bluuebunny/crossref_metadata_2025 huggingface dataset:
Advancing Precision Oncology with Digital and Virtual Twins: A Scoping Review
Authors: Ștefănigă Sebastian Aurelian , Cordoș Ariana Anamaria , Ivascu Todor , Feier Catalin Vladut Ionut , Muntean Călin , Stupinean Ciprian Viorel , Călinici Tudor , Aluaș Maria , Bolboacă Sorana D.
Published: November 2024

Digital twins (DTHs) and virtual twins (VTHs) in healthcare represent emerging technologies towards precision medicine, providing opportunities for patient-centric healthcare. Our scoping review aimed to map the current DTH and VTH technologies in oncology, summarize their technical solutions, and assess their credibility. A systematic search was conducted in the main bibliographic databases, identifying 441 records, of which 30 were included. The studies covered a wide range of cancers, including breast, lung, colorectal, and gastrointestinal malignancies, with DTH and VTH applications focusing on diagnosis, therapy, and monitoring. The results revealed heterogeneity in targeted topics, technical approaches, and outcomes. Most twining solutions use synthetic or limited real-world data, raising concerns regarding their reliability. Few studies have integrated real-time data and machine learning for predictive modeling. Technical challenges include data integration, scalability, and ethical considerations, such as data privacy and security. Moreover, the evidence lacks sufficient clinical validation, with only partial credibility in most cases. Our findings underscore the need for multidisciplinary collaboration among end-users and developers to address the technical and ethical challenges of DTH and VTH systems. Although promising for the future of personalized oncology, substantial steps are required to move beyond experimental frameworks and to achieve clinical implementation.
Computational Studies of Molybdenum-Containing Metal–Sulfur and Metal–Hydride Clusters
Authors: Lakshan Nishshanka M. , Aluthge Dinesh C. , Sameera W. M. C.
Published: November 2024

The development of transition metal clusters is an active area of research in inorganic chemistry, as they can be used as catalysts to perform chemically or biologically relevant reactions. Computational chemistry, employing density functional theory (DFT), plays a key role in rationalizing the electronic structure and properties of transition metal clusters. This article reviews recent quantum chemical studies of Mo3S4M clusters (M = Fe, Co, Ni), their CO- or N2-bound variants, and metal–hydride clusters. The ground state of the cluster systems was computed, and properties such as metal–metal bonding, orbital interactions, fluxional behavior of ligands, spectroscopy, and reaction mechanisms were rationalized and compared with available experimental results. Our research findings evidence that computational studies employing quantum chemical methods can guide experimental researchers to develop novel transition metal clusters for potential applications in catalysis.
Effect of Calcination Temperature in Large-Aperture Medium-Entropy Oxide (FeCoCuZnNa)O on CO2 Hydrogenation for Light Olefins
Authors: Ni Zhijiang , Chen Xiaoyu , Su Lin , Shen Hanyu , Yin Chaochuang
Published: November 2024

The catalytic hydrogenation of carbon dioxide is not only a way to mitigate the greenhouse effect but also provides high-value chemicals. In this work, a medium-entropy oxide catalyst (FeCoCuZnNa)O was prepared by the sol–gel method for highly active and selective hydrogenation of CO2 to value-added hydrocarbons. When reacted at 290 °C, 2.5 MPa, and 2500 mL·gcat−1·h−1, the CO2 conversion and selectivity of olefin were affected by the calcination temperature of the catalyst, and the best performances were 39% and 41.3%. The large pore size and oxygen vacancies (Ov) formed by (FeCoCuZnNa)O promote the activation of CO2 and promote the C-C coupling reaction of Fe5C2 in a hydrogenation reaction. The promoted C-C coupling reaction was related to the surface enrichment of iron species. The presence of Ov also inhibited the excessive hydrogenation reaction, further improving the selectivity of light olefins. In addition, (FeCoCuZnNa)O did not show significant deactivation within 75 h, indicating that the catalyst has strong industrial potential.
Urinary Diversion Can Improve the Chance of Implementing New Therapeutic Lines in Patients with Malignant Ureteral Obstruction: A Multicenter Study
Authors: Cartapatti Marcelo , Machado Roberto Dias , Mesquita José Carlos , Freua Raphael , Cáceres Diego , dos Reis Rodolfo Borges
Published: November 2024

Purpose: Malignant ureteral obstruction is generally associated with a poor disease prognosis; therefore, managing these cases is challenging. We describe our experience in treating malignant ureteral obstruction with urinary diversion and the impact of these procedures on the indication for new antineoplastic therapy and survival. Materials and Methods: We retrospectively reviewed the data of patients with advanced cancer associated with malignant ureteral obstruction who underwent urinary diversion at three tertiary institutions between January 2013 and July 2022. Results: This study included 420 patients (mean age, 58.7 years (range, 18–90 years) with a mean follow-up of 20.3 months. Cervical (36.2%) and bladder cancers (18.6%) were the most prevalent primary neo-plastic sites. The mean creatinine values measured before diversion, 30 days after surgery, and most recently were 3.45, 1.84, and 2.59 mg/dL, respectively. In total, 300 patients (71.4%) received antineoplastic treatment, 195 received palliative treatment, and 105 received curative treatment. After an average of 251.87 postoperative days, 265 (64%) patients died. The mean overall survival was 610.76 days. Patients with prostate and cervical neoplasms had the most prolonged overall survival (573.13 and 549.28 days, respectively), whereas patients with bladder and colorectal cancer had the worst overall survival (480.25 and 370.53 days, respectively). Conclusions: Urinary diversion improves kidney function and opens a therapeutic window for a new line of antineoplastic therapy that provides a cure or increases patient survival.
Radiation Therapy for Cutaneous Blastic Plasmacytoid Dendritic Cell Neoplasm: A Case Report and Review of the Literature
Authors: Taka Masashi , Toyoshima Shinichiro , Takamatsu Shigeyuki , Kobayashi Satoshi
Published: November 2024

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a clinically aggressive hematologic malignancy derived from plasmacytoid dendritic cells. It commonly presents as cutaneous lesions. To date, no standard treatment protocol for BPDCN exists. Traditionally treated similarly to acute leukemia or lymphoma, its prognosis remains poor. Radiation therapy is employed for isolated skin lesions, for patients that are ineligible for chemotherapy due to age or comorbidities and for post-chemotherapy recurrence. However, very limited reports are available on radiotherapy for BPDCN. We present a case involving a 94-year-old BPDCN patient treated with radiation therapy, highlighting an atypical situation of two separate radiotherapy sessions with different dosages for isolated skin lesions. Initially, 45 Gy was administered in 15 fractions (45 Gy/15 Fr), followed by a second session of 30 Gy in 10 fractions (30 Gy/10 Fr) after disease recurrence. This case is unique in detailing radiation therapy for the exceedingly rare BPDCN, particularly dose fractionation. The findings indicate that 45 Gy/15 Fr can provide adequate local control, while even a lower dose of 30 Gy/10 Fr may be effective. This case report contributes to the limited literature by proposing potential therapeutic approaches and dosage guidelines to refine future BPDCN treatment protocols.
Fetal Tele-Echocardiography—An Approach to Improving Diagnosis and Management
Authors: Ahmed Badreldeen , Elsisi Amal , Konje Justin C.
Published: November 2024

Introduction: Antenatal diagnosis of cardiac abnormalities and counselling parents about postnatal care require a multidisciplinary team, which includes a paediatric cardiologist, a neonatologist, and a fetal medicine physician. Some of these kinds of expertise are not available in all centres with fetal medicine expertise. However, with modern technology, this could be provided remotely. Our objective was to assess the feasibility and outcomes of prenatal multidisciplinary tele-echocardiography diagnostic and counselling services. Materials and Methods: Two centres based in separate countries provided a joint diagnostic and counselling service over a period of 14 months. The primary centre performed the fetal echocardiography with a Voluson E10 machine, and images were transmitted live using Zoom OPS system with video-consultation and counselling. The fetal echo was performed using the ISUOG Guidelines check list. Results: There was an initial feasibility period of 2 months during which 10 women whose fetuses had normal hearts were scanned to test the workability of the system. Over a period of 12 months, 513 high-risk fetuses were then scanned, and out of these, 27 had congenital malformations. The most common were hypoplastic left heart syndrome (HHLS) and atrio-ventricular septal defect. Tele-echocardiography and counselling were successful in all the cases. Satisfaction with the service was 3.8/4, with the main limitation being the need for further referral to a tertiary centre for delivery. Conclusions: Tele-echocardiography is reliable, and when combined with live counselling and support from a paediatric cardiologist, it is an option acceptable to patients. The greatest benefit was from being counselled by a team of experts at a single consultation rather than having to travel to another centre for consultation. With rapidly evolving technology, making video transmission easier and less expensive, we feel that consideration should be given not only to the development of tele-echocardiography but also to extending it to other aspects of fetal medicine.
The Influence of Firm Characteristics and Macroeconomic Factors on Financial Performance: Evidence from the Portuguese Hotel Industry
Authors: Matias Fernanda , Rebelo Sandra , Andraz Georgette , Guerreiro José
Published: November 2024

This study examines the determinants of the financial performance of the Portuguese hotel industry. Despite the economic relevance of the hotel industry and financial performance as an indicator of business survival, academic research on the factors that influence it in the context of this industry, particularly in Portugal, is not extensive. This study encompassed a sample of 738 hotel companies from 2016 to 2021, using data from the Orbis database. This research was based on the assumption that a company’s size, liquidity, the tangibility of its assets, and debt level influence financial performance in the hotel industry, as well as the assumption that gross domestic product and consumer sentiment also affect the business success of hotel companies. By applying a panel data methodology, the findings indicate that all variables showed significant influence on financial performance, except liquidity. The analysis also reveals that smaller companies were more negatively affected by the demand decline induced by the COVID-19 pandemic. To improve the financial performance of the Portuguese hotel industry, the findings suggest that policymakers must work towards ensuring diversified sources of financing for the hotel business, such as investment subsidies, so that companies can minimize debt, especially during periods of slow economic growth. Additionally, companies must promote management strategies that enhance self-financing. Both measures could help companies increase their size, taking advantage of good business opportunities to explore economies of scale.
Quantile Connectedness Amongst Green Assets Amid COVID-19 and Russia–Ukraine Tussle
Authors: Rehan Ayesha , Mohti Wahbeeah , Ferreira Paulo
Published: November 2024

With the advent of greening the global economy and the introduction of green financial assets, this study examines the connectedness and spillover effect of green assets using a QVAR approach focusing on the average connectedness and connectedness under extreme market conditions. The time of the study captures the crucial global incidents of COVID-19 and Russia–Ukraine war to investigate the effect of major incidents on the connectedness of green assets. The results of the QVAR analysis reveal that green assets are moderately connected under normal market conditions; however, their connection is strengthened under extreme market conditions. IOTA and SP Green Bonds are the net receivers of shocks from other assets, and SP Green Bonds are connected to green energy indices and green cryptocurrencies during turbulent markets. Since green cryptocurrencies are closely connected, a lower portion of them should be added to portfolios, whereas SP Green Bonds qualify as a good diversifying agent in a portfolio. The study has significant implications for market participants, investors, and policymakers.
Teacher Identity Discourses in Place—Exploring Discursive Resources in Pre-Service Teachers’ Constructions of Teacher Identity
Authors: Neander Christensson Johan
Published: November 2024

This methodological article focuses on how to effectively map pre-service teachers’ use of discursive resources in professional identity production. By adopting a discourse analytical approach, this study views identity construction as a situational, real-time process occurring in interaction. The aim is to contribute knowledge about how to systematically map and analyze the resources that pre-service teachers use to construct their teacher identities during their education. Drawing on the framework of Mediated Discourse Analysis, this article presents a model that integrates two key concepts: discourse domains, which refer to the types of discourse commonly used in teacher education, and layers of discourse, which address societal levels in identity construction. The results suggest that using these concepts to map students’ use of discursive resources highlights how their knowledge of the teaching profession, their education and everyday experiences can be assets when constructing their teacher identities. While the model can be further refined and developed to better show the complexity of discursive resources in identity construction processes, it shows promise as a fruitful approach. By mapping and visualizing discursive resources through this model, this study offers valuable methodological insights into how to approach professional identity development among pre-service teachers.
A Survey on Design Space Exploration Approaches for Approximate Computing Systems
Authors: Saeedi Sepide , Piri Ali , Deveautour Bastien , O’Connor Ian , Bosio Alberto , Savino Alessandro , Di Carlo Stefano
Published: November 2024

Approximate Computing (AxC) has emerged as a promising paradigm to enhance performance and energy efficiency by allowing a controlled trade-off between accuracy and resource consumption. It is extensively adopted across various abstraction levels, from software to architecture and circuit levels, employing diverse methodologies. The primary objective of AxC is to reduce energy consumption for executing error-resilient applications, accepting controlled and inherently acceptable output quality degradation. However, harnessing AxC poses several challenges, including identifying segments within a design amenable to approximation and selecting suitable AxC techniques to fulfill accuracy and performance criteria. This survey provides a comprehensive review of recent methodologies proposed for performing Design Space Exploration (DSE) to find the most suitable AxC techniques, focusing on both hardware and software implementations. DSE is a crucial design process where system designs are modeled, evaluated, and optimized for various extra-functional system behaviors such as performance, power consumption, energy efficiency, and accuracy. A systematic literature review was conducted to identify papers that ascribe their DSE algorithms, excluding those relying on exhaustive search methods. This survey aims to detail the state-of-the-art DSE methodologies that efficiently select AxC techniques, offering insights into their applicability across different hardware platforms and use-case domains. For this purpose, papers were categorized based on the type of search algorithm used, with Machine Learning (ML) and Evolutionary Algorithms (EAs) being the predominant approaches. Further categorization is based on the target hardware, including Field-Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), general-purpose Central Processing Units (CPUs), and Graphics Processing Units (GPUs). A notable observation was that most studies targeted image processing applications due to their tolerance for accuracy loss. By providing an overview of techniques and methods outlined in existing literature pertaining to the DSE of AxC designs, this survey elucidates the current trends and challenges in optimizing approximate designs.
A Coverage Hole Recovery Method for 3D UWSNs Based on Virtual Force and Energy Balance
Authors: Yan Luoheng , Huangfu Zhongmin
Published: November 2024

Underwater wireless sensor networks (UWSNs) have been applied in lots of fields. However, coverage holes are usually caused by complex underwater environment. Coverage holes seriously affect UWSNs’ performance and quality of service; thus, their recovery is crucial for 3D UWSNs. Although most of the current research recovery algorithms demand hole detection, the number of additional mobile nodes is too large, the communication and computing costs are high, and the coverage and energy balance are poor. Therefore, these methods are not suitable for UWSN hole repairing. In order to enhance the performance of hole recovery, a coverage hole recovery method for 3D UWSNs in complex underwater environments based on virtual force guidance and energy balance is proposed. The proposed method closely combines the node energy and considers complex environmental factors. A series of multi-dimensional virtual force models are established based on energy between nodes, area boundaries, zero-energy holes, low-energy coverage holes, underwater terrain, and obstacle forces. Then, a coverage hole recovery method for 3D UWSNs based on virtual force guidance and energy balance (CHRVE) is proposed. In this method, the direction and step size of mobile repairing node movement is guided by distributed computation of virtual forces, and the nodes are driven towards the target location by means of AUV or other carrier devices. The optimal position to improve coverage rate and node force balance is obtained. Simulation experiments show good adaptability and robustness to complex underwater terrain and different environments. The algorithm does not require precise coverage hole boundary detection. Furthermore, it balances network energy distribution significantly. Therefore, this method reduces the frequency of coverage hole emergence and network maintenance costs.
HGNN−BRFE: Heterogeneous Graph Neural Network Model Based on Region Feature Extraction
Authors: Zhao Yufei , Xu Shixiao , Duan Hua
Published: November 2024

With the strong capability of heterogeneous graphs in accurately modeling various types of nodes and their interactions, they have gradually become a research hotspot, promoting the rapid development of the field of heterogeneous graph neural networks (HGNNs). However, most existing HGNN models rely on meta−paths for feature extraction, which can only utilize part of the data from the graph for training and learning. This not only limits the data generalization ability of deep learning models but also affects the application effect of data−driven adaptive technologies. In response to this challenge, this study proposes a new model—heterogeneous graph neural network based on regional feature extraction (HGNN−BRFE). This model enhances performance through an “extraction−fusion” strategy in three key aspects: first, it efficiently extracts features of neighboring nodes of the same type according to specific regions; second, it effectively fuses information from different regions and hierarchical neighbors using attention mechanisms; third, it specially designs a process for feature extraction and fusion targeting heterogeneous type nodes, ensuring that the rich semantic and heterogeneity information within the heterogeneous graph is retained while maintaining the node’s own characteristics during the node embedding process to prevent the loss of its own features and potential over−smoothing issues. Experimental results show that HGNN−BRFE achieves a performance improvement of 1–3% over existing methods on classification tasks across multiple real−world datasets.
No-Reference Quality Assessment Based on Dual-Channel Convolutional Neural Network for Underwater Image Enhancement
Authors: Hu Renzhi , Luo Ting , Jiang Guowei , Lin Zhiqiang , He Zhouyan
Published: November 2024

Underwater images are important for underwater vision tasks, yet their quality often degrades during imaging, promoting the generation of Underwater Image Enhancement (UIE) algorithms. This paper proposes a Dual-Channel Convolutional Neural Network (DC-CNN)-based quality assessment method to evaluate the performance of different UIE algorithms. Specifically, inspired by the intrinsic image decomposition, the enhanced underwater image is decomposed into reflectance with color information and illumination with texture information based on the Retinex theory. Afterward, we design a DC-CNN with two branches to learn color and texture features from reflectance and illumination, respectively, reflecting the distortion characteristics of enhanced underwater images. To integrate the learned features, a feature fusion module and attention mechanism are conducted to align efficiently and reasonably with human visual perception characteristics. Finally, a quality regression module is used to establish the mapping relationship between the extracted features and quality scores. Experimental results on two public enhanced underwater image datasets (i.e., UIQE and SAUD) show that the proposed DC-CNN method outperforms a variety of the existing quality assessment methods.
Investigation into Enhancing Methane Recovery and Sequestration Mechanism in Deep Coal Seams by CO2 Injection
Authors: Sun Xiongwei , Wang Hongya , Gong Bin , Zhao Heng , Wu Haoqiang , Wu Nan , Sun Wei , Zhang Shizhao , Jiang Ke
Published: November 2024

Injecting CO2 into coal seams to enhance coal bed methane (ECBM) recovery has been identified as a viable method for increasing methane extraction. This process also has significant potential for sequestering large volumes of CO2, thereby reducing the concentration of greenhouse gases in the atmosphere. However, for deep coal seams where formation pressure is relatively high, there is limited research on CO2 injection into systems with higher methane adsorption equilibrium pressure. Existing studies, mostly confined to the low-pressure stage, fail to effectively reveal the impact of factors such as temperature, high-pressure CO2 injection, and coal types on enhancing the recovery and sequestration of CO2-displaced methane. Thus, this study aims to investigate the influence of temperature, pressure, and coal types on ECBM recovery and CO2 sequestration in deep coal seams. A series of CO2 core flooding tests were conducted on various coal cores, with CO2 injection pressures ranging from 8 to 18 MPa. The CO2 and methane adsorption rates, as well as methane displacement efficiency, were calculated and recorded to facilitate result interpretation. Based on the results of these physical experiments, numerical simulation was conducted to study multi-component competitive adsorption, desorption, and seepage flow under high temperature and high pressure in a deep coal seam’s horizontal well. Finally, the optimization of the total injection amount (0.7 PV) and injection pressure (approximately 15.0 MPa) was carried out for the plan of CO2 displacement of methane in a single well in the later stage.
Well-Test Interpretation Model of Water-Injection Well in a Low-Permeability Reservoir and Its Application
Authors: Li Jianxiong , Wang Kai , Su Sheng , Huang Kejun , Feng Haoran , Jin Ziyi , Peng Cong , Liu Jinbao , Jia Pin
Published: November 2024

For low-permeability reservoirs, water-flooding development is usually adopted, which leads to induced fractures near the wellbore, increasing reservoir heterogeneity, and making water-flooding development more complex. This paper focuses on low-permeability reservoirs, considering the characteristics of induced fractures and elliptic-flow composite, and the well-test model for injection wells is established. The mathematical model in Laplace space is obtained through dimensionless transformation and Laplace transformation. Subsequently, the Mathieu function is introduced to obtain the bottom hole pressure, and the pressure response curve is drawn. The six flow stages of the curve are defined, and the sensitivity of parameters such as half-length of induced fractures, range of lateral-swept area, permeability in unswept area, and outer boundary distance at constant pressure are analyzed. The results show that the half-length of the fracture mainly affects the linear flow of the fracture, the range of the lateral wave-affected area mainly affects the radial flow of the swept area, the permeability of the unswept area mainly affects the radial flow of the unswept area, and the outer boundary distance at constant pressure mainly affects the boundary flow. Based on the production performance of a certain injection well in J Oilfield, a series of key parameters are obtained through analytical solution model inversion, including the induced-fracture half-length of 10.32 m, the lateral-swept range of elliptic partition flow of 128.95 m, the permeability of the swept area of 6.87 mD, and the mobility ratio of 119.92, which show the superiority of the analytical solution model.
Health State Prediction of Lithium-Ion Battery Based on Improved Sparrow Search Algorithm and Support Vector Regression
Authors: Yin Deyang , Zhu Xiao , Zhang Wanjie , Zheng Jianfeng
Published: November 2024

The state of health (SOH) prediction of lithium-ion batteries is a pivotal function within the battery management system (BMS), and achieving accurate SOH predictions is crucial for ensuring system safety and prolonging battery lifespan. To enhance prediction performance, this paper introduces an SOH prediction model based on an improved sparrow algorithm and support vector regression (ISSA-SVR). The model uses nonlinear weight reduction (NWDM) to enhance the search capability of the Sparrow algorithm and combines a mixed mutation strategy to reduce the risk of local optimal traps. Then, by analyzing the characteristics of different voltage ranges, the charging time from 3.8 V to 4.1 V, the discharge time of the battery, and the number of cycles are selected as the feature set of the model. The model’s prediction capabilities are validated across various working environments and training sample sizes, and its performance is benchmarked against other algorithms. Experimental findings indicate that the proposed model not only confines SOH prediction errors to within 1.5% but also demonstrates robust adaptability and widespread applicability.
Alternative Analyzers for the Measurement of Gaseous Compounds During Type-Approval of Heavy-Duty Vehicles
Authors: Suarez-Bertoa Ricardo , Gioria Roberto , Ferrarese Christian , Finocchiaro Lorenzo , Giechaskiel Barouch
Published: November 2024

Emissions standards describe the fuels, the procedures, and, among others, the analyzers to be used for the measurement of the different compounds during the type-approval of heavy-duty engines and vehicles. Traditionally, NOx, CO, hydrocarbons, and CO2 were the gaseous compounds measured within the Euro standard, with the later addition of CH4 and NH3. Euro 7, introduced in early 2024, expanded those compounds, requiring the measurement of N2O and HCHO. With an increasing number of molecules that need to be measured and introducing carbonless fuels, such as hydrogen, that present different requirements compared to carbon-based fuels, the test procedure needs to be updated. The performances of three laboratory-grade instruments and three portable emissions measurement systems based on Fourier-transformed infrared (FTIR) or quantum cascade laser infrared (QCL-IR) technologies were investigated while measuring from the tailpipe of a Diesel engine and a compressed natural gas (CNG) vehicle. All instruments presented good agreement when emissions of NOx, CO, CH4, NH3, N2O, HCHO, and CO2 were compared using: Z-score, F-test and two tail t-test of student. Water concentration measured by the four FTIRs was also in good agreement. Moreover, the dry emissions of CO2 and CO measured by the laboratory non-dispersive infrared (NDIR) and corrected using water were a few percentages different from those obtained using the regulated carbon-based approach. The results indicate that all the investigated systems are suitable for the measurement of the investigated gaseous compounds, including CO2 and H2O.
Fatty Acid Composition, Oxidative Status, and Content of Biogenic Elements in Raw Oats Modified Through Agricultural Practices
Authors: Wojtacki Michał , Żuk-Gołaszewska Krystyna , Duliński Robert , Giza-Gołaszewska Joanna , Kalisz Barbara , Gołaszewski Janusz
Published: November 2024

The chemical composition of raw oat grain is responsible for the high dietary value and health-promoting properties of oat products. This article presents the results of a study investigating the biofortification of grain in two oat genotypes—hulless and hulled—through agronomic treatments: chemical plant protection against weeds and fungi and mineral nitrogen fertilization. The applied agronomic treatments induced different changes in the fatty acid profiles, content of tocopherols, macronutrients, and micronutrients in the grain of hulled and hulless oats. Plant health contributed to higher concentrations of unsaturated fatty acids and potassium in oat grain. In turn, nitrogen fertilization decreased the content of unsaturated fatty acids, potassium, and copper and increased the content of saturated fatty acids, calcium, and manganese in oat grain. At the same time, agronomic treatments reduced the tocopherol content of the grain, which implies that the nutritional value of oats increases in the absence of chemical plant protection agents. The correlations between the content of desirable chemical compounds and agronomic treatments were stronger in hulless oat grain, which may suggest that the agronomic modification of oat-based foods is more effective in this genotype. The content of exogenous alpha-linoleic acid C18:3 n-3 and alpha-tocopherol was higher in grain harvested from the control treatment (without chemical plant protection), whereas grain harvested from fully protected treatments accumulated more essential gamma-linolenic acid C18:3 n-6. The content of gamma-tocopherol and copper in oat grain was higher in the absence of nitrogen fertilization.
Differently Processed Low Doses of β-Glucan from Oat Bran Similarly Attenuate Postprandial Glycemic Response
Authors: Tan Denise , Yao Yueying , Zhou Yifan , Khoo Chin Meng , Penseyres Ludovic , Rytz Andreas , Pakkiri Leroy Sivappiragasam , Drum Chester Lee , Kim Jung Eun , Lê Kim-Anne
Published: November 2024

Incorporating β-glucan-rich oat bran (OB) can attenuate postprandial glycemic response (PPGR) in solid foods, but its effect in liquid matrices is unclear. This study investigated the ability of differently processed low-dose-β-glucan-containing beverages to lower PPGR, and the mechanisms of action. Twenty participants consumed five malt beverages made from cocoa powder: intact OB (Intact), OB treated with enzymatic hydrolysis (EnzymA, EnzymB) or extrusion (Extr), or no OB (Ctrl). Four-hour postprandial incremental areas under the curve (iAUC) and peak incremental concentrations (iCmax) of glucose, insulin, glucagon-like peptide 1 (GLP-1), gastric inhibitory polypeptide (GIP), and paracetamol were evaluated. The molecular weight (MW) and extractability of the β-glucan in all the test products were also assessed. The three-hour glucose iAUC significantly decreased by −26%, −28%, −32%, and −38% in Intact, EnzymA, EnzymB, and Extr, respectively, and the insulin levels of the oat-containing products were also significantly lower compared to Ctrl. Intact and Extr elicited a lower insulin iCmax and GLP-1 3 h iAUC compared to Ctrl. However, the GIP and paracetamol levels were not changed. All the processed OBs improved β-glucan extractability and lowered the MW of β-glucan compared to Intact. In conclusion, low-dose oat β-glucan in a beverage significantly reduced PPGR, with effects maintained across different oat processing methods.
Factors Influencing Self-Management Behaviors Among Patients with Post-Kidney Transplantation: A Qualitative Study of the Chronic Phase Transition
Authors: Matsumura Naoko , Mizukawa Mariko , Sato Kanae , Hashino Asuka , Kazawa Kana , Naka Makiko , Huq K. A. T. M. Ehsanul , Moriyama Michiko
Published: November 2024

Background: Kidney transplantation is an effective treatment for patients with kidney failure. Despite the advances in technology, a certain number of patients still deteriorate due to improper management. The purpose of this study was to identify the promoting and inhibitory factors that influence recipients’ self-management behaviors after a kidney transplant. Methods: We enrolled participants who had kidney transplants for more than one year, aged ≥20 years from outpatient clinics in Japan. Face-to-face interviews were conducted between April and December 2016. Results: Nine participants were included in this study. By qualitative content analysis, 115 codes and 8 categories were extracted for the factors resulting in maintenance and the promotion of self-management behaviors; those were [attentiveness to changes in one’s own body], [good partnership with medical care providers], [past painful experiences], [establishment of lifestyle habits], [autonomy to protect one’s own body], [support from family and others], [gratitude for kidney donation], and [increased self-efficacy]. We also extracted three categories that inhibited self-management behavior: [fading threat of worsening disease], [shifting priorities], and [decreased motivation to control the disease]. Conclusions: The passage of time after transplant became a barrier to continue self-management. Providing knowledge about the importance of self-management can prevent the deterioration of kidney function over time after a transplant.
The Impact of the COVID-19 Pandemic: A Longitudinal Analysis of Body Weight Variations and Their Implications for Daily Habits
Authors: Daniel Marina Martins , Liboredo Juliana Costa , Souza Tamires Cássia de Melo , Anastácio Lucilene Rezende , Ferreira Alida Rosária Silva , Ferreira Lívia Garcia
Published: November 2024

Assessing changes in lifestyle, dietary habits, eating behaviors, and stress during the pandemic and their impact on weight is crucial for developing effective interventions. This study investigated weight variations among Brazilians and associated habit changes over nine months during the COVID-19 pandemic. An online questionnaire was applied (T0/T1, T2). Weight variation classifications were determined from T0 to T1 and evaluated longitudinally for changes in lifestyle, dietary habits, food consumption, eating behavior, and perceived stress using generalized estimating equations (p < 0.05). Out of 453 participants, 23.6% lost weight, 18.1% maintained their weight, 26.0% gained up to 2.4 kg, and 32.2% gained ≥ 2.5 kg. Weight loss was associated with decreased food consumption and increased stress at T2. The group that gained up to 2.4 kg reported reduced food intake, snacking, meal preparation, and candy consumption but increased stress at T2. Those gaining ≥ 2.5 kg initially increased food consumption, snacking, meal preparation, hamburgers/canned products, sugary drinks, instant meals/snacks, candies, and fast food consumption at T1, all of which were reduced at T2, along with a decrease in uncontrolled and emotional eating. Although the pandemic initially affected daily habits differently based on weight changes, participants—especially those who gained more weight—tended to revert to pre-pandemic habits.
Factors Influencing Hotel Revenue Management in Times of Crisis: Towards Financial Sustainability
Authors: Lima Santos Luís , Gomes Conceição , Malheiros Cátia , Crespo Catarina , Bento Carla
Published: November 2024

(1) Background: Facing the challenges of a post-pandemic period and the Ukraine War and recognising the gap in scientific research on the application of revenue management (RM) in the Portuguese hotel industry, the main objective of this study is to identify the most effective and least appropriate RM practices for use in periods of low demand and crises, reflecting the financial sustainability perspective. The theoretical framework of this study focuses on the main RM practices, grouping them into price and non-price strategies. (2) Methods: A quantitative methodology was employed, collecting information from Portuguese hotels through an online questionnaire, and statistical analysis using Mann–Whitney and Chi-square tests was conducted. (3) Results: Hotels offered discounts during the pandemic, but room rates were reduced during the recovery period. These findings also revealed that commonly used techniques were the best available rate (BAR) and rate fences, particularly during the pandemic. Quality, brand image, strategic partnerships, and marketing actions are recognised as essential. However, loyalty programs, length of stay (LOS) control, rate parity, and bundled services are not commonly implemented despite their importance during periods of low demand. Larger hotels, five-star hotels, and members of international chains applied more RM practices than smaller four-star independent hotels. (4) Originality: This study provides original and valuable insights into increasing hotel revenues and occupancy rates during future periods of low demand, which benefit financial sustainability.
A Raster-Based Multi-Objective Spatial Optimization Framework for Offshore Wind Farm Site-Prospecting
Authors: Katikas Loukas , Kontos Themistoklis , Dimitriadis Panayiotis , Kavouras Marinos
Published: November 2024

Siting an offshore wind project is considered a complex planning problem with multiple interrelated objectives and constraints. Hence, compactness and contiguity are indispensable properties in spatial modeling for Renewable Energy Sources (RES) planning processes. The proposed methodology demonstrates the development of a raster-based spatial optimization model for future Offshore Wind Farm (OWF) multi-objective site-prospecting in terms of the simulated Annual Energy Production (AEP), Wind Power Variability (WPV) and the Depth Profile (DP) towards an integer mathematical programming approach. Geographic Information Systems (GIS), statistical modeling, and spatial optimization techniques are fused as a unified framework that allows exploring rigorously and systematically multiple alternatives for OWF planning. The stochastic generation scheme uses a Generalized Hurst-Kolmogorov (GHK) process embedded in a Symmetric-Moving-Average (SMA) model, which is used for the simulation of a wind process, as extracted from the UERRA (MESCAN-SURFEX) reanalysis data. The generated AEP and WPV, along with the bathymetry raster surfaces, are then transferred into the multi-objective spatial optimization algorithm via the Gurobi optimizer. Using a weighted spatial optimization approach, considering and guaranteeing compactness and continuity of the optimal solutions, the final optimal areas (clusters) are extracted for the North and Central Aegean Sea. The optimal OWF clusters, show increased AEP and minimum WPV, particularly across offshore areas from the North-East Aegean (around Lemnos Island) to the Central Aegean Sea (Cyclades Islands). All areas have a Hurst parameter in the range of 0.55–0.63, indicating greater long-term positive autocorrelation in specific areas of the North Aegean Sea.
PKCα Activation via the Thyroid Hormone Membrane Receptor Is Key to Thyroid Cancer Growth
Authors: Campos Haedo Mateo N. , Díaz Albuja Johanna A. , Camarero Sandra , Cayrol Florencia , Sterle Helena A. , Debernardi María M. , Perona Marina , Saban Melina , Ernst Glenda , Mendez Julián , Paulazo María A. , Juvenal Guillermo J. , Díaz Flaqué María C. , Cremaschi Graciela A. , Rosemblit Cinthia
Published: November 2024

Thyroid carcinoma (TC) is the most common endocrine neoplasia, with its incidence increasing in the last 40 years worldwide. The determination of genetic and/or protein markers for thyroid carcinoma could increase diagnostic precision. Accumulated evidence shows that Protein kinase C alpha (PKCα) contributes to tumorigenesis and therapy resistance in cancer. However, the role of PKCα in TC remains poorly studied. Our group and others have demonstrated that PKCs can mediate the proliferative effects of thyroid hormones (THs) through their membrane receptor, the integrin αvβ3, in several cancer types. We found that PKCα is overexpressed in TC cell lines, and it also appeared as the predominant expressed isoform in public databases of TC patients. PKCα-depleted cells significantly reduced THs-induced proliferation, mediated by the integrin αvβ3 receptor, through AKT and Erk activation. In databases of TC patients, higher PKCα expression was associated with lower overall survival. Further analyses showed a positive correlation between PKCα and genes from the MAPK and PI3K-Akt pathways. Finally, immunohistochemical analysis showed abnormal upregulation of PKCα in human thyroid tumors. Our findings establish a potential role for PKCα in the control of hormone-induced proliferation that can be explored as a therapeutic and/or diagnostic target for TC.
The Protective Role of miR-130b-3p Against Palmitate-Induced Lipotoxicity in Cardiomyocytes Through PPARγ Pathway
Authors: Alonso-Villa Elena , Mangas Alipio , Bonet Fernando , Campuzano Óscar , Quezada-Feijoo Maribel , Ramos Mónica , García-Padilla Carlos , Franco Diego , Toro Rocio
Published: November 2024

Excess lipid accumulation in the heart is associated with lipotoxicity and cardiac dysfunction due to excessive fatty acid oxidation. Peroxisome proliferator-activated receptor gamma (PPARγ) modulates the expression of key molecules involved in the FA metabolic pathway. Cardiomyocyte-specific overexpression of PPARγ causes dilated cardiomyopathy associated with lipotoxicity in mice. miR-130b-3p has been shown to be downregulated in the plasma of idiopathic dilated cardiomyopathy patients, but its role in modulating cardiomyocyte lipotoxicity via PPARγ remains unclear. Our objective was to investigate the protective role of miR-130b-3p against palmitate-induced lipotoxicity in cardiomyocytes through the modulation of the PPARγ signaling pathway. Human cardiomyoblasts were treated with palmitate. Intracellular lipid accumulation and expression of PPARγ and its downstream targets (CD36, FABP3, CAV1, VLDLR) were analyzed. Mitochondrial oxidative stress was assessed via MitoTracker Green and Redox Sensor Red staining and expression of CPT1B and SOD2. Endoplasmic reticulum stress and apoptosis were determined by examining GRP78, ATF6, XBP1s, CHOP, and caspase-3 expression. miR-130b-3p overexpression was achieved using transfection methods, and its effect on these parameters was evaluated. Luciferase assays were used to confirm PPARγ as a direct target of miR-130b-3p. Palmitate treatment led to increased lipid accumulation and upregulation of PPARγ and its downstream targets in human cardiomyoblasts. Palmitate also increased mitochondrial oxidative stress, endoplasmic reticulum stress and apoptosis. miR-130b-3p overexpression reduced PPARγ expression and its downstream signaling, alleviated mitochondrial oxidative stress and decreased endoplasmic reticulum stress and apoptosis in palmitate-stimulated cardiomyoblasts. Luciferase assays confirmed PPARγ as a direct target of miR-130b-3p. Our findings suggest that miR-130b-3p plays a protective role against palmitate-induced lipotoxicity in cardiomyocytes by modulating the PPARγ signaling pathway.
Gut Microbiota and Immune System Dynamics in Parkinson’s and Alzheimer’s Diseases
Authors: Kustrimovic Natasa , Balkhi Sahar , Bilato Giorgia , Mortara Lorenzo
Published: November 2024

The gut microbiota, a diverse collection of microorganisms in the gastrointestinal tract, plays a critical role in regulating metabolic, immune, and cognitive functions. Disruptions in the composition of these microbial communities, termed dysbiosis, have been linked to various neurodegenerative diseases (NDs), such as Parkinson’s disease (PD) and Alzheimer’s disease (AD). One of the key pathological features of NDs is neuroinflammation, which involves the activation of microglia and peripheral immune cells. The gut microbiota modulates immune responses through the production of metabolites and interactions with immune cells, influencing the inflammatory processes within the central nervous system. This review explores the impact of gut dysbiosis on neuroinflammation, focusing on the roles of microglia, immune cells, and potential therapeutic strategies targeting the gut microbiota to alleviate neuroinflammatory processes in NDs.
Nanotechnology-Driven Delivery of Caffeine Using Ultradeformable Liposomes-Coated Hollow Mesoporous Silica Nanoparticles for Enhanced Follicular Delivery and Treatment of Androgenetic Alopecia
Authors: Thepphankulngarm Nattanida , Manmuan Suwisit , Hirun Namon , Kraisit Pakorn
Published: November 2024

Androgenetic alopecia (AGA) is caused by the impact of dihydrotestosterone (DHT) on hair follicles, leading to progressive hair loss in men and women. In this study, we developed caffeine-loaded hollow mesoporous silica nanoparticles coated with ultradeformable liposomes (ULp-Caf@HMSNs) to enhance caffeine delivery to hair follicles. Caffeine, known to inhibit DHT formation, faces challenges in skin penetration due to its hydrophilic nature. We investigated caffeine encapsulated in liposomes, hollow mesoporous silica nanoparticles (HMSNs), and ultradeformable liposome-coated HMSNs to optimize drug delivery and release. For ultradeformable liposomes (ULs), the amount of polysorbate 20 and polysorbate 80 was varied. TEM images confirmed the mesoporous shell and hollow core structure of HMSNs, with a shell thickness of 25–35 nm and a hollow space of 80–100 nm. SEM and TEM analysis showed particle sizes ranging from 140–160 nm. Thermal stability tests showed that HMSNs coated with ULs exhibited a Td10 value of 325 °C and 70% residue ash, indicating good thermal stability. Caffeine release experiments indicated that the highest release occurred in caffeine-loaded HMSNs without a liposome coating. In contrast, systems incorporating ULp-Caf@HMSNs exhibited slower release rates, attributable to the dual encapsulation mechanism. Confocal laser scanning microscopy revealed that ULs-coated particles penetrated deeper into the skin than non-liposome particles. MTT assays confirmed the non-cytotoxicity of all HMSN concentrations to human follicle dermal papilla cells (HFDPCs). ULp-Caf@HMSNs promoted better cell viability than pure caffeine or caffeine-loaded HMSNs, highlighting enhanced biocompatibility without increased toxicity. Additionally, ULp-Caf@HMSNs effectively reduced ROS levels in DHT-damaged HFDPCs, suggesting they are promising alternatives to minoxidil for promoting hair follicle growth and reducing hair loss without increasing oxidative stress. This system shows promise for treating AGA.