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Francesco Bellanti, Aurelio Lo Buglio, Giuseppe Pannone, Maria Carmela Pedicillo, Ilenia Sara De Stefano, Angela Pignataro, Cristiano Capurso and Gianluigi Vendemiale
Int. J. Mol. Sci.2024, 25(11), 6056; https://doi.org/10.3390/ijms25116056 (registering DOI) - 31 May 2024
Skeletal muscle atrophy (SMA) is caused by a rise in muscle breakdown and a decline in protein synthesis, with a consequent loss of mass and function. This study characterized the effect of an amino acid mixture (AA) in models of SMA, focusing on
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Skeletal muscle atrophy (SMA) is caused by a rise in muscle breakdown and a decline in protein synthesis, with a consequent loss of mass and function. This study characterized the effect of an amino acid mixture (AA) in models of SMA, focusing on mitochondria. C57/Bl6 mice underwent immobilization of one hindlimb (I) or cardiotoxin-induced muscle injury (C) and were compared with controls (CTRL). Mice were then administered AA in drinking water for 10 days and compared to a placebo group. With respect to CTRL, I and C reduced running time and distance, along with grip strength; however, the reduction was prevented by AA. Tibialis anterior (TA) muscles were used for histology and mitochondria isolation. I and C resulted in TA atrophy, characterized by a reduction in both wet weight and TA/body weight ratio and smaller myofibers than those of CTRL. Interestingly, these alterations were lightly observed in mice treated with AA. The mitochondrial yield from the TA of I and C mice was lower than that of CTRL but not in AA-treated mice. AA also preserved mitochondrial bioenergetics in TA muscle from I and C mice. To conclude, this study demonstrates that AA prevents loss of muscle mass and function in SMA by protecting mitochondria.
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Formative assessment (FA) provides lecturers and learners with information about the quality and development of different tasks. Formative feedback becomes an essential element that increases the quality of these tasks, guides learners in the process, and motivates them to be actively involved, acquiring
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Formative assessment (FA) provides lecturers and learners with information about the quality and development of different tasks. Formative feedback becomes an essential element that increases the quality of these tasks, guides learners in the process, and motivates them to be actively involved, acquiring the learning objectives and skills. A digital learning ecosystems (DLE) offers the possibility of a quality, effective, and sustainable education, enabling people to carry on with their training from anywhere, at any time, and through personal pathways. In this framework, we present a descriptive study with a qualitative approach to explore the views of 91 participants regarding the process of FA in second language acquisition (SLA) in a DLE. According to the results, the DLE provides the necessary tools to favour FA, and to obtain valuable data on the learners’ academic achievements in SLA. The learners take an active role in learning English and competence development such as reading, writing, and listening, and other skills such as digital competence, communication, problem solving, empathy, or creativity. The data obtained help lecturers to identify learners’ difficulties in SLA and address them with different didactic strategies. It can be concluded that FA plays a relevant role in SLA in a DLE.
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Irena Barbara Padzińska-Pruszyńska, Muhammad Waqas Akbar, Murat Isbilen, Emilia Górka, Baris Kucukkaraduman, Seçil Demirkol Canlı, Ege Dedeoğlu, Shila Azizolli, Isli Cela, Abbas Guven Akcay, Hasim Hakanoglu, Lubomir Bodnar, Szczepan Cierniak, Zygmunt Kozielec, Jacek Jerzy Pruszyński, Martyna Bittel, Ali Osmay Gure, Magdalena Król and Bartłomiej Taciak
Int. J. Mol. Sci.2024, 25(11), 6054; https://doi.org/10.3390/ijms25116054 (registering DOI) - 31 May 2024
This research paper presents a novel approach to identifying biomarkers that can be used to prognosticate patients with triple-negative breast cancer (TNBC) eligible for neoadjuvant therapy. The study utilized survival and RNA sequencing data from a cohort of TNBC patients and identified 276
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This research paper presents a novel approach to identifying biomarkers that can be used to prognosticate patients with triple-negative breast cancer (TNBC) eligible for neoadjuvant therapy. The study utilized survival and RNA sequencing data from a cohort of TNBC patients and identified 276 genes whose expression was related to survival in such patients. The gene expression data were then used to classify patients into two major groups based on the presence or absence of Wingless/Integrated-pathway (Wnt-pathway) and mesenchymal (Mes) markers (Wnt/Mes). Patients with a low expression of Wnt/Mes-related genes had a favorable outcome, with no deaths observed during follow-up, while patients with a high expression of Wnt/Mes genes had a higher mortality rate of 50% within 19 months. The identified gene list could be validated and potentially used to shape treatment options for TNBC patients eligible for neoadjuvant therapy providing valuable insights into the development of more effective treatments for TNBC. Our data also showed significant variation in gene expression profiles before and after chemotherapy, with most tumors switching to a more mesenchymal/stem cell-like profile. To verify this observation, we performed an in silico analysis to classify breast cancer tumors in Prediction Analysis of Microarray 50 (PAM50) molecular classes before treatment and after treatment using gene expression data. Our findings demonstrate that following drug intervention and metastasis, certain tumors undergo a transition to alternative subtypes, resulting in diminished therapeutic efficacy. This underscores the necessity for reevaluation of patients who have experienced relapse or metastasis post-chemotherapy, with a focus on molecular subtyping. Tailoring treatment strategies based on these refined subtypes is imperative to optimize therapeutic outcomes for affected individuals.
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Background and Objectives: We aimed to develop a predictive model for the outcome of bruxism treatments using ultrasonography (USG)-based machine learning (ML) techniques. This study is a quantitative research study (predictive modeling study) in which different treatment methods applied to bruxism patients are
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Background and Objectives: We aimed to develop a predictive model for the outcome of bruxism treatments using ultrasonography (USG)-based machine learning (ML) techniques. This study is a quantitative research study (predictive modeling study) in which different treatment methods applied to bruxism patients are evaluated through artificial intelligence. Materials and Methods: The study population comprised 102 participants with bruxism in three treatment groups: Manual therapy, Manual therapy and Kinesio Tape or Botulinum Toxin-A injection. USG imaging was performed on the masseter muscle to calculate muscle thickness, and pain thresholds were evaluated using an algometer. A radiomics platform was utilized to handle imaging and clinical data, as well as to perform a subsequent radiomics statistical analysis. Results: The area under the curve (AUC) values of all machine learning methods ranged from 0.772 to 0.986 for the training data and from 0.394 to 0.848 for the test data. The Support Vector Machine (SVM) led to excellent discrimination between bruxism and normal patients from USG images. Radiomics characteristics in pre-treatment ultrasound scans of patients, showing coarse and nonuniform muscles, were associated with a greater chance of less effective pain reduction outcomes. Conclusions: This study has introduced a machine learning model using SVM analysis on ultrasound (USG) images for bruxism patients, which can detect masseter muscle changes on USG. Support Vector Machine regression analysis showed the combined ML models can also predict the outcome of the pain reduction.
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Cardiovascular diseases (CVDs) are highly prevalent, sudden onset, and relatively fatal, posing a significant public health burden. Long-term dynamic electrocardiography, which can continuously record the long-term dynamic ECG activities of individuals in their daily lives, has high research value. However, ECG signals are
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Cardiovascular diseases (CVDs) are highly prevalent, sudden onset, and relatively fatal, posing a significant public health burden. Long-term dynamic electrocardiography, which can continuously record the long-term dynamic ECG activities of individuals in their daily lives, has high research value. However, ECG signals are weak and highly susceptible to external interference, which may lead to false alarms and misdiagnosis, affecting the diagnostic efficiency and the utilization rate of healthcare resources, so research on the quality of dynamic ECG signals is extremely necessary. Aimed at the above problems, this paper proposes a dynamic ECG signal quality assessment method based on CNN and LSTM that divides the signal into three quality categories: the signal of the Q1 category has a lower noise level, which can be used for reliable diagnosis of arrhythmia, etc.; the signal of the Q2 category has a higher noise level, but it still contains information that can be used for heart rate calculation, HRV analysis, etc.; and the signal of the Q3 category has a higher noise level that can interfere with the diagnosis of cardiovascular disease and should be discarded or labeled. In this paper, we use the widely recognized MIT-BIH database, based on which the model is applied to realistically collect exercise experimental data to assess the performance of the model in dealing with real-world situations. The model achieves an accuracy of 98.65% on the test set, a macro-averaged F1 score of 98.5%, and a high F1 score of 99.71% for the prediction of Q3 category signals, which shows that the model has good accuracy and generalization performance.
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Climate change necessitates urgent actions to mitigate carbon dioxide (CO2) emissions from fossil fuel-based energy generation. Among various strategies, the deployment of carbon capture and storage (CCS) solutions is critical for reducing emissions from point sources such as power plants and
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Climate change necessitates urgent actions to mitigate carbon dioxide (CO2) emissions from fossil fuel-based energy generation. Among various strategies, the deployment of carbon capture and storage (CCS) solutions is critical for reducing emissions from point sources such as power plants and heavy industries. In this context, cryogenic carbon capture (CCC) via desublimation has emerged as a promising technology. While CCC offers high separation efficiency, minimal downstream compression work, and integration potential with existing industrial processes, challenges such as low operating temperatures and equipment costs persist. Ongoing research aims to address these hurdles in order to optimize the desublimation processes for widespread implementation. This review consolidates diverse works from the literature, providing insights into the strengths and limitations of CCC technology, including the latest pilot plant scale demonstrations. The transformative potential of CCC is first assessed on a theoretical basis, such as thermodynamic aspects and mass transfer phenomena. Then, recent advancements in the proposed process configurations are critically assessed and compared through key performance indicators. Furthermore, future research directions for this technology are clearly highlighted.
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Thiourea and its derivatives have become a significant focal point within the organic synthesis field, garnering attention for their diverse biological applications, including antibacterial, antioxidant, anticancer, anti-inflammatory, anti-Alzheimer, antituberculosis and antimalarial properties. My objective is to present a comprehensive and easily understandable analysis
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Thiourea and its derivatives have become a significant focal point within the organic synthesis field, garnering attention for their diverse biological applications, including antibacterial, antioxidant, anticancer, anti-inflammatory, anti-Alzheimer, antituberculosis and antimalarial properties. My objective is to present a comprehensive and easily understandable analysis of recent advancements in the organic synthesis of thiourea derivatives. My focus is on the structure and activity of these derivatives over the past five years, highlighting the significant progress made in the field of organic synthesis. Additionally, I evaluate the current state of research in this area and provide an overview of the latest trends and future prospects. This review will prove to be beneficial for researchers, academics and industry professionals involved in drug development and organic synthesis.
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The importance of sleep for healthy brain function is widely acknowledged. However, it remains unclear how the internal generation of dreams might facilitate cognitive processes. In this perspective, we review a computational approach inspired by artificial intelligence that proposes a framework for how
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The importance of sleep for healthy brain function is widely acknowledged. However, it remains unclear how the internal generation of dreams might facilitate cognitive processes. In this perspective, we review a computational approach inspired by artificial intelligence that proposes a framework for how dreams occurring during rapid-eye-movement (REM) sleep can contribute to learning and creativity. In this framework, REM dreams are characterized by an adversarial process that, against the dream reality, tells a discriminator network to classify the internally created sensory activity as real. Such an adversarial dreaming process is shown to facilitate the emergence of real-world semantic representations in higher cortical areas. We further discuss the potential contributions of adversarial dreaming beyond learning, such as balancing fantastic and realistic dream elements and facilitating the occurrence of creative insights. We characterize non-REM (NREM) dreams, where a single hippocampal memory is replayed at a time, as serving the complementary role of improving the robustness of cortical representations to environmental perturbations. We finally explain how subjects can become aware of the adversarial REM dreams, but less of the NREM dreams, and how content- and state-awareness in wake, dream, and lucid dreaming may appear.
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Emmanuel Chamorey, Marc Pujalte-Martin, Jean-Marc Ferrero, Hakim Mahammedi, Gwenaelle Gravis, Guilhem Roubaud, Philippe Beuzeboc, Remy Largillier, Delphine Borchiellini, Claude Linassier, Hélène Bouges, Marie-Christine Etienne-Grimaldi, Renaud Schiappa, Jocelyn Gal and Gérard Milano
Int. J. Mol. Sci.2024, 25(11), 6058; https://doi.org/10.3390/ijms25116058 (registering DOI) - 31 May 2024
This ABIGENE pharmacokinetic (PK) study sought mainly to characterize the unchanged drug PK during long-term abiraterone acetate (AA) administration in advanced prostate cancer patients (81 patients). It was observed that individual AA concentrations remained constant over treatment time, with no noticeable changes during
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This ABIGENE pharmacokinetic (PK) study sought mainly to characterize the unchanged drug PK during long-term abiraterone acetate (AA) administration in advanced prostate cancer patients (81 patients). It was observed that individual AA concentrations remained constant over treatment time, with no noticeable changes during repeated long-term drug administration for up to 120 days. There was no correlation between AA concentrations and survival outcomes. However, a significant association between higher AA concentrations and better clinical benefit was observed (p = 0.041). The safety data did not correlate with the AA PK data. A significant positive correlation (r = 0.40, p < 0.001) was observed between mean AA concentration and patient age: the older the patient, the higher the AA concentration. Patient age was found to impact steady-state AA concentration: the older the patient, the higher the mean AA concentration. Altogether, these data may help to guide future research and clinical trials in order to maximize the benefits of AA metastatic castration-resistant prostate cancer patients.
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With the development of e-commerce in Poland, consumer awareness has evolved. Buyers not only compared prices and assessed the quality of products but also began to take into account the impact of their purchases on the environment, which was previously an overlooked aspect.
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With the development of e-commerce in Poland, consumer awareness has evolved. Buyers not only compared prices and assessed the quality of products but also began to take into account the impact of their purchases on the environment, which was previously an overlooked aspect. This growing environmental awareness is part of a broader effort to address environmental issues and support practices that promote sustainability. Currently, there is a noticeable increase in ecological awareness among society, government bodies, and the scientific community, strengthening human interaction with the natural environment. The aim of this study was to examine changes in ecological awareness and ecological attitudes among Polish e-consumers over ten years and their impact on online shopping behavior. This study explored how the ecological attitudes of Polish e-consumers have evolved over the last decade and what impact these changes in environmental attitudes have had on the online purchasing behavior of these consumers. Longitudinal studies were used to enable the analysis of changes over time. The research technique was based on repeated measurements of the same phenomena and features, carried out on diverse research samples from the same population, using the same methods and tools. This study was conducted twice, in 2010 and 2020, on a sample of 1150 people in each of these years. This research employed an online survey questionnaire, which included scales for assessing the personality traits of e-consumers and the determinants of online shopping. A significant change was found in e-consumers’ attitudes towards the natural environment and their purchasing preferences. This change has had a clear impact on purchasing behavior, including an increase in the importance of convenience, access to detailed product information, and a wide range of products offered, reflecting more conscious and convenience-oriented consumer behavior.
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The article examines perceptions of tyranny in Melito’s On Pascha and Apology, both written under Marcus Aurelius (161–180). This is the first systematic treatment of a key theme in Melito, approached not only from a theological perspective but also in the context
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The article examines perceptions of tyranny in Melito’s On Pascha and Apology, both written under Marcus Aurelius (161–180). This is the first systematic treatment of a key theme in Melito, approached not only from a theological perspective but also in the context of the Second Sophistic and Roman political developments. By proposing a more precise dating for On Pascha, we trace the development and consistency of Melito’s thought and arguments in regard to the relationship between Roman Empire and Christian communities in Asia Minor during the second half of the second century CE.
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This study characterized important environmental factors that contribute to plant invasion in the forested riparian zones surrounding stream restoration sites. We sampled vegetation and environmental variables (light availability, soil physiochemistry, and site age) across invasion gradients at multiple sites in Virginia, USA. Data
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This study characterized important environmental factors that contribute to plant invasion in the forested riparian zones surrounding stream restoration sites. We sampled vegetation and environmental variables (light availability, soil physiochemistry, and site age) across invasion gradients at multiple sites in Virginia, USA. Data analysis involved a multimetric statistical approach combining correlation and Canonical Correspondence Analysis (CCA) to arrive at a plausible model for invasion risk by species. We targeted three of the most problematic invaders in these systems: Lespedeza cuneata (sericea lespedeza), Lonicera japonica (Japanese honeysuckle), and Microstegium vimineum (Japanese stiltgrass). Our analysis revealed species-specific environmental drivers of invasion, with certain factors consistently important across all targeted invaders—notably, canopy cover, nitrogen availability, soil texture, and bioavailable phosphorus, as indicated by the importance of certain proxies (e.g., metal cations). The results of this research have been used to develop a suite of best practices that can be implemented at the outset of a stream restoration project to reduce the risk of invasion in the riparian forests surrounding these sites.
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Multidrug-resistant (MDR) Escherichia coli poses a significant threat to public health, contributing to elevated rates of morbidity, mortality, and economic burden. This study focused on investigating the antibiotic resistance profiles, resistance and virulence gene distributions, biofilm formation capabilities, and sequence types of E. [...] Read more.
Multidrug-resistant (MDR) Escherichia coli poses a significant threat to public health, contributing to elevated rates of morbidity, mortality, and economic burden. This study focused on investigating the antibiotic resistance profiles, resistance and virulence gene distributions, biofilm formation capabilities, and sequence types of E. coli strains resistant to six or more antibiotic classes. Among 918 strains isolated from 33 wastewater treatment plants (WWTPs), 53.6% (492/918) demonstrated resistance, 32.5% (298/918) were MDR, and over 8% (74/918) were resistant to six or more antibiotic classes, exhibiting complete resistance to ampicillin and over 90% to sulfisoxazole, nalidixic acid, and tetracycline. Key resistance genes identified included sul2, blaTEM, tetA, strA, strB, and fimH as the predominant virulence genes linked to cell adhesion but limited biofilm formation; 69% showed no biofilm formation, and approximately 3% were strong producers. Antibiotic residue analysis detected ciprofloxacin, sulfamethoxazole, and trimethoprim in all 33 WWTPs. Multilocus sequence typing analysis identified 29 genotypes, predominantly ST131, ST1193, ST38, and ST69, as high-risk clones of extraintestinal pathogenic E. coli. This study provided a comprehensive analysis of antibiotic resistance in MDR E. coli isolated from WWTPs, emphasizing the need for ongoing surveillance and research to effectively manage antibiotic resistance.
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Moataz Mohamed Hassan, Laila Al Yazidi, Nagi Elsidig, Mohamed Al Falahi, Najah Salmi, Yahya Al-Jaffari, Labiba Al-Amri, Huyam Zeiidan and Ibrahim Al-Zakwani
Pharmacy2024, 12(3), 85; https://doi.org/10.3390/pharmacy12030085 (registering DOI) - 31 May 2024
This study explored parents’ attitudes towards vaccinating their children against COVID-19 and the rate of vaccine hesitancy in Oman. A cross-sectional, online, self-administered questionnaire, previously validated and administered between June 2021 and May 2022, was used. The questionnaire consisted of nine items. Parents
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This study explored parents’ attitudes towards vaccinating their children against COVID-19 and the rate of vaccine hesitancy in Oman. A cross-sectional, online, self-administered questionnaire, previously validated and administered between June 2021 and May 2022, was used. The questionnaire consisted of nine items. Parents of children younger than 12 years were eligible for participation. A total of 384 participants, including 207 males (54%), completed the questionnaire, resulting in an 86% response rate (384/447). The results showed that 69% of participants were hesitant to vaccinate their children aged 1–11 years. In parents of children aged 1–4 years, vaccination status was significantly associated with vaccine hesitancy (odds ratio [OR], 0.116; 95% confidence interval [CI], 0.044–0.306; p = 0.001). Furthermore, after multivariable analysis, compared to the fathers, mothers were significantly less likely to be associated with vaccine hesitancy (OR, 0.451; 95% CI, 0.240–0.848; p = 0.013).
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Prickly ash peel oleoresin (PPO) is a highly concentrated oil of Prickly ash essential oil and has a stronger aroma. However, its low water solubility, high volatility, difficulty in transport and storage, and decomposition by light, heat, and oxygen limit its wider application.
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Prickly ash peel oleoresin (PPO) is a highly concentrated oil of Prickly ash essential oil and has a stronger aroma. However, its low water solubility, high volatility, difficulty in transport and storage, and decomposition by light, heat, and oxygen limit its wider application. To solve this problem, this study used freeze-drying or spray-drying, with soybean protein isolate (SPI) or gum Arabic (GA), combined with aqueous maltodextrin (MD) as the encapsulating agents to prepare four types of PPO microcapsules (POMs). Spray-dried microcapsules with GA as the encapsulating agent achieved a high encapsulation efficiency (EE) of 92.31 ± 0.31%, improved the thermal stability of the PPO, and had spherical morphology. (Headspace solid-phase microextraction/gas chromatography–mass spectrometry) HS-SPME/GC-MS detected 41 volatile compounds in PPO; of these, linalool, β-myrcene, sabinene, and D-limonene were identified as key flavor components. Principal component analysis (PCA) effectively distinguished the significant differences in flavor between PPO, spray-dried SPI/MD microcapsules (SS), and spray-dried GA/MD microcapsules (SG). During 15 days of air-exposure, the loss of flavor from SG (54.62 ± 0.54%) was significantly lower than PPO (79.45 ± 1.45%) and SS (57.55 ± 0.36%). During the air-exposure period, SG consistently had the highest antioxidant capacity, making it desirable for PPO packaging, and expanding its potential applications within the food industry.
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Nguyen Van Qui, Le Van Khoa, Nguyen Minh Phuong, Duong Minh Vien, Tran Van Dung, Tran Ba Linh, Tran Huynh Khanh, Bui Trieu Thuong, Vo Thi Thu Tran, Nguyen Khoi Nghia, Tran Minh Tien, Emmanuel Abatih, Ann Verdoodt, Steven Sleutel and Wim Cornelis
Agronomy2024, 14(6), 1185; https://doi.org/10.3390/agronomy14061185 (registering DOI) - 31 May 2024
In the Vietnamese Mekong Delta, soil quality and crop yield are steadily declining under rice monocultures with three crops per year. The objective of this study was to evaluate the medium-term effects of rotating rice with upland crops and adding organic amendments on
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In the Vietnamese Mekong Delta, soil quality and crop yield are steadily declining under rice monocultures with three crops per year. The objective of this study was to evaluate the medium-term effects of rotating rice with upland crops and adding organic amendments on rice yield, and to relate this to soil quality. A field trial with split-plot design including two factors and three replicates was carried out from 2017 to 2020, over the course of nine consecutive cropping seasons. Crop rotations and organic amendments were applied as main-plot and subplot factors, respectively. The rotations were (1) rice–rice–rice (R–R–R), (2) soybean–rice–rice (So–R–R), and (3) sesame–rice–rice (Se–R–R), while organic amendment treatments included (i) no amendment (NO-AM), (ii) compost of rice straw and cow manure (RS+CM), and (iii) sugarcane compost (SGC); the composts were applied at a rate of 2.0 t ha−1. The rotation cycle started with the so-called spring–summer (SS) season, followed by the summer–autumn (SA) season and ending with the winter–spring (WS) season. Rice yield significantly (p < 0.05) increased under organic amendments after nine growing seasons (2019–2020 WS), with an increment of 5.1% for RS+CM (7.07 ton/ha) and 6.1% for SGC (7.14 ton/ha). Contrary to our expectation, rotations with upland crops did not significantly increase rice yield. Rice yield significantly and positively correlated with an integrated soil quality index–SQI (r = 0.85) for the topsoil (0–15 cm), but not for the subsoil (15–30 cm). The increased availability of soil nutrients (Si and marginally also P) and improved soil physical properties probably induced by organic amendments, along with other soil properties under study, cumulatively attributed to enhanced rice yield. Repeated organic amendments thus becomes an effective management practice in improving soil quality under rice-based systems and could be applied to sustain rice yield in rice-producing regions with similar soil types and climatic conditions. Use of a SQI involving several soil quality indicators enables us to quantify the overall importance of soil fertility for rice yield versus other factors, and it provides an effective means of quantifying the integrated effect of improved management. Moreover, integrating a wide range of soil quality indicators in a SQI ensures its applicability across diverse settings, including different crop rotations and various soil types.
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This study presents a novel inverse identification approach to determine the elastoplastic parameters of a 2 µm thick GaN semiconductor thin film deposited on a sapphire substrate. This approach combines instrumented nanoindentation with finite element (FE) simulations and an artificial neural network (ANN)
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This study presents a novel inverse identification approach to determine the elastoplastic parameters of a 2 µm thick GaN semiconductor thin film deposited on a sapphire substrate. This approach combines instrumented nanoindentation with finite element (FE) simulations and an artificial neural network (ANN) model. Experimental load–depth curves were obtained using a Berkovich indenter. To generate a comprehensive database for the inverse analysis, FE models were constructed to simulate load–depth responses across a wide range of GaN thin film properties. The accuracy of both 2D and 3D simulations was compared to select the optimal model for database generation. The Box–Behnken design-based data sampling method was used to define the number of simulations and input variables for the FE models. The ANN technique was then employed to establish the complex mapping between the simulated load–depth curves (input) and the corresponding stress–strain curve (output). The generated database was used to train and test the ANN model. Then, the learned ANN model was used to achieve high accuracy in identifying the stress–strain curve of the GaN thin film from the experimental load–depth data. This work demonstrates the successful application of an inverse analysis framework, combining experimental nanoindentation tests, FE modeling, and an ANN model, for the characterization of the elastoplastic behavior of GaN thin films.
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Long-term hepatic damage is associated with human morbidity and mortality owing to numerous pathogenic factors. A variety of studies have focused on improving liver health using natural products and herbal medicines. We aimed to investigate the effect of enzyme-treated Zizania latifolia ethanol extract
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Long-term hepatic damage is associated with human morbidity and mortality owing to numerous pathogenic factors. A variety of studies have focused on improving liver health using natural products and herbal medicines. We aimed to investigate the effect of enzyme-treated Zizania latifolia ethanol extract (ETZL), which increases the content of tricin via enzymatic hydrolysis, for 8 weeks on liver-related outcomes, lipid metabolism, antioxidant activity, and fatigue compared to a placebo. Healthy Korean adult males aged 19–60 years were randomized into ETZL treatment and placebo groups, and alcohol consumption was 24.96 and 28.64 units/week, respectively. Alanine transaminase, a blood marker associated with liver cell injury, significantly decreased after 8 weeks compared to the baseline in the ETZL treatment group (p = 0.004). After 8 weeks, the treatment group showed significant changes in the levels of high-density lipoprotein and hepatic steatosis index compared to the baseline (p = 0.028 and p = 0.004, respectively). ETZL treatment tended to reduce antioxidant-activity-related factors, total antioxidant status, and malondialdehyde, but there was no significant difference. In the multidimensional fatigue scale, ETZL treatment showed a significant reduction in general fatigue and total-fatigue-related values after 8 weeks compared to the baseline (p = 0.012 and p = 0.032, respectively). Taken together, the 8-week treatment of enzyme-treated Zizania latifolia ethanol extract demonstrated positive effects on liver-related outcomes, lipid metabolism, and mental fatigue without adverse effects on safety-related parameters.
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Breeding salt-tolerant crops is necessary to reduce food insecurity. Prebreeding populations are fundamental for uncovering tolerance alleles from wild germplasm. To obtain a physiological interpretation of the agronomic salt tolerance and better criteria to identify candidate genes, quantitative trait loci (QTLs) governing productivity-related
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Breeding salt-tolerant crops is necessary to reduce food insecurity. Prebreeding populations are fundamental for uncovering tolerance alleles from wild germplasm. To obtain a physiological interpretation of the agronomic salt tolerance and better criteria to identify candidate genes, quantitative trait loci (QTLs) governing productivity-related traits in a population of recombinant inbred lines (RIL) derived from S. pimpinellifolium were reanalyzed using an SNP-saturated linkage map and clustered using QTL meta-analysis to synthesize QTL information. A total of 60 out of 85 QTLs were grouped into 12 productivity MQTLs. Ten of them were found to overlap with other tomato yield QTLs that were found using various mapping populations and cultivation conditions. The MQTL compositions showed that fruit yield was genetically associated with leaf water content. Additionally, leaf Cl− and K+ contents were related to tomato productivity under control and salinity conditions, respectively. More than one functional candidate was frequently found, explaining most productivity MQTLs, indicating that the co-regulation of more than one gene within those MQTLs might explain the clustering of agronomic and physiological QTLs. Moreover, MQTL1.2, MQTL3 and MQTL6 point to the root as the main organ involved in increasing productivity under salinity through the wild allele, suggesting that adequate rootstock/scion combinations could have a clear agronomic advantage under salinity.
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Corneal biomechanics is a hot topic in ophthalmology. The biomechanical properties (BMPs) of the cornea have important implications in the management and diagnosis of corneal diseases such as ectasia and keratoconus. In addition, the characterization of BMPs is crucial to model the predictability
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Corneal biomechanics is a hot topic in ophthalmology. The biomechanical properties (BMPs) of the cornea have important implications in the management and diagnosis of corneal diseases such as ectasia and keratoconus. In addition, the characterization of BMPs is crucial to model the predictability of a corneal surgery intervention, the outcomes of refractive surgery or the follow-up of corneal diseases. The biomechanical behavior of the cornea is governed by viscoelastic properties that allow, among other structural implications, the damping of excess intraocular pressure and the reduction of damage to the optic nerve. Currently, the most versatile and complete methods to measure corneal viscoelasticity are based on air-puff corneal applanation. However, these methods lack the ability to directly measure corneal viscosity. The aim of this work is to propose a new methodology based on the analysis of corneal air-puff measurements through the standard linear solid model (SLSM) to provide analytical expressions to separately calculate the elastic and time-dependent (corneal retardation time and viscosity) properties. The results show the mean values of elasticity (E), viscosity (Ƞ) and corneal retardation time (τ) in a sample of 200 young and healthy subjects. The influence of elasticity and viscosity on viscoelasticity, high-order corneal aberrations and optical transparency is investigated. Finally, the SLSM fed back from experimental E and Ƞ values is employed to compare the creep relaxation response between a normal, an ocular hypertension patient and an Ortho-K user. Corneal biomechanics is strongly affected by intraocular pressure (IOP); however, corneal hysteresis (CH) analysis is not enough to be employed as a risk factor of glaucoma progression. Low values of CH can be accompanied by high or low corneal elasticity and viscosity depending on the IOP threshold from which the time-dependent biomechanical properties trends are reversed.
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(This article belongs to the Special Issue Visual Optics)
The seismic response of underground liquefied natural gas (LNG) storage tanks has been a significant focus in both academic and engineering circles. This study utilized Ansys (2021R1) to conduct seismic analyses of large-capacity LNG tanks, considering the fluid–structure–soil coupling interaction (FSSI), and it
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The seismic response of underground liquefied natural gas (LNG) storage tanks has been a significant focus in both academic and engineering circles. This study utilized Ansys (2021R1) to conduct seismic analyses of large-capacity LNG tanks, considering the fluid–structure–soil coupling interaction (FSSI), and it was solved using the Volume of Fluid model (VOF) and Finite Element Method (FEM). The mechanical properties of both the LNG tank structure and soil were simulated using solid elements, and seismic acceleration loads were applied. An analysis of liquefied natural gas was performed using fluid elements within FLUENT. Initially, a modal analysis of the tank was conducted, which revealed lower frequencies for a full-liquid tank (3.193 Hz) compared to an empty tank (3.714 Hz). Subsequently, the seismic responses of both the aboveground and underground LNG tank structures were separately simulated, comparing the acceleration, stress, and displacement of the tank wall structures. The findings indicate that the peak relative displacement of the aboveground empty tank wall is 122 mm, less than that of a full tank (136 mm), while the opposite holds true for underground tanks. The period and wave height of LNG liquid shaking in underground tanks are lower than those in aboveground tanks, which is more conducive to tank safety. The deformation and acceleration of underground tanks are lower than those of aboveground tanks, but the Mises stress is higher. The results indicate that underground LNG tank structures are safer under earthquake conditions.
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Endophytic fungi are present in every plant, and crops are no exception. There are more than 50,000 edible plant species on the planet, but only 15 crops provide 90 percent of the global energy intake, and “the big four”—wheat, rice, maize and potato—are
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Endophytic fungi are present in every plant, and crops are no exception. There are more than 50,000 edible plant species on the planet, but only 15 crops provide 90 percent of the global energy intake, and “the big four”—wheat, rice, maize and potato—are staples for about 5 billion people. Not only do the four staple crops contribute to global food security, but the endophytic fungi within their plant tissues are complex ecosystems that have been under scrutiny. This review presents an outline of the endophytic fungi and their secondary metabolites in four staple crops: wheat, rice, maize and potato. A total of 292 endophytic fungi were identified from the four major crops, with wheat having the highest number of 157 endophytic fungi. Potato endophytic fungi had the highest number of secondary metabolites, totaling 204 compounds, compared with only 23 secondary metabolites from the other three crops containing endophytic fungi. Some of the compounds are those with specific structural and pharmacological activities, which may be beneficial to agrochemistry and medicinal chemistry.
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With the increase in urban development intensity, the urban climate has become an important factor affecting sustainable development. The role of urban ventilation corridors in improving urban climate has received widespread attention. Urban ventilation identification and planning based on morphological methods have been
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With the increase in urban development intensity, the urban climate has become an important factor affecting sustainable development. The role of urban ventilation corridors in improving urban climate has received widespread attention. Urban ventilation identification and planning based on morphological methods have been initially applied. Traditional morphological methods do not adequately consider the dynamic process of air flow, resulting in a rough evaluation of urban ventilation patterns. This study proposes a new urban-scale ventilation corridor identification method that integrates the Lattice Boltzmann method and the K-means algorithm. Taking Wuhan, China as the research area, an empirical study in different wind directions was conducted on a 20 m grid. The results showed that three levels of ventilation corridors () and two levels of ventilation obstruction areas () were identified to depict the ventilation pattern of Wuhan’s central urban area. The method proposed in this study can meet the needs of urban-scale ventilation corridor identification in terms of spatial coverage, spatial distribution rate and dynamic analysis. Compared with the classic least cumulative ventilation cost method, the method proposed in this study can provide more morphologic details of the ventilation corridors. This plays a very important role in urban planning based on urban ventilation theory.
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