bluuebunny/crossref_metadata_2025 huggingface dataset:
Leveraging deep learning for plant disease and pest detection: a comprehensive review and future directions
Authors: Shoaib Muhammad , Sadeghi-Niaraki Abolghasem , Ali Farman , Hussain Irfan , Khalid Shah
Published: February 2025

Plant diseases and pests pose significant threats to crop yield and quality, prompting the exploration of digital image processing techniques for their detection. Recent advancements in deep learning models have shown remarkable progress in this domain, outperforming traditional methods across various fronts including classification, detection, and segmentation networks. This review delves into recent research endeavors focused on leveraging deep learning for detecting plant and pest diseases, reflecting a burgeoning interest among researchers in artificial intelligence-driven approaches for agricultural analysis. The study begins by elucidating the limitations of conventional detection methods, setting the stage for exploring the challenges and opportunities inherent in deploying deep learning in real-world applications for plant disease and pest infestation detection. Moreover, the review offers insights into potential solutions while critically analyzing the obstacles encountered. Furthermore, it conducts a meticulous examination and prognostication of the trajectory of deep learning models in plant disease and pest infestation detection. Through this comprehensive analysis, the review seeks to provide a nuanced understanding of the evolving landscape and prospects in this vital area of agricultural research. The review highlights that state-of-the-art deep learning models have achieved impressive accuracies, with classification tasks often exceeding 95% and detection and segmentation networks demonstrating precision rates above 90% in identifying plant diseases and pest infestations. These findings underscore the transformative potential of deep learning in revolutionizing agricultural diagnostics.
Network governance in ASEAN: fostering regional cooperation and integration
Authors: Sundram Pushpanathan
Published: February 2025

This article examines network governance (NG) within the context of the Association of Southeast Asian Nations (ASEAN) and its sectoral communities, specifically the ASEAN Economic Community, the ASEAN Political-Security Community, and the ASEAN Socio-Cultural Community. The goal is to explore NG’s importance in fostering cooperation among ASEAN member states and addressing regional challenges. The study begins by providing an overview of ASEAN and its objectives, highlighting the crucial role of NG in promoting collaboration and policymaking through ASEAN processes. It then offers a comprehensive literature review that evaluates the conceptual framework of NG and previous research related to its significance for ASEAN. The article further explores theories and scholarly works discussing NG within ASEAN, offering insights into key themes and discussions in the literature. Specific examples from the three sectoral communities are included based on an analysis of ASEAN NG mechanisms and structures. The evaluation of NG effectiveness in tackling regional challenges considers the contributions of state actors, such as government representatives and non-state actors (NSAs), including civil society organizations and private sector entities. This analysis reveals the inherent challenges and opportunities in implementing NG within ASEAN frameworks. It also underscores the importance of collaborative efforts between state actors and NSAs and the need for supportive institutional frameworks and mechanisms to enhance NG effectiveness in ASEAN. Overall, this article aims to deepen the understanding of NG within ASEAN, illuminating its role in promoting regional integration, addressing challenges, and advancing development across ASEAN’s three sectoral communities.
Who gets frustrated? Identifying individuals prone to frustration using a latent profile analysis
Authors: Yazdi Hannaneh , Ljung Aust Mikael , Wickman Casper , Bujacz Aleksandra , Kowalski Leo , Lundström Johan N.
Published: February 2025

Introduction

Frustration is a complex negative emotion with multifaceted components that significantly influence cognitive and behavioral responses. While previous studies have explored frustration, identifying distinct groups of individuals prone to frustration has yielded inconsistent findings. This study employs a person-centered approach to identify clusters of drivers based on frustration triggers and emotional responses to frustrating events.

Methods

A total of 2,219 drivers participated in an online survey assessing frustration experiences in various frustrating scenarios. Latent Profile Analysis (LPA) was conducted to identify subgroups based on frustration triggers and emotional responses. Predictor variables included Driving Behavior Dimensions (violations, errors, and lapses), user group categories (car-sharing, ownership, leasing), and demographic factors (age and gender).

Results

LPA identified four distinct frustration profiles: Minimal, Low, Moderate, and Severe. These profiles were associated with different frustration triggers (i.e., goal blockage, limited control) and emotional responses (i.e., anger, stress, and irritation). The Severe profile, characterized by a high probability of individuals being highly prone to frustration, exhibited the highest frustration levels and was predominantly composed of older drivers (>45 years), particularly women, from car-sharing and leasing user groups. Emotional response patterns and the likelihood of frustration arousal are consistent across profiles, varying primarily in intensity.

Discussion

These findings offer insights into frustration susceptibility and underscore the need for targeted interventions to enhance emotion regulation in driving contexts. Future research should explore personalized strategies to mitigate frustration based on individual and group characteristics.
The impact of core training combined with breathing exercises on individuals with chronic non-specific low back pain
Authors: Li Ying , Zhao Qian , Zhang Xiao , E Yan , Su Yuqin
Published: February 2025

Background

Chronic non-specific low back pain (CNLBP) is a common condition, defined as pain lasting more than 3 months between the lower thoracic margin and gluteal folds, without identifiable tissue damage. Despite its low disability rate, the complex etiology and high recurrence impose significant health and socioeconomic burdens. According to European LBP guidelines, exercise therapy is the preferred treatment for CNLBP. This study evaluates the efficacy of core training combined with breathing exercises as a therapeutic intervention for CNLBP.

Methods

Eighteen CNLBP patients were randomly assigned to three groups: core training only, core training with breathing exercises, and a control group. A 12-week intervention included VAS, ODI scores, and muscle strength tests.

Results

The combined group showed significantly greater pain reduction, functional improvement, and muscle strength enhancement compared to the other groups.

Conclusion

Core training with breathing exercises is more effective in alleviating CNLBP symptoms, highlighting the added value of integrating breathing exercises.
Exploring the relationship between physical activity and smartphone addiction among college students in Western China
Authors: Lai Chun , Cai Peiling , Liao Junyi , Li Xiwei , Wang Yuanyuan , Wang Mengping , Ye Peng , Chen Xinwei , Hambly Brett D. , Yu Xiaoping , Bao Shisan , Zhang Haifeng
Published: February 2025

Background

Smartphone addiction (SA) refers to a behavioral disorder characterized by an irresistible compulsion to excessively engage with mobile devices. Currently, the evidence regarding the relationship between physical activity (PA), exercise intensity (EI), and SA is limited, particularly within Chinese populations. This study aims to explore the correlation between PA, EI, and SA, specifically investigating how PA and EI impact SA to better understand the nature of this relationship.

Methods

A cross-sectional study was conducted involving college students from over 20 universities in Western China. Data were collected on participants’ engagement in PA, EI, and SA. Additionally, covariates such as age, gender, ethnicity, academic classification, university location, discipline, year of study, hometown region, sibling status, relationship status, and social interactions were recorded. Multivariate logistic regression models were used to assess the association between PA, EI, and SA. Stratified and interaction analyses were performed to examine whether the relationship remained consistent across different subgroups.

Results

Of the 3,506 college students surveyed, 1,905 (54.3%) experienced SA. The prevalence of SA was 11.3% lower in the group that engaged in PA compared to those who did not. In the fully adjusted model, PA was negatively associated with SA (OR = 0.70, 95% CI: 0.59–0.82, p < 0.001). EI was also inversely associated with SA. Moderate- and vigorous-intensity exercise had odds ratios of 0.81 (95% CI: 0.67–0.98, p = 0.034) and 0.83 (95% CI: 0.68–1.00, p = 0.046), respectively, compared with low-intensity exercise. Similar patterns were observed in subgroup analyses (all p values for interaction >0.05).

Conclusion

The findings indicate a significant negative association between PA, EI, and SA, highlighting the potential of promoting PA and higher EI as strategies to reduce SA among college students.
Doxorubicin and sorafenib release from mesoporous silica nanoparticles coated with polydopamine – influence of mechanical and chemical stimuli on the process
Authors: Ostrowska Sylwia , Szukowska Monika , Kim Shinik , Kim Yeonho , Wawrzyniak Dariusz , Mrówczyński Radosław
Published: February 2025

In this paper, we present results of a study on the influence of different experimental conditions on drug release, for the two anticancer drugs: doxorubicin (DOX) and sorafenib (SO), from mesoporous silica nanoparticles coated with polydopamine (PDA) shell. We tested the drugs release from the carrier into buffers of different pH (4.5; 5.5; 7.5) and with the addition of H2O2 or glutathione (GSH), while stirring the carriers in a flask or shaking them in a thermoblock, keeping the same time intervals, temperature and frequency. The obtained results and performed statistical analysis prove that the way the drug release tests are conducted has a significant influence on the efficiency of release of both drugs from the carrier. Thus, our results are of great importance for characterization of multimodal nanocarriers for biomedical application in terms of drug release and bring new knowledge for their methodological investigation.
Electricity markets price projection: an innovative approach for risk assessment based on a convolution algorithm. ERCOT case study
Authors: Llarens Daniel
Published: February 2025

In electricity markets, the determination of future energy prices is relevant for risk assessment associated with investment projects in new generation capacity and in the evaluation of risks associated with the operation of the market whose mitigation requires increasing the operating reserves in the electrical system. Traditional methods for estimating energy prices in electricity markets are based on using simulation models that represent the expected future operation of the electricity market. These models fail to estimate market prices when the greatest uncertainty that affects the system reserve is due to the unavailability of the generation fleet and the volatility of the production of renewable wind and solar generation. This document presents a new methodology that allows determining energy prices in electricity markets that is considered superior to traditional methods. It is an innovative approach for risk assessment in power markets with high participation of renewable generation (wind, solar) and thermal generation. The model determines market prices considering the randomness in the typical production of renewable generation and the randomness in the availability of thermal power plants due to forced failures. Market prices are determined through a convolution algorithm applied to the probability functions that characterize energy demand, the randomness in the production of renewable generation, and the availability of thermal generation units. The calculation methodology is considered superior to Monte Carlo-type methodologies used by other simulation programs. A case study is included where the electricity market of Texas USA (ERCOT) is simulated and comparing the market prices resulting from the new simulation model with the real market prices recorded in the year 2022. The market prices determined by the proposed new methodology provide relevant information for consumers to evaluate energy purchase alternatives correctly and for investors in new generation capacity to determine the profitability of their projects. In particular, it allows the correct determination of energy prices in periods of scarcity allowing storage media (BESS) to be correctly sized so that they can provide a quickly managed reserve and thus improve the reliability of the electrical system.
Investigating the role of biophilic design to enhance comfort in residential spaces: human physiological response in immersive virtual environment
Authors: Al Sayyed Heba , Al-Azhari Wael
Published: February 2025

Indoor environments significantly impact human health. The COVID-19 pandemic highlighted the urgency of reconnecting with nature to maintain both physiological and psychological health. Modern indoor lifestyles have increased isolation from nature, diminishing these benefits. While previous studies have demonstrated the positive effects of biophilic design on human physiological comfort, its application in residential spaces remains underexplored. This study investigates how biophilic design elements—including natural light, ventilation, and greenery—influence physiological stress and comfort in residential settings using immersive virtual environments (IVE). Ninety-four participants were exposed to two test environments: one with biophilic elements and one without. Measurements of skin conductance level (SCL) and blood pressure (BP) were recorded across three phases: relaxation, exposure to mild stressors, and recovery. The results revealed a significant reduction in SCL in biophilic environments (∆M = −0.38) compared to non-biophilic environments (∆M = −0.19). However, BP levels remained unaffected across both experiments. These findings suggest that biophilic design positively influences stress recovery and comfort, underscoring its potential in residential applications.
Insights from multi-process fan deposits in martian intracrater basins on post-Noachian climate change
Authors: Williams Rebecca M. E.
Published: February 2025

Alluvial fans are a sensitive record of environmental transitions. Prior studies have determined that martian fans are primarily located in impact crater basins and that fan deposition occurred principally between 3.7 and 3.3 Ga or later, corresponding to the presumed critical climate-changing period. This paper illustrates previously unrecognized flow types and superposition relationships in fan deposits that show a time sequence of varying processes. Examples include debris flows following earlier eroded fluvial deposits (ridges interpreted as inverted channels), an intriguing pitted deposit interpreted to be a highly viscous mudflow with air bubble release, and landforms recording the role of late-stage fluvio-glacial processes. The diversity of fan forms highlight the complex and variable conditions on post-Noachian Mars. This evidence supports fluctuating ‘warm, wet’ and ‘cold, dry’ periods, suggesting that the climate transition was variable and slowly degraded, rather than a swift monotonic decline.
Farmers’ adoption of smart agricultural technologies for black soil conservation and utilization in China: the driving factors and its mechanism
Authors: Yu Jiaping , Li Jing , Lo Kevin , Huang Shanlin , Li Yiqi , Zhao Zixin
Published: February 2025

Smart agriculture can mitigate the degradation of black soil organic matter to ensure global food security and promote sustainable agricultural development. However, the adoption of smart agricultural technology for black soil conservation and utilization is poorly understood. This study analyzes the influence mechanisms affecting farmers’ adoption intentions of one such technology, variable fertilization. We develop a structural equation model by combining the Technology Acceptance Model (TAM), Perceived Value Theory (PVT), and external factors with data from 354 farmers in Youyi State farm in the Sanjiang Plain Area, China. The results revealed that social influence (SI) was the most significant determinant of farmers’ adoption intentions (AI), emphasizing the critical role of social networks, particularly information from experienced demonstration households, in shaping decisions. Additionally, both the perceived usefulness (PU) and perceived ease of use (PEOU) of variable fertilization technology (VFT) significantly and positively influenced AI. Among these, PEOU demonstrated a greater overall impact than PU. We propose strategies for demand-driven, incentive-based, and technical support mechanisms to facilitate the adoption of VFT and conclude with recommendations to promote black soil conservation and utilization technologies among farmers.
Effectiveness of marker training for detection dogs
Authors: Lazarowski Lucia , Rogers Bart , Collins-Pisano Courtney , Krichbaum Sarah , Handley Michael , Smith Jordan G. , Waggoner Paul
Published: February 2025

Training detection dogs to alert to an odor requires precision in the timing and delivery of stimulus presentations in order to condition a strong association between odor and reward and to train a desired alert behavior that communicates the presence and location of the odor source. Marker training, in which a signal that predicts a reward is used to deliver immediate feedback for a correct response and bridge the delay between the desired behavior and reward, is a popular technique in the animal training industry. However, the application of marker training to detection dog training has not been examined, and empirical evidence of the purported benefits of marker training in general is lacking. The current study evaluated the effectiveness of marker training for odor detection learning and performance. Candidate detection dogs (n = 28) were trained to detect and alert to a target odor either with or without the use of a clicker as a marker (n = 14 per group). Effectiveness of marker training was assessed by comparing rate of learning the odor discrimination and the alert response, detection accuracy and topography of the alert behavior in an odor discrimination test, generalization of learned behavior from the odor recognition setting to a novel context (i.e., open-area operational searches), and resistance to extinction. Compared to dogs trained with the reward only, dogs trained with the marker as a signal for reward completed the training phase in fewer trials, performed the alert response more accurately in the odor recognition test, indicated the location of the odor source more precisely in the operational searches, and exhibited greater resistance to extinction when the primary reward for a correct response was withheld. These results provide evidence supporting the effectiveness of markers in animal training, and demonstrate benefits specific to the challenges commonly faced in detection dog training.
Transforming Medical Data Access: The Role and Challenges of Recent Language Models in SQL Query Automation
Authors: Tanković Nikola , Šajina Robert , Lorencin Ivan
Published: February 2025

Generating accurate SQL queries from natural language is critical for enabling non-experts to interact with complex databases, particularly in high-stakes domains like healthcare. This paper presents an extensive evaluation of state-of-the-art large language models (LLM), including LLaMA 3.3, Mixtral, Gemini, Claude 3.5, GPT-4o, and Qwen for transforming medical questions into executable SQL queries using the MIMIC-3 and TREQS datasets. Our approach employs LLMs with various prompts across 1000 natural language questions. The experiments are repeated multiple times to assess performance consistency, token efficiency, and cost-effectiveness. We explore the impact of prompt design on model accuracy through an ablation study, focusing on the role of table data samples and one-shot learning examples. The results highlight substantial trade-offs between accuracy, consistency, and computational cost between the models. This study also underscores the limitations of current models in handling medical terminology and provides insights to improve SQL query generation in the healthcare domain. Future directions include implementing RAG pipelines based on embeddings and reranking models, integrating ICD taxonomies, and refining evaluation metrics for medical query performance. By bridging these gaps, language models can become reliable tools for medical database interaction, enhancing accessibility and decision-making in clinical settings.
Spatial Distribution and Influencing Factors of Agricultural Enterprise Brands in Guangxi
Authors: Ouyang Shasha , Wen Jun , Xu Xingpeng
Published: February 2025

This study leverages advanced analytical tools such as ArcGIS spatial analysis and Geographical Detectors to conduct a comprehensive analysis of the spatial distribution characteristics, equilibrium, hotspot areas, and geographic associations of 164 district-level agribusiness brands in Guangxi, highlighting the unique insights these tools provide into the spatial heterogeneity of agricultural enterprise brands. Our findings reveal a significant concentration of brands in the northern region, particularly in Nanning, Liuzhou, and Guilin, with a dense northeast and sparse southwest distribution pattern. We identify a positive correlation between the number of regional brands and GDP and a negative correlation with distance from major highways. This suggests that regional economic development and transportation infrastructure significantly impact brand distribution. To enhance brand development, we recommend focusing on regional brand cultivation, innovation, and leveraging digital marketing strategies. This study provides actionable insights for policymakers and practitioners aiming to promote agricultural brand growth and rural revitalization in Guangxi. This pattern suggests that regions with abundant natural resources and higher economic development levels are more conducive to the formation and growth of agricultural enterprise brands, highlighting the importance of regional economic foundations and resource endowments in agricultural branding. Specifically, brands are primarily concentrated in the northern region, with Nanning, Liuzhou, and Guilin having a particularly high number of such brands. This pattern aligns with the core–periphery theory in economic geography, which suggests that economic activities tend to cluster around central cities due to agglomeration economies. The findings challenge the assumption that agricultural brands are evenly distributed across regions, highlighting the importance of regional economic foundations and infrastructure in brand development. Additionally, the significant positive correlation between the number of regional brands and Gross Domestic Product supports the idea that economic strength fosters brand development. Conversely, the significant negative correlation between the number of agricultural brand enterprises and the distance from major highways underscores the critical role of transportation infrastructure in facilitating market access and brand growth. Therefore, this study highlights the importance of cultivating regional brands, enhancing innovation capabilities, and advancing new marketing methods to promote the spatial equilibrium and sustainable development of agricultural enterprise brands, contributing to rural revitalization in Guangxi.
Application of Modified Atmosphere Preservation Technology in Cherry Storage: A Review
Authors: Liu Lu , Lin Haiyan , Zhou Xixin , Zhang Zhixu , Zhang Yi , Deng Sengwen , Peng Shiqian , Gong Shuaikun , Guo Shiyin , Fan Wei
Published: February 2025

Cherries, as high-value horticultural products, have long faced preservation challenges due to their perishable nature and limited postharvest longevity. During storage and transportation, these stone fruits are particularly susceptible to quality deterioration and pathological decay, significantly impacting commercial viability and consumer acceptance. Modified atmosphere preservation (MAP) technology has emerged as the predominant preservation method for cherry storage, recognized for its operational safety, environmental controllability, and technical reliability. This review systematically examines the physiological degradation mechanisms of cherries during storage, identifies critical environmental factors influencing decay patterns, and synthesizes recent advancements in MAP applications. The analysis encompasses technological principles and efficacy evaluations of atmospheric modification, with particular emphasis on how regulated temperature, humidity, and gas composition parameters affect the bioactive compound retention, organoleptic properties, and overall eating quality—crucial factors for enhancing consumer satisfaction and market value. Furthermore, this paper critically addresses current technological limitations, including implementation costs, operational complexity, and environmental sustainability concerns. Finally, it proposes innovative optimization strategies and outlines future development trajectories to advance technological refinement and promote sustainable innovation in terms of cherry preservation methodologies.
Utilizing Genetic Resources for Agronomic Trait Improvement: Series II
Authors: Martínez-Moreno Fernando , Picó María Belén , Díez María José , Ruiz Magdalena
Published: February 2025

Genetic resources are a particularly valuable reserve; specifically, in the search for genetic variability in agronomic traits that allow for greater adaptability, tolerance to limiting abiotic conditions, resistance to pathogens, and further traits related to valued qualities (e [...]
Improved YOLOv8-Based Segmentation Method for Strawberry Leaf and Powdery Mildew Lesions in Natural Backgrounds
Authors: Chen Mingzhou , Zou Wei , Niu Xiangjie , Fan Pengfei , Liu Haowei , Li Cuiling , Zhai Changyuan
Published: February 2025

This study addresses the challenge of segmenting strawberry leaves and lesions in natural backgrounds, which is critical for accurate disease severity assessment and automated dosing. Focusing on strawberry powdery mildew, we propose an enhanced YOLOv8-based segmentation method for leaf and lesion detection. Four instance segmentation models (SOLOv2, YOLACT, YOLOv7-seg, and YOLOv8-seg) were compared, using YOLOv8-seg as the baseline. To improve performance, SCDown and PSA modules were integrated into the backbone to reduce redundancy, decrease computational load, and enhance detection of small objects and complex backgrounds. In the neck, the C2f module was replaced with the C2fCIB module, and the SimAM attention mechanism was incorporated to improve target differentiation and reduce noise interference. The loss function combined CIOU with MPDIOU to enhance adaptability in challenging scenarios. Ablation experiments demonstrated a segmentation accuracy of 92%, recall of 85.2%, and mean average precision (mAP) of 90.4%, surpassing the YOLOv8-seg baseline by 4%, 2.9%, and 4%, respectively. Compared to SOLOv2, YOLACT, and YOLOv7-seg, the improved model’s mAP increased by 14.8%, 5.8%, and 3.9%, respectively. The improved model reduces missed detections and enhances target localization, providing theoretical support for subsequent applications in intelligent, dosage-based disease management.
Structure and Function Analyses of the Thioredoxin 2 and Thioredoxin Reductase Gene in Pacific White Shrimp (Litopenaeus vannamei)
Authors: Xu Tong , Zheng Pei-Hua , Luan Ke-Er , Zhang Xiu-Xia , Li Jun-Tao , Zhang Ze-Long , Hou Wei-Yan , Zhang Li-Min , Lu Yao-Peng , Xian Jian-An
Published: February 2025

The thioredoxin (Trx) system is one of the most significant systems in living organisms as it regulates cellular redox reactions and plays a pivotal protective role within the cell by promoting redox homeostasis. Trx and thioredoxin reductase (TrxR) are the core oxidoreductases of the Trx system. In this study, the novel full-length cDNAs of LvTrx2 and LvTrxR were cloned from Litopenaeus vannamei. The ORFs of LvTrx2 and LvTrxR were 453 bp and 1785 bp, encoding polypeptides consisting of 150 and 596 amino acids. Sequence alignment analysis revealed that the amino acid sequence of LvTrx2 shared a high degree of identity (93%) with that of Penaeus chinensis, while in LvTrxR, it exhibited a similarity level of 95% with previously submitted Penaeus chinensis and Penaeus monodon sequences. Regarding tissue-specific expression patterns, LvTrx2 showed its highest expression levels in hepatopancreas and gill. For LvTrxR, the highest expression was observed in gill followed by hepatopancreas and intestine. During exposure to ammonia-N, there was a significant upregulation in the relative mRNA levels of LvTrx2 and LvTrxR in hepatopancreas and gill, with the peak values occurring at 24 h or 48 h of exposure. After LPS injection, the LvTrx2 and LvTrxR transcripts in hepatopancreas and gill had different upregulated levels. These findings suggest that LvTrx2 and LvTrxR play pivotal roles in enhancing stress resistance and bolstering antibacterial defense mechanisms in L. vannamei. To explore the roles, LvTrx2 expression was knocked down in vivo to verify the defense mechanism against 4-NP stress. LvTrx2 silencing in 4-NP-challenged shrimp could significantly induce the gene expression of antioxidant-related genes (except for LvTrxR) and aggravate the oxidative damage of lipids. This study suggests that the Trx system is involved in regulating the antioxidant processes, and LvTrx2 and LvTrxR play a vital role in defense responses against environmental stress.
Biological Activity and Chemical Composition of Essential Oil from Leaves and Fruits of Zanthoxylum mantaro (J.F.Macbr.) J.F.Macbr
Authors: Morocho Vladimir , Eras Odalis , Rojas Teresa , Jiménez Britany , Roa María Fernanda , Cartuche Luis
Published: February 2025

Objective: In this study, the chemical composition and biological activities of the essential oils extracted from the leaves and fruits of Zanthoxylum mantaro were analyzed. Methods: The essential oils were obtained through hydrodistillation using a Clevenger-type apparatus. Chemical composition was determined by gas chromatography coupled with mass spectrometry (GC-MS) and gas chromatography with a flame ionization detector (GC-FID). The antimicrobial activity was evaluated against four Gram-positive bacteria, three Gram-negative bacteria, and two fungi using the broth microdilution method. Antioxidant activity was assessed using the ABTS (2,2′-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid) and DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging assays. Additionally, the acetylcholinesterase inhibitory effect of the essential oils was measured by a spectrophotometric method. Results and Conclusions: A total of 23 compounds were identified in the essential oil from the fruits, while 47 compounds were found in the essential oil from the leaves. The major constituents of the fruit essential oil were α-thujone (39.85%), β-thujone (25.04%), sabinene (10.71%), and terpinen-4-ol (4.38%), whereas the main compounds in the leaf essential oil were germacrene D (21.75%), nerolidol (E) (12.39%), and pentadecanal (7.14%). The essential oil from the fruits exhibited antifungal activity against Aspergillus niger (ATCC 6275), with a minimum inhibitory concentration (MIC) of 1000 μg/mL. Both the fruit and leaf essential oils showed moderate antioxidant activity in the ABTS assay, with SC50 values of 274.14 ± 1.06 μg/mL and 2798.85 ± 15.69 μg/mL, respectively. Furthermore, the fruit essential oil demonstrated considerable acetylcholinesterase inhibitory activity with an IC50 value of 65.46 ± 1.01 μg/mL, while the leaf essential oil exhibited an IC50 value of 158.2 ± 1.02 μg/mL.
Novel Variants of SCCmec Type IX Identified in Clonal Complex 398 Livestock-Associated Methicillin-Resistant Staphylococcus aureus from Pork Production Systems in Korea
Authors: Lee Gi Yong , Lee Soo In , Seong Hoon Je , Yang Soo-Jin
Published: February 2025

Background/Objectives: The occurrence of novel variants of staphylococcal cassette chromosome mec (SCCmec) in livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) has frequently been reported, posing significant zoonotic concern worldwide. In this study, the occurrence of novel types of SCCmec IX elements was identified in two clonal complex (CC) 398 LA-MRSA strains derived from a pig farm and a slaughterhouse in Korea. Methods: Whole-genome sequence analysis of the two CC398 MRSA-SCCmec IX strains, designated KF1A-1172 and JS1E-122, revealed that these strains are most closely related to previously characterized strains of CC398 LA-MRSA carrying SCCmec V isolated from pig farms in Korea. Results: Further structural analysis of the SCCmec IX in KF1A-1172 and JS1E-122 revealed the presence of multiple ccr gene complexes (ccrA5B3, ccrAB3, and a truncated ccrA1), including ccrA1B1 genes for SCCmec type IX. In addition, the pseudo-SCC (ΨSCC) elements, genes associated with the type 1 restriction–modification (RM) system, and zinc resistance gene czrC, were identified in the SCCmec IX. Conclusions: These findings suggest that the multiple recombination events of elements derived from various SCCmec types contributed to the emergence of the novel SCCmec IX variant. The identification of these novel SCCmec IX types in CC398 LA-MRSA also suggests that epidemiological diversification of SCCmec IX in CC398 LA-MRSA is an ongoing event, necessitating continued surveillance on the emergence of novel SCCmec variants. This study is the first to report the complete genome sequences of CC398 MRSA carrying SCCmec IX in Korea.
Antioxidant, Osteogenic, and Neuroprotective Effects of Homotaurine in Aging and Parkinson’s Disease Models
Authors: Minoia Arianna , Piritore Francesca Cristiana , Bolognin Silvia , Pessoa João , Bernardes de Jesus Bruno , Tiso Natascia , Romanelli Maria Grazia , Schwamborn Jens Christian , Dalle Carbonare Luca , Valenti Maria Teresa
Published: February 2025

Aging is associated with the accumulation of cellular damage due to oxidative stress and chronic low-grade inflammation, collectively referred to as “inflammaging”. This contributes to the functional decline in various tissues, including the brain and skeletal system, which closely interplay. Mesenchymal stem cells (MSCs), known for their regenerative potential and ability to modulate inflammation, offer a promising therapeutic approach to counteract aging-related declines. In this study, we investigated the effects of homotaurine (a small molecule with neuroprotective properties) on MSCs and its effects on osteogenesis. We found that homotaurine treatment significantly reduced reactive oxygen species (ROS) levels, improved MSC viability, and modulated key stress response pathways, including the sestrin 1 and p21 proteins. Furthermore, homotaurine promoted osteogenesis and angiogenesis in zebrafish models by enhancing the expression of critical osteogenesis-associated genes, such as those coding for β-catenin and Runt-related transcription factor 2 (Runx2), and increasing the levels of the kinase insert domain receptor-like angiogenesis marker in aged zebrafish. In Parkinson’s disease models using patient-specific midbrain organoids with the leucine-rich repeat kinase 2 G2019S mutation, homotaurine treatment enhanced β-catenin expression and reduced ROS levels, highlighting its potential to counteract the oxidative stress and dysfunctional signaling pathways associated with neurodegeneration. Our findings suggest that homotaurine not only offers neuroprotective benefits but also holds promise as a dual-target therapeutic strategy for enhancing both neuronal and bone homeostasis in aging and neurodegenerative diseases.
Enhancing Digital Health Engagement Among Asian Seniors: Investigating the Acceptance and Use of Fitness Apps in Promoting Healthy Aging
Authors: Hanqing Zu , Chen Xiaolong , Zhang Hongfeng , Wong Cora Un In
Published: February 2025

This study investigated how older Asian adults (aged 50+) accept fitness apps, focusing on experiential factors derived from the technology acceptance model (TAM) and the Diffusion of Innovations (DOI). Between December 2023 and March 2024, a convenience sampling method was used to recruit older adults with three months of experience using fitness apps from social media platforms and community groups in multiple Asian countries. Of the 700 initial respondents, 587 valid questionnaires were retained (an 83.8% validity rate). Structural equation modeling (SEM) assessed relationships among relative advantages, compatibility, trialability, gamification, observability, perceived ease of use (PEU), perceived usefulness (PU), behavioral intention, and actual usage. Trialability, relative advantages, and compatibility significantly enhanced PEU (p < 0.01), while gamification and observability did not. By contrast, gamification and observability positively influenced PU (p < 0.05). Both PEU and PU in turn predicted behavioral intention, which explained actual app usage (p < 0.01). These findings underscore the importance of designing fitness apps that accommodate older adults’ skills and preferences, while also incorporating engaging features that reinforce perceived usefulness. Healthcare professionals and developers may leverage these insights to tailor digital health interventions, potentially improving exercise habits and well-being among aging populations in Asia.
Development of a Risk Assessment System for Navigational Obstacles Considering Collision and Pollution Risks
Authors: Lee Daehan , Namgung Ho , Yoo Sang-Lok
Published: February 2025

Navigational obstacles can impede safe vessel operation and cause secondary accidents, necessitating their rapid removal. To conduct these removal operations efficiently, it is necessary to comprehensively assess the effects of obstacles on both collision and pollution risks. However, comprehensive risk assessments that simultaneously consider both collision and pollution risks are lacking. In this study, a navigational obstacle risk assessment system based on the fuzzy set theory was developed to support the rapid removal of obstacles. The system comprises three main components: (i) a collision risk assessment model utilizing Monte Carlo simulation, (ii) a pollution risk assessment model employing a hazard management structure for sinking vessels, and (iii) a fuzzy set-based evaluation system that integrates risk indices derived from these models to infer the comprehensive risk. The results of the simulation-based case study confirm that the developed system provides reliable risk assessment by comprehensively considering both the collision and pollution risks. The system is sensitive to changes in the risk levels and effectively reflects the realistic conditions, thereby overcoming the limitations of existing research. This demonstrates its potential as a valuable tool for decision-making for rapid removal of navigational obstacles.
A Novel Capacity Estimation Method for Lithium-Ion Batteries Based on the Adam Algorithm
Authors: Lian Yingying , Qiao Dongdong
Published: February 2025

Accurate estimation of the capacity of lithium-ion batteries is crucial for battery management and secondary utilization, which can ensure the healthy and efficient operation of the battery system. In this paper, we propose multiple machine learning algorithms to estimate the capacity using the incremental capacity (IC) curve features, including the adaptive moment estimation (Adam) model, root mean square propagation (RMSprop) model, and support vector regression (SVR) model. The Kalman filter algorithm is first used to construct the IC curve, and the peak and corresponding voltages correlated with battery life were analyzed and extracted as capacity estimation features. The three models were then used to learn the relationship between aging features and capacity. Finally, the lithium-ion battery cycle aging data were used to validate the capacity estimation performance of the three proposed machine learning models. The results show that the Adam model performs better than the other two models, balancing efficiency and accuracy in the capacity estimation of lithium-ion batteries throughout the entire lifecycle.
Molecular Signatures of Cancer Stemness Characterize the Correlations with Prognosis and Immune Landscape and Predict Risk Stratification in Pheochromocytomas and Paragangliomas
Authors: Li Lei , Liu Shuangyu , Guo Zeqi , Tang Yueming , Zhang Yue , Qiu Ling , Li Yue
Published: February 2025

Background: Pheochromocytoma and paragangliomas (PPGLs) caused refractory hypertension in clinics. The sustained risk of local or metastatic recurrences or new tumor development prompted more research on diagnosis, prognosis prediction, and immunotherapy. Method: The tumor stemness is closely related to the heterogeneous growth of tumor, metastasis, and drug-resistance, and mRNA expression-based stemness indices (mRNAsi) could reflect tumor stemness. This was calculated based on OCLR machine learning algorithm and PPGLs patients’ TCGA RNAseq data. The relationship between clinical, molecular, and tumor microenvironment (TME) features and tumor stemness was analyzed through the hub genes that best captured the stem cell characteristics of PPGLs using weighted gene co-expression network analysis (WGCNA), Cox, and LASSO regression analysis. Results: Our study found that metastatic PPGLs had higher mRNAsi scores, suggesting the degree of tumor stemness could affect metastasis and progression. HRAS, CSDE1, NF1, RET, and VHL-mutant subtypes displayed significant difference in stemness expression. Patients were divided into stemness high-score and low-score subtypes. High-score PPGLs displayed the more unfavorable prognosis compared with low-score, associated with their immune-suppressive features, manifested as low macrophages M1 infiltration and downregulated expression of immune checkpoints. Furthermore, from the viewpoint of stemness features, we established a reliable prognostic for PPGLs, which has the highest AUC value (0.908) in the field so far. And this could stratify PPGLs patients into high-risk and low-risk subtypes, showing the significant differences in prognosis, underlying mechanisms correlated with specific molecular alterations, biological processes activation, and TME. Notably, high immune infiltration and tumor neoantigen in low-risk patients and further resulted in more responsive to immunotherapy. Conclusion: We indicated that tumor stemness could act as the potential biomarker for metastasis or prognosis of PPGLs, and integrated multi-data sources, analyzed valuable stemness-related genes, developed and verified a novel stemness scoring system to predict prognosis and guide the choice of treatment strategies.
Spatial Distribution Patterns, Environmental Drivers, and Hotspot Dynamics of the European Rabbit on a Mediterranean Island: Implications for Conservation and Management
Authors: Zevgolis Yiannis G. , Konsola Foto , Bouloutsi Athanasia-Zoi , Douskou Niki-Nektaria , Emmanouilidou Ioanna , Kordatou Maria-Alexandra , Lekka Anastasia , Limnioti Maria-Eirini , Loupou Maria , Papageorgiou Despoina , Papamakariou Michailia-Theodora , Tsiripli Eleni , Tzedopoulos Panagiotis , Xagoraris Christos , Kouris Alexandros D. , Dimitrakopoulos Panayiotis G.
Published: February 2025

The European rabbit (Oryctolagus cuniculus) presents a significant conservation and management challenge in Greece. While it has been listed in national biodiversity assessments, its population dynamics on the island of Lemnos demonstrate the characteristics of a highly adaptable and rapidly expanding species, exerting substantial ecological and economic impacts. Addressing this issue requires a spatially explicit understanding of its distribution patterns and habitat preferences, particularly given its extensive population growth over the past three decades. To this end, we conducted 40 field surveys across the island, documenting 1534 presence records of the species. We applied Kernel Density Estimation, Getis-Ord Gi *, and Anselin Local Moran’s I to identify the spatial distribution patterns and significant hotspots. A spatial lag model was used to quantify hotspot intensity and clustering dynamics, while abiotic, biotic, and anthropogenic factors were analyzed to assess habitat associations. Our results revealed that rabbit hotspots are predominantly concentrated in fertile lowland agroecosystems, with nearly 60% of high-density areas overlapping conservation zones. Soil and field conditions, grazing-supporting landscapes, and arable and subsidized agricultural areas emerged as significant predictors of O. cuniculus presence. The observed spatial dependencies indicated that while hotspot intensities and clustering dynamics are influenced by the conditions in neighboring areas, habitat characteristics remain fundamental in shaping their distribution, highlighting the broader landscape-scale spatial patterns affecting rabbit populations. These findings underscore the necessity of adopting spatially informed management strategies that mitigate agricultural impacts while accounting for interconnected spatial dynamics, providing a foundation for informed decision-making to manage rabbit populations while balancing conservation and agricultural priorities.
The Impact of Tertiary Lymphoid Structures on Tumor Prognosis and the Immune Microenvironment in Colorectal Cancer
Authors: Zhao Leyi , Xi Lingze , Liu Yani , Wang Guoliang , Zong Mingtong , Xue Peng , Zhu Shijie
Published: February 2025

Background: Colorectal cancer (CRC) ranks as the third most common cancer worldwide. Tertiary lymphoid structures (TLSs), organized immune cell aggregates in non-lymphoid tissues, are linked to chronic inflammation and tumorigenesis. However, the precise relationship between TLSs and CRC prognosis remains unclear. This study aimed to develop a TLS-associated genetic signature to predict CRC prognosis and support clinical applications. Methods: Utilizing the TCGA database, we analyzed TLS-related gene expression in CRC versus normal tissues. Prognostic models were constructed using Cox and Kaplan-Meier analyses. CRC samples were stratified into high and low TLS groups via ssGSEA, with validation in the GSE75500 dataset. We identified clinical characteristics associated with TLS scores, created prognostic nomograms, analyzed the top 50 differential genes, assessed tumor mutations, estimated immune infiltration using CIBERSORT, and examined correlations between TLS scores and immune checkpoints. Results: A 13-gene TLS-associated prognostic model for CRC was developed, emphasizing immune response genes. Survival analysis indicated significantly better outcomes for the TLS-high group. Cox regression identified stage IV and M1 as independent factors influencing TLS scores. Nomogram analysis demonstrated that combining TLS scores with clinical features enhances prognostic accuracy. TLS scores were closely associated with immune checkpoint genes, suggesting potential immunotherapy benefits for TLS-high patients. Conclusions: This study developed and validated a TLS-based prognostic model for CRC, exploring relevant immune cells. The model holds promise for predicting clinical prognosis and treatment responsiveness in CRC patients.
Correction: Leung et al. Preclinical Identification of Sulfasalazine’s Therapeutic Potential for Suppressing Colorectal Cancer Stemness and Metastasis through Targeting KRAS/MMP7/CD44 Signaling. Biomedicines 2022, 10, 377
Authors: Leung Wai-Hung , Shih Jing-Wen , Chen Jian-Syun , Mokgautsi Ntlotlang , Wei Po-Li , Huang Yan-Jiun
Published: February 2025

In the original publication, there is a mistake in Figure 11B as published [...]