bluuebunny/crossref_metadata_2025 huggingface dataset:
Parameter Optimization Study of Adaptive Spiral Profiling Automatic Rubber Cutter for Natural Rubber Trees
Authors: Zhang Heng , Zhang Guohai , Li Yuan , Zhang Lina
Published: February 2025

Long-term tracking tests revealed that the adaptive spiral profiling automatic rubber cutter is prone to “knife off” and “knife jumping” states during the cutting process. These issues result in inconsistent skin thickness and poor cutting surface uniformity and can even damage natural rubber trees, leading to reduced yield, disease, and potentially death. This paper presents experimental research on the parameters affecting the performance of the adaptive spiral profiling automatic rubber cutter. It explores the impact of key parameters on cutter performance and establishes a mathematical model relating these parameters to the peel thickness and cutting surface uniformity rates. Through multi-objective parameter optimization, the optimal parameter combination was determined: a cutting speed of 15 s/knife, a blade thickness of 0.50 mm, and a bending angle of 27.5°. In six tests, the average peel thickness and cutting surface uniformity rates were 97.5% and 96.5%, respectively. These results meet national standards, suggesting that the optimized parameters significantly improve the rubber cutter’s performance. The results meet national standards, demonstrating that the optimized parameters improve the peel thickness and cutting surface uniformity. The regression model is reliable and provides a foundation for selecting better parameter combinations for future prototypes.
IoV and Blockchain for Traffic Optimization in Ro-Ro Terminals: A Case Study in the Spanish Port System
Authors: González-Cancelas Nicoletta , Vaca-Cabrero Javier , Camarero-Orive Alberto
Published: February 2025

This study examines the integration of the Internet of Vehicles (IoV) and blockchain as tools to optimize traffic management in Roll-on/Roll-off (Ro-Ro) terminals within the Spanish port system. Faced with increasing operational complexity, these technologies present innovative solutions to enhance efficiency, reduce waiting times, and ensure transparency in data management. The methodology follows five main phases: analysis of the current scenario, establishment of a baseline, calculations to evaluate key outcomes, analysis of blockchain implementation, and discussion of results. Key variables include waiting times, vehicular flow, CO2 emissions, and operational costs, comparing manual and automated scenarios. The findings reveal that the combined use of IoV and blockchain can increase vehicular flow by up to 70%, reduce waiting times by 2.56 min, and decrease CO2 emissions by 57.74 kg per hour. Additionally, automation significantly reduces operational costs, yielding average savings of over EUR 500 per hour. This study concludes that adopting these technologies transforms port operations by fostering sustainability, efficiency, and safety. However, challenges remain, including high initial implementation costs and system interoperability issues. This work underscores the need for strategic approaches to overcome these barriers and positions Spanish ports as potential leaders in logistics innovation, aligning with global demands for sustainable, efficient, and transparent port operations.
Assessment of over Four Decades the Status of White Grouper Epinephelus aeneus (Geoffroy Saint-Hilaire, 1817) Population in the Eastern Central Atlantic
Authors: Meissa Beyah , Quemper Florian , Thiaw Modou , Ba Kamarel , Tfeil Brahim Mohamed , Jallow Momodou S. , Guitton Jérome , Sharma Rishi , Gascuel Didier
Published: February 2025

Senegalese and Mauritanian fisheries exploit the same species of white grouper but have different exploitation histories. In Senegal, white grouper has been fished for a very long time (since the 1970s), whereas it is relatively recent in Mauritania. In addition, Senegalese small-scale fishermen exploit this species in the Gambia. Nevertheless, mainly for practical reasons, all attempts to assess the status of the stock have, until recently, been conducted at a national level except by the FAO CECAF North working group who assumed it to be a single stock for the three countries. However, their analysis gives very little attention to length frequency data, even though the fisheries have different selectivity that are likely to affect exploitation rates. In addition, management is mainly focused on length, with no TACs or quotas established at national or sub-regional levels. This work is based on a large compilation of available data from the databases of three countries complemented by the collection of length frequencies data within the framework of the European Union Demerstem/PESCAO project. Two approaches were combined (catch and length-based model) to establish a reliable diagnosis of the state of this resource, along with a spatial analysis to identify the areas most affected by fishing. The results obtained for the sub-region show a severe overexploitation of biomass revealed by the Bayesian biomass production surplus model (JABBA). Stock status indicators show overfishing with low biomass (B/Bmsy = 0.34) and high fishing mortality (F/Fmsy = 5.79). Overall, the trajectory of the state of the stock illustrated by the Kobe figure indicates that the white grouper stock has been overexploited since the 1990s. Fishing pressure reached its highest levels during the recent period of 2016–2018 and these results are consistent when considering stock assessment at the national level. However, the length-based model (LBB) indicates a deterioration in average length, particularly in Senegal and the Gambia, especially since 2014. Adults, who migrate, are more abundant in Mauritania. Therefore, due to its high market value, white grouper is increasingly targeted, resulting in an unprecedented rise in fishing mortality over the past decade, particularly among larger individuals, with the most significant pressure observed in Senegal and the Gambia. Given that the stock spans three countries, a coordinated management approach at the stock level is essential. However, management measures must also be adapted to the specific status of the population within each country. Without such a concerted effort, this trend is likely to persist, further endangering the resource.
Improving Temperature Adaptation for Food Safety: Colorimetric Nanoparticle-Based Time–Temperature Indicators (TTIs) to Detect Cumulative Temperature Disturbances
Authors: Lanza Gustavo , Perez-Taborda Jaime Andres , Avila Alba
Published: February 2025

The global commitment to ending hunger by 2030 has driven Colombia to align its Sustainable Development Goals (SDGs) toward reducing food waste and ensuring access to safe, nutritious food. A critical need is monitoring cumulative temperatures across food supply networks, prioritizing products over transport or storage infrastructure. This study introduces a Functional Time–Temperature Indicator (TTI) using nanodispersions of silver (Ag) and gold (Au) nanoparticles housed in 3D-printed plant-based resin containers. Nanoparticles were synthesized via three methods: in situ reduction (AgNPs), seed-based thermal synthesis (AgTNPs), and pulsed laser ablation in liquid (AuNPs). The TTIs operate through three colorimetric mechanisms: NP concentration, geometry changes, and agglomeration. At 4 °C, AgNPs and AgTNPs maintained stable color, while at 22 °C, they exhibited significant changes, with AgNPs reaching 252% variation within 5 h. AuNPs responded at lower temperatures, showing up to 27% variation. Containers enabled effective nanodispersion incorporation due to their thermal and optical properties. AgTNP-based TTIs demonstrated the most noticeable changes at 22 °C, with a total color difference (ΔE) of 39.9, easily detectable by observers. These TTIs provide robust solutions for continuous cold chain monitoring, enhancing food safety and preserving quality throughout the supply chain.
Overview of Glycometabolism of Lactic Acid Bacteria During Freeze-Drying: Changes, Influencing Factors, and Application Strategies
Authors: Noufeu Tchouli , Li Yueqin , Toure Ndeye Fatou , Yao Hui , Zeng Xiaoqun , Du Qiwei , Pan Daodong
Published: February 2025

Lactic acid bacteria (LAB) play a vital role in food fermentation and probiotics microeconomics. Freeze-drying (FD) is a commonly used method for preserving LAB powder to extend its shelf life. However, FD induces thermal, osmotic, and mechanical stresses that can impact the glycometabolism of LAB, which is the process of converting carbohydrates into energy. This review explores the effect of FD on glycometabolism, factors influencing glycometabolism, and feasible strategies in the FD process of LAB. During the three stages of FD, freezing, primary drying or sublimation, and second drying, the glycolytic activity of LAB is disrupted in the freezing stage; further, the function of glycolytic enzymes such as hexokinase, phosphofructokinase, and pyruvate kinase is hindered, and adenosine triphosphate (ATP) production drops significantly in the sublimation stage; these enzyme activities and ATP production nearly cease and exopolysaccharide (EPS) synthesis alters during the secondary drying stage. Factors such as strain variations, pretreatment techniques, growth medium components, FD parameters, and water activity influence these changes. To counteract the effects of FD on LAB glycometabolism, strategies like cryoprotectants, encapsulation, and genetic engineering can help preserve their glycometabolic activity. These methods protect LAB from harsh FD conditions, safeguarding glycolytic flux and enzymatic processes involved in carbohydrate metabolism. A deeper understanding of these glycometabolic changes is essential for optimizing FD processes and enhancing the use of LAB in food, medicine, and biotechnology, ultimately improving their performance upon rehydration.
Development of a Sensitive Enzyme Immunoassay Using Phage-Displayed Antigen-Binding Fragments for Zearalenone Detection in Cereal Samples
Authors: Chen Ying , Liu Xinmiao , Li Jiao , Liu Xing
Published: February 2025

Zearalenone (ZEN), a non-steroidal estrogenic mycotoxin, contaminates animal feed and grain crops, thereby entering the food chain and posing a significant threat to human health. Consequently, there is an urgent need for a sensitive and rapid method for detecting trace levels of ZEN. In this study, we developed a phage-displayed antigen-binding fragment (Fab-phage) and established a Fab-phage-based enzyme-linked immunosorbent assay (Fab-pELISA) for ZEN detection. Under optimal conditions, this method exhibits a half-maximal inhibitory concentration of 0.36 ng/mL, with a linear range from 0.07 to 3.89 ng/mL and a detection limit of 0.03 ng/mL. The method demonstrates high selectivity towards ZEN and good recovery rates of 97.35–122.66% with relative standard deviations not exceeding 3.5%. Furthermore, the detection results obtained using Fab-pELISA on real cereal samples are consistent with those from high-performance liquid chromatography, meeting practical application requirements. Therefore, the Fab-phage serves as a valuable biochemical reagent, and the established Fab-pELISA represents a promising analytical strategy for detecting ZEN and other trace toxic contaminants in cereals.
Structure and Functional Properties of Proteins from Different Soybean Varieties as Affected by the 11S/7S Globulin Ratio
Authors: Hou Yichen , Huang Lu , Xing Guangliang , Yuan Xiaotian , Zhang Xiaoyan , Dai Dongqing , Yuan Xingxing , Chen Xin , Xue Chenchen
Published: February 2025

Soybean (Glycine max (L.) Merrill) is a key source of plant protein, with 7S and 11S globulins being the primary fractions. This study investigated the protein content, protein composition, and 11S/7S globulin ratios of 411 soybean samples, and then selected six varieties (S1, S2, S3, S4, S5, and S6) for the analysis of the protein structures and functional properties. The results revealed that varieties with low 11S/7S ratios (S1, S2, and S3) exhibited relatively high random coil contents (20.11–22.94%) and lower β-sheet contents (34.17–38.37%), suggesting the presence of more loosely structured proteins. S2 showed good solubility (73.21%) and water-holding capacity (WHC) (2.73 g/g), which can improve product quality and yield. In contrast, varieties with high 11S/7S ratios (S4, S5, and S6) demonstrated more compact protein structures, increased surface hydrophobicity, larger particle sizes, lower absolute zeta potential values, and greater oil-holding capacity (OHC) values (7.58–8.48 g/g). S4, in particular, demonstrated superior emulsification properties, with emulsion activity index (EAI) (4.71 m2/g) and emulsion stability index (ESI) (58.73 min), which are widely used in the food industry such as in cake, ice cream, and bread. This study provides valuable information for the selection of soybean varieties with optimal 11S/7S ratios for processing soybean products.
Special Issue: “Advances in Sources, Extraction, Encapsulation, Bioavailability, and Health Benefits of Functional Food Ingredientsts”
Authors: Vadalà Rossella , Costa Rosaria , Cicero Nicola
Published: February 2025

The Special Issue “Advances in Sources, Extraction, Encapsulation, Bioavailability, and Health Benefits of Functional Food Ingredients” reaches its conclusion, having successfully compiled a collection of nine articles [...]
β-Ionone Treatment Enhances the Antioxidant Capacity in Postharvest Broccoli (Brassica oleracea L. var. Italica) by Maintaining the Levels of Bioactive Substances
Authors: Zhang Feng , Cao Mengze , Shen Letong , Shi Liyu , Chen Wei , Yang Zhenfeng
Published: February 2025

Broccoli is prone to nutrient loss during postharvest storage due to its high respiratory metabolism. In this study, we investigated the effects of 0.1 mm β-ionone on bioactive substances and antioxidant capacity during postharvest storage of broccoli. We found that the decline in the scavenging rates of 1,1-diphenyl-2-picrylhydrazyl and 2,2′-azinobis-(3-ethylbenzthiazoline-6-sulphonate) radicals was delayed in the treated florets. This delay is attributed to β-ionone treatment, which upregulated the expression of biosynthetic genes related to glucosinolates and riboflavin in broccoli, thereby slowing the loss of these nutrients. Additionally, β-ionone treatment increased the transcript levels of anabolic genes while reducing the expression of genes encoding enzymes involved in the catabolism of ascorbic acid (AsA) and glutathione (GSH), resulting in higher levels of AsA and GSH in treated broccoli compared to the control. Overall, β-ionone treatment enhanced antioxidant capacity by delaying the loss of bioactive substances in postharvest broccoli. These findings provide the first evidence that exogenous β-ionone helps preserve antioxidant capacity in postharvest horticultural products.
Analysis of Differences in Volatile Components of Rucheng Baimao (Camellia pubescens) Black Tea in Different Seasons
Authors: Zhu Junye , Zhou Yuebin , Wen Haitao
Published: February 2025

At present, there are few studies on seasonal differences in the aroma quality and volatile components of Rucheng Baimao (Camellia pubescens) black tea. In this study, sensory evaluation and volatile component analysis were carried out on one sample of Rucheng Baimao black tea corresponding to spring, summer, and autumn, respectively. The results of sensory evaluation showed that the black teas of all three seasons had floral aromas. However, the aroma quality of spring black tea was the best, followed by that of autumn black tea, and summer black tea was the worst. The analysis of volatile components showed that alcohols, esters, and alkanes were the main substance categories. In addition, the results of the aroma index were consistent with those of the sensory evaluation, indicating that spring black tea had the best aroma quality, followed by autumn black tea and then summer black tea. Eleven key differential volatile components were screened by combining PLS-DA analysis (VIP > 1, p < 0.05) and rOAV > 1. Among them, geraniol, methyl salicylate, nonanal, and (E)-citral accumulated the most in spring black tea, linalool, phenylacetaldehyde, benzaldehyde, phenethyl alcohol, benzyl alcohol, and β-ionone accumulated the most in summer black tea, and trans-nerolidol accumulated the most in autumn black tea. This study aims to provide a theoretical reference for the regulation of the aroma quality of Rucheng Baimao black tea.
Recent Advances in Processing-Induced Changes in the Structure, Techno-Functional Properties and Nutritional Quality of Animal- and Plant-Based Food Proteins
Authors: Li Ruifen , Raak Norbert , Roman Laura
Published: February 2025

Proteins are essential macronutrients in the human diet and key structural constituents of many food products [...]
Deoxynivalenol and Alternaria Toxin Exposure and Health Effects Assessment of Pregnant Shanghai Women
Authors: Li Kailin , Luo Baozhang , Cai Hua , Qi Renjie , Zhu Zhenni , He Yi , Wu Aibo , Liu Hong
Published: February 2025

Deoxynivalenol (DON) and Alternaria toxins (ATs) are two common types of mycotoxins in food. Although they are physiologically toxic to animals and various cell lines, data related to the exposure risks and health effects in the human population were still limited, especially for ATs. In this study, we combined food consumption data and human biomonitoring data of 200 pregnant volunteers from different districts of Shanghai to assess the exposure to DON and ATs. In addition, correlations between food consumption and urinary DON and ATs levels, urine biomarkers, and blood indexes were analyzed by regression analysis. For DON, the exposure assessment of the probable daily intake (PDI) indicated that a portion (37.5%) of all participants exceeded the Tolerable Daily Intake (TDI) proposed for DON. For ATs, the PDI values estimated based on the urinary concentrations indicated that 2–100% of all participants exceeded the threshold of toxicological concern (TTC) values for ATs. In addition, we innovatively found some associations between exposure to ATs and abnormal uric acid and high-density lipoprotein cholesterol indexes by regression analysis. Despite the inevitable uncertainties, these results make an important contribution to the understanding of DON and ATs exposure risks and potential health hazards in the pregnant women population.
Rapeseed and Palm Oils Can Improve the Growth, Muscle Texture, Fatty Acids and Volatiles of Marine Teleost Golden Pompano Fed Low Fish Oil Diets
Authors: Chen Fang , Lou Yunkun , Guan Junfeng , Lan Xue , Su Zeliang , Xu Chao , Li Yuanyou , Xie Dizhi
Published: February 2025

This study evaluated the effects of different lipid sources—fish oil (FO), soybean oil, rapeseed oil, and palm oil—on the growth and muscle quality of golden pompano (Trachinotus ovatus) cultured in offshore cages for 10 weeks. Three diets (D1–D3) were formulated: D1 used only fish oil, D2 blended fish, rapeseed oil, and palm oil, and D3 combined fish and soybean oils. Fish in the D1 group showed the highest weight gain, specific growth rate, and muscle protein content, significantly outperforming D3. No significant differences in muscle lipid content or edible quality were found between groups. D1 had the highest levels of long-chain and n-3 polyunsaturated fatty acids (PUFA), while D3 had higher n-6 PUFA. Saturated and monounsaturated fatty acids were higher in D1 and D2 than in D3. Muscle volatiles like aldehydes and amines were elevated in D1, with more pleasant flavors compared to D2 and D3. Muscle texture was superior in D2. These results suggest that rapeseed and palm oils can enhance growth, flavor, and texture in fish on low FO diets, offering a sustainable alternative to reduce reliance on marine-based feed in aquaculture.
Synergistic Bactericidal Efficiency of Slightly Acidic Electrolyzed Water–High-Pressure Parallel Processing on Escherichia coli in Freshly Cut Gastrodia elata Slices
Authors: Gao Qing , Nong Xin , Lang Tuanjian , Liu Yajin , Ye Shuxin , He Jinsong
Published: February 2025

The synergistic enhancement of bactericidal efficiencies on freshly cut Gastrodia elata slices by parallel processing using slightly acidic electrolyzed water (SAEW) and high-pressure (HP) technology was comprehensively investigated in this study. To this end, appropriate experimental conditions were determined through single-factor tests, which were ACCs (available chlorine concentrations) of 30, 38, and 49 mg/L; pressures of 100, 150, and 200 MPa; treatment times of 5, 7.5, and 10 min; and material-to-liquid ratios of 1:1, 1:3, and 1:5. Under these conditions, single and parallel bactericidal tests were conducted, and the corresponding synergistic enhancement values ΔI were calculated. Subsequently, using the lethal rate of Escherichia coli (E. coli) as the response value, we fitted multiple quadratic regression equations for SAEW, HP, and SAEW–HP with respect to ACC, pressure, pressure application time, and material-to-liquid ratio. The multiple quadratic regression equation for the synergistic enhancement term ΔI was then obtained through calculation. By analyzing this equation, the synergistic enhancement range was determined. Finally, experimental points were randomly selected within the synergistic enhancement range for validation. The results demonstrate that there was a synergistic bactericidal efficiency of the SAEW–HP parallel treatment of freshly cut G. elata slices. The synergistic enhancement range was pressure (xp) ∈ [52.18, 359.58] MPa; concentration of available chlorine (xc) ∈ [28.71, 46.27] mg/L; time (xt) ∈ [2.34, 12.38] min; and the material-to-solvent ratio (xr) ∈ ø g/mL. The validation experiments confirmed that within the respective ranges of p, c, and t, the SAEW–HP parallel treatment of freshly cut G. elata slices exhibited a ‘1 + 1 > 2’ synergistic enhancement effect. These findings lay a theoretical foundation for the development of green bactericidal technologies for “adopting both minimum processing and dosage to achieve the optimal effect”.
Stat-Space Approach to Three-Dimensional Thermoelastic Half-Space Based on Fractional Order Heat Conduction and Variable Thermal Conductivity Under Moor–Gibson–Thompson Theorem
Authors: Youssef Hamdy M.
Published: February 2025

This study presents a mathematical model of a three-dimensional thermoelastic half-space with variable thermal conductivity under the definition of fractional order heat conduction based on the Moor–Gibson–Thompson theorem. The non-dimensional governing equations using Laplace and double Fourier transform methods have been applied to a three-dimensional thermoelastic, isotropic, and homogeneous half-space exposed to a rectangular thermal loading pulse with a traction-free surface. The double Fourier transforms and Laplace transform inversions have been computed numerically. The numerical distributions of temperature increment, invariant stress, and invariant strain have been shown and analysed. The fractional order parameter and the variability of thermal conductivity significantly influence all examined functions and the behaviours of the thermomechanical waves. Classifying thermal conductivity as weak, normal, and strong is crucial and closely corresponds to the actual behaviour of the thermal conductivity of thermoelastic materials.
Fossil or Non-Fossil: A Case Study in the Archaeological Wheat Triticum parvicoccum (Poaceae: Triticeae)
Authors: Rivera Diego , Ferrer-Gallego P. Pablo , Obón Concepción , Alcaraz Francisco , Laguna Emilio , Goncharov Nikolay P. , Kislev Mordechai
Published: February 2025

Background/Objectives: The archaeobotanical taxon “Triticum parvicoccum” was first described in 1980 as a small-grained, naked, free-threshing, and dense ear tetraploid wheat species (2n = 4x = 28) identified from archaeological remains. This primitive tetraploid, cultivated in the Levant approximately 9000 years ago and subsequently dispersed throughout the Fertile Crescent, represents a potential contributor of the BBAA genomes to T. aestivum. This study aims to resolve the complex nomenclatural status of this taxon, which has remained ambiguous due to competing interpretations under fossil and non-fossil taxonomic regulations. Methods: We conducted a comprehensive nomenclatural review to evaluate the taxonomic validity of T. parvicoccum, analyzing previous research on the classification of archaeobotanical materials in relation to fossil status. Results: Our analysis demonstrated that archaeobotanical materials do not qualify as fossils and led to the validation of the taxon at a subspecific rank as a non-fossil entity: T. turgidum subsp. parvicoccum Kislev. subsp. nov. The holotype was established using a charred rachis fragment from Timnah (Tel Batash), an archaeological site on the inner Coastal Plain (Shfela) adjacent to the western piedmont of the Judean Mountains, Israel. Conclusions: This study resolves the longstanding nomenclatural uncertainty surrounding this archaeologically significant wheat taxon, providing a valid taxonomic designation that reflects its biological and historical importance while adhering to current botanical nomenclature standards.
Phylogeny and Specific Determination of Gloydius halys-intermedius Complex Based on Complete Mitochondrial Genes
Authors: Jin Lijie , Xia Zuyao , Liu Ning , Hou Shengyue , Lv Chuandong , Tang Lianyou , Feng Shuguang , Shi Jingsong , Bai Ming
Published: February 2025

Background: The phylogenetic resolution within the Gloydius halys-intermedius Complex remains debatable due to the following reasons: loci selection in previous studies varied between authors; limited dataset (1−5 mitochondrial or nuclear gene fragments); lack of sampling density; and nodal supports at specific nodes remain weak, specifically within Gloydius cognatus, G. halys, and G. stejnegeri. Objectives: To revise the taxonomic and phylogenetic relationships within the G. halys-intermedius Complex, we reconstructed the molecular phylogeny and performed species delimitation based on the complete mitochondrial genomes. Methods: In this study, twelve nomenclatural groups of Gloydius species were involved in the computation of Bayesian phylogenomic inference, five of the twelve nomenclature groups were newly sequenced, while the rest were acquired from the National Center for Biotechnology Information (NCBI). The Bayesian phylogenomic inference was constructed based on 13 mitochondrial protein-coding genes. Species delimitation was performed by two distance-based methods (ABGD and ASAP) and two tree-based methods (GMYC and bPTP). Results: This research resolved the systematic relationship within the G. intermedius Complex with the support of mitogenome-based phylogenomics, while indicating cryptic diversity within the Gloydius halys-intermedius Complex: G. intermedius samples from South Korea show as paraphyletic to the cluster of the samples from northeastern China. Species delimitation results based on four models resemble each other, supporting Gloydius caucasicus, G. cognatus, G. halys, and G. stejnegeri, each representing full species. The species delimitation results of this research also resemble the nomenclatural species based on previous morphometrical results. This research indicates that species delimitation efforts based on the phylogenomic approach would likely resolve complex evolutionary relationships.
A Review of Racial Differences and Disparities in ECG
Authors: Zheng Jianwei , Ani Chizobam , Abudayyeh Islam , Zheng Yunfan , Rakovski Cyril , Yaghmaei Ehsan , Ogunyemi Omolola
Published: February 2025

The electrocardiogram (ECG) is a widely used, non-invasive tool for diagnosing a range of cardiovascular conditions, including arrhythmia and heart disease-related structural changes. Despite its critical role in clinical care, racial and ethnic differences in ECG readings are often underexplored or inadequately addressed in research. Variations in key ECG parameters, such as PR interval, QRS duration, QT interval, and T-wave morphology, have been noted across different racial groups. However, the limited research in this area has hindered the development of diagnostic criteria that account for these differences, potentially contributing to healthcare disparities, as ECG interpretation algorithms largely developed from major population data may lead to misdiagnoses or inappropriate treatments for minority groups. This review aims to help cardiac researchers and cardiovascular specialists better understand, explore, and address the impact of racial and ethnic differences in ECG readings. By identifying potential causes—ranging from genetic factors to environmental influences—and exploring the resulting disparities in healthcare outcomes, we propose strategies such as the development of race-specific ECG norms, the application of artificial intelligence (AI) to improve diagnostic accuracy, and the diversification of ECG databases. Through these efforts, the medical community can advance toward more personalized and equitable cardiovascular care.
Neutrophils: Linking Inflammation to Thrombosis and Unlocking New Treatment Horizons
Authors: Li Haokun , Shan Wenbo , Zhao Xi , Sun Wei
Published: February 2025

Neutrophils play a key role in inflammatory responses and thrombosis, but their complex interactions in disease pathogenesis are not fully understood. This review examines the multifaceted roles of neutrophils, focusing on their activation, cytokine release, and formation of neutrophil extracellular traps (NETs), which contribute to host defense and thrombosis. We discuss the interaction between inflammation and coagulation, the direct effect of neutrophils on thrombus stability, and their involvement in pathological thrombotic diseases. The therapeutic potential of neutrophil drug loading in the treatment of thrombosis, as well as the clinical implications and future research directions, are highlighted. The aim of this review is to gain insight into the critical neutrophil–inflammation–thrombus axis and its potential as a therapeutic target for thrombotic diseases and to suggest possible directions for neutrophil-loaded drug therapy for thrombosis.
Targeting NEK Kinases in Gastrointestinal Cancers: Insights into Gene Expression, Function, and Inhibitors
Authors: Chen Lei , Lu Heng , Ballout Farah , El-Rifai Wael , Chen Zheng , Gokulan Ravindran Caspa , McDonald Oliver Gene , Peng Dunfa
Published: February 2025

Gastrointestinal (GI) cancers, which mainly include malignancies of the esophagus, stomach, intestine, pancreas, liver, gallbladder, and bile duct, pose a significant global health burden. Unfortunately, the prognosis for most GI cancers remains poor, particularly in advanced stages. Current treatment options, including targeted and immunotherapies, are less effective compared to those for other cancer types, highlighting an urgent need for novel molecular targets. NEK (NIMA related kinase) kinases are a group of serine/threonine kinases (NEK1-NEK11) that play a role in regulating cell cycle, mitosis, and various physiological processes. Recent studies suggest that several NEK members are overexpressed in human cancers, including gastrointestinal (GI) cancers, which can contribute to tumor progression and drug resistance. Among these, NEK2 stands out for its consistent overexpression in all types of GI cancer. Targeting NEK2 with specific inhibitors has shown promising results in preclinical studies, particularly for gastric and pancreatic cancers. The development and clinical evaluation of NEK2 inhibitors in human cancers have emerged as a promising therapeutic strategy. Specifically, an NEK2 inhibitor, T-1101 tosylate, is currently undergoing clinical trials. This review will focus on the gene expression and functional roles of NEKs in GI cancers, as well as the progress in developing NEK inhibitors.
PON-P3: Accurate Prediction of Pathogenicity of Amino Acid Substitutions
Authors: Kabir Muhammad , Ahmed Saeed , Zhang Haoyang , Rodríguez-Rodríguez Ignacio , Najibi Seyed Morteza , Vihinen Mauno
Published: February 2025

Different types of information are combined during variation interpretation. Computational predictors, most often pathogenicity predictors, provide one type of information for this purpose. These tools are based on various kinds of algorithms. Although the American College of Genetics and the Association for Molecular Pathology guidelines classify variants into five categories, practically all pathogenicity predictors provide binary pathogenic/benign predictions. We developed a novel artificial intelligence-based tool, PON-P3, on the basis of a carefully selected training dataset, meticulous feature selection, and optimization. We started with 1526 features describing variations, their sequence and structural context, and parameters for the affected genes and proteins. The final random boosting method was tested and compared with a total of 23 predictors. PON-P3 performed better than recently introduced predictors, which utilize large language models or structural predictions. PON-P3 was better than methods that use evolutionary data alone or in combination with different gene and protein properties. PON-P3 classifies cases into three categories as benign, pathogenic, and variants of uncertain significance (VUSs). When binary test data were used, some metapredictors performed slightly better than PON-P3; however, in real-life situations, with patient data, those methods overpredict both pathogenic and benign cases. We predicted with PON-P3 all possible amino acid substitutions in all human proteins encoded from MANE transcripts. The method was also used to predict all unambiguous VUSs (i.e., without conflicts) in ClinVar. A total of 12.9% were predicted to be pathogenic, and 49.9% were benign.
Viral Network Analyzer (VirNA): A Novel Minimum Spanning Networks Algorithm for Investigating Viral Evolution
Authors: Mazzotti Giorgia , Bianco Luca , Lavezzo Enrico , Bado Martina , Toppo Stefano , Fontana Paolo
Published: February 2025

Next Generation Sequencing technologies are essential in public health surveillance for tracking pathogen evolution, spread, and the emergence of new variants. However, the extensive sequencing of viral genomes during recent pandemics has highlighted the limitations of traditional molecular phylogenetic algorithms in capturing fine-grained evolutionary details when analyzed sequences are highly similar and datasets are large-scale. VirNA (Viral Network Analyzer) addresses this challenge by reconstructing detailed mutation patterns and tracing pathogen evolutionary routes in specific geographical regions through Minimum Spanning Networks. It enables users to analyze thousands of sequences, generating networks where nodes represent genomic sequences linked to their metadata, while edges represent potential evolutionary pathways. VirNA is a powerful tool for analyzing large, high-quality datasets, providing detailed insights into rapid pathogen evolution over short time periods, with potential applications in pandemic surveillance.
Open-World Semi-Supervised Learning for fMRI Analysis to Diagnose Psychiatric Disease
Authors: Hu Chang , Dong Yihong , Peng Shoubo , Wu Yuehan
Published: February 2025

Due to the incomplete nature of cognitive testing data and human subjective biases, accurately diagnosing mental disease using functional magnetic resonance imaging (fMRI) data poses a challenging task. In the clinical diagnosis of mental disorders, there often arises a problem of limited labeled data due to factors such as large data volumes and cumbersome labeling processes, leading to the emergence of unlabeled data with new classes, which can result in misdiagnosis. In the context of graph-based mental disorder classification, open-world semi-supervised learning for node classification aims to classify unlabeled nodes into known classes or potentially new classes, presenting a practical yet underexplored issue within the graph community. To improve open-world semi-supervised representation learning and classification in fMRI under low-label settings, we propose a novel open-world semi-supervised learning approach tailored for functional magnetic resonance imaging analysis, termed Open-World Semi-Supervised Learning for fMRI Analysis (OpenfMA). Specifically, we employ spectral augmentation self-supervised learning and dynamic concept contrastive learning to achieve open-world graph learning guided by pseudo-labels, and construct hard positive sample pairs to enhance the network’s focus on potential positive pairs. Experiments conducted on public datasets validate the superior performance of this method in the open-world psychiatric disease diagnosis domain.
Variability of the Hot Box Method in Assessing Thermal Resistance of a Double Leaf Brick Wall
Authors: Ribas Manuel , Barreira Eva , Almeida Ricardo M. S. F.
Published: February 2025

The accurate thermal performance assessment of building components is critical for improving energy efficiency in buildings, mainly as space climatization accounts for a large percentage of energy consumption. The literature review points out multiple parameters that influence the measurement of the U-value using the HFM method. However, most of these studies are focused on in situ tests and little information exists on the variability of the results of the hot box method to assess thermal resistance. According to EN 1934, a baffle must be positioned between the surface of the specimen and the fans of the climatic chamber to maintain acceptable air temperature gradients and uniform air temperature distribution to minimize the convective effects. However, no clear information about its position is given. This study investigates the variability in the measurement of the thermal resistance of double leaf brick wall specimen using the hot box method, focusing on the effect of the layout configuration. An experimental campaign was carried out and three configurations were considered: no baffle, a baffle positioned 1.15 m from the wall, and a baffle positioned 0.05 m from the specimen. The experimental results demonstrate that baffle positioning significantly influences measurement variability. The best-performing configuration (P1) resulted in the lowest variability and the closest agreement with theoretical values, with an average R-value deviation of approximately 25%. These findings are relevant for optimizing testing protocols and improving the reliability of thermal resistance assessments. Furthermore, the results have implications for energy efficiency policies and building retrofitting strategies, aligning with global sustainability goals to reduce building energy demand and carbon emissions.
Diversity of Leaf Katydids of Odzala-Kokoua National Park, Republic of Congo, Central Tropical Africa (Insecta: Orthoptera: Tettigoniidae)
Authors: Massa Bruno
Published: February 2025

The study of specimens collected during the night at a lamp allowed for the description of one new genus Phanreticula n. gen., and six new species, namely Phanreticula fenestrata n. sp., Habrocomes piotri n. sp., Conocephalus (Anisoptera) mollyae n. sp., Phlaurocentrum armatum n. sp., Tetraconcha danielae n. sp., and Tetraconcha fuscopunctata n. sp. Further, females of Paraeulioptera emitflesti Massa, 2020 (known only from the male sex) have been collected and characteristics of its ovipositor allowed for the inclusion of this species in the tribe Catoptropterigini. In addition, Pleothrix conradti (Bolívar, 1906) has been rediscovered after 118 years from its description from material collected in Cameroon, and the male of Griffinipteryx mukonja (Griffini, 1908), known only from three females collected in Cameroon in 1800s, is described for the first time. Finally, an updating of the species belonging to the genus Tetraconcha Karsch, 1890 has been carried out; presently, 24 species are known, including 2 other new species from the Ivory Coast (west tropical Africa), Tetraconcha alberti n. sp., and Tetraconcha tonkouiensis n. sp. Overall, 108 species of Tettigoniidae are listed here.
Natriuretic Peptides as a Predictor for Delirium After Cardiac Surgery: A Prospective Observational Study
Authors: Huisinga Cyril , Struck Eric , Mihatsch Lorenz , Heyn Jens , Hagl Christian , Zwissler Bernhard , von Dossow Vera , Saller Thomas
Published: February 2025

Background/Objectives: Subsequent to surgical procedures under cardiopulmonary bypass, at least one third of the patients experience delirium. Among others, the disruption of the blood–brain barrier results from the release of natriuretic peptides during surgery. Furthermore, natriuretic peptides increase the effect of dopamine agonists, which is a key element in the pathomechanism of delirium. The primary endpoint of this study was the adjusted mean difference in natriuretic peptide concentration before surgery between patients with and without delirium. The secondary endpoints were the differences in cognitive performance and quality of life, and physical performance. Methods: Single center observational study. Setting in the Cardiac surgery and intensive care at a German tertiary medical center. Eighty patients for elective cardiac surgery under cardiopulmonary bypass for valve replacement or coronary artery bypass grafting. Preoperative NT-pro C-type natriuretic peptide (CNP) was determined. After surgery, delirium was assessed five times daily using the confusion assessment method for intensive care until 72 h after surgery and before hospital discharge. Data on quality of life and physical performance were also collected. Results: Overall, 28/80 (35%) patients developed delirium. Patients with delirium showed an increased concentration of NT-proCNP preoperatively (p = 0.016) compared to those who did not experience delirium. Patients with delirium during hospitalization reported deterioration in their physical role function (p = 0.036), vitality (p = 0.004), and social function (p = 0.008) before surgery. Conclusions: Increased NT-proCNP before surgery is associated with the occurrence of delirium. A relevant reduction in cognitive and physical performance and quality of life may be a new risk factor for delirium.
Recent Advances in Coronary Chronic Total Occlusions
Authors: Synetos Andreas , Koliastasis Leonidas , Ktenopoulos Nikolaos , Katsaros Odysseas , Vlasopoulou Konstantina , Drakopoulou Maria , Apostolos Anastasios , Tsalamandris Soritios , Latsios George , Toutouzas Konstantinos , Patrikios Ioannis , Tsioufis Constantinos
Published: February 2025

Coronary chronic total occlusions (CTOs) have been a point of interest of the medical community for the last decade. The natural history of CTOs was for a long time unknown, as the presence of a single CTO was the most frequent cause for the exclusion of patients from randomized controlled trials (RCTs). Recent CTO RCTs have failed to show any benefit in terms of hard endpoints as major adverse cardiovascular events, but have shown a significant improvement in quality of life, as well in the frequency of angina; however, these studies are characterized by the limitation of the short duration of their follow-up period. Real-world data from observational studies indicate a significant improvement in cardiovascular death and overall mortality, suggesting that the results depend on the duration of the follow-up, and not on the procedure per se. The aim of the current review is to summarize all the existing RCTs, and to analyze the most important registries, as well as to present the current development of techniques to boost the successful interventional treatment of CTOs.
Machine Learning-Based Model for Grip Strength Prediction in Healthy Adults: A Nationwide Dataset-Based Study
Authors: Park Mina , Kim Yeo Hyung , Lee Jung Soo
Published: February 2025

Background: This study aimed to develop machine learning models for estimating the handgrip strength (HGS) in healthy adults and to identify the model with the highest accuracy and generalizability. Methods: Data from the Korean National Health and Nutrition Examination Survey (2014–2019), including 21,147 participants aged >19 years, were analyzed. The maximum HGS was measured using a standardized protocol, with 11 demographic, anthropometric, and physical activity predictors. Polynomial regression (PR), multilayer perceptron (MLP), and extreme gradient boosting (XGBoost) models were developed and evaluated using the root-mean-square error (RMSE) and coefficient of determination (R2). Results: The HGS was found to vary by gender, age, and hand dominance, with males and younger individuals showing higher values. The XGBoost model achieved the highest R2 (0.717), demonstrating superior predictive accuracy and generalizability compared with PR and MLP. Key predictors in the XGBoost model included weight, age, height, and waist circumference, while hand dominance was less significant. Conclusions: The XGBoost model outperformed the MLP and PR models, achieving the highest R2 value. It holds promise for clinical applications, enabling accurate HGS estimation to support early diagnosis, targeted interventions, and personalized goal setting.
Beyond Confinement: A Systematic Review on Factors Influencing Binge Drinking Among Adolescents and Young Adults During the Pandemic
Authors: Merino-Casquero Andrea , Andrade-Gómez Elena , Fagundo-Rivera Javier , Fernández-León Pablo
Published: February 2025

Objectives: This study aimed to enhance the understanding of factors influencing changes in binge drinking (BD) behavior during the COVID-19 pandemic, with a particular focus on its impact on the health of individuals aged 12 to 25 years. Methods: A systematic review was conducted, encompassing studies published between January 2020 and September 2024. Articles were retrieved from PubMed, Web of Science, and Scopus, following PRISMA guidelines and the Joanna Briggs Institute (JBI) review protocols. Inclusion criteria targeted studies focusing on BD during the COVID-19 pandemic in adolescents or school-aged individuals without specific medical conditions. Exclusions included studies limited to a single gender, ethnicity, or profession, as well as doctoral theses and editorials. JBI tools were used to assess the quality of the selected studies. Results: From 33 studies (19 cross-sectional and 14 longitudinal), trends in BD during the pandemic varied: 2 studies reported an increase, while 21 indicated a decrease. Key factors linked to increased BD included pandemic stressors (e.g., isolation, social disconnection and non-compliance with restrictions), psychosocial issues (e.g., depression, anxiety, boredom, and low resilience), prior substance use, and sociodemographic variables (e.g., low education, economic extremes, living arrangements, and limited family support). Female gender and academic disengagement were also risk factors. Conversely, factors like stay-at-home orders, fear of contagion, family support, studying health sciences, and resilient coping strategies contributed to reduced BD. Other variables, such as pandemic stress and self-efficacy, had inconsistent effects. Conclusions: Factors contributing to increased BD included pandemic-related stress, mental health conditions, and unhealthy habits, while protective factors included stay-at-home orders, social support, and resilient coping. The study highlights the need for effective prevention and intervention strategies, emphasizing a holistic approach in healthcare, early detection, and tailored interventions, particularly for vulnerable groups such as adolescents.