bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of Handgrip Strength on Survival in Hemodialysis Patients
Authors: Park Kyungho , Jeong Seongyeop , Park Hyerim , Lee Eu Jin , Ham Young Rok , Na Ki Ryang , Choi Dae Eun
Published: January 2025

Background: Hemodialysis patients face a high mortality risk, requiring effective clinical assessments. In these patients, muscle wasting due to protein-energy wasting (PEW) leads to increased frailty, which is strongly associated with worse outcomes, including higher mortality. As muscle mass declines, so does functional capacity, making regular assessment of both muscle mass and function critical for prognostic evaluation. Handgrip strength (HGS) offers a quick and reliable measure of muscle strength and functional capacity. In this study, we focused on the impact of HGS on survival in hemodialysis patients, analyzing its relationship with muscle mass and BMI. Methods: This retrospective cohort study included 408 dialysis patients (221 males, 187 females) who underwent bioimpedance spectroscopy (BIS) and HGS assessments between March 2021 and August 2023. Data collected included BIS profiles, HGS, dialysis status, age, complete blood count, blood chemistry, mortality, and CONUT scores. Results: Cox proportional hazards regression analysis revealed that lean tissue index (LTI) (HR 3.30, 95% CI 1.75–6.19), body mass index (BMI) (HR 2.65, 95% CI 1.17–6.01), and handgrip strength (HGS) (HR 4.22, 95% CI 2.05–8.70) were significant predictors of survival in the overall dialysis patient cohort. Gender-specific analysis showed that in males, both LTI (HR 4.81, 95% CI 1.89–12.23) and HGS (HR 5.45, 95% CI 2.18–13.61) significantly predicted survival. In females, HGS (HR 6.01, 95% CI 2.42–14.94) was a significant predictor, while LTI was also significant (HR 3.22, 95% CI 1.24–8.40, p = 0.017). In the multivariate Cox proportional hazards analysis, which adjusted for age, diabetes mellitus (DM), hypertension (HTN), BMI, fat tissue index (FTI), LTI, serum albumin, C-reactive protein (CRP), and CONUT score, HGS remained a significant predictor of survival in female dialysis patients (HR 2.77, 95% CI 1.00–7.65, p = 0.049). Conclusions: HGS has been identified as an important factor for survival in dialysis patients, particularly in female patients, independent of muscle mass and BMI.
Towards Meaningful Interpretation of Molecular Data: Insights Gained from HMMD Challenges in Salmonella Detection for Future NGS Integration in Clinical Microbiology
Authors: Kim Hyunji , Seo Soo Hyun , Kim Jae-Seok , Lee Kwang Jun , Park Kyoung Un
Published: January 2025

Background: With advancements in molecular diagnostics, including Highly Multiplexed Microbiological/Medical Countermeasure Diagnostic Devices (HMMDs) and the impending integration of Next-Generation Sequencing (NGS) into clinical microbiology, interpreting the flood of nucleic acid data in a clinically meaningful way has become a crucial challenge. This study focuses on the Luminex xTAG Gastrointestinal Pathogen Panel (GPP) for Salmonella detection, evaluating the impact of MFI threshold adjustments on diagnostic accuracy and exploring the need for an “indeterminate” result category to enhance clinical utility in molecular diagnostics. Methods: A retrospective review of Salmonella-positive cases detected via the Luminex xTAG GPP was conducted from June 2016 to November 2023. Key metrics included patient symptoms, stool culture results, and potential infection sources. Results were analyzed using the assay’s MFI cutoffs in Versions 1.11 and 1.12. Statistical comparisons between culture-confirmed and non-confirmed cases were performed using Kruskal–Wallis tests to assess MFI value distributions. Results: Among 2573 tests, 212 were Salmonella-positive under Version 1.11, while 185 were positive under Version 1.12. Adjusting the MFI threshold in Version 1.12 reduced false positives from 40.6% to 38.4% but led to one culture-confirmed positive case being missed. Statistically significant MFI differences were observed between culture-positive and culture-negative cases, suggesting that fixed binary cutoffs may not always yield clinically accurate interpretations. Discussion: The MFI threshold adjustment decreased false positives without fundamentally improving diagnostic accuracy, highlighting the limitations of binary interpretations in HMMDs. Introducing an “indeterminate” category, especially for cases with low MFI values, could aid clinicians in integrating molecular results with patient context. This approach offers a framework for future NGS integration, where nuanced interpretation will be essential to differentiate clinically significant findings from incidental data. Conclusions: Implementing an “indeterminate” interpretation category for HMMDs could enhance clinical decision-making and refine public health surveillance by focusing on clinically relevant findings. As NGS moves toward clinical application, establishing similar interpretive standards will be essential to manage the complexity and volume of molecular data effectively.
Few-Shot Graph Anomaly Detection via Dual-Level Knowledge Distillation
Authors: Li Xuan , Cheng Dejie , Zhang Luheng , Zhang Chengfang , Feng Ziliang
Published: January 2025

Graph anomaly detection is crucial in many high-impact applications across diverse fields. In anomaly detection tasks, collecting plenty of annotated data tends to be costly and laborious. As a result, few-shot learning has been explored to address the issue by requiring only a few labeled samples to achieve good performance. However, conventional few-shot models may not fully exploit the information within auxiliary sets, leading to suboptimal performance. To tackle these limitations, we propose a dual-level knowledge distillation-based approach for graph anomaly detection, DualKD, which leverages two distinct distillation losses to improve generalization capabilities. In our approach, we initially train a teacher model to generate prediction distributions as soft labels, capturing the entropy of uncertainty in the data. These soft labels are then employed to construct the corresponding loss for training a student model, which can capture more detailed node features. In addition, we introduce two representation distillation losses—short and long representation distillation—to effectively transfer knowledge from the auxiliary set to the target set. Comprehensive experiments conducted on four datasets verify that DualKD remarkably outperforms the advanced baselines, highlighting its effectiveness in enhancing identification performance.
Unique Information Through the Lens of Channel Ordering: An Introduction and Review
Authors: Banerjee Pradeep Kr.
Published: January 2025

The problem of constructing information measures with a well-defined interpretation is of fundamental significance in information theory. A good definition of an information measure entails certain desirable properties while also providing answers to operational problems. In this work, we investigate the properties of the unique information, an information measure that quantifies a deviation from the Blackwell order. Beyond providing an accessible introduction to the topic from a channel ordering perspective, we present a novel resource-theoretic characterization of unique information in a cryptographic task related to secret key agreement. Our operational view of unique information entails rich physical intuition that leads to new insights into secret key agreement in the context of non-negative decompositions of the mutual information into redundant and synergistic contributions. Through this lens, we illuminate new directions for research in partial information decompositions and information-theoretic cryptography.
Non-Orthogonality of QAM and Sunflower-like Modulated Coherent-State Signals
Authors: Kato Kentaro
Published: January 2025

The limitations of cloning and discriminating quantum states are related to the non-orthogonality of the states. Hence, understanding the collective features of quantum states is essential for the future development of quantum communications technology. This paper investigates the non-orthogonality of different coherent-state signal constellations used in quantum communications, namely phase-shift keying (PSK), quadrature-amplitude modulation (QAM), and a newly defined signal named the sunflower-like (SUN) coherent-state signal. The non-orthogonality index (NOI) and the average probability of correct detection (detection probability) are numerically computed. Results show that PSK NOI increases faster than QAM and SUN as the number of signals increases for a given number of signal photons. QAM and SUN exhibit similar NOI and detection probability, behaving similarly to randomly generated signals for a larger number of signals. Approximation formulas are provided for the detection probability as a function of NOI for each signal type. While similar to QAM, SUN signal offers potential advantages for applications requiring uniform signal-space distribution. The findings provide valuable insights for designing useful quantum signal constellations.
Multiple Kernel Transfer Learning for Enhancing Network Intrusion Detection in Encrypted and Heterogeneous Network Environments
Authors: Amamra Abdelfattah , Terrelonge Vincent
Published: January 2025

Conventional supervised machine learning is widely used for intrusion detection without packet payload inspection, showing good accuracy in detecting known attacks. However, these methods require large labeled datasets, which are scarce due to privacy concerns, and struggle with generalizing to real-world traffic and adapting to domain shifts. Additionally, they are ineffective against zero-day attacks and need frequent retraining, making them difficult to maintain in dynamic network environments. To overcome the limitations of traditional machine learning methods, we propose novel Deterministic (DetMKTL) and Stochastic Multiple-Kernel Transfer Learning (StoMKTL) algorithms that are based on transfer learning. These algorithms leverage multiple kernel functions to capture complex, non-linear relationships in network traffic, enhancing adaptability and accuracy while reducing dependence on large labeled datasets. The proposed algorithms demonstrated good accuracy, particularly in cross-domain evaluations, achieving accuracy rates exceeding 90%. This highlights the robustness of the models in handling diverse network environments and varying data distributions. Moreover, our models exhibited superior performance in detecting multiple types of cyber attacks, including zero-day threats. Specifically, the detection rates reached up to 87% for known attacks and approximately 75% for unseen attacks or their variants. This emphasizes the ability of our algorithms to generalize well to novel and evolving threat scenarios, which are often overlooked by traditional systems. Additionally, the proposed algorithms performed effectively in encrypted traffic analysis, achieving an accuracy of 86%. This result demonstrates the possibility of our models to identify malicious activities within encrypted communications without compromising data privacy.
Cognitive Agents Powered by Large Language Models for Agile Software Project Management
Authors: Cinkusz Konrad , Chudziak Jarosław A. , Niewiadomska-Szynkiewicz Ewa
Published: January 2025

This paper investigates the integration of cognitive agents powered by Large Language Models (LLMs) within the Scaled Agile Framework (SAFe) to reinforce software project management. By deploying virtual agents in simulated software environments, this study explores their potential to fulfill fundamental roles in IT project development, thereby optimizing project outcomes through intelligent automation. Particular emphasis is placed on the adaptability of these agents to Agile methodologies and their transformative impact on decision-making, problem-solving, and collaboration dynamics. The research leverages the CogniSim ecosystem, a platform designed to simulate real-world software engineering challenges, such as aligning technical capabilities with business objectives, managing interdependencies, and maintaining project agility. Through iterative simulations, cognitive agents demonstrate advanced capabilities in task delegation, inter-agent communication, and project lifecycle management. By employing natural language processing to facilitate meaningful dialogues, these agents emulate human roles and improve the efficiency and precision of Agile practices. Key findings from this investigation highlight the ability of LLM-powered cognitive agents to deliver measurable improvements in various metrics, including task completion times, quality of deliverables, and communication coherence. These agents exhibit scalability and adaptability, ensuring their applicability across diverse and complex project environments. This study underscores the potential of integrating LLM-powered agents into Agile project management frameworks as a means of advancing software engineering practices. This integration not only refines the execution of project management tasks but also sets the stage for a paradigm shift in how teams collaborate and address emerging challenges. By integrating the capabilities of artificial intelligence with the principles of Agile, the CogniSim framework establishes a foundation for more intelligent, efficient, and adaptable software development methodologies.
A Learning Resource Recommendation Method Based on Graph Contrastive Learning
Authors: Yong Jiu , Wei Jianguo , Lei Xiaomei , Dang Jianwu , Lu Wenhuan , Cheng Meijuan
Published: January 2025

The existing learning resource recommendation systems suffer from data sparsity and missing data labels, leading to the insufficient mining of the correlation between users and courses. To address these issues, we propose a learning resource recommendation method based on graph contrastive learning, which uses graph contrastive learning to construct an auxiliary recommendation task combined with a main recommendation task, achieving the joint recommendation of learning resources. Firstly, the interaction bipartite graph between the user and the course is input into a lightweight graph convolutional network, and the embedded representation of each node in the graph is obtained after compilation. Then, for the input user–course interaction bipartite graph, noise vectors are randomly added to each node in the embedding space to perturb the embedding of graph encoder node, forming a perturbation embedding representation of the node to enhance the data. Subsequently, the graph contrastive learning method is used to construct auxiliary recommendation tasks. Finally, the main task of recommendation supervision and the constructed auxiliary task of graph contrastive learning are jointly learned to alleviate data sparsity. The experimental results show that the proposed method in this paper has improved the Recall@5 by 5.7% and 11.2% and the NDCG@5 by 0.1% and 6.4%, respectively, on the MOOCCube and Amazon-Book datasets compared with the node enhancement methods. Therefore, the proposed method can significantly improve the mining level of users and courses by using a graph comparison method in the auxiliary recommendation task and has better noise immunity and robustness.
Advances and Classification of Autonomous Systems in Biomedical Devices: Integration of Energy Harvesting and Ultra-Low Power Consumption
Authors: Amezquita Garcia José Alejandro , Bravo Zanoguera Miguel E. , Murrieta-Rico Fabian N.
Published: January 2025

Autonomous electronic systems are becoming increasingly important in people’s lives, as a result of advances in efficient energy storage systems, devices that can be permanently implanted in humans, and the trend towards compact devices that function as an extension of the human body. In addition, strategies continue to be found for the integration of energy harvesting in a constant and efficient manner. Covering the numerous advances made in biomedical devices can be quite overwhelming. This work presents a review of the latest strategies developed to produce energy from human body activity, the energy collectors for devices, and the strategies to create ultra-low-power wearable devices. The review focuses on the potential energy sufficiency required to power devices that can be implanted or worn, while also providing information about the patient’s condition. A comparison between the energies produced by different instruments and the improvements in the development of low-consumption devices is presented, with a focus on the type of medical devices. A new approach is established to classify and locate the most recent advances in autonomous systems in biomedicine based on their complexity/function.
Energy Waste as a Side-Effect of Photovoltaic Development: Net Impact of Photovoltaics on CO2 Emissions in European Union Countries
Authors: Gajdzik Bożena , Wolniak Radosław , Nagaj Rafał , Žuromskaitė-Nagaj Brigita , Grebski Wiesław
Published: January 2025

Decarbonization policies are being implemented in all EU countries where renewable energy is being developed. One of the main energy sources used for this purpose is photovoltaic energy. However, the development of photovoltaics does not only mean environmental benefits in the form of green energy and thus a reduction in greenhouse gas emissions from fossil fuel energy production, but also energy waste. The development of photovoltaics generates energy waste, some of which cannot be recovered, which in turn has a negative impact on gas emissions. The aim of this article is to analyse the amount of energy waste from photovoltaics in European Union countries and the net impact of photovoltaics on greenhouse gas emissions. Data sources are Eurostat and Our World In Data. The analysis will be carried out for the majority of EU countries, excluding the smallest countries whose data may distort the overall results. The analysis should show the overall impact of PV in the countries analysed and the changes over the period studied. The results will also indicate whether the impact of PV on decarbonization is similar across the EU countries analysed, or whether there are clusters of countries due to the impact of PV, or a negative impact in some of them.
Thermal Finite-Element Model of Electric Machine Cooled by Spray
Authors: Bergfried Christian , Abdi Qezeljeh Samaneh , Roisman Ilia V. , De Gersem Herbert , Hussong Jeanette , Späck-Leigsnering Yvonne
Published: January 2025

The demand for higher power density in electrical machines necessitates advanced cooling strategies. Spray cooling emerges as a promising and relatively straightforward technology, albeit involving complex physics. In this paper, a quasi-3D thermal finite-element model of stator winding is created by the extrusion of a 2D cross-sectional finite-element model along the winding direction. The cooling effects of the spray impact are simulated as a heat flux that uses an impedance boundary condition at the surface of the winding overhang. The results confirm the advantageous performance of spray cooling, indicating that it may enable a tenfold increase in power density compared to standard air- or water-cooled machines.
Assessing Critical Raw Materials and Their Supply Risk in Energy Technologies—A Literature Review
Authors: Montana Francesco , Cellura Maurizio , Di Silvestre Maria Luisa , Longo Sonia , Luu Le Quyen , Riva Sanseverino Eleonora , Sciumè Giuseppe
Published: January 2025

Climate change is leading modern society to seek innovative solutions for sustainable development and a zero-carbon economy. Nevertheless, new technologies strongly rely on precious raw materials and might suffer from supply chain risks. The European Union has identified a set of raw materials deemed to be critical or strategic because they appear essential for energy transition technologies. Consequently, long-term energy system planning must factor in the availability of these critical raw materials when selecting specific technologies, as their supply could be affected by global policies or conflicts. This paper provides a literature review on the assessment of critical raw materials in energy technologies comparing the main approaches on critical raw materials content assessment in technologies, long-term planning studies considering critical raw materials, and the development of indicators for critical raw materials content in energy technologies. The main findings of this review suggest that existing reliable databases with the bill of materials, such as life cycle inventories, should be exploited and that proper indicators to rank the criticality of materials and the importance of a specific technology should be developed. These findings are discussed and organized proposing a method for the optimal planning of an energy technologies mix in regional or national energy systems considering the availability and future supply of critical raw materials.
Optimization Study of Photovoltaic Cell Arrangement Strategies in Greenhouses
Authors: Qin Yuzhe , Cheng Qing
Published: January 2025

The replacement of greenhouse surfaces with photovoltaic cells currently presents issues with internal shading and uneven illumination, which adversely affect crop growth and yield. Therefore, in order to improve greenhouse lighting by altering the arrangement of photovoltaic cells for greater economic and environmental benefits, four cities (Harbin, Shenyang, Nanjing, and Guangzhou) were selected for this study. Greenhouse models were established using the DesignBuilder software tool, focusing on the summer and winter growth stages of cherry tomatoes and strawberries. Two arrangements were employed—compact (CR) and checkerboard (BR)—to evaluate 18 scenarios based on power generation, illuminance uniformity, and temperature. Analysis revealed that, among the four cities, the checkerboard arrangement improved average illumination uniformity by 37.34%, 37.9%, 38.2%, and 35.8%, respectively, compared with the compact arrangement. Except for nine rows of photovoltaic cells in Guangzhou, the unit of area power generation of the schemes exceeded 80 kWh/m2 in summer, with excellent power generation efficiency. In winter, there was a relative decrease. Among the four cities, only Harbin reached seven rows of photovoltaic cells which produced more than 80 kWh/m2 under the unit of area of photovoltaic cells, while the other three cities achieved five rows. Strawberries are not suitable for growing in Harbin and Shenyang in winter. In addition to this, cherry tomatoes and strawberries in different regions and at different stages have the best arrangements for growth and for maximizing cost efficiency.
Museum Education
Authors: Todino Michele Domenico , Campitiello Lucia
Published: January 2025

Museum education involves using a museum’s resources and collections to facilitate learning for diverse audiences. It includes activities like tours, workshops, and interactive exhibits that promote active, inquiry-based learning. Focused on accessibility and inclusivity, museum education aims to engage visitors, enhance their understanding, and foster a deeper appreciation for cultural, historical, or scientific content to foster active citizenship and lifelong learning in a non-formal learning context. Museum education uses collections and exhibits to engage audiences through hands-on, inquiry-based learning. By integrating digital tools and interactive technologies, it enhances learning through immersive and distance-based experiences. This approach promotes active engagement, critical thinking, and meaning-making, transforming traditional teaching methods. Museums serve as inclusive spaces where knowledge—embodied in artifacts and digital mediators—supports cognitive, emotional, and social development, fostering deeper connections with culture and history.
Underlying Causes of Long-Term Environmental Pollution by Waste from an Abandoned Metal Mining District: When Legislative and Remediation Measures Are Ineffective
Authors: García Gregorio , Rosique Guadalupe
Published: January 2025

Since ancient times, mining activities have been recognised as having a strong environmental impact. Due to the extraordinary amount of waste and impacts on the landscape, environmental concerns caused by mining can be found worldwide. The risks associated with mining waste are of great concern, especially when these residues come from metal mining and its associated potentially toxic elements that can be released into the environment. The reality of many of these metal mining areas is that, despite the extensive regulatory frameworks and remediation techniques applied, they continue to have high levels of contamination, posing a source of environmental and public health risk to their surroundings. The issues underlying this situation are details that can only be detected by experience in the management and thorough knowledge of the dynamics of these tailings in the long term. And in many cases, the key is in the details. For this purpose, the case of the former metal mining district of Cartagena-La Unión (SE Spain), one of the most affected areas in the European continent by these metal mining wastes, has been analyzed. In conclusion, it has been shown that the legal status of these waste and mining operations and the lack of control and effectiveness of rehabilitation activities are behind the worrying environmental situation of these areas. The interaction between the legal framework and the environmental and technical knowledge of these tailings and mining areas reveals practical issues beyond the scope of general analysis. This case study, conducted in the main Spanish metal mining area, concerns waste volume, and its findings offer the potential to improve the safety and environmental quality of metal mining regions elsewhere.
Effects of Warming on Change Rate of Soil Organic Carbon Content in Forest Soils
Authors: Xu Hongtao , Huang Lulu , Wang Shaoyong
Published: January 2025

Climate warming affects the carbon cycle in terrestrial environments. However, the effects of warming on the change rate of soil organic carbon (SOC) content in forest soils are unclear. Here, we extracted 276 data points from 98 published papers to examine the effects of warming on the change rate of SOC content in the soil mineral profile (0–20 or 0–30 cm), focusing on the regulatory effects of warming magnitude and duration and the humidity index. Warming promoted an increase in SOC content from 67.47 to 69.90 g kg−1 in forest soils, with a change rate of SOC content of 0.85 g kg−1 yr−1 on a global scale. The change rate of SOC content decreased from 1.22 to 0.11 g kg−1 yr−1 at a warming magnitude of 0–2 and >2 °C, respectively, and it changed from 0.96 to −0.81 to −0.51 g kg−1 yr−1 at warming durations of 0–5, 5–10, and >10 years, respectively. The change rate of SOC content was higher at a humidity index value of 30–50 than at 0–30 and >50. Although climate warming increases the SOC content, the change rate of SOC content decreases with increased magnitude and duration of warming but increases with an increased humidity index. These findings help elucidate SOC accumulation in the context of climate change.
Utilization of Okara as a Culture Medium by Membrane Concentration Process for High Oil Production by Oleaginous Yeast, Lipomyces starkeyi
Authors: Taki Hiroya , Mine Kentaro , Miyamoto Mana , Seto Jiro , Matsuo Shinji , Kumagai Kazuo , Matsuyama Hideto
Published: January 2025

Palm oil, widely used in various products, poses environmental and climate change risks. “Yeast oil” produced by Lipomyces starkeyi, an oil-producing yeast, is one of the sustainable alternatives for palm oil and was successfully produced as an edible substitute for palm oil. However, the high cost of the culture medium for oil production remains a challenge for practical applications. Okara is a by-product of tofu and soymilk production. Because yeast extract contributes to the high cost of the culture medium, we considered using okara, a cheap and nitrogen-rich substitute, to reduce costs. In the initial study with okara, the production of yeast oil was confirmed, but its productivity was low due to the high viscosity caused by its insoluble solids. To overcome this, we extracted and concentrated nitrogen components in okara using the membrane concentration process. Using NF (nanofiltration) membrane concentration, oil production increased 1.69 and 1.44 times compared to the unconcentrated extract solution (added 90% (v/v) in the culture medium) and yeast extract (added 5% (w/v) in the culture medium), respectively. These findings indicate the potential for a significant cost reduction in the culture medium and high oil yield in yeast oil production.
Effects of Lactobacillus buchneri and Lactobacillus rhamnosus on Ryegrass Silage Fermentation and Aerobic Stability
Authors: Han Furong , Zhang Mingzhu , Sun Wentao , Wu Changrong , Huang Yuan , Xia Guanghao , Chen Chao , Yang Fuyu , Hao Jun
Published: January 2025

Italian ryegrass is a high-quality forage grass, and a full understanding of the changes in its microbiome and metabolome during aerobic exposure can prolong its aerobic stability and improve its utilization value. Italian ryegrass silage was prepared with deionized water (CK), Lactobacillus rhamnosus BDy3-10 (LR), Lactobacillus buchneri TSy1-3 (LB), and a mixture of these two lactic acid bacteria (M). The silage was maintained at ambient temperature for 60 days followed by aerobic exposure. The results show that the Italian ryegrass silage in the LB and M groups exhibited aerobic stability for up to 19 days. A total of 1881 chemicals were identified in Italian ryegrass silage. These metabolites are associated with bacterial communities, especially Lactobacillus. The addition of lactic acid bacteria resulted in a common differential metabolic pathway compared to CK: “phenylpropanoid biosynthesis”. “Flavone and flavonol biosynthesis” was the significant differential metabolic pathway between LB and LR. Inoculation with LB significantly increased the concentrations of lactic acid, acetic acid, vitexin, and luteolin. In conclusion, lactic acid bacteria (LAB) additives affect the microbial community and metabolites of silage. The application of LB inoculants is a feasible way to obtain well-fermented Italian ryegrass silage and improve aerobic stability, even at higher moisture content levels.
Dietary Alpha-Lipoic Acid Alleviated Hepatic Glycogen Deposition and Improved Inflammation Response of Largemouth Bass (Micropterus salmoides) Fed on High Dietary Carbohydrates
Authors: Fang Zishuo , Pan Xianwei , Gong Ye , Zhang Nihe , Chen Shiwen , Liu Ning , Chen Naisong , Li Songlin
Published: January 2025

In order to mitigate the adverse effects of high carbohydrates on largemouth bass and to investigate the feasibility of LA as a feed additive, the present study observed the effects of added α-lipoic acid (LA) on growth performance, glucose metabolism and immunity in largemouth bass fed on high dietary carbohydrates (10% α-cassava starch inclusion). A total of 315 juvenile largemouth bass (initial body weight, 5.09 ± 0.10 g) were divided into nine tanks (800 L) (upper radius 0.65 m × lower radius 0.5 m × height 1 m), with each holding 35 fish. Three iso-nitrogenous and iso-lipidic diets supplementing with 0 g/kg, 0.5 g/kg and 1 g/kg LA (LA0, LA500, LA1000) were designed to feed juvenile largemouth bass on a satiation diet twice daily for eight weeks with each diet feeding to triplicate groups. The results indicated that the performance in growth was significantly enhanced by the addition of dietary LA (p < 0.05). Meanwhile, hepatic glycogen content was significantly reduced (p < 0.05), and the expression of genes relating to insulin pathway and glycolysis significantly increased with LA inclusion (p < 0.05). The relative expression of insulin receptor a (ira) in the LA500 group was the highest, while the relative expression of glycerol kinase (gk), phosphofructokinase liver type (pfkl) and phosphoenolpyruvate carboxykinase (pepck) was the highest in the LA1000 group (p < 0.05). In addition, LA supplementation significantly increased the activity of lysozyme, which reached its maximum value in the LA500 group (p < 0.05). LA supplementation also promoted the expression of genes relating to anti-inflammatory and inhibited the expression of pro-inflammatory related genes (p < 0.05). Above all, the dietary addition of LA could improve performance in growth, alleviated hepatic glycogen deposition, and improved the immunity function of largemouth bass fed on high dietary carbohydrates. This provides us with ideas to mitigate the adverse effects of high carbohydrates on largemouth bass in actual production and provides a basis for the application of LA in aquatic biology.
Effect of Dietary Oils with Different Fatty Acid Compositions on Serum Lipid and Gut Microbiota of Rats
Authors: Zhu Tingwei , Kuai Yiming , Guo Xingfeng , Bu Guanhao , Yang Chenxian , Chen Fusheng
Published: January 2025

The effects of three dietary oils (rapeseed oil, camellia oil, linseed oil) with different fatty acid compositions on the growth performance, digestion and gut microbiota of SD rats after 8 weeks of feeding were studied. The serum metabolic index and liver histomorphology of rats were measured using an automatic biochemical analyzer and light microscope. Furthermore, 16S rDNA amplicon sequencing technology was used to analyze the gut microbiota. It was found that these differences in fatty acid composition had no significant effect on body fat and liver tissue. However, after digestion, the rapeseed oil group showed lowest triglyceride content (1.22 ± 0.15) and a lower LDL/HDL ratio (0.41 ± 0.02). For gut microbiota distribution, the linseed oil group showed a higher Firmicutes/Bacteroides ratio (6.11 ± 0.54) and a high proportion of Lactobacillus. These data indicate that both the unsaturated fatty acid content and n-3 unsaturated fatty acids collectively had an effect on digestion metabolism, and the influence order may be n-3 unsaturated fatty acids > unsaturated fatty acid content.
Myrica rubra Preharvest Treatment with Melatonin Improves Antioxidant and Phenylpropanoid Pathways During Postharvest Storage
Authors: Chen Jun-Quan , Ma Yun-Shuang , Zhou Hejiang , Yu Rui-Xue , Xiong Miao , Yang Na , Wang Ji-Qiu , Tian Yang , Su Ling-Yan
Published: January 2025

Myrica rubra is known for its popularity and robust nutritional value. While fresh Myrica rubra fruit is a perishable commodity, it has a short post-harvest life and is susceptible to fungal decay after harvest. Melatonin has been reported to delay the aging and quality decline of various fruits and vegetables after harvest. However, the effects of pre-harvest melatonin treatment on the maintenance of post-harvest quality and storage extension of fresh Myrica rubra fruit are still unclear. The impact of pre-harvest spraying of melatonin at different concentrations (100 μM, 300 μM, and 500 μM) on the fruit quality of Myrica rubra during storage at room temperature or 4 °C was investigated. The results indicated that in the final stage of storage, compared with the control group, different concentrations of melatonin reduced the decay index by 13.0–47.1% and also decreased the weight loss, the content of O2−•, and the content of malondialdehyde (MDA), respectively. Meanwhile, melatonin increased the content of antioxidants such as superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), as well as the total polyphenols and flavonoids content. Finally, RNA transcriptome sequencing revealed that melatonin enhanced the antioxidant capacity by increasing the expression of both antioxidant enzymes and changing phenylpropanoid pathway-related genes, therefore maintaining the fresh Myrica rubra quality. Our findings uncovered a potent role and mechanism of melatonin in maintaining Myrica rubra fruit quality during storage and suggest that pre-harvest melatonin spraying may be a convenient and effective method for prolonging storage and maintaining quality of fruits after picking.
A Novel Eco-Friendly Process for the Synthesis and Purification of Ascorbyl-6-Oleates
Authors: Ji Ha-Eun , Kim Se-Young , So Heejin , Prayitno Vivian , Lee Ki-Teak , Shin Jung-Ah
Published: January 2025

Commercial ascorbyl-6-O-esters (AEs) are composed of saturated fatty acids with relatively high melting points, resulting in limited solubility in lipophilic media. Therefore, a lipase-catalysed synthesis and purification method for ascorbyl-6-O-oleate (AO) was proposed in this study. The esterification synthesis (i.e., bonding of oleoyl group to ascorbic acid) rate was 19.7% using acetone as the reaction solvent. The transesterification synthesis (i.e., exchange of acyl group with oleic acid (OA) in ascorbyl-6-O-palmitate (AP)) rate increased to 73.8% (AP:OA = 1:3, molar ratio). The esterification product was purified sequentially by liquid–liquid extraction using ethyl acetate and water, followed by hexane and acetonitrile, resulting in 94.8 area% AO confirmed by HPLC. When acetonitrile was replaced with 90% methanol, AO achieved 97.2 area%. Similarly, the transesterification product showed 94.3 area% AEs (AP:AO = 8.9:91.1) after recrystallisation and liquid–liquid extraction. Finally, all purified AO revealed peaks corresponding to the hydroxyl groups at the C-2 and C-3 carbons (11.10 and 8.41 ppm, 1H-NMR), whereas OA selectively esterified at the C-6 carbon (13C-NMR). FT-IR confirmed the presence of the ester bond (1733 cm−1) and olefin structure (3006 cm−1) of OA, and LC-ESI-MS/MS identified AO peaks at m/z 439.3. DSC analysis showed broad endothermic curves at 23.1–46.7 °C when the purified AO samples were pre-cooled at −25 °C.
Ameliorative Effects of Raisin Polyphenol Extract on Oxidative Stress and Aging In Vitro and In Vivo via Regulation of Sirt1–Nrf2 Signaling Pathway
Authors: Gao Wenjing , Zhao Caiyun , Shang Xin , Li Bin , Guo Jintian , Wang Jingteng , Wu Bin , Fu Yinghua
Published: January 2025

Raisins are an important source of polyphenolic compounds in plant foods, and polyphenols are associated with antioxidant and anti-aging activity. In this work, 628 polyphenols in raisin extracts were characterized using UPLC-MS/MS, mainly including tricetin 3′-glucuronide, diisobutyl phthalate, butyl isobutyl phthalate, isoquercitrin and 6-hydroxykaempferol-7-O-glucoside. The oxidative stress in H2O2-induced HepG2 cells and D-gal-induced aging mice was alleviated by raisin polyphenols (RPs) via increases in the cellular levels of superoxide dismutase (SOD), catalase (CAT) and glutathione (GSH), along with decreases in malonaldehyde (MDA), reactive oxygen species (ROS) and advanced glycosylation end-products (AGEs) levels. In addition, it was observed that RPs enhanced Sirt1 and Sirt3 expression, initiating the Keap1-Nrf2 signaling pathway, by upregulating the levels of nuclear Nrf2, facilitating the expressions of the antioxidant proteins NQO1 and HO-1, and downregulating Keap1 and cytoplasmic Nrf2 protein levels in H2O2-induced HepG2 cells and D-gal-induced aging mice. In summary, RP exerted antioxidant and anti-aging effects via regulating the Sirt1–Nrf2 signaling pathway in vitro and in vivo.
Celiac Disease, Gluten-Free Diet, and Eating Disorders: From Bench to Bedside
Authors: Wei Yaohui , Wang Yating , Yuan Yonggui , Chen Jue
Published: January 2025

Celiac disease (CD) and eating disorders (EDs) are complex chronic conditions in adolescents, sharing symptoms such as weight change, malnutrition, and gastrointestinal symptoms. CD, an autoimmune disorder triggered by gluten ingestion, is managed through a strict gluten-free diet that can unintentionally foster disordered eating behaviors due to dietary restrictions. Conversely, EDs may mask and complicate CD symptoms, leading to diagnostic delays and treatment challenges. Evidence reveals an increased risk of EDs in CD individuals and vice versa, indicating a potential bidirectional relationship. This review explores the mechanisms and clinical implications of this interplay and proposes integrated screening and care strategies to improve the quality of life for individuals with both conditions.
Changes in Volatile Compounds and Sensory Properties of Chicken with Armillaria mellea During the Pressure-Cooking Process
Authors: Dong Xiaolan , Xia Chuntao , Fan Hongxiu , Zhang Xu , Sun Tong , Wang Zhiyu , Liu Tingting
Published: January 2025

Chicken with Armillaria mellea prepared via pressure cooking is a traditional Chinese delicacy with great potential for food development. Optimizing its cooking time is crucial. In this study, chicken and Armillaria mellea were pressure-cooked for different amounts of time (20 min, 25 min, 30 min, 35 min, and 40 min). In total, 101 and 81 volatile compounds were identified by GC-MS and GC-IMS, respectively. The results showed that the content of volatile compounds was the highest at 40 min. Nonanal, decanal, (E,E)-2,4-nonadienal, (E,E)-2,4-decadienal, and 1-octen-3-ol were identified as the most critical aroma compounds at this time, which brought unique fat, oil, and mushroom aroma to chicken with Armillaria mellea during the pressure-cooking process. The optimal time was determined to be 35 min through sensory properties. In summary, the optimal cooking time for chicken with Armillaria mellea prepared via pressure cooking is 35–40 min. Our research results not only preliminarily determined the optimal conditions for industrial processing of the prepared dish of with Armillaria mellea prepared via pressure cooking, laying a foundation for the later industrial production of prepared dishes and international sales, but also stimulated innovative composite food development and promoted people’s exploration of the mechanism of heat treatment on composite food flavor and taste.
Soy Protein Isolate Improved the Properties of Fish Oil-Loaded Chitosan–Sodium Tripolyphosphate Capsules
Authors: Wang Yunning , Asad Mubeen , Wang Deqian , Gao Xiaofan , Zheng Guoliang , Zhong Jian , Xie Jing , Wang Zhengquan
Published: January 2025

In this paper, the effect of soybean isolate protein (SPI) content on the physicochemical properties and oxidative stability of chitosan–sodium tripolyphosphate (CS-STPP)-loaded fish oil capsules was investigated. The SPI/CS-STTP capsules formed after the addition of different amounts of SPI were larger in size and more homogeneous in morphology than the CS-STPP capsules, and the SPI was encapsulated on the surface of the CS matrix, altering the surface properties and morphology of the particles. The study of different CS-to-SPI blend ratios (1:0, 3:1, 2:1, 1:1, 1:2) showed that the water content of the microcapsules increased from 49.79% to 53.27–64.99%, the fish oil loading increased from 17.06% to 18.31–24.89%, and the encapsulation rate increased from 89.42% to 93.90–96.14%. In addition, the addition of SPI reduced the maximum peroxide value from 445 to 264 meq/kg oil. In the simulated in vitro digestion experiments, the addition of various amounts of SPI resulted in a significantly lower percentage of final free fatty acid (FFA) release than observed for CS-STPP capsules alone. These changes observed in the properties may be due to structural differences between CS-STPP capsules and SPI/CS-STPP capsules. All the results confirm that the obtained capsules are promising for the development of functional foods and drugs.
Advancing Road Safety: A Comprehensive Evaluation of Object Detection Models for Commercial Driver Monitoring Systems
Authors: Zia Huma , Hassan Imtiaz ul , Khurram Muhammad , Harris Nicholas , Shah Fatima , Imran Nimra
Published: January 2025

This paper addresses the critical issue of road safety in the indispensable role of transportation for societal well-being and economic growth. Despite global initiatives like Vision Zero, traffic accidents persist, largely influenced by driver behavior. Advanced driver monitoring systems (ADMSs) utilizing computer vision have emerged to mitigate this issue, but existing systems are often costly and inaccessible, particularly for bus companies. This study introduces a lightweight, deep-learning-based ADMS tailored for real-time driver behavior monitoring, addressing practical barriers to enhance safety measures. A meticulously curated dataset, encompassing diverse demographics and lighting conditions, captures 4966 images depicting five key driver behaviors: eye closure, yawning, smoking, mobile phone usage, and seatbelt compliance. Three object detection models—Faster R-CNN, RetinaNet, and YOLOv5—were evaluated using critical performance metrics. YOLOv5 demonstrated exceptional efficiency, achieving an FPS of 125, a compact model size of 42 MB, and an mAP@IoU 50% of 93.6%. Its performance highlights a favorable trade-off between speed, model size, and prediction accuracy, making it ideal for real-time applications. Faster R-CNN achieved an FPS of 8.56, a model size of 835 MB, and an mAP@IoU 50% of 89.93%, while RetinaNet recorded an FPS of 16.24, a model size of 442 MB, and an mAP@IoU 50% of 87.63%. The practical deployment of the ADMS on a mini CPU demonstrated cost-effectiveness and high performance, enhancing accessibility in real-world settings. By elucidating the strengths and limitations of different object detection models, this research contributes to advancing road safety through affordable, efficient, and reliable technology solutions.
In Situ Aqueous Spice Extract-Based Antifungal Lock Strategy for Salvage of Foley’s Catheter Biofouled with Candida albicans Biofilm Gel
Authors: Sadanandan Bindu , Vijayalakshmi Vaniyamparambath , Shetty Kalidas , Rathish Adithya , Shivkumar Harshala , Gundreddy Malavika , Narendra Nikhil Kumar Kagganti , Devaiah Nethra Machamada
Published: January 2025

Candida forms a gel-like biofilm in the Foley’s catheter (FC) causing tenacious biofouling and severe urinary tract infections (UTIs). For the first time, a spice extract-based antifungal lock therapy (ALT) has been developed to inhibit the Candida albicans gel matrix in FC. Aqueous extracts of garlic, clove, and Indian gooseberry were used as ALT lock solutions and tested against biofilm-forming multidrug-resistant clinical isolates of C. albicans. Reduction in the gel matrices formation in the catheter was confirmed by Point inoculation, MTT assay, CFU, and SEM analysis at 12 and 24 h of incubation. Garlic was effective in controlling both C. albicans M207 and C. albicans S470; however, clove and gooseberry effectively controlled the latter. As evidenced by CFU assay, there were 82.85% and 99.68% reductions in the growth of C. albicans M207 and S470, respectively, at 24 h of incubation. SEM revealed a switch from the biofilm to the yeast mode and a drastic reduction in cell numbers, with mostly clumped or lysed cells. The study will provide an impetus to the development of novel spice extract-based ALT, reducing the selection pressure on the pathogen and lowering antimicrobial resistance. Further research in this area has the potential to leverage clinical applications.