bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Soil Fertility in Alpine Shrub Communities of the Qilian Mountains, Northwest China
Authors: Ma Jian , Feng Qi , Li Guang , Liu Wei , Chen Peng , Li Ning , Qian Wanjian , Teng Yufeng , Li Xiaopeng , Li Jing
Published: February 2025

Understanding soil fertility is significant for the restoration and scientific management of shrub vegetation in the Qilian Mountains. This study focused on the soils associated with five common alpine shrub species—Salix gilashanica, Potentilla fruticosa, Caragana jubata, Caragana tangutica, and Berberis diaphana. We examined soil fertility characteristics, analyzed the relationships among soil fertility indicators, and evaluated the comprehensive fertility status of soil within shrub communities using principal component analysis. The results indicated that (1) the mean values of soil organic matter, total nitrogen, and total phosphorus were 77.94, 3.85, and 0.74 g kg−1, respectively; (2) the soil organic matter and total nitrogen content were significantly higher than the national averages, while the total phosphorus content was slightly lower; and (3) the soil pH and total potassium showed weak variability, the total phosphorus content exhibited moderate variability, and other nutrient indicators (including soil organic matter, total nitrogen, alkali-hydrolyzable nitrogen, available phosphorus, available potassium, soil bulk density, and soil water content) exhibited strong variability. Soil organic matter exhibited a significant positive correlation with total nitrogen, alkali-hydrolyzable nitrogen, and soil water content but negatively correlated with soil pH and bulk density. Total nitrogen was positively correlated with alkali-hydrolyzable nitrogen, available phosphorus, and soil water content but negatively correlated with soil pH and soil bulk density. Total phosphorus demonstrated a positive correlation with total potassium and soil bulk density, whereas total potassium was negatively correlated with available phosphorus. The order of soil fertility of the five communities was Salix gilashanica > Potentilla fruticosa > Berberis diaphana > Caragana jubata > Caragana tangutica. The soil fertility index, based on PCA, indicated that Salix gilashanica exhibited the highest fertility status. The findings of this study provide a theoretical reference for the restoration and reconstruction of shrub vegetation, the enhancement of soil fertility, and the improvement of fragile ecosystems in the Qilian Mountains. It also provides essential insights for soil restoration and sustainable ecosystem management in alpine environments.
How Do Waterbird Communities Respond to Multi-Scale Environmental Variables in the Satellite Wetlands Surrounding a Ramsar Site, Shengjin Lake in China?
Authors: Pan Chengrong , Xu Sheng , Qian Zhenbing , Liao Qichen , Wu Tongxinyu , Wang Guangyao
Published: February 2025

The global degradation and loss of natural wetlands are increasingly threatening wetland-dependent taxa, particularly waterbirds, which are highly vulnerable to environmental changes. In response to these threats, an increasing number of waterbirds are relocating to surrounding satellite wetlands in search of compensatory habitats. However, how waterbirds utilize these satellite wetlands and respond to varying environmental variables remain poorly understood. In the winter of 2022–2023 and summer of 2023, we conducted surveys on waterbird assemblages in 49 satellite wetlands of different types (reservoirs, aquaculture ponds, paddy fields and natural ponds) surrounding Shengjin Lake, a Ramsar site, and analyzed the relationship between community metrics and environmental factors. Large numbers of waterbirds were recorded during both summer and winter, including several threatened and nationally protected species. Species richness and number of individuals varied significantly across wetland types, with aquaculture ponds supporting the highest number of species and individuals. These two metrics showed positive correlations with wetland areas and landscape connectivity in both seasons. Species richness was also positively correlated with habitat diversity in summer. The number of individuals was positively correlated with habitat diversity and negatively with distance to human settlements, but the pattern was in contrast to that in winter. The Shannon–Wiener diversity index displayed a similar pattern among wetland types in winter but did not in summer. We detected no effects of environmental factors on the diversity index. Species composition differed markedly between wetland types in both seasons, especially between reservoirs and aquaculture ponds. To safeguard waterbird communities in the middle and lower reaches of the Yangtze River, we recommend integrating surrounding satellite wetlands into the regional wetland network and reducing human disturbances, particularly during the winter months.
Virtual Reality, Augmented Reality, and Mixed Reality in Experiential Learning: Transforming Educational Paradigms
Authors: Crogman Horace T. , Cano Victor D. , Pacheco Edlyn , Sonawane Rohan B. , Boroon Reza
Published: February 2025

Virtual reality (VR), augmented reality (AR), and mixed reality (MR) have impacts on experiential learning, redefining educational paradigms through immersive and interactive environments. By integrating extended reality (XR) technologies, learners can transcend traditional barriers to engage with dynamic simulations, historical recreations, and scientific visualizations that enhance engagement, comprehension, and retention. This research reviews the existing literature, highlighting the benefits of XR in fostering critical thinking, collaboration, and practical skill development while addressing challenges such as accessibility, cost, and cognitive overload. Empirical findings from a mixed-methods approach, including case studies, faculty training programs, and pilot classes, underscore XR’s efficacy in improving student performance, engagement, and inclusivity. This paper concludes by emphasizing XR’s potential to revolutionize experiential learning, fostering authentic, memorable, and transformative educational experiences across disciplines.
The Limits of the Current Consensus Regarding the Carbon Footprint of Photovoltaic Modules Manufactured in China: A Review and Case Study
Authors: Mariutti Enrico
Published: February 2025

A transition to low-carbon energy sources is pivotal in addressing the escalating challenges of climate change and environmental degradation. Solar energy, particularly photovoltaic (PV) technology, stands out as a prominent solution because of its potential for clean and sustainable electricity generation with minimal greenhouse gas emissions. However, accurately assessing the carbon footprint of PV modules is essential for guiding policy, industry practices, and research. This paper reviews the state of the current literature and highlights the difficulties in estimating the carbon footprint of PV modules manufactured in China. It emphasises the inherent limitations of Process-Based Life Cycle Assessments (PLCAs), including data collection challenges, dynamic environmental changes, and subjective methodological choices. Through the case study of Ecoinvent 3.7 the study underscores the need for improved transparency, standardisation, and reproducibility in Life Cycle Assessments (LCAs) to provide more accurate and reliable environmental impact evaluations.
The Effect of Economic Freedom, Indicators of Financial Sector Development, Income and Education on Renewable Energy Use: An Empirical Analysis of Post-Transition EU Member States
Authors: Sart Gamze , Bayar Yilmaz , Danilina Marina
Published: February 2025

Fossil fuels are among the most crucial factors underlying global environment impairment through CO2 emissions. In addition to this, the globalized world has witnessed significant price volatility, instability and disruptions in the supply of fossil fuels. Therefore, renewable energy transition (RET) has become a mandatory option for countries to tackle these environmental, economic, and energy insecurity problems in energy markets dominated by fossil fuels. But the RET process has remarkably slowed down in recent years due to increasing economic volatility, financial obstacles, geopolitical risks, and bottlenecks in the development of low-carbon technologies. In this regard, this study investigates the effect of market structure proxied by economic freedom and indicators of financial development, together with real GDP per capita and education, on the utilization of renewable energy in post-transition EU member states across the 2000–2021 duration by utilizing causality and cointegration tests. The outcomes of the causality analysis reveal a feedback relationship among renewable energy use, economic freedom, indicators of financial development, and real GDP per capita but a unilateral causality between education and renewable energy use. On the other hand, the outcomes of AMG estimation reveal a positive effect of economic freedom, real GDP per capita, and education on the utilization of renewable energy in some countries but a negative effect of financial institutions’ development on renewable energy use and mixed results on the effect of financial markets’ development regarding renewable energy use. Our results indicate that education is a significant instrument to make progress in renewable energy use via multiple channels, but governments should incentivize the financial system to support the RET process by favorable lending and sustainable finance instruments like green bonds or sustainability-linked loans.
Multi-Objective Optimization of Daylighting–Thermal Performance in Cold-Region University Library Atriums: A Parametric Design Approach
Authors: Gao Yunong , Zhao Shuting , Huang Yong , Pan Hui
Published: February 2025

Open atrium spaces in university libraries have emerged as a prevalent architectural trend. While increasing daylighting through enlarged glazing areas enhances the indoor environment, it simultaneously introduces significant thermal challenges in cold regions where environmental comfort demands lead to higher energy loads. This study investigates the optimization of daylighting–thermal performance balance through a multi-objective parametric approach to address the inherent conflicts between environmental quality and energy efficiency in atrium design. In this paper, we take the library project in the cold region as a practical case, use the measured data to support the simulation experiment, combine the parametric platform and multi-objective coupling optimization algorithm to carry out digital modeling, and explore the dynamic relationship between the atrium light, heat environment, and the value of energy consumption under the influence of a variety of parameters. The experimental results show that the quality and energy efficiency of the atrium light environment are improved after parameter optimization. The energy consumption per unit area (EUI) is reduced by 84.84 kwh/m2–106.83 kwh/m2 while the adequate natural illuminance (UDI) is increased by 5.06–27.64%, which confirms the feasibility of the research and development of the building light–heat coupling optimization technology route and program module. This paper aims to explore the quantitative law of design elements on light–heat balance at the early stage of architectural design and to provide a theoretical basis and reference blueprint for improving the comprehensive decision-making ability of architects in sustainable design and realizing integrated and efficient program decision-making.
A Novel Hydrogen Leak Detection Method for PEM Fuel Cells Using Active Thermography
Authors: Totaro Martina , Santonocito Dario , Risitano Giacomo , Barbera Orazio , Giacoppo Giosuè
Published: February 2025

Hydrogen leakage in Proton Exchange Membrane (PEM) fuel cells poses critical safety, efficiency, and operational reliability risks. This study introduces an innovative infrared (IR) thermography-based methodology for detecting and quantifying hydrogen leaks towards the outside of PEM fuel cells. The proposed method leverages the catalytic properties of a membrane electrode assembly (MEA) as an active thermal tracer, facilitating real-time visualisation and assessment of hydrogen leaks. Experimental tests were conducted on a single-cell PEM fuel cell equipped with intact and defective gaskets to evaluate the method’s effectiveness. Results indicate that the active tracer generates distinct thermal signatures proportional to the leakage rate, overcoming the limitations of hydrogen’s low IR emissivity. Comparative analysis with passive tracers and baseline configurations highlights the active tracer-based approach’s superior positional accuracy and sensitivity. Additionally, the method aligns detected thermal anomalies with defect locations, validated through pressure distribution maps. This novel, non-invasive technique offers precise, reliable, and scalable solutions for hydrogen leak detection, making it suitable for dynamic operational environments and industrial applications. The findings significantly advance hydrogen’s safety diagnostics, supporting the broader adoption of hydrogen-based energy systems.
Energy-Oriented Economic Evaluation of Phase Shifters Utilizing Risk-Adjusted Lifecycle Cost Analysis
Authors: Cai Hui , Qi Wanchun , Peng Zhuyi , Zou Jie , Sun Wentao , Zhu Ying , Han Xingning
Published: February 2025

In response to the growing need for efficient and sustainable energy systems, phase shifters are pivotal in enhancing the flexibility and reliability of power grids while facilitating the integration of renewable energy sources. This paper conducts a comprehensive economic evaluation of various phase shifter technologies, including symmetrical dual-core mechanical phase shifters, electronic phase shifters, and controllable phase shifters, using a lifecycle cost (LCC) analysis framework tailored for the energy sector. The assessment employs probability distributions and Monte Carlo simulation methods to analyze their economic performance, considering key energy-related cost factors such as initial investment, operational efficiency, maintenance, and decommissioning. An uncertainty analysis is introduced to refine the accuracy of LCC calculations, while sensitivity analysis highlights the influence of cost fluctuations—especially in initial investment and operating costs—on overall performance. The results reveal that while large-capacity phase shifters involve higher upfront costs, their superior operational efficiency and lower long-term unit costs can provide substantial economic advantages for sustainable energy applications. These findings offer valuable insights for optimizing energy equipment selection and guiding investment decisions in the transition toward greener and more resilient energy systems.
Fine-Grained Fish Individual Recognition in Underwater Environments Using Global Detail Enhancement and Keypoint Region Fusion
Authors: Zhao Yidan , Chen Ming , Feng Guofu , Zhai Wanying , Xiao Peng , Huang Yongxiang
Published: February 2025

With the rapid advancement of intelligent aquaculture, precise individual identification of underwater fish has become a crucial method for achieving smart farming. By accurately recognizing and tracking individuals within the same species, researchers can enable individual-level identification and tracking, significantly enhancing the efficiency of research and management. To address the challenges of complex underwater environments and subtle differences among similar individuals that affect recognition accuracy, this paper proposes a fish individual identification method based on global detail enhancement and keypoint region fusion. This method simultaneously learns global refined features and keypoint region features, dynamically capturing effective keypoint features while mitigating errors caused by noise through weighted fusion. The network first employs a global detail enhancement module to extract global features, such as overall morphology and texture information, followed by the extraction of fine-grained features from keypoint regions. Through the weighted fusion, the network further emphasizes critical areas, thereby enhancing robustness and adaptability in complex underwater scenarios. This design effectively integrates global refined features and local keypoint features, providing comprehensive support for accurate fish individual identification. Experimental results show that the proposed method achieves mAP and Rank-1 scores of 89.7% and 95.3%, respectively, and demonstrates strong generalization capabilities in other fish identification tasks.
Forging Prawn and Salmon Flavours with Non-Animal-Based Ingredients
Authors: Luo Jiaqiang , Frank Damian , Arcot Jayashree
Published: February 2025

The development of plant-based seafood alternatives with authentic flavour profiles remains a significant challenge, limiting their appeal to seafood consumers. This study hypothesised that incorporation of flavour precursors including free amino acids, betaine, and long chain omega-3 fatty acids would enhance the flavour resemblance of plant-based prawn and salmon prototypes to their authentic seafood counterparts. Prototypes were analysed using headspace solid-phase microextraction gas chromatography–mass spectrometry and evaluated by a semi-trained sensory panel. Volatile analysis revealed 64 compounds across prototypes, with significant variations attributed to precursor combinations and thermal treatments. Frying enhanced volatile profiles, particularly in plant-based prawn prototypes fortified with all three flavour precursors, producing key prawn odourants, including pyrazines and trimethylamine. Notably, betaine pyrolysis under moderate cooking conditions was demonstrated as a potential pathway for trimethylamine formation, contributing to fish-like odours. Sensory evaluation showed that the final plant-based prawn prototype exhibited strong cooked crustacean and grilled notes, aligning with the observed volatile profile. While the salmon prototype displayed key salmon odourants, its cooked salmon odour was less pronounced, suggesting a need for a more robust flavouring strategy. This study highlights the potential of targeted flavour precursor formulations to improve the flavour quality of plant-based seafood alternatives, paving the way for their wider acceptance.
The Modulatory Role of Bioactive Compounds in Functional Foods on Inflammation and Metabolic Pathways in Chronic Diseases
Authors: Ma Zheng Feei , Fu Caili , Lee Yeong Yeh
Published: February 2025

Chronic diseases are major contributors to global morbidity and mortality. More than 70% of deaths worldwide are caused by chronic diseases, including cardiovascular diseases (CVDs), obesity, type 2 diabetes, and cancer. These diseases are characterised by chronic low-grade inflammation and metabolic dysregulation. Incorporating functional foods into daily diet has been suggested as a complementary strategy to promote health and lower the risk of non-communicable diseases. Functional foods, known as foods that confer health benefits beyond basic nutrition, have been reported to exhibit preventive and therapeutic benefits such as anti-inflammatory properties for human health. Therefore, the aim of this state-of-the-art review will synthesise the findings from recent and high-quality studies that investigated the modulatory role of some commonly reported bioactive active compounds, such as polyphenols, omega-3 fatty acids, probiotics, and prebiotics, in inflammation and metabolic pathways.
Challenges in Using the Official Italian Method to Detect Bovine Whey Proteins in Protected Designation of Origin Buffalo Mozzarella: A Proteomic Approach to Face Observed Limits
Authors: Della Cerra Federica , Esposito Mariapia , Caira Simonetta , Scaloni Andrea , Addeo Francesco
Published: February 2025

This study critically examines the limitations of the official Italian methodology used for detecting bovine adulteration milk in Protected Designation of Origin (PDO) Mozzarella di Bufala Campana (MdBC). This method focuses on the whey fraction of cheese samples, which comprises about 1% of total MdBC proteins, and is based on a high-performance liquid chromatography (HPLC) quantification of the bovine β-lactoglobulin A (β-Lg A) as a marker. Here, we have demonstrated that this official methodology suffers from measurement inconsistencies due to its reliance on raw bovine whey standards, which fail to account for β-Lg genetic polymorphisms in real MdBC samples and protein thermal modifications during cheesemaking. To overcome these limitations, we propose a dual proteomics-based approach using matrix-assisted laser desorption ionization (MALDI-TOF) mass spectrometry (MS) and nano-HPLC-electrospray (ESI)−tandem mass spectrometry (MS/MS) analysis of MdBC extracted whey. MALDI-TOF-MS focused on identifying proteotypic peptides specific to bovine and buffalo β-Lg and α-lactalbumin (α-La), enabling high specificity for distinguishing the two animal species at adulteration levels as low as 1%. Complementing this, nano-HPLC-ESI-MS/MS provided a comprehensive profile by identifying over 100 bovine-specific peptide markers from β-Lg, α-La, albumin, lactoferrin, and osteopontin. Both methods ensured precise detection and quantification of bovine milk adulteration in complex matrices like pasta filata cheeses, achieving high sensitivity even at minimal adulteration levels. Accordingly, the proposed dual proteomics-based approach overcomes challenges associated with whey protein polymorphism, heat treatment, and processing variability, and complements casein-based methodologies already validated under European standards. This integrated framework of analyses focused on whey and casein fraction enhances the reliability of adulteration detection and safeguards the authenticity of PDO buffalo mozzarella, upholding its unique quality and integrity.
Black Gram (Vigna mungo L.) Husk as a Source of Bioactive Compounds: An Evaluation of Starch Digestive Enzyme Inhibition Effects
Authors: Ngoc Dinh Chi Vo , Prabsangob Nopparat
Published: February 2025

This research recovered bioactive compounds from black gram husk (BGH, a by-product of sprout processing) using different ethanol concentrations and maceration times. Based on the results, the highest phenolic and saponin contents were recovered using an 80% ethanolic solution for 3 h, with the extract having both antioxidant and starch digestive enzyme inhibition effects. The major bioactive compounds present in the extract were gallic acid, gentisic acid, ferulic acid, and vitexin. The extract from BGH had an effective binding affinity to α-glucosidase, resulting in a potent ability of the extract to delay enzyme activity. Based on in vitro starch digestion using cooked rice as a model, adding the extract (10 mg/mL) increased the resistant starch content (from 53.9% to 55.9%) and lowered the estimated glucose index (from 83.1% to 81.0%) as compared to the control without the extract. Based on the overall results, the BGH extract could be promising as a functional ingredient with antioxidant activity and the ability to control postprandial blood glucose levels in the development of healthy food products.
AS 314: A Massive Dusty Hypergiant or a Low-Mass Post-Asymptotic Giant Branch Object?
Authors: Bakhytkyzy Aigerim , Miroshnichenko Anatoly S. , Klochkova Valentina G. , Panchuk Vladimir E. , Zharikov Sergey V. , Mahy Laurent , Van Winckel Hans , Agishev Aldiyar T. , Khokhlov Serik A.
Published: February 2025

AS 314 (V452 Sct) is a poorly studied early-type emission-line star, which exhibits an infrared excess at wavelengths longer than 10 μm. Its earlier studies have been limited to small amounts of observational data and led to controversial conclusions about its fundamental parameters and evolutionary status. Comparison of high-resolution spectra of AS 314 taken over 20 years ago with those of Luminous Blue Variables and other high-luminosity objects suggested its observed properties can be explained by a strong stellar wind from a distant (D∼10 kpc) massive star, possibly in a binary system. However, a recent assessment of its low-resolution spectrum along with a new distance from a Gaia parallax (∼1.6 kpc) resulted in an alternative hypothesis that AS 314 is a low-mass post-asymptotic giant branch (post-AGB) star. The latter hypothesis ignored the high-resolution data, which gave rise to the former explanation. We collected over 30 mostly high-resolution spectra taken in 1997–2023, supplemented them with results of long-term photometric surveys, compared the spectra and the spectral energy distribution with those of post-AGB objects and B/A supergiants, and concluded that the observed properties AS 314 are more consistent with those of the latter.
Whole-Genome Selective Scans Detect Genes Associated with Cashmere Traits and Climatic Adaptation in Cashmere Goats (Capra hircus) in China
Authors: Dan Hongying , Zhong Hai’an , Akhatayeva Zhanerke , Lin Kejian , Xu Songsong
Published: February 2025

Background: Cashmere, valued for its exceptional softness and warmth, is a major focus in goat breeding due to its high economic importance. However, the molecular mechanisms underlying cashmere production remain largely unknown, hindering efforts to optimize yield and quality. Additionally, domestic goats exhibit remarkable adaptability to diverse climates, ranging from arid northern regions to humid southern areas, yet the genetic basis for these adaptations is poorly understood. Exploring the genetic factors driving cashmere production and climatic adaptation could provide crucial insights into trait evolution and support the development of breeding strategies for improved productivity and resilience. Methods: We utilized whole-genome resequencing data from 157 samples representing 14 goat populations to analyze the genetic diversity between cashmere and non-cashmere breeds. Additionally, we conducted the tests of selective sweeps (i.e., pairwise FST, θπ and XP-EHH) for cashmere traits and genome–environment association analysis (i.e., XtX statistic), respectively. Results: We identified strong selective signatures in previous reports (e.g., AKT3, FOXP1, FGF5, TGFBR3) and novel genes (e.g., ZEB1, ZNRF3, MAPK8IP3, MAPK8IP2, AXIN1) associated with cashmere traits. Further gene annotation and KEGG analyses showed that these genes were identified to be the most probable genes accounting for the cashmere traits. Also, we detected some genes such as PDGFRB, PRDM8, SLC26A2, SCAMP1, EPHX1, CDC25A, and POLK that played critical roles in the adaptation of goats to local climate variation. Conclusions: Collectively, our results provide novel insights into the genetic mechanisms underlying the cashmere traits and climatic adaptation, and also identified new genetic markers for genetic improvement in goats.
Identification of Genetic Relationships and Group Structure Analysis of Yanqi Horses
Authors: Wang Yaru , Tang Chi , Xue Pengfei , Yang Na , Sun Xiaoyuan , Serik Khizat , Assanbayer Tolegen , Shamekova Malika , Kozhanov Zhassulan , Sapakhova Zagipa , Khurramovich Jurakulov Kobil , Zhou Xiaoling , Kairat Iskhan , Muhatai Gemingguli
Published: February 2025

Background/Objectives: The Yanqi horse is a distinguished local breed in China, known for its robust physique and strong adaptability. However, due to insufficient breeding populations and a loosely structured breeding system, the number of Yanqi horses has been declining annually. To protect its genetic resources and develop scientific breeding strategies, this study aimed to analyze the genetic diversity, parentage relationships, and genetic structure of the Yanqi horse conservation population using microsatellite markers. Materials and Methods: A total of 117 Yanqi horses were selected for genotyping analysis using 16 microsatellite markers. Genetic diversity parameters (e.g., allele number, heterozygosity, F-statistics) were calculated using GeneAIEX (v.6.503) and Fstat software (v.2.9.4). Parentage analysis was conducted using Cervus software. Bayesian clustering analysis was performed using STRUCTURE software (v.2.3.4), and a phylogenetic tree was constructed based on Nei’s genetic distance to reveal the population genetic structure. Results: A total of 191 alleles were detected, with an average allele number of 11.969, observed heterozygosity of 0.481, and expected heterozygosity of 0.787. Parentage testing showed a cumulative exclusion probability (CEP) of 0.9652999 when one parent’s genotype was known and 0.9996999 when both parents’ genotypes were known, achieving an accuracy of 99%. Genetic differentiation analysis revealed moderate genetic divergence among populations (FST = 0.128) and moderate inbreeding levels (FIS = 0.396). Bayesian clustering analysis (K = 4) indicated that the Yanqi horse population could be divided into four genetic clusters, reflecting the impact of geographical isolation on genetic structure. Conclusions: The Yanqi horse conservation population exhibits moderate genetic diversity, high accuracy in parentage identification, and moderate genetic differentiation and inbreeding. The findings provide a scientific basis for the conservation and sustainable utilization of Yanqi horse genetic resources. Future efforts should focus on strengthening conservation measures, optimizing breeding strategies, and further investigating the genetic background using genomic technologies to ensure the sustainable development of the Yanqi horse population.
Optimizing Model Performance and Interpretability: Application to Biological Data Classification
Authors: Huang Zhenyu , Mu Xuechen , Cao Yangkun , Chen Qiufen , Qiao Siyu , Shi Bocheng , Xiao Gangyi , Wang Yan , Xu Ying
Published: February 2025

This study introduces a novel framework that simultaneously addresses the challenges of performance accuracy and result interpretability in transcriptomic-data-based classification. Background/objectives: In biological data classification, it is challenging to achieve both high performance accuracy and interpretability at the same time. This study presents a framework to address both challenges in transcriptomic-data-based classification. The goal is to select features, models, and a meta-voting classifier that optimizes both classification performance and interpretability. Methods: The framework consists of a four-step feature selection process: (1) the identification of metabolic pathways whose enzyme-gene expressions discriminate samples with different labels, aiding interpretability; (2) the selection of pathways whose expression variance is largely captured by the first principal component of the gene expression matrix; (3) the selection of minimal sets of genes, whose collective discerning power covers 95% of the pathway-based discerning power; and (4) the introduction of adversarial samples to identify and filter genes sensitive to such samples. Additionally, adversarial samples are used to select the optimal classification model, and a meta-voting classifier is constructed based on the optimized model results. Results: The framework applied to two cancer classification problems showed that in the binary classification, the prediction performance was comparable to the full-gene model, with F1-score differences of between −5% and 5%. In the ternary classification, the performance was significantly better, with F1-score differences ranging from −2% to 12%, while also maintaining excellent interpretability of the selected feature genes. Conclusions: This framework effectively integrates feature selection, adversarial sample handling, and model optimization, offering a valuable tool for a wide range of biological data classification problems. Its ability to balance performance accuracy and high interpretability makes it highly applicable in the field of computational biology.
The Potential of Transgenic Hybrid Aspen Plants with a Recombinant Lac Gene from the Fungus Trametes hirsuta to Degrade Trichlorophenol
Authors: Vidyagina Elena O. , Subbotina Natalia M. , Belova Eugenia N. , Kovalitskaya Yulia A. , Evdokimov Vyacheslav A. , Belyi Vladimir A. , Kochetov Alexey P. , Surin Alexey K. , Krutovsky Konstantin V. , Shestibratov Konstantin A.
Published: February 2025

Objective: Laccases are known to be able to degrade phenolic compounds to simpler components. The main objective of our study was to analyze this property in transgenic aspen plants carrying the laccase gene Lac from Trametes hirsuta which can be potentially used in soil phytoremediation. Methods: We created transgenic aspen plants carrying the laccase gene Lac from Trametes hirsute using the agrobacterial transformation of stem explants with the pBI–Lac vector containing the Lac gene from the white rot fungus T. hirsuta 072 (NCBI GenBank accession number KP027478). Transgenic plants were micropropagated and cultivated in vitro in lines. The degradation of 2,4,6-trichlorophenol (2,4,6-TCP) by plant roots was analyzed by mass-spectrometry with electron ionization using a gas chromatograph. Results: Although plants have their own laccases, those of fungal origin are more effective. All transgenic plants that expressed the recombinant gene degraded 2,4,6-TCP more effectively than non-transformed plants in the control (the degradation efficiency ranged 92 to 98% versus 82% in non-transformed control). Line 47Lac8 demonstrated a 16% higher efficiency than the non-transformed plants in the control. There was also an inverse relationship between the viability of a transgenic line and its level of expression of the recombinant gene. Thus, line 47Lac4 was not viable under native conditions, probably due to lignin synthesis disruptions during the initiation of secondary tissues. This is confirmed by changes in the expression of native genes of lignin biosynthesis. The rest of the transgenic lines did not differ significantly from control in wood growth and biochemistry. The transgenic plant roots were shown to preserve the ability to express the Lac gene ex vitro. Conclusions: Three transgenic lines (47Lac5, 47Lac8, and 47Lac23) with the Lac gene can be recommended for use in soil phytoremediation.
Exploring Nurses’ Knowledge of and Attitudes Towards the Management of Patients with Heart Failure in Saudi Arabia: A Cross-Sectional Design
Authors: Alshammari Bushra , Alanazi Layla , Dardouri Maha , Aouicha Wiem , Tlili Mohamed Ayoub , Alkubati Sameer A. , Alrasheeday Awatif , Almuaiqli Ali Mohammed , Alqahtani Abdulaziz Saeed , Alanazi Mohammad Saud , Alshammri Azizah Dhaher , Alanazi Fatimah Mansour , Alshammrey Najah Sayel , Motakef Hajer I. , Alshammari Farhan
Published: February 2025

Background: Heart failure (HF) is a significant health burden associated with severe morbidity, mortality, and hospitalization costs and it poses challenges not only to individuals and their families but also to societal and governmental resources. In fact, nurses are indispensable in managing HF patients. The success of patient self-care preparation through education relies not only on the patient’s abilities and attitude but also on the nurse’s proficiency in these tasks and their knowledge and attitudes can significantly impact patient outcomes. This study aimed to evaluate nurses’ knowledge and attitudes regarding HF management in Saudi Arabia. Methods: A cross-sectional survey was conducted among a convenience sample of 218 nurses employed at King Fahad Specialist Hospital in Tabuk, Saudi Arabia. Data were collected through an online questionnaire with two sections: one assessing nurses’ knowledge of HF management and the other evaluating their attitudes toward it. The data collection took place between March and June 2024. Results: Overall, 55% of nurses showed inadequate knowledge regarding HF management. Further analysis revealed that 46.8% of nurses had a negative attitude towards HF management. Multivariate analysis revealed that graduate nurses (bachelor or diploma) had significantly 4.48 times higher risk to produce inadequate knowledge of HF management in comparison to post-graduate nurses (OR = 4.48; CI 95% [2.18–9.21], p < 0.003). Regarding attitudes, nurses who did not receive previous training on HF management had a probability of 2.31 times to produce s negative attitude in comparison to nurses who received training (OR = 2.31; CI 95% [1.33–3.99], p = 0.003). Conclusions: The study underscores the need for educational programs, continuous professional development, promotion of positive attitudes, and fostering interdisciplinary collaboration to improve HF management. Future research should delve into the long-term impact of interventions, explore organizational factors, and investigate the relationship between knowledge, attitudes, and clinical practices.
Jatropha curcas Seed Germination: Effect of Seed Imbibition, Aging, Storage, and Salinity
Authors: Suarez-Padrón Isidro Elias , Pompelli Marcelo F. , Carlucci Claudia , Perneth-Montaño Marvin José , Ruiz Andrés José Betin , Seleiman Mahmoud F. , Alotaibi Majed , Almutairi Khalid F. , Oviedo Zumaque Luis Eliécer , Pineda-Rodríguez Yirlis Yadeth , Rodríguez-Paez Luis Alfonso
Published: February 2025

Renewable energy sources are essential to mitigating climate change, with biofuels offering a sustainable alternative to fossil fuels by reducing greenhouse gas emissions. Jatropha curcas, the best, non-edible, high-oil-yielding species, is a leading candidate for biodiesel production. However, ensuring a stable seed supply through effective storage is critical for biodiesel markets stability. This study evaluated the physiological and biochemical viability of J. curcas seeds stored at 4 °C with controlled humidity using 1.5 g of silica gel per gram of seed over 12 months. The results demonstrated that low-temperature, low-humidity storage significantly reduced metabolic activity, embryo respiration, and seed deterioration, preserving high germinability and oil quality. Despite a slight increase in mean germination time, seeds retained resilience in germination potential and viability. Additionally, preliminary assessments of salt tolerance revealed the potential of J. curcas seeds to germinate under saline conditions, supported by analyses of mineral nutrition and salt tolerance-related gene expression. These findings underscore the practicality of optimized storage conditions for maintaining seed quality and economic value, ensuring a consistent supply chain for biodiesel production. This study highlights the importance of integrating storage strategies into biodiesel systems to enhance sustainability and market resilience in the face of fluctuating production demands.
Comprehensive Analysis of High-Sensitive Flow Cytometry and Molecular Mensurable Residual Disease in Philadelphia Chromosome-Positive Acute Leukemia
Authors: de Azambuja Ana Paula , Mion Ana Lucia Vieira , Schluga Yara Carolina , Beltrame Miriam Perlingeiro , Senegaglia Alexandra Cristina , Funke Vaneuza Araujo Moreira , Bonfim Carmem , Pasquini Ricardo
Published: February 2025

Monitoring measurable residual disease (MRD) is critical for the management of B-cell acute lymphoblastic leukemia (B-ALL). While a quantitative assessment of BCR::ABL1 transcripts is standard for Philadelphia chromosome-positive cases (Ph+ ALL), a multiparameter flow cytometry (FCM) is commonly used for MRD detection in other genetic subtypes. A total of 106 B-ALL patients underwent genetic and phenotypic analyses. Among them, 27 patients (20 adults and 7 children) harbored the t(9;22)(q34.1;q11.2) translocation and/or the BCR::ABL1 rearrangement. A high correlation between the BCR::ABL1 transcript levels (PCR-MRD) and a standardized FCM-based method for MRD detection (FCM-MRD) was observed (r = 0.7801, p < 0.001), with a concordance rate of 88% (κ = 0.761). The FCM detected MRD in 82.9% of the samples with transcript levels of > 0.01%. The CD34+CD38−/dim blast pattern was significantly more frequent in Ph+ ALL (77.7%), compared to other B-ALL cases (20.2%, p < 0.0001). Additionally, Ph+ ALL exhibited a higher expression of CD66c+/CD73+ (94.0% vs. 56.9%), CD66c+/CD304+ (58.8% vs. 6.9%), and CD73+/CD304+ (75.5% vs. 15.5%) than the other B-ALL subtypes (p < 0.001). In conclusion, this high-sensitivity FCM-MRD demonstrated comparable performance to the PCR-MRD, serving as a complementary tool for MRD assessment in Ph+ ALL. Moreover, a distinct leukemia-associated immunophenotype was identified, highlighting potential biomarkers for MRD monitoring.
Therapeutic Mechanisms of Medicine Food Homology Plants in Alzheimer’s Disease: Insights from Network Pharmacology, Machine Learning, and Molecular Docking
Authors: Wen Shuran , Han Ye , Li You , Zhan Dongling
Published: February 2025

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by a gradual decline in cognitive function. Currently, there are no effective treatments for this condition. Medicine food homology plants have gained increasing attention as potential natural treatments for AD because of their nutritional value and therapeutic benefits. In this work, we aimed to provide a deeper understanding of how medicine food homology plants may help alleviate or potentially treat AD by identifying key targets, pathways, and small molecule compounds from 10 medicine food homology plants that play an important role in this process. Using network pharmacology, we identified 623 common targets between AD and the compounds from the selected 10 plants, including crucial proteins such as STAT3, IL6, TNF, and IL1B. Additionally, the small molecules from the selected plants were grouped into four clusters using hierarchical clustering. The ConPlex algorithm was then applied to predict the binding capabilities of these small molecules to the key protein targets. Cluster 3 showed superior predicted binding capabilities to STAT3, TNF, and IL1B, which was further validated by molecular docking. Scaffold analysis of small molecules in Cluster 3 revealed that those with a steroid-like core—comprising three fused six-membered rings and one five-membered ring with a carbon–carbon double bond—exhibited better predicted binding affinities and were potential triple-target inhibitors. Among them, MOL005439, MOL000953, and MOL005438 were identified as the top-performing compounds. This study highlights the potential of medicine food homology plants as a source of active compounds that could be developed into new drugs for AD treatment. However, further pharmacokinetic studies are essential to assess their efficacy and minimize side effects.
Development of Polymeric Nanoparticles Loaded with Phlomis crinita Extract: A Promising Approach for Enhanced Wound Healing
Authors: Kosksi Tahsine , Bustos-Salgado Paola , Rejeb Marwa , Selmi Arem , Debbabi Nawres , Espinoza Lupe Carolina , Sosa Lilian , Silva-Abreu Marcelle , Calpena Ana Cristina , Chekir-Ghedira Leila
Published: February 2025

The use of nanoparticles improves the stability, solubility, and skin permeability of natural compounds in skincare products. Based on these advantages, this study aimed to incorporate the Phlomis crinita extract into polymeric nanoparticles to improve its topical skin delivery for wound healing purposes. The study involved the preparation of nanoparticles of PLGA and PLGA-PEG (PCE-PLGA-NPs and PCE-PLGA-PEG-NPs) using the solvent displacement method, physicochemical and biopharmaceutical characterization, tolerance studies by the HET-CAM assay and evaluation of skin integrity parameters, and in vitro efficacy via a scratch wound healing experiment. The prepared nanoparticles were nanometer-sized with spherical form and demonstrated an encapsulation efficiency greater than 90%. The major component (luteolin) was released following a kinetic model of hyperbola for PCE-PLGA-PEG-NPs and one-phase exponential association for PCE-PLGA-NPs. Moreover, the important permeability of luteolin skin was observed, especially for PCE-PLGA-PEG-NPs. Both formulations exhibited no irritation and no damaging effects on skin integrity, suggesting their safety. Finally, the results of the scratch wound healing experiment using 3T3-L1 cells revealed significant cell migration and proliferation, with an improved efficacy for PCE-PLGA-PEG-NPs compared to the free extract, demonstrating the potential of this formulation in the treatment of wound healing.
Genetic Variants in Oxytocinergic System Genes and Their Association with Postpartum Depression Susceptibility
Authors: Ciolac Livia , Andreescu Nicoleta Ioana , Farcaș Simona Sorina , Bernad Elena Silvia , Tudor Anca , Nițu Dumitru-Răzvan , Popa Daian-Ionel , Maghiari Anca-Laura , Craina Marius Lucian
Published: February 2025

One of the most frequent forms of maternal morbidity following childbirth is postpartum depression. Postpartum depression (PPD), a disabling condition as a major public health concern, has a significant negative impact on the child’s emotional, mental as well as intellectual development if left undiagnosed and untreated, which can later have long-term complications. The oxytocin system is an excellent candidate gene system in the maternal context. Differences in vulnerability of mothers for the onset of postpartum psychiatric disorders could be influenced by individual differences in the genetic profile of each one. In this original research, we aimed to explore if there are any possible contributions of genetic variation on both the oxytocin receptor gene (OXTR) and the oxytocin gene (OXT) to the occurrence of postpartum depression, aiming to provide the latest evidence and determine which genetic polymorphisms significantly create a susceptibility for this condition. A total of 100 mothers were preliminarily genotyped before they completed the Edinburgh Postnatal Depression Scale Questionnaire (EPDS) at 6 weeks postpartum. DNA was extracted from peripheral blood samples of the participants (N = 100) and evaluated for the oxytocin gene (OXT_rs2740210; OXT_rs4813627) and oxytocin receptor gene (OXTR_ rs237885) single nucleotide polymorphisms. The results highlighted a significant interaction between the oxytocin OXT_rs2740210 genotype and maternal postpartum depression in mothers with the CC genotype but not in those with AA/AC genotypes. This reveals that an interaction of vulnerable genotypes (CC genotype of OXT_rs2740210, C allele in genotype of OXT_rs2740210, G allele in genotype of OXT_rs4813627) with an environmental burden or other risk factors would predispose the mothers to develop postpartum depression. We found no significant association between the interaction effect of the oxytocin receptor gene OXTR_rs237885 genotype depending on the occurrence of maternal postpartum depression. These findings prove the implication of the oxytocinergic system gene variants in vulnerability for postpartum depression and indicate the need for future studies adopting a multilevel approach in order to increase understanding.
Cocaine Differentially Affects Mitochondrial Function Depending on Exposure Time
Authors: Wattad Sahar , Bryant Gabriella , Shmuel Miriam , Smith Hannah L. , Yaka Rami , Thornton Claire
Published: February 2025

Cocaine use is a rising global concern, and increased use is accompanied by a significant increase in people entering treatment for the first time. However, there are still no complete therapies, and preclinical tools are necessary to both understand the action of cocaine and mitigate for its effects. Cocaine exposure rapidly impacts cellular and mitochondrial health, leading to oxidative stress. This study evaluated the effects of acute, repeated, and chronic cocaine exposure on C17.2 neural precursor cells. A single exposure to high concentrations of cocaine caused rapid cell death, with lower concentrations increasing markers of oxidative stress and mitochondrial dysfunction within 4 h of exposure. Alterations in cellular bioenergetics and mitochondrial fusion and fission gene expression (OPA1, DRP1) were also observed, which returned to baseline by 24 h after insult. Repeated exposure over 3 days reduced cell proliferation and spare mitochondrial respiratory capacity, suggesting compromised cellular resilience. Interestingly, chronic exposure over 4 weeks led to cellular adaptation and restoring mitochondrial bioenergetics and ATP production while mitigating for oxidative stress. These findings highlight the time-dependent cellular effects of cocaine, with initial toxicity and mitochondrial impairment transitioning to adaptive responses under chronic exposure.