bluuebunny/crossref_metadata_2025 huggingface dataset:
Expert Judgment Supporting a Bayesian Network to Model the Survival of Pancreatic Cancer Patients
Authors: Secchettin Erica , Paiella Salvatore , Azzolina Danila , Casciani Fabio , Salvia Roberto , Malleo Giuseppe , Gregori Dario
Published: January 2025

Purpose: Pancreatic cancer is known for its poor prognosis. The most effective treatment combines surgery with peri-operative chemotherapy. Current prognostic tools are designed to predict patient outcomes and inform treatment decisions based on collected data. Bayesian networks (BNs) can integrate objective data with subjective clinical insights, such as expert opinions, or they can be independently based on either element. This pilot study is one of the first efforts to incorporate expert opinions into a prognostic model using a Bayesian framework. Methods: A clinical hybrid BN was selected to model the long-term overall survival of pancreatic cancer patients. The SHELF expert judgment method was employed to enhance the BN’s effectiveness. This approach involved a two-phase protocol: an initial single-center pilot phase followed by a definitive international phase. Results: Experts generally agreed on the distribution shape among the 12 clinically relevant predictive variables identified for the BN. However, discrepancies were noted in the tumor size, age, and ASA score nodes. With regard to expert concordance for each node, tumor size, and ASA score exhibited absolute concordance, indicating a strong consensus among experts. Ca19.9 values and resectability status showed high concordance, reflecting a solid agreement among the experts. The remaining nodes showed acceptable concordance. Conclusions: This project introduces a novel clinical hybrid Bayesian network (BN) that incorporates expert elicitation and clinical variables present at diagnosis to model the survival of pancreatic cancer patients. This model aims to provide research-based evidence for more reliable prognosis predictions and improved decision-making, addressing the limitations of existing survival prediction models. A validation process will be essential to evaluate the model’s performance and clinical applicability.
Key Role of Phosphorylation in Small Heat Shock Protein Regulation via Oligomeric Disaggregation and Functional Activation
Authors: Sluzala Zachary B. , Hamati Angelina , Fort Patrice E.
Published: January 2025

Heat shock proteins (HSPs) are essential molecular chaperones that protect cells by aiding in protein folding and preventing aggregation under stress conditions. Small heat shock proteins (sHSPs), which include members from HSPB1 to HSPB10, are particularly important for cellular stress responses. These proteins share a conserved α-crystallin domain (ACD) critical for their chaperone function, with flexible N- and C-terminal extensions that facilitate oligomer formation. Phosphorylation, a key post-translational modification (PTM), plays a dynamic role in regulating sHSP structure, oligomeric state, stability, and chaperone function. Unlike other PTMs such as deamidation, oxidation, and glycation—which are often linked to protein destabilization—phosphorylation generally induces structural transitions that enhance sHSP activity. Specifically, phosphorylation promotes the disaggregation of sHSP oligomers into smaller, more active complexes, thereby increasing their efficiency. This disaggregation mechanism is crucial for protecting cells from stress-induced damage, including apoptosis, inflammation, and other forms of cellular dysfunction. This review explores the role of phosphorylation in modulating the function of sHSPs, particularly HSPB1, HSPB4, and HSPB5, and discusses how these modifications influence their protective functions in cellular stress responses.
Impact of High Glucose on Bone Collagenous Matrix Composition, Structure, and Organization: An Integrative Analysis Using an Ex Vivo Model
Authors: Araújo Rita , Páscoa Ricardo N. M. J. , Bernardino Raquel , Gomes Pedro S.
Published: January 2025

Diabetes mellitus is a widespread metabolic disorder linked to numerous systemic complications, including adverse effects on skeletal health, such as increased bone fragility and fracture risk. Emerging evidence suggests that high glucose may disrupt the extracellular matrix (ECM) of bone, potentially altering its composition and organization. Collagen, the primary organic component of the ECM, is critical for maintaining structural integrity and biomechanical properties. However, definitive evidence and a comprehensive understanding of the molecular mechanisms through which high glucose impacts the ECM and collagen remain elusive. This study employed an ex vivo embryonic chicken femur model to investigate the effects of high glucose on the collagenous matrix. A comprehensive approach integrating histological evaluation, histomorphometry, ATR-FTIR spectroscopy, and proteomics was adopted to unravel structural, biochemical, and molecular changes in the ECM. Histomorphometric analysis revealed disrupted collagen fibril architecture, characterized by altered fibril diameter, alignment, and spatial organization. ATR-FTIR spectroscopy highlighted biochemical modifications, including non-enzymatic glycation that impaired collagen crosslinking and reduced matrix integrity. Proteomic profiling unveiled significant alterations in ECM composition and function, including downregulation of key collagen crosslinking enzymes and upregulation of inflammatory and coagulation pathways. High glucose profoundly disrupts the collagenous matrix of bone, weakening its structural integrity and organization. These findings emphasize the critical impact of high glucose environments on extracellular matrix composition and bone quality, offering insights into the mechanisms behind diabetic bone fragility and guiding future research toward targeted therapeutic strategies.
The Dynamicity of the Oxytocin Receptor in the Brain May Trigger Sensory Deficits in Autism Spectrum Disorder
Authors: Camerino Claudia
Published: January 2025

Sensory processing abnormalities have been noted since the first clinical description of autism in 1940. However, it was not until the release of the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) in 2013 that sensory challenges were considered as symptoms of autism spectrum disorder (ASD). Multisensory processing is of paramount importance in building a perceptual and cognitive representation of reality. For this reason, deficits in multisensory integration may be a characteristic of ASD. The neurohormone oxytocin (Oxt) is involved in the etiology of ASD, and there are several ongoing clinical trials regarding Oxt administration in ASD patients. Recent studies indicate that Oxt triggers muscle contraction modulating thermogenesis, while abnormal thermoregulation results in sensory deficits, as in ASD. Activation of the Oxt system through exposure to cold stress regulates the expression of oxytocin receptor (Oxtr) in the brain and circulating Oxt, and if this mechanism is pathologically disrupted, it can lead to sensory processing abnormalities since Oxt acts as a master gene that regulates thermogenesis. This review will describe the sensory deficits characteristic of ASD together with the recent theories regarding how the modulation of Oxt/Oxtr in the brain influences sensory processing in ASD.
The Mouth of the River Ter in the Early Middle Ages in the Mediterranean Coast
Authors: Bouzas Sabater Marc , Burch i Rius Josep , Castanyer Masoliver Pere , Julià Brugués Ramon , Nolla Brufau Josep Maria , Pons Mir Pere , Sagrera Aradilla Jordi , Solà Sobiranas Joan
Published: January 2025

The River Ter is one of the axes which, in a west-east direction, has historically articulated the population of the extreme north-east of the Iberian Peninsula. Although its upper, middle and part of the lower courses do not present any problems in its course, its mouth in the Mediterrane-an Sea has raised many questions due to the existence of two potential branches, one to the north that would flow into the Gulf of Roses and another to the south that would flow into the Bay of Pals. In 2016, an exhaustive documentary study on the potential southern branch provided exhaustive information on the existence of lake areas and their relationship with the settlement between the 9th and 11th centuries, but raised doubts about the existence of the river in the bay from Pals. Subsequently, between 2020 and 2022, geological studies have been carried out in this area which demonstrate the existence of the river in this area but with a variable course, with changes in the river channel (meandering, diffuse and braided), and with notable changes that conditioned the settlement of this sector of the coast and as was recorded in written documentation between the 9th and 11th centuries.
Research on the Durability of Modified Crumb Rubber Asphalt Mixtures in High-Altitude and Seasonally Frozen Regions
Authors: Liu Song , Lu Peng , Sun Xuecong , Wang Hongchang , Fei Zhuang
Published: January 2025

Asphalt pavements in high-altitude and seasonally frozen regions of China encounter significant challenges that impact their stability and durability. This study aims to evaluate the performance of modified crumb rubber (MCR) asphalt mixtures under typical conditions of high-altitude seasonal frozen regions, specifically focusing on the effects of ultraviolet (UV) exposure and freeze–thaw cycling. Laboratory tests were designed to simulate UV irradiation and freeze–thaw cycling on asphalt mixtures, and then a series of tests were conducted on the pre-treated asphalt mixture specimens to investigate the effects on the performance including cohesion, high-temperature stability, low-temperature cracking resistance, water stability, and fatigue resistance. The MCR asphalt mixtures were tested in comparison to the Styrene–Butadiene–Styrene (SBS) modified asphalt and conventional crumb rubber modified asphalt mixtures. The test results indicated that MCR-modified asphalt mixture exhibited better cohesion and water stability than other tested mixtures. Under UV aging conditions, it showed a relatively slow performance degradation rate due to its unique composition that mitigates stress sensitivity. Also, when subjected to freeze–thaw cycling, the incorporation of MCR particles in the asphalt mixture resulted in delayed micro-crack propagation and a self-healing effect, thus mitigating its performance degradation rate compared to the other mixtures. The findings suggest that MCR MCR-modified asphalt mixture is a promising alternative for improving the durability of pavement in high-altitude and seasonally frozen regions.
The Disappearance of COVID-19 Data Dashboards: The Case of Ephemeral Data
Authors: Laituri Melinda , Kalra Yogya , Yang Chaowei
Published: January 2025

Data dashboards provide a means for sharing multiple data products at a glance and were ubiquitous during the COVID-19 pandemic. Data dashboards tracked global and country-specific statistics and provided cartographic visualizations of cases, deaths, vaccination rates and other metrics. We examined the role of geospatial data on COVID-19 dashboards in the form of maps, charts, and graphs. We organize our review of 193 COVID-19 dashboards by region and compare the accessibility and operationality of dashboards over time and the use of web maps and geospatial visualizations. We found that of the dashboards reviewed, only 17% included geospatial visualizations. We observe that many of the COVID-19 dashboards from our analysis are no longer accessible (66%) and consider the ephemeral nature of data and dashboards. We conclude that coordinated efforts and a call to action to ensure the standardization, storage, and maintenance of geospatial data for use on data dashboards and web maps are needed for long-term use, analyses, and monitoring to address current and future public health and other challenging issues.
Towards Personalized Radiotherapy in Pelvic Cancer: Patient-Related Risk Factors for Late Radiation Toxicity
Authors: Nuijens Anna C. , Oei Arlene L. , Franken Nicolaas A. P. , Rasch Coen R. N. , Stalpers Lukas J. A.
Published: January 2025

Normal tissue reactions vary significantly among patients receiving the same radiation treatment regimen, reflecting the multifactorial etiology of late radiation toxicity. Predicting late radiation toxicity is crucial, as it aids in the initial decision-making process regarding the treatment modalities. For patients undergoing radiotherapy, anticipating late toxicity allows for planning adjustments to optimize individualized care. Various dosimetric parameters have been shown to influence the incidence of late toxicity, and the literature available on this topic is extensive. This narrative review examines patient-related determinants of late toxicity following external beam radiotherapy for pelvic tumors, with a focus on prostate and cervical cancer patients. In Part I, we address various methods for quantifying radiation toxicity, providing context for interpreting toxicity data. Part II examines the current insights into the clinical risk factors for late toxicity. While certain factors—such as previous abdominal surgery, smoking behavior, and severe acute toxicity—have consistently been reported, most of the others show inconsistent associations. In Part III, we explore the influence of genetic factors and discuss promising predictive assays. Single-nucleotide polymorphisms (SNPs) likely elevate the risk in specific combinations. Advances in artificial intelligence now allow for the identification of SNP patterns from large datasets, supporting the development of polygenic risk scores. These innovations hold promise for improving personalized treatment strategies and reducing the burden of late toxicity in cancer survivors.
Early Effects of Bronchoscopic Cryotherapy in Metastatic Non-Small Cell Lung Cancer Patients Receiving Immunotherapy: A Single-Center Prospective Study
Authors: Vasiliauskas Gediminas , Žemaitė Evelina , Skrodenienė Erika , Poškienė Lina , Maziliauskienė Gertrūda , Mačionis Aurimas , Miliauskas Skaidrius , Vajauskas Donatas , Žemaitis Marius
Published: January 2025

Background/Objectives: Cryotherapy is used for local tissue destruction through rapid freeze–thaw cycles. It induces cancer cell necrosis followed by inflammation in the treated tumor microenvironment, and it stimulates systemic adaptive immunity. Combining cryotherapy with immunotherapy may provide a sustained immune response by preventing T cell exhaustion. Methods: Fifty-five patients with metastatic non-small cell lung cancer who had received no prior treatment were randomized into two groups in a 1:1 ratio: the bronchoscopic cryotherapy group or the control group. Patients received up to four cycles of pembrolizumab as monotherapy or in combination with platinum-based chemotherapy. Immune-related adverse events (irAEs), complications, tumor size changes, overall response rate (ORR), and disease control rate (DCR) were evaluated. Results: Lung tumors, treated with cryotherapy, demonstrated continuous reduction from the baseline (22.4 cm2 vs. 14.4 cm2 vs. 10.2 cm2, p < 0.001). Similar changes were observed in pulmonary tumors in the control group (19.0 cm2 vs. 10.0 cm2, p < 0.001). The median change in pulmonary tumors between two groups was not significant (−42.9% vs. −27.7%, p = 0.175). No significant differences were observed in the ORR (28.6% vs. 23.1%, p = 0.461) or target lesion decrease (−24.0% vs. −23.4%, p = 0.296) between the groups. However, the DCR was significantly higher in the cryotherapy group (95.2% vs. 73.1%, p = 0.049). No cases of serious bleeding during cryotherapy or pneumothorax were observed. Six patients (25.0%) in the cryotherapy group and eight (26.7%) in the control group experienced irAEs. Conclusions: Our study demonstrated that combined bronchoscopic cryotherapy and immunotherapy with or without chemotherapy may reduce the rate of progressive disease in metastatic non-small cell lung cancer patients while maintaining a satisfactory safety profile.
Comparative Analysis of Automated and Handheld Breast Ultrasound Findings for Small (≤1 cm) Breast Cancers Based on BI-RADS Category
Authors: Mun Han Song , Ko Eun Young , Han Boo-Kyung , Ko Eun Sook , Choi Ji Soo , Kim Haejung , Kim Myoung Kyoung , Kim Jieun
Published: January 2025

Objectives: This study aimed to compare ultrasound (US) findings between automated and handheld breast ultrasound (ABUS and HHUS, respectively) in small breast cancers, based on the breast imaging reporting and data system (BI-RADS) category. Methods: We included 51 women (mean age: 52 years; range: 39–66 years) with breast cancer (invasive or DCIS), all of whom underwent both ABUS and HHUS. Patients with tumors measuring ≤1 cm on either modality were enrolled. Two breast radiologists retrospectively evaluated multiple imaging features, including shape, orientation, margin, echo pattern, and posterior characteristics and assigned BI-RADS categories. Lesion sizes were compared between US and pathological findings. Statistical analyses were performed using Bowker’s test of symmetry, a paired t-test, and a cumulative link mixed model. Results: ABUS assigned lower BI-RADS categories than HHUS while still maintaining malignancy suspicion in categories 4A or higher (54.8% consistent with HHUS; 37.3% downcategorized in ABUS, p = 0.005). While ABUS demonstrated less aggressive margins in some cases (61.3% consistent with HHUS; 25.8% showing fewer suspicious margins in ABUS), this difference was not statistically significant (p = 0.221). Similarly, ABUS exhibited slightly greater height–width ratios compared to HHUS (median, interquartile range: 0.98, 0.7–1.12 vs. 0.86, 0.74–1.10, p = 0.166). No significant differences were observed in other US findings or tumor sizes between the two modalities (all p > 0.05). Conclusions: Small breast cancers exhibited suspicious US features on both ABUS and HHUS, yet they were assigned lower BI-RADS assessment categories on ABUS compared to HHUS. Therefore, when conducting breast cancer screening with ABUS, it is important to remain attentive to even subtle suspicious findings, and active consideration for biopsy may be warranted.
MixCFormer: A CNN–Transformer Hybrid with Mixup Augmentation for Enhanced Finger Vein Attack Detection
Authors: Wang Zhaodi , Yang Shuqiang , Qin Huafeng , Liu Yike , Wang Junqiang
Published: January 2025

Finger vein recognition has gained significant attention for its importance in enhancing security, safeguarding privacy, and ensuring reliable liveness detection. As a foundation of vein recognition systems, vein detection faces challenges, including low feature extraction efficiency, limited robustness, and a heavy reliance on real-world data. Additionally, environmental variability and advancements in spoofing technologies further exacerbate data privacy and security concerns. To address these challenges, this paper proposes MixCFormer, a hybrid CNN–transformer architecture that incorporates Mixup data augmentation to improve the accuracy of finger vein liveness detection and reduce dependency on large-scale real datasets. First, the MixCFormer model applies baseline drift elimination, morphological filtering, and Butterworth filtering techniques to minimize the impact of background noise and illumination variations, thereby enhancing the clarity and recognizability of vein features. Next, finger vein video data are transformed into feature sequences, optimizing feature extraction and matching efficiency, effectively capturing dynamic time-series information and improving discrimination between live and forged samples. Furthermore, Mixup data augmentation is used to expand sample diversity and decrease dependency on extensive real datasets, thereby enhancing the model’s ability to recognize forged samples across diverse attack scenarios. Finally, the CNN and transformer architecture leverages both local and global feature extraction capabilities to capture vein feature correlations and dependencies. Residual connections improve feature propagation, enhancing the stability of feature representations in liveness detection. Rigorous experimental evaluations demonstrate that MixCFormer achieves a detection accuracy of 99.51% on finger vein datasets, significantly outperforming existing methods.
Short-Term Photovoltaic Power Forecasting Based on the VMD-IDBO-DHKELM Model
Authors: Wang Shengli , Guo Xiaolong , Sun Tianle , Xu Lihui , Zhu Jinfeng , Li Zhicai , Zhang Jinjiang
Published: January 2025

A short-term photovoltaic power forecasting method is proposed, integrating variational mode decomposition (VMD), an improved dung beetle algorithm (IDBO), and a deep hybrid kernel extreme learning machine (DHKELM). First, the weather factors less relevant to photovoltaic (PV) power generation are filtered using the Spearman correlation coefficient. Historical data are then clustered into three categories—sunny, cloudy, and rainy days—using the K-means algorithm. Next, the original PV power data are decomposed through VMD. A DHKELM-based combined prediction model is developed for each component of the decomposition, tailored to different weather types. The model’s hyperparameters are optimized using the IDBO. The final power forecast is determined by combining the outcomes of each individual component. Validation is performed using actual data from a PV power plant in Australia and a PV power station in Kashgar, China demonstrates. Numerical evaluation results show that the proposed method improves the Mean Absolute Error (MAE) by 3.84% and the Root-Mean-Squared Error (RMSE) by 3.38%, confirming its accuracy.
Assessment of Mango Canopy Water Content Through the Fusion of Multispectral Unmanned Aerial Vehicle (UAV) and Sentinel-2 Remote Sensing Data
Authors: Liu Jinlong , Huang Jing , Wu Mengjuan , Qin Tengda , Jia Haoyi , Hao Shaozheng , Jin Jia , Huang Yuqing , Pumijumnong Nathsuda
Published: January 2025

This study proposes an Additive Wavelet Transform (AWT)-based method to fuse Multispectral UAV (MS UAV, 5 cm resolution) and Sentinel-2 satellite imagery (10–20 m resolution), generating 5 cm resolution fused images with a focus on near-infrared and shortwave infrared bands to enhance the accuracy of mango canopy water content monitoring. The fused Sentinel-2 and MS UAV data were validated and calibrated using field-collected hyperspectral data to construct vegetation indices, which were then used with five machine learning (ML) models to estimate Fuel Moisture Content (FMC), Equivalent Water Thickness (EWT), and canopy water content (CWC). The results indicate that the addition of fused Sentinel-2 data significantly improved the estimation accuracy of all parameters compared to using MS UAV data alone, with the Genetic Algorithm Backpropagation Neural Network (GABP) model performing best (R2 = 0.745, 0.859, and 0.702 for FMC, EWT, and CWC, respectively), achieving R2 improvements of 0.066, 0.179, and 0.210. Slope, canopy coverage, and human activities were identified as key factors influencing the spatial variability of FMC, EWT, and CWC, with CWC being the most sensitive to environmental changes, providing a reliable representation of mango canopy water status.
Isolation and Characterization of Indigenous Acetobacter Strains from Cashew Apple and Their Potential Use in Vinegar Production
Authors: Ouattara Yaya Anianhou , Soro Doudjo , Fossou Kouakou Romain , Yebouet Ahou Cinthia Ines , Cissé Ismael Abraham , Akissi Dogbo Marius , Zézé Adolphe , Assidjo Emmanuel , Yao Kouassi Benjamin
Published: January 2025

Côte d’Ivoire has the largest cashew tree cultivation area in the world, but the cashew apple produced is still underutilized despite its potential for industrial use. The present study aimed to isolate and identify acetic acid bacterial strains and assess their potential use for cashew apple-based vinegar production. Vinegar mother from fermented juice was used to isolate acetic acid bacteria on a standard glucose-based medium. Physiological and biochemical tests followed by 16S rRNA gene analysis and phylogeny were used for isolate characterization. Moreover, their acetic acid production capacity was assessed. As results, five strains of the Acetobacter genus were isolated. Phenotypic and phylogenetic analysis revealed that four of them, namely OYA2, OYA6, OYA9, and OYA10, belong to the A. tropicalis/A. senegalensis species complex with 99.7% or 100% similarity. The fifth strain, OYA7, being similar (99.7%) to A. syzygii. All the isolates were resistant to alcohol 15% (v/v) and grew well between pH 5.0 and 6.5. Their optimal growth temperatures varied between 27 °C and 37 °C, and only isolate OYA6 grew at a temperature of up to 40 °C. They produced vinegar with a yield (Yp/s, g/g) varying from 0.82 to 0.92, and acetic acid contents (g/L) of 80.67, 70.26, 70.11, 68.70 and 67.22 were obtained with OYA6, OYA7, OYA2, OYA10, and OYA9, respectively. Thus, the isolate OYA6 appeared as the best candidate for vinegar production, owing to its superior yield and thermotolerance abilities that need to be further explored for industry use.
Tailoring Structural, Emulsifying, and Interfacial Properties of Rice Bran Protein Through Limited Enzymatic Hydrolysis After High-Hydrostatic-Pressure Pretreatment
Authors: Wang Shirang , Hua Zhen , Wang Tengyu , Yu Guoping , Sun Yu
Published: January 2025

We carried out limited enzymatic hydrolysis with trypsin on rice bran protein (RBP) pretreated by high hydrostatic pressure (HHP) in this study. The effects of the degree of hydrolysis (DH) on the structural and emulsifying properties were investigated. The results indicated that the molecular structure of RBP changed after limited enzymatic hydrolysis. The rice bran protein hydrolysate (RBPH, DH8) exhibited a better molecular distribution, a smaller particle size (200.4 nm), a better emulsifying activity index (31.82 m2/g), and an improved emulsifying stability index (24.69 min). RBPH emulsions with different DH (0–12) values were prepared. The interfacial properties, such as particle size, the ζ-potential, and the interfacial tension of the emulsions, were measured. Compared to the control, the interfacial properties of the RBPH emulsions were significantly improved after limited enzymatic hydrolysis. The RBPH emulsion at DH8 showed better stability with a smaller emulsion droplet size (2.31 μm), a lower ζ-potential (−25.56 mV), and a lower interfacial tension. This study can provide a theoretical basis for the application of RBP as the plant protein-based emulsifier in the beverage industry.
Proximate Composition and In Vitro Bioactive Properties of Leaf Extracts from Seven Viola Species
Authors: Zeng Guangnian , Li Xingfan , Zhao Chunbo , Pang Yongkang , Luo Xiongfei , Tang Zhonghua
Published: January 2025

Viola, an edible wild plant, is valued for its distinctive flavor and health-promoting properties. This study examines the proximate composition, bioactive compounds, and in vitro biological activities of seven Viola leaves (Viola prionantha, Viola collina, Viola acuminata, Viola variegata, Viola tokubuchiana var. takedana, Viola mirabilis, and Viola philippica). Findings reveal that the leaves of the seven Viola species are rich in phenolic compounds (131.13 mg gallic acid equivalents (GAE)/100 g fresh weight (FW)–384.80 mg GAE/100 g FW), flavonoids (13.09 mg rutin equivalents (RE)/100 g FW–40.08 mg RE/100 g FW), fatty acids (palmitic acid, linoleic acid, oleic acid, and α-linolenic acid), and essential minerals, such as potassium, calcium, and magnesium. The leaf extracts demonstrated significant inhibitory effects on α-glucosidase (84.17%) and pancreatic lipase (77.54%) at a concentration of 1 g of extract per milliliter of solution. Additionally, the biological activity of Viola leaves, particularly their antioxidant capacity, is associated with their phenolic and flavonoid content, with caffeic acid contributing up to 35.2% of the total phenolic acids and isoquercitrin being one of the most bioavailable flavonoids. These results indicate that Viola offers potential notable health benefits, presenting a valuable addition to enhancing modern dietary patterns and overall health.
Rainy and Dry Seasons Are Relevant Factors Affecting Chemical and Antioxidant Properties of Meliponini Honey
Authors: Lavinas Flavia C. , Gomes Brendo A. , Silva Marcos V. T. , Lima Raissa , Leitão Suzana G. , Moura Mirian R. L. , Simas Rosineide C. , Barbosa Renata F. , Silva Fabricio O. , Carneiro Carla S. , Rodrigues Igor A.
Published: January 2025

Brazilian stingless bee species produce honey with distinct physicochemical and bioactive properties shaped by environmental factors. This study investigated the effects of the rainy and dry seasons on the physicochemical characteristics, chemical fingerprinting, mineral content, and antioxidant capacity of honey from Melipona mondury and Melipona bicolor. The honey samples were analyzed for their phytochemical properties (official methods), total phenolics (Folin–Ciocalteu method), flavonoid content (aluminum complex formation method), antioxidant capacity (FRAP and ABTS assays), and antioxidant activity (erythrocyte model). The mineral content was assessed via TXRF spectroscopy, and chemical fingerprinting was conducted using mass spectrometry. Chemometric tools were used for the samples’ discriminating analyses, including Principal Component Analysis (PCA) and Partial Least Squares–Discriminant Analysis (PLS-DA). Seasonal variations significantly affected the moisture, total soluble solids, and acidity. In turn, the antioxidant capacity was influenced mainly by the bee species. The mineral composition, particularly potassium, phosphorus, and calcium, remained stable. Multivariate analysis identified m/z ions (VIP scores > 2.5), rather than physicochemical or antioxidant capacity parameters, as critical for seasonal discrimination. The antioxidant activity, assessed by oxidative hemolysis prevention, was robust across the seasons, with M. mondury honey (2 mg·mL−1) from the rainy season outperforming ascorbic acid. These findings underscore the impact of the rainy and dry seasons and the potential of secondary metabolite fingerprinting to identify collection periods.
Coffee Pulp from Azores: A Novel Phytochemical-Rich Food with Potential Anti-Diabetic Properties
Authors: Costa Anabela S. G. , Peixoto Juliana A. Barreto , Machado Susana , Espírito Santo Liliana , Soares Thiago F. , Andrade Nelson , Azevedo Rui , Almeida Agostinho , Costa Helena S. , Oliveira Maria Beatriz Prior Pinto , Martel Fátima , Simal-Gandara Jesus , Alves Rita C.
Published: January 2025

Coffee pulp, a by-product of wet coffee processing, shows significant potential in the food and health domains, but its real applications remain underexplored. This work investigated the chemical composition and bioactive properties of coffee pulp from São Miguel Island (Azores, Portugal). The studied coffee pulp exhibited high fiber content (52% dw), mostly insoluble; notable mineral levels (10.6%), mainly K, Ca, and Mg; and 6% dw of total amino acids, with hydroxyproline, aspartic acid, glutamic acid, and leucine in higher amounts. Despite containing low fat (1.6% dw), mainly saturated, it also showed considerable amounts of polyunsaturated fatty acids with a favorable n6/n3 ratio (1.40) and vitamin E (α-, β-, and γ-tocopherols). Its antioxidant capacity can be partially explained by the chlorogenic acid content (9.2 mg/g dw), and caffeine (0.98%) was present in similar amounts to those observed in some arabica coffee beans. A decrease in glucose uptake in Caco-2 cells was found, but not in fructose, suggesting selective inhibition of SGLT1 and potential antidiabetic effects. These results show that Azorean coffee pulp has potential as a sustainable and bioactive ingredient for incorporation into functional foods or dietary supplements.
Finite-Time Synchronization of Fractional-Order Complex-Valued Multi-Layer Network via Adaptive Quantized Control Under Deceptive Attacks
Authors: Xu Lulu , Yu Juan , Hu Cheng , Xiong Kailong , Shi Tingting
Published: January 2025

This article investigates the problem of finite-time synchronization of fractional-order complex-valued random multi-layer networks without decomposing them into two real-valued systems. Firstly, by promoting real-valued signum functions, sign functions on the complex-valued domain are introduced. Simultaneously, quantization functions in the complex-valued domain are also introduced, and several related formulas for sign functions and quantization functions in complex-valued domain are established. Under the framework of the given sign function and quantization function, an adaptive quantized control scheme with or without deception attacks is designed. According to the finite-time theorem, Lyapunov function, and graph theory methods, some sufficient criteria for realizing finite-time synchronization in complex-valued fractional-order multi-layer networks have been obtained. Furthermore, the setting time of finite-time synchronization is effectively evaluated. Eventually, the reliability of our results and the practicality of control strategies are verified through numerical examples.
Dealing with Childhood Externalizing Behavior: Protocol for a Feasibility RCT of the Being a Parent Program
Authors: Maciel Laura , Pires Ana Rita , Basto-Pereira Miguel , Day Crispin
Published: January 2025

Concerning numbers of childhood behavior problems have been reported worldwide. Parenting interventions are considered one of the most effective early strategies to intervene with externalizing conduct. This protocol outlines a feasibility RCT that aims to implement a parenting intervention in Portugal and (a) test key feasibility parameters, (b) assess the fidelity and acceptability of the program, and (c) explore its effectiveness in childhood behavior problems, parenting skills, parental concern, and parental sense of competence. A double-blinded, two-arm feasibility RCT is described. The participants are the primary caregivers of children between the ages of two and eleven years old that identify difficulties in managing their child’s behavior. Families will be randomly assigned to an intervention arm and a waitlist control arm. Parents in the intervention arm will participate in the Being a Parent program (Portuguese version: Ser Pai & Ser Mãe), an eight-week group intervention. Outcomes will be assessed using quantitative and qualitative measures throughout three assessment periods (pre- and post-intervention, and follow-up). This study marks the first feasibility RCT of the Being a Parent program outside the UK. The findings will provide information on the global strength of this program. Challenges and clinical implications are also discussed.
Critical Geochemical and Microbial Reactions in Underground Hydrogen Storage: Quantifying Hydrogen Loss and Evaluating CO2 as Cushion Gas
Authors: Al Homoud Rana , Machado Marcos Vitor Barbosa , Daigle Hugh , Ates Harun
Published: January 2025

Hydrogen is a pivotal energy carrier for achieving sustainability and stability, but safe and efficient geological underground hydrogen storage (UHS) is critical for its large-scale application. This study investigates the impacts of geochemical and biochemical reactions on UHS, addressing challenges that threaten storage efficiency and safety. Geochemical reactions in saline aquifers, particularly the generation of hydrogen sulfide (H2S), were analyzed using advanced compositional and geochemical modeling calibrated with experimental kinetic data. The results indicate that geochemical reactions have a minimal effect on hydrogen consumption. However, by year 10 of storage operations, H2S levels could reach 12–13 ppm, necessitating desulfurization to maintain storage performance and safety. The study also examines the methanogenesis reaction, where microorganisms consume hydrogen and carbon dioxide to produce methane. Numerical simulations reveal that microbial activity under suitable conditions can reduce in situ hydrogen volume by up to 50%, presenting a critical hurdle to UHS feasibility. These findings highlight the necessity of conducting microbial analyses of reservoir brines during the screening phase to mitigate hydrogen losses. The novelty of this work lies in its comprehensive field-scale analysis of impurity-induced geochemical and microbial reactions and their implications for underground hydrogen storage. By integrating kinetic parameters derived from experimental data with advanced computational modeling, this study uncovers the mechanisms driving these reactions and highlights their impact on storage efficiency, and safety. By offering a detailed field-scale perspective, the findings provide a pivotal framework for advancing future hydrogen storage projects and ensuring their practical viability.
MicroRNA Expression Profile in Acute Ischemic Stroke
Authors: Mainali Shraddha , Nepal Gaurav , Shumilov Kirill , Webb Amy , Fadda Paolo , Mirebrahimi Darya , Hamed Mohammad , Nana-Sinkam Patrick , Worrall Bradford B. , Woo Daniel , Johnson Nicholas
Published: January 2025

Acute ischemic stroke with large vessel occlusion (LVO) continues to present a considerable challenge to global health, marked by substantial morbidity and mortality rates. Although definitive diagnostic markers exist in the form of neuroimaging, their expense, limited availability, and potential for diagnostic delay can often result in missed opportunities for life-saving interventions. Despite several past attempts, research efforts to date have been fraught with challenges likely due to multiple factors, such as the inclusion of diverse stroke types, variable onset intervals, differing pathobiologies, and a range of infarct sizes, all contributing to inconsistent circulating biomarker levels. In this context, microRNAs (miRNAs) have emerged as a promising biomarker, demonstrating potential as biomarkers across various diseases, including cancer, cardiovascular conditions, and neurological disorders. These circulating miRNAs embody a wide spectrum of pathophysiological processes, encompassing cell death, inflammation, angiogenesis, neuroprotection, brain plasticity, and blood–brain barrier integrity. This pilot study explores the utility of circulating exosome-enriched extracellular vesicle (EV) miRNAs as potential biomarkers for anterior circulation LVO (acLVO) stroke. In our longitudinal prospective cohort study, we collected data from acLVO stroke patients at four critical time intervals post-symptom onset: 0–6 h, 6–12 h, 12–24 h, and 5–7 days. For comparative analysis, healthy individuals were included as control subjects. In this study, extracellular vesicles (EVs) were isolated from the plasma of participants, and the miRNAs within these EVs were profiled utilizing the NanoString nCounter system. Complementing this, a scoping review was conducted to examine the roles of specific miRNAs such as miR-140-5p, miR-210-3p, and miR-7-5p in acute ischemic stroke (AIS). This review involved a targeted PubMed search to assess their influence on crucial pathophysiological pathways in AIS, and their potential applications in diagnosis, treatment, and prognosis. The review also included an assessment of additional miRNAs linked to stroke. Within the first 6 h of symptom onset, three specific miRNAs (miR-7-5p, miR-140-5p, and miR-210-3p) exhibited significant differential expression compared to other time points and healthy controls. These miRNAs have previously been associated with neuroprotection, cellular stress responses, and tissue damage, suggesting their potential as early markers of acute ischemic stroke. This study highlights the potential of circulating miRNAs as blood-based biomarkers for hyperacute acLVO ischemic stroke. However, further validation in a larger, risk-matched cohort is required. Additionally, investigations are needed to assess the prognostic relevance of these miRNAs by linking their expression profiles with radiological and functional outcomes.
Regulation of PHD2 by HIF-1α in Erythroid Cells: Insights into Erythropoiesis Under Hypoxia
Authors: Wang Shunjuan , Xu Qiying , Liu Wenjing , Zhang Na , Qi Yuelin , Tang Feng , Ge Rili
Published: January 2025

The hypoxia-inducible factor (HIF) pathway has been demonstrated to play a pivotal role in the process of high-altitude adaptation. PHD2, a key regulator of the HIF pathway, has been found to be associated with erythropoiesis. However, the relationship between changes in Phd2 abundance and erythroid differentiation under hypoxic conditions remains to be elucidated. A hemin-induced K562 erythroid differentiation model was used to explore the effects of PHD2 knockdown under hypoxia. Erythroid differentiation was assessed by flow cytometry and immunofluorescence. HIF-1α’s regulation of PHD2 was examined using luciferase assays and ChIP-seq. CRISPR/Cas9 was applied to knock out EGLN1 and HIF1A, and a fluorescent reporter system was developed to track PHD2 expression. PHD2 knockdown enhanced erythroid differentiation, evident by increased CD71 and CD235a expression. Reporter assays and ChIP-seq identified an HIF-1α binding site in the EGLN1 5′ UTR, confirming HIF-1α as a regulator of PHD2 expression. The fluorescent reporter system provided real-time monitoring of endogenous PHD2 expression, showing that HIF-1α significantly modulates PHD2 levels under hypoxic conditions. PHD2 influences erythropoiesis under hypoxia, with HIF-1α regulating its expression. This feedback loop between HIF-1α and PHD2 sheds light on mechanisms driving erythroid differentiation under low-oxygen conditions.
DFCNformer: A Transformer Framework for Non-Stationary Time-Series Forecasting Based on De-Stationary Fourier and Coefficient Network
Authors: Jin Yuxin , Mao Yuhan , Chen Genlang
Published: January 2025

Time-series data are widely applied in real-world scenarios, but the non-stationary nature of their statistical properties and joint distributions over time poses challenges for existing forecasting models. To tackle this challenge, this paper introduces a forecasting model called DFCNformer (De-stationary Fourier and Coefficient Network Transformer), designed to mitigate accuracy degradation caused by non-stationarity in time-series data. The model initially employs a stabilization strategy to unify the statistical characteristics of the input time series, restoring their original features at the output to enhance predictability. Then, a time-series decomposition method splits the data into seasonal and trend components. For the seasonal component, a Transformer-based encoder–decoder architecture with De-stationary Fourier Attention (DSF Attention) captures temporal features, using differentiable attention weights to restore non-stationary information. For the trend component, a multilayer perceptron (MLP) is used for prediction, enhanced by a Dual Coefficient Network (Dual-CONET) that mitigates distributional shifts through learnable distribution coefficients. Ultimately, the forecasts of the seasonal and trend components are combined to generate the overall prediction. Experimental findings reveal that when the proposed model is tested on six public datasets, in comparison with five classic models it reduces the MSE by an average of 9.67%, with a maximum improvement of 40.23%.
Concussion and the Autonomic, Immune, and Endocrine Systems: An Introduction to the Field and a Treatment Framework for Persisting Symptoms
Authors: Pertab Jon L. , Merkley Tricia L. , Winiarski Holly , Cramond Kelly M. J. , Cramond Alex J.
Published: January 2025

A significant proportion of patients who sustain a concussion/mild traumatic brain injury endorse persisting, lingering symptoms. The symptoms associated with concussion are nonspecific, and many other medical conditions present with similar symptoms. Medical conditions that overlap symptomatically with concussion include anxiety, depression, insomnia, chronic pain, chronic fatigue, fibromyalgia, and cervical strain injuries. One of the factors that may account for these similarities is that these conditions all present with disturbances in the optimal functioning of the autonomic nervous system and its intricate interactions with the endocrine system and immune system—the three primary regulatory systems in the body. When clinicians are working with patients presenting with persisting symptoms after concussion, evidence-based treatment options drawn from the literature are limited. We present a framework for the assessment and treatment of persisting symptoms following concussion based on the available evidence (treatment trials), neuroanatomical principles (research into the physiology of concussion), and clinical judgment. We review the research supporting the premise that behavioral interventions designed to stabilize and optimize regulatory systems in the body following injury have the potential to reduce symptoms and improve functioning in patients. Foundational concussion rehabilitation strategies in the areas of sleep stabilization, fatigue management, physical exercise, nutrition, relaxation protocols, and behavioral activation are outlined along with practical strategies for implementing intervention modules with patients.
The Impact of Agricultural Digitization on Land Productivity: An Empirical Test Based on Micro Panel Data
Authors: Zhang Hongming , Zhu Haihua
Published: January 2025

Digital technology has transformed agriculture by changing traditional production methods and resource allocation. This paper investigates how agricultural digitization affects land productivity, based on farm household data. Findings indicate that agricultural digitization significantly enhances land productivity, with results remaining robust under sensitivity and endogeneity tests. Heterogeneity analysis reveals that the positive effects are more pronounced for larger landholdings, lower levels of human capital, and older farming populations. Mechanism analysis indicates that agricultural digitization improves land productivity by optimizing resource allocation, reducing pollution, enhancing risk resilience, and facilitating the adoption of new technologies. These findings provide valuable insights for developing countries pursuing agricultural digital transformation.
Empowering Humanitarian Efforts: A Dynamic Approach to Competitive Intelligence (CI)
Authors: Ahatsi Emmanuel , Nie Lin , Olanrewaju Oludolapo Akanni
Published: January 2025

Background: The article examines the adoption of competitive intelligence (CI) in Ghana’s humanitarian sector, identifying barriers such as resource limitations and organizational challenges, while highlighting CI’s potential to enhance decision-making, partnerships, and efficiency. Methods: The study adopted a mixed-method research approach. Survey questionnaires and interviews were conducted with 34 humanitarian organisations in Ghana as part of the study. Results: The study established that, few humanitarian organisations in Ghana are practising CI. Many organisations have no established and specific procedures and staff for CI. The main challenges organisations experience when implementing CI include limited resources, especially in funding, lack of skilled workforce, and limited technological support. Other challenges include the organisational culture, lack of support from organisational leadership, and competing priorities. However, the study re-vealed the benefits and opportunities of CI for Ghana’s humanitarian sector, which include better decision-making and resource utilisation, cooperation and partnerships, flexibility and prepared-ness, and organisational efficiency and outcomes. Conclusion: The study concluded that the human-itarian organisations in Ghana will need to address the challenges mentioned above and build on those opportunities to harness the potential of CI effectively. Some suggestions include the sensitisation of CI, resource mobilisation, capacity development, culture change, and CI institutionalisation.