bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of Socioeconomic Factors on Cognitive Ability in Community-Dwelling Older Adults: Mediating Effect of Social Participation and Social Support
Authors: Zheng Yiling , Zhang Yu , Ye Mingzhu , Wang Tingting , Guo Huining , Zheng Guohua
Published: February 2025

Background and Purpose: Previous studies have demonstrated the effect of socioeconomic status on the mental or cognitive health in adults. Nevertheless, the effect of specific socioeconomic factors on cognitive function in older people and the mechanism remain to be further investigated. In this study, three specific socioeconomic factors (i.e., income, occupation and education) were used as independent variables, and social support and social participation were used as the parallel or serial mediating variables to investigate the effect on cognitive function in community-dwelling older adults and the specific pathway of influence.
Methods: A cross-sectional study was conducted in the Pudong New District of Shanghai, China. A total of 970 community-dwelling older adults aged over 60 years old were enrolled. Socioeconomic factors in older adults, including income, education level, and occupation before retirement, were investigated, and their cognitive function, social support and social participation levels were measured using the MoCA, MSPSS and the quantity of participation in social activities, respectively. Covariates, including lifestyle, health status, sleep quality, and nutritional status, were assessed using a self-designed questionnaire, the PSQI, and the MNA-SF scale. Omnibus mediation effect analysis was adopted to examine the mediation effect, and the mediation analysis was performed using the SPSS PROCESS program.
Results: The results showed that the higher levels of socioeconomic conditions (income, occupational experience and education) were linked with better cognitive function in community-dwelling older adults; social participation mediated the aforementioned relationship, with the relative indirect effect of income, occupation and education accounting for 18.36%-20.15%, 28.36%-35.64% and 17.14%-39.19% of their total effects, respectively, compared to their low levels; social support only mediated the relationship of income and education with cognitive function, with the indirect effect accounting for 4.21%-6.77% and 5.29%-10.32%, respectively, compared to their low levels. Serial mediation showed that income and education affected social participation through social support and subsequently cognitive function, with the relative indirect effects accounting for 2.0%-3.3% and 2.4%-4.6% of their total effects, respectively, compared to their low levels.
Conclusion: This study demonstrates that social support and social participation independently and cumulatively mediate the relationship between socioeconomic conditions and cognitive function in community-dwelling older adults. The findings provide new insights for the future improvement of cognitive function in community-dwelling older adults in the future.
Comparison of Kalman filter and H-infinity filter for Battery State of Charge Estimation with a Detailed Validation Method
Authors: Milde Waleri , Kerle Laurin
Published: February 2025

Correct and reliable determination of the state of charge (SOC) of a lithium-ion battery is essential in today’s
applications. The SOC can be determined in different ways; there are simple methods such as integrating
the current over time (Coulomb counting) or mathematical filters, in particular the Kalman filter and the
H-infinity filter. In addition to the measured values, the latter two also require a battery model in which
the behavior of the battery is described under different temperatures, states of charge and currents. The
most common variants of the two filter techniques were compared: Extended, Adaptive Extended, Dualextended
and, for the Kalman filter, the Unscented Kalman filter. In this paper we present a comparison
method in order to objectively evaluate the different methods and thus make a suitable decision for the
respective application. In addition, the computing power of the individual methods is evaluated on a digital
signal processor. The comparison method uses various criteria and a rating scale. The individual criteria
are: Accuracy of estimation, temperature stability, transient behavior, residual charge determination and
drift behavior. Each state of charge algorithm undergoes the same test procedures and is evaluated on the
basis of the criteria. Three test procedures are used: a test for short-term behavior with low dynamics, a test
for short-term behavior and strong dynamics and a test for long-term behavior with different temperatures.
Based on the digital signal processor (DSP) implementation, it was shown that the runtimes depend on the
number of RC elements in the battery model. In all tests, the Kalman filter managed with fewer processor
cycles than its H-Infinity counterpart. The greatest deviations were observed at low temperatures. Overall,
both filters ran stably and the tests showed that neither filter was clearly superior to the other.
Impact of Fecal Microbiota Transplant Formulations, Storage Conditions, and Duration on Bacterial Viability, Functionality, and Clinical Outcomes in Patients with Recurrent Clostridioides difficile Infection
Authors: Shaheen Mohamed , McDougall Chelsea , Chan Leona , Franz Rose , Wong Karen , Gielbelhaus Ryland T. , Nguyen Gwen , Nam Seo Lin , de la Mata A. Paulina , Yeo Sam , Harynuk James J , Pakpour Sepideh , Xu Huiping , Kao Dina
Published: February 2025

Fecal microbiota transplantation (FMT) is the most effective therapy for preventing recurrent Clostridioides difficile infection (rCDI). However, the impact of FMT formulations and storage conditions on bacterial viability, community structure, functionality, and clinical efficacy remains under-investigated. We studied the effect of different storage conditions on bacterial viability (live/dead staining and cell sorting), community structure (16S rDNA analysis), and metabolic functionality (fermentation) of frozen and lyophilized FMT formulations. Clinical success rates of rCDI patients were correlated retrospectively with FMT formulations, storage durations, and host factors using the Edmonton FMT program database. Bacterial viability remained at 10%–20% across various storage conditions and formulations and was comparable to that of fresh FMT. Live and dead bacterial fractions in both frozen and lyophilized FMT preparations exhibited distinct community structures. Storage durations, but not temperatures, negatively affected bacterial diversity. More short chain fatty acids were found in metabolomic profiling of in vitro fermentation products using lyophilized than frozen FMT. Clinical success rates in 537 rCDI patients receiving a single dose of FMT were not significantly different among the three formulations. However, longer storage durations and advanced recipient age negatively impacted clinical efficacy. Together, our findings suggest that FMT formulations and storage durations should be considered when establishing guidelines for product shelf life for optimal treatment outcomes.
Integrating Renewable Energy, Wastewater Treatment, and Agroforestry: A Sustainable Green Village Model for Climate Adaptation in Oman
Authors: Al-Maskari Sultan , Ibrahim Bachar , Kramm Steven
Published: February 2025

Addressing socio-economic and environmental challenges in Dar Al Sawda, Oman, this study proposes a sustainable integrated resource management model that combines renewable energy, agroforestry, and advanced wastewater treatment. Using semi-structured interviews with community members and local experts, along with PVSyst simulations, the study identifies critical needs and introduces innovative solutions, including ReedBox technology for wastewater treatment and agri-photovoltaic systems integrating solar energy production with olive cultivation. The proposed system consists of two 15 m³ ReedBox units, treating approximately 26 m³ of wastewater per day, ensuring efficient water recycling for irrigation. Simultaneously, 300 olive trees are cultivated beneath elevated solar panels, enhancing crop yield and water conservation through shade provision. Simulation results confirm the system’s feasibility, generating 147,708 kWh of solar energy annually, with a specific yield of 1969 kWh/kWp/year and a performance ratio (PR) of 85.24%. This energy output is sufficient to power the wastewater treatment system and meet essential household electricity needs. This integrated approach enhances water efficiency, food security, and energy independence, offering a scalable and replicable model for sustainable development in arid and resource-limited regions.
The Effect of the Conformation Process on Physicochemical Properties of CMC/Starch Hydrogels
Authors: Vedovello Priscila , Paiva Robert Silva , Bortoletto-Santos Ricardo , Ribeiro Caue , Putti Fernando Ferrari
Published: February 2025

This study discusses the preparation of biopolymeric hydrogels (Biomaterial) via different techniques, such as casting and extrusion, to compare the effects of the process and the use of citric acid as a crosslinker on hydrogel morphology, physicochemical properties, and swelling degree. Casting is widely used for its low cost and space-saving nature, but up-scaling is problematic. Extrusion offers a way to produce materials in large quantities; these materials can undergo mechanical and thermal energy, which can significantly alter their properties. The samples obtained by extrusion had porous surfaces, which are critical for water penetration and swelling of superabsorbent hydrogels. In contrast, the hydrogels produced by casting did not form pores, resulting in a lower degree of swelling. Extrusion increased the swelling degree threefold due to the formation of pores, influencing water absorption and diffusion dynamics, especially in samples with higher starch content, where crosslinking occurred more effectively.
Economic importance of Aquaculture in Europe and in Spain: European Court of Auditors' Report on Aquaculture in the EU
Authors: Algarra-Paredes Angel , Ortega-Larrea Ana-Lucia , Bordonado-Bermejo María-Julia
Published: February 2025

Aquaculture is an economic activity aimed at producing and fattening aquatic organisms (animals and plants) in their environment. This activity includes the rearing of fish, molluscs, algae, and other aquatic organisms. It can be carried out in marine, brackish, or inland waters as well as in terrestrial installations equipped with water recirculation systems. The sustainable development of aquaculture (in environmental, economic, and social terms) is one of the main objectives of the EU Common Fisheries Policy (CFP). Consequently, the EU has been providing financial resources through specific programs for aquaculture to producer countries.
Transforming 3D MRI to 2D Feature Maps Using Pre-Trained Models for Diagnosis of Attention Deficit Hyperactivity Disorder
Authors: Hosseini Elahe , Hosseini Seyyed Ali , Servaes Stijn , Hall Brandon , Rosa-Neto Pedro , Moradi Ali-Reza , Kumar Ajay , Pedram Mir Mohsen , Chawla Sanjeev
Published: February 2025

According to the World Health Organization (WHO), approximately 5% of children and 2.5% of adults suffer from attention deficit hyperactivity disorder (ADHD). This disorder can have significant negative consequences on people’s lives, particularly children. In recent years, methods based on artificial intelligence and neuroimaging techniques, such as MRI, have made significant progress, paving the way for more reliable diagnostic methods than traditional clinical approaches. In this paper, we present our machine learning based analytical approach, more precisely, a novel feature extraction technique, to more accurately and reliably diagnose ADHD using clinically available neuroimaging data. Utilizing the ADHD200 dataset, which encompasses demographic factors and anatomical MRI scans in a diverse ADHD population, our study focuses on leveraging modern machine learning methods. The preprocessing stage employs a pre-trained Visual Geometry Group16 (VGG16) network to extract Two-Dimensional (2D) feature maps from anatomical 3D MRI data, thereby reducing computational complexity and enhancing efficiency. The inclusion of personal attributes, such as age, gender, intelligence quotient, and handedness, strengthens the diagnostic models. Four deep-learning architectures, Convolutional Neural Network 2D (CNN2D), CNN1D, Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU), were explored for the analysis of the MRI data, with and without inclusion of clinical characteristics. A 10-fold cross-validation revealed that the LSTM model, which incorporated both MRI data and personal attributes, had the best performance, achieving higher accuracy (0.8637) and area under the curve (AUC:0.9025). Our findings demonstrate that the proposed approach, which extracts 2D features from 3D MRI images and integrates these features with clinical characteristics, may be useful in diagnosis of ADHD with high accuracy.
Advances in Microbial and Plant Based Biopolymers: Synthesis and Applications in Next-Generation Materials
Authors: Kannan Drishya , Reddy M Venkateswar , Mohanakrishna Gunda , Sarkar Omprakash , Isha Isha , Rohit M V , Patel Aesha , Chang Young-Cheol
Published: February 2025

Biopolymers have made significant strides in recent years, driven by the increasing demand for sustainable alternatives to petroleum-based plastics. They are derived from renewable sources and are biodegradable, making them appealing solutions for addressing plastic waste and reducing environmental impact. In this direction, plant-based (lignin, cellulose) and bacterial (PHA) based biopolymers are gaining significant attention. These biopolymers are highly researched for innovations and technology development due to their demand in sustainable, renewable materials for a wide range of applications. The present review discusses the state of art in plant based and bacterial biopolymers in terms of bioproduction, downstream processing, high-end applications in next generation materials and scope of future applications. The challenges associated with cost of production, processing and scalability are also discussed. This review enables researchers in the bio-based space to visualize a broader perspective of plant based and bacterial biopolymers towards replacing petroleum-based products in a more sustainable and environmentally friendly interventions and envisages a paradigm shift a linear to a circular and bio based economy.
Can Generalist Predator Calosoma chinense Kirby Control Spodoptera frugiperda (J. E. Smith)?
Authors: Tian Caihong , Huang Jianrong , Zhang Junyi , Li Guoping , Yin Xinming , Feng Hongqiang
Published: February 2025

Abstract: Calosoma chinense Kirby is a generalist predatory that consumes multiple pests.To better elucidate the behavioral and ecological aspects of this species, we identified the field species and investigated the predation capacity of the third instar larvae and both sexes of adults against the first to six instar larvae, pupae, male and female adults of Spodoptera frugiperda.The predation choice for different developmental stage of S. frugiperda were further conducted. Our results showed that C. sinensis at different developmental stages could prey on S. frugiperda at various stages, especial to larvae and adults, which possess strong predatory abilities. Among them, female adults of C. sinensis exhibited the strongest predatory ability against S. frugiperda 1st instar larvae, with the highest daily consumption of 38.90 ± 0.79 individuals. 1st instar larvae of C. sinensis also showed a certain predatory ability towards S. frugiperda, with the daily consumption of 6.95 ± 0.88 1st instar larvae individuals of S. frugiperda per predator. The predation ability of C. sinensis larvae increased with instar, particularly for 1st to 3rd instar S. frugiperda larvae, C. sinensis female adults have the strongest predation ability, followed by male adults, and then the 3rd instar larvae. However, there was no significant difference in predation capacity between 4th to 6th instar larvae and male and female adults of S. frugiperda, nor between two sexes adults and 3rd instar larvae of C. sinensis. The predation choice experiment revealed that the 3rd instar larvae, male and female adults of C. sinensis showed a positive preference to S. frugiperda larvae from the 1st to 4th instar, while to the 5th to 6th instar exhibited a negative preference. Overall, C. sinensis exhibited a strong ability to prey on S. frugiperda, indicating it have the potential for application in biological control.
Cholesterol and SREBP2 Dynamics During Spermatogenesis Stages in Rabbits: Effects of High-Fat Diet and Protective Role of Extra Virgin Olive Oil
Authors: Avena María Virginia , Funes Abi Karenina , Monclus Maria Angeles , Boarelli Paola Vanina , Barbisan Luis Fernando , Bernal-López Rosa , Gomez-Huelvas Ricardo , Saez-Lancellotti Tania Estefanía , Fornes Miguel Walter
Published: February 2025

High-fat diets (HFDs) compromise male fertility, and cholesterol dysregulation is implicated. Sterol regulatory element-binding protein 2 (SREBP2), a key transcription factor that regulates cholesterol biosynthesis and uptake, is crucial in maintaining testicular cholesterol homeostasis. This study examined SREBP2 dynamics and cholesterol levels in rabbit spermatogenesis under HFDs. Our findings indicate that SREBP2 expression fluctuates throughout the seminiferous epithelium cycle, with HFDs inducing stage-specific disruptions in cholesterol balance, ultimately leading to the emergence of sperm with increased membrane cholesterol, reduced count, impaired motility, abnormal morphology, and decreased functionality. Interestingly, SREBP2 expression patterns in the control group revealed its critical role in normal spermatogenesis. Supplementation with extra virgin olive oil (EVOO) reversed these effects, normalizing SREBP2 expression, and cholesterol content and improving sperm quality. These findings highlight the importance of stage-specific analysis in understanding the impact of dietary fat on male fertility and suggest EVOO as a potential nutritional intervention to safeguard reproductive health.
Current Biomarkers in Non-Small Cell Lung Cancer (NSCLC)—The (Molecular) Pathologist’s Perspective
Authors: Steinestel Konrad , Arndt Annette
Published: February 2025

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality worldwide. Advances in tissue-based biomarkers have significantly enhanced diagnostic and therapeutic approaches in NSCLC, enabling precision medicine strategies. This review provides a comprehensive analysis of the molecular pathologist’s practical approach to assessing NSCLC biomarkers across various specimen types (liquid biopsy, broncho-alveolar lavage, transbronchial biopsy/ endobronchial ultrasound-guided biopsy and surgical specimen) including challenges such as biological heterogeneity and preanalytical variability. We discuss the role of programmed death ligand 1 (PD-L1) immunohistochemistry in predicting immunotherapy response, the practice of histopathological tumor regression grading after neoadjuvant chemoimmunotherapy, and the application of DNA- and RNA-based techniques for detecting actionable molecular alterations. Finally, we emphasize the critical need for quality management to ensure the reliability and reproducibility of biomarker testing in NSCLC.
Bayesian Model Averaging for Satellite Precipitation Data Fusion: From Accuracy Estimation to Runoff Simulation
Authors: Ning Shaowei , Cheng Yang , Zhou Yuliang , Wang Jie , Zhang Yuliang , Jin Juliang , Thapa Bhesh Raj
Published: February 2025

Precipitation plays a vital role in the hydrological cycle, directly impacting water resource management and the prediction of flood and drought risks. This study explores an approach by applying the Bayesian Model Averaging (BMA) algorithm to merge multiple precipitation datasets, aiming to improve the accuracy of precipitation estimates for hydrological simulations. The BMA framework combines four widely used precipitation datasets—CHIRPS, ERA5, GSMaP, and IMERG—across the Ganjiang River Basin in China from 2008 to 2020. To evaluate the performance of the merged dataset, researchers analyzed it alongside its individual components and the MSWEP dataset at daily, monthly, and seasonal scales. Several key metrics, including CC, RMSE, and KGE, were used for assessment. Additionally, the Variable Infiltration Capacity (VIC) hydrological model was employed to examine how these datasets influence runoff simulation. The results indicate that the BMA-merged dataset significantly enhances precipitation estimation accuracy compared to individual datasets. It achieved the highest CC (0.72) and KGE (0.70) at the daily scale and demonstrated superior seasonal performance, particularly in minimizing biases during autumn and winter. When applied to hydrological simulations, the BMA-driven VIC model closely mirrored observed runoff patterns, proving its effectiveness for long-term runoff predictions in the region. Overall, this study underscores the potential of the BMA approach to refine precipitation inputs for hydrological models, offering valuable insights for sustainable water resource management and risk mitigation in complex hydrological environments.
The Role of Genetic Factors and Its Relationship with Immunity in Asthma Associated with IBD Based on Integrated Bioinformatics Analysis
Authors: Tian Yu , Chen Liping , Lian Zhichuang , Yang Xiaohong , Wu Chao
Published: February 2025

The occurrence of asthma combined with IBD has been found in clinical practice, but the pathogenesis is not fully understood，this study is to use the bioinformatics technology to explore the related genes of asthma associated with IBD and its potential biological function. Transcriptomes dataset for asthma and IBD were screened by GEO data base. Cases in the datasets are divided into the case group and the control group. Differentially expressed genes with P<0.05 and | log2FC |>2 were selected. The intersected genes were used for GO and KEGG analysis. Cibersortx was used to analyze the relationship between differentially expressed genes and immune cells.ANXA3, TNFRSF21 and ZDHHC19 were significant in both pathogenesis of asthma and IBD. It was found that TNFRSF21 was positively correlated with plasma cells in asthma, negatively correlated with neutrophil function, and negatively correlated with NK cell activation in IBD. In conclusion, ANXA3, TNFRSF21, and ZDHHC19 were selected as the intersected genes associated with asthma and IBD, which may contribute to the development of the disease via cell membrane function and S-palmitoylation. The low expression of TNFRSF21 may lead to the disorder of immune function and the morbidity of patients with asthma associated with IBD.
Controlled Deep Breathing for Rapid Recovery from Hypoxia in Military Pilots and Aircrews
Authors: Rodríguez-Sequeira Alexander , Gallego-Saiz Jesús F. , Fernández-García José Carlos , Vicente-Arche-Navarro Álvaro
Published: February 2025

The objective of this research was to determine whether controlled deep breathing (CDB) versus uncontrolled spontaneous breathing (USB) in a normobaric hypoxia environment can increase exposure time in this environmental situation. For this purpose, military pilots and aircrew (n = 167), all of whom were male, underwent a normobaric hypoxia test. They were monitored with a pulse oximeter and subjected to a gradual exposure of up to 18,000 ft (rotary wing) and up to 25,000 ft (fixed wing). Prior to this test, they were briefed and the CDB protocol tested. Subjects using CDB spent more time in hypoxia than those using USB (12':20'' ± 1':28'' vs 9':44'' ± 1':36'', p<.000). For those who exceeded the altitudes of 18,000 ft and 25,000 ft, there were more participants and better percentages were detected, both in a pressurized and non-pressurized cabin, for CDB vs USB (350.76% and 268.88%, respectively). We therefore conclude that CDB can be considered a strategy to induce slower decompression in hypoxic situations in pilots and crew of military aircraft, thus helping to avoid fatal accidents.
Investigation of the Relationship Between Nursing Students' Worry Levels Regarding Climate Change and Sleep Quality
Authors: Bor Neşe Ataman
Published: February 2025

Climate change has an impact on the prevalence of insufficient sleep and sleep disorders. This study aimed to determine the levels of climate change-related worry and sleep quality among nursing students. This descriptive and cross-sectional study was conducted between August and September 2024. A total of 422 volunteer nursing students from seven universities in different regions of Turkey participated. Data were collected using the Personal Information Form, Climate Change Worry Scale (CCWS), and Pittsburgh Sleep Quality Index (PSQI). Statistical analyses included frequency, percentage, mean, standard deviation, Mann-Whitney U, Kruskal-Wallis, and Spearman correlation tests. The average CCWS score of the students was 33.22±11.14, and the average PSQI score was 6.39±3.46. Among the participants, 52.8% had poor sleep quality (PSQI ≥5). Gender, economic status, place of residence, climate change education, daily sleep duration, sleep latency, and smoking were identified as factors influencing CCWS and PSQI scores. A positive, moderate, and significant correlation was found between CCWS and PSQI scores(r=0.263; p<0.05). Nursing students had moderate levels of climate change-related worry and poor sleep quality. Educational programs and awareness campaigns aimed at enhancing knowledge about climate change could empower students to take action, reduce their worry levels, and improve their sleep quality.
Liar Sentence Mirroring Our Reasoning as Hegel’s Quasi-Speculative Sentence
Authors: Lee Jae
Published: February 2025

This paper explores parallels between the liar paradox and various aspects of philosophical reasoning. It begins by analyzing the liar sentence, highlighting its self-referential nature and alternating truth values. The paper then draws connections between the Liar and Hegel's speculative sentence, proposing it as a "quasi-speculative sentence" that mirrors dialectical reasoning. Subsequent sections examine the logocentric predicament and determinism, illustrating how they embody similar self-negating structures. The analysis sheds light on the underlying structure of our philosophical reasoning.
Grade 2 Listed Dwellings Sustainable Development: A Wall Replication Method with Slim Wheat Straw Panels for Heritage Retrofitting
Authors: Yasser Farres , Klalib Hynda Aoun , Elnokaly Amira , Ianakiev Anton
Published: February 2025

The urgent global mandate to achieve net-zero carbon emissions by 2030 has accelerated innovation in sustainable construction materials, particularly natural insulation solutions. This study addresses persistent challenges such as complex production processes, non-compostable components, and limited adherence to industry standards by developing and evaluating a novel slim insulation panel made from agricultural waste, specifically wheat straw. Targeted at retrofitting Grade 2 Listed dwellings in the UK—where external modifications are restricted—the panels combine simplicity, full compostability, and conformity with regulatory benchmarks. Prototypes were fabricated using wheat straw and two compostable binders, tested for thermal performance, moisture stability, and biodegradability using an innovative Actual Wall Replication Method (AWRM) to mimic real-world conditions. Findings demonstrated superior thermal conductivity and durability, with panels achieving significant energy-saving potential without compromising heritage integrity. The work highlights wheat straw's viability as an eco-friendly insulation material and accentuates the necessity of realistic testing for accurate performance assessment. This study offers a replicable framework for integrating circular economy principles into heritage retrofitting, bridging the gap between ambitious environmental targets and historic building preservation, thereby contributing to broader sustainable development goals.
Gender Disparities in Financial Inclusion: the Potential of Digital Loans in Empowering Female Health Entrepreneurs in Kenya
Authors: Ashubwe Jacklyne , Wanyama Maureen , Siyumbu Joseph , Zuijlen Ines van , Mutegi Nick , Verschuur Sabine , de Wit Tobias Rinke , Mulder Dorien , Janssens Wendy , Dieteren Charlotte
Published: February 2025

In Sub-Saharan Africa, female entrepreneurs are well-represented in healthcare but struggle to access financial services. Digital financing technologies could help close this gap. This study assessed the readiness, perspectives and gender disparities in (digital) loan characteristics among Kenyan health Small and Medium Enterprises (SMEs). We interviewed 24 and surveyed 410 health SME owners and analyzed loan-history data from 850 health SMEs to compare traditional and digital loans, focusing on gender disparities. IDIs identified low trust in digital lenders, while survey results indicated a strong demand for loans, regardless of gender. SME owners willing to take risks, with monthly financial needs and positive perceptions of digital loans were more likely to take a digital loan. Loan-history data showed a gender difference in the initial traditional loan amount, with women-owned businesses receiving less, but this gap disappeared for digital loans. Over 50% of women-led businesses using digital loans experienced significant growth, suggesting increased digital revenues linked to these loans. This study highlights the financing gap among Kenyan health SMEs and the potential of digital loans to enhance financial inclusion. Low trust in digital lenders, especially among those without direct experience, calls for better information dissemination to build confidence in digital financial products.
Fabrication of fusogenic and magnet-responsive cells for transplantation of an intact mitochondrial network
Authors: Xu Liqun , Li Xiao , Fan Xing , Yan Wei , Wu Wanfei , Li Junwei , Deng Ronghao , Zhu Haibao , Mao Aihua , Sun Pingnan , Zhang Xin , Xu Wencan , Chiju Wei
Published: February 2025

Background
Mitochondrial transplantation is a promising cure for many diseases associated with mitochondrial defects or ageing; however, a reliable method for mitochondria transfer is still in urgent need.
Method
In this study, we assembled fusogenic and magnet-responsive cells (FMRCs), which were enucleated stem cells loaded with Fe3O4 nanoparticles and further incorporated with fusogenic vesicular stomatitis virus glycoprotein G (VSV-G). Fusion was carried out in the presence of a magnetic force.
Results
Mitochondrial transplantation in the presence of a magnetic force via fusion from FMRCs restored normal mitotic activity, mitochondrial membrane potential, ROS levels and ATP production in cells containing partial mtDNA depletion, or in cybrids harboring mtDNA with a 4977-bp deletion. SNP tracing and qPCR analysis of the mitochondrial and nuclear genomes unequivocally demonstrated that exogenous mitochondria were able to reside stably and predominately. Mitochondria transplantation stimulated autophgy and thus the clearance of defective endogenous counterparts, resulted in lower mtDNA heteroplasmy.
Conclusion
The results suggest that FMRCs is an excellent vehicle for mitochondrial transplantation, which could be applied to the treatment of ageing and mitochondria associated diseases.
LTCONS_00014107-miR-29b-2-3p-GPR37 axis promotes heat stimulation induced esophageal carcinogenesis
Authors: Liu Wenting , Wang Jing , Qu Jiaping , Cheng Dan , Li Jiaqiong , Yeung Yiu To , Zhou Liting , Gao Yunfeng , Huang Hui , Dong Zigang , Li Xing
Published: February 2025

Esophageal cancer is a common malignant tumor of the digestive system, Esophageal squamous cell carcinoma (ESCC) is the major histological subtype of esophageal cancer. Multiple epidemiological evidence shows that consumption of hot temperature food and beverages is an important risk factor for developing ESCC, however, it is underlying mechanism remains unclear. Herein, for the first time, we constructed an animal model of esophageal precancerous lesions induced by heat stimulation in rats and simulated the human habit of eating hot food and drinks. Both LncRNA and miRNA expression of esophageal tissues were profiled by RNA-seq. We found LTCONS_00014107 was lowly expressed but miR-29b-2-3p was highly expressed in heat-induced ESCC and degradation of LTCONS_00014107 promoted the expression of miR-29b-2-3p since it is speculated that LTCONS_00014107 could be a precursor of miR-29b-2-3p. The functional study showed that knockdown miR-29b-2-3p could inhibit ESCC cell proliferation, whereas overexpression of miR-29b-2-3p could promote ESCC progression. Finally, through data analysis from the publicly available databases followed by verification using Dual-Luciferase assay, we found GPR37 could bind with miR-29b-2-3p and may be a potential target of miR-29b-2-3p. Overall, our research showed the function of LTCONS_00014107 in heat-induced ESCC and provided a theoretical and experimental basis of LTCONS_00014107-miR-29b-2-3p-GPR37 axis as the potential biomarkers and therapeutic targets in ESCC.
Navigating Chemical-Linguistic Sharing Space with Heterogeneous Molecular Encoding
Authors: Lv Liuzhenghao , Li Hao , Wang Yu , Yan Zhiyuan , Chen Zijun , Lin Zongying , Yuan Li , Tian Yonghong
Published: February 2025

Chemical language models (CLMs) are prominent for their effectiveness in exploring chemical space and enabling molecular design and engineering.
However, while exploring chemical-linguistic space, CLMs suffer from the semantic gap between natural language and molecular representations. This challenge is primarily due to the inherent modeling differences between molecules and texts: molecules operate unified modeling to learn chemical space, while natural language sequentially models their semantic space. Additionally, the limited availability of high-quality text-to-molecule datasets further exacerbates this challenge.
To address the problem, we first verified the information bias in molecular representations from different perspectives.
We then developed the Heterogeneous Molecular Encoding (HME) framework, a unified molecular encoder compressing the molecular features from fragment sequence, topology, and conformation with Q-learning.
To better model chemical-linguistic space, we further constructed the MCMoD dataset, which contains over one million molecules with various conditions, including properties, fragments, and descriptions.
Experimentally, HME promotes CLMs to achieve chemical-linguistic sharing space exploration from two aspects: (1) chemical space exploration with linguistic guidance, where HME achieves significant improvements (+37.8% FCD) for molecular design in multiple constraints, even in zero-shot learning scenarios; (2) linguistic space exploration with molecular guidance, where HME generates textual descriptions with high qualities (+11.6% BLEU) for molecules. These results highlight the precision of HME in handling multi-objective and cross-domain tasks, as well as its remarkable generalization capability on unseen task combinations.
HME offers a new perspective on navigating the chemical-linguistic sharing space, advancing the potential of CLMs in both fundamental research and practical applications in chemistry.
Exploring Barriers to AI Course Assistant Adoption: A Mixed-Methods Study on Student Non-Utilization
Authors: Hanshaw George , Sullivan Christopher
Published: February 2025

This research investigates the factors behind the non-utilization of the AI course assistant Spark among students at Los Angeles Pacific University (LAPU). Despite AI’s proven ability to enhance academic performance, motivation, and efficiency, a significant portion of students choose not to engage with this technology. Through a mixed-methods exploratory approach, key barriers to adoption are identified, including perceptions of unnecessity, lack of interest, and unfamiliarity with AI tools. External challenges, such as technical issues and a preference for traditional learning methods, are also examined. By combining sentiment analysis with thematic analysis of student survey responses, the findings offer a comprehensive understanding of the reasons for non-use. Targeted strategies—improving communication about AI’s benefits, providing training to build familiarity, and integrating AI more seamlessly into coursework—are recommended to increase adoption. Addressing these barriers is crucial, as non-utilization not only limits individual academic growth but also undermines efforts to equip students with essential skills for an AI-driven future. This research contributes to the growing literature on AI in education and provides actionable insights for educators and institutions seeking to maximize the impact of AI on learning outcomes.
Technology enhanced health professions education (TEHPE) in Eastern and Southern Africa: a Needs Assessment
Authors: Chipamaunga Shalote Rudo , Prozesky Detlef , Kafumukache Elliot , Katowa-Mukwato Patricia , Dithole Kefalotse , Merwe Lynette van der , Owusu-Sekyere Samuel , Molwantwa Mmoloki Cornelius , Gwini Rudo
Published: February 2025

Background
The COVID-19 pandemic escalated the adoption and development of technology-enhanced health professions education during large-scale lockdown mandated in multiple countries. Although the use of technology is a hallmark of the education of healthcare professionals, including clinical education, challenges including poor availability, lack of skills and support for technology-enhanced learning and teaching are reported. This study aimed to assess the needs for technology enhanced health professions education in higher education institutions in Eastern and Southern Africa.
Methods
This was a descriptive, cross-sectional survey to yield quantitative and qualitative data from healthcare students, educators and managers. The Substitution, Augmentation, Modification, Redefinition Model, our conceptual framework, underpinned our study and served as an organizing framework.
Results
Twelve program directors, 35 educators and 264 students responded from undergraduate nursing and medical programs. The findings indicate that ‘Other technologies used’ were relatively few – only 89 instances were mentioned by 299 respondents, and of these 89 some were basic hardware (laptops, data projectors) and online data source, which could fall under one or more of the 13 types that were drawn from the literature and the individual experiences of the researchers. There was extreme variation (between programmes and institutions) in the use of technologies. This finding is best explained by variations in the way in which programmes are offered and ‘educator’ preferences – there is clearly no ‘one size fits all’. On reasons for using educational technology, there is wide variation between categories of respondent, programmes and institutions. The main obstacles to the use of technology include that staff and students lack the required skills; no training is available; poor connectivity; lack of hardware and of funds to buy software; and lack of online learning resources.
Conclusions
The information generated, in such detail was not available before and opens many opportunities for further research as well as for planning and implementing improvements in technology enhanced health professions education. Based on the data, we propose practical recommendations organized around: Infrastructure Development, Training and Capacity Building, Curriculum reviews to align with technology, Institutional Support and Policy Development, Collaboration and Resource Sharing and Addressing Equity and Inclusion.
JNK pathway suppression drives resistance to combination endocrine therapy and CDK4/6 inhibition in ER+ breast cancer
Authors: Caldon C. , Alexandrou Sarah , Lee Christine , Fernandez Kristine , Wiharja Celine , Eshraghi Leila , Reeves John , Reed Daniel , Portman Neil , Phan Zoe , Milioli Heloisa , Nikolic Iva , Cadell Antonia , Croucher David , Simpson Kaylene , Lim Elgene , Hickey Theresa , Millar Ewan , Alves Carla , Ditzel Henrik
Published: February 2025

Endocrine therapy in combination with CDK4/6 inhibition doubles the progression-free survival of patients with advanced ER + breast cancer, but resistance is inevitable, leaving patients with limited treatment options. Here, we performed unbiased genome-wide CRISPR/Cas9 knockout screens using ER + breast cancer cells to identify novel drivers of resistance to combination endocrine therapy (tamoxifen) and CDK4/6 inhibitor (palbociclib) treatment. Our screens identified the inactivation of JNK signalling, including loss of the kinase MAP2K7, as a key driver of combination resistance. We developed multiple CRISPR/Cas9 knockout ER + breast cancer cell lines (MCF-7 and T-47D) to investigate the effects of MAP2K7 and downstream MAPK8 and MAPK9 loss. MAP2K7 knockout increased metastatic burden in vivo and led to impaired JNK-mediated stress responses, as well as promoting cell survival and reducing senescence entry following endocrine therapy and CDK4/6 inhibitor treatment. Mechanistically, this occurred via loss of the AP-1 transcription factor c-JUN, leading to an attenuated response to combination endocrine therapy plus CDK4/6 inhibition. Furthermore, we analysed ER + advanced breast cancer patient cohorts and found that inactivation of the JNK pathway was associated with increased metastatic burden, and low pJNKT183/Y185 activity correlated with a poorer response to systemic endocrine and CDK4/6 inhibitor therapies. Overall, we demonstrate that suppression of JNK signalling enables persistent growth during combined endocrine therapy and CDK4/6 inhibition. Our data provide a pre-clinical rationale to screen patients’ tumours for JNK signalling deficiency prior to receiving combined endocrine therapy and CDK4/6 inhibition.
Group Therapy for Depression in People Living with HIV in Kampala, Uganda
Authors: Lofgren Sarah , Akinyange Vanessa , Arinda Anita , Sebuliba Raymond , Bond David J , Boulware David R , Nakasujja Noeline
Published: February 2025

Depression in people living with HIV (PWH) is associated with reduced medication adherence, viral suppression, and retention-in-care. In low-resourced settings, depression interventions are needed for PWH to improve outcomes.
We conducted a randomized trial at a large, public HIV clinic. We enrolled PWH who started HIV medications <3 months prior and had depression. We randomized participants 1:1 to either an 8-week group therapy intervention or enhanced usual care. We measured depression with the Patient Health Questionnaire (PHQ-9) and Hamilton depression rating scale.
Between 2021-2023, we enrolled 137 PWH. The median age was 30 years. The median CD4 count was 332 cells/mcL. Female participants made up 64%. Baseline depression metrics were not different between groups. Most subjects had mild depression. Moderate-severe depression (PHQ-9 >10) was present in 37% of the intervention group and 38% of the control group. At three months, we found that the percentage of mild depression was significantly lower in the intervention compared to the control (11% (5/47) versus 34% (21/62), p=0.005). By 6 months, depression metrics were not statistically different as depression had resolved in 3% (3/102). The change in PHQ-9 was significantly greater in the intervention group compared to the control group.
An 8-week group therapy depression intervention was successful in relieving depression in PWH at three months compared to enhanced usual care. Group therapy can be adapted to different settings and effectively improves mood in PWH. Further work is needed to adapt psychological interventions to different settings among people with HIV in low- and middle-income settings.
A Lightweight Algorithm for Steel Surface Defect Detection Using Improved YOLOv8
Authors: Ma Shuangbao , Zhao Xin , Wan Li , Zhang Yapeng , Gao Hongliang
Published: February 2025

In response to the issues of low precision, a large number of parameters and high model complexity in steel surface defect detection, a lightweight algorithm using improved YOLOv8 is proposed. Firstly, GhostNet is utilized as the backbone network in order to reduce the number of model parameters and computational complexity. Secondly, the MPCA((MultiPath Coordinate Attention, MPCA) attention mechanism is integrated to enhance feature extraction capabilities. Finally, the SIoU (Simplified IoU, SIoU) is used to replace the traditional CIoU loss function, which can make the anchor frame more fast and accurate in the regression process, to improve the stability and the robustness of detection. The experimental results indicate that these enhancements have led to a reduction of 37% in calculation amount for the improved YOLOv8n algorithm, a decrease of 32% in parameter count, and an increase in average detection accuracy (mAP) by 1.2%. This model achieves a balance between lightweighting and detection accuracy while providing a viable solution for deployment in computationally resource-constrained edge computing environments such as embedded systems and mobile devices.
Identification of Low Observable Targets in Through Wall Imaging(TWI) Using Parallel Analytical Compressive Sensing (PACS) method
Authors: Taslimi M. , Ebrahimzadeh A. , Zakeri B. , Andargoli S. M. Hesseini
Published: February 2025

Through Wall Imaging (TWI) can be implemented using compressive sensing (CS) with fewer measurements, and a real model scenario of TWI can be realized using the finite difference time domain (FDTD) method. We propose parallel analytical compressive sensing (PACS) method to improve dielectric objects detection through the wall. We also present an optimized convolutional perfectly matched layers (CPML) using artificial bee colony (ABC) algorithm to reduce low frequency harmonics reflection of the ultra-wide band (UWB) transmitted signal from CPML layers. The PACS method calculates the measurement matrix based on the local maximums of the received signals. This process involves converting the norm-1 cost function into norm-2, providing a closed form formula to solve the CS problem. Coherence condition is satisfied by singular value decomposition (SVD) of the measurement matrix which in turn reduces the hardware complexity of the receiver. Closed form formula is executed separately for each target using a novel algorithm and their answers are added up. The proposed method achieves a compression ratio of 15% and is compared with the CFAR-BP algorithm for different SNRs which demonstrates its performance accuracy.
Bioinspired Navigation Based on Distributed Mechanoreception in the Leech
Authors: Gill Jeffrey , Nichols Sebastian , Mota Bruno , Harley Cynthia , Taylor Brian
Published: February 2025

Water waves help aquatic animals locate environmental stimuli. While previous studies suggest that leech mechanoreceptors have evolved to respond to relevant wave frequencies, the underlying neural processing remains unclear. This work presents a simplified computational model that mimics leech goal seeking behavior in an agent-based simulation. A simulated leech was tasked with finding the source of an artificial water wave stimulus. The agent's distributed mechanoreceptor array detected wave motion, which was processed with a computational neuroscience Winner-Take-All (WTA) framework to generate motion commands. The computational model's performance aligned with data from animal experiments. The model also suggested how different patterns of sensor ablation or placement might affect navigation performance. Our model can complement animal experiments by enabling questions to be posed that are challenging to address with live animals. Our study may also provide insights into novel approaches for processing data from multiple sensors in man-made systems.