bluuebunny/crossref_metadata_2025 huggingface dataset:
The Laser Processing of the Stainless-Steel Surface Layer of a Heat Exchanger Membrane in Order to Enhance Its Heat Transfer Coefficient
Authors: Kozłowska Ewa Dorota , Szkodo Marek , Muszyński Tomasz , Adamska Paulina
Published: January 2025

Research on temperature regulation is essential for ensuring thermal comfort and optimizing machine performance. Effective cooling systems are critical in industrial processes and everyday electronic devices in order to prevent overheating. Laser-modified heat exchangers can enhance heat dissipation without increasing weight, addressing the need for energy-efficient solutions in the market. The main aim of this experimental research was to establish an efficient method for altering the surface layer of AISI 316L stainless steel with laser pulses and to determine the effectiveness of the laser alterations to the surface layer in the context of intensifying the convective heat transfer. A series of laser-texturing processes was performed on the surface layer of AISI 316L steel using a Nd: YAG pulse laser. Selected samples were subjected to a series of measurements using a recuperator-type heat exchanger. Based on the measurements’ results, the heat transfer coefficients, α, obtained from the modified surfaces were determined. The results were compared with other data from the existing literature and those obtained from unmodified reference samples. The intensification of the convective heat transfer was achieved for 43% of the modifications conducted with a pulsed laser. The highest observed average increase in the heat transfer coefficient, α, was 16.53%. However, the effective intensification of the convective heat transfer, in some cases, was only observed for a certain range of temperatures or flow dynamics parameters.
Sample Tracking Tool: A Comprehensive Approach Based on OpenArray Technology and R Scripting for Genomic Sample Monitoring
Authors: Trastulli Giulia , Calvino Giulia , Papasergi Bruno , Megalizzi Domenica , Peconi Cristina , Zampatti Stefania , Strafella Claudia , Caltagirone Carlo , Giardina Emiliano , Cascella Raffaella
Published: January 2025

Background/Objectives: Centralizing genetic sequencing in specialized facilities is pivotal for reducing the costs associated with diagnostic testing. These centers must be able to verify data quality and ensure sample integrity. This study aims at developing a protocol for tracking NGS-analyzed samples to prevent errors and mix-ups, ensuring proper quality control, accuracy, and reliability in genetic testing procedures. To this purpose, a protocol based on the genotyping of a panel of 60 single-nucleotide polymorphisms (SNPs) by OpenArrayTM technology was employed. Methods: The protocol was initially tested on a cohort of 758 samples and subsequently validated on a cohort of 100 samples. Furthermore, its ability to accurately detect identical and different samples was evaluated through a simulation test conducted on an additional 100 samples. Results: In total, 55 probes achieved a call rate ≥90% and were subjected to the sample matching process performed by an R tool specifically developed. The SNP panel achieved a random match probability of 3.29 × 10−15, proving its suitability for efficiently tracking samples and rapidly identifying any errors or mix-up during the analytical processing. Conclusions: The features of OpenArrayTM technology, cost-effectiveness, rapid analysis, and high discriminative power make it a suitable tool for sample tracking. In conclusion, this method represents a valuable example for promoting laboratory centralization and minimizing the risks related to different laboratory procedures and the management of a high number of samples.
Sensorless Control of PMaSynRM Based on Hybrid Active Flux Observer
Authors: Li Zhiqi , Su Jian , Gao Huizhen , Zhang Erxuan , Kuang Xiaolin , Li Chengrui , Bi Guangdong , Xu Dianguo
Published: January 2025

Permanent Magnet assisted Synchronous Reluctance Motor (PMaSynRM) is widely used in electric vehicles, aerospace and other fields with its high speed range, high cost performance and so on. To improve the rotor position estimation accuracy of active flux observer which only uses voltage model or current model in the existing sensorless control methods of PMaSynRM, this paper proposes a sensorless control method of PMaSynRM based on the hybrid of voltage model and current model. In this paper, the definition of active flux is determined according to the mathematical model of PMaSynRM, and then the active flux observer is constructed. The observer includes voltage model and current model, and the proportional integral controller is added to the observer, and the current model is used as feedback compensation to realize the stable operation of the motor without position sensor. The simulation results show that the active flux observer can realize high position observation accuracy and achieve the stable operation of the PMaSynRM in a wide speed range. The proposed method can effectively improve the system load capacity and anti-interference ability.
Optimization Scheme of Collaborative Intrusion Detection System Based on Blockchain Technology
Authors: Huang Jiachen , Chen Yuling , Wang Xuewei , Ouyang Zhi , Du Nisuo
Published: January 2025

In light of the escalating complexity of the cyber threat environment, the role of Collaborative Intrusion Detection Systems (CIDSs) in reinforcing contemporary cybersecurity defenses is becoming ever more critical. This paper presents a Blockchain-based Collaborative Intrusion Detection Framework (BCIDF), an innovative methodology aimed at enhancing the efficacy of threat detection and information dissemination. To address the issue of alert collisions during data exchange, an Alternating Random Assignment Selection Mechanism (ARASM) is proposed. This mechanism aims to optimize the selection process of domain leader nodes, thereby partitioning traffic and reducing the size of conflict domains. Unlike conventional CIDS approaches that typically rely on independent node-level detection, our framework incorporates a Weighted Random Forest (WRF) ensemble learning algorithm, enabling collaborative detection among nodes and significantly boosting the system’s overall detection capability. The viability of the BCIDF framework has been rigorously assessed through extensive experimentation utilizing the NSL-KDD dataset. The empirical findings indicate that BCIDF outperforms traditional intrusion detection systems in terms of detection precision, offering a robust and highly effective solution within the realm of cybersecurity.
A Novel Field-Programmable Gate Array-Based Self-Sustaining Current Balancing Approach for Silicon Carbide MOSFETs
Authors: Giannopoulos Nektarios , Ioannidis Georgios , Vokas Georgios , Psomopoulos Constantinos S.
Published: January 2025

In medium- and high-power-density applications, silicon carbide (SiC) metal-oxide semiconductor field effect transistors (MOSFETs) are often connected in parallel increasing the current capability. However, the current sharing of paralleled SiC MOSFETs is affected by the mismatched technical parameters of devices and the deviated power circuit parasitic inductances, even if power devices are controlled by a single gate driver. This leads to unevenly distributed power losses causing different stress between SiC MOSFETs. As a result, unbalanced current sharing increases the probability of severe power switch(es) and system failures. For over a decade, the current imbalance issue between parallel-connected SiC MOSFETs has concerned the scientific community, and many methods and techniques have been proposed. However, most of these solutions are impossible to realize without the necessity of screening power devices to measure their technical parameters. Consequently, system costs significantly increase due to the expensive equipment for screening SiC MOSFETs. Also, transient current imbalance is the main concern of most papers, without addressing static imbalance. In this paper, an innovative approach is proposed, capable of suppressing both static and transient current imbalance between paralleled SiC MOSFETs, under both symmetrical and asymmetrical layouts, through an improved active gate driver and without the requirement for any power device screening process. Additionally, the proposed solution employs a self-sustaining algorithmic approach utilizing current sensors and a field-programmable gate array (FPGA). The functionality of the proposed solution is verified through experimental tests, achieving current imbalance suppression between two paralleled SiC MOSFETs, actively and autonomously.
A Semi-Analytical Method for the Identification of DC-Decay Parameters at an Arbitrary Rotor Position in Large Synchronous Machines
Authors: Lai Zhenming , Kang Haoyu , Liu Demin , Wang Zhichao , Yang Yong , Wang Jin
Published: January 2025

Experimental approaches for the identification of dynamic parameters in synchronous machines mainly include two methods, a three-phase sudden short-circuit (TPSSC) test and a standstill frequency response (SSFR) test. However, the former has significant safety risks, while the latter has a complex implementation process, resulting in insufficient adaptability to large-scale units. To overcome the above obstacles, this paper proposes an improved DC-decay test method that can be performed at an arbitrary rotor position so that the rotor pre-positioning process in the conventional DC-decay test can be neglected. Meanwhile, combining the transient analysis theory and particle swarm optimization algorithm, a semi-analytical parameter identification method is proposed. Finally, the proposed method is applied using a 172 MVA large synchronous machine. Compared to the results obtained by the TPSSC test using the Prony algorithm and other conventional type tests, the error of the parameter calculation results obtained with the conventional method reached a maximum of 16.6%, while that of the proposed method was merely 8.6%, and the experimental period could be shortened from 5 days to half a day.
A Dynamic Modeling Approach: Simplifying DFIG Theory, Simulation, and Analysis
Authors: Dal Mehmet , Kennel Ralph M.
Published: January 2025

The operation and modelling of doubly fed induction generators (DFIGs) are quite different in grid-connected and stand-alone operated wind energy conversion systems (WECSs). Researchers usually simulate DFIGs in these operations using the pre-built models provided in commercial software, which are built using complex modeling techniques that most researchers in the field are unfamiliar with. In this paper, a simple and easy-to-use modeling approach based on the basic dynamic voltage equations of an induction machine (IM) is proposed to provide a more physical and practical understanding of the dynamic behavior of DFIGs, considering the difference between stand-alone and grid-connected operations. The basic theory and various dynamic models of DFIGs are reviewed and discussed to clarify the complexity of using alternative reference frame coordinates and various state variables in these models. A generic fifth-order DFIG model that is defined in an arbitrary general reference coordinate frame is considered. It is a flux-based model that allows for change in the parameters of the DFIG online and can be used only for grid-connected operations under control. In addition, this model is expanded to be used for stand-alone operation, but can also be used for grid-connected mode operation. The stand-alone model consists of a hybrid modeling approach and more closely resembles the real structure of a stand-alone DFIG system. The modeling technique used for the stand-alone DFIG provides a practical, non-mathematical way to solve the challenge of defining the dynamic equation of the stator voltage when different sizes and types of loads are connected to the stator. Many technical research problems and critical events that are challenging in DFIG-based WECSs can be studied using the proposed simulation models. As pioneering examples, several effective simulations are carried out, aiming to provide new researchers in this field with a more practical, in-depth, and intuitive understanding of the theory and operating principle of DFIGs in both stand-alone and grid-connected operations. The accuracy of the proposed stand-alone model is demonstrated by comparative simulation tests performed in parallel operation with two other pre-built models with the same conditions and power size. Furthermore, both proposed models are validated by simulating them for two different-sized DFIGs of 15 kW and 2 MW. In addition, a real experiment is conducted for the current controlled operation of a stand-alone DFIG using the introduced small-sized laboratory hardware setup. The results obtained through simulations and experiment are presented and discussed.
Effect of Pitch Angle on Structural and Aerodynamic Characteristics of Vertical-Axis Wind Turbines (VAWTs) Using Leading-Edge Protuberance Blades
Authors: Elangovan Karthikvel , Pillai S. Nadaraja
Published: January 2025

An experimental investigation was carried out to understand the effects of LEP (leading-edge protuberance) blades on the structural characteristics of VAWTs. A series of experiments were performed on VAWTs with straight and LEP blades for a wide range of wind velocity (6 m/s to 20 m/s) and pitch angles (−20° to 20°), and the structural excitations on the VAWT structure were measured using a triaxial accelerometer in each case. The raw acceleration data were extensively processed in the time and frequency domains to identify the variation in structural excitation caused by the unsteady wind and aerodynamic loads on the VAWT structure. Understanding the aerodynamic changes and their impact on structural characteristics is essential. The current study examines how LEP influences the structural excitation of VAWTs. However, a great deal of aerodynamic variation was observed for the LEP blades, so the straight blades of the VAWT were replaced with various modified LEP blades, for which a similar set of experiments was carried out. The study presents a better performance (self-starting, stall-mitigating) for VAWTs with LEP 3 and 2 blades, with a significant reduction in the excitation of loads due to wind load and the changes in aerodynamics observed in the along- and across-wind directions.
Sources of Genetic Variation in Faidherbia albida (Del.) A. Chev. Sub-Saharan African Populations
Authors: Tchatchoua Tchapda Dorothy , Mathieson Iain , Zhebentyayeva Tetyana , Poethig R. Scott , Carlson John E.
Published: January 2025

The adaptation of Faidherbia albida (Del.) A. Chev. to drought conditions, its reverse phenology, ability to improve soil fertility, importance as source of forage, and its medicinal properties make it an excellent tree for Sub-Saharan African communities. However, there has been little effort to develop improved genotypes of F. albida, in part because there is relatively little information about phenotypic and genetic variation within this species. This study’s aim was to characterize the genetic diversity of F. albida among Sub-Saharan natural populations with the goal of identifying material for the improvement of the species in Cameroon and other African countries. We genotyped seven simple sequence repeat (SSR) loci in 267 individuals, 15 populations, and 8 countries in Sub-Saharan Africa representing the range of distribution of F. albida. A total of 32 alleles were identified. The highest level of polymorphism was found in Senegal and Ethiopia. Structure analysis of allelic distributions differentiated the 15 populations into three clusters representing West, East, and South Africa. However, one population in Ethiopia (Rama) was strikingly similar to the West Africa cluster. Genetic diversity decreased from West and East Africa to South Africa. These results support the hypothesis that F. albida originated in West or East Africa and subsequently spread to South Africa. Further sequence-based genotyping of these and additional populations will provide an accurate picture of the origin and subsequent spread of this species and reveal new sources of genetic variation for its improvement.
Quantitative Impacts of Socio-Economic Changes on REDD+ Benefits in Xishuangbanna Rainforests
Authors: Lu Siqi , Lu Heli , Zhang Chuanrong , Miao Changhong , Kizos Thanasis
Published: January 2025

REDD+ is a UN-backed framework aimed at reducing carbon emissions in developing countries through sustainable forest management and the protection and enhancement of forest carbon stocks. These are key goals for the international community to achieve climate change mitigation through forestry. REDD+ programs deliver carbon, environmentally based, and social benefits through incentives provided to local societies. This study focuses on a quantitative assessment of the REDD+ framework from the perspective of localized socio-economic shifts. The drivers–pressures–state–impact and partial least squares–structural equation models were employed to evaluate impacts of socio-economic change on multiple REDD+ benefits and their influential factors in the tropical rainforests of Xishuangbanna, China. The results revealed that land-use changes form essential and complex links between socio-economic and eco-environmental changes. Socio-economic shifts in the recent twenty years in Xishuangbanna impacted carbon emissions mainly through land-use change (impact coefficient = 0.909), which was nearly three times the impact of land-use change on environmental degradation (0.322) and more than twice its impact on social benefits (0.363). Such unbalanced impacts suggest a need to optimize local policies through contextualized measures in a way that effectively addresses livelihood improvements, enhancing carbon storage and environmental services to achieve REDD+ targets in the tropical rainforests of China.
The Grain for Green Program Promotes Soil Organic Matter Accumulation and Improves Soil Fungal Diversity in the Southwestern Karst Region
Authors: Tan Shuhui , Cao Yanqiang , Zhang Zhongfeng , Zhou Longwu , Li Xiangqin
Published: January 2025

Soil microorganisms play pivotal roles in terrestrial ecological processes. However, how soil microbial biomass and community characteristics respond to changes in land utilization in karst regions remains largely unknown. The present study investigated the impacts of land-use change on soil chemical properties, microbial community structure, and biomass in a karst region of southwest China across four land-use types: shrubland (natural vegetation restoration), plantation forest (managed vegetation restoration), orchards, and croplands. Vegetation restoration increased microbial biomass carbon and microbial biomass nitrogen. Shrubland had the highest bacterial and fungal abundance and fungal diversity; in addition, the soil microbial community structure differed significantly among land-use types. The dominant bacterial phyla were Actinobacteria, Proteobacteria, Acidobacteria, and Chloroflexi, whereas Ascomycota was the predominant fungal phylum, with its abundance declining significantly following vegetation restoration. Soil properties, including soil organic matter and available phosphorus, were strongly associated with microbial community composition and diversity in karst areas. The findings of this study are essential for gaining a deeper understanding of how changes in land-use affect soil properties and microbial dynamics, and provide valuable insights for ecological restoration and agricultural management in karst regions.
Novel Development and Sensory Evaluation of Extruded Snacks from Unripe Banana (Musa ABB cv. Kluai ‘Namwa’) and Rice Flour Enriched with Antioxidant-Rich Curcuma longa Microcapsules
Authors: Awaeloh Nurulhusna , Limsuwan Surasak , Na-Phatthalung Pinanong , Kaewmanee Thammarat , Chusri Sasitorn
Published: January 2025

With the growing consumer demand for natural functional ingredients that promote health and well-being while preventing age-related diseases, this study aimed to develop extruded snacks enriched with Curcuma longa (turmeric) microcapsules, recognized for their significant antioxidant properties. Unripe banana flour (Musa ABB cv. Kluai ‘Namwa’) and rice (Oryza sativa) flour were employed as a gluten-free base to create this novel extruded snack. Curcuma longa extract microcapsules were prepared using a spray-drying technique with varying core-to-wall ratios. Antioxidant capacities were assessed through DPPH, ABTS, superoxide radical scavenging, metal chelating, and ferric-reducing assays. The CM6 microcapsules, prepared at 140 °C with a 1:10 core-to-wall ratio, exhibited potent antioxidant activity, with 58.93 ± 3.31% inhibition for DPPH radicals, 87.58 ± 1.33% for ABTS, and 78.41 ± 1.40% for superoxide radicals. Snacks enriched with 0.25% CM6 microcapsules received high consumer acceptance, with an average liking score of 7.5 out of 9. These findings suggest that snacks made with these gluten-free flours and Curcuma longa microcapsules could be novel, convenient, and appealing functional food products that offer an attractive way to deliver antioxidant benefits with high consumer acceptance. Further research on evaluating the active constituents in the snack, its long-term health benefits, and shelf-life stability is recommended for commercialization.
Sex Estimation from the Fibula and Tibia: A Study in Three Portuguese Reference Collections
Authors: Marques Sandra , Pinto Catarina , Ferreira Maria Teresa , Garcia Susana , Curate Francisco
Published: January 2025

Background/Objectives: Sex estimation constitutes an important tool in the process of identifying an anonymous individual in forensic contexts. The bones commonly used in sex estimation are those that exhibit greater sexual dimorphism, such as the pelvis or the femur. However, these bones are not always available, which means that it is necessary to find alternative bones for analysis. The main purposes of this study include the assessment of fibular and tibial sexual dimorphism in samples from three Portuguese reference skeletal collections, and the development of metric models for the estimation of biological sex. Methods: A sample of 290 individuals (160 females; 130 males), belonging to the Coimbra Identified Skeletal Collection (training sample), the Lisbon Identified Skeletal Collection (test sample), and 21st the Century Identified Skeletal Collection (training sample), was employed to develop models for sex prediction through logistic regression. Results: From the identification of the most dimorphic bone dimensions, 13 models were created with an accuracy ranging between 80.1% and 89.7% in the training sample (under cross-validation), and between 82.5% and 91.7% in the test sample Conclusions: The results of this work show that predictive models based on the fibula and tibia can be accurate and unbiased.
Population Genetics of Haliotis discus hannai in China Inferred Through EST-SSR Markers
Authors: Yang Hongsu , Wu Zhou , Ge Guangyu , Sun Xiujun , Wu Biao , Liu Zhihong , Yu Tao , Zheng Yanxin , Zhou Liqing
Published: January 2025

Background/Objectives: The Pacific abalone Haliotis discus hannai originated in cold waters and is an economically important aquaculture shellfish in China. Our goal was to clarify the current status of the genetic structure of Pacific abalone in China. Methods: In this study, eighteen polymorphic EST-SSR loci were successfully developed based on the hemolymph transcriptome data of Pacific abalone, and thirteen highly polymorphic EST-SSR loci were selected for the genetic variation analysis of the six populations collected. Results: The results showed that the average number of observed alleles was 8.0769 (RC)-11.3848 (DQ) in each population. The number of observed alleles in the DQ, NH, and TJ populations was significantly higher than that in the RC population. The cultivated population outside the Changshan Islands has experienced a 22.79% reduction in allele diversity compared to the wild population of DQ. The pairwise Fst values and analysis of molecular variance (AMOVA) revealed significant population differentiation among all populations except DQ and NH populations, with RC and ZZ cultured populations exhibiting the largest population differentiation (Fst = 0.1334). The phylogenetic tree and structural analysis divided the six populations into two groups (group 1: NH, DQ, and ZZ; group 2: DL, TJ, and RC), and there was no relationship between geographical distance and genetic distance. Conclusions: These results may reflect the large-scale culture from different populations in China and the exchange of juveniles between hatcheries. Different breeding conditions have led to a higher degree of genetic differentiation between the RC and ZZ populations. This study enables a better understanding of the genetic diversity and structure of current Pacific abalone populations.
Sickle Cell Anemia and Inflammation: A Review of Stones and Landmarks Paving the Road in the Last 25 Years
Authors: Dorneles Jessica , de Menezes Mayer Amanda , Chies José Artur Bogo
Published: January 2025

A quarter of a century ago, sickle cell disease (SCD) was mainly viewed as a typical genetic disease inherited as a classical Mendelian trait. Therefore, the main focus concerning SCD was on diagnosis, meaning, genotyping, and identification of homozygous and heterozygous individuals carrying the relevant HbS mutant allele. Nowadays, it is well established that sickle cell disease is indeed the result of homozygosis for the HbS variant, although this single feature is not capable of explaining the highly diverse clinical presentation of SCD. In fact, an important feature of SCD is the chronic inflammation that accompanies the sickling of erythrocytes. In this manuscript, we will revisit the early evidence of inflammation in SCD and review what was uncovered during the last 25 years. Here, we describe Sickle cell anemia as a major participant in the history of science. In fact, SCD was the first genetic disease where the causal mutation was identified and is also the first disease for which treatment through genome editing was approved, making this disease a landmark in the road of molecular biology.
Neohesperidin Mitigates High-Fat-Diet-Induced Colitis In Vivo by Modulating Gut Microbiota and Enhancing SCFAs Synthesis
Authors: Lu Kun , Shan Sijie , Zeng Yanling , Yang Guliang
Published: January 2025

Previous research has consistently shown that high-fat diet (HFD) consumption can lead to the development of colonic inflammation. Neohesperidin (NHP), a naturally occurring flavanone glycoside in citrus fruits, has anti-inflammatory properties. However, the efficacy and mechanism of NHP in countering prolonged HFD-induced inflammation remains unclear. In this study, rats on HFD were intragastrically administered (i.g.) with NHP for 12 consecutive weeks. Results indicate that this natural compound is effective in reducing colorectal inflammation at doses of 40–80 mg/kg body weight (BW) by i.g. administration, with significant decreases in inflammation markers such as TNF-α and IL-1β levels. It also improved intestinal mucosal tissue integrity and reduced HFD-stimulated colorectal inflammation via the JAK2/STAT3 pathway. Furthermore, intestinal microbiota sequencing results show that NHP intervention significantly downregulated the Firmicutes/Bacteroidetes ratio. This ratio is closely related to the preventive role in the context of glycolipid metabolism disorder. Compared with fecal cultures of rats from the HFD group, after 48 h in vitro fermentation, those from the NHP group had distinct microbiota composition and notably higher concentrations of SCFAs. Collectively, these observations suggest that 80 mg/kg BW NHP possesses biological activities in downregulating HFD-induced colorectal inflammation by regulating intestinal flora and promoting SCFAs formation.
Pharmacodynamic Mechanisms of Cicadae Periostracum in Parkinson’s Disease: A Metabolomics-Based Study
Authors: Li Mengmeng , Xiong Fuyu , Wu Shifei , Wei Wenlong , Wang Hanze , Qiao Yajun , Guo Dean
Published: January 2025

Cicadae Periostracum (CP) is a traditional Chinese animal-derived medicine with the potential to treat Parkinson’s disease (PD). This study aims to explore the pharmacodynamic mechanisms of CP against PD-based on metabolomics technology and provide a theoretical basis for developing new anti-PD medicine. First, MPP+-induced SH-SY5Y cells were used to evaluate the anti-PD activity of CP. In the animal study, an MPTP-induced PD mouse model was employed to assess CP’s therapeutic effects. Immunofluorescence (IF) staining and Western blotting (WB) were used to evaluate its neuroprotective activity on neurons. A Serum metabolomics analysis was conducted to examine CP’s regulatory effects on metabolites and to identify vital metabolic pathways. Finally, cellular experiments were performed to validate the critical pathways. Cellular activity experiments demonstrated that CP mitigates MPP+-induced SH-SY5Y cytotoxicity, inhibits apoptosis, and restores mitochondrial homeostasis. Animal experiments revealed that CP significantly alleviates dyskinesia in PD mice, enhances motor performance, and restores neuronal integrity while reducing α-synuclein (α-syn) aggregation in the striatum (STR), showing its strong anti-PD effect. Metabolomic analysis revealed that CP can significantly improve the metabolic disorders of ten biomarkers that are mainly involved in amino acid metabolism and fatty acid β-oxidation and are closely related to oxidative stress pathways. Finally, pathway verification was performed, and the results show that CP exerted neuroprotective effects against PD through the dual signaling pathways of Bcl-2/Bax/Caspase-3 and Nrf2/HO-1. This study provides a comprehensive strategy for elucidating the mechanisms by which CP exerts its therapeutic effects against PD, highlighting its potential in developing anti-PD drugs.
Jun, an Oncological Foe or Friend?
Authors: Jafri Zuhayr , Li Yue , Zhang Jingwen , O’Meara Connor H. , Khachigian Levon M.
Published: January 2025

Jun/JUN is a basic leucine zipper (bZIP) protein and a prototypic member of the activator protein-1 (AP-1) family of transcription factors that can act as homo- or heterodimers, interact with DNA elements and co-factors, and regulate gene transcription. Jun is expressed by both immune and inflammatory cells. Jun is traditionally seen as an oncoprotein that regulates processes involved in transformation and oncogenesis in human tumours. This article examines the traditional view that Jun plays a permissive role in cancer development and progression, whilst exploring emerging evidence supporting Jun’s potential to prevent immune cell exhaustion and promote anti-tumour efficacy.
Improving Sentiment Analysis Performance on Imbalanced Moroccan Dialect Datasets Using Resample and Feature Extraction Techniques
Authors: Nassr Zineb , Benabbou Faouzia , Sael Nawal , Hamim Touria
Published: January 2025

Sentiment analysis is a crucial component of text mining and natural language processing (NLP), involving the evaluation and classification of text data based on its emotional tone, typically categorized as positive, negative, or neutral. While significant research has focused on structured languages like English, unstructured languages, such as the Moroccan Dialect (MD), face substantial resource limitations and linguistic challenges, making effective sentiment analysis difficult. This study addresses this gap by exploring the integration of data-balancing techniques with machine learning (ML) methods, specifically investigating the impact of resampling techniques and feature extraction methods, including Term Frequency–Inverse Document Frequency (TF-IDF), Bag of Words (BOW), and N-grams. Through rigorous experimentation, we evaluate the effectiveness of these approaches in enhancing sentiment analysis accuracy for the Moroccan dialect. Our findings demonstrate that strategic resampling, combined with the TF-IDF method, significantly improves classification accuracy and robustness. We also explore the interaction between resampling strategies and feature extraction methods, revealing varying levels of effectiveness across different combinations. Notably, the Support Vector Machine (SVM) classifier, when paired with TF-IDF representation, achieves superior performance, with an accuracy of 90.24% and a precision of 90.34%. These results highlight the importance of tailored resampling techniques, appropriate feature extraction methods, and machine learning optimization in advancing sentiment analysis for under-resourced and dialect-heavy languages like the Moroccan dialect, providing a practical framework for future research and development in NLP for unstructured languages.
Centrality of Hygienic Honey Bee Workers in Colony Social Networks
Authors: Perez Adrian , Johnson Brian R.
Published: January 2025

Many social and environmental variables can affect the interactions among individuals in an insect colony that fundamentally structure its social organization. Along with important attributes such as age and caste, immunity-related factors such as the performance of sanitary tasks or exposure to a pathogen can also influence an individual’s social interactions and their place in the resulting social network. Most work on this subject has supported the hypothesis that health-compromised individuals will exhibit altered social or spatial behavior that presumably limits the spread of infection. Here, we test this hypothesis using honey bee workers recently involved in hygienic behavior, an important set of sanitary tasks in which unhealthy brood are uncapped and then removed from the colony. Using static social networks, we quantify the interaction patterns of workers recently involved in hygienic tasks and compare their network centrality to non-hygienic workers. Using dynamic networks, we analyze the capability of hygienic workers to spread a potential infection throughout the colony. We find no substantial differences in how connected hygienic workers are in the network, and we show that hygienic workers would spread a novel infection throughout the colony to the same extent as non-hygienic workers. Our results suggest that experience with certain sanitary tasks may not necessarily produce rapid changes in social behavior. This work highlights the importance of considering the benefits of remaining socially integrated in important information networks and the temporal limitations for how quickly organized immune responses can occur in response to potential infections.
Cryptoblabes gnidiella Millière (Pyralidae, Phycitinae): An Emerging Grapevine Pest in Greece
Authors: Simoglou Konstantinos B. , Topalidis Iraklis , Avtzis Dimitrios N. , Kaltsidis Achilleas , Roditakis Emmanouil
Published: January 2025

The honeydew moth, Cryptoblabes gnidiella Millière (Lepidoptera: Pyralidae), is native to the Mediterranean Basin. However, it has recently been reported as an emerging grapevine pest in southern European Union countries and in the Middle East, North Africa, and South America. This may be attributed to the global warming trends. In this brief communication, we present the first documented cases of honeydew moth infestation of grapevine in Greece, specifically in two organic vineyards in the Regional Unit of Drama in Northeastern Greece in 2024. Notably, the infestations were limited to the late-ripening grape cultivar ‘Xinomavro’, harvested in October, while other cultivars such as ‘Assyrtiko’, ‘Malagousia’, ‘Cabernet sauvignon’, ‘Sauvignon blanc’, ‘Limniona’, ‘Chardonnay’, and ‘Agiorgitiko’, harvested in late August and early September, showed no signs of infestation. This suggests that the actual impact of C. gnidiella in Greece may be underestimated, as previous late summer infestations of lepidopteran larvae in vineyards were likely misattributed to L. botrana. We discuss the potential implications and concerns regarding the occurrence and management of this pest in Greece.
The Efficacy of the Charlson Comorbidity Index and Its Age-Adjusted Version in Forecasting Mortality and Postoperative Outcomes Following Isolated Coronary Artery Bypass Grafting
Authors: Baris Ozgur , Oksuzler Kizilbay Gozde , Holat Canbolat Mert , Uzturk Mustafa Egemen , Canikoglu Mustafa , Durmaz Aysegul , Omay Oguz , Yavuz Sadan
Published: January 2025

Background/Objectives: The Charlson Comorbidity Index (CCI) is designed for evaluating comorbidities and mortality risks, with the age-adjusted CCI (ACCI) combining age and comorbidity assessments. Despite its long-standing use, research on CCI’s application in cardiac surgery patients is limited. This study assessed the effectiveness of CCI and ACCI in predicting in-hospital mortality and post-surgery outcomes for patients undergoing isolated coronary artery bypass grafting (CABG). Methods: CCI and ACCI scores were derived from medical records between 2016 and 2022. Patient demographics, surgical techniques, and postoperative complications were documented. Results: Totally 393 patients [297 (75.6%) males, 96 (24.4%) females] with an average age of 65 years were included. Median CCI and ACCI scores were 1 (1–2) and 4 (3–5), respectively. In-hospital mortality occurred in 5.9% (n = 23) of cases, with CCI being an independent predictor (OR 1.865, 95% CI 1.117–3.116; p = 0.017). Both CCI and ACCI scores negatively correlated with preoperative EF (%) and positively correlated with ICU and total hospital stay, cardiopulmonary bypass time, and cross-clamp time. ACCI score also positively correlated with extubation time. Patients categorized by CCI comorbidity severity (no comorbidity, mild, moderate, severe) showed a significant increase in postoperative complications with increasing severity, including postoperative VT (p = 0.000), acute renal failure (p = 0.009), pneumonia (p = 0.007), and in-hospital mortality (p = 0.001). Conclusions: Both CCI and ACCI are prognostic indicators for in-hospital mortality in isolated CABG surgery patients, effectively predicting postoperative complications, extended ICU stays, and prolonged hospital stays. Implementing these scoring systems could enhance patient care and improve surgical decision-making.
Spontaneous Chest Wall Hematoma in a Hemodialysis Patient: A Case Report
Authors: Kim Seung-Hyun , Lee Ho-Jun , Kim Dong-Wan , Choi Jun-Ho , Hwang Jae-Ha , Kim Kwang-Seog
Published: January 2025

Background/Objectives: Spontaneous chest wall hematomas are rare but potentially life-threatening complications, particularly in patients with multiple comorbidities such as those undergoing hemodialysis. This case report aims to highlight the significance of early diagnosis and appropriate management in preventing complications associated with this condition. Methods: We report the case of a 79-year-old man with end-stage renal disease on hemodialysis, presenting with a large spontaneous hematoma (18.7 × 13.1 × 9.6 cm) in the right upper chest wall. Initial interventions, including diagnostic imaging and transarterial angiography, did not detect active bleeding. Surgical exploration revealed bleeding from a branch of the lateral thoracic artery, which was managed through vessel ligation and hematoma drainage. Results: The hematoma was successfully managed through surgical intervention, with no postoperative complications such as infection, recurrent bleeding, or wound issues. The patient’s recovery was uneventful, and he was discharged in stable condition. This case underscores the role of microvascular fragility and uremic coagulopathy in the development of spontaneous bleeding in hemodialysis patients. Conclusions: This case emphasizes the importance of timely recognition and individualized management of spontaneous soft tissue bleeding in hemodialysis patients. Surgical intervention is necessary for large hematomas or cases of hemodynamic instability to ensure hemostasis and mitigate complications.
Utility of Artificial Intelligence for Decision Making in Thoracic Multidisciplinary Tumor Boards
Authors: Zabaleta Jon , Aguinagalde Borja , Lopez Iker , Fernandez-Monge Arantza , Lizarbe Jon A. , Mainer Maria , Ferrer-Bonsoms Juan A. , de Assas Mateo
Published: January 2025

Background/Objectives: The aim of this study was to analyze whether the implementation of artificial intelligence (AI), specifically the Natural Language Processing (NLP) branch developed by OpenAI, could help a thoracic multidisciplinary tumor board (MTB) make decisions if provided with all of the patient data presented to the committee and supported by accepted clinical practice guidelines. Methods: This is a retrospective comparative study. The inclusion criteria were defined as all patients who presented at the thoracic MTB with a suspicious or first diagnosis of non-small-cell lung cancer between January 2023 and June 2023. Intervention: GPT 3.5 turbo chat was used, providing the clinical case summary presented in committee proceedings and the latest SEPAR lung cancer treatment guidelines. The application was asked to issue one of the following recommendations: follow-up, surgery, chemotherapy, radiotherapy, or chemoradiotherapy. Statistical analysis: A concordance analysis was performed by measuring the Kappa coefficient to evaluate the consistency between the results of the AI and the committee’s decision. Results: Fifty-two patients were included in the study. The AI had an overall concordance of 76%, with a Kappa index of 0.59 and a consistency and replicability of 92.3% for the patients in whom it recommended surgery (after repeating the cases four times). Conclusions: AI is an interesting tool which could help in decision making in MTBs.
The Role of Stress Hyperglycemia on Delirium Onset
Authors: Lagonigro Ester , Pansini Antonella , Mone Pasquale , Guerra Germano , Komici Klara , Fantini Carlo
Published: January 2025

Delirium is an acute neuropsychiatric syndrome that recognizes one or more underlying causal medical conditions. Stress hyperglycemia usually refers to transient hyperglycemia associated with stress conditions such as stroke, myocardial infarction, and major surgery. Both delirium and stress hyperglycemia share common pathways, such as activation of inflammation. Stress hyperglycemia has been associated with negative outcomes, and recent studies suggested that there is an increased risk of delirium onset in patients with stress hyperglycemia. The purpose of this review is to illustrate the relationship between stress hyperglycemia and delirium. Initially, we illustrate the role of diabetes on delirium onset, summarize the criteria used for the diagnosis of stress hyperglycemia, discuss the impact of stress hyperglycemia on outcome, and focus on the evidence about the relationship between stress hyperglycemia and delirium.
Peripheral Extracellular Vesicles for Diagnosis and Prognosis of Resectable Lung Cancer: The LUCEx Study Protocol
Authors: Rodríguez-Sanz Jorge , Muñoz-González Nadia , Cubero José Pablo , Ordoñez Pablo , Gil Victoria , Langarita Raquel , Ruiz Myriam , Forner Marta , Marín-Oto Marta , Vera Elisabet , Baptista Pedro , Polverino Francesca , Domingo Juan Antonio , García-Tirado Javier , Marin José María , Sanz-Rubio David
Published: January 2025

Background/Objectives: Lung cancer is the primary cause of cancer-related deaths. Most patients are typically diagnosed at advanced stages. Low-dose computed tomography (LDCT) has been proven to reduce lung cancer mortality, but screening programs using LDCT are associated with a high number of false positives and unnecessary thoracotomies. It is therefore imperative that a certain diagnosis is refined, especially in cases of solitary pulmonary nodules that are difficult to technically access for an accurate preoperative diagnosis. Extracellular vesicles (EVs) involved in intercellular communication may be an innovative biomarker for diagnosis and therapeutic strategies in lung cancer, regarding their ability to carry tumor-specific cargo. The aim of the LUCEx study is to determine if extracellular vesicle cargoes from both lung tissue and blood could provide complementary information to screen lung cancer patients and enable personalized follow-up after the surgery. Methods: The LUCEx study is a prospective study aiming to recruit 600 patients with lung cancer and 50 control subjects (false positives) undergoing surgery after diagnostic imaging for suspected pulmonary nodules using computed tomography (CT) scans. These patients will undergo curative surgery at the Department of Thoracic Surgery of the Miguel Servet Hospital in Zaragoza, Spain, and will be followed-up for at least 5 years. At baseline, samples from both tumor distal lung tissue and preoperative peripheral blood will be collected and processed to compare the quantity and content of EVs, particularly their micro-RNA (miRNA) cargo. At the third and fifth years of follow-up, CT scans, functional respiratory tests, and blood extractions will be performed. Discussion: Extracellular vesicles and their miRNA have emerged as promising tools for the diagnosis and prognosis of several diseases, including cancer. The LUCEx study, based on an observational clinical cohort, aims to understand the role of these vesicles and their translational potential as complementary tools for imaging diagnosis and prognosis.
The Triad of Risk: Linking MASLD, Cardiovascular Disease and Type 2 Diabetes; From Pathophysiology to Treatment
Authors: Michalopoulou Eleni , Thymis John , Lampsas Stamatios , Pavlidis George , Katogiannis Konstantinos , Vlachomitros Dimitrios , Katsanaki Eleni , Kostelli Gavriella , Pililis Sotirios , Pliouta Loukia , Kountouri Aikaterini , Papanikolaou Ioannis S. , Lambadiari Vaia , Ikonomidis Ignatios
Published: January 2025

Metabolic dysfunction-associated steatotic liver disease (MASLD) is an emerging global health concern, and it is not only the keystone precursor of eventual liver-related morbidity, but it also places patients at considerably higher cardiovascular risk, which is still a leading cause of death in these patients. The most important common underlying pathophysiological mechanisms in these diseases are primarily related to insulin resistance, chronic inflammation and oxidative stress. The presence of MASLD with cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM) elevates the risk for poor outcomes, thus this review highlights a method to the therapeutic approaches. Given the intertwined nature of MASLD, T2DM, and CVD, there is an urgent need for therapeutic strategies that address all three conditions. Although lifestyle changes are important as treatment, medication plays a crucial role in managing hyperglycemia, enhancing liver function and lowering cardiovascular risk. The onset and progression of MASLD should be addressed through a multifaceted therapeutic approach, targeting inflammatory, immune, metabolic, oxidative stress, hormonal and gutaxis pathways, alongside the treatment strategies for T2DM. In this review, we discuss the effects of antidiabetic drugs with an impact on both liver outcomes and cardiovascular risk in patients affected by MASLD, T2DM and CDV.