURRENTS-Net, an operational real-time convolutional neural network (CNN) model for daily ocean current reconstruction. This study focuses on the Mediterranean Sea, a region where operational models have great difficulty predicting surface currents. Notably, our model showcases higher accuracy compared to commonly used alternative methods. HIRES-CURRENTS-Net integrates high-resolution measurements from the infrared or visible spectrum—high resolution Sea Surface Temperature (SST) or chlorophyll (CHL) images—in addition to the low-resolution Sea Surface Height (SSH) maps derived from satellite altimeters. In the first stage, we apply a transfer learning method which uses a high-resolution numerical model to pre-train our CNN model on simulated SSH and SST data with synthetic clouds. The observation of System Simulation Experiments (OSSEs) offers us a sufficient training dataset with reference surface currents at very high resolution, and a model trained on this data can then be applied to real data. In the second stage, to enhance the real-time operational performance of our model over previous methods, we fine-tune the CNN model on real satellite data using a novel pseudo-labeling strategy. We validate HIRES-CURRENTS-Net on real data from drifters and demonstrate that our data-driven approach proves effective for real-time sea surface current reconstruction with potential operational applications such as ship routing. Full article
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17 pages, 2365 KiB  
Article
Characterization of CD34+ Cells from Patients with Acute Myeloid Leukemia (AML) and Myelodysplastic Syndromes (MDS) Using a t-Distributed Stochastic Neighbor Embedding (t-SNE) Protocol
by Cathrin Nollmann, Wiebke Moskorz, Christian Wimmenauer, Paul S. J?ger, Ron P. Cadeddu, J?rg Timm, Thomas Heinzel and Rainer Haas
Cancers 2024, 16(7), 1320; https://doi.org/10.3390/cancers16071320 (registering DOI) - 28 Mar 2024
Abstract
Using multi-color flow cytometry analysis, we studied the immunophenotypical differences between leukemic cells from patients with AML/MDS and hematopoietic stem and progenitor cells (HSPCs) from patients in complete remission (CR) following their successful treatment. The panel of markers included CD34, CD38, CD45RA, CD123 [...] Read more.
Using multi-color flow cytometry analysis, we studied the immunophenotypical differences between leukemic cells from patients with AML/MDS and hematopoietic stem and progenitor cells (HSPCs) from patients in complete remission (CR) following their successful treatment. The panel of markers included CD34, CD38, CD45RA, CD123 as representatives for a hierarchical hematopoietic stem and progenitor cell (HSPC) classification as well as programmed death ligand 1 (PD-L1). Rather than restricting the evaluation on a 2- or 3-dimensional analysis, we applied a t-distributed stochastic neighbor embedding (t-SNE) approach to obtain deeper insight and segregation between leukemic cells and normal HPSCs. For that purpose, we created a t-SNE map, which resulted in the visualization of 27 cell clusters based on their similarity concerning the composition and intensity of antigen expression. Two of these clusters were “leukemia-related” containing a great proportion of CD34+/CD38 hematopoietic stem cells (HSCs) or CD34+ cells with a strong co-expression of CD45RA/CD123, respectively. CD34+ cells within the latter cluster were also highly positive for PD-L1 reflecting their immunosuppressive capacity. Beyond this proof of principle study, the inclusion of additional markers will be helpful to refine the differentiation between normal HSPCs and leukemic cells, particularly in the context of minimal disease detection and antigen-targeted therapeutic interventions. Furthermore, we suggest a protocol for the assignment of new cell ensembles in quantitative terms, via a numerical value, the Pearson coefficient, based on a similarity comparison of the t-SNE pattern with a reference. Full article
(This article belongs to the Topic AI in Medical Imaging and Image Processing)
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17 pages, 4054 KiB  
Article
Experimental Investigation on the Effects of Mineral Water Composition on the Leaching of Cement-Based Materials
by Alienor Pouyanne, Sonia Boudache, Beno?t Hilloulin, Ahmed Loukili and Emmanuel Roziere
Materials 2024, 17(7), 1548; https://doi.org/10.3390/ma17071548 (registering DOI) - 28 Mar 2024
Abstract
The common phenomenon observed for concrete in aggressive water is leaching, which involves the dissolution of cement hydration products. Many studies have focused on leaching in demineralised water or acid attacks, but mineral water still deserves further investigation. In most standards, the aggressiveness [...] Read more.
The common phenomenon observed for concrete in aggressive water is leaching, which involves the dissolution of cement hydration products. Many studies have focused on leaching in demineralised water or acid attacks, but mineral water still deserves further investigation. In most standards, the aggressiveness of a given water body is determined by its pH and not its composition. The effect of the calcium content of the water on degradation is yet to be determined. In this paper, the leaching of Portland cement-based mortar was induced by two types of drinking water with different calcium contents and buffer capacity in controlled conditions. The Langelier saturation index (LSI) was used to describe water aggressiveness based on the calco-carbonic equilibrium. The studied waters had the same pH but LSIs of +0.5 and −1.0 corresponding to scaling with respect to aggressive water; demineralised water was used as a reference. Microstructural damage was checked by TGA and X-ray microtomography. Macroscopic measurements were used to monitor global degradation. The soft water caused a 53% deeper deterioration of the mortar sample than the hard water. Soft water-induced leaching was found to be similar yet slower to leaching via demineralised water (with a mass loss of −2.01% and −2.16% after 200 days, respectively). In contrast, hard water induced strongly time-dependent leaching, and the damage was located close to the surface. The roughness of leached specimens was 18% higher in hard water than in soft water. The formation of calcite on the sample surface not only affects the leaching rate by creating a protective surface layer, but it could also act as a calcium ion pump. Full article
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17 pages, 2819 KiB  
Article
Selective Genotyping and Phenotyping for Optimization of Genomic Prediction Models for Populations with Different Diversity
by Marina ?eran, Vuk ?or?evi?, Jegor Miladinovi?, Marjana Vasiljevi?, Vojin ?uki?, Predrag Ran?elovi? and Simona Ja?imovi?
Plants 2024, 13(7), 975; https://doi.org/10.3390/plants13070975 (registering DOI) - 28 Mar 2024
Abstract
To overcome the different challenges to food security caused by a growing population and climate change, soybean (Glycine max (L.) Merr.) breeders are creating novel cultivars that have the potential to improve productivity while maintaining environmental sustainability. Genomic selection (GS) is an [...] Read more.
To overcome the different challenges to food security caused by a growing population and climate change, soybean (Glycine max (L.) Merr.) breeders are creating novel cultivars that have the potential to improve productivity while maintaining environmental sustainability. Genomic selection (GS) is an advanced approach that may accelerate the rate of genetic gain in breeding using genome-wide molecular markers. The accuracy of genomic selection can be affected by trait architecture and heritability, marker density, linkage disequilibrium, statistical models, and training set. The selection of a minimal and optimal marker set with high prediction accuracy can lower genotyping costs, computational time, and multicollinearity. Selective phenotyping could reduce the number of genotypes tested in the field while preserving the genetic diversity of the initial population. This study aimed to evaluate different methods of selective genotyping and phenotyping on the accuracy of genomic prediction for soybean yield. The evaluation was performed on three populations: recombinant inbred lines, multifamily diverse lines, and germplasm collection. Strategies adopted for marker selection were as follows: SNP (single nucleotide polymorphism) pruning, estimation of marker effects, randomly selected markers, and genome-wide association study. Reduction of the number of genotypes was performed by selecting a core set from the initial population based on marker data, yet maintaining the original population’s genetic diversity. Prediction ability using all markers and genotypes was different among examined populations. The subsets obtained by the model-based strategy can be considered the most suitable for marker selection for all populations. The selective phenotyping based on makers in all cases had higher values of prediction ability compared to minimal values of prediction ability of multiple cycles of random selection, with the highest values of prediction obtained using AN approach and 75% population size. The obtained results indicate that selective genotyping and phenotyping hold great potential and can be integrated as tools for improving or retaining selection accuracy by reducing genotyping or phenotyping costs for genomic selection. Full article
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13 pages, 3545 KiB  
Article
The Optimization of the Steam-Heat-Treated Process of Rattan (Calamus Simplicifolius) Based on the Response Surface Analysis and Its Chemical Changes
by Minmin Xu, Zhihui Wang, Zhenrui Li, Zhenbing Sun, Lili Shang, Genlin Tian, Jianfeng Ma and Xing’e Liu
Forests 2024, 15(4), 615; https://doi.org/10.3390/f15040615 (registering DOI) - 28 Mar 2024
Abstract
The objective of this study is to investigate the impacts of steam heat treatment parameters (e.g., temperature, time, and pressure) on the impact toughness of rattan (Calamus Simplicifolius). The Box–Behnken design response surface analysis was employed to optimize the steam heat [...] Read more.
The objective of this study is to investigate the impacts of steam heat treatment parameters (e.g., temperature, time, and pressure) on the impact toughness of rattan (Calamus Simplicifolius). The Box–Behnken design response surface analysis was employed to optimize the steam heat treatment parameters. Impact toughness was selected as the evaluation index, with single-factor tests conducted as a baseline for comparison. Changes in chemical composition, cellulose crystallinity, and pyrolysis properties were analyzed using X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectra, Thermogravimetry–Fourier transform infrared (TG-FTIR) spectra, and wet-chemistry methods for both untreated control samples and the heat-treated samples. The results show that a 1 h steam heat treatment at 160 °C under 0.1 MPa pressure has the optimal process parameters for the rattan. The achieved impact toughness value closely matches the predicted value at 71.29 kJ/m2. After the steam heat treatment, hemicellulose and cellulose contents decrease, whereas relative lignin content increases significantly, leading to improved toughness characteristics in Calamus Simplicifolius samples. The TG results indicate that maximum weight loss occurs at temperatures of 352 °C, 354 °C, and 361 °C, respectively, for three different samples. This suggests that the thermal stability is enhanced as a result of the heat treatment. These findings will help optimize the heat treatments of the rattan material. Full article
(This article belongs to the Section Wood Science and Forest Products)
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15 pages, 10685 KiB  
Article
Dysregulated Glucuronidation of Bilirubin Exacerbates Liver Inflammation and Fibrosis in Schistosomiasis Japonica through the NF-κB Signaling Pathway
by Qingkai Xue, Yuyan Wang, Yiyun Liu, Haiyong Hua, Xiangyu Zhou, Yongliang Xu, Ying Zhang, Chunrong Xiong, Xinjian Liu, Kun Yang and Yuzheng Huang
Pathogens 2024, 13(4), 287; https://doi.org/10.3390/pathogens13040287 (registering DOI) - 28 Mar 2024
Abstract
Hepatic fibrosis is an important pathological manifestation of chronic schistosome infection. Patients with advanced schistosomiasis show varying degrees of abnormalities in liver fibrosis indicators and bilirubin metabolism. However, the relationship between hepatic fibrosis in schistosomiasis and dysregulated bilirubin metabolism remains unclear. In this [...] Read more.
Hepatic fibrosis is an important pathological manifestation of chronic schistosome infection. Patients with advanced schistosomiasis show varying degrees of abnormalities in liver fibrosis indicators and bilirubin metabolism. However, the relationship between hepatic fibrosis in schistosomiasis and dysregulated bilirubin metabolism remains unclear. In this study, we observed a positive correlation between total bilirubin levels and the levels of ALT, AST, LN, and CIV in patients with advanced schistosomiasis. Additionally, we established mouse models at different time points following S. japonicum infection. As the infection time increased, liver fibrosis escalated, while liver UGT1A1 consistently exhibited a low expression, indicating impaired glucuronidation of bilirubin metabolism in mice. In vitro experiments suggested that SEA may be a key inhibitor of hepatic UGT1A1 expression after schistosome infection. Furthermore, a high concentration of bilirubin activated the NF-κB signaling pathway in L-O2 cells in vitro. These findings suggested that the dysregulated glucuronidation of bilirubin caused by S. japonicum infection may play a significant role in schistosomiasis liver fibrosis through the NF-κB signaling pathway. Full article
(This article belongs to the Special Issue Schistosomiasis—Where Are We and Where Do We Want to Go?)
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27 pages, 1241 KiB  
Article
Computational Ensemble Gene Co-Expression Networks for the Analysis of Cancer Biomarkers
by Julia Figueroa-Martínez, Dulcenombre M. Saz-Navarro, Aurelio López-Fernández, Domingo S. Rodríguez-Baena and Francisco A. Gómez-Vela
Informatics 2024, 11(2), 14; https://doi.org/10.3390/informatics11020014 (registering DOI) - 28 Mar 2024
Abstract
Gene networks have become a powerful tool for the comprehensive examination of gene expression patterns. Thanks to these networks generated by means of inference algorithms, it is possible to study different biological processes and even identify new biomarkers for such diseases. These biomarkers [...] Read more.
Gene networks have become a powerful tool for the comprehensive examination of gene expression patterns. Thanks to these networks generated by means of inference algorithms, it is possible to study different biological processes and even identify new biomarkers for such diseases. These biomarkers are essential for the discovery of new treatments for genetic diseases such as cancer. In this work, we introduce an algorithm for genetic network inference based on an ensemble method that improves the robustness of the results by combining two main steps: first, the evaluation of the relationship between pairs of genes using three different co-expression measures, and, subsequently, a voting strategy. The utility of this approach was demonstrated by applying it to a human dataset encompassing breast and prostate cancer-associated stromal cells. Two gene networks were computed using microarray data, one for breast cancer and one for prostate cancer. The results obtained revealed, on the one hand, distinct stromal cell behaviors in breast and prostate cancer and, on the other hand, a list of potential biomarkers for both diseases. In the case of breast tumor, ST6GAL2, RIPOR3, COL5A1, and DEPDC7 were found, and in the case of prostate tumor, the genes were GATA6-AS1, ARFGEF3, PRR15L, and APBA2. These results demonstrate the usefulness of the ensemble method in the field of biomarker discovery. Full article
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19 pages, 7951 KiB  
Article
Population Variation and Phylogeography of Cherry Blossom (Prunus conradinae) in China
by Jingjing Dong, Xiangui Yi, Xianrong Wang, Meng Li, Xiangzhen Chen, Shucheng Gao, Wenyi Fu, Siyu Qian, Xinglin Zeng and Yingke Yun
Plants 2024, 13(7), 974; https://doi.org/10.3390/plants13070974 (registering DOI) - 28 Mar 2024
Abstract
Prunus conradinae (subgenus Cerasus, Rosaceae) is a significant germplasm resource of wild cherry blossom in China. To ensure the comprehensiveness of this study, we used a large sample size (12 populations comprising 244 individuals) which involved the fresh leaves of P. conradinae [...] Read more.
Prunus conradinae (subgenus Cerasus, Rosaceae) is a significant germplasm resource of wild cherry blossom in China. To ensure the comprehensiveness of this study, we used a large sample size (12 populations comprising 244 individuals) which involved the fresh leaves of P. conradinae in Eastern, Central, and Southwestern China. We combined morphological and molecular evidence (three chloroplast DNA (cpDNA) sequences and one nuclear DNA (nr DNA) sequence) to examine the population of P. conradinae variation and differentiation. Our results revealed that Central, East, and Southwest China are important regions for the conservation of P. conradinae to ensure adequate germplasm resources in the future. We also found support for a new variant, P. conradinae var. rubrum. We observed high genetic diversity within P. conradinae (haplotype diversity [Hd] = 0.830; ribotype diversity [Rd] = 0.798), with novel genetic variation and a distinct genealogical structure among populations. There was genetic variation among populations and phylogeographic structure among populations and three geographical groups (Central, East, and Southwest China). The genetic differentiation coefficient was the lowest in the Southwest region and the gene exchange was obvious, while the differentiation was obvious in Central China. In the three geographic groups, we identified two distinct lineages: an East China lineage (Central China and East China) and a Southwest China lineage ((Central China and Southwest China) and East China). These two lineages originated approximately 4.38 million years ago (Mya) in the early Pliocene due to geographic isolation. P. conradinae expanded from Central China to East China at 3.32 Mya (95% HPD: 1.12–5.17 Mya) in the Pliocene. The population of P. conradinae spread from East China to Southwest China, and the differentiation time was 2.17 Mya (95% (HPD: 0.47–4.54 Mya), suggesting that the population of P. conradinae differentiated first in Central and East China. The population of P. conradinae experienced differentiation from Central China to Southwest China around 1.10 Mya (95% HPD: 0.11–2.85 Mya) during the early Pleistocene of the Quaternary period. The southeastern region of East China, near Mount Wuyi, likely serves as a refuge for P. conradinae. This study establishes a theoretical foundation for the classification, identification, conservation, and exploitation of germplasm resources of P. conradinae. Full article
(This article belongs to the Special Issue Origin and Evolution of the East Asian Flora (EAF))
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15 pages, 14650 KiB  
Article
Study on Process Mineralogy of the Combined Copper Oxide Ore in Tibet and Acid Leaching Behavior with Calcium Fluoride
by Zujiang Pan, Cuo Jian, Zaihua Peng, Xinzhuang Fu, Rui He, Tong Yue and Wei Sun
Minerals 2024, 14(4), 352; https://doi.org/10.3390/min14040352 (registering DOI) - 28 Mar 2024
Abstract
The Yulong copper deposit in Tibet is a typical porphyry copper deposit, with about 30 million tons of copper oxide ore in the surface layer. However, more than 40% of the copper resources are in a combination state, resulting in an extraction efficiency [...] Read more.
The Yulong copper deposit in Tibet is a typical porphyry copper deposit, with about 30 million tons of copper oxide ore in the surface layer. However, more than 40% of the copper resources are in a combination state, resulting in an extraction efficiency of only 50% for copper via the hydrometallurgical process. In this study, the process mineralogy of the combined copper oxide ore was systematically investigated and a calcium fluoride-enhanced leaching process is proposed to increase the leaching efficiency of the combined copper ore. The process mineralogy of the combined copper oxide ore was analyzed using various testing techniques, including chemical analysis, X-ray diffraction, and a process mineralogy parameter testing system (Mineral Liberation Analysis). The results revealed that limonite accounted for 86.12% of the sample, and 63.51% of the copper resource existed in the form of combined copper oxide in limonite. However, it is difficult for the uniformly distributed combined copper oxide in limonite to sufficiently make contact with sulfuric acid, which is the leaching agent, resulting in low copper leaching efficiency. The enhanced leaching behavior of the combined copper oxide ores was also investigated, thereby determining effective and economical enhanced leaching conditions. Under optimal conditions, at a grinding fineness ratio of −0.074 mm (accounting for 85%), liquid-solid ratio of 4:1, sulfuric acid concentration of 50 g/L, temperature of 30 °C, CaF2 dosage of 1% of the ore mass, and leaching time of 4 h, the copper leaching efficiency increased to 60.57%, which was 7.34% higher than that of atmospheric pressure leaching. Finally, the enhanced leaching slag was analyzed using an electron probe microanalyzer. It indicated that fluorine ions can erode the combined copper oxide ore and facilitate the diffusion of hydrogen ions inside the limonite, thereby achieving a strengthening effect. Full article
(This article belongs to the Section Mineral Processing and Extractive Metallurgy)
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22 pages, 1533 KiB  
Article
Effects of a Physical Training Program on Cognitive and Physical Performance and Health-Related Variables in Professional esports Players: A Pilot Study
by Manuel Sanz-Matesanz, Luis Manuel Martínez-Aranda and Gemma María Gea-García
Appl. Sci. 2024, 14(7), 2845; https://doi.org/10.3390/app14072845 (registering DOI) - 28 Mar 2024
Abstract
The present study focused on the effects of a physical training program on physical- and psychological-related variables in professional esports players. Five professional League of Legends (LOL) players belonging to the highest national category participated in this study. Data were obtained before and [...] Read more.
The present study focused on the effects of a physical training program on physical- and psychological-related variables in professional esports players. Five professional League of Legends (LOL) players belonging to the highest national category participated in this study. Data were obtained before and after a 5 h virtual training session (acute), as well as before and after an 8-week intervention period, focused on decreasing the impact of fatigue on players’ health and performance. The results showed that a complete virtual training session influences their performance, decreasing jump height and joint mobility (p < 0.01), as well as increasing perceived physical and cognitive exertion by 76.9% (p < 0.01) and 166.67% on the “Rating of Fatigue” scale (p = 0.002). Moreover, the intervention was able to reduce the impact of fatigue (30.8% and 43.3% reduction in cognitive and overall fatigue, respectively, p < 0.05), improving, at the same time, the amount of muscle mass by 2%, jumping ability by 9.8% to 21%, and strength levels in various exercises by 63% to 173% (p < 0.01). The implementation of a physical training program is capable of reducing the players’ fatigue perception, improving their physical conditioning and health status, and decreasing the injury risk. Full article
(This article belongs to the Special Issue Human Performance and Health in Sports)
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12 pages, 1396 KiB  
Article
Bio-Inoculation of Tomato (Solanum lycopersicum L.) and Jalapeño Pepper (Capsicum annuum L.) with Enterobacter sp. DBA51 Increases Growth and Yields under Open-Field Conditions
by John Paul Délano-Frier, Alberto Flores-Olivas and José Humberto Valenzuela-Soto
Agronomy 2024, 14(4), 702; https://doi.org/10.3390/agronomy14040702 (registering DOI) - 28 Mar 2024
Abstract
The rhizobacterium Enterobacter sp. DBA51 (DBA51), isolated from the semi-desert in Coahuila, Mexico, was previously found to increase the vegetative growth of tomato and tobacco plants cultivated under greenhouse conditions. The present report describes the results obtained from two independent open-field experiments performed [...] Read more.
The rhizobacterium Enterobacter sp. DBA51 (DBA51), isolated from the semi-desert in Coahuila, Mexico, was previously found to increase the vegetative growth of tomato and tobacco plants cultivated under greenhouse conditions. The present report describes the results obtained from two independent open-field experiments performed with tomato and jalapeño pepper commercial crops inoculated with DBA51. Additionally, plants inoculated with Bacillus subtilis LPM1 (LPM1) and uninoculated plants were included as positive and negative controls, respectively. DBA51 and LPM1 significantly promoted growth at vegetative stages in the tomato plants; this effect was evident in the stem diameter (DBA51 with p < 0.0001 and LPM1 with p < 0.0001) and height (DBA51 with p < 0.0001 and LPM1 with p < 0.0001) of the tomato plants. However, no differences were detected in the jalapeño pepper plants. Additionally, DBA51 and LPM1 treatments increased tomato fruit production by 80% and 31%, respectively, compared to uninoculated plants. A similar increase in yield was recorded in DBA51- and LPM1-treated jalapeño pepper plants, which was 75% and 56% higher than uninoculated controls, respectively. These results strongly recommend the potential use of DBA51 as a biofertilizer in horticultural crops. Full article
(This article belongs to the Section Agricultural Biosystem and Biological Engineering)
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20 pages, 27313 KiB  
Article
A Digital Twin for Assessing the Remaining Useful Life of Offshore Wind Turbine Structures
by Rafael Pacheco-Blazquez, Julio Garcia-Espinosa, Daniel Di Capua and Andres Pastor Sanchez
J. Mar. Sci. Eng. 2024, 12(4), 573; https://doi.org/10.3390/jmse12040573 (registering DOI) - 28 Mar 2024
Abstract
This paper delves into the application of digital twin monitoring techniques for enhancing offshore floating wind turbine performance, with a detailed case study that uses open-source digital twin software. We explore the practical implementation of digital twins and their efficacy in optimizing operations [...] Read more.
This paper delves into the application of digital twin monitoring techniques for enhancing offshore floating wind turbine performance, with a detailed case study that uses open-source digital twin software. We explore the practical implementation of digital twins and their efficacy in optimizing operations and predictive maintenance, focusing on controlling the real-time structural state of composite wind turbine structures and forecasting the remaining useful life by tracking the fatigue state in the structure. Our findings emphasize digital twins’ potential as a valuable tool for renewable energy, driving efficiency and sustainability in offshore floating wind installations. These aspects, along with the aforementioned simulations, whether in real-time or forecasted, reduce costly and unnecessary inspections and scheduled maintenance. Full article
(This article belongs to the Special Issue Ocean Digital Twins)
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16 pages, 9798 KiB  
Article
Modeling and Subjective Evaluation Method of Driveability for Fuel Cell Vehicles
by Jun Zhan, Huainan Zhu, Chunguang Duan, Zhao-Hui Zhong, Wei Huang, Baoli Zhu and Guangjian Xu
Energies 2024, 17(7), 1620; https://doi.org/10.3390/en17071620 (registering DOI) - 28 Mar 2024
Abstract
Aiming at the demand for subjective evaluation of driveability for fuel cell vehicles, the modeling and evaluation method of driveability for fuel cell vehicles were studied in this paper. Firstly, a real-time model of the fuel cell vehicle powertrain system was established, which [...] Read more.
Aiming at the demand for subjective evaluation of driveability for fuel cell vehicles, the modeling and evaluation method of driveability for fuel cell vehicles were studied in this paper. Firstly, a real-time model of the fuel cell vehicle powertrain system was established, which included the fuel cell model, power battery model, DC/DC converter model and drive motor model. Secondly, it was integrated with the vehicle dynamics model to form a virtual prototype of a fuel cell vehicle. And a virtual subjective evaluation platform for fuel cell vehicles was built by combining the virtual prototype and high-fidelity driving simulator. Thirdly, a subjective evaluation method of driveability for fuel cell vehicles was proposed, which included the starting performance, acceleration performance, uniform speed performance and tip-in/tip-out performance. Finally, the paper used the platform and method mentioned above to conduct subjective evaluations of the fuel cell vehicles. Full article
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17 pages, 4543 KiB  
Article
A Recent Development of a Network Approach to Assessment Data: Latent Space Item Response Modeling for Intelligence Studies
by Inhan Kang and Minjeong Jeon
J. Intell. 2024, 12(4), 38; https://doi.org/10.3390/jintelligence12040038 (registering DOI) - 28 Mar 2024
Abstract
This article aims to provide an overview of the potential advantages and utilities of the recently proposed Latent Space Item Response Model (LSIRM) in the context of intelligence studies. The LSIRM integrates the traditional Rasch IRT model for psychometric data with the latent [...] Read more.
This article aims to provide an overview of the potential advantages and utilities of the recently proposed Latent Space Item Response Model (LSIRM) in the context of intelligence studies. The LSIRM integrates the traditional Rasch IRT model for psychometric data with the latent space model for network data. The model has person-wise latent abilities and item difficulty parameters, capturing the main person and item effects, akin to the Rasch model. However, it additionally assumes that persons and items can be mapped onto the same metric space called a latent space and distances between persons and items represent further decreases in response accuracy uncaptured by the main model parameters. In this way, the model can account for conditional dependence or interactions between persons and items unexplained by the Rasch model. With two empirical datasets, we illustrate that (1) the latent space can provide information on respondents and items that cannot be captured by the Rasch model, (2) the LSIRM can quantify and visualize potential between-person variations in item difficulty, (3) latent dimensions/clusters of persons and items can be detected or extracted based on their latent positions on the map, and (4) personalized feedback can be generated from person-item distances. We conclude with discussions related to the latent space modeling integrated with other psychometric models and potential future directions. Full article
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26 pages, 2705 KiB  
Review
Neurofilament Light Chains in Systemic Amyloidosis: A Systematic Review
by Milou Berends, Hans L. A. Nienhuis, David Adams, Chafic Karam, Marco Luigetti, Michael Polydefkis, Mary M. Reilly, Yoshiki Sekijima and Bouke P. C. Hazenberg
Int. J. Mol. Sci. 2024, 25(7), 3770; https://doi.org/10.3390/ijms25073770 (registering DOI) - 28 Mar 2024
Abstract
Peripheral and autonomic neuropathy are common disease manifestations in systemic amyloidosis. The neurofilament light chain (NfL), a neuron-specific biomarker, is released into the blood and cerebrospinal fluid after neuronal damage. There is a need for an early and sensitive blood biomarker for polyneuropathy, [...] Read more.
Peripheral and autonomic neuropathy are common disease manifestations in systemic amyloidosis. The neurofilament light chain (NfL), a neuron-specific biomarker, is released into the blood and cerebrospinal fluid after neuronal damage. There is a need for an early and sensitive blood biomarker for polyneuropathy, and this systematic review provides an overview on the value of NfL in the early detection of neuropathy, central nervous system involvement, the monitoring of neuropathy progression, and treatment effects in systemic amyloidosis. A literature search in PubMed, Embase, and Web of Science was performed on 14 February 2024 for studies investigating NfL levels in patients with systemic amyloidosis and transthyretin gene-variant (TTRv) carriers. Only studies containing original data were included. Included were thirteen full-text articles and five abstracts describing 1604 participants: 298 controls and 1306 TTRv carriers or patients with or without polyneuropathy. Patients with polyneuropathy demonstrated higher NfL levels compared to healthy controls and asymptomatic carriers. Disease onset was marked by rising NfL levels. Following the initiation of transthyretin gene-silencer treatment, NfL levels decreased and remained stable over an extended period. NfL is not an outcome biomarker, but an early and sensitive disease-process biomarker for neuropathy in systemic amyloidosis. Therefore, NfL has the potential to be used for the early detection of neuropathy, monitoring treatment effects, and monitoring disease progression in patients with systemic amyloidosis. Full article
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
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24 pages, 14203 KiB  
Review
Fractal Metasurfaces and Antennas: An Overview for Advanced Applications in Wireless Communications
by Francesca Venneri, Sandra Costanzo and Antonio Borgia
Appl. Sci. 2024, 14(7), 2843; https://doi.org/10.3390/app14072843 (registering DOI) - 28 Mar 2024
Abstract
This paper provides an overview of fractal antennas and metasurfaces, exploring their design principles, performance, and applications. Fractal antennas, incorporating self-similar geometric shapes, offer several advantages, such as their multiband operation, compact size, and improved performance. Metasurfaces, on the other hand, are two-dimensional [...] Read more.
This paper provides an overview of fractal antennas and metasurfaces, exploring their design principles, performance, and applications. Fractal antennas, incorporating self-similar geometric shapes, offer several advantages, such as their multiband operation, compact size, and improved performance. Metasurfaces, on the other hand, are two-dimensional structures composed of subwavelength unit cells and are designed to achieve advantageous and unusual electromagnetic properties by enabling precise control over electromagnetic waves. This paper discusses the fundamental concepts of fractal antennas and metasurfaces, compares their characteristics, and presents the latest advances in research. Additionally, it highlights applications in wireless communications, energy harvesting, sensing, and beyond. Full article
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16 pages, 808 KiB  
Article
“I Wouldn’t Even Know What to Ask for”: Patients’ and Caregivers’ Experiences of Psychological Support for Huntington’s Disease in Italy
by Nicolò Zarotti, Barbara D’Alessio, Marta Scocchia, Melissa Casella and Ferdinando Squitieri
NeuroSci 2024, 5(2), 98-113; https://doi.org/10.3390/neurosci5020007 (registering DOI) - 28 Mar 2024
Abstract
People with Huntington’s disease (HD) often experience psychological difficulties linked with disease progression and the adjustment to living with a chronic condition, which are also frequently shared by their informal caregivers (e.g., partners). Although limited, the current literature on psychological care for people [...] Read more.
People with Huntington’s disease (HD) often experience psychological difficulties linked with disease progression and the adjustment to living with a chronic condition, which are also frequently shared by their informal caregivers (e.g., partners). Although limited, the current literature on psychological care for people with HD shows that interventions have the potential to drive improvements in mental health and quality of life. However, the experience of accessing and receiving psychological support for HD remains unclear across several countries. This study adopted a qualitative design to explore the experiences of psychological support for HD from the perspectives of patients and caregivers living in Italy. Semi-structured interviews were carried out with 14 participants—7 patients with early-manifest HD and 7 partners acting as their caregivers. The resulting data were analysed through thematic analysis. Four overarching themes were identified: (1) the availability of psychological support for HD, (2) barriers to accessing psychological support, (3) enablers to accessing psychological support, and (4) the future development of public psychological provision for HD. In Italy, patients and caregivers perceive public psychological support for HD as unavailable or inadequate, and private therapy is often seen as unaffordable. Barriers such as distrust in public healthcare and preconceptions about therapy may limit access, while advice from HD organisations and seeking therapy for other reasons may act as enablers. A strong emphasis is put on the need for accessible public psychological support throughout all the stages of the condition. Full article
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13 pages, 10486 KiB  
Article
A Method for Analyzing the Phenotypes of Nonheading Chinese Cabbage Leaves Based on Deep Learning and OpenCV Phenotype Extraction
by Haobin Xu, Linxiao Fu, Jinnian Li, Xiaoyu Lin, Lingxiao Chen, Fenglin Zhong and Maomao Hou
Agronomy 2024, 14(4), 699; https://doi.org/10.3390/agronomy14040699 (registering DOI) - 28 Mar 2024
Abstract
Nonheading Chinese cabbage is an important leafy vegetable, and quantitative identification and automated analysis of nonheading Chinese cabbage leaves are crucial for cultivating new varieties with higher quality, yield, and resistance. Traditional leaf phenotypic analysis relies mainly on phenotypic observation and the practical [...] Read more.
Nonheading Chinese cabbage is an important leafy vegetable, and quantitative identification and automated analysis of nonheading Chinese cabbage leaves are crucial for cultivating new varieties with higher quality, yield, and resistance. Traditional leaf phenotypic analysis relies mainly on phenotypic observation and the practical experience of breeders, leading to issues such as time consumption, labor intensity, and low precision, which result in low breeding efficiency. Considering these issues, a method for the extraction and analysis of phenotypes of nonheading Chinese cabbage leaves is proposed, targeting four qualitative traits and ten quantitative traits from 1500 samples, by integrating deep learning and OpenCV image processing technology. First, a leaf classification model is trained using YOLOv8 to infer the qualitative traits of the leaves, followed by the extraction and calculation of the quantitative traits of the leaves using OpenCV image processing technology. The results indicate that the model achieved an average accuracy of 95.25%, an average precision of 96.09%, an average recall rate of 96.31%, and an average F1 score of 0.9620 for the four qualitative traits. From the ten quantitative traits, the OpenCV-calculated values for the whole leaf length, leaf width, and total leaf area were compared with manually measured values, showing RMSEs of 0.19 cm, 0.1762 cm, and 0.2161 cm2, respectively. Bland–Altman analysis indicated that the error values were all within the 95% confidence intervals, and the average detection time per image was 269 ms. This method achieved good results in the extraction of phenotypic traits from nonheading Chinese cabbage leaves, significantly reducing the personpower and time costs associated with genetic resource analysis. This approach provides a new technique for the analysis of nonheading Chinese cabbage genetic resources that is high-throughput, precise, and automated. Full article
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14 pages, 12833 KiB  
Article
Exploring the PpEXPs Family in Peach: Insights into Their Role in Fruit Texture Development through Identification and Transcriptional Analysis
by Yakun Guo, Conghao Song, Fan Gao, Yixin Zhi, Xianbo Zheng, Xiaobei Wang, Haipeng Zhang, Nan Hou, Jun Cheng, Wei Wang, Langlang Zhang, Xia Ye, Jidong Li, Bin Tan, Xiaodong Lian and Jiancan Feng
Horticulturae 2024, 10(4), 332; https://doi.org/10.3390/horticulturae10040332 (registering DOI) - 28 Mar 2024
Abstract
Expansins (EXPs) loosen plant cell walls and are involved in diverse developmental processes through modifying cell-walls; however, little is known about the role of PpEXPs in peach fruit. In this study, 26 PpEXP genes were identified in the peach genome and grouped into [...] Read more.
Expansins (EXPs) loosen plant cell walls and are involved in diverse developmental processes through modifying cell-walls; however, little is known about the role of PpEXPs in peach fruit. In this study, 26 PpEXP genes were identified in the peach genome and grouped into four subfamilies, with 20 PpEXPAs, three PpEXPBs, one PpEXPLA and two PpEXPLBs. The 26 PpEXPs were mapped on eight chromosomes. The primary mode of gene duplication of the PpEXPs was dispersed gene duplication (DSD, 50%). Notably, cis-elements involved in light responsiveness and MeJA-responsiveness were detected in the promoter regions of all PpEXPs, while ethylene responsive elements were observed in 12 PpEXPs. Transcript profiling of PpEXPs in the peach fruit varieties of MF (melting), NMF (non-melting) and SH (stony hard) at different stages showed that PpEXPs displayed distinct expression patterns. Among the 26 PpEXPs, 15 PpEXPs were expressed in the fruit. Combining the expressing patterns of PpEXPs in fruits with different flesh textures, PpEXPA7, PpEXPA13 and PpEXPA15 were selected as candidate genes, as they were highly consistent with the patterns of previous reported key genes (PpPGM, PpPGF and PpYUC11) in regard to peach fruit texture. The genes with different expression patterns between MF and NMF were divided into 16 modules, of which one module, with pink and midnightblue, negatively correlated with the phenotype of fruit firmness and was identified as PpEXPA1 and PpEXPA7, while the other module was identified as PpERF in the pink module, which might potentially effect fruit texture development by regulating PpEXPs. These results provide a foundation for the functional characterization of PpEXPs in peach. Full article
(This article belongs to the Special Issue Advances in Developmental Biology in Tree Fruit and Nut Crops)
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24 pages, 25802 KiB  
Article
Towards Transdisciplinary Heritage Assessment: An Analysis of the Use of Landscape Study Methods as a Holistic Toolbox for Cultural Site Characterisation in the Spanish Context
by Celia López-Bravo
Architecture 2024, 4(2), 197-220; https://doi.org/10.3390/architecture4020013 (registering DOI) - 28 Mar 2024
Abstract
This research work arises from the need to design specific techniques for the characterisation of cultural sites. Assuming the increasing complexity of the protection typologies, the expansion of working scales gives thanks to technology and the pursuit of social sustainability objectives. Thus, its [...] Read more.
This research work arises from the need to design specific techniques for the characterisation of cultural sites. Assuming the increasing complexity of the protection typologies, the expansion of working scales gives thanks to technology and the pursuit of social sustainability objectives. Thus, its main objective is to search for innovative tools that other disciplines can contribute to the work of architects specialising in heritage studies. To this end, the research explores the main methodologies, maps, guides, and registers of landscape and historic landscape characterisation developed in Europe, particularly in Spain, over the last 40 years. Considering this intense and profound evolution of landscape analysis, useful strategies for the assessment of cultural sites from their conception in the 21st century arise. Nevertheless, landscape characterisation methods have been mainly developed and applied by geographers and are absent in many urban and territorial heritage studies. In response, this article proposes a new methodological approach focusing on contextual values to be used in the assessment of architectural heritage at the territorial scale. Full article
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18 pages, 27356 KiB  
Article
Deep Ordinal Classification in Forest Areas Using Light Detection and Ranging Point Clouds
by Alejandro Morales-Martín, Francisco-Javier Mesas-Carrascosa, Pedro Antonio Gutiérrez, Fernando-Juan Pérez-Porras, Víctor Manuel Vargas and César Hervás-Martínez
Sensors 2024, 24(7), 2168; https://doi.org/10.3390/s24072168 (registering DOI) - 28 Mar 2024
Abstract
Recent advances in Deep Learning and aerial Light Detection And Ranging (LiDAR) have offered the possibility of refining the classification and segmentation of 3D point clouds to contribute to the monitoring of complex environments. In this context, the present study focuses on developing [...] Read more.
Recent advances in Deep Learning and aerial Light Detection And Ranging (LiDAR) have offered the possibility of refining the classification and segmentation of 3D point clouds to contribute to the monitoring of complex environments. In this context, the present study focuses on developing an ordinal classification model in forest areas where LiDAR point clouds can be classified into four distinct ordinal classes: ground, low vegetation, medium vegetation, and high vegetation. To do so, an effective soft labeling technique based on a novel proposed generalized exponential function (CE-GE) is applied to the PointNet network architecture. Statistical analyses based on Kolmogorov–Smirnov and Student’s t-test reveal that the CE-GE method achieves the best results for all the evaluation metrics compared to other methodologies. Regarding the confusion matrices of the best alternative conceived and the standard categorical cross-entropy method, the smoothed ordinal classification obtains a more consistent classification compared to the nominal approach. Thus, the proposed methodology significantly improves the point-by-point classification of PointNet, reducing the errors in distinguishing between the middle classes (low vegetation and medium vegetation). Full article
(This article belongs to the Special Issue Remote Sensing for Spatial Information Extraction and Process)
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12 pages, 3476 KiB  
Article
Atomic Diffusivities of Yttrium, Titanium and Oxygen Calculated by Ab Initio Molecular Dynamics in Molten 316L Oxide-Dispersion-Strengthened Steel Fabricated via Additive Manufacturing
by Zhengming Wang, Seongun Yang, Stephanie B. Lawson, V. Vinay K. Doddapaneni, Marc Albert, Benjamin Sutton, Chih-Hung Chang, Somayeh Pasebani and Donghua Xu
Materials 2024, 17(7), 1543; https://doi.org/10.3390/ma17071543 (registering DOI) - 28 Mar 2024
Abstract
Oxide-dispersion-strengthened (ODS) steels have long been viewed as a prime solution for harsh environments. However, conventional manufacturing of ODS steels limits the final product geometry, is difficult to scale up to large components, and is expensive due to multiple highly involved, solid-state processing [...] Read more.
Oxide-dispersion-strengthened (ODS) steels have long been viewed as a prime solution for harsh environments. However, conventional manufacturing of ODS steels limits the final product geometry, is difficult to scale up to large components, and is expensive due to multiple highly involved, solid-state processing steps required. Additive manufacturing (AM) can directly incorporate dispersion elements (e.g., Y, Ti and O) during component fabrication, thus bypassing the need for an ODS steel supply chain, the scale-up challenges of powder processing routes, the buoyancy challenges associated with casting ODS steels, and the joining issues for net-shape component fabrication. In the AM process, the diffusion of the dispersion elements in the molten steel plays a key role in the precipitation of the oxide particles, thereby influencing the microstructure, thermal stability and high-temperature mechanical properties of the resulting ODS steels. In this work, the atomic diffusivities of Y, Ti, and O in molten 316L stainless steel (SS) as functions of temperature are determined by ab initio molecular dynamics simulations. The latest Vienna Ab initio Simulation Package (VASP) package that incorporates an on-the-fly machine learning force field for accelerated computation is used. At a constant temperature, the time-dependent coordinates of the target atoms in the molten 316L SS were analyzed in the form of mean square displacement in order to obtain diffusivity. The values of the diffusivity at multiple temperatures are then fitted to the Arrhenius form to determine the activation energy and the pre-exponential factor. Given the challenges in experimental measurement of atomic diffusivity at such high temperatures and correspondingly the lack of experimental data, this study provides important physical parameters for future modeling of the oxide precipitation kinetics during AM process. Full article
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