bluuebunny/crossref_metadata_2025 huggingface dataset:
SwinInsSeg: An Improved SOLOv2 Model Using the Swin Transformer and a Multi-Kernel Attention Module for Ship Instance Segmentation
Authors: Sharma Rabi , Saqib Muhammad , Lin Chin-Teng , Blumenstein Michael
Published: January 2025

Maritime surveillance is essential for ensuring security in the complex marine environment. The study presents SwinInsSeg, an instance segmentation model that combines the Swin transformer and a lightweight MKA module to segment ships accurately and efficiently in maritime surveillance. Current models have limitations in segmenting multiscale ships and achieving accurate segmentation boundaries. SwinInsSeg addresses these limitations by identifying ships of various sizes and capturing finer details, including both small and large ships, through the MKA module, which emphasizes important information at different processing stages. Performance evaluations on the MariBoats and ShipInsSeg datasets show that SwinInsSeg outperforms YOLACT, SOLO, and SOLOv2, achieving mask average precision scores of 50.6% and 52.0%, respectively. These results demonstrate SwinInsSeg’s superior capability in segmenting ship instances with improved accuracy.
EEG-Based Emotion Recognition with Combined Fuzzy Inference via Integrating Weighted Fuzzy Rule Inference and Interpolation
Authors: Li Fangyi , Yu Fusheng , Shen Liang , Li Hexi , Yang Xiaonan , Shen Qiang
Published: January 2025

Emotions play a significant role in shaping psychological activities, behaviour, and interpersonal communication. Reflecting this importance, automated emotion classification has become a vital research area in artificial intelligence. Electroencephalogram (EEG)-based emotion recognition is particularly promising due to its high temporal resolution and resistance to manipulation. This study introduces an advanced fuzzy inference algorithm for EEG data-driven emotion recognition, effectively addressing the ambiguity of emotional states. By combining adaptive fuzzy rule generation, feature evaluation, and weighted fuzzy rule interpolation, the proposed approach achieves accurate emotion classification while handling incomplete knowledge. Experimental results demonstrate that the integrated fuzzy system outperforms state-of-the-art techniques, offering improved recognition accuracy and robustness under uncertainty.
A Multi-Robot Collaborative Exploration Method Based on Deep Reinforcement Learning and Knowledge Distillation
Authors: Wang Rui , Lyu Ming , Zhang Jie
Published: January 2025

Multi-robot collaborative autonomous exploration in communication-constrained scenarios is essential in areas such as search and rescue. During the exploration process, the robot teams must minimize the occurrence of redundant scanning of the environment. To this end, we propose to view the robot team as an agent and obtain a policy network that can be centrally executed by training with an improved SAC deep reinforcement learning algorithm. In addition, we transform the obtained policy network into distributed networks that can be adapted to communication-constrained scenarios using knowledge distillation. Our proposed method offers an innovative solution to the decision-making problem for multiple robots. We conducted experiments on our proposed method within simulated environments. The experimental results show the adaptability of our proposed method to various sizes of environments and its superior performance compared to the current mainstream methods.
Alveolar Rhabdomyosarcoma of Nasopharynx and Paranasal Sinuses in Children Diagnosis and Treatment—Review of the Literature and Case Report
Authors: Mârțu Cristian , Tîrnovanu Ștefan Dragoș , Mârțu Ioana , Ferariu Dan , Mârțu Dan , Jităreanu Alexandra , Rădulescu Luminița
Published: January 2025

Alveolar rhabdomyosarcoma (aRMS) is a rare pediatric malignant tumor with a poor prognosis, particularly when located in the rhinopharynx and sphenoidal floor, which complicates diagnosis and increases the risk of misclassification as benign growths. The specific genotype of aRMS is associated with a worse clinical outcome. In young children, especially those aged 4 to 12 years, rhinopharyngeal masses are often attributed to chronic adenoiditis; however, other benign (e.g., angiofibroma in boys) and malignant tumors may also be present. Initial symptoms frequently include nasal obstruction, muco-purulent nasal discharge, serous otitis media, sinusitis, and epistaxis. Rhabdomyosarcoma is the second most common ENT neoplasm in children, following lymphoma, with an incidence of approximately 6 cases per 1,000,000 annually. This report presents the case of an 8-year-old boy diagnosed with aRMS, accompanied by a literature review. Alveolar rhabdomyosarcoma should be suspected in children presenting with a vegetative tumor in the rhinopharynx or paranasal sinuses. Combined treatment approaches (surgery, radiotherapy, and chemotherapy) should be tailored to tumor characteristics. Neuronavigation-guided functional endoscopic sinus surgery (FESS) is an effective option for achieving complete tumor excision, depending on tumor size and extent. The prognosis remains reserved and is contingent upon accurate evaluation and timely intervention. Rigorous follow-up, including endoscopic and imagistic investigation, is crucial for early detection of recurrences, thereby improving treatment outcomes.
Development of a Neuroevolution Machine Learning Potential of Al-Cu-Li Alloys
Authors: Chen Fei , Wang Han , Jiang Yanan , Zhan Lihua , Yang Youliang
Published: January 2025

Al-Li alloys are widely used in aerospace applications due to their high strength, high fracture toughness, and strong resistance to stress corrosion. However, the lack of interatomic potentials has hindered systematic investigations of the relationship between structures and properties. To address this issue, we apply a neural network-based neuroevolutionary machine learning potential (NEP) and use evolutionary strategies to train it for large-scale molecular dynamics (MD) simulations. The results obtained from this potential function are compared with those from Density Functional Theory (DFT) calculations, with training errors of 2.1 meV/atom for energy, 47.4 meV/Å for force, and 14.8 meV/atom for virial, demonstrating high training accuracy. Using this potential, we simulate cluster formation and the high-temperature stability of the T1 phase, with results consistent with previous experimental findings, confirming the accurate predictive capability of this potential. This approach provides a simple and efficient method for predicting atomic motion, offering a promising tool for the thermal treatment of Al-Li alloys.
Comparative Metabolic Analysis of Different Indica Rice Varieties Associated with Seed Storability
Authors: Wu Fangxi , Wei Yidong , Zhu Yongsheng , Luo Xi , He Wei , Wang Yingheng , Cai Qiuhua , Xie Huaan , Xie Guosheng , Zhang Jianfu
Published: January 2025

Seed storability is a crucial agronomic trait and indispensable for the safe storage of rice seeds and grains. Nevertheless, the metabolite mechanisms governing Indica rice seed storability under natural conditions are still poorly understood. Methods: Therefore, the seed storage tolerance of global rice core germplasms stored for two years under natural aging conditions were identified, and two extreme groups with different seed storabilities from the Indica rice group were analyzed using the UPLC-MS/MS metabolomic strategy. Results: Our results proved that the different rice core accessions showed significant variability in storage tolerance, and the metabolite analysis of the two Indica rice pools exhibited different levels of storability. A total of 103 differentially accumulated metabolites (DAMs) between the two pools were obtained, of which 38 were up-regulated and 65 were down-regulated, respectively. Further analysis disclosed that the aging-resistant rice accessions had higher accumulation levels of flavonoids, terpenoids, phenolic acids, organic acids, lignans, and coumarins while exhibiting lower levels of lipids and alkaloids compared to the storage-sensitive rice accessions. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis indicated that several biosynthesis pathways were involved in the observed metabolite differences, including alpha-linolenic acid metabolism, butanoate metabolism, and propanoate metabolism. Notably, inhibition of the linolenic acid metabolic pathway could enhance seed storability. Additionally, increased accumulations of organic acids, such as succinic acid, D-malic acid, and methylmalonic acid, in the butanoate and propanoate metabolisms were identified as a beneficial factor for seed storage. Conclusions: These new findings will deepen our understanding of the underlying mechanisms governing rice storability.
Analytical Solutions for Electroosmotic Flow and Heat Transfer Characteristics of Nanofluids in Circular Cylindrical Microchannels with Slip-Dependent Zeta Potential Considering Thermal Radiative Effects
Authors: Tan Zouqing , Ren Xiangcheng
Published: January 2025

This study analyzes the impact of slip-dependent zeta potential on the heat transfer characteristics of nanofluids in cylindrical microchannels with consideration of thermal radiation effects. An analytical model is developed, accounting for the coupling between surface potential and interfacial slip. The linearized Poisson–Boltzmann equation, along with the momentum and energy conservation equations, is solved analytically to obtain the electrical potential field, velocity field, temperature distribution, and Nusselt number for both slip-dependent (SD) and slip-independent (SI) zeta potentials. Subsequently, the effects of key parameters, including electric double-layer (EDL) thickness, slip length, nanoparticle volume fraction, thermal radiation parameters, and Brinkman number, on the velocity field, temperature field, and Nusselt number are discussed. The results show that the velocity is consistently higher for the SD zeta potential compared to the SI zeta potential. Meanwhile, the temperature for the SD case is higher than that for the SI case at lower Brinkman numbers, particularly for a thinner EDL. However, an inverse trend is observed at higher Brinkman numbers. Similar trends are observed for the Nusselt number under both SD and SI zeta potential conditions at different Brinkman numbers. Furthermore, for a thinner EDL, the differences in flow velocity, temperature, and Nusselt number between the SD and SI conditions are more pronounced.
Synthesis of CF3-Indazoles via Rh(III)-Catalyzed C-H [4+1] Annulation of Azobenzenes with CF3-Imidoyl Sulfoxonium Ylides
Authors: Shang Yilong , Li Chen , Wang Guiqiu , Yao Guiwei , Wu Hongliang , Chen Xun , Zhai Ruirui
Published: January 2025

An efficient Rh(III)-catalyzed C-H activation of azobenzenes and subsequent [4+1] cascade annulation with CF3-imidoyl sulfoxonium ylides was developed, yielding diverse CF3-indazoles. This protocol featured easily available starting materials, excellent functional group tolerance and high efficiency. Moreover, the antitumor activities of selected CF3-indazoles against human cancer cell lines were also studied, and the results indicated that several compounds displayed considerable antiproliferative activities.
Novel Electrochemiluminescence Sensor for Dopamine Detection Based on Perylene Diimide/CuO Nanomaterials
Authors: Tian Qirong , Sun Xinyang , Li Chuan , Shang Lei , Ma Rongna , Li Xiaojian , Jia Liping , He Shuijian , Zhang Qian , Zhang Wei , Wang Huaisheng
Published: January 2025

Dopamine (DA) is an important catecholamine neurotransmitter and its abnormal concentration is closely related to diseases such as hypertension, Parkinson’s disease and schizophrenia. Due to the advantages of high sensitivity and fast response for electrochemiluminescence (ECL), developing ECL sensors for detecting DA was very critical in clinical diagnosis. ECL resonance energy transfer (ECL-RET) was an effective signaling mechanism. However, the shortage of highly efficient ECL-RET pairs impeded the development of DA sensors. Herein, methyl-modified perylene diimide derivative (PDI-CH3) self-assembly nanorod materials as luminophores and CuO nanomaterials as acceptors were integrated into nanocomposites. An obvious ECL-RET was found in PDI-CH3/CuO nanocomposites. After PDI-CH3/CuO nanocomposites were treated with DA, a large increase in ECL intensity was observed. Then, PDI-CH3/CuO nanocomposites were taken as an ECL platform to detect DA. This ECL sensor exhibited a linear response to DA from 10−12 M to 10−8 M with a limit of detection of 0.20 pM. Compared with other sensors for DA detection, the constructed ECL sensor exhibited higher sensitivity. In addition, the novel ECL sensor in this work showed good practicability in a human serum sample.
Pt@ZnCo2O4 Microspheres as Peroxidase Mimics: Enhanced Catalytic Activity and Application for L-Cysteine Detection
Authors: Liao Shuqi , Deng Weisen , Yang Feng , Zhou Jutao , Wu Ling , Yu Donghong , Cao Zhong
Published: January 2025

Compared to natural enzymes, the development of efficient artificial simulated enzymes, such as those based on bimetallic materials with high catalytic activity and good stability, is an important way until now. Herein, we employed ZnCo2O4 microspheres as carriers to synthesize Pt-doped composites with different amounts using a one-pot method. The morphology and structure of the synthesized materials were characterized using XRD, SEM, BET, FT-IR, XPS, and Zeta potential techniques. It was found that Pt0 adhered well to the surface of ZnCo2O4 microspheres, with a 12.5% Pt doped ratio exhibiting abundant oxygen vacancies, excellent substrate affinity, and high peroxidase-like activity. Using fluorescent probes and electrochemical methods, the peroxidase-like catalytic mechanism has been explored that Pt@ZnCo2O4 microspheres can accelerate the electron transfer between H2O2 and 3,3′,5,5′-tetramethylbenzidine (TMB). Based on the optimal loading ratio of 12.5% of Pt@ZnCo2O4, a colorimetric sensor for visual detection of L-cysteine (L-Cys) was constructed, exhibiting a wide linear range of 0.1~50 µM and a low detection limit of 0.0163 µM. The sensor possesses good selectivity, reusability, and usage stability, which can be well applied to the determination of L-Cys in health product capsules with recovery rates of 96.9%~103.7% and RSD of 1.07%~6.50%. This work broadens the application prospects of spinel materials such as ZnCo2O4 in the field of biological analysis and also provides inspiration for the development of new artificial simulated enzymes.
Efficient Synthesis of cis,cis-Muconic Acid by Catechol Oxidation of Ozone in the Presence of a Base
Authors: Katayama Kohtaro , Hotta Hiroki , Tsujino Yoshio
Published: January 2025

Muconic acid, a crucial precursor in synthesizing materials like PET bottles and nylon, is pivotal for the anticipated growth in the textiles and plastics industries. This study presents a novel chemical synthesis route for cis,cis-muconic acid (ccMA) using catechol. Biochemical methods face scale-up challenges due to microorganism sensitivity and complex extraction processes, while chemical methods involve environmentally harmful substances and have low yields. Our research introduces a method that enhances ccMA yield to 56% by employing ozonation in the presence of an alkali, significantly simplifying the synthesis process. This one-step synthesis reduces reagent use and labor, aligns with green chemistry principles, and avoids using toxic chemicals. The methodology, involving the low-temperature ozonation of catechol with base addition, reduces ccMA degradation and improves yield, as confirmed by an HPLC analysis and replicated experiments. This promising approach could lead to sustainable industrial synthesis of muconic acid derivatives. Further investigations will focus on refining this method for larger-scale applications and testing its economic viability, aiming to optimize conditions for maximum efficiency and yield.
Enhancing Communication Networks in the New Era with Artificial Intelligence: Techniques, Applications, and Future Directions
Authors: El-Hajj Mohammed
Published: January 2025

Artificial intelligence (AI) transforms communication networks by enabling more efficient data management, enhanced security, and optimized performance across diverse environments, from dense urban 5G/6G networks to expansive IoT and cloud-based systems. Motivated by the increasing need for reliable, high-speed, and secure connectivity, this study explores key AI applications, including traffic prediction, load balancing, intrusion detection, and self-organizing network capabilities. Through detailed case studies, I illustrate AI’s effectiveness in managing bandwidth in high-density urban networks, securing IoT devices and edge networks, and enhancing security in cloud-based communications through real-time intrusion and anomaly detection. The findings demonstrate AI’s substantial impact on creating adaptive, secure, and efficient communication networks, addressing current and future challenges. Key directions for future work include advancing AI-driven network resilience, refining predictive models, and exploring ethical considerations for AI deployment in network management.
Glial Perturbation in Metal Neurotoxicity: Implications for Brain Disorders
Authors: Ijomone Olayemi K. , Ukwubile Ileje I. , Aneke Vivian O. , Olajide Tobiloba S. , Inyang Happiness O. , Omotosho Omolabake I. , Oyerinde Toheeb O. , Anadu Victor E. , Gbayisomore Tolulope J. , Okeowo Oritoke M. , Oyeniran David A. , Ogundahunsi Olumide A. T. , Ijomone Omamuyovwi M.
Published: January 2025

Overexposure of humans to heavy metals and essential metals poses a significant risk for the development of neurological and neurodevelopmental disorders. The mechanisms through which these metals exert their effects include the generation of reactive oxygen species, mitochondrial dysfunction, activation of inflammatory pathways, and disruption of cellular signaling. The function of glial cells in brain development and in the maintenance of homeostasis cannot be overlooked. The glial cells are particularly susceptible to metal-induced neurotoxicity. Accumulation of metals in the brain promotes microglial activation, triggering inflammatory responses that can coincide with other mechanisms of neurotoxicity, inducing alteration in synaptic transmission, cognitive deficit, and neuronal damage. In this review, we highlighted the role of glial dysfunction in some selected neurodegenerative diseases and neurodevelopmental disorders. We further dive into how exposure to metals such as nickel, manganese, methyl mercury, cadmium, iron, arsenic, and lead affect the functions of the microglia, astrocytes, and oligodendrocytes and the mechanisms through which they exert the effects on the brain in relation to some selected neurodegenerative diseases and neurodevelopmental disorders. Potential therapeutic interventions such as the use of new and improved chelating agents and antioxidant therapies might be a significant approach to alleviating these metal-induced glial perturbations.
Maternal Perception and Childhood Overweight: Examining Parenting Styles and Eating Behaviors Among Preschoolers: A Cross-Sectional Study from Samsun, Türkiye
Authors: Savcı Refia Gözdenur , Yalçın Sıddıka Songül
Published: January 2025

Background: Accurate maternal perceptions of children’s weight status are crucial for early childhood obesity prevention, with evidence suggesting that maternal misperception may delay timely interventions. This study investigated the accuracy of maternal perceptions of child weight and examined associations with parenting styles and children’s eating behaviors and demographic factors among preschool-aged children in Samsun, Türkiye. Methods: This cross-sectional study included 318 mother–child pairs recruited from preschools in socio-economically diverse areas of Samsun. Maternal perceptions of child weight status were assessed using a visual scale, while children’s anthropometric measurements (height, weight) were recorded to calculate BMI-for-age Z-scores. Parenting styles and children’s eating behaviors were evaluated using the Parental Attitude Scale (PAS) and the Children’s Eating Behavior Questionnaire (CEBQ), respectively. Data analysis involved chi-square tests and multiple logistic regression to explore associations between maternal perception accuracy, parenting styles, and children’s eating behaviors. Results: Among 318 mother–child pairs, 59.7% underestimated their child’s weight status, with this figure being 84.9% among overweight children. Authoritative parenting was the most common style (78%); no significant association was found between parenting style and maternal perception accuracy. Accurate estimators showed significantly higher scores for food responsiveness (median: 9 (7–12), p = 0.028) and the enjoyment of food (mean: 16.3 ± 4.8, p = 0.003), whereas underestimators scored higher for satiety responsiveness (mean: 23.2 ± 5.7, p = 0.042) and slowness in eating (mean: 11.2 ± 4.2, p = 0.004). Conclusions: Maternal underestimations of child weight are prevalent, particularly for overweight children, are associated with children’s specific eating behaviors. Targeted educational interventions focusing on improving maternal awareness and promoting responsive feeding practices are essential to combat childhood obesity.
Exploring the Role of Glycine Metabolism in Coronary Artery Disease: Insights from Human Genetics and Mouse Models
Authors: Biswas Subarna , Hilser James R. , Woodward Nicholas C. , Wang Zeneng , Gukasyan Janet , Nemet Ina , Schwartzman William S. , Huang Pin , Han Yi , Fouladian Zachary , Charugundla Sarada , Spencer Neal J. , Pan Calvin , Tang W. H. Wilson , Lusis Aldons J. , Hazen Stanley L. , Hartiala Jaana A. , Allayee Hooman
Published: January 2025

Background: Circulating glycine levels have been associated with reduced risk of coronary artery disease (CAD) in humans but these associations have not been observed in all studies. We evaluated whether the relationship between glycine levels and atherosclerosis was causal using genetic analyses in humans and feeding studies in mice. Methods: Serum glycine levels were evaluated for association with risk of CAD in the UK Biobank. Genetic determinants of glycine levels were identified through a genome-wide association study (GWAS) and used to evaluate the causal relationship between glycine and risk of CAD by Mendelian randomization (MR). A dietary supplementation study was carried out with atherosclerosis-prone apolipoprotein E deficient (ApoE−/−) mice to determine the effects of increased circulating glycine levels on cardiometabolic traits and aortic lesion formation. Results: Among 105,718 UK Biobank subjects, elevated serum glycine levels were associated with significantly reduced risk of prevalent CAD (Quintile 5 vs. Quintile 1 OR = 0.76, 95% CI 0.67–0.87; p < 0.0001) and incident CAD (Quintile 5 vs. Quintile 1 HR = 0.70, 95% CI 0.65–0.77; p < 0.0001) after adjustment for age, sex, ethnicity, anti-hypertensive and lipid-lowering medications, blood pressure, kidney function, and diabetes. A GWAS meta-analysis with 230,947 subjects identified 61 loci for glycine levels, of which 26 were novel. MR analyses provided modest evidence that genetically elevated glycine levels were causally associated with reduced systolic blood pressure and risk of type 2 diabetes, but did not provide significant evidence for an association with decreased risk of CAD. Glycine supplementation in mice had no effects on cardiometabolic traits or atherosclerotic lesion development. Conclusions: While expanding the genetic architecture of glycine metabolism, MR analyses and in vivo feeding studies did not provide evidence that the clinical association of this amino acid with atherosclerosis represents a causal relationship.
Influence of Nursing Time and Staffing on Medication Errors: A Cross-Sectional Analysis of Administrative Data
Authors: Moriwaki Mutsuko , Tanaka Michiko , Kakehashi Masayuki , Koizumi Masato , Horiguchi Hiromasa , Hayashida Kenshi
Published: January 2025

Background: Medication errors cause adverse events; however, studies have yet to examine medication errors related to nursing hours while considering ward characteristics in Japan. Purpose: This study investigated medication errors caused by nurses to quantitatively assess ward activity as busyness in nursing duties. Methods: This study considered patients hospitalized in the general wards of 10 National Hospital Organization institutions between April 2019 and March 2020. The study data were obtained from the Diagnosis Procedure Combination system, incident report system, and reports on nurse staffing and work hours. Data for 27,629 ward days with 88,475 patients were analyzed. Multivariate analysis was performed to determine the impact of factors on medication errors. Results: The mean patient age was 71.43 years (SD = 15.08). The medication error rate in nursing wards was 13.71%. The mean nursing time per patient during day shift was 1.95 h (SD = 0.58) in the non-medication error group and 2.06 h (SD = 0.58) in the medication error group (p < 0.01). The nursing time per patient in the medication error group compared to that in the non-medication error group had an odds ratio of 1.31 (p < 0.01) during day shifts. Conclusions/Implications for practice: Contrary to evidence, the results showed that medication errors caused by nurses related to increased nurse time with patients during day shifts. Further investigation is needed on the relationship of busyness with nursing duties to ensure an adequate nurse–patient ratio, nursing time, and improved patient safety.
Advances in Pure Drug Self-Assembled Nanosystems: A Novel Strategy for Combined Cancer Therapy
Authors: Niu Runyan , Liu Xuexue , Yang Xian , Du Xiao , Wang Siliang , Ma Xiaolong , Yin Shaoping , Shao Lihua , Zhang Jinping
Published: January 2025

Nanoparticle-based drug delivery systems hold great promise for improving the effectiveness of anti-tumor therapies. However, their clinical translation remains hindered by several significant challenges, including intricate preparation processes, limited drug loading capacity, and concerns regarding potential toxicity. In this context, pure drug-assembled nanosystems (PDANSs) have emerged as a promising alternative, attracting extensive research interest due to their simple preparation methods, high drug loading efficiency, and suitability for large-scale industrial production. This innovative approach presents new opportunities to enhance both the safety and therapeutic efficacy of cancer treatments. This review comprehensively explores recent progress in the application of PDANSs for cancer therapy. It begins by detailing the self-assembly mechanisms and fundamental principles underlying PDANS formation. The discussion then advances to strategies for assembling single pure drug nanoparticles, as well as the co-assembly of multiple drugs. Subsequently, the review addresses the therapeutic potential of PDANSs in combination treatment modalities, encompassing diagnostic and therapeutic applications. These include combinations of chemotherapeutic agents, phototherapeutic approaches, the integration of chemotherapy with phototherapy, and the synergistic use of immunotherapy with other treatment methods. Finally, the review highlights the potential of PDANSs in advancing tumor therapy and their prospects for clinical application, providing key insights for future research aimed at optimizing this technology and broadening its utility in cancer treatment.
Pharmacist-Mediated Deprescribing in Long-Term Care Facilities: A Systematic Review
Authors: Gonçalves João Rafael , Magalhães Neuza , Machado Sara , Ramalhinho Isabel , Cavaco Afonso Miguel
Published: January 2025

Multimorbidity and polypharmacy are prevalent among Long-Term Care (LTC) users. Older people, who most use LTC services, are more prone to drug-related problems, which polypharmacy aggravates. Deprescribing is a key intervention to address polypharmacy and inappropriate medication. Evidence shows that pharmacists’ expertise in medicines and their growing involvement in clinical-oriented activities have proven to play an essential role across many healthcare settings, including LTC. Thus, this study aimed to identify and assess LTC pharmacist-mediated deprescribing. A systematic review was undertaken following the PRISMA checklist, using three literature databases (PubMed, Scopus, and Web of Knowledge). A set of 18 keywords, divided into three domains (professional, type of care, and type of setting), were combined into search equations. The studies selected were assessed through the Quality Assessment Tool for Quantitative Studies. Fifteen studies met the inclusion criteria out of 288 initial hits. Pharmacist-mediated deprescribing was divided into specific (targeted to a medicine group) and non-specific. Half of the studies were graded as low quality (53%). In total, the studies enrolled 6928 patients and 45 pharmacists. The ATC groups A, C, M, and N, as well as medicines with anticholinergic properties, were the most addressed medicines groups. Acceptance rates of pharmacists’ recommendations ranged between 30% and 100%. Generically, the number of medicines was reduced after the intervention. Mixed results were found for falls and quality of life outcomes. Cost savings associated with the interventions ranged from neutral to as high as 3800 €/patient/year. Barriers to deprescribing were mainly linked to patients’ or family members’ refusal to change. In conclusion, pharmacist-mediated deprescribing seems feasible in LTC. The studies’ methodological heterogeneity hampers robust comparisons and conclusions. The medicine groups targeted by deprescribing can help tailor interventions to optimize the use of medicines in LTC. A detailed understanding of barriers and enablers to deprescribing would support developing and implementing these interventions.
Machine Learning and Artificial Intelligence Systems Based on the Optical Spectral Analysis in Neuro-Oncology
Authors: Savelieva Tatiana , Romanishkin Igor , Ospanov Anuar , Goryaynov Sergey , Pavlova Galina , Pronin Igor , Loschenov Victor
Published: January 2025

Decision support systems based on machine learning (ML) techniques are already empowering neuro-oncologists. These systems provide comprehensive diagnostics, offer a deeper understanding of diseases, predict outcomes, and assist in customizing treatment plans to individual patient needs. Collectively, these elements represent artificial intelligence (AI) in neuro-oncology. This paper reviews recent studies which apply machine learning algorithms to optical spectroscopy data from central nervous system (CNS) tumors, both ex vivo and in vivo. We first cover general issues such as the physical basis of the optical-spectral methods used in neuro-oncology, and the basic algorithms used in spectral signal preprocessing, feature extraction, data clustering, and supervised classification methods. Then, we review in more detail the methodology and results of applying ML techniques to fluorescence, elastic and inelastic scattering, and IR spectroscopy.
Real-Time Respiratory Monitoring Using a Sparse-Sampled Frequency-Scanning White-Light Interferometry System
Authors: Liu Wenyan , Qian Cheng , Li Kexin , Wang Yiping , Cai Xiaoyan , Liu Qiang
Published: January 2025

Fiber-optic tip sensors offer significant potential in biomedical applications due to their high sensitivity, compact size, and resistance to electromagnetic interference. This study focuses on advancing phase demodulation techniques for ultra-short Fabry–Pérot cavities within limited spectral bandwidths to enhance their application in biomedicine and diagnostics. We propose a novel sparse-sampled white-light interferometry system for respiratory monitoring, utilizing a monolithic integrated semiconductor tunable laser for quasi-continuous frequency scanning across 191.2–196.15 THz at a sampling rate of 5 kHz. A four-step phase-shifting algorithm (PSA) ensures precise phase demodulation, enabling high sensitivity for short-cavity fiber-optic sensors under constrained spectral bandwidth conditions. Humidity sensors fabricated via a self-growing polymerization process further enhance the system’s functionality. The experimental results demonstrate the system’s capability to accurately capture diverse breathing patterns—including normal, rapid, and deep states—with fast response and recovery times. These findings establish the system’s potential for real-time respiratory monitoring in clinical and point-of-care settings.
Genome-Wide Identification and Expression Analysis of Amino Acid/Auxin Permease (AAAP) Genes in Grapes (Vitis vinifera L.) Under Abiotic Stress and During Development
Authors: Guo Xufeng , He Na , Huang Biying , Chen Chongyao , Zhang Yanxia , Yang Xiaoyu , Li Jie , Dong Zhigang
Published: January 2025

Amino acids in wine grapes function as precursors for various secondary metabolites and play a vital role in plant growth, development, and stress resistance. The amino acid/auxin permease (AAAP) genes encode a large family of transporters; however, the identification and function of the AAAP gene family in grapes remain limited. Consequently, we conducted a comprehensive bioinformatics analysis of all AAAP genes in grapes, encompassing genome sequence analysis, conserved protein domain identification, chromosomal localization, phylogenetic relationship analysis, and gene expression profiling. This study identified 60 VvAAAP genes, distributed on 14 chromosomes and classified into eight subfamilies. Microarray and transcriptome data revealed that most VvAAAP genes decrease during development, but VvAAAP7 and VvAAAP33 gradually increase. VvAAAP23 and VvAAAP46 exhibited significantly higher expression levels, while VvAAAP30 demonstrated lower expression when subjected to salt and drought stress. VvAAAP genes exhibited diverse expression patterns, suggesting that the AAAP gene family possesses both diversity and specific functions in grapes. Furthermore, the expression patterns of VvAAAP genes analyzed by RT-qPCR facilitate further investigation into the biological functions of individual genes in different tissues. These findings provide valuable insights into the continued analysis of the AAAP gene family’s functions in grapes.
Chemical Composition, In Vivo, and In Silico Molecular Docking Studies of the Effect of Syzygium aromaticum (Clove) Essential Oil on Ochratoxin A-Induced Acute Neurotoxicity
Authors: Brahmi Mostapha , Adli Djallal Eddine H. , Kaoudj Imane , Alkholifi Faisal K. , Arabi Wafaa , Sohbi Soumia , Ziani Kaddour , Kahloula Khaled , Slimani Miloud , Sweilam Sherouk Hussein
Published: January 2025

The aim of our research was to understand the impact of ochratoxin A (OTA) exposure on various physiological and behavioral aspects in adult Wistar rats, and to evaluate the efficacy of a Syzygium aromaticum essential oil (EOC) treatment in restoring the damage caused by this toxin. The essential oils were extracted by hydrodistillation, a yield of 12.70% was obtained for EOC, and the GC-MS characterization of this essential oil revealed that its principal major components are eugenol (80.95%), eugenyl acetate (10.48%), β-caryophyllene (7.21%), and α-humulene (0.87%). Acute OTA intoxication was induced by an intraperitoneal (IP) injection of 289 µg/kg/b.w. every 48 h for 12 doses, resulting in significant reductions in the body and brain weights of exposed rats when compared with controls. The neurobehavioral analysis using several behavioral testing techniques, such as the forced swimming, the dark/light test, the Morris water maze, and the open field test, clearly revealed that OTA exposure causes neurobehavioral disorders, including decreased locomotor activity, a reduced willingness to explore the environment, reflecting a state of stress, anxiety and depression, as well as impaired memory and learning. In addition, OTA intoxication has been associated with metabolic disturbances such as hyperglycemia and hypercortisolemia. However, treatment with EOC mitigated these adverse effects by improving body and brain weights and restoring neurobehavioral function. The in silico analysis revealed significant affinities between clove oils and two tested esterase enzymes (ACh and BuChE) that were more than or similar to the four neurotransmitters “dopamine, serotonin, norepinephrine, and glutamic acid” and the co-crystallized ligands NAG, MES, and GZ5. These results highlight the therapeutic potential of EOC in combating the toxic effects of OTA and pave the way for future research into the mechanisms of action and therapeutic applications of natural compounds in the prevention and treatment of poison-induced diseases.
Field Investigation of Wave Attenuation in a Mangrove Forest Dominated by Avicennia marina (Forsk.) Viern.
Authors: Wei Xing , Mo Wenyuan , Xiong Lanlan , Hu Xin , Cheng Hao
Published: January 2025

Based on field observation at the north coast of the Zhanjiang Bay in southern China, the characteristics of wave attenuation due to the drag force of one mangrove species, Avicennia marina (Forsk.) Viern., were quantitatively analyzed. The results demonstrated that the mean significant wave height decreased by ~62% within a forest belt up to 80 m due to various bio-physical interactions. Affected by the unique vertical configuration of vegetation, the wave attenuation rate is positively correlated with water depth. The drag force within the forest can be approximated by the function Cd=0.7344e0.1409Am, where Am is the projected area of the submerged obstacle at a certain water depth. The wave attenuation rate and the vegetation density (ρveg) in volume (‰) satisfy the fitting relationship of r=5×10−4·ρveg−3.6×10−3. These findings can accumulate quantitative information for studying the influence of mangrove vegetation on wave attenuation characteristics and provide necessary basic data for modeling studies to investigate the processes contributing to the attenuation capacity of mangroves.
The Roles of MicroRNAs in the Regulation of Rice–Pathogen Interactions
Authors: Jia Yanfeng , Wei Kai , Qin Jiawang , Zhai Wenxue , Li Quanlin , Li Yalan
Published: January 2025

Rice is exposed to attacks by the three most destructive pathogens, Magnaporthe oryzae (M. oryzae), Xanthomonas oryzae pv. oryzae (Xoo), and Rhizoctonia solani (R. solani), which cause substantial yield losses and severely threaten food security. To cope with pathogenic infections, rice has evolved diverse molecular mechanisms to respond to a wide range of pathogens. Among these strategies, plant microRNAs (miRNAs), endogenous single-stranded short non-coding RNA molecules, have emerged as promising candidates in coordinating plant–pathogen interactions. MiRNAs can modulate target gene expression at the post-transcriptional level through mRNA cleavage and/or translational inhibition. In rare instances, they also influence gene expression at the transcriptional level through DNA methylation. In recent years, substantial advancements have been achieved in the investigation of microRNA-mediated molecular mechanisms in rice immunity. Therefore, we attempt to summarize the current advances of immune signaling mechanisms in rice–pathogen interactions that are regulated by osa-miRNAs, including their functions and molecular mechanisms. We also focus on recent findings concerning the role of osa-miRNAs that respond to M. oryzae, Xoo, and R. solani, respectively. These insights enhance our understanding of how the mechanisms of osa-miRNAs mediate rice immunity and may facilitate the development of improved strategies for breeding pathogen-resistant rice varieties.
Potential of a Remotely Piloted Aircraft System with Multispectral and Thermal Sensors to Monitor Vineyard Characteristics for Precision Viticulture
Authors: Lee Leeko , Reynolds Andrew , Dorin Briann , Shemrock Adam
Published: January 2025

Grapevines are subjected to many physiological and environmental stresses that influence their vegetative and reproductive growth. Water stress, cold damage, and pathogen attacks are highly relevant stresses in many grape-growing regions. Precision viticulture can be used to determine and manage the spatial variation in grapevine health within a single vineyard block. Newer technologies such as remotely piloted aircraft systems (RPASs) with remote sensing capabilities can enhance the application of precision viticulture. The use of remote sensing for vineyard variation detection has been extensively investigated; however, there is still a dearth of literature regarding its potential for detecting key stresses such as winter hardiness, water status, and virus infection. The main objective of this research is to examine the performance of modern remote sensing technologies to determine if their application can enhance vineyard management by providing evidence-based stress detection. To accomplish the objective, remotely sensed data such as the normalized difference vegetation index (NDVI) and thermal imaging from RPAS flights were measured from six commercial vineyards in Niagara, ON, along with the manual measurement of key viticultural data including vine water stress, cold stress, vine size, and virus titre. This study verified that the NDVI could be a useful metric to detect variation across vineyards for agriculturally important variables including vine size and soil moisture. The red-edge and near-infrared regions of the electromagnetic reflectance spectra could also have a potential application in detecting virus infection in vineyards.
Evaluating Maize Hybrids for Yield, Stress Tolerance, and Carotenoid Content: Insights into Breeding for Climate Resilience
Authors: Popa Călin , Călugăr Roxana Elena , Varga Andrei , Muntean Edward , Băcilă Ioan , Vana Carmen Daniela , Racz Ionuț , Tritean Nicolae , Berindean Ioana Virginia , Ona Andreea D. , Muntean Leon
Published: January 2025

To ensure food and feed security, modern maize hybrids must not only perform well under changing climate conditions but also consistently achieve higher and stable yields, exhibit maximum tolerance to stress factors, and produce high quality grains. In a study conducted in 2022 and 2023, 50 maize hybrids were developed from crosses of five elite (highly productive) inbred lines and ten lines possessing favorable genes for carotenoid content. These hybrids were tested under particularly unfavorable conditions for maize cultivation. The aim was to identify which lines effectively transmit the desired traits to the offspring (general combining ability—GCA), and to identify superior hybrids in terms of productivity, adaptability, and quality (specific combining ability—SCA). The study revealed that total carotenoids ranged from 2.30 to 40.20 μg/g for the inbred lines and from 7.45 to 25.08 μg/g for hybrids. A wider distribution of values was observed in the inbred lines compared to the hybrids for key carotenoids such as lutein, zeaxanthin, β-cryptoxanthin, and β-carotene. Among the hybrids, notable performers in yield, adaptability, and carotenoid content included E390×D302, A452×D302, and A447×D302. The paternal inbred line D302 exhibited a high general combining ability for yield (1446 kg ha−1) and, when crossed with several inbred lines, produced hybrids with enhanced yields and higher levels of zeaxanthin, lutein, and β-carotene, as well as improved unbroken plants percent.
Evaluating a Soil Amendment for Cadmium Mitigation and Enhanced Nutritional Quality in Faba Bean Genotypes: Implications for Food Safety
Authors: Cheng Liping , Lian Jiapan , Wang Xin , Munir Mehr Ahmed Mujtaba , Huang Xiwei , He Zhenli , Xu Chengjian , Tong Wenbin , Yang Xiaoe
Published: January 2025

Soil amendments combined with low cadmium (Cd)-accumulating crops are commonly used for remediating Cd contamination and ensuring food safety. However, the combined effects of soil amendments and the cultivation of faba beans (Vicia faba L.)—known for their high nutritional quality and low Cd accumulation—in moderately Cd-contaminated soils remain underexplored. This study investigates the impact of a soil amendment (SA) on agronomic traits, seed nutrition, and Cd accumulation in 11 faba bean genotypes grown in acidic soil (1.3 mg·kg−1 Cd, pH 5.39). The SA treatment increased soil pH to 6.0 (an 11.31% increase) and reduced DTPA-Cd by 37.1%. Although the average yield of faba beans decreased marginally by 8.74%, it remained within the 10% national permissible limit. Notably, SA treatment reduced Cd concentration in seeds by 60% and significantly mitigated Mn and Al toxicity. Additionally, SA treatment enhanced levels of essential macronutrients (Ca, Mg, P, S) and micronutrients (Mo, Cu) while lowering Phytate (Phy)/Ca, Phy/Mg, and Phy/P ratios, thus improving mineral nutrient bioavailability. Among the genotypes, F3, F5, and F6 showed the most favorable balance of nutrient quality, and yield following SA application. This study provides valuable insights into the effectiveness of SA for nutrient fortification and Cd contamination mitigation in Cd-contaminated farmland.
Photosynthetic Induction Characteristics in Saplings of Four Sun-Demanding Trees and Shrubs
Authors: Liu Qiuping , Jin Wei , Huang Liying , Wang Danfeng , Xu Kedong , Wei Yunmin
Published: January 2025

Light serves as the unique driving force of photosynthesis in plants, yet its intensity varies over time and space, leading to corresponding changes in the photosynthetic rate. Here, the photosynthetic induction response under constant and fluctuating light was examined in naturally occurring saplings of four sun-demanding woody species, Eucalyptus. Ficus macrocarpa L., Hibiscus syriacus L. and Ficus carica L. We aimed to find out the relations among gas exchange parameter adaptions among different species during photosynthetic induction. The net photosynthetic rates (A) versus time course curves were sigmoidal or hyperbolic after the dark-adapted leaves were irradiated by continuous saturated light. Compared with other species, Ficus carica L. have the largest net photosynthesis rate, stomatal conductance to CO2 (gsc), and the maximum carboxylation rate (Vcmax) at both the initial and steady photosynthetic state. The initial gsc (gsci) was as much as sixfold higher compared to the other shrub, Hibiscus syriacus L. The time required to reach 90% of A (tA90) was 7–30 min; tA90 of Ficus carica L. and Ficus macrocarpa L. were lower than that of the other two species. The time required to reach 90% of gsc (tgsc90) significantly lagged behind tA90 among species. Biochemical induction was fast in leaves of Ficus carica L., as about 4 min were needed to reach 90% of Vcmax, while the other species needed 7–18 min. Correlation analysis showed that the tgsc90 was the main factor in limiting tA90, especially for Eucalyptus spp. and Hibiscus syriacus L.; gsci was negatively correlated with tgsc90 among species. Moreover, time-integrated limitation analysis revealed that gsc still accounted for the largest limitation in constraining A of Eucalyptus spp. and Hibiscus syriacus L. and Ficus macrocarpa L. Overall, the findings suggest that to enhance the carbon gain by woody species under naturally dynamic light environments, attention should be focused on improving the rate of stomatal opening or initial stomatal conductance.