bluuebunny/crossref_metadata_2025 huggingface dataset:
Extracts from Tartary Buckwheat Sprouts Restricts Oxidative Injury Induced by Hydrogen Peroxide in HepG2 by Upregulating the Redox System
Authors: Li Xiaoping , Zhang Yuwei , Zhao Wen , Ren Tian , Wang Xiaolong , Hu Xinzhong
Published: November 2024

Oxidative stress, which results from an overproduction of reactive oxygen species (ROS), can cause damage that may contribute to a range of metabolic disorders. Antioxidants are considered to upregulate the activity of antioxidant enzymes, which are crucial for eliminating excess ROS and safeguarding the body against oxidative stress-induced damage. In the present study, the effect of polyphenol extracts from tartary buckwheat sprouts (TBSE) on the redox system of HepG2-cell-induced oxidative injury by hydrogen peroxide were investigated for evaluating the protective effect and mechanism of tartary buckwheat sprouts (TBS). The results revealed that TBSE that had sprouted for a period of 10 days possessed six predominant phenolic compounds, ranked from the most abundant to the least: chlorogenic acid, syringic acid, caffeic acid, rutin, ferulic acid, and quercetin. TBSE could successfully inhibit H2O2-induced ROS overproduction, restore and balance the mitochondrial membrane potential, while also significantly increasing cellular antioxidant activity (CAA) and the expression of protective enzymes such as SOD, CAT, and GST. More interestingly, treating HepG2 cells with TBSE triggered the translocation of Nrf2 to the nucleus, accompanied by a negative feedback mechanism involving Keap1. Therefore, it regulated the downstream production of antioxidant enzymes, including NQO1 and HO-1. Overall, this finding suggested that TBSE could restore the redox state of H2O2-resistant HepG2 cells, indicating TBSE protected cells from H2O2-induced oxidative stress significantly. Beneficial resistance and effects on redox balance were attributed to activation of Nrf2. Present work revealed the potential health benefits of TBS and provided a test basis for developing functional food of TBS.
Optimization Function for Determining Optimal Dose Range for Beef and Seed Potato Irradiation
Authors: Kozlova Elena , Bliznyuk Ulyana , Chernyaev Alexander , Borshchegovskaya Polina , Braun Arcady , Ipatova Victoria , Zolotov Sergey , Nikitchenko Alexander , Chulikova Natalya , Malyuga Anna , Zubritskaya Yana , Bolotnik Timofey , Oprunenko Anastasia , Kozlov Aleksandr , Beklemishev Mikhail , Yagudina Roza , Rodin Igor
Published: November 2024

The objective of this study is to develop a universally applicable approach for establishing the optimal dose range for the irradiation of plant and animal products. The approach involves the use of the optimization function for establishing the optimal irradiation dose range for each category of plant and animal product to maximize the suppression of targeted pathogens while preserving the surrounding molecules and biological structures. The proposed function implies that pathogens found in the product can be efficiently suppressed provided that irradiation is performed with the following criteria in mind: a high irradiation dose uniformity, a high probability of irradiation hitting pathogens and controlled heterogeneity of radiobiological sensitivity of pathogens. This study compares the optimal dose ranges for animal and plant products using beef tenderloin and seed potato tubers as examples. In a series of experiments, our team traced the dose dependencies of myoglobin oxidation in beef and the amount of potential damage to albumin’s native structure. The behavior patterns of myoglobin derivatives and the amount of potential damage to albumin found in this study determined the optimal dose range, which appeared to be wider for beef irradiation compared to that for seed potato tubers, as they do not require uniform irradiation of the entire volume since targeted phytopathogens are predominantly found within the surface layers of the tubers. The use of proprietary methods involving spectrophotometry and high-performance liquid chromatography–mass spectrometry provides a novel perspective on the quantitative assessment of the myoglobin oxidation level and the potential damage to albumin’s native structure.
Fifty Years After the Discovery of the First Stellar-Mass Black Hole: A Review of Cyg X-1
Authors: Jiang Jiachen
Published: November 2024

Around 50 years ago, the famous bet between Stephen Hawking and Kip Thorne on whether Cyg X-1 hosts a stellar-mass black hole became a well-known story in the history of black hole science. Today, Cyg X-1 is widely recognised as hosting a stellar-mass black hole with a mass of approximately 20 solar masses. With the advancement of X-ray telescopes, Cyg X-1 has become a prime laboratory for studies in stellar evolution, accretion physics, and high-energy plasma physics. In this review, we explore the latest results from X-ray observations of Cyg X-1, focusing on its implications for black hole spin, its role in stellar evolution, the geometry of the innermost accretion regions, and the plasma physics insights derived from its X-ray emissions. This review primarily focuses on Cyg X-1; however, the underlying physics applies to other black hole X-ray binaries and, to some extent, to AGNs.
Recent Advances of Cellulose-Based Hydrogels Combined with Natural Colorants in Smart Food Packaging
Authors: Yang Lan , Yuan Qian-Yu , Lou Ching-Wen , Lin Jia-Horng , Li Ting-Ting
Published: November 2024

Due to the frequent occurrence of food safety problems in recent years, healthy diets are gradually receiving worldwide attention. Chemical pigments are used in smart food packaging because of their bright colors and high visibility. However, due to shortcomings such as carcinogenicity, people are gradually looking for natural pigments to be applied in the field of smart food packaging. In traditional smart food packaging, the indicator and the packaging bag substrate have different degrees of toxicity. Smart food packaging that combines natural colorants and cellulose-based hydrogels is becoming more and more popular with consumers for being natural, non-toxic, environmentally friendly, and renewable. This paper reviews the synthesis methods and characteristics of cellulose-based hydrogels, as well as the common types and characteristics of natural pigments, and discusses the application of natural colorants and cellulose-based hydrogels in food packaging, demonstrating their great potential in smart food packaging.
Machine Learning Analysis of Borehole Data for Geotechnical Insights
Authors: Mitelman Amichai
Published: November 2024

This paper explores the use of machine learning (ML) to analyze borehole data aiming to enhance geotechnical insights, using the Gaza Strip as a case study. The data set consists of 632 boreholes, with features including spatial coordinates, ground level, and soil type per depth. A random forest (RF) classification model was applied to predict soil types, achieving an accuracy of approximately 75%. Notably, the model retained this accuracy even when the data set size was reduced to 30%, suggesting predictable subsurface conditions over large areas. A comparative analysis of common misclassifications revealed that errors mostly occurred between similar soil types, indicating the model’s ability to capture meaningful geological patterns. Unsupervised learning using k-means clustering revealed no clear-cut boundaries between clusters, indicating localized geological anomalies despite large-scale predictability. These findings align with the demonstrated stability of the Gaza Tunnel Network (GTN), a vast network of tunnels which was constructed without comprehensive site investigations. This study demonstrates the potential of ML to improve geotechnical assessments and suggests that fewer boreholes may be needed for large-scale projects, offering cost-saving opportunities. For future research, it is recommended to integrate advanced ML tools, including large language models (LLMs) for analyzing qualitative data from borehole logs, and interpretability methods to enhance model explainability, thus enhancing geological understanding and increasing predictive power.
Professional Nurses’ Views and Experiences of Poor Health-Seeking Behavior Among Men in Limpopo Province, South Africa
Authors: Chavalala Lazarros , Lebese Rachel Tsakani , Makhado Lufuno
Published: November 2024

Background/Objectives: The health-seeking behavior of men is a public health concern and is associated with poor health outcomes and lower life expectancy among men. Masculinity norms are among the factors contributing to men’s poor health-seeking behavior. This study explored the views and experiences of purposively selected nurses on men’s health-seeking behavior. Methods: Through qualitative descriptive design, individual semi-structured interviews were conducted with 14 professional nurses, and collected data were audio recorded and transcribed verbatim. Tech’s eight steps were used to analyze data and guide the development of the main themes and sub-themes. Trustworthiness was ensured through credibility, confirmability, dependability, and transferability. Ethical approval was granted by the University of Venda Research ethics committee with reference number FHS/21/PH/26/1215. Results: Self-medication, a lack of trust in Western medicine, and the use of traditional healers were identified as reasons men underutilize health care services. Men were viewed as people who consult heath care services when illness is severe, feel uncomfortable with female nurses, and value respect from clinicians. Conclusions: Cultural norms still remain a barrier among men in this study setting, as men did not feel comfortable with their private parts being physically examined by female clinicians. There is a need to take note of cultural norms impacting health care service usage by men.
Approaches to Reach Trustworthy Patient Education: A Narrative Review
Authors: Lyu Xiafei , Li Jing , Li Sheyu
Published: November 2024

Background: Patient education is a cornerstone of modern healthcare. Health literacy improves health-related quality of life and health outcomes of patients, enhanced by effective patient education. Inadequate competency of patient education in healthcare providers triggered this review to summarize common approaches and recent advancements. Methods: This narrative review summarizes common approaches and recent advancements in patient education with their relations to health literacy, their strengths, limitations, and practical issues. Results: This review highlighted the multifaceted approaches to patient education, emphasizing the importance of tailoring methods to meet the diverse needs of patients. By integrating various strategies, including intrapersonal, interpersonal, and societal/community-level interventions, healthcare providers can create a more comprehensive educational experience that addresses the complexities of patient needs, meanwhile improving the health literacy of patients. With the rise of digital media and artificial intelligence, there is an increasing need for innovative educational resources that can effectively reach and engage patients. Ongoing research and collaboration among healthcare professionals and policymakers will be essential to refine educational strategies and adapt to emerging challenges. It is essential to remain vigilant about potential conflicts of interest that may compromise the integrity of educational content. Conclusion: Effective patient education empowers individuals and their contributions to a healthier society by fostering informed decision-making and encouraging proactive health management.
Dental Anomalies in Saudi Arabia: A Systematic Review
Authors: Aljohani Khalid , Shanab Hanan , Alqarni Ali , Merdad Khalid
Published: November 2024

Background: Epidemiological studies have shown varying prevalence rates of dental anomalies worldwide, ranging from 5.2% to 56.9%, with a higher rate of 90.4% in patients with cleft lip and palate. In Saudi Arabia, studies have also reported varied prevalence rates, likely due to genetic differences or sampling variations. However, no research has yet evaluated the quality of these studies or provided an overall prevalence estimate, which is the aim of the present study. This systematic review aims to assess the prevalence and types of dental anomalies across various regions of the Kingdom of Saudi Arabia (KSA). Methods: A comprehensive literature search identified 10 relevant studies on different dental anomalies in Saudi Arabia. The quality of the enrolled studies was assessed using the Newcastle–Ottawa Scale (NOS), showing variability in the methodological quality of the included cohort studies, with several studies demonstrating a moderate to high risk of bias. Results: Common anomalies included hypodontia, hyperdontia, microdontia, and impacted teeth. This study highlights the varying prevalence of dental anomalies in different regions of Saudi Arabia, ranging from 2.6% to 45.1%. Conclusions: This review highlights the need for early diagnosis and tailored treatment approaches to mitigate the clinical challenges posed by these anomalies, underscoring the importance of standardized diagnostic criteria and further research to understand regional and demographic differences in the prevalence of dental anomalies in Saudi Arabia.
Impacts of Square Stepping Exercise on Physical-Cognitive Function, Biomarkers, Body Composition and Mental Health in Healthy Senior Aged 60 and Above: A Systematic Review
Authors: Franco-García Juan Manuel , Carlos-Vivas Jorge , Castillo-Paredes Antonio , Mayordomo-Pinilla Noelia , Rojo-Ramos Jorge , Pérez-Gómez Jorge
Published: November 2024

Background: The aim of this systematic review is to analyze the effects of Square Stepping Exercise (SSE) on physical and cognitive function in older people, including its effects on biomarkers, body composition and mental health, focusing only on research that assessed the efficacy of SSE-based interventions. Methods: PubMed, Web of Science, Scopus and Cochrane databases were searched from June 2006 to June 2024 according to the PRISMA guidelines. The main search terms used were related to “older people” and “square-stepping exercise”. Controlled trials that included at least one intervention group focused on SSE were included. Participants had to be healthy, without physical or cognitive impairment, and the studies published in English or Spanish. The methodological quality of the selected research was assessed using the Physiotherapy Evidence Database (PEDro). Results: Twelve studies were selected from a total of 444 original records, with a total sample size of 577 participants. The health parameters of the participants were homogeneous, with ages ranging from 60 to 80 years. Significant gains were reported in certain physical function assessments, including balance, lower body strength and power, gait speed and flexibility. There were also significant findings in cognitive function, particularly in general cognitive status, focused attention, response time, basic task performance, and executive function. In addition, SSE can improve metrics such as body composition, brain-derived neurotrophic factor (BDNF), and mental health characteristics. Conclusions: SSE has the potential to significantly improve physical function, cognitive performance and body composition, as well as provide mental health benefits and have variable effects on biomarkers and cardiovascular health.
Validation of a Questionnaire to Assess the Usability of and User Experience with Mobile Health Applications
Authors: de Dios López Anna , Real Jordi , Meza Claudia , Borras-Santos Alicia , Collado-Borrell Roberto , Escudero-Vilaplana Vicente , Gomis-Pastor Mar
Published: November 2024

Background/objectives: The growing use of mobile health (mHealth) applications needs reliable tools to assess their usability and user experience in clinical practice to improve the digital health (eHealth) interventions and ensure engagement, as higher engagement is often linked to increased efficacy of healthcare interventions. This study aimed to validate the patient Satisfaction and Usability with APPs questionnaire (pSUAPP), a multidimensional tool designed for the comprehensive assessment of mHealth applications, particularly for the integrated follow-up of patients with chronic diseases. Methods: A validation study was conducted between August and December 2022 with 85 participants from two hospitals in Spain, who completed the pSUAPP questionnaire, comprising 27 Likert-like items across four dimensions: first contact, registration, features and overall experience, and 1 open question. The questionnaire was validated by a panel of 11 experts and further assessed for psychometric properties. Results: The mean pSUAPP score was 79.0 (SD = 12.0), indicating high usability and positive user experience, with the highest scores in the ‘features’ dimension. The pSUAPP demonstrated moderate correlation with the System Usability Scale (SUS) and high reliability (Cronbach’s alpha and omega t > 0.9). A reproducibility analysis showed negligible changes between repeated measures. Conclusions: The pSUAPP questionnaire was found to be a robust tool for evaluating mHealth app usability and user experience, with potential application across various clinical settings.
The Frontiers of Smart Healthcare Systems
Authors: Lin Nan , Paul Rudy , Guerra Santiago , Liu Yan , Doulgeris James , Shi Min , Lin Maohua , Engeberg Erik D. , Hashemi Javad , Vrionis Frank D.
Published: November 2024

Artificial Intelligence (AI) is poised to revolutionize numerous aspects of human life, with healthcare among the most critical fields set to benefit from this transformation. Medicine remains one of the most challenging, expensive, and impactful sectors, with challenges such as information retrieval, data organization, diagnostic accuracy, and cost reduction. AI is uniquely suited to address these challenges, ultimately improving the quality of life and reducing healthcare costs for patients worldwide. Despite its potential, the adoption of AI in healthcare has been slower compared to other industries, highlighting the need to understand the specific obstacles hindering its progress. This review identifies the current shortcomings of AI in healthcare and explores its possibilities, realities, and frontiers to provide a roadmap for future advancements.
The Heritage Building Information Modeling Methodology for Structural Diagnosis: An Integrated System of Digital Models for the Baptistery of San Giovanni in Pisa
Authors: Bartolini Giada , De Falco Anna , Gianfranceschi Lorenzo , Martino Massimiliano , Vignali Laura
Published: November 2024

The structural diagnosis of monumental buildings necessitates organizing diverse cross-disciplinary data. The H-BIM procedure employs 3D digital models to create a comprehensive virtual repository, offering advantages in documentation access, interoperability, intervention design, cost evaluation, and maintenance management. This work proposes an approach to combining different models while addressing interoperability challenges by best exploiting their positive characteristics. After evaluating the advantages and limitations of textured-mesh and NURBS-based models, and virtual reality environments based on specific comparison criteria, an integrated system of these models within the H-BIM framework is proposed. The latter is applied to study the relevant case of the Baptistery of San Giovanni in Pisa, Italy. The integrated H-BIM model is designed primarily to facilitate the structural diagnosis of the monument, and illustrates how combining different 3D representations, each providing multiple information with different levels of detail, enhances its capabilities. This integration results in a more effective tool for the multidisciplinary conservation of cultural heritage, accommodating a wide range of data beyond structural aspects, thus fostering collaboration among professionals from various fields of expertise.
Analysis of the Urban Transformations Derived from Railway Housing Construction in Spain During Francoism (1939–1975): An Underestimated Heritage in Use
Authors: Martínez-Corral Aurora , Cuéllar Domingo , Domínguez Rodrigo Tomás L.
Published: November 2024

Two essential characteristics of railway implementation are the large spaces of land occupied in the city and the need for workers. In Spain, both reasons and the post-war period led to the construction of many homes for employees throughout the country using different typologies, ensembles, dwelling designs, free spaces, mixed uses, and a relationship with the surrounding city. The present work presents a quantitative and qualitative analysis of these aspects, concluding on their impact on the current configuration of the urban environment of the cities where they are located and the possibility of urban regeneration that these developments offer. It is a housing stock that is 95% in use and that, in some cases, given the city’s growth, occupies privileged current urban positions that have led to its revaluation despite its construction characteristics. The research carried out provides the analysis of the entire country, accounting for and observing the great variety of existing case studies related to different sizes of populations, typologies, and locations (center–periphery), among others. The main conclusions reflect the total absence of urban or architectural approaches in implementing these homes, the lack of quality of the free or community spaces generated between blocks, and the absolute disinterest in the quality of life beyond providing housing for workers close to the workplace. At the antipodes of current approaches to the design of social housing and living conditions, this situation discourages the regeneration of these homes aligned with the objectives of the 2030 Agenda, making their heritage conservation difficult.
The Role of Alpha-Linolenic Acid and Other Polyunsaturated Fatty Acids in Mental Health: A Narrative Review
Authors: Bertoni Camilla , Pini Cecilia , Mazzocchi Alessandra , Agostoni Carlo , Brambilla Paolo
Published: November 2024

The present review investigates the relationship between polyunsaturated fatty acids (PUFAs) and mental health disorders, such as dementia, psychosis, schizophrenia, Alzheimer’s disease, anorexia nervosa, and impairment problems in animals and human models. Data were collected from a variety of studies: randomized intervention trials, observational and interventional studies, case reports, and epidemiological studies. The evidence suggests that PUFAs are beneficial for mental health, brain function, and behavior. ALA, EPA, and DHA have very significant neuroprotective properties, particularly in inducing changes to the synaptic membrane and modulating brain cell signaling. In the case of neurodegenerative disorders, PUFAs incorporated into cellular membranes have been shown to protect against cell atrophy and death. The formal analyses of the included studies pointed to a decrease in ALA, EPA, and DHA levels in various populations (e.g., children, adolescents, adults, and seniors) presenting with different types of mental disorders. These results indicate that PUFA supplementation may be considered as an innovative therapeutic strategy to reduce the risk of neuronal degeneration.
Effect of Low-Molecular-Weight Hyaluronate-Based Nanoparticles on the In Vitro Expression of Cartilage Markers
Authors: Bianchera Annalisa , Borghetti Paolo , Ravanetti Francesca , Bertocchi Laura , De Angelis Elena , Bettini Ruggero
Published: November 2024

Hyaluronic acid (HA) is a key component of synovial fluid as it plays a crucial role in joint physiology. Its biological activity is influenced by molecular weight, local concentration, and persistence in joints. High-molecular-weight HA has a consolidated history of clinical use, whereas little is known about the metabolic effect of low-molecular-weight hyaluronate on cartilage differentiation. This study explores the potential of HA-based nanoparticles (NPs) on chondrocytes differentiation in vitro. Starting from 25 kDa and 250 kDa sodium hyaluronate solutions, two types of NPs were prepared by antisolvent precipitation in ethanol. The resulting NPs were dried in the presence of dipalmitoyl phosphatidylcholine, a natural synovial fluid component, then applied on an in vitro model of horse articular chondrocytes: no toxicity was observed and NPs prepared from 250 kDa HA promoted chondrocyte differentiation to a larger extent with respect to corresponding HA solutions, as evidenced by increased gene expression of chondrogenic markers (Col2a1 and Sox9) and reduced expression of dedifferentiation markers (Col1a1 and Runx2). These findings suggest that HA-based NPs are more effective at promoting the cellular internalization of the molecule and the differentiation of chondrocytes in vitro and could be a promising platform for drug delivery and cartilage repair.
Saliva of Therioaphis trifolii (Drepanosiphidae) Activates the SA Plant Hormone Pathway, Inhibits the JA Plant Hormone Pathway, and Improves Aphid Survival Rate
Authors: Zhu Kaihui , Zhang Neng , Zhang Daogang , Cai Ni , Liu Rong , Dong Hui , Zhang Zehua , Tu Xiongbing
Published: November 2024

The spotted alfalfa aphid (Therioaphis trifolii) is a kind of destructive pest of cultivated alfalfa (Medicago sativa) that results in significant financial losses for the livestock sector. To understand how T. trifolii navigates the biochemical defenses of its host, we investigated the effects of susceptible and resistant aphid strains on two alfalfa cultivars. T. trifolii was reared for over 50 generations on two cultivars—WL343, which is susceptible to T. trifolii, and Zhongmu No. 1, which is resistant—resulting in the development of a resistant aphid strain (R-aphid) and a susceptible aphid strain (S-aphid). The results showed that the survival rate of R-aphids was significantly higher than that of S-aphids (p = 0.039) on the resistant cultivar Zhongmu No. 1, while there was no significant difference in survival rates between the two aphid strains on WL343 (p = 0.139). This suggests that S- and R-aphids differ in their ability to modulate plant defense mechanisms, influencing their survival rates. The application of saliva from R-aphids reared on Zhongmu No. 1 (R-saliva) reduced the repellency and toxicity of treated plants, improving aphid survival. Furthermore, R-aphid infestation and R-saliva application activated the salicylic acid (SA) signaling pathway while suppressing the jasmonic acid (JA) pathway, enhancing the host plant’s suitability for aphid colonization. We propose that R-aphids may use their saliva to activate the SA pathway, which in turn inhibits JA synthesis, weakening the plant’s defenses. These findings provide valuable insights into how T. trifolii interacts with host plant defense systems.
Immune System-Related Plasma Pathogenic Extracellular Vesicle Subpopulations Predict Osteoarthritis Progression
Authors: Zhang Xin , Ma Sisi , Naz Syeda Iffat , Soderblom Erik J. , Jain Vaibhav , Aliferis Constantin , Kraus Virginia Byers
Published: November 2024

Certain molecules found on the surface or within the cargo of extracellular vesicles (EVs) are linked to osteoarthritis (OA) severity and progression. We aimed to identify plasma pathogenic EV subpopulations that can predict knee radiographic OA (rOA) progression. We analyzed the mass spectrometry-based proteomic data of plasma EVs and synovial fluid (SF) EVs from knee OA patients (n = 16, 50% female). The identified surface markers of interest were further evaluated in plasma EVs from an independent cohort of knee OA patients (n = 30, 47% female) using flow cytometry. A total of 199 peptides with significant correlation between plasma and SF EVs were identified. Of these, 41.7% were linked to immune system processes, 15.5% to inflammatory responses, and 16.7% to the complement system. Crucially, five previously identified knee rOA severity-indicating surface markers—FGA, FGB, FGG, TLN1, and AMBP—were confirmed on plasma EV subpopulations in an independent cohort. These markers’ baseline frequencies on large plasma EVs predicted rOA progression with an AUC of 0.655–0.711. Notably, TLN1 was expressed in OA joint tissue, whereas FGA, FGB, FGG, and AMBP were predominantly liver derived. These surface markers define specific pathogenic EV subpopulations, offering potential OA prognostic biomarkers and novel therapeutic targets for disease modification.
Proteomic Analysis of Biomarkers Predicting Treatment Response in Patients with Head and Neck Cancers
Authors: Zebene Emeshaw Damtew , Lombardi Rita , Pucci Biagio , Medhin Hagos Tesfay , Seife Edom , Di Gennaro Elena , Budillon Alfredo , Woldemichael Gurja Belay
Published: November 2024

Head and neck cancers (HNCs) are the sixth most commonly diagnosed cancer and the eighth leading cause of cancer-related mortality worldwide, with squamous cell carcinoma being the most prevalent type. The global incidence of HNCs is steadily increasing, projected to rise by approximately 30% per year by 2030, a trend observed in both developed and undeveloped countries. This study involved serum proteomic profiling to identify predictive clinical biomarkers in cancer patients undergoing chemoradiotherapy (CRT). Fifteen HNC patients at Tikur Anbessa Specialized Hospital, Radiotherapy (RT) center in Addis Ababa were enrolled. Serum samples were collected before and after RT, and patients were classified as responders (R) or non-responders (NR). Protein concentrations in the serum were determined using the Bradford assay, followed by nano-HPLC–MS/MS for protein profiling. Progenesis QI for proteomics identified 55 differentially expressed proteins (DEPs) between R and NR, with a significance of p < 0.05 and a fold-change (FC) ≥ 1.5. The top five-up-regulated proteins included MAD1L1, PSMC2, TRIM29, C5, and SERPING1, while the top five-down-regulated proteins were RYR1, HEY2, HIF1A, TF, and CNN3. Notably, about 16.4% of the DEPs were involved in cellular responses to DNA damage from cancer treatments, encompassing proteins related to deoxyribonucleic acid (DNA) damage sensing, checkpoint activation, DNA repair, and apoptosis/cell cycle regulation. The analysis of the relative abundance of ten proteins with high confidence scores identified three DEPs: ADIPOQ, HEY2, and FUT10 as potential predictive biomarkers for treatment response. This study highlighted the identification of three potential predictive biomarkers—ADIPOQ, HEY2, and FUT10—through serum proteomic profiling in HNC patients undergoing RT, emphasizing their significance in predicting treatment response.
Fast Colorimetric Detection of H2O2 and Glucose: A Way Based on Magnetic Nanoparticles Composed of Fe3(PO4)2·8H2O Isolated from Burkholderia cepacia CG-1
Authors: Jia Mingyu , Wang Jueyu , Liu Yuxuan , Cui Daizong , Zhao Min
Published: November 2024

In this study, Fe3(PO4)2·8H2O magnetic nanoparticles (MNPs) were successfully extracted from the strain Burkholderia cepacia CG-1. We subsequently characterized their composition, structure, and morphology, revealing that these nanoparticles consisted of Fe3(PO4)2·8H2O with an average diameter of 66.87 ± 0.56 nm. Our measurements indicated magnetic parameters of 151 Oe for coercivity, 2 emu/g for saturation remanence, and 16 emu/g for saturation magnetization. Our findings confirmed that these magnetic nanoparticles exhibited intrinsic peroxidase-like activity, catalyzing the oxidation of 3,3,5,5-tetramethylbenzidine (TMB) in the presence of H2O2. Compared to horseradish peroxidase (HRP), the peroxidase mimic demonstrated greater stability under various physicochemical conditions. To investigate the mechanisms underlying the peroxidase-like catalysis of Fe3(PO4)2·8H2O, we employed fluorescence spectroscopy and electron spin resonance (ESR) analysis. The results revealed that the peroxidase-like activity of Fe3(PO4)2·8H2O stemmed from the generation of hydroxyl radicals (·OH). Furthermore, we established a platform for the colorimetric detection of H2O2 and glucose. Our method was capable of detecting H2O2 concentrations as low as 1.0 × 10−3 mmol/L. Impressively, this sensitive method was successfully applied to determine glucose levels in human serum.
Structure and Properties of Poly(Ethylene-co-vinyl Acetate) Nanocomposites with Dual-Functionalized Dolomite Nanoparticles
Authors: Ahmad Fauzi Asfa Amalia , Osman Azlin Fazlina , Alosime Eid M. , Abdul Halim Khairul Anwar , Abdullah Mohd Aidil Adhha
Published: November 2024

Poly(ethylene-co-vinyl acetate) (PEVAc) is a copolymer that consists of non-polar polyethylene (PE) and a polar polyvinyl acetate (PVAc) monomer. PEVAc has high elasticity and is resilient, making it suitable for a variety of applications. However, the tensile strength of this copolymer needs to be improved for specific applications that require enough strength to tolerate high external tension or stress. This study proposed the use of dual-functionalized dolomite nanoparticles (DF-DNPs) composed of polar and non-polar nano-dolomite (P-DNPs and NP-DNPs) as nanofillers to reinforce the PEVAc. PEVAc/DF-DNP film appears to have a more homogeneous mixture, which is better for forming an optimal nanocomposite material. It also exhibits the highest tensile strength (10.48 MPa), elongation at break (1175.73%), and tensile toughness (62.12 MPa), which are higher by increments of 46.8%, 9.4%, and 20.3%, respectively, as compared to the neat PEVAc. The result proved that using DF-DNPs as a nanofiller can improve the strength of PEVAc while maintaining its flexibility to avoid brittleness of the nanocomposite film. Furthermore, its thermal characteristics were also successfully enhanced. A biostability assessment showed that the use of DF-DNPs as nanofiller caused the PEVAc copolymer to achieve the best water resistance, as it only exhibited a 2.63% weight increase, the lowest reduction in tensile properties among the studied fillers, and the best retention in surface degradation upon 3-month exposure to the in vitro environment. These findings indicate that the DF-DNPs help in developing a homogeneous nanocomposite by interacting with PE and PVAc.
Human-Induced Pluripotent Stem Cell-Derived Neural Organoids as a Novel In Vitro Platform for Developmental Neurotoxicity Assessment
Authors: Hongen Tsunehiko , Sakai Kenta , Ito Tomohiro , Qin Xian-Yang , Sone Hideko
Published: November 2024

There has been a recent drive to replace in vivo studies with in vitro studies in the field of toxicity testing. Therefore, instead of conventional animal or planar cell culture models, there is an urgent need for in vitro systems whose conditions can be strictly controlled, including cell–cell interactions and sensitivity to low doses of chemicals. Neural organoids generated from human-induced pluripotent stem cells (iPSCs) are a promising in vitro platform for modeling human brain development. In this study, we developed a new tool based on various iPSCs to study and predict chemical-induced toxicity in humans. The model displayed several neurodevelopmental features and showed good reproducibility, comparable to that of previously published models. The results revealed that basic fibroblast growth factor plays a key role in the formation of the embryoid body, as well as complex neural networks and higher-order structures such as layered stacking. Using organoid models, pesticide toxicities were assessed. Cells treated with low concentrations of rotenone underwent apoptosis to a greater extent than those treated with high concentrations of rotenone. Morphological changes associated with the development of neural progenitor cells were observed after exposure to low doses of chlorpyrifos. These findings suggest that the neuronal organoids developed in this study mimic the developmental processes occurring in the brain and nerves and are a useful tool for evaluating drug efficacy, safety, and toxicity.
Role of Circulating X-Chromosome Inactivation and Xist as Biomarkers in Female Carriers of Fabry Disease
Authors: Rossi Salvatore , Fargnoli Arcangelo , Di Natale Daniele , Dalla Zanna Gianmarco , Funcis Antonio , Re Federica , Gragnaniello Vincenza , Verrecchia Elena , Burlina Alberto , Tabolacci Elisabetta , Silvestri Gabriella
Published: November 2024

Background: Fabry Disease (FD) is an X-linked lysosomal disease, in which, unlike other X-linked disorders, most female carriers manifest signs or symptoms for unknown reasons. Objectives: Herein, we aimed to test the potential role of X-chromosome inactivation (XCI) in leukocytes as a prognostic biomarker of disease in FD female carriers. Moreover, we explored if levels of X-inactive-specific transcript (Xist), a long non-coding RNA driving XCI, were detectable in the leukocytes of FD female carriers. Methods: We tested the XCI pattern in leukocytes on 33 consecutive females carrying pathogenic GLA variants. Disease severity was defined using the Mainz Severity Score Index (MSSI). Xist levels in leukocytes were assessed by real-time PCR and compared to the levels of 22 controls. Results: XCI was obtained for 31 female patients, finding 16 skewed (51.6%) individuals. Global MSSI did not differ in skewed vs. non-skewed FD carriers. In skewed FD females, the renal function and mean cardiologic MSSI subscore were significantly worse, and systemic arterial hypertension was more frequent. Xist levels detected in leukocytes were similar between female patients and controls, and did not differ by phenotype or XCI status. Conclusions: A skewed XCI pattern in leukocytes may represent a prognostic biomarker of worse renal and cardiac outcomes in female FD carriers.
Hybrid Machine Learning for Stunting Prevalence: A Novel Comprehensive Approach to Its Classification, Prediction, and Clustering Optimization in Aceh, Indonesia
Authors: Hasdyna Novia , Dinata Rozzi Kesuma , Rahmi  , Fajri T. Irfan
Published: November 2024

Stunting remains a significant public health issue in Aceh, Indonesia, and is influenced by various socio-economic and environmental factors. This study aims to address key challenges in accurately classifying stunting prevalence, predicting future trends, and optimizing clustering methods to support more effective interventions. To this end, we propose a novel hybrid machine learning framework that integrates classification, predictive modeling, and clustering optimization. Support Vector Machines (SVM) with Radial Basis Function (RBF) and Sigmoid kernels were employed to improve the classification accuracy, with the RBF kernel outperforming the Sigmoid kernel, achieving an accuracy rate of 91.3% compared with 85.6%. This provides a more reliable tool for identifying high-risk populations. Furthermore, linear regression was used for predictive modeling, yielding a low Mean Squared Error (MSE) of 0.137, demonstrating robust predictive accuracy for future stunting prevalence. Finally, the clustering process was optimized using a weighted-product approach to enhance the efficiency of K-Medoids. This optimization reduced the number of iterations from seven to three and improved the Calinski–Harabasz Index from 85.2 to 93.7. This comprehensive framework not only enhances the classification, prediction, and clustering of results but also delivers actionable insights for targeted public health interventions and policymaking aimed at reducing stunting in Aceh.
A New Prediction Model of Cutterhead Torque in Soil Strata Based on Ultra-Large Section EPB Pipe Jacking Machine
Authors: Lu Jianwei , Sun Bo , Gong Qiuming , Song Tiantian , Li Wei , Zhou Wenpeng , Li Yang
Published: November 2024

Cutterhead torque is a key operational parameter for earth pressure balance (EPB) TBM tunneling in soil strata. The effective management of cutterhead torque can significantly maintain face stability and ensure the tunneling machine operates steadily. The Shenzhen Metro Line 12 project at Shasan Station utilized the world’s largest rectangular pipe jacking machine for constructing the subway station. This project has enabled the collection of relevant data to analyze the factors influencing cutterhead torque and to establish a predictive model. The data encompass an abundant array of cutterhead design parameters, operational parameters, properties of the excavated soil, and environmental factors, revealing the distribution characteristics of cutterhead torque during tunneling. The correlation between various factors and cutterhead torque has been examined. By employing multiple regression analysis and a Levenberg–Marquardt (L-M) algorithm-based neural network, an optimal prediction model for EPB cutterhead torque has been developed. This prediction model incorporates various factors, including cutterhead diameter, RPM, soil chamber pressure, soil shear strength, and the soil consistency index. And the degree of influence of each factor on the cutter torque was also revealed. The prediction results demonstrated good accuracy compared to previous models, providing valuable insights and guidance for EPB TBMs or pipe jacking machines operating in soil strata. The current limitations of this model and suggestions for future work have also been addressed.
Chronic Complications of Diabetes: Prevalence, Prevention, and Management
Authors: Migdalis Ilias N.
Published: November 2024

The prevalence of diabetes, especially of type 2 diabetes (T2D), is increasing globally, driven mainly by behavioral and societal factors, related to obesity, nutrition, and physical activity [...]
Eco-Friendly Wall Cladding Panels from Recycled Fishing Gear and Clamshell Waste
Authors: Belmokhtar Zakariae , Cousin Patrice , Elkoun Saïd , Robert Mathieu
Published: November 2024

Eco-friendly wall cladding panels were developed from fishing industry waste by incorporating discarded ropes, wood fibers from lobster cages, and clamshell powder. Four panel formulations were investigated using MAPP and MAPE coupling agents: FRW-M (97% fishing rope), 30WF-M (67% rope with 30% wood fibers), 30CS-M (67% rope with 30% clamshell powder), and a hybrid 15CS15WF-M (67% rope with 15% each of wood fibers and clamshell powder). A DSC analysis revealed that clamshell powder addition reduced melting temperatures and crystallinity, while wood fiber incorporation led to slight increases in melting temperatures. The hybrid formulation exhibited enhanced crystallization temperatures despite lower overall crystallinity. A dynamic mechanical analysis showed an 85% improvement in storage modulus for the hybrid panel, with flexural testing demonstrating a 202% increase in modulus and 20% increase in strength. SEM-EDS analysis confirmed improved filler dispersion and interfacial adhesion in the hybrid formulation. Water absorption was lowest in FRW-M and highest in 30WF-M, while burning rate tests showed 30CS-M and 30WF-M as the best and worst performers, respectively. The hybrid formulation emerged as the optimal solution, combining enhanced mechanical properties with improved water resistance and fire retardancy, presenting a viable sustainable alternative for wall cladding applications.
Towards Effective Participation: A Stakeholder-Centered Evaluation for Aggregating Spatially Explicit Data
Authors: Leahy Sebastian , Dias Eduardo
Published: November 2024

As participatory mapping becomes more ingrained into participatory practices, it is vital to understand what makes a method effective. Through the employment of a participatory mapping experiment within an ongoing urban greening initiative, this research aims at validating two established aggregation methods of spatially explicit data points in participatory mapping. Utilizing a paper mapping activity with community residents, the collected spatial data points were analyzed using both democratic and weighted aggregation. Subsequently, a follow-up study was employed to validate the perceived feeling of ownership among both of the methods in terms of the stakeholders’ sense of community representation within the visual outputs. This research introduces a novel approach to the evaluation of participatory mapping practices. A key finding includes the development of a comprehensive methodological model that explores various aspects of a participatory process. Additionally, a new criterion was presented, stakeholder representation, in which to evaluate effectiveness. The difference between the methods was not found to be significant, as the mapping results revealed a consistent overlap in the areas of interest across the stakeholder groups, suggesting a general public consensus on the local development priorities. These insights hold considerable value for local decisions makers, as agreement areas provide a stable foundation for planning. Lastly, this research contributes to the ongoing efforts to evaluate and standardize participatory mapping methods, while also addressing the potential of varied aggregation methods to enhance effectiveness.
Response of Vegetation Phenology to Meteorological Factors in Different Eco-Geographic Zones in China
Authors: Liang Yutong , Yang Jinxin , Yang Qiang , Chen Wenkai , Fan Juncheng , Chen Yuanyuan
Published: November 2024

Vegetation phenology is highly sensitive to climate change, and an examination of vegetation phenology across diverse climatic conditions is crucial for identifying key factors influencing vegetation dynamics. However, there is a significant lack of macroscopic research and quantitative assessments on the response of vegetation phenology to meteorological factors in large-scale zones. This study employed Whittaker filtering and dynamic thresholding to extract phenological parameters of vegetation in China. Trend analysis was used to investigate the spatiotemporal changes in vegetation phenology from 1982 to 2022, while partial correlation and ridge regression analysis were conducted to quantify the response of vegetation in different zones to meteorological factors. The findings of this study demonstrate that over the past four decades, the start of the growing season (SOS) of vegetation in China has progressively advanced annually, whereas the end of the growing season (EOS) has progressively delayed annually, leading to an annual increase in the length of the growing season (LOS). Notably, these changes exhibit significant spatial variations. The response of vegetation phenology to temperature and precipitation is relatively complex and is closely related to local climatic conditions, humidity, vegetation type, etc. Different zones and diverse vegetation types have very different sensitivities to the same meteorological factor, sometimes even demonstrating contrasting responses. Consequently, this study is expected to clarify the response relationship between different vegetation ecosystems and meteorological factors in large-scale areas.
Identification and Regulation of Cold Rolling Interface State Based on a Novel Modified Forward Slip Model
Authors: Xin Yanli , Gao Zhiying , Zang Yong , Wang Xiaoyong
Published: November 2024

With the development of rolled steel strips towards higher strength and thinner thickness, negative forward slip has been frequently observed during the process of cold rolling, and this phenomenon closely related to interface is believed to seriously influence rolling stability. However, the existing classic forward slip models are limited to calculating positive forward slip values and cannot reflect negative forward slip effects. Therefore, in this paper, based on BLAND-FORD forward slip theory, a novel modified forward slip model capable of predicting negative forward slip is established and verified, in which the corresponding flattened curve is characterized and a compensation coefficient related to actual tension and coil number is supplemented. Then, a dimensionless sensitivity factor is defined to compare and analyze the influences of various parameters on forward slip through the modified model, in order to pick a more effective and reasonable regulation approach. Finally, an idea of keeping stable forward slip through dynamic tension regulation is suggested and applied in the actual rolling process, and it is drawn that this strategy can be used to avoid fluctuations of process parameters and suppress mill chatter. As a result, the presented modified forward slip model can identify both positive and negative forward slips and is helpful in regulating the interface state and improving the stability of the rolling process.